WorldWideScience

Sample records for fault diagnostics development

  1. Development of Fault Models for Hybrid Fault Detection and Diagnostics Algorithm: October 1, 2014 -- May 5, 2015

    Energy Technology Data Exchange (ETDEWEB)

    Cheung, Howard [Purdue Univ., West Lafayette, IN (United States); Braun, James E. [Purdue Univ., West Lafayette, IN (United States)

    2015-12-31

    This report describes models of building faults created for OpenStudio to support the ongoing development of fault detection and diagnostic (FDD) algorithms at the National Renewable Energy Laboratory. Building faults are operating abnormalities that degrade building performance, such as using more energy than normal operation, failing to maintain building temperatures according to the thermostat set points, etc. Models of building faults in OpenStudio can be used to estimate fault impacts on building performance and to develop and evaluate FDD algorithms. The aim of the project is to develop fault models of typical heating, ventilating and air conditioning (HVAC) equipment in the United States, and the fault models in this report are grouped as control faults, sensor faults, packaged and split air conditioner faults, water-cooled chiller faults, and other uncategorized faults. The control fault models simulate impacts of inappropriate thermostat control schemes such as an incorrect thermostat set point in unoccupied hours and manual changes of thermostat set point due to extreme outside temperature. Sensor fault models focus on the modeling of sensor biases including economizer relative humidity sensor bias, supply air temperature sensor bias, and water circuit temperature sensor bias. Packaged and split air conditioner fault models simulate refrigerant undercharging, condenser fouling, condenser fan motor efficiency degradation, non-condensable entrainment in refrigerant, and liquid line restriction. Other fault models that are uncategorized include duct fouling, excessive infiltration into the building, and blower and pump motor degradation.

  2. Relating faults in diagnostic reasoning with diagnostic errors and patient harm.

    NARCIS (Netherlands)

    Zwaan, L.; Thijs, A.; Wagner, C.; Wal, G. van der; Timmermans, D.R.M.

    2012-01-01

    Purpose: The relationship between faults in diagnostic reasoning, diagnostic errors, and patient harm has hardly been studied. This study examined suboptimal cognitive acts (SCAs; i.e., faults in diagnostic reasoning), related them to the occurrence of diagnostic errors and patient harm, and studied

  3. Case-Based Fault Diagnostic System

    International Nuclear Information System (INIS)

    Mohamed, A.H.

    2014-01-01

    Nowadays, case-based fault diagnostic (CBFD) systems have become important and widely applied problem solving technologies. They are based on the assumption that “similar faults have similar diagnosis”. On the other hand, CBFD systems still suffer from some limitations. Common ones of them are: (1) failure of CBFD to have the needed diagnosis for the new faults that have no similar cases in the case library. (2) Limited memorization when increasing the number of stored cases in the library. The proposed research introduces incorporating the neural network into the case based system to enable the system to diagnose all the faults. Neural networks have proved their success in the classification and diagnosis problems. The suggested system uses the neural network to diagnose the new faults (cases) that cannot be diagnosed by the traditional CBR diagnostic system. Besides, the proposed system can use the another neural network to control adding and deleting the cases in the library to manage the size of the cases in the case library. However, the suggested system has improved the performance of the case based fault diagnostic system when applied for the motor rolling bearing as a case of study

  4. Fault-tolerant and Diagnostic Methods for Navigation

    DEFF Research Database (Denmark)

    Blanke, Mogens

    2003-01-01

    to diagnose faults and autonomously provide valid navigation data, disregarding any faulty sensor data and use sensor fusion to obtain a best estimate for users. This paper discusses how diagnostic and fault-tolerant methods are applicable in marine systems. An example chosen is sensor fusion for navigation......Precise and reliable navigation is crucial, and for reasons of safety, essential navigation instruments are often duplicated. Hardware redundancy is mostly used to manually switch between instruments should faults occur. In contrast, diagnostic methods are available that can use analytic redundancy...

  5. Integrated system fault diagnostics utilising digraph and fault tree-based approaches

    International Nuclear Information System (INIS)

    Bartlett, L.M.; Hurdle, E.E.; Kelly, E.M.

    2009-01-01

    With the growing intolerance to failures within systems, the issue of fault diagnosis has become ever prevalent. Information concerning these possible failures can help to minimise the disruption to the functionality of the system by allowing quick rectification. Traditional approaches to fault diagnosis within engineering systems have focused on sequential testing procedures and real-time mechanisms. Both methods have been predominantly limited to single fault causes. Latest approaches also consider the issue of multiple faults in reflection to the characteristics of modern day systems designed for high reliability. In addition, a diagnostic capability is required in real time and for changeable system functionality. This paper focuses on two approaches which have been developed to cater for the demands of diagnosis within current engineering systems, namely application of the fault tree analysis technique and the method of digraphs. Both use a comparative approach to consider differences between actual system behaviour and that expected. The procedural guidelines are discussed for each method, with an experimental aircraft fuel system used to test and demonstrate the features of the techniques. The effectiveness of the approaches is compared and their future potential highlighted

  6. Common faults in turbines and applying neural networks in order to fault diagnostic by vibration analysis

    International Nuclear Information System (INIS)

    Masoudifar, M.; AghaAmini, M.

    2001-01-01

    Today the fault diagnostic of the rotating machinery based on the vibration analysis is an effective method in designing predictive maintenance programs. In this method, vibration level of the turbines is monitored and if it is higher than the allowable limit, vibrational data will be analyzed and the growing faults will be detected. But because of the high complexity of the system monitoring, the interpretation of the measured data is more difficult. Therefore, design of the fault diagnostic expert systems by using the expert's technical experiences and knowledge; seem to be the best solution. In this paper,at first several common faults in turbines are studied and the how applying the neural networks to interpret the vibrational data for fault diagnostic is explained

  7. Using Fault Trees to Advance Understanding of Diagnostic Errors.

    Science.gov (United States)

    Rogith, Deevakar; Iyengar, M Sriram; Singh, Hardeep

    2017-11-01

    Diagnostic errors annually affect at least 5% of adults in the outpatient setting in the United States. Formal analytic techniques are only infrequently used to understand them, in part because of the complexity of diagnostic processes and clinical work flows involved. In this article, diagnostic errors were modeled using fault tree analysis (FTA), a form of root cause analysis that has been successfully used in other high-complexity, high-risk contexts. How factors contributing to diagnostic errors can be systematically modeled by FTA to inform error understanding and error prevention is demonstrated. A team of three experts reviewed 10 published cases of diagnostic error and constructed fault trees. The fault trees were modeled according to currently available conceptual frameworks characterizing diagnostic error. The 10 trees were then synthesized into a single fault tree to identify common contributing factors and pathways leading to diagnostic error. FTA is a visual, structured, deductive approach that depicts the temporal sequence of events and their interactions in a formal logical hierarchy. The visual FTA enables easier understanding of causative processes and cognitive and system factors, as well as rapid identification of common pathways and interactions in a unified fashion. In addition, it enables calculation of empirical estimates for causative pathways. Thus, fault trees might provide a useful framework for both quantitative and qualitative analysis of diagnostic errors. Future directions include establishing validity and reliability by modeling a wider range of error cases, conducting quantitative evaluations, and undertaking deeper exploration of other FTA capabilities. Copyright © 2017 The Joint Commission. Published by Elsevier Inc. All rights reserved.

  8. The Impact of Gas Turbine Component Leakage Fault on GPA Performance Diagnostics

    Directory of Open Access Journals (Sweden)

    E. L. Ntantis

    2016-01-01

    Full Text Available The leakage analysis is a key factor in determining energy loss from a gas turbine. Once the components assembly fails, air leakage through the opening increases resulting in a performance loss. Therefore, the performance efficiency of the engine cannot be reliably determined, without good estimates and analysis of leakage faults. Consequently, the implementation of a leakage fault within a gas turbine engine model is necessary for any performance diagnostic technique that can expand its diagnostics capabilities for more accurate predictions. This paper explores the impact of gas turbine component leakage fault on GPA (Gas Path Analysis Performance Diagnostics. The analysis is demonstrated with a test case where gas turbine performance simulation and diagnostics code TURBOMATCH is used to build a performance model of a model engine similar to Rolls-Royce Trent 500 turbofan engine, and carry out the diagnostic analysis with the presence of different component fault cases. Conclusively, to improve the reliability of the diagnostic results, a leakage fault analysis of the implemented faults is made. The diagnostic tool used to deal with the analysis of the gas turbine component implemented faults is a model-based method utilizing a non-linear GPA.

  9. ISHM-oriented adaptive fault diagnostics for avionics based on a distributed intelligent agent system

    Science.gov (United States)

    Xu, Jiuping; Zhong, Zhengqiang; Xu, Lei

    2015-10-01

    In this paper, an integrated system health management-oriented adaptive fault diagnostics and model for avionics is proposed. With avionics becoming increasingly complicated, precise and comprehensive avionics fault diagnostics has become an extremely complicated task. For the proposed fault diagnostic system, specific approaches, such as the artificial immune system, the intelligent agents system and the Dempster-Shafer evidence theory, are used to conduct deep fault avionics diagnostics. Through this proposed fault diagnostic system, efficient and accurate diagnostics can be achieved. A numerical example is conducted to apply the proposed hybrid diagnostics to a set of radar transmitters on an avionics system and to illustrate that the proposed system and model have the ability to achieve efficient and accurate fault diagnostics. By analyzing the diagnostic system's feasibility and pragmatics, the advantages of this system are demonstrated.

  10. Study on fault diagnostic system using modularized knowledge; Mojuru gata chishiki wo mochiita ijo shindan system ni kansuru kenkyu

    Energy Technology Data Exchange (ETDEWEB)

    Shimada, Y.; Sayama, H.; Suzuki, K. [Okayama Univ. (Japan). Dept. of Industrial and Mechanical Engineering

    1997-08-15

    Recently, a fault diagnostic expert system was prosperously developed as an objective of chemical plants and nuclear power plants. In this paper, a fault diagnostic method using modularized knowledge was proposed, a fault diagnostic system was constructed for an experimental plant, and the effectiveness of this method was clarified by carrying out a fault diagnostic experiment. The characteristics of the proposed fault diagnostic system were as follows: The necessary knowledge for diagnosing faults was made into each process element. Based on this method, the revision and addition of a knowledge base could be carried out in each element, and the design change of a plant could be flexibly corresponded by only changing the related part of the process flow graph. The estimated results were stored into the working memory, not only faults of an element in which faults resulted could be estimated, but also the fault propagating path could be clarified. 8 refs., 6 figs., 3 tabs.

  11. Torsional vibration signal analysis as a diagnostic tool for planetary gear fault detection

    Science.gov (United States)

    Xue, Song; Howard, Ian

    2018-02-01

    This paper aims to investigate the effectiveness of using the torsional vibration signal as a diagnostic tool for planetary gearbox faults detection. The traditional approach for condition monitoring of the planetary gear uses a stationary transducer mounted on the ring gear casing to measure all the vibration data when the planet gears pass by with the rotation of the carrier arm. However, the time variant vibration transfer paths between the stationary transducer and the rotating planet gear modulate the resultant vibration spectra and make it complex. Torsional vibration signals are theoretically free from this modulation effect and therefore, it is expected to be much easier and more effective to diagnose planetary gear faults using the fault diagnostic information extracted from the torsional vibration. In this paper, a 20 degree of freedom planetary gear lumped-parameter model was developed to obtain the gear dynamic response. In the model, the gear mesh stiffness variations are the main internal vibration generation mechanism and the finite element models were developed for calculation of the sun-planet and ring-planet gear mesh stiffnesses. Gear faults on different components were created in the finite element models to calculate the resultant gear mesh stiffnesses, which were incorporated into the planetary gear model later on to obtain the faulted vibration signal. Some advanced signal processing techniques were utilized to analyses the fault diagnostic results from the torsional vibration. It was found that the planetary gear torsional vibration not only successfully detected the gear fault, but also had the potential to indicate the location of the gear fault. As a result, the planetary gear torsional vibration can be considered an effective alternative approach for planetary gear condition monitoring.

  12. The Absolute Deviation Rank Diagnostic Approach to Gear Tooth Composite Fault

    Directory of Open Access Journals (Sweden)

    Guangbin Wang

    2017-01-01

    Full Text Available Aiming at nonlinear and nonstationary characteristics of the different degree with single fault gear tooth broken, pitting, and composite fault gear tooth broken-pitting, a method for the diagnosis of absolute deviation of gear faults is presented. The method uses ADAMS, respectively, set-up dynamics model of single fault gear tooth broken, pitting, and composite fault gear tooth broken-pitting, to obtain the result of different degree of broken teeth, pitting the single fault and compound faults in the meshing frequency, and the amplitude frequency doubling through simulating analysis. Through the comparison with the normal state to obtain the sensitive characteristic of the fault, the absolute value deviation diagnostic approach is used to identify the fault and validate it through experiments. The results show that absolute deviation rank diagnostic approach can realize the recognition of gear single faults and compound faults with different degrees and provide quick reference to determine the degree of gear fault.

  13. Study on a self diagnostic monitoring system for an air-operated valve: development of a fault library

    International Nuclear Information System (INIS)

    Chai, Jang Bom; Kim, Yun Chul; Kim, Woo Shik; Cho, Hang Duke

    2004-01-01

    In the interest of nuclear power plant safety, a Self-Diagnostic Monitoring System (SDMS) is needed to monitor defects in safety-related components. An Air-Operated Valve (AOV) is one of the components to be monitored since the failure of its operation could potentially have catastrophic consequences. In this paper, a model of the AOV is developed with the parameters that affect the operational characteristics. The model is useful for both understanding the operation and correlating parameters and defects. Various defects are introduced in the experiments to construct a fault library, which will be used in a pattern recognition approach. Finally, the validity of the fault library is examined

  14. Autonomous power expert fault diagnostic system for Space Station Freedom electrical power system testbed

    Science.gov (United States)

    Truong, Long V.; Walters, Jerry L.; Roth, Mary Ellen; Quinn, Todd M.; Krawczonek, Walter M.

    1990-01-01

    The goal of the Autonomous Power System (APS) program is to develop and apply intelligent problem solving and control to the Space Station Freedom Electrical Power System (SSF/EPS) testbed being developed and demonstrated at NASA Lewis Research Center. The objectives of the program are to establish artificial intelligence technology paths, to craft knowledge-based tools with advanced human-operator interfaces for power systems, and to interface and integrate knowledge-based systems with conventional controllers. The Autonomous Power EXpert (APEX) portion of the APS program will integrate a knowledge-based fault diagnostic system and a power resource planner-scheduler. Then APEX will interface on-line with the SSF/EPS testbed and its Power Management Controller (PMC). The key tasks include establishing knowledge bases for system diagnostics, fault detection and isolation analysis, on-line information accessing through PMC, enhanced data management, and multiple-level, object-oriented operator displays. The first prototype of the diagnostic expert system for fault detection and isolation has been developed. The knowledge bases and the rule-based model that were developed for the Power Distribution Control Unit subsystem of the SSF/EPS testbed are described. A corresponding troubleshooting technique is also described.

  15. Confirmation of Thermal Images and Vibration Signals for Intelligent Machine Fault Diagnostics

    Directory of Open Access Journals (Sweden)

    Achmad Widodo

    2012-01-01

    Full Text Available This paper deals with the maintenance technique for industrial machinery using the artificial neural network so-called self-organizing map (SOM. The aim of this work is to develop intelligent maintenance system for machinery based on an alternative way, namely, thermal images instead of vibration signals. SOM is selected due to its simplicity and is categorized as an unsupervised algorithm. Following the SOM training, machine fault diagnostics is performed by using the pattern recognition technique of machine conditions. The data used in this work are thermal images and vibration signals, which were acquired from machine fault simulator (MFS. It is a reliable tool and is able to simulate several conditions of faulty machine such as unbalance, misalignment, looseness, and rolling element bearing faults (outer race, inner race, ball, and cage defects. Data acquisition were conducted simultaneously by infrared thermography camera and vibration sensors installed in the MFS. The experimental data are presented as thermal image and vibration signal in the time domain. Feature extraction was carried out to obtain salient features sensitive to machine conditions from thermal images and vibration signals. These features are then used to train the SOM for intelligent machine diagnostics process. The results show that SOM can perform intelligent fault diagnostics with plausible accuracies.

  16. A Diagnostic System for Speed-Varying Motor Rotary Faults

    Directory of Open Access Journals (Sweden)

    Chwan-Lu Tseng

    2014-01-01

    Full Text Available This study proposed an intelligent rotary fault diagnostic system for motors. A sensorless rotational speed detection method and an improved dynamic structural neural network are used. Moreover, to increase the convergence speed of training, a terminal attractor method and a hybrid discriminant analysis are also adopted. The proposed method can be employed to detect the rotary frequencies of motors with varying speeds and can enhance the discrimination of motor faults. To conduct the experiments, this study used wireless sensor nodes to transmit vibration data and employed MATLAB to write codes for functional modules, including the signal processing, sensorless rotational speed estimation, neural network, and stochastic process control chart. Additionally, Visual Basic software was used to create an integrated human-machine interface. The experimental results regarding the test of equipment faults indicated that the proposed novel diagnostic system can effectively estimate rotational speeds and provide superior ability of motor fault discrimination with fast training convergence.

  17. Sensor Selection for Aircraft Engine Performance Estimation and Gas Path Fault Diagnostics

    Science.gov (United States)

    Simon, Donald L.; Rinehart, Aidan W.

    2016-01-01

    This paper presents analytical techniques for aiding system designers in making aircraft engine health management sensor selection decisions. The presented techniques, which are based on linear estimation and probability theory, are tailored for gas turbine engine performance estimation and gas path fault diagnostics applications. They enable quantification of the performance estimation and diagnostic accuracy offered by different candidate sensor suites. For performance estimation, sensor selection metrics are presented for two types of estimators including a Kalman filter and a maximum a posteriori estimator. For each type of performance estimator, sensor selection is based on minimizing the theoretical sum of squared estimation errors in health parameters representing performance deterioration in the major rotating modules of the engine. For gas path fault diagnostics, the sensor selection metric is set up to maximize correct classification rate for a diagnostic strategy that performs fault classification by identifying the fault type that most closely matches the observed measurement signature in a weighted least squares sense. Results from the application of the sensor selection metrics to a linear engine model are presented and discussed. Given a baseline sensor suite and a candidate list of optional sensors, an exhaustive search is performed to determine the optimal sensor suites for performance estimation and fault diagnostics. For any given sensor suite, Monte Carlo simulation results are found to exhibit good agreement with theoretical predictions of estimation and diagnostic accuracies.

  18. Study on Fault Diagnostics of a Turboprop Engine Using Inverse Performance Model and Artificial Intelligent Methods

    Science.gov (United States)

    Kong, Changduk; Lim, Semyeong

    2011-12-01

    Recently, the health monitoring system of major gas path components of gas turbine uses mostly the model based method like the Gas Path Analysis (GPA). This method is to find quantity changes of component performance characteristic parameters such as isentropic efficiency and mass flow parameter by comparing between measured engine performance parameters such as temperatures, pressures, rotational speeds, fuel consumption, etc. and clean engine performance parameters without any engine faults which are calculated by the base engine performance model. Currently, the expert engine diagnostic systems using the artificial intelligent methods such as Neural Networks (NNs), Fuzzy Logic and Genetic Algorithms (GAs) have been studied to improve the model based method. Among them the NNs are mostly used to the engine fault diagnostic system due to its good learning performance, but it has a drawback due to low accuracy and long learning time to build learning data base if there are large amount of learning data. In addition, it has a very complex structure for finding effectively single type faults or multiple type faults of gas path components. This work builds inversely a base performance model of a turboprop engine to be used for a high altitude operation UAV using measured performance data, and proposes a fault diagnostic system using the base engine performance model and the artificial intelligent methods such as Fuzzy logic and Neural Network. The proposed diagnostic system isolates firstly the faulted components using Fuzzy Logic, then quantifies faults of the identified components using the NN leaned by fault learning data base, which are obtained from the developed base performance model. In leaning the NN, the Feed Forward Back Propagation (FFBP) method is used. Finally, it is verified through several test examples that the component faults implanted arbitrarily in the engine are well isolated and quantified by the proposed diagnostic system.

  19. Modeling and Measurement Constraints in Fault Diagnostics for HVAC Systems

    Energy Technology Data Exchange (ETDEWEB)

    Najafi, Massieh; Auslander, David M.; Bartlett, Peter L.; Haves, Philip; Sohn, Michael D.

    2010-05-30

    Many studies have shown that energy savings of five to fifteen percent are achievable in commercial buildings by detecting and correcting building faults, and optimizing building control systems. However, in spite of good progress in developing tools for determining HVAC diagnostics, methods to detect faults in HVAC systems are still generally undeveloped. Most approaches use numerical filtering or parameter estimation methods to compare data from energy meters and building sensors to predictions from mathematical or statistical models. They are effective when models are relatively accurate and data contain few errors. In this paper, we address the case where models are imperfect and data are variable, uncertain, and can contain error. We apply a Bayesian updating approach that is systematic in managing and accounting for most forms of model and data errors. The proposed method uses both knowledge of first principle modeling and empirical results to analyze the system performance within the boundaries defined by practical constraints. We demonstrate the approach by detecting faults in commercial building air handling units. We find that the limitations that exist in air handling unit diagnostics due to practical constraints can generally be effectively addressed through the proposed approach.

  20. Study on Practical Application of Turboprop Engine Condition Monitoring and Fault Diagnostic System Using Fuzzy-Neuro Algorithms

    Science.gov (United States)

    Kong, Changduk; Lim, Semyeong; Kim, Keunwoo

    2013-03-01

    The Neural Networks is mostly used to engine fault diagnostic system due to its good learning performance, but it has a drawback due to low accuracy and long learning time to build learning data base. This work builds inversely a base performance model of a turboprop engine to be used for a high altitude operation UAV using measuring performance data, and proposes a fault diagnostic system using the base performance model and artificial intelligent methods such as Fuzzy and Neural Networks. Each real engine performance model, which is named as the base performance model that can simulate a new engine performance, is inversely made using its performance test data. Therefore the condition monitoring of each engine can be more precisely carried out through comparison with measuring performance data. The proposed diagnostic system identifies firstly the faulted components using Fuzzy Logic, and then quantifies faults of the identified components using Neural Networks leaned by fault learning data base obtained from the developed base performance model. In leaning the measuring performance data of the faulted components, the FFBP (Feed Forward Back Propagation) is used. In order to user's friendly purpose, the proposed diagnostic program is coded by the GUI type using MATLAB.

  1. evelopment of a boiling water reactor fault diagnostic system with a signed directed graph method

    International Nuclear Information System (INIS)

    Chen, M.; Yu, C.C.; Liou, C.T.; Liao, L.Y.

    1990-01-01

    The fault diagnostic system for a nuclear power reactor is expected to be a useful decision support system for the operators during transients and accident conditions. A considerable research effort has been devoted to the development of automated fault diagnostic systems. One major approach, which has been widely used in chemical engineering, is to identify the possible causes of process disturbance using a logic-oriented method called signed directed graph (SDG). A knowledge based system was developed with the rules derived from the SDG representation. The SDG for the Chinshan nuclear power plant, which is a typical boiling water reactor, is established. The personal consultant system is used as the expert system development tool in this paper

  2. Constitution and application of reactor make-up system's fault diagnostic Bayesian networks

    International Nuclear Information System (INIS)

    Liang Jie; Cai Qi; Chu Zhuli; Wang Haiping

    2013-01-01

    A fault diagnostic Bayesian network of reactor make-up system was constituted. The system's structure characters, operation rules and experts' experience were combined and an initial net was built. As the fault date sets were learned with the particle swarm optimization based Bayesian network structure, the structure of diagnostic net was completed and used to inference case. The built net can analyze diagnostic probability of every node in the net and afford assistant decision to fault diagnosis. (authors)

  3. Prodiag--a hybrid artificial intelligence based reactor diagnostic system for process faults

    International Nuclear Information System (INIS)

    Reifman, J.; Wei, T.Y.C.; Vitela, J.E.; Applequist, C. A.; Chasensky, T.M.

    1996-01-01

    Commonwealth Research Corporation (CRC) and Argonne National Laboratory (ANL) are collaborating on a DOE-sponsored Cooperative Research and Development Agreement (CRADA), project to perform feasibility studies on a novel approach to Artificial Intelligence (Al) based diagnostics for component faults in nuclear power plants. Investigations are being performed in the construction of a first-principles physics-based plant level process diagnostic expert system (ES) and the identification of component-level fault patterns through operating component characteristics using artificial neural networks (ANNs). The purpose of the proof-of-concept project is to develop a computer-based system using this Al approach to assist process plant operators during off-normal plant conditions. The proposed computer-based system will use thermal hydraulic (T-H) signals complemented by other non-T-H signals available in the data stream to provide the process operator with the component which most likely caused the observed process disturbance.To demonstrate the scale-up feasibility of the proposed diagnostic system it is being developed for use with the Chemical Volume Control System (CVCS) of a nuclear power plant. A full-scope operator training simulator representing the Commonwealth Edison Braidwood nuclear power plant is being used both as the source of development data and as the means to evaluate the advantages of the proposed diagnostic system. This is an ongoing multi-year project and this paper presents the results to date of the CRADA phase

  4. A Fault Diagnostic Method for Position Sensor of Switched Reluctance Wind Generator

    DEFF Research Database (Denmark)

    Wang, Chao; Liu, Xiao; Liu, Hui

    2016-01-01

    Fast and accurate fault diagnosis of the position sensor is of great significance to ensure the reliability as well as sensor fault tolerant operation of the Switched Reluctance Wind Generator (SRWG). This paper presents a fault diagnostic scheme for a SRWG based on the residual between the estim...

  5. Gearbox tooth cut fault diagnostics using acoustic emission and vibration sensors--a comparative study.

    Science.gov (United States)

    Qu, Yongzhi; He, David; Yoon, Jae; Van Hecke, Brandon; Bechhoefer, Eric; Zhu, Junda

    2014-01-14

    In recent years, acoustic emission (AE) sensors and AE-based techniques have been developed and tested for gearbox fault diagnosis. In general, AE-based techniques require much higher sampling rates than vibration analysis-based techniques for gearbox fault diagnosis. Therefore, it is questionable whether an AE-based technique would give a better or at least the same performance as the vibration analysis-based techniques using the same sampling rate. To answer the question, this paper presents a comparative study for gearbox tooth damage level diagnostics using AE and vibration measurements, the first known attempt to compare the gearbox fault diagnostic performance of AE- and vibration analysis-based approaches using the same sampling rate. Partial tooth cut faults are seeded in a gearbox test rig and experimentally tested in a laboratory. Results have shown that the AE-based approach has the potential to differentiate gear tooth damage levels in comparison with the vibration-based approach. While vibration signals are easily affected by mechanical resonance, the AE signals show more stable performance.

  6. Faults Diagnostics of Railway Axle Bearings Based on IMF’s Confidence Index Algorithm for Ensemble EMD

    Science.gov (United States)

    Yi, Cai; Lin, Jianhui; Zhang, Weihua; Ding, Jianming

    2015-01-01

    As train loads and travel speeds have increased over time, railway axle bearings have become critical elements which require more efficient non-destructive inspection and fault diagnostics methods. This paper presents a novel and adaptive procedure based on ensemble empirical mode decomposition (EEMD) and Hilbert marginal spectrum for multi-fault diagnostics of axle bearings. EEMD overcomes the limitations that often hypothesize about data and computational efforts that restrict the application of signal processing techniques. The outputs of this adaptive approach are the intrinsic mode functions that are treated with the Hilbert transform in order to obtain the Hilbert instantaneous frequency spectrum and marginal spectrum. Anyhow, not all the IMFs obtained by the decomposition should be considered into Hilbert marginal spectrum. The IMFs’ confidence index arithmetic proposed in this paper is fully autonomous, overcoming the major limit of selection by user with experience, and allows the development of on-line tools. The effectiveness of the improvement is proven by the successful diagnosis of an axle bearing with a single fault or multiple composite faults, e.g., outer ring fault, cage fault and pin roller fault. PMID:25970256

  7. Development of fault diagnostic technique using reactor noise analysis

    International Nuclear Information System (INIS)

    Park, Jin Ho; Kim, J. S.; Oh, I. S.; Ryu, J. S.; Joo, Y. S.; Choi, S.; Yoon, D. B.

    1999-04-01

    The ultimate goal of this project is to establish the analysis technique to diagnose the integrity of reactor internals using reactor noise. The reactor noise analyses techniques for the PWR and CANDU NPP(Nuclear Power Plants) were established by which the dynamic characteristics of reactor internals and SPND instrumentations could be identified, and the noise database corresponding to each plant(both Korean and foreign one) was constructed and compared. Also the change of dynamic characteristics of the Ulchin 1 and 2 reactor internals were simulated under presumed fault conditions. Additionally portable reactor noise analysis system was developed so that real time noise analysis could directly be able to be performed at plant site. The reactor noise analyses techniques developed and the database obtained from the fault simulation, can be used to establish a knowledge based expert system to diagnose the NPP's abnormal conditions. And the portable reactor noise analysis system may be utilized as a substitute for plant IVMS(Internal Vibration Monitoring System). (author)

  8. Development of fault diagnostic technique using reactor noise analysis

    Energy Technology Data Exchange (ETDEWEB)

    Park, Jin Ho; Kim, J. S.; Oh, I. S.; Ryu, J. S.; Joo, Y. S.; Choi, S.; Yoon, D. B

    1999-04-01

    The ultimate goal of this project is to establish the analysis technique to diagnose the integrity of reactor internals using reactor noise. The reactor noise analyses techniques for the PWR and CANDU NPP(Nuclear Power Plants) were established by which the dynamic characteristics of reactor internals and SPND instrumentations could be identified, and the noise database corresponding to each plant(both Korean and foreign one) was constructed and compared. Also the change of dynamic characteristics of the Ulchin 1 and 2 reactor internals were simulated under presumed fault conditions. Additionally portable reactor noise analysis system was developed so that real time noise analysis could directly be able to be performed at plant site. The reactor noise analyses techniques developed and the database obtained from the fault simulation, can be used to establish a knowledge based expert system to diagnose the NPP's abnormal conditions. And the portable reactor noise analysis system may be utilized as a substitute for plant IVMS(Internal Vibration Monitoring System). (author)

  9. CRISP. Simulation tool for fault detection and diagnostics in high-DG power networks

    International Nuclear Information System (INIS)

    Fontela, M.; Andrieu, C.; Raison, B.

    2004-08-01

    This document gives a description of a tool proposed for fault detection and diagnostics. The main principles of the functions of fault localization are described and detailed for a given MV network that will be used for the ICT experiment in Grenoble (experiment 3B). The aim of the tool is to create a technical, simple and realistic context for testing ICT dedicated to an electrical application. The tool gives the expected inputs and outputs contents of the various distributed ICT components when a fault occurs in a given MV network. So the requirements for the ICT components are given in term of expected data collected, analysed and transmitted. Several examples are given in order to illustrate the inputs/outputs in case of different faults. The tool includes a topology description which is a main aspect to develop in the future for managing the distribution network. Updating topology in real time will become necessary for fault diagnostic and protection, but also necessary for the various possible added applications (local market balance and local electrical power quality for instance). The tool gives a context and a simple view for the ICT components behaviours assuming an ideal response and transmission from them. The real characteristics and possible limitations for the ICT (information latency, congestion, security) will be established during the experiments from the same context described in the HTFD tool

  10. Sequential fault diagnosis for mechatronics system using diagnostic hybrid bond graph and composite harmony search

    Directory of Open Access Journals (Sweden)

    Ming Yu

    2015-12-01

    Full Text Available This article proposes a sequential fault diagnosis method to handle asynchronous distinct faults using diagnostic hybrid bond graph and composite harmony search. The faults under consideration include fault mode, abrupt fault, and intermittent fault. The faults can occur in different time instances, which add to the difficulty of decision making for fault diagnosis. This is because the earlier occurred fault can exhibit fault symptom which masks the fault symptom of latter occurred fault. In order to solve this problem, a sequential identification algorithm is developed in which the identification task is reactivated based on two conditions. The first condition is that the latter occurred fault has at least one inconsistent coherence vector element which is consistent in coherence vector of the earlier occurred fault, and the second condition is that the existing fault coherence vector has the ability to hide other faults and the second-level residual exceeds the threshold. A new composite harmony search which is capable of handling continuous variables and binary variables simultaneously is proposed for identification purpose. Experiments on a mobile robot system are conducted to assess the proposed sequential fault diagnosis algorithm.

  11. Gearbox Tooth Cut Fault Diagnostics Using Acoustic Emission and Vibration Sensors — A Comparative Study

    Directory of Open Access Journals (Sweden)

    Yongzhi Qu

    2014-01-01

    Full Text Available In recent years, acoustic emission (AE sensors and AE-based techniques have been developed and tested for gearbox fault diagnosis. In general, AE-based techniques require much higher sampling rates than vibration analysis-based techniques for gearbox fault diagnosis. Therefore, it is questionable whether an AE-based technique would give a better or at least the same performance as the vibration analysis-based techniques using the same sampling rate. To answer the question, this paper presents a comparative study for gearbox tooth damage level diagnostics using AE and vibration measurements, the first known attempt to compare the gearbox fault diagnostic performance of AE- and vibration analysis-based approaches using the same sampling rate. Partial tooth cut faults are seeded in a gearbox test rig and experimentally tested in a laboratory. Results have shown that the AE-based approach has the potential to differentiate gear tooth damage levels in comparison with the vibration-based approach. While vibration signals are easily affected by mechanical resonance, the AE signals show more stable performance.

  12. Gearbox Tooth Cut Fault Diagnostics Using Acoustic Emission and Vibration Sensors — A Comparative Study

    Science.gov (United States)

    Qu, Yongzhi; He, David; Yoon, Jae; Van Hecke, Brandon; Bechhoefer, Eric; Zhu, Junda

    2014-01-01

    In recent years, acoustic emission (AE) sensors and AE-based techniques have been developed and tested for gearbox fault diagnosis. In general, AE-based techniques require much higher sampling rates than vibration analysis-based techniques for gearbox fault diagnosis. Therefore, it is questionable whether an AE-based technique would give a better or at least the same performance as the vibration analysis-based techniques using the same sampling rate. To answer the question, this paper presents a comparative study for gearbox tooth damage level diagnostics using AE and vibration measurements, the first known attempt to compare the gearbox fault diagnostic performance of AE- and vibration analysis-based approaches using the same sampling rate. Partial tooth cut faults are seeded in a gearbox test rig and experimentally tested in a laboratory. Results have shown that the AE-based approach has the potential to differentiate gear tooth damage levels in comparison with the vibration-based approach. While vibration signals are easily affected by mechanical resonance, the AE signals show more stable performance. PMID:24424467

  13. Mechanical fault diagnostics for induction motor with variable speed drives using Adaptive Neuro-fuzzy Inference System

    Energy Technology Data Exchange (ETDEWEB)

    Ye, Z. [Department of Electrical & amp; Computer Engineering, Queen' s University, Kingston, Ont. (Canada K7L 3N6); Sadeghian, A. [Department of Computer Science, Ryerson University, Toronto, Ont. (Canada M5B 2K3); Wu, B. [Department of Electrical & amp; Computer Engineering, Ryerson University, Toronto, Ont. (Canada M5B 2K3)

    2006-06-15

    A novel online diagnostic algorithm for mechanical faults of electrical machines with variable speed drive systems is presented in this paper. Using Wavelet Packet Decomposition (WPD), a set of feature coefficients, represented with different frequency resolutions, related to the mechanical faults is extracted from the stator current of the induction motors operating over a wide range of speeds. A new integrated diagnostic system for electrical machine mechanical faults is then proposed using multiple Adaptive Neuro-fuzzy Inference Systems (ANFIS). This paper shows that using multiple ANFIS units significantly reduces the scale and complexity of the system and speeds up the training of the network. The diagnostic algorithm is validated on a three-phase induction motor drive system, and it is proven to be capable of detecting rotor bar breakage and air gap eccentricity faults with high accuracy. The algorithm is applicable to a variety of industrial applications where either continuous on-line monitoring or off-line fault diagnostics is required. (author)

  14. A phase angle based diagnostic scheme to planetary gear faults diagnostics under non-stationary operational conditions

    Science.gov (United States)

    Feng, Ke; Wang, Kesheng; Ni, Qing; Zuo, Ming J.; Wei, Dongdong

    2017-11-01

    Planetary gearbox is a critical component for rotating machinery. It is widely used in wind turbines, aerospace and transmission systems in heavy industry. Thus, it is important to monitor planetary gearboxes, especially for fault diagnostics, during its operational conditions. However, in practice, operational conditions of planetary gearbox are often characterized by variations of rotational speeds and loads, which may bring difficulties for fault diagnosis through the measured vibrations. In this paper, phase angle data extracted from measured planetary gearbox vibrations is used for fault detection under non-stationary operational conditions. Together with sample entropy, fault diagnosis on planetary gearbox is implemented. The proposed scheme is explained and demonstrated in both simulation and experimental studies. The scheme proves to be effective and features advantages on fault diagnosis of planetary gearboxes under non-stationary operational conditions.

  15. Fault diagnostics for turbo-shaft engine sensors based on a simplified on-board model.

    Science.gov (United States)

    Lu, Feng; Huang, Jinquan; Xing, Yaodong

    2012-01-01

    Combining a simplified on-board turbo-shaft model with sensor fault diagnostic logic, a model-based sensor fault diagnosis method is proposed. The existing fault diagnosis method for turbo-shaft engine key sensors is mainly based on a double redundancies technique, and this can't be satisfied in some occasions as lack of judgment. The simplified on-board model provides the analytical third channel against which the dual channel measurements are compared, while the hardware redundancy will increase the structure complexity and weight. The simplified turbo-shaft model contains the gas generator model and the power turbine model with loads, this is built up via dynamic parameters method. Sensor fault detection, diagnosis (FDD) logic is designed, and two types of sensor failures, such as the step faults and the drift faults, are simulated. When the discrepancy among the triplex channels exceeds a tolerance level, the fault diagnosis logic determines the cause of the difference. Through this approach, the sensor fault diagnosis system achieves the objectives of anomaly detection, sensor fault diagnosis and redundancy recovery. Finally, experiments on this method are carried out on a turbo-shaft engine, and two types of faults under different channel combinations are presented. The experimental results show that the proposed method for sensor fault diagnostics is efficient.

  16. Fault Diagnostics for Turbo-Shaft Engine Sensors Based on a Simplified On-Board Model

    Directory of Open Access Journals (Sweden)

    Yaodong Xing

    2012-08-01

    Full Text Available Combining a simplified on-board turbo-shaft model with sensor fault diagnostic logic, a model-based sensor fault diagnosis method is proposed. The existing fault diagnosis method for turbo-shaft engine key sensors is mainly based on a double redundancies technique, and this can’t be satisfied in some occasions as lack of judgment. The simplified on-board model provides the analytical third channel against which the dual channel measurements are compared, while the hardware redundancy will increase the structure complexity and weight. The simplified turbo-shaft model contains the gas generator model and the power turbine model with loads, this is built up via dynamic parameters method. Sensor fault detection, diagnosis (FDD logic is designed, and two types of sensor failures, such as the step faults and the drift faults, are simulated. When the discrepancy among the triplex channels exceeds a tolerance level, the fault diagnosis logic determines the cause of the difference. Through this approach, the sensor fault diagnosis system achieves the objectives of anomaly detection, sensor fault diagnosis and redundancy recovery. Finally, experiments on this method are carried out on a turbo-shaft engine, and two types of faults under different channel combinations are presented. The experimental results show that the proposed method for sensor fault diagnostics is efficient.

  17. Advanced monitoring, fault diagnostics, and maintenance of cryogenic systems

    CERN Document Server

    Girone, Mario; Pezzetti, Marco

    In this Thesis, advanced methods and techniques of monitoring, fault diagnostics, and predictive maintenance for cryogenic processes and systems are described. In particular, in Chapter 1, mainstreams in research on measurement systems for cryogenic processes are reviewed with the aim of dening key current trends and possible future evolutions. Then, in Chapter 2, several innovative methods are proposed. A transducer based on a virtual ow meter is presented for monitoring helium distribution and consumption in cryogenic systems for particle accelerators [1]. Furthermore, a comprehensive metrological analysis of the proposed transducer for verifying the metrological performance and pointing out most critical uncertainty sources is described [2]. A model-based method for fault detection and early-stage isolation, able to work with few records of Frequency Response Function (FRF) on an unfaulty compressor, is then proposed [3]. To enrich the proposal, a distributed diagnostic procedure, based on a micro-genetic...

  18. Study on Unified Chaotic System-Based Wind Turbine Blade Fault Diagnostic System

    Science.gov (United States)

    Kuo, Ying-Che; Hsieh, Chin-Tsung; Yau, Her-Terng; Li, Yu-Chung

    At present, vibration signals are processed and analyzed mostly in the frequency domain. The spectrum clearly shows the signal structure and the specific characteristic frequency band is analyzed, but the number of calculations required is huge, resulting in delays. Therefore, this study uses the characteristics of a nonlinear system to load the complete vibration signal to the unified chaotic system, applying the dynamic error to analyze the wind turbine vibration signal, and adopting extenics theory for artificial intelligent fault diagnosis of the analysis signal. Hence, a fault diagnostor has been developed for wind turbine rotating blades. This study simulates three wind turbine blade states, namely stress rupture, screw loosening and blade loss, and validates the methods. The experimental results prove that the unified chaotic system used in this paper has a significant effect on vibration signal analysis. Thus, the operating conditions of wind turbines can be quickly known from this fault diagnostic system, and the maintenance schedule can be arranged before the faults worsen, making the management and implementation of wind turbines smoother, so as to reduce many unnecessary costs.

  19. Development of a rule-based diagnostic platform on an object-oriented expert system shell

    International Nuclear Information System (INIS)

    Wang, Wenlin; Yang, Ming; Seong, Poong Hyun

    2016-01-01

    Highlights: • Multilevel Flow Model represents system knowledge as a domain map in expert system. • Rule-based fault diagnostic expert system can identify root cause via a causal chain. • Rule-based fault diagnostic expert system can be used for fault simulation training. - Abstract: This paper presents the development and implementation of a real-time rule-based diagnostic platform. The knowledge is acquired from domain experts and textbooks and the design of the fault diagnosis expert system was performed in the following ways: (i) establishing of corresponding classes and instances to build the domain map, (ii) creating of generic fault models based on events, and (iii) building of diagnostic reasoning based on rules. Knowledge representation is a complicated issue of expert systems. One highlight of this paper is that the Multilevel Flow Model has been used to represent the knowledge, which composes the domain map within the expert system as well as providing a concise description of the system. The developed platform is illustrated using the pressure safety system of a pressurized water reactor as an example of the simulation test bed; the platform is developed using the commercial and industrially validated software G2. The emulation test was conducted and it has been proven that the fault diagnosis expert system can identify the faults correctly and in a timely way; this system can be used as a simulation-based training tool to assist operators to make better decisions.

  20. An Integrated Architecture for On-Board Aircraft Engine Performance Trend Monitoring and Gas Path Fault Diagnostics

    Science.gov (United States)

    Simon, Donald L.

    2010-01-01

    Aircraft engine performance trend monitoring and gas path fault diagnostics are closely related technologies that assist operators in managing the health of their gas turbine engine assets. Trend monitoring is the process of monitoring the gradual performance change that an aircraft engine will naturally incur over time due to turbomachinery deterioration, while gas path diagnostics is the process of detecting and isolating the occurrence of any faults impacting engine flow-path performance. Today, performance trend monitoring and gas path fault diagnostic functions are performed by a combination of on-board and off-board strategies. On-board engine control computers contain logic that monitors for anomalous engine operation in real-time. Off-board ground stations are used to conduct fleet-wide engine trend monitoring and fault diagnostics based on data collected from each engine each flight. Continuing advances in avionics are enabling the migration of portions of the ground-based functionality on-board, giving rise to more sophisticated on-board engine health management capabilities. This paper reviews the conventional engine performance trend monitoring and gas path fault diagnostic architecture commonly applied today, and presents a proposed enhanced on-board architecture for future applications. The enhanced architecture gains real-time access to an expanded quantity of engine parameters, and provides advanced on-board model-based estimation capabilities. The benefits of the enhanced architecture include the real-time continuous monitoring of engine health, the early diagnosis of fault conditions, and the estimation of unmeasured engine performance parameters. A future vision to advance the enhanced architecture is also presented and discussed

  1. A study on the fault diagnostic techniques for reactor internal structures using neutron noise analysis

    International Nuclear Information System (INIS)

    Kim, Tae Ryong; Jeong, Seong Ho; Park, Jin Ho; Park, Jin Suk

    1994-08-01

    The unfavorable phenomena, such as flow induced vibration and aging process in reactor internals, cause degradation of structural integrity and may result in loosing some mechanical binding components which might impact other equipments and components or cause flow blockage. Since these malfunctions and potential failures change reactor noise signal, it is necessary to analyze reactor noise signal for early fault diagnosis in the point of few of safety and plant economics. The objectives of this study are to establish fault diagnostic and TS(thermal shield), and to develop a data acquisition and signal processing software system. In the first year of this study, an analysis technique for the reactor internal vibration using the reactor noise was proposed. With the technique proposed and the reactor noise signals (ex-core neutron and acceleration), the dynamic characteristics of Ulchin-1 reactor internals were obtained, and compared with those of Tricastin-1 which is the prototype of Ulchin-1. In the second year, a PC-based expert system for reactor internals fault diagnosis is developed, which included data acquisition, signal processing, feature extraction function, and represented diagnostic knowledge by the IF-THEN rule. To know the effect of the faults, the reactor internals of Ulchin-1 is modeled using FEM and simulated with an artificial defect given in the hold-down spring. Trend in the dynamic characteristics of reactor internals is also observed during one fuel cycle to know the effect of boron concentration. 100 figs, 7 tabs, 18 refs. (Author)

  2. An efficient diagnostic technique for distribution systems based on under fault voltages and currents

    Energy Technology Data Exchange (ETDEWEB)

    Campoccia, A.; Di Silvestre, M.L.; Incontrera, I.; Riva Sanseverino, E. [Dipartimento di Ingegneria Elettrica elettronica e delle Telecomunicazioni, Universita degli Studi di Palermo, viale delle Scienze, 90128 Palermo (Italy); Spoto, G. [Centro per la Ricerca Elettronica in Sicilia, Monreale, Via Regione Siciliana 49, 90046 Palermo (Italy)

    2010-10-15

    Service continuity is one of the major aspects in the definition of the quality of the electrical energy, for this reason the research in the field of faults diagnostic for distribution systems is spreading ever more. Moreover the increasing interest around modern distribution systems automation for management purposes gives faults diagnostics more tools to detect outages precisely and in short times. In this paper, the applicability of an efficient fault location and characterization methodology within a centralized monitoring system is discussed. The methodology, appropriate for any kind of fault, is based on the use of the analytical model of the network lines and uses the fundamental components rms values taken from the transient measures of line currents and voltages at the MV/LV substations. The fault location and identification algorithm, proposed by the authors and suitably restated, has been implemented on a microprocessor-based device that can be installed at each MV/LV substation. The speed and precision of the algorithm have been tested against the errors deriving from the fundamental extraction within the prescribed fault clearing times and against the inherent precision of the electronic device used for computation. The tests have been carried out using Matlab Simulink for simulating the faulted system. (author)

  3. Vibration monitoring and fault diagnostics of a thermal power plant

    International Nuclear Information System (INIS)

    Hafeez, T.; Ghani, R.; Chohan, G.Y.; Amir, M.

    2003-01-01

    A thermal power plant was monitored from HP-turbine to the generator end. The vibration data at different plant locations was obtained with the help of a data collector/analyzer. The spectra of-all locations generate the symptoms for different problems of moderate and high vibration levels like bent shaft, misalignment in the exciter rotor and three couplings, mechanical looseness on generator and exciter sides. The possible causes of these faults are discussed on the basis of presented vibration spectra in this paper. The faults were later on rectified on the basis of this diagnostics. (author)

  4. Development of a low cost test rig for standalone WECS subject to electrical faults.

    Science.gov (United States)

    Himani; Dahiya, Ratna

    2016-11-01

    In this paper, a contribution to the development of low-cost wind turbine (WT) test rig for stator fault diagnosis of wind turbine generator is proposed. The test rig is developed using a 2.5kW, 1750 RPM DC motor coupled to a 1.5kW, 1500 RPM self-excited induction generator interfaced with a WT mathematical model in LabVIEW. The performance of the test rig is benchmarked with already proven wind turbine test rigs. In order to detect the stator faults using non-stationary signals in self-excited induction generator, an online fault diagnostic technique of DWT-based multi-resolution analysis is proposed. It has been experimentally proven that for varying wind conditions wavelet decomposition allows good differentiation between faulty and healthy conditions leading to an effective diagnostic procedure for wind turbine condition monitoring. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

  5. Fault diagnosis

    Science.gov (United States)

    Abbott, Kathy

    1990-01-01

    The objective of the research in this area of fault management is to develop and implement a decision aiding concept for diagnosing faults, especially faults which are difficult for pilots to identify, and to develop methods for presenting the diagnosis information to the flight crew in a timely and comprehensible manner. The requirements for the diagnosis concept were identified by interviewing pilots, analyzing actual incident and accident cases, and examining psychology literature on how humans perform diagnosis. The diagnosis decision aiding concept developed based on those requirements takes abnormal sensor readings as input, as identified by a fault monitor. Based on these abnormal sensor readings, the diagnosis concept identifies the cause or source of the fault and all components affected by the fault. This concept was implemented for diagnosis of aircraft propulsion and hydraulic subsystems in a computer program called Draphys (Diagnostic Reasoning About Physical Systems). Draphys is unique in two important ways. First, it uses models of both functional and physical relationships in the subsystems. Using both models enables the diagnostic reasoning to identify the fault propagation as the faulted system continues to operate, and to diagnose physical damage. Draphys also reasons about behavior of the faulted system over time, to eliminate possibilities as more information becomes available, and to update the system status as more components are affected by the fault. The crew interface research is examining display issues associated with presenting diagnosis information to the flight crew. One study examined issues for presenting system status information. One lesson learned from that study was that pilots found fault situations to be more complex if they involved multiple subsystems. Another was pilots could identify the faulted systems more quickly if the system status was presented in pictorial or text format. Another study is currently under way to

  6. A flexible simulator for training an early fault diagnostic system

    International Nuclear Information System (INIS)

    Marsiletti, M.; Santinelli, A.; Zuenkov, M.; Poletykin, A.

    1997-01-01

    An early fault diagnostic system has been developed addressed to timely trouble shooting in process plants during any operational modes. The theory of this diagnostic system is related with the usage of learning methods for automatic generation of knowledge bases. This approach enables the conversion of ''cause→effect'' relations into ''effect→possible-causes'' ones. The diagnostic rules are derived from the operation of a plant simulator according to a specific procedure. Flexibility, accuracy and high speed are the major characteristics of the training simulator, used to generate the diagnostic knowledge base. The simulator structure is very flexible, being based on LEGO code but allowing the use of practically any kind of FORTRAN routines (recently also ACSL macros has been introduced) as plant modules: this permits, when needed, a very accurate description of the malfunctions the diagnostic system should ''known''. The high speed is useful to shorten the ''learning'' phase of the diagnostic system. The feasibility of the overall system has been assessed, using as reference plant the conventional Sampierdarena (Italy) power station, that is a combined cycle plant dedicated to produce both electrical and heat power. The hardware configuration of this prototype system was made up of a network of a Hewlett-Packard workstation and a Digital VAX-Station. The paper illustrates the basic structure of the simulator used for this diagnostic system training purpose, as well as the theoretical background on which the diagnostic system is based. Some evidence of the effectiveness of the concept through the application to Sampierdarena 40 MW cogeneration plant is reported. Finally an outline of an ongoing application to a WWER-1000 plant is given; the operating system is, in this case, UNIX. (author)

  7. A methodology for the quantitative evaluation of NPP fault diagnostic systems' dynamic aspects

    International Nuclear Information System (INIS)

    Kim, J.H.; Seong, P.H.

    2000-01-01

    A fault diagnostic system (FDS) is an operator decision support system which is implemented both to increase NPP efficiency as well as to reduce human error and cognitive workload that may cause nuclear power plant (NPP) accidents. Evaluation is an indispensable activity in constructing a reliable FDS. We first define the dynamic aspects of fault diagnostic systems (FDSs) for evaluation in this work. The dynamic aspect is concerned with the way a FDS responds to input. Next, we present a hierarchical structure in the evaluation for the dynamic aspects of FDSs. Dynamic aspects include both what a FDS provides and how a FDS operates. We define the former as content and the latter as behavior. Content and behavior contain two elements and six elements in the lower hierarchies, respectively. Content is a criterion for evaluating the integrity of a FDS, the problem types which a FDS deals with, along with the level of information. Behavior contains robustness, understandability, timeliness, transparency, effectiveness, and communicativeness of FDSs. On the other hand, the static aspects are concerned with the hardware and the software of the system. For quantitative evaluation, the method used to gain and aggregate the priorities of the criteria in this work is the analytic hierarchy process (AHP). The criteria at the lowest level are quantified through simple numerical expressions and questionnaires developed in this work. these well describe the characteristics of the criteria and appropriately use subjective, empirical, and technical methods. Finally, in order to demonstrate the feasibility of our evaluation method, we have performed one case study for the fault diagnosis module of OASYS TM (On-Line Operator Aid SYStem for Nuclear Power Plant), which is an operator support system developed at the Korea Advanced Institute of Science and Technology (KAIST)

  8. Development of a Diagnostic Complexity Questionnaire

    International Nuclear Information System (INIS)

    Collier, Steve

    1998-02-01

    The HRP human error analysis project has for some time been investigating what makes certain fault scenarios difficult for operators. One line of research has been to develop a questionnaire to measure diagnostic complexity. This report concerns some theoretical and experimental work underpinning the development of the questionnaire. A study of the literature reviewed the factors or components thought to contribute to difficulty in diagnosing and problem-solving. Two experimental studies of complexity were carried out using two versions of a questionnaire based on the review. The studies were simulator based, using scenarios designed to be diagnostically challenging. A factor-analytic approach to the analysis of the study data was suggested in the literature review. This is reported here (together with other analyses) though the factor analysis did not produce so clear results as was hoped. The present analysis found no clear factor structure with the first version of the complexity questionnaire used in experiment I. Partly because of this result, a factor-analytic approach to a second version of the questionnaire used in experiment II was not considered appropriate. A descriptive and qualitative analysis of the two questionnaire studies and a synthesis of the results from them both was promising. There were indications of components of complexity and some indications of what contributes to a personal perception of high or low diagnostic difficulty in fault scenarios. Components adding to diagnostic difficulty were tentatively named 'severity', 'need for co-operation', 'stress' and 'spread of changes'. Components not adding to difficulty were 'directness of indications', 'familiarity' and 'lack of stress'. There was some evidence of different responses to these components in a comparison of rule-based vs. knowledge-based diagnostic scenarios. These findings and experience with analysis techniques will feed into the design of further work on the human error

  9. Enhanced Bank of Kalman Filters Developed and Demonstrated for In-Flight Aircraft Engine Sensor Fault Diagnostics

    Science.gov (United States)

    Kobayashi, Takahisa; Simon, Donald L.

    2005-01-01

    In-flight sensor fault detection and isolation (FDI) is critical to maintaining reliable engine operation during flight. The aircraft engine control system, which computes control commands on the basis of sensor measurements, operates the propulsion systems at the demanded conditions. Any undetected sensor faults, therefore, may cause the control system to drive the engine into an undesirable operating condition. It is critical to detect and isolate failed sensors as soon as possible so that such scenarios can be avoided. A challenging issue in developing reliable sensor FDI systems is to make them robust to changes in engine operating characteristics due to degradation with usage and other faults that can occur during flight. A sensor FDI system that cannot appropriately account for such scenarios may result in false alarms, missed detections, or misclassifications when such faults do occur. To address this issue, an enhanced bank of Kalman filters was developed, and its performance and robustness were demonstrated in a simulation environment. The bank of filters is composed of m + 1 Kalman filters, where m is the number of sensors being used by the control system and, thus, in need of monitoring. Each Kalman filter is designed on the basis of a unique fault hypothesis so that it will be able to maintain its performance if a particular fault scenario, hypothesized by that particular filter, takes place.

  10. Fault diagnostics of dynamic system operation using a fault tree based method

    International Nuclear Information System (INIS)

    Hurdle, E.E.; Bartlett, L.M.; Andrews, J.D.

    2009-01-01

    For conventional systems, their availability can be considerably improved by reducing the time taken to restore the system to the working state when faults occur. Fault identification can be a significant proportion of the time taken in the repair process. Having diagnosed the problem the restoration of the system back to its fully functioning condition can then take place. This paper expands the capability of previous approaches to fault detection and identification using fault trees for application to dynamically changing systems. The technique has two phases. The first phase is modelling and preparation carried out offline. This gathers information on the effects that sub-system failure will have on the system performance. Causes of the sub-system failures are developed in the form of fault trees. The second phase is application. Sensors are installed on the system to provide information about current system performance from which the potential causes can be deduced. A simple system example is used to demonstrate the features of the method. To illustrate the potential for the method to deal with additional system complexity and redundancy, a section from an aircraft fuel system is used. A discussion of the results is provided.

  11. Development of Monitoring and Diagnostic Methods for Robots Used In Remediation of Waste Sites - Final Report

    International Nuclear Information System (INIS)

    Martin, M.

    2000-01-01

    This project is the first evaluation of model-based diagnostics to hydraulic robot systems. A greater understanding of fault detection for hydraulic robots has been gained, and a new theoretical fault detection model developed and evaluated

  12. A Generic Modeling Process to Support Functional Fault Model Development

    Science.gov (United States)

    Maul, William A.; Hemminger, Joseph A.; Oostdyk, Rebecca; Bis, Rachael A.

    2016-01-01

    Functional fault models (FFMs) are qualitative representations of a system's failure space that are used to provide a diagnostic of the modeled system. An FFM simulates the failure effect propagation paths within a system between failure modes and observation points. These models contain a significant amount of information about the system including the design, operation and off nominal behavior. The development and verification of the models can be costly in both time and resources. In addition, models depicting similar components can be distinct, both in appearance and function, when created individually, because there are numerous ways of representing the failure space within each component. Generic application of FFMs has the advantages of software code reuse: reduction of time and resources in both development and verification, and a standard set of component models from which future system models can be generated with common appearance and diagnostic performance. This paper outlines the motivation to develop a generic modeling process for FFMs at the component level and the effort to implement that process through modeling conventions and a software tool. The implementation of this generic modeling process within a fault isolation demonstration for NASA's Advanced Ground System Maintenance (AGSM) Integrated Health Management (IHM) project is presented and the impact discussed.

  13. Pilot study of dynamic Bayesian networks approach for fault diagnostics and accident progression prediction in HTR-PM

    Energy Technology Data Exchange (ETDEWEB)

    Zhao, Yunfei; Tong, Jiejuan; Zhang, Liguo, E-mail: lgzhang@tsinghua.edu.cn; Zhang, Qin

    2015-09-15

    Highlights: • Dynamic Bayesian network is used to diagnose and predict accident progress in HTR-PM. • Dynamic Bayesian network model of HTR-PM is built based on detailed system analysis. • LOCA Simulations validate the above model even if part monitors are lost or false. - Abstract: The first high-temperature-reactor pebble-bed demonstration module (HTR-PM) is under construction currently in China. At the same time, development of a system that is used to support nuclear emergency response is in progress. The supporting system is expected to complete two tasks. The first one is diagnostics of the fault in the reactor based on abnormal sensor measurements obtained. The second one is prognostic of the accident progression based on sensor measurements obtained and operator actions. Both tasks will provide valuable guidance for emergency staff to take appropriate protective actions. Traditional method for the two tasks relies heavily on expert judgment, and has been proven to be inappropriate in some cases, such as Three Mile Island accident. To better perform the two tasks, dynamic Bayesian networks (DBN) is introduced in this paper and a pilot study based on the approach is carried out. DBN is advantageous in representing complex dynamic systems and taking full consideration of evidences obtained to perform diagnostics and prognostics. Pearl's loopy belief propagation (LBP) algorithm is recommended for diagnostics and prognostics in DBN. The DBN model of HTR-PM is created based on detailed system analysis and accident progression analysis. A small break loss of coolant accident (SBLOCA) is selected to illustrate the application of the DBN model of HTR-PM in fault diagnostics (FD) and accident progression prognostics (APP). Several advantages of DBN approach compared with other techniques are discussed. The pilot study lays the foundation for developing the nuclear emergency response supporting system (NERSS) for HTR-PM.

  14. The Diagnostic Challenge Competition: Probabilistic Techniques for Fault Diagnosis in Electrical Power Systems

    Science.gov (United States)

    Ricks, Brian W.; Mengshoel, Ole J.

    2009-01-01

    Reliable systems health management is an important research area of NASA. A health management system that can accurately and quickly diagnose faults in various on-board systems of a vehicle will play a key role in the success of current and future NASA missions. We introduce in this paper the ProDiagnose algorithm, a diagnostic algorithm that uses a probabilistic approach, accomplished with Bayesian Network models compiled to Arithmetic Circuits, to diagnose these systems. We describe the ProDiagnose algorithm, how it works, and the probabilistic models involved. We show by experimentation on two Electrical Power Systems based on the ADAPT testbed, used in the Diagnostic Challenge Competition (DX 09), that ProDiagnose can produce results with over 96% accuracy and less than 1 second mean diagnostic time.

  15. Integrated fault tree development environment

    International Nuclear Information System (INIS)

    Dixon, B.W.

    1986-01-01

    Probabilistic Risk Assessment (PRA) techniques are utilized in the nuclear industry to perform safety analyses of complex defense-in-depth systems. A major effort in PRA development is fault tree construction. The Integrated Fault Tree Environment (IFTREE) is an interactive, graphics-based tool for fault tree design. IFTREE provides integrated building, editing, and analysis features on a personal workstation. The design philosophy of IFTREE is presented, and the interface is described. IFTREE utilizes a unique rule-based solution algorithm founded in artificial intelligence (AI) techniques. The impact of the AI approach on the program design is stressed. IFTREE has been developed to handle the design and maintenance of full-size living PRAs and is currently in use

  16. Subassembly faults diagnostic of an LMFBR type reactor by the measurement of temperature noise

    International Nuclear Information System (INIS)

    Kokorev, B.V.; Palkin, I.I.; Turchin, N.M.; Pallagi, D.; Horanyi, S.

    1979-09-01

    The subassembly faults detection possibility by temperature noise analysis of an LMFBR is described. The paper contains the results of diagnostical examinations obtained on electrically heated NaK test rigs. On the basis of these results the measurement of temperature noise RMS value seems to be a practicable method to detect local blockages in an early phase. (author)

  17. Turbine engine rotor blade fault diagnostics through casing pressure and vibration sensors

    International Nuclear Information System (INIS)

    Cox, J; Anusonti-Inthra, P

    2014-01-01

    In this study, an exact solution is provided for a previously indeterminate equation used for rotor blade fault diagnostics. The method estimates rotor blade natural frequency through turbine engine casing pressure and vibration sensors. The equation requires accurate measurements of low-amplitude sideband signals in the frequency domain. With this in mind, statistical evaluation was also completed with the goal of determining the effect of sampling time and frequency on sideband resolution in the frequency domain

  18. Modeling, control and fault diagnosis of an isolated wind energy conversion system with a self-excited induction generator subject to electrical faults

    International Nuclear Information System (INIS)

    Attoui, Issam; Omeiri, Amar

    2014-01-01

    Highlights: • A new model of the SEIG is developed to simulate both the rotor and stator faults. • This model takes iron loss, main flux and cross flux saturation into account. • A new control strategy based on Fractional-Order Controller (FOC) is proposed. • The control strategy is developed for the control of the wind turbine speed. • An on-line diagnostic procedure based on the stator currents analysis is presented. - Abstract: In this paper, a contribution to modeling and fault diagnosis of rotor and stator faults of a Self-Excited Induction Generator (SEIG) in an Isolated Wind Energy Conversion System (IWECS) is proposed. In order to control the speed of the wind turbine, while basing on the linear model of wind turbine system about a specified operating point, a new Fractional-Order Controller (FOC) with a simple and practical design method is proposed. The FOC ensures the stability of the nonlinear system in both healthy and faulty conditions. Furthermore, in order to detect the stator and rotor faults in the squirrel-cage self-excited induction generator, an on-line fault diagnostic technique based on the spectral analysis of stator currents of the squirrel-cage SEIG by a Fast Fourier Transform (FFT) algorithm is used. Additionally, a generalized model of the squirrel-cage SEIG is developed to simulate both the rotor and stator faults taking iron loss, main flux and cross flux saturation into account. The efficiencies of generalized model, control strategy and diagnostic procedure are illustrated with simulation results

  19. Development of methods for evaluating active faults

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    2013-08-15

    The report for long-term evaluation of active faults was published by the Headquarters for Earthquake Research Promotion on Nov. 2010. After occurrence of the 2011 Tohoku-oki earthquake, the safety review guide with regard to geology and ground of site was revised by the Nuclear Safety Commission on Mar. 2012 with scientific knowledges of the earthquake. The Nuclear Regulation Authority established on Sep. 2012 is newly planning the New Safety Design Standard related to Earthquakes and Tsunamis of Light Water Nuclear Power Reactor Facilities. With respect to those guides and standards, our investigations for developing the methods of evaluating active faults are as follows; (1) For better evaluation on activities of offshore fault, we proposed a work flow to date marine terrace (indicator for offshore fault activity) during the last 400,000 years. We also developed the analysis of fault-related fold for evaluating of blind fault. (2) To clarify the activities of active faults without superstratum, we carried out the color analysis of fault gouge and divided the activities into thousand of years and tens of thousands. (3) To reduce uncertainties of fault activities and frequency of earthquakes, we compiled the survey data and possible errors. (4) For improving seismic hazard analysis, we compiled the fault activities of the Yunotake and Itozawa faults, induced by the 2011 Tohoku-oki earthquake. (author)

  20. Recent advances in control and diagnostics development and application

    International Nuclear Information System (INIS)

    Monson, L.R.; King, R.W.; Lindsay, R.W.; Staffon, J.D.

    1989-01-01

    The power industry is undergoing rapid technological advances and cultural changes. Technologies are advancing and evolving so rapidly that the industry is hard pressed to keep up and take full advantage of the many developments now in progress. Recent advantages in state-of-the-art computer technology are making in-roads in the form of advanced computer control, expert systems, on-line performance monitoring and diagnostics. Validation and verification schemes are being developed which provide increased confidence in the correctness and reliability of both computer hardware and software. Our challenge in the nuclear community is to effectively apply these new technologies to improve the operation, safety, and reliability of our plants. This presentation discusses two areas of development that are essential to advanced control strategies: application of diagnostic systems to improve fault-tolerance, and model-based graphic displays. 4 refs., 4 figs

  1. Ares I-X Ground Diagnostic Prototype

    Science.gov (United States)

    Schwabacher, Mark A.; Martin, Rodney Alexander; Waterman, Robert D.; Oostdyk, Rebecca Lynn; Ossenfort, John P.; Matthews, Bryan

    2010-01-01

    The automation of pre-launch diagnostics for launch vehicles offers three potential benefits: improving safety, reducing cost, and reducing launch delays. The Ares I-X Ground Diagnostic Prototype demonstrated anomaly detection, fault detection, fault isolation, and diagnostics for the Ares I-X first-stage Thrust Vector Control and for the associated ground hydraulics while the vehicle was in the Vehicle Assembly Building at Kennedy Space Center (KSC) and while it was on the launch pad. The prototype combines three existing tools. The first tool, TEAMS (Testability Engineering and Maintenance System), is a model-based tool from Qualtech Systems Inc. for fault isolation and diagnostics. The second tool, SHINE (Spacecraft Health Inference Engine), is a rule-based expert system that was developed at the NASA Jet Propulsion Laboratory. We developed SHINE rules for fault detection and mode identification, and used the outputs of SHINE as inputs to TEAMS. The third tool, IMS (Inductive Monitoring System), is an anomaly detection tool that was developed at NASA Ames Research Center. The three tools were integrated and deployed to KSC, where they were interfaced with live data. This paper describes how the prototype performed during the period of time before the launch, including accuracy and computer resource usage. The paper concludes with some of the lessons that we learned from the experience of developing and deploying the prototype.

  2. Software development to assist in fault tree construction

    International Nuclear Information System (INIS)

    Simic, Z.; Mikulicic, V.

    1992-01-01

    This paper reviews and classifies fault tree construction methods developed for system safety and reliability. We have outlined two generally different approaches: automatic and interactive fault tree construction. Automatic fault tree approach is no jet enough developed to covering various uses in practice. Interactive approach is intending to be support to the analyst (not vice verse like in automatic approach). The aim is not so high as automatic one but it is accessible. We have favored interactive approach as well because to our opinion the process of fault tree construction is very important for better system understanding. We have described our example of interactive fault tree construction approach. Computer code GIFFT (Graphical Interactive Fault Tree Tool) is in phase of intensive testing and final developing. (author) [hr

  3. Rule - based Fault Diagnosis Expert System for Wind Turbine

    Directory of Open Access Journals (Sweden)

    Deng Xiao-Wen

    2017-01-01

    Full Text Available Under the trend of increasing installed capacity of wind power, the intelligent fault diagnosis of wind turbine is of great significance to the safe and efficient operation of wind farms. Based on the knowledge of fault diagnosis of wind turbines, this paper builds expert system diagnostic knowledge base by using confidence production rules and expert system self-learning method. In Visual Studio 2013 platform, C # language is selected and ADO.NET technology is used to access the database. Development of Fault Diagnosis Expert System for Wind Turbine. The purpose of this paper is to realize on-line diagnosis of wind turbine fault through human-computer interaction, and to improve the diagnostic capability of the system through the continuous improvement of the knowledge base.

  4. A methodology and status of technology for fault diagnosis

    International Nuclear Information System (INIS)

    Kim, Jung Taek; Ham, Chang Shik; Kwon, Kee Choon; Lee, Dong Young; Hwang, In Koo; Song, Soon Ja; Park, Joo Hweon

    1998-05-01

    Since the 1980's, a nuclear industry has been attempting to apply an artificial intelligent system into MMIS. Such attempts have, especially, been led by U.S.A., Japan and Halden, which were more active for studying an artificial intelligent system. a diagnostic system is being developed such a small system that is the more frequent faults or directly effects fault into a operation and a safety of plants. Such a small diagnostic system gives a diagnostic information into the alarm processing systems or the plant information monitoring systems as integrated with these large systems. There are two major methods of diagnosis of faults. The first method is to make a misbehavior on components or processes into knowledge base and the other is to make a misbehavior on components or processes into processing model. The latter has the advantage of the former. There are OASYS and alarm processing system in ADIOS as the typical diagnostic systems on knowledge base. There are MOAS-II, Halden's diagnostic systems and diagnostic model in ADIOS as the typical diagnostic systems on model base. (author). 32 refs., 18 tabs., 28 figs

  5. Fault-tolerant quantum computing in the Pauli or Clifford frame with slow error diagnostics

    Directory of Open Access Journals (Sweden)

    Christopher Chamberland

    2018-01-01

    Full Text Available We consider the problem of fault-tolerant quantum computation in the presence of slow error diagnostics, either caused by measurement latencies or slow decoding algorithms. Our scheme offers a few improvements over previously existing solutions, for instance it does not require active error correction and results in a reduced error-correction overhead when error diagnostics is much slower than the gate time. In addition, we adapt our protocol to cases where the underlying error correction strategy chooses the optimal correction amongst all Clifford gates instead of the usual Pauli gates. The resulting Clifford frame protocol is of independent interest as it can increase error thresholds and could find applications in other areas of quantum computation.

  6. Development and testing of a diagnostic system for intelligen distributed control at EBR-2

    International Nuclear Information System (INIS)

    Edwards, R.M.; Ruhl, D.W.; Klevans, E.H.; Robinson, G.E.

    1990-01-01

    A diagnostic system is under development for demonstration of Intelligent Distributed Control at the Experimental Breeder Reactor (EBR--II). In the first phase of the project a diagnostic system is being developed for the EBR-II steam plant based on the DISYS expert systems approach. Current testing uses recorded plant data and data from simulated plant faults. The dynamical simulation of the EBR-II steam plant uses the Babcock and Wilcox (B ampersand W) Modular Modeling System (MMS). At EBR-II the diagnostic system operates in the UNIX workstation and receives live plant data from the plant Data Acquisition System (DAS). Future work will seek implementation of the steam plant diagnostic in a distributed manner using UNIX based computers and Bailey microprocessor-based control system. 10 refs., 6 figs

  7. Final results from the development of the diagnostic expert system DESYRE

    International Nuclear Information System (INIS)

    Scherer, K.P.; Eggert, H.; Sheleisiek, K.; Stille, P.; Schoeller, H.

    1997-01-01

    In the Kernforschungszentrum Karlsruhe (KfK), a distributed knowledge based diagnostic system is developed to supervise the primary system including the core of the Kompakte Natriumgekuehlte Kernreaktoranlage (KNK II), a 20 MWe experimental fast reactor. The problem is to detect anomalies and disturbances in the beginning state before fault propagation - early diagnosis - and provide the scram analysis to detect the causality when a system shutdwon occurs. (author). 9 refs, 15 figs

  8. Hypothetical Scenario Generator for Fault-Tolerant Diagnosis

    Science.gov (United States)

    James, Mark

    2007-01-01

    The Hypothetical Scenario Generator for Fault-tolerant Diagnostics (HSG) is an algorithm being developed in conjunction with other components of artificial- intelligence systems for automated diagnosis and prognosis of faults in spacecraft, aircraft, and other complex engineering systems. By incorporating prognostic capabilities along with advanced diagnostic capabilities, these developments hold promise to increase the safety and affordability of the affected engineering systems by making it possible to obtain timely and accurate information on the statuses of the systems and predicting impending failures well in advance. The HSG is a specific instance of a hypothetical- scenario generator that implements an innovative approach for performing diagnostic reasoning when data are missing. The special purpose served by the HSG is to (1) look for all possible ways in which the present state of the engineering system can be mapped with respect to a given model and (2) generate a prioritized set of future possible states and the scenarios of which they are parts.

  9. A Fault Alarm and Diagnosis Method Based on Sensitive Parameters and Support Vector Machine

    Science.gov (United States)

    Zhang, Jinjie; Yao, Ziyun; Lv, Zhiquan; Zhu, Qunxiong; Xu, Fengtian; Jiang, Zhinong

    2015-08-01

    Study on the extraction of fault feature and the diagnostic technique of reciprocating compressor is one of the hot research topics in the field of reciprocating machinery fault diagnosis at present. A large number of feature extraction and classification methods have been widely applied in the related research, but the practical fault alarm and the accuracy of diagnosis have not been effectively improved. Developing feature extraction and classification methods to meet the requirements of typical fault alarm and automatic diagnosis in practical engineering is urgent task. The typical mechanical faults of reciprocating compressor are presented in the paper, and the existing data of online monitoring system is used to extract fault feature parameters within 15 types in total; the inner sensitive connection between faults and the feature parameters has been made clear by using the distance evaluation technique, also sensitive characteristic parameters of different faults have been obtained. On this basis, a method based on fault feature parameters and support vector machine (SVM) is developed, which will be applied to practical fault diagnosis. A better ability of early fault warning has been proved by the experiment and the practical fault cases. Automatic classification by using the SVM to the data of fault alarm has obtained better diagnostic accuracy.

  10. Two Trees: Migrating Fault Trees to Decision Trees for Real Time Fault Detection on International Space Station

    Science.gov (United States)

    Lee, Charles; Alena, Richard L.; Robinson, Peter

    2004-01-01

    We started from ISS fault trees example to migrate to decision trees, presented a method to convert fault trees to decision trees. The method shows that the visualizations of root cause of fault are easier and the tree manipulating becomes more programmatic via available decision tree programs. The visualization of decision trees for the diagnostic shows a format of straight forward and easy understands. For ISS real time fault diagnostic, the status of the systems could be shown by mining the signals through the trees and see where it stops at. The other advantage to use decision trees is that the trees can learn the fault patterns and predict the future fault from the historic data. The learning is not only on the static data sets but also can be online, through accumulating the real time data sets, the decision trees can gain and store faults patterns in the trees and recognize them when they come.

  11. Advanced diagnostic system for piston slap faults in IC engines, based on the non-stationary characteristics of the vibration signals

    Science.gov (United States)

    Chen, Jian; Randall, Robert Bond; Peeters, Bart

    2016-06-01

    Artificial Neural Networks (ANNs) have the potential to solve the problem of automated diagnostics of piston slap faults, but the critical issue for the successful application of ANN is the training of the network by a large amount of data in various engine conditions (different speed/load conditions in normal condition, and with different locations/levels of faults). On the other hand, the latest simulation technology provides a useful alternative in that the effect of clearance changes may readily be explored without recourse to cutting metal, in order to create enough training data for the ANNs. In this paper, based on some existing simplified models of piston slap, an advanced multi-body dynamic simulation software was used to simulate piston slap faults with different speeds/loads and clearance conditions. Meanwhile, the simulation models were validated and updated by a series of experiments. Three-stage network systems are proposed to diagnose piston faults: fault detection, fault localisation and fault severity identification. Multi Layer Perceptron (MLP) networks were used in the detection stage and severity/prognosis stage and a Probabilistic Neural Network (PNN) was used to identify which cylinder has faults. Finally, it was demonstrated that the networks trained purely on simulated data can efficiently detect piston slap faults in real tests and identify the location and severity of the faults as well.

  12. Fault-tolerant architecture: Evaluation methodology

    International Nuclear Information System (INIS)

    Battle, R.E.; Kisner, R.A.

    1992-08-01

    The design and reliability of four fault-tolerant architectures that may be used in nuclear power plant control systems were evaluated. Two architectures are variations of triple-modular-redundant (TMR) systems, and two are variations of dual redundant systems. The evaluation includes a review of methods of implementing fault-tolerant control, the importance of automatic recovery from failures, methods of self-testing diagnostics, block diagrams of typical fault-tolerant controllers, review of fault-tolerant controllers operating in nuclear power plants, and fault tree reliability analyses of fault-tolerant systems

  13. Fault isolability with different forms of the faults–symptoms relation

    Directory of Open Access Journals (Sweden)

    Kóscielny Jan Maciej

    2016-12-01

    Full Text Available The definitions and conditions for fault isolability of single faults for various forms of the diagnostic relation are reviewed. Fault isolability and unisolability on the basis of a binary diagnostic matrix are analyzed. Definitions for conditional and unconditional isolability and unisolability on the basis of a fault information system (FIS, symptom sequences and directional residuals are formulated. General definitions for conditional and unconditional isolability and unisolability in the cases of simultaneous evaluation of diagnostic signal values and a sequence of symptoms are provided. A comprehensive example is discussed.

  14. Fault diagnosis of power transformer based on fault-tree analysis (FTA)

    Science.gov (United States)

    Wang, Yongliang; Li, Xiaoqiang; Ma, Jianwei; Li, SuoYu

    2017-05-01

    Power transformers is an important equipment in power plants and substations, power distribution transmission link is made an important hub of power systems. Its performance directly affects the quality and health of the power system reliability and stability. This paper summarizes the five parts according to the fault type power transformers, then from the time dimension divided into three stages of power transformer fault, use DGA routine analysis and infrared diagnostics criterion set power transformer running state, finally, according to the needs of power transformer fault diagnosis, by the general to the section by stepwise refinement of dendritic tree constructed power transformer fault

  15. Tools for functional analysis of faults and methods of fault-stable motion control

    International Nuclear Information System (INIS)

    Timofeev, A.V.

    2003-01-01

    In this article a big attention is given to the problems of functional diagnostics, when control and faults diagnostics are made in real time simultaneously in the process of functioning of controlled dynamical systems

  16. Towards the development of multilevel-multiagent diagnostic aids

    International Nuclear Information System (INIS)

    Stratton, R.C.; Jarrell, D.B.

    1991-10-01

    Presented here is our methodology for developing automated aids for diagnosing faults in complex systems. We have designed these aids as multilevel-multiagent diagnostic aids based on principles that should be generally applicable to any complex system. In this methodology, ''multilevel'' refers to information models described at successful levels of abstraction that are tied together in such a way that reasoning is directed to the appropriate level as determined by the problem solving requirements. The concept of ''multiagent'' refers to the method of information processing within the multilevel model network; each model in the network is an independent information processor, i.e., an intelligent agent. 19 refs., 15 figs., 9 tabs

  17. Developing a PC-based expert system for fault analysis of reactor instruments

    International Nuclear Information System (INIS)

    Diwakar, M.P.; Rathod, N.C.; Bairi, B.R.; Darbhe, M.D.; Joglekar, S.S.

    1989-01-01

    This paper describes the development of an expert system for fault analysis of electronic instruments in the CIRUS nuclear reactor. The system was developed in Prolog on an IBM PC-XT compatible computer. A 'model-based' approach (Button et al, 1986) was adopted combining 'frames' and 'rules' to provide flexible control over the inferencing mechanisms. Frames represent the domain-objects as well as the inter-object relationships. They include 'demons' or 'active values' for triggering actions. Rules, along with frames, are used for fault analysis. The rules can be activated either in a data-driven or a goal-driven manner. The use of frames makes rule management easier. It is felt that developing in-house shell proved advantageous, compared to using commercially available shells. Choosing the model-based approach was efficient compared to a production system architecture. Therefore, the use of hybrid representations for diagnostic applications is advocated. Based on the experience, some general recommendations for developing such systems are presented. The expert system helps novice operators to understand the process of diagnosis and achieve a significant required level of competence. The system may not achieve the required level of proficiency by itself, but it can be used to train operators to become experts. (author). 12 refs

  18. Simultaneous Sensor and Process Fault Diagnostics for Propellant Feed System

    Science.gov (United States)

    Cao, J.; Kwan, C.; Figueroa, F.; Xu, R.

    2006-01-01

    The main objective of this research is to extract fault features from sensor faults and process faults by using advanced fault detection and isolation (FDI) algorithms. A tank system that has some common characteristics to a NASA testbed at Stennis Space Center was used to verify our proposed algorithms. First, a generic tank system was modeled. Second, a mathematical model suitable for FDI has been derived for the tank system. Third, a new and general FDI procedure has been designed to distinguish process faults and sensor faults. Extensive simulations clearly demonstrated the advantages of the new design.

  19. Rectifier Fault Diagnosis and Fault Tolerance of a Doubly Fed Brushless Starter Generator

    Directory of Open Access Journals (Sweden)

    Liwei Shi

    2015-01-01

    Full Text Available This paper presents a rectifier fault diagnosis method with wavelet packet analysis to improve the fault tolerant four-phase doubly fed brushless starter generator (DFBLSG system reliability. The system components and fault tolerant principle of the high reliable DFBLSG are given. And the common fault of the rectifier is analyzed. The process of wavelet packet transforms fault detection/identification algorithm is introduced in detail. The fault tolerant performance and output voltage experiments were done to gather the energy characteristics with a voltage sensor. The signal is analyzed with 5-layer wavelet packets, and the energy eigenvalue of each frequency band is obtained. Meanwhile, the energy-eigenvalue tolerance was introduced to improve the diagnostic accuracy. With the wavelet packet fault diagnosis, the fault tolerant four-phase DFBLSG can detect the usual open-circuit fault and operate in the fault tolerant mode if there is a fault. The results indicate that the fault analysis techniques in this paper are accurate and effective.

  20. Application of support vector machine based on pattern spectrum entropy in fault diagnostics of rolling element bearings

    International Nuclear Information System (INIS)

    Hao, Rujiang; Chu, Fulei; Peng, Zhike; Feng, Zhipeng

    2011-01-01

    This paper presents a novel pattern classification approach for the fault diagnostics of rolling element bearings, which combines the morphological multi-scale analysis and the 'one to others' support vector machine (SVM) classifiers. The morphological pattern spectrum describes the shape characteristics of the inspected signal based on the morphological opening operation with multi-scale structuring elements. The pattern spectrum entropy and the barycenter scale location of the spectrum curve are extracted as the feature vectors presenting different faults of the bearing, which are more effective and representative than the kurtosis and the enveloping demodulation spectrum. The 'one to others' SVM algorithm is adopted to distinguish six kinds of fault signals which were measured in the experimental test rig under eight different working conditions. The recognition results of the SVM are ideal and more precise than those of the artificial neural network even though the training samples are few. The combination of the morphological pattern spectrum parameters and the 'one to others' multi-class SVM algorithm is suitable for the on-line automated fault diagnosis of the rolling element bearings. This application is promising and worth well exploiting

  1. A Fault Diagnosis Methodology for Gear Pump Based on EEMD and Bayesian Network.

    Science.gov (United States)

    Liu, Zengkai; Liu, Yonghong; Shan, Hongkai; Cai, Baoping; Huang, Qing

    2015-01-01

    This paper proposes a fault diagnosis methodology for a gear pump based on the ensemble empirical mode decomposition (EEMD) method and the Bayesian network. Essentially, the presented scheme is a multi-source information fusion based methodology. Compared with the conventional fault diagnosis with only EEMD, the proposed method is able to take advantage of all useful information besides sensor signals. The presented diagnostic Bayesian network consists of a fault layer, a fault feature layer and a multi-source information layer. Vibration signals from sensor measurement are decomposed by the EEMD method and the energy of intrinsic mode functions (IMFs) are calculated as fault features. These features are added into the fault feature layer in the Bayesian network. The other sources of useful information are added to the information layer. The generalized three-layer Bayesian network can be developed by fully incorporating faults and fault symptoms as well as other useful information such as naked eye inspection and maintenance records. Therefore, diagnostic accuracy and capacity can be improved. The proposed methodology is applied to the fault diagnosis of a gear pump and the structure and parameters of the Bayesian network is established. Compared with artificial neural network and support vector machine classification algorithms, the proposed model has the best diagnostic performance when sensor data is used only. A case study has demonstrated that some information from human observation or system repair records is very helpful to the fault diagnosis. It is effective and efficient in diagnosing faults based on uncertain, incomplete information.

  2. A distributed fault tolerant architecture for nuclear reactor control and safety functions

    International Nuclear Information System (INIS)

    Hecht, M.; Agron, J.; Hochhauser, S.

    1989-01-01

    This paper reports on a fault tolerance architecture that provides tolerance to a broad scope of hardware, software, and communications faults which is being developed. This architecture relies on widely commercially available operating systems, local area networks, and software standards. Thus, development time is significantly shortened, and modularity allows for continuous and inexpensive system enhancement throughout the expected 20- year life. The fault containment and parallel processing capabilites of computers network are being exploited to provide a high performance, high availability network capable of tolerating a broad scope of hardware software, and operating system faults. The system can tolerate all but one known (and avoidable) single fault, two known and avoidable dual faults, and will detect all higher order fault sequences and provide diagnostics to allow for rapid manual recovery

  3. Estimation of Faults in DC Electrical Power System

    Science.gov (United States)

    Gorinevsky, Dimitry; Boyd, Stephen; Poll, Scott

    2009-01-01

    This paper demonstrates a novel optimization-based approach to estimating fault states in a DC power system. Potential faults changing the circuit topology are included along with faulty measurements. Our approach can be considered as a relaxation of the mixed estimation problem. We develop a linear model of the circuit and pose a convex problem for estimating the faults and other hidden states. A sparse fault vector solution is computed by using 11 regularization. The solution is computed reliably and efficiently, and gives accurate diagnostics on the faults. We demonstrate a real-time implementation of the approach for an instrumented electrical power system testbed, the ADAPT testbed at NASA ARC. The estimates are computed in milliseconds on a PC. The approach performs well despite unmodeled transients and other modeling uncertainties present in the system.

  4. Soft-Fault Detection Technologies Developed for Electrical Power Systems

    Science.gov (United States)

    Button, Robert M.

    2004-01-01

    The NASA Glenn Research Center, partner universities, and defense contractors are working to develop intelligent power management and distribution (PMAD) technologies for future spacecraft and launch vehicles. The goals are to provide higher performance (efficiency, transient response, and stability), higher fault tolerance, and higher reliability through the application of digital control and communication technologies. It is also expected that these technologies will eventually reduce the design, development, manufacturing, and integration costs for large, electrical power systems for space vehicles. The main focus of this research has been to incorporate digital control, communications, and intelligent algorithms into power electronic devices such as direct-current to direct-current (dc-dc) converters and protective switchgear. These technologies, in turn, will enable revolutionary changes in the way electrical power systems are designed, developed, configured, and integrated in aerospace vehicles and satellites. Initial successes in integrating modern, digital controllers have proven that transient response performance can be improved using advanced nonlinear control algorithms. One technology being developed includes the detection of "soft faults," those not typically covered by current systems in use today. Soft faults include arcing faults, corona discharge faults, and undetected leakage currents. Using digital control and advanced signal analysis algorithms, we have shown that it is possible to reliably detect arcing faults in high-voltage dc power distribution systems (see the preceding photograph). Another research effort has shown that low-level leakage faults and cable degradation can be detected by analyzing power system parameters over time. This additional fault detection capability will result in higher reliability for long-lived power systems such as reusable launch vehicles and space exploration missions.

  5. A Three-Dimensional Receiver Operator Characteristic Surface Diagnostic Metric

    Science.gov (United States)

    Simon, Donald L.

    2011-01-01

    Receiver Operator Characteristic (ROC) curves are commonly applied as metrics for quantifying the performance of binary fault detection systems. An ROC curve provides a visual representation of a detection system s True Positive Rate versus False Positive Rate sensitivity as the detection threshold is varied. The area under the curve provides a measure of fault detection performance independent of the applied detection threshold. While the standard ROC curve is well suited for quantifying binary fault detection performance, it is not suitable for quantifying the classification performance of multi-fault classification problems. Furthermore, it does not provide a measure of diagnostic latency. To address these shortcomings, a novel three-dimensional receiver operator characteristic (3D ROC) surface metric has been developed. This is done by generating and applying two separate curves: the standard ROC curve reflecting fault detection performance, and a second curve reflecting fault classification performance. A third dimension, diagnostic latency, is added giving rise to 3D ROC surfaces. Applying numerical integration techniques, the volumes under and between the surfaces are calculated to produce metrics of the diagnostic system s detection and classification performance. This paper will describe the 3D ROC surface metric in detail, and present an example of its application for quantifying the performance of aircraft engine gas path diagnostic methods. Metric limitations and potential enhancements are also discussed

  6. Advance in study of intelligent diagnostic method for nuclear power plant

    International Nuclear Information System (INIS)

    Zhou Gang; Yang Li

    2008-01-01

    The advance of research on the application of three types of intelligent diagnostic approach based on neural network (ANN), fuzzy logic and expert system to the operation status monitoring and fault diagnosis of nuclear power plant (NPP) was reviewed. The research status and characters on status monitoring and fault diagnosis approaches based on neural network, fuzzy logic and expert system for nuclear power plant were analyzed. The development trend of applied research on intelligent diagnostic approaches for nuclear power plant was explored. The analysis results show that the research achievements on intelligent diagnostic approaches based on fuzzy logic and expert system for nuclear power plant are not much relatively. The research of intelligent diagnostic approaches for nuclear power plant concentrate on the aspect of operation status monitoring and fault diagnosis based on neural networks for nuclear power plant. The advancing tendency of intelligent diagnostic approaches for nuclear power plant is the combination of various intelligent diagnostic approaches, the combination of neural network diagnostic approaches and other diagnostic approaches as well as multiple neural network diagnostic approaches. (authors)

  7. Development of a fault test experimental facility model using Matlab

    Energy Technology Data Exchange (ETDEWEB)

    Pereira, Iraci Martinez; Moraes, Davi Almeida, E-mail: martinez@ipen.br, E-mail: dmoraes@dk8.com.br [Instituto de Pesquisas Energeticas e Nucleares (IPEN/CNEN-SP), Sao Paulo, SP (Brazil)

    2015-07-01

    The Fault Test Experimental Facility was developed to simulate a PWR nuclear power plant and is instrumented with temperature, level and pressure sensors. The Fault Test Experimental Facility can be operated to generate normal and fault data, and these failures can be added initially small, and their magnitude being increasing gradually. This work presents the Fault Test Experimental Facility model developed using the Matlab GUIDE (Graphical User Interface Development Environment) toolbox that consists of a set of functions designed to create interfaces in an easy and fast way. The system model is based on the mass and energy inventory balance equations. Physical as well as operational aspects are taken into consideration. The interface layout looks like a process flowchart and the user can set the input variables. Besides the normal operation conditions, there is the possibility to choose a faulty variable from a list. The program also allows the user to set the noise level for the input variables. Using the model, data were generated for different operational conditions, both under normal and fault conditions with different noise levels added to the input variables. Data generated by the model will be compared with Fault Test Experimental Facility data. The Fault Test Experimental Facility theoretical model results will be used for the development of a Monitoring and Fault Detection System. (author)

  8. Development of a fault test experimental facility model using Matlab

    International Nuclear Information System (INIS)

    Pereira, Iraci Martinez; Moraes, Davi Almeida

    2015-01-01

    The Fault Test Experimental Facility was developed to simulate a PWR nuclear power plant and is instrumented with temperature, level and pressure sensors. The Fault Test Experimental Facility can be operated to generate normal and fault data, and these failures can be added initially small, and their magnitude being increasing gradually. This work presents the Fault Test Experimental Facility model developed using the Matlab GUIDE (Graphical User Interface Development Environment) toolbox that consists of a set of functions designed to create interfaces in an easy and fast way. The system model is based on the mass and energy inventory balance equations. Physical as well as operational aspects are taken into consideration. The interface layout looks like a process flowchart and the user can set the input variables. Besides the normal operation conditions, there is the possibility to choose a faulty variable from a list. The program also allows the user to set the noise level for the input variables. Using the model, data were generated for different operational conditions, both under normal and fault conditions with different noise levels added to the input variables. Data generated by the model will be compared with Fault Test Experimental Facility data. The Fault Test Experimental Facility theoretical model results will be used for the development of a Monitoring and Fault Detection System. (author)

  9. FAULT DIAGNOSIS IN ROTATING MACHINE USING FULL SPECTRUM OF VIBRATION AND FUZZY LOGIC

    Directory of Open Access Journals (Sweden)

    ROGER R. DA SILVA

    2017-11-01

    Full Text Available Industries are always looking for more efficient maintenance systems to minimize machine downtime and productivity liabilities. Among several approaches, artificial intelligence techniques have been increasingly applied to machine diagnosis. Current paper forwards the development of a system for the diagnosis of mechanical faults in the rotating structures of machines, based on fuzzy logic, using rules foregrounded on the full spectrum of the machine´s complex vibration signal. The diagnostic system was developed in Matlab and it was applied to a rotor test rig where different faults were introduced. Results showed that the diagnostic system based on full spectra and fuzzy logic is capable of identifying with precision different types of faults, which have similar half spectrum. The methodology has a great potential to be implemented in predictive maintenance programs in industries and may be expanded to include the identification of other types of faults not covered in the case study under analysis.

  10. Combining principles of Cognitive Load Theory and diagnostic error analysis for designing job aids: Effects on motivation and diagnostic performance in a process control task.

    Science.gov (United States)

    Kluge, Annette; Grauel, Britta; Burkolter, Dina

    2013-03-01

    Two studies are presented in which the design of a procedural aid and the impact of an additional decision aid for process control were assessed. In Study 1, a procedural aid was developed that avoids imposing unnecessary extraneous cognitive load on novices when controlling a complex technical system. This newly designed procedural aid positively affected germane load, attention, satisfaction, motivation, knowledge acquisition and diagnostic speed for novel faults. In Study 2, the effect of a decision aid for use before the procedural aid was investigated, which was developed based on an analysis of diagnostic errors committed in Study 1. Results showed that novices were able to diagnose both novel faults and practised faults, and were even faster at diagnosing novel faults. This research contributes to the question of how to optimally support novices in dealing with technical faults in process control. Copyright © 2012 Elsevier Ltd and The Ergonomics Society. All rights reserved.

  11. Modeling of HVAC operational faults in building performance simulation

    International Nuclear Information System (INIS)

    Zhang, Rongpeng; Hong, Tianzhen

    2017-01-01

    Highlights: •Discuss significance of capturing operational faults in existing buildings. •Develop a novel feature in EnergyPlus to model operational faults of HVAC systems. •Compare three approaches to faults modeling using EnergyPlus. •A case study demonstrates the use of the fault-modeling feature. •Future developments of new faults are discussed. -- Abstract: Operational faults are common in the heating, ventilating, and air conditioning (HVAC) systems of existing buildings, leading to a decrease in energy efficiency and occupant comfort. Various fault detection and diagnostic methods have been developed to identify and analyze HVAC operational faults at the component or subsystem level. However, current methods lack a holistic approach to predicting the overall impacts of faults at the building level—an approach that adequately addresses the coupling between various operational components, the synchronized effect between simultaneous faults, and the dynamic nature of fault severity. This study introduces the novel development of a fault-modeling feature in EnergyPlus which fills in the knowledge gap left by previous studies. This paper presents the design and implementation of the new feature in EnergyPlus and discusses in detail the fault-modeling challenges faced. The new fault-modeling feature enables EnergyPlus to quantify the impacts of faults on building energy use and occupant comfort, thus supporting the decision making of timely fault corrections. Including actual building operational faults in energy models also improves the accuracy of the baseline model, which is critical in the measurement and verification of retrofit or commissioning projects. As an example, EnergyPlus version 8.6 was used to investigate the impacts of a number of typical operational faults in an office building across several U.S. climate zones. The results demonstrate that the faults have significant impacts on building energy performance as well as on occupant

  12. Sliding Mode Fault Tolerant Control with Adaptive Diagnosis for Aircraft Engines

    Science.gov (United States)

    Xiao, Lingfei; Du, Yanbin; Hu, Jixiang; Jiang, Bin

    2018-03-01

    In this paper, a novel sliding mode fault tolerant control method is presented for aircraft engine systems with uncertainties and disturbances on the basis of adaptive diagnostic observer. By taking both sensors faults and actuators faults into account, the general model of aircraft engine control systems which is subjected to uncertainties and disturbances, is considered. Then, the corresponding augmented dynamic model is established in order to facilitate the fault diagnosis and fault tolerant controller design. Next, a suitable detection observer is designed to detect the faults effectively. Through creating an adaptive diagnostic observer and based on sliding mode strategy, the sliding mode fault tolerant controller is constructed. Robust stabilization is discussed and the closed-loop system can be stabilized robustly. It is also proven that the adaptive diagnostic observer output errors and the estimations of faults converge to a set exponentially, and the converge rate greater than some value which can be adjusted by choosing designable parameters properly. The simulation on a twin-shaft aircraft engine verifies the applicability of the proposed fault tolerant control method.

  13. Simultaneous-Fault Diagnosis of Gearboxes Using Probabilistic Committee Machine

    Science.gov (United States)

    Zhong, Jian-Hua; Wong, Pak Kin; Yang, Zhi-Xin

    2016-01-01

    This study combines signal de-noising, feature extraction, two pairwise-coupled relevance vector machines (PCRVMs) and particle swarm optimization (PSO) for parameter optimization to form an intelligent diagnostic framework for gearbox fault detection. Firstly, the noises of sensor signals are de-noised by using the wavelet threshold method to lower the noise level. Then, the Hilbert-Huang transform (HHT) and energy pattern calculation are applied to extract the fault features from de-noised signals. After that, an eleven-dimension vector, which consists of the energies of nine intrinsic mode functions (IMFs), maximum value of HHT marginal spectrum and its corresponding frequency component, is obtained to represent the features of each gearbox fault. The two PCRVMs serve as two different fault detection committee members, and they are trained by using vibration and sound signals, respectively. The individual diagnostic result from each committee member is then combined by applying a new probabilistic ensemble method, which can improve the overall diagnostic accuracy and increase the number of detectable faults as compared to individual classifiers acting alone. The effectiveness of the proposed framework is experimentally verified by using test cases. The experimental results show the proposed framework is superior to existing single classifiers in terms of diagnostic accuracies for both single- and simultaneous-faults in the gearbox. PMID:26848665

  14. Development of methods for evaluating active faults

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    2012-08-15

    The HERP report for long-term evaluation of active faults and the NSC safety review guide with regard to geology and ground of site were published on Nov. 2010 and on Dec. 2010, respectively. With respect to those reports, our investigation is as follows; (1) For assessment of seismic hazard, we estimated seismic sources around NPPs based on information of tectonic geomorphology, earthquake distribution and subsurface geology. (2) For evaluation on the activity of blind fault, we calculated the slip rate on the 2008 Iwate-Miyagi Nairiku Earthquake fault, using information on late Quaternary fluvial terraces. (3) To evaluate the magnitude of earthquakes whose sources are difficult to identify, we proposed a new method for calculation of the seismogenic layer thickness. (4) To clarify the activities of active faults without superstratum, we carried out the color analysis of fault gouge and divided the activities into thousand of years and tens of thousands. (5) For improving chronology of sediments, we detected new widespread cryptotephras using mineral chemistry and developed late Quaternary cryptotephrostratigraphy around NPPs. (author)

  15. Development of monitoring and diagnostic methods for robots used in remediation of waste sites. 1997 annual progress report

    International Nuclear Information System (INIS)

    Tecza, J.

    1998-01-01

    'Safe and efficient clean up of hazardous and radioactive waste sites throughout the DOE complex will require extensive use of robots. This research effort focuses on developing Monitoring and Diagnostic (M and D) methods for robots that will provide early detection, isolation, and tracking of impending faults before they result in serious failure. The utility and effectiveness of applying M and D methods to hydraulic robots has never been proven. The present research program is utilizing seeded faults in a laboratory test rig that is representative of an existing hydraulically-powered remediation robot. This report summarizes activity conducted in the first 9 months of the project. The research team has analyzed the Rosie Mobile Worksystem as a representative hydraulic robot, developed a test rig for implanted fault testing, developed a test plan and agenda, and established methods for acquiring and analyzing the test data.'

  16. Comparative Study of Fault Diagnostic Methods in Voltage Source Inverter Fed Three Phase Induction Motor Drive

    Science.gov (United States)

    Dhumale, R. B.; Lokhande, S. D.

    2017-05-01

    Three phase Pulse Width Modulation inverter plays vital role in industrial applications. The performance of inverter demeans as several types of faults take place in it. The widely used switching devices in power electronics are Insulated Gate Bipolar Transistors (IGBTs) and Metal Oxide Field Effect Transistors (MOSFET). The IGBTs faults are broadly classified as base or collector open circuit fault, misfiring fault and short circuit fault. To develop consistency and performance of inverter, knowledge of fault mode is extremely important. This paper presents the comparative study of IGBTs fault diagnosis. Experimental set up is implemented for data acquisition under various faulty and healthy conditions. Recent methods are executed using MATLAB-Simulink and compared using key parameters like average accuracy, fault detection time, implementation efforts, threshold dependency, and detection parameter, resistivity against noise and load dependency.

  17. CRISP. Fault detection, analysis and diagnostics in high-DG distribution systems

    International Nuclear Information System (INIS)

    Fontela, M.; Bacha, S.; Hadsjaid, N.; Andrieu, C.; Raison, B.; Penkov, D.

    2004-04-01

    The fault in the electrotechnical meaning is defined in the document. The main part of faults in overhead lines are non permanent faults, what entails the network operator to maintain the existing techniques to clear as fast as possible these faults. When a permanent fault occurs the operator has to detect and to limit the risks as soon as possible. Different axes are followed: limitation of the fault current, clearing the faulted feeder, locating the fault by test and try under possible fault condition. So the fault detection, fault clearing and fault localization are important functions of an EPS (electric power systems) to allow secure and safe operation of the system. The function may be improved by means of a better use of ICT components in the future sharing conveniently the intelligence needed near the distributed devices and a defined centralized intelligence. This improvement becomes necessary in distribution EPS with a high introduction of DR (distributed resources). The transmission and sub-transmission protection systems are already installed in order to manage power flow in all directions, so the DR issue is less critical for this part of the power system in term of fault clearing and diagnosis. Nevertheless the massive introduction of RES involves another constraints to the transmission system which are the bottlenecks caused by important local and fast installed production as wind power plants. Dealing with the distribution power system, and facing a permanent fault, two main actions must be achieved: identify the faulted elementary EPS area quickly and allow the field crew to locate and to repair the fault as soon as possible. The introduction of DR in distribution EPS involves some changes in fault location methods or equipment. The different existing neutral grounding systems make it difficult the achievement of a general method relevant for any distribution EPS in Europe. Some solutions are studied in the CRISP project in order to improve the

  18. Fault Management Metrics

    Science.gov (United States)

    Johnson, Stephen B.; Ghoshal, Sudipto; Haste, Deepak; Moore, Craig

    2017-01-01

    This paper describes the theory and considerations in the application of metrics to measure the effectiveness of fault management. Fault management refers here to the operational aspect of system health management, and as such is considered as a meta-control loop that operates to preserve or maximize the system's ability to achieve its goals in the face of current or prospective failure. As a suite of control loops, the metrics to estimate and measure the effectiveness of fault management are similar to those of classical control loops in being divided into two major classes: state estimation, and state control. State estimation metrics can be classified into lower-level subdivisions for detection coverage, detection effectiveness, fault isolation and fault identification (diagnostics), and failure prognosis. State control metrics can be classified into response determination effectiveness and response effectiveness. These metrics are applied to each and every fault management control loop in the system, for each failure to which they apply, and probabilistically summed to determine the effectiveness of these fault management control loops to preserve the relevant system goals that they are intended to protect.

  19. Development Ground Fault Detecting System for D.C Voltage Line

    Energy Technology Data Exchange (ETDEWEB)

    Kim Taek Soo; Song Ung Il; Gwon, Young Dong; Lee Hyoung Kee [Korea Electric Power Research Institute, Taejon (Korea, Republic of)

    1996-12-31

    It is necessary to keep the security of reliability and to maximize the efficiency of maintenance by prompt detection of a D.C feeder ground fault point at the built ed or a building power plants. At present, the most of the power plants are set up the ground fault indicator lamp in the monitor room. If a ground fault occurs on DC voltage feeder, a current through the ground fault relay is adjusted and the lamps have brightened while the current flows the relay coil. In order to develop such a system, it is analyzed a D.C feeder ground circuit theoretically and studied a principles which can determine ground fault point or a polarity discrimination and a phase discrimination of the line. So, the developed system through this principles can compute a resistance ground fault current and a capacitive ground fault current. It shows that the system can defect a ground fault point or a bad insulated line by measuring a power plant D.C feeder insulation resistance at the un interruptible power status, and therefore the power plant could protect an unexpected service interruption . (author). 18 refs., figs.

  20. Diagnosis and fault-tolerant control

    CERN Document Server

    Blanke, Mogens; Lunze, Jan; Staroswiecki, Marcel

    2016-01-01

    Fault-tolerant control aims at a gradual shutdown response in automated systems when faults occur. It satisfies the industrial demand for enhanced availability and safety, in contrast to traditional reactions to faults, which bring about sudden shutdowns and loss of availability. The book presents effective model-based analysis and design methods for fault diagnosis and fault-tolerant control. Architectural and structural models are used to analyse the propagation of the fault through the process, to test the fault detectability and to find the redundancies in the process that can be used to ensure fault tolerance. It also introduces design methods suitable for diagnostic systems and fault-tolerant controllers for continuous processes that are described by analytical models of discrete-event systems represented by automata. The book is suitable for engineering students, engineers in industry and researchers who wish to get an overview of the variety of approaches to process diagnosis and fault-tolerant contro...

  1. Development of direct dating methods of fault gouges: Deep drilling into Nojima Fault, Japan

    Science.gov (United States)

    Miyawaki, M.; Uchida, J. I.; Satsukawa, T.

    2017-12-01

    It is crucial to develop a direct dating method of fault gouges for the assessment of recent fault activity in terms of site evaluation for nuclear power plants. This method would be useful in regions without Late Pleistocene overlying sediments. In order to estimate the age of the latest fault slip event, it is necessary to use fault gouges which have experienced high frictional heating sufficient for age resetting. It is said that frictional heating is higher in deeper depths, because frictional heating generated by fault movement is determined depending on the shear stress. Therefore, we should determine the reliable depth of age resetting, as it is likely that fault gouges from the ground surface have been dated to be older than the actual age of the latest fault movement due to incomplete resetting. In this project, we target the Nojima fault which triggered the 1995 Kobe earthquake in Japan. Samples are collected from various depths (300-1,500m) by trenching and drilling to investigate age resetting conditions and depth using several methods including electron spin resonance (ESR) and optical stimulated luminescence (OSL), which are applicable to ages later than the Late Pleistocene. The preliminary results by the ESR method show approx. 1.1 Ma1) at the ground surface and 0.15-0.28 Ma2) at 388 m depth, respectively. These results indicate that samples from deeper depths preserve a younger age. In contrast, the OSL method dated approx. 2,200 yr1) at the ground surface. Although further consideration is still needed as there is a large margin of error, this result indicates that the age resetting depth of OSL is relatively shallow due to the high thermosensitivity of OSL compare to ESR. In the future, we plan to carry out further investigation for dating fault gouges from various depths up to approx. 1,500 m to verify the use of these direct dating methods.1) Kyoto University, 2017. FY27 Commissioned for the disaster presentation on nuclear facilities (Drilling

  2. Development of the Global Earthquake Model’s neotectonic fault database

    Science.gov (United States)

    Christophersen, Annemarie; Litchfield, Nicola; Berryman, Kelvin; Thomas, Richard; Basili, Roberto; Wallace, Laura; Ries, William; Hayes, Gavin P.; Haller, Kathleen M.; Yoshioka, Toshikazu; Koehler, Richard D.; Clark, Dan; Wolfson-Schwehr, Monica; Boettcher, Margaret S.; Villamor, Pilar; Horspool, Nick; Ornthammarath, Teraphan; Zuñiga, Ramon; Langridge, Robert M.; Stirling, Mark W.; Goded, Tatiana; Costa, Carlos; Yeats, Robert

    2015-01-01

    The Global Earthquake Model (GEM) aims to develop uniform, openly available, standards, datasets and tools for worldwide seismic risk assessment through global collaboration, transparent communication and adapting state-of-the-art science. GEM Faulted Earth (GFE) is one of GEM’s global hazard module projects. This paper describes GFE’s development of a modern neotectonic fault database and a unique graphical interface for the compilation of new fault data. A key design principle is that of an electronic field notebook for capturing observations a geologist would make about a fault. The database is designed to accommodate abundant as well as sparse fault observations. It features two layers, one for capturing neotectonic faults and fold observations, and the other to calculate potential earthquake fault sources from the observations. In order to test the flexibility of the database structure and to start a global compilation, five preexisting databases have been uploaded to the first layer and two to the second. In addition, the GFE project has characterised the world’s approximately 55,000 km of subduction interfaces in a globally consistent manner as a basis for generating earthquake event sets for inclusion in earthquake hazard and risk modelling. Following the subduction interface fault schema and including the trace attributes of the GFE database schema, the 2500-km-long frontal thrust fault system of the Himalaya has also been characterised. We propose the database structure to be used widely, so that neotectonic fault data can make a more complete and beneficial contribution to seismic hazard and risk characterisation globally.

  3. A dynamic integrated fault diagnosis method for power transformers.

    Science.gov (United States)

    Gao, Wensheng; Bai, Cuifen; Liu, Tong

    2015-01-01

    In order to diagnose transformer fault efficiently and accurately, a dynamic integrated fault diagnosis method based on Bayesian network is proposed in this paper. First, an integrated fault diagnosis model is established based on the causal relationship among abnormal working conditions, failure modes, and failure symptoms of transformers, aimed at obtaining the most possible failure mode. And then considering the evidence input into the diagnosis model is gradually acquired and the fault diagnosis process in reality is multistep, a dynamic fault diagnosis mechanism is proposed based on the integrated fault diagnosis model. Different from the existing one-step diagnosis mechanism, it includes a multistep evidence-selection process, which gives the most effective diagnostic test to be performed in next step. Therefore, it can reduce unnecessary diagnostic tests and improve the accuracy and efficiency of diagnosis. Finally, the dynamic integrated fault diagnosis method is applied to actual cases, and the validity of this method is verified.

  4. A Dynamic Integrated Fault Diagnosis Method for Power Transformers

    Science.gov (United States)

    Gao, Wensheng; Liu, Tong

    2015-01-01

    In order to diagnose transformer fault efficiently and accurately, a dynamic integrated fault diagnosis method based on Bayesian network is proposed in this paper. First, an integrated fault diagnosis model is established based on the causal relationship among abnormal working conditions, failure modes, and failure symptoms of transformers, aimed at obtaining the most possible failure mode. And then considering the evidence input into the diagnosis model is gradually acquired and the fault diagnosis process in reality is multistep, a dynamic fault diagnosis mechanism is proposed based on the integrated fault diagnosis model. Different from the existing one-step diagnosis mechanism, it includes a multistep evidence-selection process, which gives the most effective diagnostic test to be performed in next step. Therefore, it can reduce unnecessary diagnostic tests and improve the accuracy and efficiency of diagnosis. Finally, the dynamic integrated fault diagnosis method is applied to actual cases, and the validity of this method is verified. PMID:25685841

  5. Fault diagnosis of locomotive electro-pneumatic brake through uncertain bond graph modeling and robust online monitoring

    Science.gov (United States)

    Niu, Gang; Zhao, Yajun; Defoort, Michael; Pecht, Michael

    2015-01-01

    To improve reliability, safety and efficiency, advanced methods of fault detection and diagnosis become increasingly important for many technical fields, especially for safety related complex systems like aircraft, trains, automobiles, power plants and chemical plants. This paper presents a robust fault detection and diagnostic scheme for a multi-energy domain system that integrates a model-based strategy for system fault modeling and a data-driven approach for online anomaly monitoring. The developed scheme uses LFT (linear fractional transformations)-based bond graph for physical parameter uncertainty modeling and fault simulation, and employs AAKR (auto-associative kernel regression)-based empirical estimation followed by SPRT (sequential probability ratio test)-based threshold monitoring to improve the accuracy of fault detection. Moreover, pre- and post-denoising processes are applied to eliminate the cumulative influence of parameter uncertainty and measurement uncertainty. The scheme is demonstrated on the main unit of a locomotive electro-pneumatic brake in a simulated experiment. The results show robust fault detection and diagnostic performance.

  6. Physical Modeling for Anomaly Diagnostics and Prognostics, Phase II

    Data.gov (United States)

    National Aeronautics and Space Administration — Ridgetop developed an innovative, model-driven anomaly diagnostic and fault characterization system for electromechanical actuator (EMA) systems to mitigate...

  7. Diagnostic development

    International Nuclear Information System (INIS)

    Barnett, C.F.; Brisson, D.A.; Greco, S.E.

    1978-01-01

    During the past year the far-infrared or submillimeter diagnostic research program resulted in three major developments: (1) an optically pumped 0.385-μm D 2 O-laser oscillator-amplifier system was operated at a power level of 1 MW with a line width of less than 50 MHz; (2) a conical Pyrex submillimeter laser beam dump with a retention efficiency greater than 10 4 was developed for the ion temperature Thompson scattering experiment; and (3) a new diagnostic technique was developed that makes use of the Faraday rotation of a modulated submillimeter laser beam to determine plasma current profile. Measurements of the asymmetric distortion of the H/sub α/ (6563 A) spectral line profile show that the effective toroidal drift velocity, dv/sub two vertical bars i/dT/sub i/, may be used as an indicator of plasma quality and as a complement to other ion temperature diagnostics

  8. Vibration Feature Extraction and Analysis for Fault Diagnosis of Rotating Machinery-A Literature Survey

    Directory of Open Access Journals (Sweden)

    Saleem Riaz

    2017-02-01

    Full Text Available Safety, reliability, efficiency and performance of rotating machinery in all industrial applications are the main concerns. Rotating machines are widely used in various industrial applications. Condition monitoring and fault diagnosis of rotating machinery faults are very important and often complex and labor-intensive. Feature extraction techniques play a vital role for a reliable, effective and efficient feature extraction for the diagnosis of rotating machinery. Therefore, developing effective bearing fault diagnostic method using different fault features at different steps becomes more attractive. Bearings are widely used in medical applications, food processing industries, semi-conductor industries, paper making industries and aircraft components. This paper review has demonstrated that the latest reviews applied to rotating machinery on the available a variety of vibration feature extraction. Generally literature is classified into two main groups: frequency domain, time frequency analysis. However, fault detection and diagnosis of rotating machine vibration signal processing methods to present their own limitations. In practice, most healthy ingredients faulty vibration signal from background noise and mechanical vibration signals are buried. This paper also reviews that how the advanced signal processing methods, empirical mode decomposition and interference cancellation algorithm has been investigated and developed. The condition for rotating machines based rehabilitation, prevent failures increase the availability and reduce the cost of maintenance is becoming necessary too. Rotating machine fault detection and diagnostics in developing algorithms signal processing based on a key problem is the fault feature extraction or quantification. Currently, vibration signal, fault detection and diagnosis of rotating machinery based techniques most widely used techniques. Furthermore, the researchers are widely interested to make automatic

  9. Vibrational methods of the overhead gas-pipelines technological equipment diagnostics

    International Nuclear Information System (INIS)

    Zakhezin, A.M.; Malysheva, T.V.

    2001-01-01

    The diagnostic methods of overhead gas-pipelines of the technical equipment of gas-compressor station are considered in this article by carrying out registration certification documentation. Some faults of overhead technical gas-pipelines have been proposed. This paper is devoted to the diagnostic methods of the whole gas- pipelines and their parts for some faults during expert checking fulfillment and carrying out registration certification documentation. The analysis of all defects allows to determine a 'between-repairs interval', to develop some operations to avoid these faults and to estimate the repair operation quality, to reduce failure probability. As an example of the effectiveness of technical condition service of vibrational methods by expertise fulfillment have been considered for some defects of the overhead pipelines. (author)

  10. FaultBuster: data driven fault detection and diagnosis for industrial systems

    DEFF Research Database (Denmark)

    Bergantino, Nicola; Caponetti, Fabio; Longhi, Sauro

    2009-01-01

    . Multivariate statistical models based on principal components are used to detect abnormal situations. Tailored to alarms, a probabilistic inference engine process the fault evidences to output the most probable diagnosis. Results from the DX 09 Diagnostic Challenge shown strong detection properties, while...

  11. Unsupervised Fault Diagnosis of a Gear Transmission Chain Using a Deep Belief Network

    Directory of Open Access Journals (Sweden)

    Jun He

    2017-07-01

    Full Text Available Artificial intelligence (AI techniques, which can effectively analyze massive amounts of fault data and automatically provide accurate diagnosis results, have been widely applied to fault diagnosis of rotating machinery. Conventional AI methods are applied using features selected by a human operator, which are manually extracted based on diagnostic techniques and field expertise. However, developing robust features for each diagnostic purpose is often labour-intensive and time-consuming, and the features extracted for one specific task may be unsuitable for others. In this paper, a novel AI method based on a deep belief network (DBN is proposed for the unsupervised fault diagnosis of a gear transmission chain, and the genetic algorithm is used to optimize the structural parameters of the network. Compared to the conventional AI methods, the proposed method can adaptively exploit robust features related to the faults by unsupervised feature learning, thus requires less prior knowledge about signal processing techniques and diagnostic expertise. Besides, it is more powerful at modelling complex structured data. The effectiveness of the proposed method is validated using datasets from rolling bearings and gearbox. To show the superiority of the proposed method, its performance is compared with two well-known classifiers, i.e., back propagation neural network (BPNN and support vector machine (SVM. The fault classification accuracies are 99.26% for rolling bearings and 100% for gearbox when using the proposed method, which are much higher than that of the other two methods.

  12. Unsupervised Fault Diagnosis of a Gear Transmission Chain Using a Deep Belief Network.

    Science.gov (United States)

    He, Jun; Yang, Shixi; Gan, Chunbiao

    2017-07-04

    Artificial intelligence (AI) techniques, which can effectively analyze massive amounts of fault data and automatically provide accurate diagnosis results, have been widely applied to fault diagnosis of rotating machinery. Conventional AI methods are applied using features selected by a human operator, which are manually extracted based on diagnostic techniques and field expertise. However, developing robust features for each diagnostic purpose is often labour-intensive and time-consuming, and the features extracted for one specific task may be unsuitable for others. In this paper, a novel AI method based on a deep belief network (DBN) is proposed for the unsupervised fault diagnosis of a gear transmission chain, and the genetic algorithm is used to optimize the structural parameters of the network. Compared to the conventional AI methods, the proposed method can adaptively exploit robust features related to the faults by unsupervised feature learning, thus requires less prior knowledge about signal processing techniques and diagnostic expertise. Besides, it is more powerful at modelling complex structured data. The effectiveness of the proposed method is validated using datasets from rolling bearings and gearbox. To show the superiority of the proposed method, its performance is compared with two well-known classifiers, i.e., back propagation neural network (BPNN) and support vector machine (SVM). The fault classification accuracies are 99.26% for rolling bearings and 100% for gearbox when using the proposed method, which are much higher than that of the other two methods.

  13. Knowledge acquisition for nuclear power plant unit diagnostic system

    International Nuclear Information System (INIS)

    Li Xiaodong; Xi Shuren

    2003-01-01

    The process of acquiring knowledge and building a knowledge base is critical to realize fault diagnostic system at unit level in a nuclear power plant. It directly determines whether the diagnostic system can be applied eventually in a commercial plant. A means to acquire knowledge and its procedures was presented in this paper for fault diagnostic system in a nuclear power plant. The work can be carried out step by step and it is feasible in a commercial nuclear power plant. The knowledge base of the fault diagnostic system for a nuclear power plant can be built after the staff finish the tasks according to the framework presented in this paper

  14. Distributed bearing fault diagnosis based on vibration analysis

    Science.gov (United States)

    Dolenc, Boštjan; Boškoski, Pavle; Juričić, Đani

    2016-01-01

    Distributed bearing faults appear under various circumstances, for example due to electroerosion or the progression of localized faults. Bearings with distributed faults tend to generate more complex vibration patterns than those with localized faults. Despite the frequent occurrence of such faults, their diagnosis has attracted limited attention. This paper examines a method for the diagnosis of distributed bearing faults employing vibration analysis. The vibrational patterns generated are modeled by incorporating the geometrical imperfections of the bearing components. Comparing envelope spectra of vibration signals shows that one can distinguish between localized and distributed faults. Furthermore, a diagnostic procedure for the detection of distributed faults is proposed. This is evaluated on several bearings with naturally born distributed faults, which are compared with fault-free bearings and bearings with localized faults. It is shown experimentally that features extracted from vibrations in fault-free, localized and distributed fault conditions form clearly separable clusters, thus enabling diagnosis.

  15. Simultaneous-Fault Diagnosis of Gas Turbine Generator Systems Using a Pairwise-Coupled Probabilistic Classifier

    Directory of Open Access Journals (Sweden)

    Zhixin Yang

    2013-01-01

    Full Text Available A reliable fault diagnostic system for gas turbine generator system (GTGS, which is complicated and inherent with many types of component faults, is essential to avoid the interruption of electricity supply. However, the GTGS diagnosis faces challenges in terms of the existence of simultaneous-fault diagnosis and high cost in acquiring the exponentially increased simultaneous-fault vibration signals for constructing the diagnostic system. This research proposes a new diagnostic framework combining feature extraction, pairwise-coupled probabilistic classifier, and decision threshold optimization. The feature extraction module adopts wavelet packet transform and time-domain statistical features to extract vibration signal features. Kernel principal component analysis is then applied to further reduce the redundant features. The features of single faults in a simultaneous-fault pattern are extracted and then detected using a probabilistic classifier, namely, pairwise-coupled relevance vector machine, which is trained with single-fault patterns only. Therefore, the training dataset of simultaneous-fault patterns is unnecessary. To optimize the decision threshold, this research proposes to use grid search method which can ensure a global solution as compared with traditional computational intelligence techniques. Experimental results show that the proposed framework performs well for both single-fault and simultaneous-fault diagnosis and is superior to the frameworks without feature extraction and pairwise coupling.

  16. Decision table development and application to the construction of fault trees

    International Nuclear Information System (INIS)

    Salem, S.L.; Wu, J.S.; Apostolakis, G.

    1979-01-01

    A systematic methodology for the construction of fault trees based on the use of decision tables has been developed. These tables are used to describe each possible output state of a component as a set of combinations of states of inputs and internal operational or T states. Two methods for modeling component behavior via decision tables have been developed, one inductive and one deductive. These methods are useful for creating decision tables that realistically model the operational and failure modes of electrical, mechanical, and hydraulic components as well as human interactions inhibit conditions and common-cause events. A computer code CAT (Computer Automated Tree) has been developed to automatically produce fault trees from decision tables. A simple electrical system was chosen to illustrate the basic features of the decision table approach and to provide an example of an actual fault tree produced by this code. This example demonstrates the potential utility of such an automated approach to fault tree construction once a basic set of general decision tables has been developed

  17. A novel vibration-based fault diagnostic algorithm for gearboxes under speed fluctuations without rotational speed measurement

    Science.gov (United States)

    Hong, Liu; Qu, Yongzhi; Dhupia, Jaspreet Singh; Sheng, Shuangwen; Tan, Yuegang; Zhou, Zude

    2017-09-01

    The localized failures of gears introduce cyclic-transient impulses in the measured gearbox vibration signals. These impulses are usually identified from the sidebands around gear-mesh harmonics through the spectral analysis of cyclo-stationary signals. However, in practice, several high-powered applications of gearboxes like wind turbines are intrinsically characterized by nonstationary processes that blur the measured vibration spectra of a gearbox and deteriorate the efficacy of spectral diagnostic methods. Although order-tracking techniques have been proposed to improve the performance of spectral diagnosis for nonstationary signals measured in such applications, the required hardware for the measurement of rotational speed of these machines is often unavailable in industrial settings. Moreover, existing tacho-less order-tracking approaches are usually limited by the high time-frequency resolution requirement, which is a prerequisite for the precise estimation of the instantaneous frequency. To address such issues, a novel fault-signature enhancement algorithm is proposed that can alleviate the spectral smearing without the need of rotational speed measurement. This proposed tacho-less diagnostic technique resamples the measured acceleration signal of the gearbox based on the optimal warping path evaluated from the fast dynamic time-warping algorithm, which aligns a filtered shaft rotational harmonic signal with respect to a reference signal assuming a constant shaft rotational speed estimated from the approximation of operational speed. The effectiveness of this method is validated using both simulated signals from a fixed-axis gear pair under nonstationary conditions and experimental measurements from a 750-kW planetary wind turbine gearbox on a dynamometer test rig. The results demonstrate that the proposed algorithm can identify fault information from typical gearbox vibration measurements carried out in a resource-constrained industrial environment.

  18. Integrated control and diagnostic system architectures for future installations

    International Nuclear Information System (INIS)

    Wood, R.; March-Leuba, J.

    2000-01-01

    Nuclear reactors of the 21st century will employ increasing levels of automation and fault tolerance to increase availability, reduce accident risk, and lower operating costs. Key developments in control algorithms, fault diagnostics, fault tolerance, and distributed communications are needed to implement the fully automated plant. It will be equally challenging to integrate developments in separate information and control fields into a cohesive system, which collectively achieves the overall goals of improved safety, reliability, maintainability, and cost-effectiveness. Under the Nuclear Energy Research Initiative (NERI), the US Department of Energy is sponsoring a project to address some of the technical issues involved in meeting the long-range goal of 21st century reactor control systems. This project involves researchers from Oak Ridge National Laboratory, the University of Tennessee, and North Carolina State University. The research tasks under this project focus on some of the first-level breakthroughs in control design, diagnostic techniques, and information system design that will provide a path to enable the design process to be automated in the future. This paper describes the conceptual development of an integrated nuclear plant control and information system architecture, which incorporates automated control system development that can be traced to a set of technical requirements. The expectation is that an integrated plant architecture with optimal control and efficient use of diagnostic information can reduce the potential for operational errors and minimize challenges to the plant safety systems

  19. Surveillance and diagnostics in NPPs - progress made, operational needs, and perspective for future developments

    International Nuclear Information System (INIS)

    Wach, D.

    1996-01-01

    After a brief description of the broad and comprehensive knowledge base in incipient failure detection and on-line diagnostics at Institut fuer Sicherheitstechnologie ISTec, the international situation is reflected, and the operational needs as known from all the regular services of ISTec are discussed. ISTec has been involved in signal analyses, diagnosis support, and surveillance services. Long-term trending of signatures and features are performed, signature data banks with reference and fault-effected signatures were built up, a diagnosis center with advanced support tools has been established. The emphasis is placed on the development necessary in future to cope with the operator's interests. Most of the recent R and D work, aimed at the implementation of new information processing tools and techniques, will need time to be accepted in practice (long-term perspectives). Therefore, the actions and developments described under short-term perspectives should be pushed in order to progress in on-line NPP early failure diagnostics. (author)

  20. Geometric analysis of alternative models of faulting at Yucca Mountain, Nevada

    International Nuclear Information System (INIS)

    Young, S.R.; Stirewalt, G.L.; Morris, A.P.

    1993-01-01

    Realistic cross section tectonic models must be retrodeformable to geologically reasonable pre-deformation states. Furthermore, it must be shown that geologic structures depicted on cross section tectonic models can have formed by kinematically viable deformation mechanisms. Simple shear (i.e., listric fault models) is consistent with extensional geologic structures and fault patterns described at Yucca Mountain, Nevada. Flexural slip models yield results similar to oblique simple shear mechanisms, although there is no strong geological evidence for flexural slip deformation. Slip-line deformation is shown to generate fault block geometrics that are a close approximation to observed fault block structures. However, slip-line deformation implies a degree of general ductility for which there is no direct geological evidence. Simple and hybrid 'domino' (i.e., planar fault) models do not adequately explain observed variations of fault block dip or the development of 'rollover' folds adjacent to major bounding faults. Overall tectonic extension may be underestimated because of syn-tectonic deposition (growth faulting) of the Tertiary pyroclastic rocks that comprise Yucca Mountain. A strong diagnostic test of the applicability of the domino model may be provided by improved knowledge of Tertiary volcanic stratigraphy

  1. Fault Diagnosis for Actuators in a Class of Nonlinear Systems Based on an Adaptive Fault Detection Observer

    Directory of Open Access Journals (Sweden)

    Runxia Guo

    2016-01-01

    Full Text Available The problem of actuators’ fault diagnosis is pursued for a class of nonlinear control systems that are affected by bounded measurement noise and external disturbances. A novel fault diagnosis algorithm has been proposed by combining the idea of adaptive control theory and the approach of fault detection observer. The asymptotical stability of the fault detection observer is guaranteed by setting the adaptive adjusting law of the unknown fault vector. A theoretically rigorous proof of asymptotical stability has been given. Under the condition that random measurement noise generated by the sensors of control systems and external disturbances exist simultaneously, the designed fault diagnosis algorithm is able to successfully give specific estimated values of state variables and failures rather than just giving a simple fault warning. Moreover, the proposed algorithm is very simple and concise and is easy to be applied to practical engineering. Numerical experiments are carried out to evaluate the performance of the fault diagnosis algorithm. Experimental results show that the proposed diagnostic strategy has a satisfactory estimation effect.

  2. Fault Detection And Diagnosis For Air Conditioners And Heat Pumps Based On Virtual Sensors

    OpenAIRE

    Kim, Woohyun

    2013-01-01

    The primary goal of this research is to develop and demonstrate an integrated, on-line performance monitoring and diagnostic system with low cost sensors for air conditioning and heat pump equipment. Automated fault detection and diagnostics (FDD) has the potential for improving energy efficiency along with reducing service costs and comfort complaints. To achieve this goal, virtual sensors with low cost measurements and simple models were developed to estimate quantities that would be expens...

  3. Detection of inter-turn faults in transformer winding using the capacitor discharge method

    Science.gov (United States)

    Michna, Michał; Wilk, Andrzej; Ziółko, Michał; Wołoszyk, Marek; Swędrowski, Leon; Szwangruber, Piotr

    2017-12-01

    The paper presents results of an analysis of inter-turn fault effects on the voltage and current waveforms of a capacitor discharge through transformer windings. The research was conducted in the frame of the Facility of Antiproton and Ion Research project which goal is to build a new international accelerator facility that utilizes superconducting magnets. For the sake of electrical quality assurance of the superconducting magnet circuits, a measurement and diagnostic system is currently under development at Gdansk University of Technology (GUT). Appropriate measurements and simulations of the special transformer system were performed to verify the proposed diagnostic method. In order to take into account the nonlinearity and hysteresis of the magnetic yoke, a novel mathematical model of the transformer was developed. A special test bench was constructed to emulate the inter-turn faults within transformer windings.

  4. Detection of inter-turn faults in transformer winding using the capacitor discharge method

    Directory of Open Access Journals (Sweden)

    Michna Michał

    2017-12-01

    Full Text Available The paper presents results of an analysis of inter-turn fault effects on the voltage and current waveforms of a capacitor discharge through transformer windings. The research was conducted in the frame of the Facility of Antiproton and Ion Research project which goal is to build a new international accelerator facility that utilizes superconducting magnets. For the sake of electrical quality assurance of the superconducting magnet circuits, a measurement and diagnostic system is currently under development at Gdansk University of Technology (GUT. Appropriate measurements and simulations of the special transformer system were performed to verify the proposed diagnostic method. In order to take into account the nonlinearity and hysteresis of the magnetic yoke, a novel mathematical model of the transformer was developed. A special test bench was constructed to emulate the inter-turn faults within transformer windings.

  5. Development of an Intelligent Car Engine Fault Troubleshooting ...

    African Journals Online (AJOL)

    Development of an Intelligent Car Engine Fault Troubleshooting System (CEFTS) ... and also provides a troubleshooting framework for other researchers to work on. Keywords: ... inference engine, knowledge acquisition, artificial intelligence.

  6. Process plant alarm diagnosis using synthesised fault tree knowledge

    International Nuclear Information System (INIS)

    Trenchard, A.J.

    1990-01-01

    The development of computer based tools, to assist process plant operators in their task of fault/alarm diagnosis, has received much attention over the last twenty five years. More recently, with the emergence of Artificial Intelligence (AI) technology, the research activity in this subject area has heightened. As a result, there are a great variety of fault diagnosis methodologies, using many different approaches to represent the fault propagation behaviour of process plant. These range in complexity from steady state quantitative models to more abstract definitions of the relationships between process alarms. Unfortunately, very few of the techniques have been tried and tested on process plant and even fewer have been judged to be commercial successes. One of the outstanding problems still remains the time and effort required to understand and model the fault propagation behaviour of each considered process. This thesis describes the development of an experimental knowledge based system (KBS) to diagnose process plant faults, as indicated by process variable alarms. In an attempt to minimise the modelling effort, the KBS has been designed to infer diagnoses using a fault tree representation of the process behaviour, generated using an existing fault tree synthesis package (FAULTFINDER). The process is described to FAULTFINDER as a configuration of unit models, derived from a standard model library or by tailoring existing models. The resultant alarm diagnosis methodology appears to work well for hard (non-rectifying) faults, but is likely to be less robust when attempting to diagnose intermittent faults and transient behaviour. The synthesised fault trees were found to contain the bulk of the information required for the diagnostic task, however, this needed to be augmented with extra information in certain circumstances. (author)

  7. Detecting and diagnosing SSME faults using an autoassociative neural network topology

    Science.gov (United States)

    Ali, M.; Dietz, W. E.; Kiech, E. L.

    1989-01-01

    An effort is underway at the University of Tennessee Space Institute to develop diagnostic expert system methodologies based on the analysis of patterns of behavior of physical mechanisms. In this approach, fault diagnosis is conceptualized as the mapping or association of patterns of sensor data to patterns representing fault conditions. Neural networks are being investigated as a means of storing and retrieving fault scenarios. Neural networks offer several powerful features in fault diagnosis, including (1) general pattern matching capabilities, (2) resistance to noisy input data, (3) the ability to be trained by example, and (4) the potential for implementation on parallel computer architectures. This paper presents (1) an autoassociative neural network topology, i.e. the network input and output is identical when properly trained, and hence learning is unsupervised; (2) the training regimen used; and (3) the response of the system to inputs representing both previously observed and unkown fault scenarios. The effects of noise on the integrity of the diagnosis are also evaluated.

  8. Cooperative research and development for artificial intelligence based reactor diagnostic system

    International Nuclear Information System (INIS)

    Reifman, J.; Wei, T.Y.C.; Abboud, R.G.; Chasensky, T.M.

    1994-01-01

    Artificial Intelligence (AI) techniques in the form of knowledge-based Expert Systems (ESs) have been proposed to provide on-line decision-making support for plant operators during both normal and emergency conditions. However, in spite of the great interest in these advanced techniques, their application in the diagnosis of large-scale processes has not yet reached its full potential because of limitations of the knowledge base. These limitations include problems with knowledge acquisition and the use of an event-oriented approach for process diagnosis. To investigate the capabilities of this two-level hierarchical knowledge structure, Commonwealth Research Corporation (CRC) and Argonne National Laboratory (ANL)are collaborating on a DOE-sponsored Cooperative Research and Development Agreement (CRADA) project to perform feasibility studies on the proposed diagnostic system. Investigations are being performed in the construction of a physics-based plant level process diagnostic ES and the characterization of component-level fault project is to develop a computer-based system using this Al approach to assist process plant operators during off-normal plant conditions. The proposed computer-based system will use T-H signals complemented by other non-T-H signals available in the data stream to provide the process operator with the component which most likely caused the observed process disturbance. To demonstrate the scale-up feasibility of the proposed diagnostic system it is being developed for use with the Chemical Volume Control System (CVCS) of a nuclear power plant. This is an ongoing multi-year project and the remainder of this paper presents a mid-term status report

  9. Neural network application to diesel generator diagnostics

    International Nuclear Information System (INIS)

    Logan, K.P.

    1990-01-01

    Diagnostic problems typically begin with the observation of some system behavior which is recognized as a deviation from the expected. The fundamental underlying process is one involving pattern matching cf observed symptoms to a set of compiled symptoms belonging to a fault-symptom mapping. Pattern recognition is often relied upon for initial fault detection and diagnosis. Parallel distributed processing (PDP) models employing neural network paradigms are known to be good pattern recognition devices. This paper describes the application of neural network processing techniques to the malfunction diagnosis of subsystems within a typical diesel generator configuration. Neural network models employing backpropagation learning were developed to correctly recognize fault conditions from the input diagnostic symptom patterns pertaining to various engine subsystems. The resulting network models proved to be excellent pattern recognizers for malfunction examples within the training set. The motivation for employing network models in lieu of a rule-based expert system, however, is related to the network's potential for generalizing malfunctions outside of the training set, as in the case of noisy or partial symptom patterns

  10. Fault Detection of Reciprocating Compressors using a Model from Principles Component Analysis of Vibrations

    International Nuclear Information System (INIS)

    Ahmed, M; Gu, F; Ball, A D

    2012-01-01

    Traditional vibration monitoring techniques have found it difficult to determine a set of effective diagnostic features due to the high complexity of the vibration signals originating from the many different impact sources and wide ranges of practical operating conditions. In this paper Principal Component Analysis (PCA) is used for selecting vibration feature and detecting different faults in a reciprocating compressor. Vibration datasets were collected from the compressor under baseline condition and five common faults: valve leakage, inter-cooler leakage, suction valve leakage, loose drive belt combined with intercooler leakage and belt loose drive belt combined with suction valve leakage. A model using five PCs has been developed using the baseline data sets and the presence of faults can be detected by comparing the T 2 and Q values from the features of fault vibration signals with corresponding thresholds developed from baseline data. However, the Q -statistic procedure produces a better detection as it can separate the five faults completely.

  11. Research and design of distributed intelligence fault diagnosis system in nuclear power plant

    International Nuclear Information System (INIS)

    Liu Yongkuo; Xie Chunli; Cheng Shouyu; Xia Hong

    2011-01-01

    In order to further reduce the misoperation after the faults occurring of nuclear power plant, according to the function distribution of nuclear power equipment and the distributed control features of digital instrument control system, a nuclear power plant distributed condition monitoring and fault diagnosis system was researched and designed. Based on decomposition-integrated diagnostic thinking, a fuzzy neural network and RBF neural network was presented to do the distributed local diagnosis and multi-source information fusion technology for the global integrated diagnosis. Simulation results show that the developed distributed status monitoring and fault diagnosis system can diagnose more typical accidents of PWR to provide effective diagnosis and operation information. (authors)

  12. Layered clustering multi-fault diagnosis for hydraulic piston pump

    Science.gov (United States)

    Du, Jun; Wang, Shaoping; Zhang, Haiyan

    2013-04-01

    Efficient diagnosis is very important for improving reliability and performance of aircraft hydraulic piston pump, and it is one of the key technologies in prognostic and health management system. In practice, due to harsh working environment and heavy working loads, multiple faults of an aircraft hydraulic pump may occur simultaneously after long time operations. However, most existing diagnosis methods can only distinguish pump faults that occur individually. Therefore, new method needs to be developed to realize effective diagnosis of simultaneous multiple faults on aircraft hydraulic pump. In this paper, a new method based on the layered clustering algorithm is proposed to diagnose multiple faults of an aircraft hydraulic pump that occur simultaneously. The intensive failure mechanism analyses of the five main types of faults are carried out, and based on these analyses the optimal combination and layout of diagnostic sensors is attained. The three layered diagnosis reasoning engine is designed according to the faults' risk priority number and the characteristics of different fault feature extraction methods. The most serious failures are first distinguished with the individual signal processing. To the desultory faults, i.e., swash plate eccentricity and incremental clearance increases between piston and slipper, the clustering diagnosis algorithm based on the statistical average relative power difference (ARPD) is proposed. By effectively enhancing the fault features of these two faults, the ARPDs calculated from vibration signals are employed to complete the hypothesis testing. The ARPDs of the different faults follow different probability distributions. Compared with the classical fast Fourier transform-based spectrum diagnosis method, the experimental results demonstrate that the proposed algorithm can diagnose the multiple faults, which occur synchronously, with higher precision and reliability.

  13. Development and Evaluation of Fault-Tolerant Flight Control Systems

    Science.gov (United States)

    Song, Yong D.; Gupta, Kajal (Technical Monitor)

    2004-01-01

    The research is concerned with developing a new approach to enhancing fault tolerance of flight control systems. The original motivation for fault-tolerant control comes from the need for safe operation of control elements (e.g. actuators) in the event of hardware failures in high reliability systems. One such example is modem space vehicle subjected to actuator/sensor impairments. A major task in flight control is to revise the control policy to balance impairment detectability and to achieve sufficient robustness. This involves careful selection of types and parameters of the controllers and the impairment detecting filters used. It also involves a decision, upon the identification of some failures, on whether and how a control reconfiguration should take place in order to maintain a certain system performance level. In this project new flight dynamic model under uncertain flight conditions is considered, in which the effects of both ramp and jump faults are reflected. Stabilization algorithms based on neural network and adaptive method are derived. The control algorithms are shown to be effective in dealing with uncertain dynamics due to external disturbances and unpredictable faults. The overall strategy is easy to set up and the computation involved is much less as compared with other strategies. Computer simulation software is developed. A serious of simulation studies have been conducted with varying flight conditions.

  14. A fuzzy logic intelligent diagnostic system for spacecraft integrated vehicle health management

    Science.gov (United States)

    Wu, G. Gordon

    1995-01-01

    Due to the complexity of future space missions and the large amount of data involved, greater autonomy in data processing is demanded for mission operations, training, and vehicle health management. In this paper, we develop a fuzzy logic intelligent diagnostic system to perform data reduction, data analysis, and fault diagnosis for spacecraft vehicle health management applications. The diagnostic system contains a data filter and an inference engine. The data filter is designed to intelligently select only the necessary data for analysis, while the inference engine is designed for failure detection, warning, and decision on corrective actions using fuzzy logic synthesis. Due to its adaptive nature and on-line learning ability, the diagnostic system is capable of dealing with environmental noise, uncertainties, conflict information, and sensor faults.

  15. An Effective Fault Feature Extraction Method for Gas Turbine Generator System Diagnosis

    Directory of Open Access Journals (Sweden)

    Jian-Hua Zhong

    2016-01-01

    Full Text Available Fault diagnosis is very important to maintain the operation of a gas turbine generator system (GTGS in power plants, where any abnormal situations will interrupt the electricity supply. The fault diagnosis of the GTGS faces the main challenge that the acquired data, vibration or sound signals, contain a great deal of redundant information which extends the fault identification time and degrades the diagnostic accuracy. To improve the diagnostic performance in the GTGS, an effective fault feature extraction framework is proposed to solve the problem of the signal disorder and redundant information in the acquired signal. The proposed framework combines feature extraction with a general machine learning method, support vector machine (SVM, to implement an intelligent fault diagnosis. The feature extraction method adopts wavelet packet transform and time-domain statistical features to extract the features of faults from the vibration signal. To further reduce the redundant information in extracted features, kernel principal component analysis is applied in this study. Experimental results indicate that the proposed feature extracted technique is an effective method to extract the useful features of faults, resulting in improvement of the performance of fault diagnosis for the GTGS.

  16. Diagnostic Development on NSTX

    International Nuclear Information System (INIS)

    A.L. Roquemore; D. Johnson; R. Kaita; et al

    1999-01-01

    Diagnostics are described which are currently installed or under active development for the newly commissioned NSTX device. The low aspect ratio (R/a less than or equal to 1.3) and low toroidal field (0.1-0.3T) used in this device dictate adaptations in many standard diagnostic techniques. Technical summaries of each diagnostic are given, and adaptations, where significant, are highlighted

  17. A System for Fault Management and Fault Consequences Analysis for NASA's Deep Space Habitat

    Science.gov (United States)

    Colombano, Silvano; Spirkovska, Liljana; Baskaran, Vijaykumar; Aaseng, Gordon; McCann, Robert S.; Ossenfort, John; Smith, Irene; Iverson, David L.; Schwabacher, Mark

    2013-01-01

    NASA's exploration program envisions the utilization of a Deep Space Habitat (DSH) for human exploration of the space environment in the vicinity of Mars and/or asteroids. Communication latencies with ground control of as long as 20+ minutes make it imperative that DSH operations be highly autonomous, as any telemetry-based detection of a systems problem on Earth could well occur too late to assist the crew with the problem. A DSH-based development program has been initiated to develop and test the automation technologies necessary to support highly autonomous DSH operations. One such technology is a fault management tool to support performance monitoring of vehicle systems operations and to assist with real-time decision making in connection with operational anomalies and failures. Toward that end, we are developing Advanced Caution and Warning System (ACAWS), a tool that combines dynamic and interactive graphical representations of spacecraft systems, systems modeling, automated diagnostic analysis and root cause identification, system and mission impact assessment, and mitigation procedure identification to help spacecraft operators (both flight controllers and crew) understand and respond to anomalies more effectively. In this paper, we describe four major architecture elements of ACAWS: Anomaly Detection, Fault Isolation, System Effects Analysis, and Graphic User Interface (GUI), and how these elements work in concert with each other and with other tools to provide fault management support to both the controllers and crew. We then describe recent evaluations and tests of ACAWS on the DSH testbed. The results of these tests support the feasibility and strength of our approach to failure management automation and enhanced operational autonomy

  18. Intelligent systems in technical and medical diagnostics

    CERN Document Server

    Korbicz, Jozef

    2013-01-01

    For many years technical and medical diagnostics has been the area of intensive scientific research. It covers well-established topics as well as emerging developments in control engineering, artificial intelligence, applied mathematics, pattern recognition and statistics. At the same time, a growing number of applications of different fault diagnosis methods, especially in electrical, mechanical, chemical and medical engineering, is being observed. This monograph contains a collection of 44 carefully selected papers contributed by experts in technical and medical diagnostics, and constitutes

  19. A novelty detection diagnostic methodology for gearboxes operating under fluctuating operating conditions using probabilistic techniques

    Science.gov (United States)

    Schmidt, S.; Heyns, P. S.; de Villiers, J. P.

    2018-02-01

    In this paper, a fault diagnostic methodology is developed which is able to detect, locate and trend gear faults under fluctuating operating conditions when only vibration data from a single transducer, measured on a healthy gearbox are available. A two-phase feature extraction and modelling process is proposed to infer the operating condition and based on the operating condition, to detect changes in the machine condition. Information from optimised machine and operating condition hidden Markov models are statistically combined to generate a discrepancy signal which is post-processed to infer the condition of the gearbox. The discrepancy signal is processed and combined with statistical methods for automatic fault detection and localisation and to perform fault trending over time. The proposed methodology is validated on experimental data and a tacholess order tracking methodology is used to enhance the cost-effectiveness of the diagnostic methodology.

  20. Observer-based FDI for Gain Fault Detection in Ship Propulsion Benchmark

    DEFF Research Database (Denmark)

    Lootsma, T.F.; Izadi-Zamanabadi, Roozbeh; Nijmeijer, H.

    2001-01-01

    A geometric approach for input-affine nonlinear systems is briefly described and then applied to a ship propulsion benchmark. The obtained results are used to design a diagnostic nonlinear observer for successful FDI of the diesel engine gain fault......A geometric approach for input-affine nonlinear systems is briefly described and then applied to a ship propulsion benchmark. The obtained results are used to design a diagnostic nonlinear observer for successful FDI of the diesel engine gain fault...

  1. Observer-based FDI for Gain Fault Detection in Ship Propulsion Benchmark

    DEFF Research Database (Denmark)

    Lootsma, T.F.; Izadi-Zamanabadi, Roozbeh; Nijmeijer, H.

    2001-01-01

    A geometric approach for input-affine nonlinear systems is briefly described and then applied to a ship propulsion benchmark. The obtained results are used to design a diagnostic nonlinear observer for successful FDI of the diesel engine gain fault.......A geometric approach for input-affine nonlinear systems is briefly described and then applied to a ship propulsion benchmark. The obtained results are used to design a diagnostic nonlinear observer for successful FDI of the diesel engine gain fault....

  2. Fault Diagnosis of Power Systems Using Intelligent Systems

    Science.gov (United States)

    Momoh, James A.; Oliver, Walter E. , Jr.

    1996-01-01

    The power system operator's need for a reliable power delivery system calls for a real-time or near-real-time Al-based fault diagnosis tool. Such a tool will allow NASA ground controllers to re-establish a normal or near-normal degraded operating state of the EPS (a DC power system) for Space Station Alpha by isolating the faulted branches and loads of the system. And after isolation, re-energizing those branches and loads that have been found not to have any faults in them. A proposed solution involves using the Fault Diagnosis Intelligent System (FDIS) to perform near-real time fault diagnosis of Alpha's EPS by downloading power transient telemetry at fault-time from onboard data loggers. The FDIS uses an ANN clustering algorithm augmented with a wavelet transform feature extractor. This combination enables this system to perform pattern recognition of the power transient signatures to diagnose the fault type and its location down to the orbital replaceable unit. FDIS has been tested using a simulation of the LeRC Testbed Space Station Freedom configuration including the topology from the DDCU's to the electrical loads attached to the TPDU's. FDIS will work in conjunction with the Power Management Load Scheduler to determine what the state of the system was at the time of the fault condition. This information is used to activate the appropriate diagnostic section, and to refine if necessary the solution obtained. In the latter case, if the FDIS reports back that it is equally likely that the faulty device as 'start tracker #1' and 'time generation unit,' then based on a priori knowledge of the system's state, the refined solution would be 'star tracker #1' located in cabinet ITAS2. It is concluded from the present studies that artificial intelligence diagnostic abilities are improved with the addition of the wavelet transform, and that when such a system such as FDIS is coupled to the Power Management Load Scheduler, a faulty device can be located and isolated

  3. Feature Selection and Fault Classification of Reciprocating Compressors using a Genetic Algorithm and a Probabilistic Neural Network

    Energy Technology Data Exchange (ETDEWEB)

    Ahmed, M; Gu, F; Ball, A, E-mail: M.Ahmed@hud.ac.uk [Diagnostic Engineering Research Group, University of Huddersfield, HD1 3DH (United Kingdom)

    2011-07-19

    Reciprocating compressors are widely used in industry for various purposes and faults occurring in them can degrade their performance, consume additional energy and even cause severe damage to the machine. Vibration monitoring techniques are often used for early fault detection and diagnosis, but it is difficult to prescribe a given set of effective diagnostic features because of the wide variety of operating conditions and the complexity of the vibration signals which originate from the many different vibrating and impact sources. This paper studies the use of genetic algorithms (GAs) and neural networks (NNs) to select effective diagnostic features for the fault diagnosis of a reciprocating compressor. A large number of common features are calculated from the time and frequency domains and envelope analysis. Applying GAs and NNs to these features found that envelope analysis has the most potential for differentiating three common faults: valve leakage, inter-cooler leakage and a loose drive belt. Simultaneously, the spread parameter of the probabilistic NN was also optimised. The selected subsets of features were examined based on vibration source characteristics. The approach developed and the trained NN are confirmed as possessing general characteristics for fault detection and diagnosis.

  4. Feature Selection and Fault Classification of Reciprocating Compressors using a Genetic Algorithm and a Probabilistic Neural Network

    International Nuclear Information System (INIS)

    Ahmed, M; Gu, F; Ball, A

    2011-01-01

    Reciprocating compressors are widely used in industry for various purposes and faults occurring in them can degrade their performance, consume additional energy and even cause severe damage to the machine. Vibration monitoring techniques are often used for early fault detection and diagnosis, but it is difficult to prescribe a given set of effective diagnostic features because of the wide variety of operating conditions and the complexity of the vibration signals which originate from the many different vibrating and impact sources. This paper studies the use of genetic algorithms (GAs) and neural networks (NNs) to select effective diagnostic features for the fault diagnosis of a reciprocating compressor. A large number of common features are calculated from the time and frequency domains and envelope analysis. Applying GAs and NNs to these features found that envelope analysis has the most potential for differentiating three common faults: valve leakage, inter-cooler leakage and a loose drive belt. Simultaneously, the spread parameter of the probabilistic NN was also optimised. The selected subsets of features were examined based on vibration source characteristics. The approach developed and the trained NN are confirmed as possessing general characteristics for fault detection and diagnosis.

  5. Recent diagnostic developments on LHD

    International Nuclear Information System (INIS)

    Sudo, S.; Nagayama, Y.; Peterson, B.J.

    2003-01-01

    Standard diagnostics for fundamental plasma parameters and for plasma physics are routinely utilized for daily operation and physics study in the large helical device (LHD) with high reliability. Diagnostics for steady state plasma are intensively developed, especially for T e , n e (YAG laser Thomson, CO 2 laser polarimeter), data acquisition in steady state, heat resistant probes. To clarify the plasma property of the helical structure, 2-D or 3-D diagnostics are intensively developed: Tangential cameras (Fast SX TV, Photon counting CCD, H α TV); Tomography (Tangential SX CCD, Bolometer); Imaging (Bolometer, ECE, Reflectometer). Divertor and edge physics are one of important key issues for steady state operation. Diagnostics for neutral flux (H α array, Zeeman spectroscopy) and n e (Fast scanning probe, Li beam probe, Pulsed radar reflectometer). In addition to these, advanced diagnostics are being intensively developed with national and international collaborations in LHD. (author)

  6. Development of JT-60 diagnostics system

    International Nuclear Information System (INIS)

    Suzuki, Yasuo

    1988-01-01

    The various kinds of plasma diagnostics have been developed and utilized in the JT-60 experiments. The features of JT-60 diagnostics system and the historical proceeding of the development are described in this paper. Taking account of the design consideration, JT-60 diagnostics system is sorted out into eight groups, which include six diagnostics systems, the data processing system and diagnostics supporting system. The all devices in the JT-60 diagnostics system were instrumented on schedule in the end of the fiscal year of 1985 and have contributed to JT-60 experiments. (author)

  7. Development of Hydrologic Characterization Technology of Fault Zones

    International Nuclear Information System (INIS)

    Karasaki, Kenzi; Onishi, Tiemi; Wu, Yu-Shu

    2008-01-01

    Through an extensive literature survey we find that there is very limited amount of work on fault zone hydrology, particularly in the field using borehole testing. The common elements of a fault include a core, and damage zones. The core usually acts as a barrier to the flow across it, whereas the damage zone controls the flow either parallel to the strike or dip of a fault. In most of cases the damage zone is the one that is controlling the flow in the fault zone and the surroundings. The permeability of damage zone is in the range of two to three orders of magnitude higher than the protolith. The fault core can have permeability up to seven orders of magnitude lower than the damage zone. The fault types (normal, reverse, and strike-slip) by themselves do not appear to be a clear classifier of the hydrology of fault zones. However, there still remains a possibility that other additional geologic attributes and scaling relationships can be used to predict or bracket the range of hydrologic behavior of fault zones. AMT (Audio frequency Magneto Telluric) and seismic reflection techniques are often used to locate faults. Geochemical signatures and temperature distributions are often used to identify flow domains and/or directions. ALSM (Airborne Laser Swath Mapping) or LIDAR (Light Detection and Ranging) method may prove to be a powerful tool for identifying lineaments in place of the traditional photogrammetry. Nonetheless not much work has been done to characterize the hydrologic properties of faults by directly testing them using pump tests. There are some uncertainties involved in analyzing pressure transients of pump tests: both low permeability and high permeability faults exhibit similar pressure responses. A physically based conceptual and numerical model is presented for simulating fluid and heat flow and solute transport through fractured fault zones using a multiple-continuum medium approach. Data from the Horonobe URL site are analyzed to demonstrate the

  8. Development of Hydrologic Characterization Technology of Fault Zones

    Energy Technology Data Exchange (ETDEWEB)

    Karasaki, Kenzi; Onishi, Tiemi; Wu, Yu-Shu

    2008-03-31

    Through an extensive literature survey we find that there is very limited amount of work on fault zone hydrology, particularly in the field using borehole testing. The common elements of a fault include a core, and damage zones. The core usually acts as a barrier to the flow across it, whereas the damage zone controls the flow either parallel to the strike or dip of a fault. In most of cases the damage zone isthe one that is controlling the flow in the fault zone and the surroundings. The permeability of damage zone is in the range of two to three orders of magnitude higher than the protolith. The fault core can have permeability up to seven orders of magnitude lower than the damage zone. The fault types (normal, reverse, and strike-slip) by themselves do not appear to be a clear classifier of the hydrology of fault zones. However, there still remains a possibility that other additional geologic attributes and scaling relationships can be used to predict or bracket the range of hydrologic behavior of fault zones. AMT (Audio frequency Magneto Telluric) and seismic reflection techniques are often used to locate faults. Geochemical signatures and temperature distributions are often used to identify flow domains and/or directions. ALSM (Airborne Laser Swath Mapping) or LIDAR (Light Detection and Ranging) method may prove to be a powerful tool for identifying lineaments in place of the traditional photogrammetry. Nonetheless not much work has been done to characterize the hydrologic properties of faults by directly testing them using pump tests. There are some uncertainties involved in analyzing pressure transients of pump tests: both low permeability and high permeability faults exhibit similar pressure responses. A physically based conceptual and numerical model is presented for simulating fluid and heat flow and solute transport through fractured fault zones using a multiple-continuum medium approach. Data from the Horonobe URL site are analyzed to demonstrate the

  9. Development of an accurate transmission line fault locator using the global positioning system satellites

    Science.gov (United States)

    Lee, Harry

    1994-01-01

    A highly accurate transmission line fault locator based on the traveling-wave principle was developed and successfully operated within B.C. Hydro. A transmission line fault produces a fast-risetime traveling wave at the fault point which propagates along the transmission line. This fault locator system consists of traveling wave detectors located at key substations which detect and time tag the leading edge of the fault-generated traveling wave as if passes through. A master station gathers the time-tagged information from the remote detectors and determines the location of the fault. Precise time is a key element to the success of this system. This fault locator system derives its timing from the Global Positioning System (GPS) satellites. System tests confirmed the accuracy of locating faults to within the design objective of +/-300 meters.

  10. Research on fault diagnosis with SDG method for nuclear power plant

    International Nuclear Information System (INIS)

    Liu Yongkuo; Liu Zhen; Wu Xiaotian

    2014-01-01

    Abstract: The diagnosis of the operational state of a nuclear power plant (NPP) plays an important role for the safety and reliability of NPP operation. In this paper, the qualitative method for fault diagnosis based on signed directed graph (SDG) was applied in a complex NPP system because the mathematical model of NPP is difficult to be built. The reactor coolant system (RCS) was taken as the diagnostic object, and the approach of building SDG model was presented and the SDG model of the RCS was built. Based on the SDG model, a fault diagnosis system of RCS was developed, and the steam generator tube rupture (SGTR) and rod ejection accidents were taken as example to analyze the process of diagnosis inference. The simulation results show that the method based on SDG can effectively diagnose the fault in RCS, and it can also provide good explanation for the fault propagation paths. Therefore, this method can help operators to make correct decisions. (authors)

  11. Aircraft Engine Sensor/Actuator/Component Fault Diagnosis Using a Bank of Kalman Filters

    Science.gov (United States)

    Kobayashi, Takahisa; Simon, Donald L. (Technical Monitor)

    2003-01-01

    In this report, a fault detection and isolation (FDI) system which utilizes a bank of Kalman filters is developed for aircraft engine sensor and actuator FDI in conjunction with the detection of component faults. This FDI approach uses multiple Kalman filters, each of which is designed based on a specific hypothesis for detecting a specific sensor or actuator fault. In the event that a fault does occur, all filters except the one using the correct hypothesis will produce large estimation errors, from which a specific fault is isolated. In the meantime, a set of parameters that indicate engine component performance is estimated for the detection of abrupt degradation. The performance of the FDI system is evaluated against a nonlinear engine simulation for various engine faults at cruise operating conditions. In order to mimic the real engine environment, the nonlinear simulation is executed not only at the nominal, or healthy, condition but also at aged conditions. When the FDI system designed at the healthy condition is applied to an aged engine, the effectiveness of the FDI system is impacted by the mismatch in the engine health condition. Depending on its severity, this mismatch can cause the FDI system to generate incorrect diagnostic results, such as false alarms and missed detections. To partially recover the nominal performance, two approaches, which incorporate information regarding the engine s aging condition in the FDI system, will be discussed and evaluated. The results indicate that the proposed FDI system is promising for reliable diagnostics of aircraft engines.

  12. Power System Transient Diagnostics Based on Novel Traveling Wave Detection

    Science.gov (United States)

    Hamidi, Reza Jalilzadeh

    Modern electrical power systems demand novel diagnostic approaches to enhancing the system resiliency by improving the state-of-the-art algorithms. The proliferation of high-voltage optical transducers and high time-resolution measurements provide opportunities to develop novel diagnostic methods of very fast transients in power systems. At the same time, emerging complex configuration, such as multi-terminal hybrid transmission systems, limits the applications of the traditional diagnostic methods, especially in fault location and health monitoring. The impedance-based fault-location methods are inefficient for cross-bounded cables, which are widely used for connection of offshore wind farms to the main grid. Thus, this dissertation first presents a novel traveling wave-based fault-location method for hybrid multi-terminal transmission systems. The proposed method utilizes time-synchronized high-sampling voltage measurements. The traveling wave arrival times (ATs) are detected by observation of the squares of wavelet transformation coefficients. Using the ATs, an over-determined set of linear equations are developed for noise reduction, and consequently, the faulty segment is determined based on the characteristics of the provided equation set. Then, the fault location is estimated. The accuracy and capabilities of the proposed fault location method are evaluated and also compared to the existing traveling-wave-based method for a wide range of fault parameters. In order to improve power systems stability, auto-reclosing (AR), single-phase auto-reclosing (SPAR), and adaptive single-phase auto-reclosing (ASPAR) methods have been developed with the final objectives of distinguishing between the transient and permanent faults to clear the transient faults without de-energization of the solid phases. However, the features of the electrical arcs (transient faults) are severely influenced by a number of random parameters, including the convection of the air and plasma

  13. Development of expert system for fault diagnosis and restoration at substations

    Energy Technology Data Exchange (ETDEWEB)

    Choo, Jin Boo; Kwon, Tae Won; Yoon, Yong Beum; Park, Sung Taek [Korea Electric Power Corp. (KEPCO), Taejon (Korea, Republic of). Research Center; Park, Young Moon; Lee, Heung Jae [Electrical Engineering and Science Research Institute (Korea, Republic of)

    1996-12-31

    When a fault occurs in power systems, the operators have to make precise judgements on the situation and take appropriate actions rapidly to protect the system and minimize the black-out area. However, the larger and the more complex the power systems become, the more difficult it becomes to expect the effective actions of human operators. Therefore, it is a very important issue to support the operators of the local power systems in the case of various faults. We develop an expert system for fault diagnosis and reconfiguration of local power system. The expert system has a capability of identifying the location and the type of faults, the black-out area, and an appropriate reconfiguration procedure for re-energizing or minimizing the service interruption (author). 35 refs., 45 figs.

  14. Development of expert system for fault diagnosis and restoration at substations

    Energy Technology Data Exchange (ETDEWEB)

    Choo, Jin Boo; Kwon, Tae Won; Yoon, Yong Beum; Park, Sung Taek [Korea Electric Power Corp. (KEPCO), Taejon (Korea, Republic of). Research Center; Park, Young Moon; Lee, Heung Jae [Electrical Engineering and Science Research Institute (Korea, Republic of)

    1995-12-31

    When a fault occurs in power systems, the operators have to make precise judgements on the situation and take appropriate actions rapidly to protect the system and minimize the black-out area. However, the larger and the more complex the power systems become, the more difficult it becomes to expect the effective actions of human operators. Therefore, it is a very important issue to support the operators of the local power systems in the case of various faults. We develop an expert system for fault diagnosis and reconfiguration of local power system. The expert system has a capability of identifying the location and the type of faults, the black-out area, and an appropriate reconfiguration procedure for re-energizing or minimizing the service interruption (author). 35 refs., 45 figs.

  15. Vibration-based Fault Diagnostic of a Spur Gearbox

    Directory of Open Access Journals (Sweden)

    Hartono Dennis

    2016-01-01

    Full Text Available This paper presents comparative studies of Fast Fourier Transform (FFT, Short Time Fourier Transform (STFT and Continuous Wavelet Transform (CWT as several advanced time-frequency analysis methods for diagnosing an early stage of spur gear tooth failure. An incipient fault of a chipped tooth was investigated in this work using vibration measurements from a spur gearbox test rig. Time Synchronous Averaging was implemented for the analysis to enhance the clarity of fault feature from the gear of interest. Based on the experimental results and analysis, it was shown that FFT method could identify the location of the faulty gear with sufficient accuracy. On the other hand, Short Time Fourier Transform method could not provide the angular location information of the faulty gear. It was found that the Continuous Wavelet Transform method offered the best representation of angle-frequency representation. It was not only able to distinguish the difference between the normal and faulty gearboxes from the joint angle-frequency results but could also provide an accurate angular location of the faulty gear tooth in the gearbox.

  16. Role of seismogenic processes in fault-rock development: An example from Death Valley, California

    Science.gov (United States)

    Pavlis, Terry L.; Serpa, Laura F.; Keener, Charles

    1993-03-01

    Fault rocks developed along the Mormon Point turtleback of southern Death Valley suggest that a jog in the oblique-slip Death Valley fault zone served as an ancient seismic barrier, where dominantly strike-slip ruptures were terminated at a dilatant jog. Dramatic spatial variations in fault-rock thickness and type within the bend are interpreted as the products of: (1) fault "overshoot," in which planar ruptures bypass the intersection of the two faults composing the bend and slice into the underlying footwall; and (2) implosion brecciation, in which coseismic ruptures arrested at a releasing bend in the fault lead to catastrophic collapse brecciation, fluid influx, and mineralization.

  17. Intellectual property considerations for molecular diagnostic development with emphasis on companion diagnostics.

    Science.gov (United States)

    Glorikian, Harry; Warburg, Richard Jeremy; Moore, Kelly; Malinowski, Jennifer

    2018-02-01

    The development of molecular diagnostics is a complex endeavor, with multiple regulatory pathways to consider and numerous approaches to development and commercialization. Companion diagnostics, devices which are "essential for the safe and effective use of a corresponding drug or diagnostic product" (see U.S. Food & Drug Administration, In Vitro Diagnostics - Companion Diagnostics, U.S. Dept. of Health & Human Services(2016), available at https://www.fda.gov/medicaldevices/productsandmedicalprocedures/invitrodiagnostics/ucm407297.htm ) and complementary diagnostics, which are more broadly associated with a class of drug, are becoming increasingly important as integral components of the implementation of precision medicine. Areas covered: The following article will highlight the intellectual property ('IP') considerations pertinent to molecular diagnostics development with special emphasis on companion diagnostics. Expert opinion/commentary Summary: For all molecular diagnostics, intellectual property (IP) concerns are of paramount concern, whether the device will be marketed only in the United States or abroad. Taking steps to protect IP at each stage of product development is critical to optimize profitability of a diagnostic product. Also the legal framework around IP protection of diagnostic technologies has been changing over the previous few years and can be expected to continue to change in the foreseeable near future, thus, a comprehensive IP strategy should take into account the fact that changes in the law can be expected.

  18. Various Indices for Diagnosis of Air-gap Eccentricity Fault in Induction Motor-A Review

    Science.gov (United States)

    Nikhil; Mathew, Lini, Dr.; Sharma, Amandeep

    2018-03-01

    From the past few years, research has gained an ardent pace in the field of fault detection and diagnosis in induction motors. In the current scenario, software is being introduced with diagnostic features to improve stability and reliability in fault diagnostic techniques. Human involvement in decision making for fault detection is slowly being replaced by Artificial Intelligence techniques. In this paper, a brief introduction of eccentricity fault is presented along with their causes and effects on the health of induction motors. Various indices used to detect eccentricity are being introduced along with their boundary conditions and their future scope of research. At last, merits and demerits of all indices are discussed and a comparison is made between them.

  19. Combinatorial Optimization Algorithms for Dynamic Multiple Fault Diagnosis in Automotive and Aerospace Applications

    Science.gov (United States)

    Kodali, Anuradha

    facility, respectively. The set-covering matrix encapsulates the relationship among the rows (tests or demand points) and columns (faults or locations) of the system at each time. By relaxing the coupling constraints using Lagrange multipliers, the DSC problem can be decoupled into independent subproblems, one for each column. Each subproblem is solved using the Viterbi decoding algorithm, and a primal feasible solution is constructed by modifying the Viterbi solutions via a heuristic. The proposed Viterbi-Lagrangian relaxation algorithm (VLRA) provides a measure of suboptimality via an approximate duality gap. As a major practical extension of the above problem, we also consider the problem of diagnosing faults with delayed test outcomes, termed delay-dynamic set-covering (DDSC), and experiment with real-world problems that exhibit masking faults. Also, we present simulation results on OR-library datasets (set-covering formulations are predominantly validated on these matrices in the literature), posed as facility location problems. Finally, we implement these algorithms to solve problems in aerospace and automotive applications. Firstly, we address the diagnostic ambiguity problem in aerospace and automotive applications by developing a dynamic fusion framework that includes dynamic multiple fault diagnosis algorithms. This improves the correct fault isolation rate, while minimizing the false alarm rates, by considering multiple faults instead of the traditional data-driven techniques based on single fault (class)-single epoch (static) assumption. The dynamic fusion problem is formulated as a maximum a posteriori decision problem of inferring the fault sequence based on uncertain outcomes of multiple binary classifiers over time. The fusion process involves three steps: the first step transforms the multi-class problem into dichotomies using error correcting output codes (ECOC), thereby solving the concomitant binary classification problems; the second step fuses the

  20. Non deterministic finite automata for power systems fault diagnostics

    Directory of Open Access Journals (Sweden)

    LINDEN, R.

    2009-06-01

    Full Text Available This paper introduces an application based on finite non-deterministic automata for power systems diagnosis. Automata for the simpler faults are presented and the proposed system is compared with an established expert system.

  1. Case-based reasoning combined with statistics for diagnostics and prognosis

    International Nuclear Information System (INIS)

    Olsson, T; Funk, P

    2012-01-01

    Many approaches used for diagnostics today are based on a precise model. This excludes diagnostics of many complex types of machinery that cannot be modelled and simulated easily or without great effort. Our aim is to show that by including human experience it is possible to diagnose complex machinery when there is no or limited models or simulations available. This also enables diagnostics in a dynamic application where conditions change and new cases are often added. In fact every new solved case increases the diagnostic power of the system. We present a number of successful projects where we have used feature extraction together with case-based reasoning to diagnose faults in industrial robots, welding, cutting machinery and we also present our latest project for diagnosing transmissions by combining Case-Based Reasoning (CBR) with statistics. We view the fault diagnosis process as three consecutive steps. In the first step, sensor fault signals from machines and/or input from human operators are collected. Then, the second step consists of extracting relevant fault features. In the final diagnosis/prognosis step, status and faults are identified and classified. We view prognosis as a special case of diagnosis where the prognosis module predicts a stream of future features.

  2. Hybrid Model-Based and Data-Driven Fault Detection and Diagnostics for Commercial Buildings: Preprint

    Energy Technology Data Exchange (ETDEWEB)

    Frank, Stephen; Heaney, Michael; Jin, Xin; Robertson, Joseph; Cheung, Howard; Elmore, Ryan; Henze, Gregor

    2016-08-01

    Commercial buildings often experience faults that produce undesirable behavior in building systems. Building faults waste energy, decrease occupants' comfort, and increase operating costs. Automated fault detection and diagnosis (FDD) tools for buildings help building owners discover and identify the root causes of faults in building systems, equipment, and controls. Proper implementation of FDD has the potential to simultaneously improve comfort, reduce energy use, and narrow the gap between actual and optimal building performance. However, conventional rule-based FDD requires expensive instrumentation and valuable engineering labor, which limit deployment opportunities. This paper presents a hybrid, automated FDD approach that combines building energy models and statistical learning tools to detect and diagnose faults noninvasively, using minimal sensors, with little customization. We compare and contrast the performance of several hybrid FDD algorithms for a small security building. Our results indicate that the algorithms can detect and diagnose several common faults, but more work is required to reduce false positive rates and improve diagnosis accuracy.

  3. Fault Diagnosis of Nonlinear Systems Using Structured Augmented State Models

    Institute of Scientific and Technical Information of China (English)

    Jochen Aβfalg; Frank Allg(o)wer

    2007-01-01

    This paper presents an internal model approach for modeling and diagnostic functionality design for nonlinear systems operating subject to single- and multiple-faults. We therefore provide the framework of structured augmented state models. Fault characteristics are considered to be generated by dynamical exosystems that are switched via equality constraints to overcome the augmented state observability limiting the number of diagnosable faults. Based on the proposed model, the fault diagnosis problem is specified as an optimal hybrid augmented state estimation problem. Sub-optimal solutions are motivated and exemplified for the fault diagnosis of the well-known three-tank benchmark. As the considered class of fault diagnosis problems is large, the suggested approach is not only of theoretical interest but also of high practical relevance.

  4. Adapting plant measurement data to improve hardware fault detection performance in pressurised water reactors

    International Nuclear Information System (INIS)

    Cilliers, A.C.; Mulder, E.J.

    2012-01-01

    Highlights: ► Attempt was to use available resources at a nuclear plant in a value added fashion. ► Includes plant measurement data and plant training and engineering simulator capabilities. ► Solving the fault masking effect by the distributed control systems in the plant. ► Modelling the effect of inaccuracies in plant models used in the simulators. ► Combination of above resulted in the development of a deterministic fault identifications system. -- Abstract: With the fairly recent adoption of digital control and instrumentation systems in the nuclear industry a lot of research now focus on the development expert fault identification systems. The fault identification systems enable detecting early onset faults of fault causes which allows maintenance planning on the equipment showing signs of deterioration or failure. This includes valve and leaks and small cracks in steam generator tubes usually detected by means of ultrasonic inspection. Detecting faults early during transient operation in NPPs is problematic due to the absence of a reliable reference to compare plant measurements with during transients. The distributed application of control systems operating independently to keep the plant operating within the safe operating boundaries complicates the problem since the control systems would not only operate to reduce the effect of transient disturbances but fault disturbances as well. This paper provides a method to adapt the plant measurements that isolates the control actions on the fault and re-introduces it into the measurement data, thereby improving plant diagnostic performance.

  5. Fault diagnosis in spur gears based on genetic algorithm and random forest

    Science.gov (United States)

    Cerrada, Mariela; Zurita, Grover; Cabrera, Diego; Sánchez, René-Vinicio; Artés, Mariano; Li, Chuan

    2016-03-01

    There are growing demands for condition-based monitoring of gearboxes, and therefore new methods to improve the reliability, effectiveness, accuracy of the gear fault detection ought to be evaluated. Feature selection is still an important aspect in machine learning-based diagnosis in order to reach good performance of the diagnostic models. On the other hand, random forest classifiers are suitable models in industrial environments where large data-samples are not usually available for training such diagnostic models. The main aim of this research is to build up a robust system for the multi-class fault diagnosis in spur gears, by selecting the best set of condition parameters on time, frequency and time-frequency domains, which are extracted from vibration signals. The diagnostic system is performed by using genetic algorithms and a classifier based on random forest, in a supervised environment. The original set of condition parameters is reduced around 66% regarding the initial size by using genetic algorithms, and still get an acceptable classification precision over 97%. The approach is tested on real vibration signals by considering several fault classes, one of them being an incipient fault, under different running conditions of load and velocity.

  6. Development of Characterization Technology for Fault Zone Hydrology

    International Nuclear Information System (INIS)

    Karasaki, Kenzi; Onishi, Tiemi; Gasperikova, Erika; Goto, Junichi; Tsuchi, Hiroyuki; Miwa, Tadashi; Ueta, Keiichi; Kiho, Kenzo; Miyakawa, Kimio

    2010-01-01

    Several deep trenches were cut, and a number of geophysical surveys were conducted across the Wildcat Fault in the hills east of Berkeley, California. The Wildcat Fault is believed to be a strike-slip fault and a member of the Hayward Fault System, with over 10 km of displacement. So far, three boreholes of ∼ 150m deep have been core-drilled and borehole geophysical logs were conducted. The rocks are extensively sheared and fractured; gouges were observed at several depths and a thick cataclasitic zone was also observed. While confirming some earlier, published conclusions from shallow observations about Wildcat, some unexpected findings were encountered. Preliminary analysis indicates that Wildcat near the field site consists of multiple faults. The hydraulic test data suggest the dual properties of the hydrologic structure of the fault zone. A fourth borehole is planned to penetrate the main fault believed to lie in-between the holes. The main philosophy behind our approach for the hydrologic characterization of such a complex fractured system is to let the system take its own average and monitor a long term behavior instead of collecting a multitude of data at small length and time scales, or at a discrete fracture scale and to 'up-scale,' which is extremely tenuous.

  7. Fault-weighted quantification method of fault detection coverage through fault mode and effect analysis in digital I&C systems

    Energy Technology Data Exchange (ETDEWEB)

    Cho, Jaehyun; Lee, Seung Jun, E-mail: sjlee420@unist.ac.kr; Jung, Wondea

    2017-05-15

    Highlights: • We developed the fault-weighted quantification method of fault detection coverage. • The method has been applied to specific digital reactor protection system. • The unavailability of the module had 20-times difference with the traditional method. • Several experimental tests will be effectively prioritized using this method. - Abstract: The one of the most outstanding features of a digital I&C system is the use of a fault-tolerant technique. With an awareness regarding the importance of thequantification of fault detection coverage of fault-tolerant techniques, several researches related to the fault injection method were developed and employed to quantify a fault detection coverage. In the fault injection method, each injected fault has a different importance because the frequency of realization of every injected fault is different. However, there have been no previous studies addressing the importance and weighting factor of each injected fault. In this work, a new method for allocating the weighting to each injected fault using the failure mode and effect analysis data was proposed. For application, the fault-weighted quantification method has also been applied to specific digital reactor protection system to quantify the fault detection coverage. One of the major findings in an application was that we may estimate the unavailability of the specific module in digital I&C systems about 20-times smaller than real value when we use a traditional method. The other finding was that we can also classify the importance of the experimental case. Therefore, this method is expected to not only suggest an accurate quantification procedure of fault-detection coverage by weighting the injected faults, but to also contribute to an effective fault injection experiment by sorting the importance of the failure categories.

  8. Fault diagnosis and fault-tolerant control based on adaptive control approach

    CERN Document Server

    Shen, Qikun; Shi, Peng

    2017-01-01

    This book provides recent theoretical developments in and practical applications of fault diagnosis and fault tolerant control for complex dynamical systems, including uncertain systems, linear and nonlinear systems. Combining adaptive control technique with other control methodologies, it investigates the problems of fault diagnosis and fault tolerant control for uncertain dynamic systems with or without time delay. As such, the book provides readers a solid understanding of fault diagnosis and fault tolerant control based on adaptive control technology. Given its depth and breadth, it is well suited for undergraduate and graduate courses on linear system theory, nonlinear system theory, fault diagnosis and fault tolerant control techniques. Further, it can be used as a reference source for academic research on fault diagnosis and fault tolerant control, and for postgraduates in the field of control theory and engineering. .

  9. Failure characteristics analysis and fault diagnosis for liquid rocket engines

    CERN Document Server

    Zhang, Wei

    2016-01-01

    This book concentrates on the subject of health monitoring technology of Liquid Rocket Engine (LRE), including its failure analysis, fault diagnosis and fault prediction. Since no similar issue has been published, the failure pattern and mechanism analysis of the LRE from the system stage are of particular interest to the readers. Furthermore, application cases used to validate the efficacy of the fault diagnosis and prediction methods of the LRE are different from the others. The readers can learn the system stage modeling, analyzing and testing methods of the LRE system as well as corresponding fault diagnosis and prediction methods. This book will benefit researchers and students who are pursuing aerospace technology, fault detection, diagnostics and corresponding applications.

  10. In-operation diagnostic system for reactor coolant pump

    International Nuclear Information System (INIS)

    Sugiyama, Mitsunobu; Hasegawa, Ichiro; Kitahara, Hiromichi; Shimamura, Kazuo; Yasuda, Chiaki; Ikeda, Yasuhiro; Kida, Yasuo.

    1996-01-01

    A reactor coolant pump (RCP) is one of the most important rotating machines in the primary loop nuclear power plants. To improve the reliability and of nuclear power plants, a new diagnostic system that enables early detection of RCP faults has been developed. This system is based on continuous monitoring of vibration and other process data. Vibration is an important indicator of mechanical faults providing information on physical phenomena such as changes in dynamic characteristics and excitation forces changes that signal failure or incipient failure. This new system features comparative vibration analysis and simulation to anticipate equipment failure. (author)

  11. Health Monitoring for Condition-Based Maintenance of a HMMWV using an Instrumented Diagnostic Cleat

    Science.gov (United States)

    2008-10-15

    identify faults in the bearings, shaft , etc. In wheeled ground vehicles, loading varies significantly as mentioned above. If loads acting on the...vehicle could be fully measured or controlled in terms of the terrain input motions and/or spindle forces/moments, fault identification in wheeled...diagnostic results. - Vehicle speed traversing the cleat can be controlled. - Configuration of cleats can be designed to develop specific tests for

  12. Qualitative Event-Based Diagnosis: Case Study on the Second International Diagnostic Competition

    Science.gov (United States)

    Daigle, Matthew; Roychoudhury, Indranil

    2010-01-01

    We describe a diagnosis algorithm entered into the Second International Diagnostic Competition. We focus on the first diagnostic problem of the industrial track of the competition in which a diagnosis algorithm must detect, isolate, and identify faults in an electrical power distribution testbed and provide corresponding recovery recommendations. The diagnosis algorithm embodies a model-based approach, centered around qualitative event-based fault isolation. Faults produce deviations in measured values from model-predicted values. The sequence of these deviations is matched to those predicted by the model in order to isolate faults. We augment this approach with model-based fault identification, which determines fault parameters and helps to further isolate faults. We describe the diagnosis approach, provide diagnosis results from running the algorithm on provided example scenarios, and discuss the issues faced, and lessons learned, from implementing the approach

  13. IMPLEMENTATION OF TURNOUTS TECHNICAL DIAGNOSTICS SYSTEMS

    Directory of Open Access Journals (Sweden)

    S. YU. Buryak

    2015-06-01

    Full Text Available Purpose. In the paper it is necessary to: 1 find out the causes of turnouts faults to determine diagnostic features failures; 2 consider the requirements structure, purpose components of turnouts, work and technology of their maintenance to determine the construction of the economic activities related to system to the turnout’s maintenance; 3 substantiate the possibility, necessity and prospects of automated diagnostics turnout’s implementation; 4 elaborate a prototype of an automated hardware and software system for the turnouts control parameters and perform diagnostics on them. Methodology. In the paper possible turnouts faults were presented and manifestations and influence on its work were shown. According to the current technology works the process analyze of turnouts’ maintenance was conducted, were defined the basic performed operations during the examination of appearance, parameters and check the repair or replacement of parts and assemblies. Based on the analysis of reasons of turnouts malfunctioning and their fixes were systematized types of damages and ways to deal with them, an information scheme of troubleshooting were created, opportunities and limits of automating the process of diagnostics were identified and compared with the existing method of turnouts maintenance. A diagnostics system block diagram was created, an algorithm of its work was developed and established main basic principles of operation. Software and hardware to determine the turnout’s state considering diagnostic performance of points in use were applied. Findings. During the experiment was created a method of automated turnout’s diagnostics with AC electric drives, managed centrally. The results of automated hardware and software system make it possible to control turnout’s parameters and perform diagnostics on them. Originality. Authors created the method of turnout’s state determination by current curve and its spectral composition in the

  14. A Novel Data Hierarchical Fusion Method for Gas Turbine Engine Performance Fault Diagnosis

    Directory of Open Access Journals (Sweden)

    Feng Lu

    2016-10-01

    Full Text Available Gas path fault diagnosis involves the effective utilization of condition-based sensor signals along engine gas path to accurately identify engine performance failure. The rapid development of information processing technology has led to the use of multiple-source information fusion for fault diagnostics. Numerous efforts have been paid to develop data-based fusion methods, such as neural networks fusion, while little research has focused on fusion architecture or the fusion of different method kinds. In this paper, a data hierarchical fusion using improved weighted Dempster–Shaffer evidence theory (WDS is proposed, and the integration of data-based and model-based methods is presented for engine gas-path fault diagnosis. For the purpose of simplifying learning machine typology, a recursive reduced kernel based extreme learning machine (RR-KELM is developed to produce the fault probability, which is considered as the data-based evidence. Meanwhile, the model-based evidence is achieved using particle filter-fuzzy logic algorithm (PF-FL by engine health estimation and component fault location in feature level. The outputs of two evidences are integrated using WDS evidence theory in decision level to reach a final recognition decision of gas-path fault pattern. The characteristics and advantages of two evidences are analyzed and used as guidelines for data hierarchical fusion framework. Our goal is that the proposed methodology provides much better performance of gas-path fault diagnosis compared to solely relying on data-based or model-based method. The hierarchical fusion framework is evaluated in terms to fault diagnosis accuracy and robustness through a case study involving fault mode dataset of a turbofan engine that is generated by the general gas turbine simulation. These applications confirm the effectiveness and usefulness of the proposed approach.

  15. Bevel Gearbox Fault Diagnosis using Vibration Measurements

    Directory of Open Access Journals (Sweden)

    Hartono Dennis

    2016-01-01

    Full Text Available The use of vibration measurementanalysis has been proven to be effective for gearbox fault diagnosis. However, the complexity of vibration signals observed from a gearbox makes it difficult to accurately detectfaults in the gearbox. This work is based on a comparative studyof several time-frequency signal processing methods that can be used to extract information from transient vibration signals containing useful diagnostic information. Experiments were performed on a bevel gearbox test rig using vibration measurements obtained from accelerometers. Initially, thediscrete wavelet transform was implementedfor vibration signal analysis to extract the frequency content of signal from the relevant frequency region. Several time-frequency signal processing methods werethen incorporated to extract the fault features of vibration signals and their diagnostic performances were compared. It was shown thatthe Short Time Fourier Transform (STFT could not offer a good time resolution to detect the periodicity of the faulty gear tooth due the difficulty in choosing an appropriate window length to capture the impulse signal. The Continuous Wavelet Transform (CWT, on the other hand, was suitable to detection of vibration transients generated by localized fault from a gearbox due to its multi-scale property. However, both methods still require a thorough visual inspection. In contrast, it was shown from the experiments that the diagnostic method using the Cepstrumanalysis could provide a direct indication of the faulty tooth without the need of a thorough visual inspection as required by CWT and STFT.

  16. Recent diagnostic developments on LHD

    International Nuclear Information System (INIS)

    Sudo, S; Ozaki, T; Ashikawa, N; Emoto, M; Goto, M; Hamada, Y; Ida, K; Ido, T; Iguchi, H; Inagaki, S; Isobe, M; Kawahata, K; Khlopenkov, K; Kobuchi, T; Liang, Y; Masuzaki, S; Minami, T; Morita, S; Muto, S; Nagayama, Y; Nakanishi, H; Narihara, K; Nishizawa, A; Ohdachi, S; Osakabe, M; Peterson, B J; Sakakibara, S; Sasao, M; Sato, K; Shoji, M; Tamura, N; Tanaka, K; Toi, K; Tokuzawa, T; Watanabe, K; Watanabe, T; Yamada, I; Goncharov, P; Ejiri, A; Okajima, S; Mase, A; Tsuji-Iio, S; Akiyama, T; Lyon, J F; Vyacheslavov, L N; Sanin, A

    2003-01-01

    The recent diagnostic developments on the large helical device (LHD) are described briefly. LHD is the largest helical machine with all superconducting coils, and its purpose is to prove the ability of a helical system to confine a fusion-relevant plasma in steady state. According to the missions of LHD research, the diagnostic devices are categorized as follows: diagnostics for (i) high nτ E T plasmas and transport physics; (ii) magnetohydrodynamic stability; (iii) long pulse operation and divertor function; and (iv) energetic particles. These are briefly described focusing on the recent developments of the devices. Since the LHD experiment started in March 1998, five series of experimental campaigns have been carried out. The LHD diagnostics during these periods were operated successfully, and contributed to the analysis of the experimental results

  17. Simulation-based diagnostics and control for nuclear power plants. Final report, April 15, 1992--April 14, 1995

    International Nuclear Information System (INIS)

    Lee, J.C.

    1995-07-01

    The objective of the project was to develop and test a simulation-based diagnostics and control guidance system that can be used to diagnose and manage off-normal transient events in nuclear power plants. The research has focused on developing two diagnostic approaches suitable for detection and identification of faults involving multiple components, subject to uncertainties in system modeling and observations. The first approach is based on a fuzzy logic framework that can diagnose binary failures using a single-failure diagnostic knowledge base. Construction of the binary-failure knowledge base is accomplished through the use of macroscopic conservation relationships and a fuzzy inference structure is developed to determine the magnitude of faults and the associated certainty. In the second diagnostic approach, an adaptive Kalman filter algorithm is derived to yield information on the type and magnitude of feasible component transitions that can account for system observations. To obtain the likelihood of feasible component failures or degradations, a general probabilistic formulation is developed where statistical distributions associated with component reliability data are explicitly represented. Testing of the diagnostic algorithms has been performed through the analysis of simulated transient events for light water reactor systems. Preliminary studies have been conducted to develop Monte Carlo algorithms for flexible control of transient events

  18. DIAGNOSTICS OF META-INSTABLE STATE OF SEISMICALLY ACTIVE FAULT

    Directory of Open Access Journals (Sweden)

    S. A. Bornyakov

    2017-01-01

    Full Text Available Based on the results of a laboratory simulation of the seismic fault reactivation by “stick-slip” process, it was shown that the system of two blocks just before an impulse offset goes through the meta-instable dynamic state, with early and late stages of meta-instability [Ma et al., 2012]. In the first stage the offset begins in slow stationary mode with slow stresses relaxation on contact between blocks. In the second stage of the “accelerated synergies” strain rate increases and, subsequently, the deformation process through a process of self-organization came to dynamic impulse offset. The experimental results were used for interpretation of the results of spectral analysis of the deformation monitoring data. The data were held within the southern part ofLakeBaikal, where Kultuk earthquake (27.08.2008, Ms=6.1. took place. Its epicenter was located in the South end zone of the main Sayan fault. Monitoring of deformations of rocks was carried out from April to November2008 in tunnel, located at30 km from the epicenter of the earthquake. The time series data was divided into month periods and then the periods were processed by the method of spectral analysis. The results showed that before the earthquake has ordered view spectrogram, whereas in other time intervals, both before and after the earthquake such orderliness in spectrograms is missing. An ordered view spectrograms for deformation monitoring data can be interpreted as a consequence of the self-organiza­tion of deformation process in the transition of seismically active fault into meta-unstable before the Kultuk earthquake.

  19. Faulting at Mormon Point, Death Valley, California: A low-angle normal fault cut by high-angle faults

    Science.gov (United States)

    Keener, Charles; Serpa, Laura; Pavlis, Terry L.

    1993-04-01

    New geophysical and fault kinematic studies indicate that late Cenozoic basin development in the Mormon Point area of Death Valley, California, was accommodated by fault rotations. Three of six fault segments recognized at Mormon Point are now inactive and have been rotated to low dips during extension. The remaining three segments are now active and moderately to steeply dipping. From the geophysical data, one active segment appears to offset the low-angle faults in the subsurface of Death Valley.

  20. Study on seismic hazard assessment of large active fault systems. Evolution of fault systems and associated geomorphic structures: fault model test and field survey

    International Nuclear Information System (INIS)

    Ueta, Keichi; Inoue, Daiei; Miyakoshi, Katsuyoshi; Miyagawa, Kimio; Miura, Daisuke

    2003-01-01

    Sandbox experiments and field surveys were performed to investigate fault system evolution and fault-related deformation of ground surface, the Quaternary deposits and rocks. The summary of the results is shown below. 1) In the case of strike-slip faulting, the basic fault sequence runs from early en echelon faults and pressure ridges through linear trough. The fault systems associated with the 2000 western Tottori earthquake are shown as en echelon pattern that characterize the early stage of wrench tectonics, therefore no thoroughgoing surface faulting was found above the rupture as defined by the main shock and aftershocks. 2) Low-angle and high-angle reverse faults commonly migrate basinward with time, respectively. With increasing normal fault displacement in bedrock, normal fault develops within range after reverse fault has formed along range front. 3) Horizontal distance of surface rupture from the bedrock fault normalized by the height of the Quaternary deposits agrees well with those of model tests. 4) Upward-widening damage zone, where secondary fractures develop, forms in the handing wall side of high-angle reverse fault at the Kamioka mine. (author)

  1. Training diagnostic skills for nuclear power plants

    International Nuclear Information System (INIS)

    Goodstein, L.P.

    1986-11-01

    Operators of large-scale industrial process plants such as nuclear power stations and chemical plants are faced with a critical and complex task when confronted with disturbances in normal operation caused by technical failures or mainte- nances errors. Great care must be taken to prepare and support the operators during such situations. Procedural systems are provided, trained on full-scale highfidelity simulators is often a prerequisite and decision-support systems are starting to be incorporated, especially in modern control rooms. During recent years, it has become increasingly clear from ''real-life'' studies in complex production and transport industries that professional highly skilled troubleshooters can develop effective general purpose search strategies for locating and dealing with faults and, most importantly, with new and not previously experienced faults. This research has indicated that means for training of these general diagnostic abilities can be developed. In addition, other work has dealt with the problem of observing and analyzing operator behaviour in coping with disturbances. The NKA/LIT-4 project has continued these efforts in studying methods for training diagnostic skills as well as for observing and testing operator behaviour on training simulators. (author)

  2. General review of diagnostic systems in EDF PWR units

    International Nuclear Information System (INIS)

    Chevalier, R.; Brasseur, S.; Ricard, B.

    1998-01-01

    Since the beginning of the French nuclear program, Electricite de France (EDF) has looked for ways to improve the availability and safety of its nuclear units. Therefore, monitoring systems on turbogenerators, reactor coolant pumps, primary circuits and core internal structures were designed by the Research and Development Division and implemented with technologies available during the 1970's. However, mainly because of difficulties for data interpretation by plant personnel, EDF subsequently decided to design and develop different tools to help plant operators to process a diagnosis: - a new generation of the Monitoring and Diagnostic System called PSAD, - expert systems for diagnosis on reactor coolant pumps (RCP) 'DIAPO' and turbogenerator units (TG) 'DIVA', - diagnostic guides written for most equipment pending the installation of new monitoring and diagnosis systems. The first version of PSAD, installed in five units, performs on-line monitoring of the turbogenerator shaft line, steam inlet valves, the reactor coolant pumps and the generator stator. The second version not yet implemented, will include Loose Part Detection (LPD) and Core Internal Structure Monitoring (CISM). The level of diagnosis achieved by PSAD depends on the component monitored. The TG and RCP monitoring functions of PSAD compute high level diagnosis descriptors such as natural frequencies and long term trends but do not elaborate a diagnosis automatically. However, a diagnostic assistance window is available on-line, whenever a warning message is displayed, whether for immediate or later action. The window presents a diagnostic approach whose purpose is to find the causes of the symptoms observed. This diagnosis approach is automated in the DIVA and DIAPO expert systems. Numerous potential faults can be identified for both systems thanks to a hierarchy of abnormal situations. The user interactively answers questions when information is needed to progress in the diagnosis. The resulting

  3. Component vibration of VVER-reactors - diagnostics and modelling

    International Nuclear Information System (INIS)

    Altstadt, E.; Scheffler, M.; Weiss, F.-P.

    1995-01-01

    Flow induced vibrations of reactor pressure vessel (RPV) internals (control element and core barrel motions) at VVER-440 reactors have led to the development of dedicated methods for on-line monitoring. These methods need a certain developed stage of the faults to be detected. To achieve a real sensitive early detection of mechanical faults of RPV internals, a theoretical vibration model was developed based on finite elements. The model comprises the whole primary circuit including the steam generators (SG). By means of that model all eigenfrequencies up to 30 Hz and the corresponding mode shapes were calculated for the normal vibration behaviour. Moreover the shift of eigenfrequencies and of amplitudes due to the degradation or to the failure of internal clamping and spring elements could be investigated, showing that a recognition of such degradations even inside the RPV is possible by pure excore vibration measurements. A true diagnostic, that is the identification of the failed component, might become possible because different faults influence different and well separated eigenfrequencies. (author)

  4. Fan fault diagnosis based on symmetrized dot pattern analysis and image matching

    Science.gov (United States)

    Xu, Xiaogang; Liu, Haixiao; Zhu, Hao; Wang, Songling

    2016-07-01

    To detect the mechanical failure of fans, a new diagnostic method based on the symmetrized dot pattern (SDP) analysis and image matching is proposed. Vibration signals of 13 kinds of running states are acquired on a centrifugal fan test bed and reconstructed by the SDP technique. The SDP pattern templates of each running state are established. An image matching method is performed to diagnose the fault. In order to improve the diagnostic accuracy, the single template, multiple templates and clustering fault templates are used to perform the image matching.

  5. TREDRA, Minimal Cut Sets Fault Tree Plot Program

    International Nuclear Information System (INIS)

    Fussell, J.B.

    1983-01-01

    1 - Description of problem or function: TREDRA is a computer program for drafting report-quality fault trees. The input to TREDRA is similar to input for standard computer programs that find minimal cut sets from fault trees. Output includes fault tree plots containing all standard fault tree logic and event symbols, gate and event labels, and an output description for each event in the fault tree. TREDRA contains the following features: a variety of program options that allow flexibility in the program output; capability for automatic pagination of the output fault tree, when necessary; input groups which allow labeling of gates, events, and their output descriptions; a symbol library which includes standard fault tree symbols plus several less frequently used symbols; user control of character size and overall plot size; and extensive input error checking and diagnostic oriented output. 2 - Method of solution: Fault trees are generated by user-supplied control parameters and a coded description of the fault tree structure consisting of the name of each gate, the gate type, the number of inputs to the gate, and the names of these inputs. 3 - Restrictions on the complexity of the problem: TREDRA can produce fault trees with a minimum of 3 and a maximum of 56 levels. The width of each level may range from 3 to 37. A total of 50 transfers is allowed during pagination

  6. Novel neural networks-based fault tolerant control scheme with fault alarm.

    Science.gov (United States)

    Shen, Qikun; Jiang, Bin; Shi, Peng; Lim, Cheng-Chew

    2014-11-01

    In this paper, the problem of adaptive active fault-tolerant control for a class of nonlinear systems with unknown actuator fault is investigated. The actuator fault is assumed to have no traditional affine appearance of the system state variables and control input. The useful property of the basis function of the radial basis function neural network (NN), which will be used in the design of the fault tolerant controller, is explored. Based on the analysis of the design of normal and passive fault tolerant controllers, by using the implicit function theorem, a novel NN-based active fault-tolerant control scheme with fault alarm is proposed. Comparing with results in the literature, the fault-tolerant control scheme can minimize the time delay between fault occurrence and accommodation that is called the time delay due to fault diagnosis, and reduce the adverse effect on system performance. In addition, the FTC scheme has the advantages of a passive fault-tolerant control scheme as well as the traditional active fault-tolerant control scheme's properties. Furthermore, the fault-tolerant control scheme requires no additional fault detection and isolation model which is necessary in the traditional active fault-tolerant control scheme. Finally, simulation results are presented to demonstrate the efficiency of the developed techniques.

  7. A Deep Learning Approach for Fault Diagnosis of Induction Motors in Manufacturing

    Science.gov (United States)

    Shao, Si-Yu; Sun, Wen-Jun; Yan, Ru-Qiang; Wang, Peng; Gao, Robert X.

    2017-11-01

    Extracting features from original signals is a key procedure for traditional fault diagnosis of induction motors, as it directly influences the performance of fault recognition. However, high quality features need expert knowledge and human intervention. In this paper, a deep learning approach based on deep belief networks (DBN) is developed to learn features from frequency distribution of vibration signals with the purpose of characterizing working status of induction motors. It combines feature extraction procedure with classification task together to achieve automated and intelligent fault diagnosis. The DBN model is built by stacking multiple-units of restricted Boltzmann machine (RBM), and is trained using layer-by-layer pre-training algorithm. Compared with traditional diagnostic approaches where feature extraction is needed, the presented approach has the ability of learning hierarchical representations, which are suitable for fault classification, directly from frequency distribution of the measurement data. The structure of the DBN model is investigated as the scale and depth of the DBN architecture directly affect its classification performance. Experimental study conducted on a machine fault simulator verifies the effectiveness of the deep learning approach for fault diagnosis of induction motors. This research proposes an intelligent diagnosis method for induction motor which utilizes deep learning model to automatically learn features from sensor data and realize working status recognition.

  8. Multiscale Permutation Entropy Based Rolling Bearing Fault Diagnosis

    Directory of Open Access Journals (Sweden)

    Jinde Zheng

    2014-01-01

    Full Text Available A new rolling bearing fault diagnosis approach based on multiscale permutation entropy (MPE, Laplacian score (LS, and support vector machines (SVMs is proposed in this paper. Permutation entropy (PE was recently proposed and defined to measure the randomicity and detect dynamical changes of time series. However, for the complexity of mechanical systems, the randomicity and dynamic changes of the vibration signal will exist in different scales. Thus, the definition of MPE is introduced and employed to extract the nonlinear fault characteristics from the bearing vibration signal in different scales. Besides, the SVM is utilized to accomplish the fault feature classification to fulfill diagnostic procedure automatically. Meanwhile, in order to avoid a high dimension of features, the Laplacian score (LS is used to refine the feature vector by ranking the features according to their importance and correlations with the main fault information. Finally, the rolling bearing fault diagnosis method based on MPE, LS, and SVM is proposed and applied to the experimental data. The experimental data analysis results indicate that the proposed method could identify the fault categories effectively.

  9. Reliability database development for use with an object-oriented fault tree evaluation program

    Science.gov (United States)

    Heger, A. Sharif; Harringtton, Robert J.; Koen, Billy V.; Patterson-Hine, F. Ann

    1989-01-01

    A description is given of the development of a fault-tree analysis method using object-oriented programming. In addition, the authors discuss the programs that have been developed or are under development to connect a fault-tree analysis routine to a reliability database. To assess the performance of the routines, a relational database simulating one of the nuclear power industry databases has been constructed. For a realistic assessment of the results of this project, the use of one of existing nuclear power reliability databases is planned.

  10. Development of new diagnostics for WEST

    International Nuclear Information System (INIS)

    Lotte, P.; Moreau, P.; Gil, C.

    2015-01-01

    WEST, the upgraded superconducting tokamak Tore Supra, will be an international experimental platform aimed to support ITER Physics program. The main objective of WEST is to provide relevant plasma conditions for validating plasma facing component (PFC) technology, in particular the actively cooled Tungsten divertor monoblocks, and also assessing high heat flux and high fluence plasma wall interactions with Tungsten in order to prepare ITER divertor operation. In parallel, WEST will also open new experimental opportunities for developing integrated H mode operation and exploring steady state scenarios in a metallic environment. In order to fulfil the Scientific Program of WEST, new diagnostics have been developed in addition to the already existing diagnostics of Tore Supra, modified and improved during the shutdown. For the PFC technology validation program, new tools have been implemented, like a full infrared survey of the PFC, a new calorimetry system, local temperature measurements (thermocouple and Bragg grating optical fiber), and several sets of Langmuir probes. For the analysis of long pulse H mode operation, new plasma diagnostics will be implemented, among which the Visible Spectroscopy diagnostic for W sources and transport studies, the Soft-Xray diagnostic based on gas electron multiplier detectors for transport and MHD studies, the X-ray imaging crystal spectroscopy diagnostic with advanced solid state detector properties for ion temperature, ion density and plasma rotation velocity measurements, and the ECE Imaging diagnostic for MHD and turbulence studies. Most of these new diagnostics are developed with the participation of French Universities or through international collaborations. This paper focuses on the description of these four plasma diagnostics. (author)

  11. Faults and ridges - Historical development in Tempe Terra and Ulysses Patera regions of Mars

    International Nuclear Information System (INIS)

    Scott, D.H.; Dohm, J.M.

    1990-01-01

    Tempe Terra and the area north of Ulysses Patera are selected to demonstrate the various stages of faulting and ridge development in local areas. This work is accomplished by using Viking photomosaics to determine crosscutting relations of structures as well as their morphology and trend orientations. Results show that from the Early Noachian through the Early Amazonian Epochs, at least eight episodes of faulting occurred at Tempe Terra and six at Ulysses Patera. Tectonic activity at Tempe Terra was expressed mainly by densely spaced faults along the northeast extension of the Tharsis rise; faulting culminated in the Middle and Late Noachian and was superseded by transverse fault systems from the Alba Patera region during the Hesperian. Ridge formation, however, was most active in the Early Hesperian. At Ulysses Patera, an early history of tectonism is recorded by complex arrays of faults in a relatively small area of Noachian rocks. 14 refs

  12. A fault diagnosis method based on signed directed graph and matrix for nuclear power plants

    International Nuclear Information System (INIS)

    Liu, Yong-Kuo; Wu, Guo-Hua; Xie, Chun-Li; Duan, Zhi-Yong; Peng, Min-Jun; Li, Meng-Kun

    2016-01-01

    Highlights: • “Rules matrix” is proposed for FDD. • “State matrix” is proposed to solve SDG online inference. • SDG inference and search method are combined for FDD. - Abstract: In order to solve SDG online fault diagnosis and inference, matrix diagnosis and inference methods are proposed for fault detection and diagnosis (FDD). Firstly, “rules matrix” based on SDG model is used for FDD. Secondly, “status matrix” is proposed to achieve SDG online inference. According to different diagnosis results, “status matrix” is applied for the depth-first search and the breadth-first search respectively to find the propagation paths of each fault. Finally, the SDG model of the secondary-loop system in pressurized water reactor (PWR) is built to verify the effectiveness of the proposed method. The simulation experiment results indicate that the “status matrix” used for online inference can be used to find the fault propagation paths and to explain the causes for fault. Therefore, it can be concluded that the proposed method is one of the fault diagnosis for nuclear power plants (NPPs), which can be used to facilitate the development of fault diagnostic system.

  13. A fault diagnosis method based on signed directed graph and matrix for nuclear power plants

    Energy Technology Data Exchange (ETDEWEB)

    Liu, Yong-Kuo, E-mail: LYK08@126.com [Fundamental Science on Nuclear Safety and Simulation Technology Laboratory, Harbin Engineering University, Harbin 150001 (China); Wu, Guo-Hua [Fundamental Science on Nuclear Safety and Simulation Technology Laboratory, Harbin Engineering University, Harbin 150001 (China); Institute of Nuclear Energy Technology, Tsinghua University, Beijing 100084 (China); Xie, Chun-Li [Traffic College, Northeast Forestry University, Harbin, 150040 (China); Duan, Zhi-Yong; Peng, Min-Jun; Li, Meng-Kun [Fundamental Science on Nuclear Safety and Simulation Technology Laboratory, Harbin Engineering University, Harbin 150001 (China)

    2016-02-15

    Highlights: • “Rules matrix” is proposed for FDD. • “State matrix” is proposed to solve SDG online inference. • SDG inference and search method are combined for FDD. - Abstract: In order to solve SDG online fault diagnosis and inference, matrix diagnosis and inference methods are proposed for fault detection and diagnosis (FDD). Firstly, “rules matrix” based on SDG model is used for FDD. Secondly, “status matrix” is proposed to achieve SDG online inference. According to different diagnosis results, “status matrix” is applied for the depth-first search and the breadth-first search respectively to find the propagation paths of each fault. Finally, the SDG model of the secondary-loop system in pressurized water reactor (PWR) is built to verify the effectiveness of the proposed method. The simulation experiment results indicate that the “status matrix” used for online inference can be used to find the fault propagation paths and to explain the causes for fault. Therefore, it can be concluded that the proposed method is one of the fault diagnosis for nuclear power plants (NPPs), which can be used to facilitate the development of fault diagnostic system.

  14. In-flight Fault Detection and Isolation in Aircraft Flight Control Systems

    Science.gov (United States)

    Azam, Mohammad; Pattipati, Krishna; Allanach, Jeffrey; Poll, Scott; Patterson-Hine, Ann

    2005-01-01

    In this paper we consider the problem of test design for real-time fault detection and isolation (FDI) in the flight control system of fixed-wing aircraft. We focus on the faults that are manifested in the control surface elements (e.g., aileron, elevator, rudder and stabilizer) of an aircraft. For demonstration purposes, we restrict our focus on the faults belonging to nine basic fault classes. The diagnostic tests are performed on the features extracted from fifty monitored system parameters. The proposed tests are able to uniquely isolate each of the faults at almost all severity levels. A neural network-based flight control simulator, FLTZ(Registered TradeMark), is used for the simulation of various faults in fixed-wing aircraft flight control systems for the purpose of FDI.

  15. A Research on the Electrical Test Fault Diagnostic and Data Mining of a Manned Spacecraft

    Directory of Open Access Journals (Sweden)

    Yang Feng

    2017-01-01

    Full Text Available The paper introduces the modeling method and modeling tool for the fault diagnosis of manned spacecraft, the multi-signal flow graph model of a manned space equipment was established using this method; the framework of the fault detection and diagnosis system of manned spacecraft is proposed, the function of ground system and function of the spacecraft are clearly defined. The structure of the functional module is given separately; finally, the tool builds the fault detection and diagnosis system, the application of fault diagnosis method for manned spacecraft is used for reference.

  16. Stator fault detection for multi-phase machines with multiple reference frames transformation

    DEFF Research Database (Denmark)

    Bianchini, Claudio; Fornasiero, Emanuele; Matzen, T.N.

    2009-01-01

    The paper focuses on a new diagnostic index for fault detection of a five-phase permanent-magnet machine. This machine has been designed for fault tolerant applications, and it is characterized by a mutual inductance equal to zero and a high self inductance, in order to limit the short-circuit cu...

  17. Fault-tolerant cooperative output regulation for multi-vehicle systems with sensor faults

    Science.gov (United States)

    Qin, Liguo; He, Xiao; Zhou, D. H.

    2017-10-01

    This paper presents a unified framework of fault diagnosis and fault-tolerant cooperative output regulation (FTCOR) for a linear discrete-time multi-vehicle system with sensor faults. The FTCOR control law is designed through three steps. A cooperative output regulation (COR) controller is designed based on the internal mode principle when there are no sensor faults. A sufficient condition on the existence of the COR controller is given based on the discrete-time algebraic Riccati equation (DARE). Then, a decentralised fault diagnosis scheme is designed to cope with sensor faults occurring in followers. A residual generator is developed to detect sensor faults of each follower, and a bank of fault-matching estimators are proposed to isolate and estimate sensor faults of each follower. Unlike the current distributed fault diagnosis for multi-vehicle systems, the presented decentralised fault diagnosis scheme in each vehicle reduces the communication and computation load by only using the information of the vehicle. By combing the sensor fault estimation and the COR control law, an FTCOR controller is proposed. Finally, the simulation results demonstrate the effectiveness of the FTCOR controller.

  18. Small business development for molecular diagnostics.

    Science.gov (United States)

    Anagostou, Anthanasia; Liotta, Lance A

    2012-01-01

    Molecular profiling, which is the application of molecular diagnostics technology to tissue and blood -specimens, is an integral element in the new era of molecular medicine and individualized therapy. Molecular diagnostics is a fertile ground for small business development because it can generate products that meet immediate demands in the health-care sector: (a) Detection of disease risk, or early-stage disease, with a higher specificity and sensitivity compared to previous testing methods, and (b) "Companion diagnostics" for stratifying patients to receive a treatment choice optimized to their individual disease. This chapter reviews the promise and challenges of business development in this field. Guidelines are provided for the creation of a business model and the generation of a marketing plan around a candidate molecular diagnostic product. Steps to commercialization are outlined using existing molecular diagnostics companies as learning examples.

  19. A Framework for Diagnosis of Critical Faults in Unmanned Aerial Vehicles

    DEFF Research Database (Denmark)

    Hansen, Søren; Blanke, Mogens; Adrian, Jens

    2014-01-01

    , and based on a large number of data logged during flights, diagnostic methods are employed to diagnose faults and the performance of these fault detectors are evaluated against light data. The paper demonstrates a significant potential for reducing the risk of unplanned loss of remotely piloted vehicles......Unmanned Aerial Vehicles (UAVs) need a large degree of tolerance towards faults. If not diagnosed and handled in time, many types of faults can have catastrophic consequences if they occur during flight. Prognosis of faults is also valuable and so is the ability to distinguish the severity...... of the different faults in terms of both consequences and the frequency with which they appear. In this paper flight data from a fleet of UAVs is analysed with respect to certain faults and their frequency of appearance. Data is taken from a group of UAV's of the same type but with small differences in weight...

  20. Rolling bearing fault diagnosis based on information fusion using Dempster-Shafer evidence theory

    Science.gov (United States)

    Pei, Di; Yue, Jianhai; Jiao, Jing

    2017-10-01

    This paper presents a fault diagnosis method for rolling bearing based on information fusion. Acceleration sensors are arranged at different position to get bearing vibration data as diagnostic evidence. The Dempster-Shafer (D-S) evidence theory is used to fuse multi-sensor data to improve diagnostic accuracy. The efficiency of the proposed method is demonstrated by the high speed train transmission test bench. The results of experiment show that the proposed method in this paper improves the rolling bearing fault diagnosis accuracy compared with traditional signal analysis methods.

  1. Development of Monitoring and Diagnostic Methods for Robots Used in Remediation of Waste Sites 1999 Technical Progress Report

    International Nuclear Information System (INIS)

    Martin, Michael

    1999-01-01

    The final assembly of the test rig was completed in January 1999 (see Figure 1). The test rig incorporated a wheel motor typical of those used for hydraulic robots, and allowed wheel motor loading at expected operating conditions. The rig included instrumentation, as shown in Figure 2, for acquisition of key parameters for both unfaulted baseline and inserted fault runs. Checkout of the test rig was accomplished in two phases. In the first phase, only the wheel motor was connected to the hydraulic supply and the driven pump disconnected. With the rig in this configuration, operation of the wheel motor control loop and the monitoring and diagnostic (M and D) data acquisition system was verified. In the second phase, the driven pump was connected to the wheel motor and the operation of the rig under load was confirmed and unfaulted baseline data were acquired. A list of 13 faults was developed (see Table 1). All faults were inserted and data were acquired. The data files were electronically transmitted to Rice University for analysis using Analytical Redundancy (AR), a model-based static space technique that derives the maximum number of independent tests of the consistency of sensor data with the linearized system model and past sensor and control inputs

  2. Bayesian Based Diagnostic Model for Condition Based Maintenance of Offshore Wind Farms

    Directory of Open Access Journals (Sweden)

    Masoud Asgarpour

    2018-01-01

    Full Text Available Operation and maintenance costs are a major contributor to the Levelized Cost of Energy for electricity produced by offshore wind and can be significantly reduced if existing corrective actions are performed as efficiently as possible and if future corrective actions are avoided by performing sufficient preventive actions. This paper presents an applied and generic diagnostic model for fault detection and condition based maintenance of offshore wind components. The diagnostic model is based on two probabilistic matrices; first, a confidence matrix, representing the probability of detection using each fault detection method, and second, a diagnosis matrix, representing the individual outcome of each fault detection method. Once the confidence and diagnosis matrices of a component are defined, the individual diagnoses of each fault detection method are combined into a final verdict on the fault state of that component. Furthermore, this paper introduces a Bayesian updating model based on observations collected by inspections to decrease the uncertainty of initial confidence matrix. The framework and implementation of the presented diagnostic model are further explained within a case study for a wind turbine component based on vibration, temperature, and oil particle fault detection methods. The last part of the paper will have a discussion of the case study results and present conclusions.

  3. Functional Fault Modeling Conventions and Practices for Real-Time Fault Isolation

    Science.gov (United States)

    Ferrell, Bob; Lewis, Mark; Perotti, Jose; Oostdyk, Rebecca; Brown, Barbara

    2010-01-01

    The purpose of this paper is to present the conventions, best practices, and processes that were established based on the prototype development of a Functional Fault Model (FFM) for a Cryogenic System that would be used for real-time Fault Isolation in a Fault Detection, Isolation, and Recovery (FDIR) system. The FDIR system is envisioned to perform health management functions for both a launch vehicle and the ground systems that support the vehicle during checkout and launch countdown by using a suite of complimentary software tools that alert operators to anomalies and failures in real-time. The FFMs were created offline but would eventually be used by a real-time reasoner to isolate faults in a Cryogenic System. Through their development and review, a set of modeling conventions and best practices were established. The prototype FFM development also provided a pathfinder for future FFM development processes. This paper documents the rationale and considerations for robust FFMs that can easily be transitioned to a real-time operating environment.

  4. Fault zone hydrogeology

    Science.gov (United States)

    Bense, V. F.; Gleeson, T.; Loveless, S. E.; Bour, O.; Scibek, J.

    2013-12-01

    Deformation along faults in the shallow crust (research effort of structural geologists and hydrogeologists. However, we find that these disciplines often use different methods with little interaction between them. In this review, we document the current multi-disciplinary understanding of fault zone hydrogeology. We discuss surface- and subsurface observations from diverse rock types from unlithified and lithified clastic sediments through to carbonate, crystalline, and volcanic rocks. For each rock type, we evaluate geological deformation mechanisms, hydrogeologic observations and conceptual models of fault zone hydrogeology. Outcrop observations indicate that fault zones commonly have a permeability structure suggesting they should act as complex conduit-barrier systems in which along-fault flow is encouraged and across-fault flow is impeded. Hydrogeological observations of fault zones reported in the literature show a broad qualitative agreement with outcrop-based conceptual models of fault zone hydrogeology. Nevertheless, the specific impact of a particular fault permeability structure on fault zone hydrogeology can only be assessed when the hydrogeological context of the fault zone is considered and not from outcrop observations alone. To gain a more integrated, comprehensive understanding of fault zone hydrogeology, we foresee numerous synergistic opportunities and challenges for the discipline of structural geology and hydrogeology to co-evolve and address remaining challenges by co-locating study areas, sharing approaches and fusing data, developing conceptual models from hydrogeologic data, numerical modeling, and training interdisciplinary scientists.

  5. Fault diagnostics in power transformer model winding for different alpha values

    Directory of Open Access Journals (Sweden)

    G.H. Kusumadevi

    2015-09-01

    Full Text Available Transient overvoltages appearing at line terminal of power transformer HV windings can cause failure of winding insulation. The failure can be from winding to ground or between turns or sections of winding. In most of the cases, failure from winding to ground can be detected by changes in the wave shape of surge voltage appearing at line terminal. However, detection of insulation failure between turns may be difficult due to intricacies involved in identifications of faults. In this paper, simulation investigations carried out on a power transformer model winding for identifying faults between turns of winding has been reported. The power transformer HV winding has been represented by 8 sections, 16 sections and 24 sections. Neutral current waveform has been analyzed for same model winding represented by different number of sections. The values of α (‘α’ value is the square root of total ground capacitance to total series capacitance of winding considered for windings are 5, 10 and 20. Standard lightning impulse voltage (1.2/50 μs wave shape have been considered for analysis. Computer simulations have been carried out using software PSPICE version 10.0. Neutral current and frequency response analysis methods have been used for identification of faults within sections of transformer model winding.

  6. Characterization of leaky faults

    International Nuclear Information System (INIS)

    Shan, Chao.

    1990-05-01

    Leaky faults provide a flow path for fluids to move underground. It is very important to characterize such faults in various engineering projects. The purpose of this work is to develop mathematical solutions for this characterization. The flow of water in an aquifer system and the flow of air in the unsaturated fault-rock system were studied. If the leaky fault cuts through two aquifers, characterization of the fault can be achieved by pumping water from one of the aquifers, which are assumed to be horizontal and of uniform thickness. Analytical solutions have been developed for two cases of either a negligibly small or a significantly large drawdown in the unpumped aquifer. Some practical methods for using these solutions are presented. 45 refs., 72 figs., 11 tabs

  7. Development of Hydrologic Characterization Technology of Fault Zones: Phase I, 2nd Report

    International Nuclear Information System (INIS)

    Karasaki, Kenzi; Onishi, Tiemi; Black, Bill; Biraud, Sebastien

    2009-01-01

    This is the year-end report of the 2nd year of the NUMO-LBNL collaborative project: Development of Hydrologic Characterization Technology of Fault Zones under NUMO-DOE/LBNL collaboration agreement, the task description of which can be found in the Appendix 3. Literature survey of published information on the relationship between geologic and hydrologic characteristics of faults was conducted. The survey concluded that it may be possible to classify faults by indicators based on various geometric and geologic attributes that may indirectly relate to the hydrologic property of faults. Analysis of existing information on the Wildcat Fault and its surrounding geology was performed. The Wildcat Fault is thought to be a strike-slip fault with a thrust component that runs along the eastern boundary of the Lawrence Berkeley National Laboratory. It is believed to be part of the Hayward Fault system but is considered inactive. Three trenches were excavated at carefully selected locations mainly based on the information from the past investigative work inside the LBNL property. At least one fault was encountered in all three trenches. Detailed trench mapping was conducted by CRIEPI (Central Research Institute for Electric Power Industries) and LBNL scientists. Some intriguing and puzzling discoveries were made that may contradict with the published work in the past. Predictions are made regarding the hydrologic property of the Wildcat Fault based on the analysis of fault structure. Preliminary conceptual models of the Wildcat Fault were proposed. The Wildcat Fault appears to have multiple splays and some low angled faults may be part of the flower structure. In parallel, surface geophysical investigations were conducted using electrical resistivity survey and seismic reflection profiling along three lines on the north and south of the LBNL site. Because of the steep terrain, it was difficult to find optimum locations for survey lines as it is desirable for them to be as

  8. Benchmarking Diagnostic Algorithms on an Electrical Power System Testbed

    Science.gov (United States)

    Kurtoglu, Tolga; Narasimhan, Sriram; Poll, Scott; Garcia, David; Wright, Stephanie

    2009-01-01

    Diagnostic algorithms (DAs) are key to enabling automated health management. These algorithms are designed to detect and isolate anomalies of either a component or the whole system based on observations received from sensors. In recent years a wide range of algorithms, both model-based and data-driven, have been developed to increase autonomy and improve system reliability and affordability. However, the lack of support to perform systematic benchmarking of these algorithms continues to create barriers for effective development and deployment of diagnostic technologies. In this paper, we present our efforts to benchmark a set of DAs on a common platform using a framework that was developed to evaluate and compare various performance metrics for diagnostic technologies. The diagnosed system is an electrical power system, namely the Advanced Diagnostics and Prognostics Testbed (ADAPT) developed and located at the NASA Ames Research Center. The paper presents the fundamentals of the benchmarking framework, the ADAPT system, description of faults and data sets, the metrics used for evaluation, and an in-depth analysis of benchmarking results obtained from testing ten diagnostic algorithms on the ADAPT electrical power system testbed.

  9. The distribution of deformation in parallel fault-related folds with migrating axial surfaces: comparison between fault-propagation and fault-bend folding

    Science.gov (United States)

    Salvini, Francesco; Storti, Fabrizio

    2001-01-01

    In fault-related folds that form by axial surface migration, rocks undergo deformation as they pass through axial surfaces. The distribution and intensity of deformation in these structures has been impacted by the history of axial surface migration. Upon fold initiation, unique dip panels develop, each with a characteristic deformation intensity, depending on their history. During fold growth, rocks that pass through axial surfaces are transported between dip panels and accumulate additional deformation. By tracking the pattern of axial surface migration in model folds, we predict the distribution of relative deformation intensity in simple-step, parallel fault-bend and fault-propagation anticlines. In both cases the deformation is partitioned into unique domains we call deformation panels. For a given rheology of the folded multilayer, deformation intensity will be homogeneously distributed in each deformation panel. Fold limbs are always deformed. The flat crests of fault-propagation anticlines are always undeformed. Two asymmetric deformation panels develop in fault-propagation folds above ramp angles exceeding 29°. For lower ramp angles, an additional, more intensely-deformed panel develops at the transition between the crest and the forelimb. Deformation in the flat crests of fault-bend anticlines occurs when fault displacement exceeds the length of the footwall ramp, but is never found immediately hinterland of the crest to forelimb transition. In environments dominated by brittle deformation, our models may serve as a first-order approximation of the distribution of fractures in fault-related folds.

  10. Advanced Model of Squirrel Cage Induction Machine for Broken Rotor Bars Fault Using Multi Indicators

    Directory of Open Access Journals (Sweden)

    Ilias Ouachtouk

    2016-01-01

    Full Text Available Squirrel cage induction machine are the most commonly used electrical drives, but like any other machine, they are vulnerable to faults. Among the widespread failures of the induction machine there are rotor faults. This paper focuses on the detection of broken rotor bars fault using multi-indicator. However, diagnostics of asynchronous machine rotor faults can be accomplished by analysing the anomalies of machine local variable such as torque, magnetic flux, stator current and neutral voltage signature analysis. The aim of this research is to summarize the existing models and to develop new models of squirrel cage induction motors with consideration of the neutral voltage and to study the effect of broken rotor bars on the different electrical quantities such as the park currents, torque, stator currents and neutral voltage. The performance of the model was assessed by comparing the simulation and experimental results. The obtained results show the effectiveness of the model, and allow detection and diagnosis of these defects.

  11. Rolling element bearings diagnostics using the Symbolic Aggregate approXimation

    Science.gov (United States)

    Georgoulas, George; Karvelis, Petros; Loutas, Theodoros; Stylios, Chrysostomos D.

    2015-08-01

    Rolling element bearings are a very critical component in various engineering assets. Therefore it is of paramount importance the detection of possible faults, especially at an early stage, that may lead to unexpected interruptions of the production or worse, to severe accidents. This research work introduces a novel, in the field of bearing fault detection, method for the extraction of diagnostic representations of vibration recordings using the Symbolic Aggregate approXimation (SAX) framework and the related intelligent icons representation. SAX essentially transforms the original real valued time-series into a discrete one, which is then represented by a simple histogram form summarizing the occurrence of the chosen symbols/words. Vibration signals from healthy bearings and bearings with three different fault locations and with three different severity levels, as well as loading conditions, are analyzed. Considering the diagnostic problem as a classification one, the analyzed vibration signals and the resulting feature vectors feed simple classifiers achieving remarkably high classification accuracies. Moreover a sliding window scheme combined with a simple majority voting filter further increases the reliability and robustness of the diagnostic method. The results encourage the potential use of the proposed methodology for the diagnosis of bearing faults.

  12. Numerical modelling of the mechanical and fluid flow properties of fault zones - Implications for fault seal analysis

    NARCIS (Netherlands)

    Heege, J.H. ter; Wassing, B.B.T.; Giger, S.B.; Clennell, M.B.

    2009-01-01

    Existing fault seal algorithms are based on fault zone composition and fault slip (e.g., shale gouge ratio), or on fault orientations within the contemporary stress field (e.g., slip tendency). In this study, we aim to develop improved fault seal algorithms that account for differences in fault zone

  13. Three-Dimensional Growth of Flexural Slip Fault-Bend and Fault-Propagation Folds and Their Geomorphic Expression

    Directory of Open Access Journals (Sweden)

    Asdrúbal Bernal

    2018-03-01

    Full Text Available The three-dimensional growth of fault-related folds is known to be an important process during the development of compressive mountain belts. However, comparatively little is known concerning the manner in which fold growth is expressed in topographic relief and local drainage networks. Here we report results from a coupled kinematic and surface process model of fault-related folding. We consider flexural slip fault-bend and fault-propagation folds that grow in both the transport and strike directions, linked to a surface process model that includes bedrock channel development and hillslope diffusion. We investigate various modes of fold growth under identical surface process conditions and critically analyse their geomorphic expression. Fold growth results in the development of steep forelimbs and gentler, wider backlimbs resulting in asymmetric drainage basin development (smaller basins on forelimbs, larger basins on backlimbs. However, topographies developed above fault-propagation folds are more symmetric than those developed above fault-bend folds as a result of their different forelimb kinematics. In addition, the surface expression of fault-bend and fault-propagation folds depends both on the slip distribution along the fault and on the style of fold growth. When along-strike plunge is a result of slip events with gently decreasing slip towards the fault tips (with or without lateral propagation, large plunge-panel drainage networks are developed at the expense of backpanel (transport-opposing and forepanel (transport-facing drainage basins. In contrast, if the fold grows as a result of slip events with similar displacements along strike, plunge-panel drainage networks are poorly developed (or are transient features of early fold growth and restricted to lateral fold terminations, particularly when the number of propagation events is small. The absence of large-scale plunge-panel drainage networks in natural examples suggests that the

  14. An expert fault diagnosis system for vehicle air conditioning product development

    NARCIS (Netherlands)

    Tan, C.F.; Tee, B.T.; Khalil, S.N.; Chen, W.; Rauterberg, G.W.M.

    2015-01-01

    The paper describes the development of the vehicle air-conditioning fault diagnosis system in automotive industries with expert system shell. The main aim of the research is to diagnose the problem of new vehicle air-conditioning system development process and select the most suitable solution to

  15. PC based diagnostic system for nitrogen production unit of HWP

    International Nuclear Information System (INIS)

    Lamba, D.S.; Rao, V.C.; Krishnan, S.; Kamaraj, T.; Krishnaswamy, C.

    1992-01-01

    The plant diagnostic system monitors the input data from local processing unit and tries to diagnose the cause of the failure. The system is a rule based application program that can perform tasks itself using fault tree model which displays the logical relationships between critical events and their possible ways occurrence, i.e. hardware failure, process faults and human error etc. Unit 37 Nitrogen Plant is taken as a prototype model for trying the plant diagnostics system. (author). 3 refs., 2 figs

  16. Application of the Systematic Sensor Selection Strategy for Turbofan Engine Diagnostics

    Science.gov (United States)

    Sowers, T. Shane; Kopasakis, George; Simon, Donald L.

    2008-01-01

    The data acquired from available system sensors forms the foundation upon which any health management system is based, and the available sensor suite directly impacts the overall diagnostic performance that can be achieved. While additional sensors may provide improved fault diagnostic performance, there are other factors that also need to be considered such as instrumentation cost, weight, and reliability. A systematic sensor selection approach is desired to perform sensor selection from a holistic system-level perspective as opposed to performing decisions in an ad hoc or heuristic fashion. The Systematic Sensor Selection Strategy is a methodology that optimally selects a sensor suite from a pool of sensors based on the system fault diagnostic approach, with the ability of taking cost, weight, and reliability into consideration. This procedure was applied to a large commercial turbofan engine simulation. In this initial study, sensor suites tailored for improved diagnostic performance are constructed from a prescribed collection of candidate sensors. The diagnostic performance of the best performing sensor suites in terms of fault detection and identification are demonstrated, with a discussion of the results and implications for future research.

  17. An Artificial Intelligence Approach for Gears Diagnostics in AUVs.

    Science.gov (United States)

    Marichal, Graciliano Nicolás; Del Castillo, María Lourdes; López, Jesús; Padrón, Isidro; Artés, Mariano

    2016-04-12

    In this paper, an intelligent scheme for detecting incipient defects in spur gears is presented. In fact, the study has been undertaken to determine these defects in a single propeller system of a small-sized unmanned helicopter. It is important to remark that although the study focused on this particular system, the obtained results could be extended to other systems known as AUVs (Autonomous Unmanned Vehicles), where the usage of polymer gears in the vehicle transmission is frequent. Few studies have been carried out on these kinds of gears. In this paper, an experimental platform has been adapted for the study and several samples have been prepared. Moreover, several vibration signals have been measured and their time-frequency characteristics have been taken as inputs to the diagnostic system. In fact, a diagnostic system based on an artificial intelligence strategy has been devised. Furthermore, techniques based on several paradigms of the Artificial Intelligence (Neural Networks, Fuzzy systems and Genetic Algorithms) have been applied altogether in order to design an efficient fault diagnostic system. A hybrid Genetic Neuro-Fuzzy system has been developed, where it is possible, at the final stage of the learning process, to express the fault diagnostic system as a set of fuzzy rules. Several trials have been carried out and satisfactory results have been achieved.

  18. An Artificial Intelligence Approach for Gears Diagnostics in AUVs

    Directory of Open Access Journals (Sweden)

    Graciliano Nicolás Marichal

    2016-04-01

    Full Text Available In this paper, an intelligent scheme for detecting incipient defects in spur gears is presented. In fact, the study has been undertaken to determine these defects in a single propeller system of a small-sized unmanned helicopter. It is important to remark that although the study focused on this particular system, the obtained results could be extended to other systems known as AUVs (Autonomous Unmanned Vehicles, where the usage of polymer gears in the vehicle transmission is frequent. Few studies have been carried out on these kinds of gears. In this paper, an experimental platform has been adapted for the study and several samples have been prepared. Moreover, several vibration signals have been measured and their time-frequency characteristics have been taken as inputs to the diagnostic system. In fact, a diagnostic system based on an artificial intelligence strategy has been devised. Furthermore, techniques based on several paradigms of the Artificial Intelligence (Neural Networks, Fuzzy systems and Genetic Algorithms have been applied altogether in order to design an efficient fault diagnostic system. A hybrid Genetic Neuro-Fuzzy system has been developed, where it is possible, at the final stage of the learning process, to express the fault diagnostic system as a set of fuzzy rules. Several trials have been carried out and satisfactory results have been achieved.

  19. ECH system developments including the design of an intelligent fault processor on the DIII-D tokamak

    International Nuclear Information System (INIS)

    Ponce, D.; Lohr, J.; Tooker, J.F.; O'Neill, R.C.; Moeller, C.P.; Doane, J.L.; Noraky, S.; Dubovenko, K.; Gorelov, Y.A.; Cengher, M.; Penaflor, B.G.; Ellis, R.A.

    2011-01-01

    A new generation fault processor is in development which is intended to increase fault handling flexibility and reduce the number of incomplete DIII-D shots due to gyrotron faults. The processor, which is based upon a field programmable gate array device, will analyze signals for aberrant operation and ramp down high voltage to try to avoid hard faults. The processor will then attempt to ramp back up to an attainable operating point. The new generation fault processor will be developed during an expansion of the electron cyclotron heating (ECH) areas that will include the installation of a depressed collector gyrotron and associated equipment. Existing systems will also be upgraded. Testing of real-time control of the ECH launcher poloidal drives by the DIII-D plasma control system will be completed. The ECH control system software will be upgraded for increased scalability and to increase operator productivity. Resources permitting, all systems will receive an extra layer of interlocks for the filament and magnet power supplies, added shielding for the tank electronics, programmable filament boost shape for long pulses, and electronics upgrades for the installation of the advanced fault processor.

  20. Development of an air coil superconducting fault current limiter

    Energy Technology Data Exchange (ETDEWEB)

    Naeckel, Oliver

    2016-07-01

    Electrical power grids are the lifeline of technical infrastructure and fundamental for industry and modern lives. Fault Currents can disrupt the continuous supply of electrical energy, cause instable grid conditions and damage electrical equipment. The Air Coil Superconducting Fault Current Limiter (AC-SFCL) is a measure to effectively limit fault currents. The concept is investigated and proven experimentally by designing, building and successfully testing a 60 kV, 400 V, z=6% demonstrator.

  1. Status of ITER neutron diagnostic development

    Science.gov (United States)

    Krasilnikov, A. V.; Sasao, M.; Kaschuck, Yu. A.; Nishitani, T.; Batistoni, P.; Zaveryaev, V. S.; Popovichev, S.; Iguchi, T.; Jarvis, O. N.; Källne, J.; Fiore, C. L.; Roquemore, A. L.; Heidbrink, W. W.; Fisher, R.; Gorini, G.; Prosvirin, D. V.; Tsutskikh, A. Yu.; Donné, A. J. H.; Costley, A. E.; Walker, C. I.

    2005-12-01

    Due to the high neutron yield and the large plasma size many ITER plasma parameters such as fusion power, power density, ion temperature, fast ion energy and their spatial distributions in the plasma core can be measured well by various neutron diagnostics. Neutron diagnostic systems under consideration and development for ITER include radial and vertical neutron cameras (RNC and VNC), internal and external neutron flux monitors (NFMs), neutron activation systems and neutron spectrometers. The two-dimensional neutron source strength and spectral measurements can be provided by the combined RNC and VNC. The NFMs need to meet the ITER requirement of time-resolved measurements of the neutron source strength and can provide the signals necessary for real-time control of the ITER fusion power. Compact and high throughput neutron spectrometers are under development. A concept for the absolute calibration of neutron diagnostic systems is proposed. The development, testing in existing experiments and the engineering integration of all neutron diagnostic systems into ITER are in progress and the main results are presented.

  2. Status of ITER neutron diagnostic development

    International Nuclear Information System (INIS)

    Krasilnikov, A.V.; Sasao, M.; Kaschuck, Yu.A.; Nishitani, T.; Batistoni, P.; Zaveryaev, V.S.; Popovichev, S.; Iguchi, T.; Jarvis, O.N.; Kaellne, J.; Fiore, C.L.; Roquemore, A.L.; Heidbrink, W.W.; Fisher, R.; Gorini, G.; Prosvirin, D.V.; Tsutskikh, A.Yu.; Donne, A.J.H.; Costley, A.E.; Walker, C.I.

    2005-01-01

    Due to the high neutron yield and the large plasma size many ITER plasma parameters such as fusion power, power density, ion temperature, fast ion energy and their spatial distributions in the plasma core can be measured well by various neutron diagnostics. Neutron diagnostic systems under consideration and development for ITER include radial and vertical neutron cameras (RNC and VNC), internal and external neutron flux monitors (NFMs), neutron activation systems and neutron spectrometers. The two-dimensional neutron source strength and spectral measurements can be provided by the combined RNC and VNC. The NFMs need to meet the ITER requirement of time-resolved measurements of the neutron source strength and can provide the signals necessary for real-time control of the ITER fusion power. Compact and high throughput neutron spectrometers are under development. A concept for the absolute calibration of neutron diagnostic systems is proposed. The development, testing in existing experiments and the engineering integration of all neutron diagnostic systems into ITER are in progress and the main results are presented

  3. Status of ITER neutron diagnostic development

    International Nuclear Information System (INIS)

    Sasao, M.; Krasilnikov, A.V.; Kaschuck, Yu.A.; Nishitani, T.; Batistoni, P.; Zaveryaev, V.S.; Popovichev, S.; Jarvis, O.N.; Iguchi, T.; Kaellne, J.; Fiore, C.L.; Roquemore, A.L.; Heidbrink, W.W.; Fisher, R.; Gorini, G.; Donne, A.J.H.; Costley, A.E.; Walker, C.I.

    2005-01-01

    Due to the high neutron yield and the large plasma size many ITER plasma parameters such as fusion power, power density, ion temperature, fast ion energy and their spatial distributions in the plasma core can be well measured by various neutron diagnostics. Neutron diagnostic systems under consideration and development for ITER include: radial and vertical neutron cameras (RNC and VNC), internal and external neutron flux monitors, neutron activation systems and neutron spectrometers. The two-dimensional neutron source strength and spectral measurements can be provided by the combined RNC and VNC. The neutron flux monitors need to meet the ITER requirement of time-resolved measurements of the neutron source strength and can provide the signals necessary for real-time control of the ITER fusion power. Compact and high throughput neutron spectrometers are under development. A concept for the absolute calibration of neutron diagnostic systems is proposed. The development, testing in existing experiments and the engineering integration of all neutron diagnostic systems into ITER are in progress and the main results are presented. (author)

  4. Contribution of qualitative analysis and fuzzy sets to industrial process fault diagnosis: application to the Diapason project

    International Nuclear Information System (INIS)

    Montmain, J.; Leyval, L.

    1994-01-01

    The construction of fault indicators is the foundation of model-based fault diagnosis. The development of precise mathematical models for complex facilities is generally difficult and expensive; new and less constraining techniques, notably seeking to account for behaviour, open new perspectives for fault detection and diagnosis. The authors propose a combined approach based on quantitative processing with qualitative assessment of the results. A veritable numerical-symbolic interface then ensures a more satisfactory balance between the two levels of knowledge - analytic and heuristic -necessary to optimize the performance of a diagnostic procedure. Our supervision support system DIAPASON provides operators of industrial continuous processes with an aid to watch and diagnosis. The reasoning is based on a causal graph and on a knowledge base. After an overview of qualitative simulation, defect diagnosis and fault diagnosis, the way in which these three cooperate in DIAPASON is amplified. (authors). 21 refs., 5 figs

  5. Contribution of qualitative analysis and fuzzy sets to industrial process fault diagnosis: Application to the DIAPASON project

    International Nuclear Information System (INIS)

    Montmain, J.; Leyval, L.

    1994-01-01

    The construction of fault indicators is the foundation of model-based fault diagnosis. The development of precise mathematical models for complex facilities is generally difficult and expensive; new and less constraining techniques, notably seeking to account for behaviour, open new perspectives for fault detection and diagnosis. The authors propose a combined approach based on quantitative processing with qualitative assessment of the results. A veritable numerical-symbolic interface then ensure a more satisfactory balance between the two levels of knowledge - analytic and heuristic - necessary to optimize the performance of a diagnostic procedure. Our supervision support system DIAPASON provides operators of industrial continuous processes with an aid to watch and diagnosis. The reasoning is based on a casual graph and on a knowledge base. After an overview of qualitative simulation, defect diagnosis and fault diagnosis, the way in which these three cooperate in DIAPASON is amplified. (author). 21 refs, 5 figs

  6. Continental deformation accommodated by non-rigid passive bookshelf faulting: An example from the Cenozoic tectonic development of northern Tibet

    Science.gov (United States)

    Zuza, Andrew V.; Yin, An

    2016-05-01

    Collision-induced continental deformation commonly involves complex interactions between strike-slip faulting and off-fault deformation, yet this relationship has rarely been quantified. In northern Tibet, Cenozoic deformation is expressed by the development of the > 1000-km-long east-striking left-slip Kunlun, Qinling, and Haiyuan faults. Each have a maximum slip in the central fault segment exceeding 10s to ~ 100 km but a much smaller slip magnitude (~bookshelf-fault model for the Cenozoic tectonic development of northern Tibet. Our model, quantitatively relating discrete left-slip faulting to distributed off-fault deformation during regional clockwise rotation, explains several puzzling features, including the: (1) clockwise rotation of east-striking left-slip faults against the northeast-striking left-slip Altyn Tagh fault along the northwestern margin of the Tibetan Plateau, (2) alternating fault-parallel extension and shortening in the off-fault regions, and (3) eastward-tapering map-view geometries of the Qimen Tagh, Qaidam, and Qilian Shan thrust belts that link with the three major left-slip faults in northern Tibet. We refer to this specific non-rigid bookshelf-fault system as a passive bookshelf-fault system because the rotating bookshelf panels are detached from the rigid bounding domains. As a consequence, the wallrock of the strike-slip faults deforms to accommodate both the clockwise rotation of the left-slip faults and off-fault strain that arises at the fault ends. An important implication of our model is that the style and magnitude of Cenozoic deformation in northern Tibet vary considerably in the east-west direction. Thus, any single north-south cross section and its kinematic reconstruction through the region do not properly quantify the complex deformational processes of plateau formation.

  7. Sliding mode fault tolerant control dealing with modeling uncertainties and actuator faults.

    Science.gov (United States)

    Wang, Tao; Xie, Wenfang; Zhang, Youmin

    2012-05-01

    In this paper, two sliding mode control algorithms are developed for nonlinear systems with both modeling uncertainties and actuator faults. The first algorithm is developed under an assumption that the uncertainty bounds are known. Different design parameters are utilized to deal with modeling uncertainties and actuator faults, respectively. The second algorithm is an adaptive version of the first one, which is developed to accommodate uncertainties and faults without utilizing exact bounds information. The stability of the overall control systems is proved by using a Lyapunov function. The effectiveness of the developed algorithms have been verified on a nonlinear longitudinal model of Boeing 747-100/200. Copyright © 2012 ISA. Published by Elsevier Ltd. All rights reserved.

  8. Clustering of the Self-Organizing Map based Approach in Induction Machine Rotor Faults Diagnostics

    Directory of Open Access Journals (Sweden)

    Ahmed TOUMI

    2009-12-01

    Full Text Available Self-Organizing Maps (SOM is an excellent method of analyzingmultidimensional data. The SOM based classification is attractive, due to itsunsupervised learning and topology preserving properties. In this paper, theperformance of the self-organizing methods is investigated in induction motorrotor fault detection and severity evaluation. The SOM is based on motor currentsignature analysis (MCSA. The agglomerative hierarchical algorithms using theWard’s method is applied to automatically dividing the map into interestinginterpretable groups of map units that correspond to clusters in the input data. Theresults obtained with this approach make it possible to detect a rotor bar fault justdirectly from the visualization results. The system is also able to estimate theextent of rotor faults.

  9. Data-driven design of fault diagnosis and fault-tolerant control systems

    CERN Document Server

    Ding, Steven X

    2014-01-01

    Data-driven Design of Fault Diagnosis and Fault-tolerant Control Systems presents basic statistical process monitoring, fault diagnosis, and control methods, and introduces advanced data-driven schemes for the design of fault diagnosis and fault-tolerant control systems catering to the needs of dynamic industrial processes. With ever increasing demands for reliability, availability and safety in technical processes and assets, process monitoring and fault-tolerance have become important issues surrounding the design of automatic control systems. This text shows the reader how, thanks to the rapid development of information technology, key techniques of data-driven and statistical process monitoring and control can now become widely used in industrial practice to address these issues. To allow for self-contained study and facilitate implementation in real applications, important mathematical and control theoretical knowledge and tools are included in this book. Major schemes are presented in algorithm form and...

  10. Diagnostic development and support of MHD test facilities

    Energy Technology Data Exchange (ETDEWEB)

    1990-01-01

    The Diagnostic Instrumentation and Analysis Laboratory (DIAL) at Mississippi State University (MSU) is developing diagnostic instruments for MHD power train data acquisition and for support of MHD component development test facilities. Microprocessor-controlled optical instruments, initially developed for Heat Recovery/Seed Recovery support, are being refined, and new systems to measure temperatures and gas-seed-slag stream characteristics are being developed. To further data acquisition and analysis capabilities, the diagnostic systems are being interfaced with DIAL's computers. Technical support for the diagnostic needs of the national MHD research effort is being provided. DIAL personnel will also cooperate with government agencies and private industries to improve the transformation of research and development results into processes, products and services applicable to their needs. 25 figs., 6 tabs.

  11. Diagnostic development and support of MHD test facilities

    International Nuclear Information System (INIS)

    Shepard, W.S.; Cook, R.L.

    1990-01-01

    The Diagnostic Instrumentation and Analysis Laboratory (DIAL) at Mississippi State University (MSU) is developing diagnostic instruments for MHD power train data acquisition and for support of MHD component development test facilities. Microprocessor-controlled optical instruments, initially developed for Heat Recovery/ Seed Recovery support, are being refined, and new systems to measure temperatures and gas-seed-slag stream characteristics are being developed. To further data acquisition and analysis capabilities, the diagnostic systems are being interfaced with DIAL's computers. Technical support for the diagnostic needs of the national MHD research effort is being provided. DIAL personnel will also cooperate with government agencies and private industries to improve the transformation of research and development results into processes, products and services applicable to their needs

  12. Designing Fault-Injection Experiments for the Reliability of Embedded Systems

    Science.gov (United States)

    White, Allan L.

    2012-01-01

    This paper considers the long-standing problem of conducting fault-injections experiments to establish the ultra-reliability of embedded systems. There have been extensive efforts in fault injection, and this paper offers a partial summary of the efforts, but these previous efforts have focused on realism and efficiency. Fault injections have been used to examine diagnostics and to test algorithms, but the literature does not contain any framework that says how to conduct fault-injection experiments to establish ultra-reliability. A solution to this problem integrates field-data, arguments-from-design, and fault-injection into a seamless whole. The solution in this paper is to derive a model reduction theorem for a class of semi-Markov models suitable for describing ultra-reliable embedded systems. The derivation shows that a tight upper bound on the probability of system failure can be obtained using only the means of system-recovery times, thus reducing the experimental effort to estimating a reasonable number of easily-observed parameters. The paper includes an example of a system subject to both permanent and transient faults. There is a discussion of integrating fault-injection with field-data and arguments-from-design.

  13. What is Fault Tolerant Control

    DEFF Research Database (Denmark)

    Blanke, Mogens; Frei, C. W.; Kraus, K.

    2000-01-01

    Faults in automated processes will often cause undesired reactions and shut-down of a controlled plant, and the consequences could be damage to the plant, to personnel or the environment. Fault-tolerant control is the synonym for a set of recent techniques that were developed to increase plant...... availability and reduce the risk of safety hazards. Its aim is to prevent that simple faults develop into serious failure. Fault-tolerant control merges several disciplines to achieve this goal, including on-line fault diagnosis, automatic condition assessment and calculation of remedial actions when a fault...... is detected. The envelope of the possible remedial actions is wide. This paper introduces tools to analyze and explore structure and other fundamental properties of an automated system such that any redundancy in the process can be fully utilized to enhance safety and a availability....

  14. Distance and Density Similarity Based Enhanced k-NN Classifier for Improving Fault Diagnosis Performance of Bearings

    Directory of Open Access Journals (Sweden)

    Sharif Uddin

    2016-01-01

    Full Text Available An enhanced k-nearest neighbor (k-NN classification algorithm is presented, which uses a density based similarity measure in addition to a distance based similarity measure to improve the diagnostic performance in bearing fault diagnosis. Due to its use of distance based similarity measure alone, the classification accuracy of traditional k-NN deteriorates in case of overlapping samples and outliers and is highly susceptible to the neighborhood size, k. This study addresses these limitations by proposing the use of both distance and density based measures of similarity between training and test samples. The proposed k-NN classifier is used to enhance the diagnostic performance of a bearing fault diagnosis scheme, which classifies different fault conditions based upon hybrid feature vectors extracted from acoustic emission (AE signals. Experimental results demonstrate that the proposed scheme, which uses the enhanced k-NN classifier, yields better diagnostic performance and is more robust to variations in the neighborhood size, k.

  15. Application of CMAC Neural Network to Solar Energy Heliostat Field Fault Diagnosis

    Directory of Open Access Journals (Sweden)

    Neng-Sheng Pai

    2013-01-01

    Full Text Available Solar energy heliostat fields comprise numerous sun tracking platforms. As a result, fault detection is a highly challenging problem. Accordingly, the present study proposes a cerebellar model arithmetic computer (CMAC neutral network for automatically diagnosing faults within the heliostat field in accordance with the rotational speed, vibration, and temperature characteristics of the individual heliostat transmission systems. As compared with radial basis function (RBF neural network and back propagation (BP neural network in the heliostat field fault diagnosis, the experimental results show that the proposed neural network has a low training time, good robustness, and a reliable diagnostic performance. As a result, it provides an ideal solution for fault diagnosis in modern, large-scale heliostat fields.

  16. A modular neural network scheme applied to fault diagnosis in electric power systems.

    Science.gov (United States)

    Flores, Agustín; Quiles, Eduardo; García, Emilio; Morant, Francisco; Correcher, Antonio

    2014-01-01

    This work proposes a new method for fault diagnosis in electric power systems based on neural modules. With this method the diagnosis is performed by assigning a neural module for each type of component comprising the electric power system, whether it is a transmission line, bus or transformer. The neural modules for buses and transformers comprise two diagnostic levels which take into consideration the logic states of switches and relays, both internal and back-up, with the exception of the neural module for transmission lines which also has a third diagnostic level which takes into account the oscillograms of fault voltages and currents as well as the frequency spectrums of these oscillograms, in order to verify if the transmission line had in fact been subjected to a fault. One important advantage of the diagnostic system proposed is that its implementation does not require the use of a network configurator for the system; it does not depend on the size of the power network nor does it require retraining of the neural modules if the power network increases in size, making its application possible to only one component, a specific area, or the whole context of the power system.

  17. Development of a morphological convolution operator for bearing fault detection

    Science.gov (United States)

    Li, Yifan; Liang, Xihui; Liu, Weiwei; Wang, Yan

    2018-05-01

    This paper presents a novel signal processing scheme, namely morphological convolution operator (MCO) lifted morphological undecimated wavelet (MUDW), for rolling element bearing fault detection. In this scheme, a MCO is first designed to fully utilize the advantage of the closing & opening gradient operator and the closing-opening & opening-closing gradient operator for feature extraction as well as the merit of excellent denoising characteristics of the convolution operator. The MCO is then introduced into MUDW for the purpose of improving the fault detection ability of the reported MUDWs. Experimental vibration signals collected from a train wheelset test rig and the bearing data center of Case Western Reserve University are employed to evaluate the effectiveness of the proposed MCO lifted MUDW on fault detection of rolling element bearings. The results show that the proposed approach has a superior performance in extracting fault features of defective rolling element bearings. In addition, comparisons are performed between two reported MUDWs and the proposed MCO lifted MUDW. The MCO lifted MUDW outperforms both of them in detection of outer race faults and inner race faults of rolling element bearings.

  18. Adaptive Technology Application for Vibration-Based Diagnostics of Roller Bearings on Industrial Plants

    Directory of Open Access Journals (Sweden)

    Mironov Aleksey

    2014-09-01

    Full Text Available Roller bearings are widely used in equipment of different applications; therefore, the issues related to the assessment of bearing technical state and localization of bearing faults are quite important and relevant. The reason is that technical state of a bearing is a critical component, which determines efficiency of a mechanism or equipment. For bearings inspection and diagnostics, various methods of vibration-based diagnostics are used. The adaptive technology for vibration-based diagnostics developed in „D un D centrs” is an effective tool for evaluation of technical state of bearings in operation compared to the existing SKF method.

  19. Enhancing reactor availability factor by diagnostic monitoring and data acquisition of electrical equipments

    International Nuclear Information System (INIS)

    Singh, G.

    2006-01-01

    Electrical energy has made significant contribution to rapid growth of industrial activity in the country. Development and improvement of energy conversion devices or electrical apparatus have supported the growth. Reliability is probably the most important factor in electrical supply system, not only to give uninterrupted service but to provide an economic supply. Regular diagnostic testing of electrical equipments will make a significant contribution to the reliability of electrical supply. The purpose of diagnostic monitoring is to recognize the development of faults at an early stage, which consequently allows greater freedom to schedule the outages resulting in lower downtime and lower capitalized losses. The insulation constitutes the heart of any electrical/power equipment. The insulation in power equipment in normal condition undergoes certain changes in the physical, chemical, electrical and mechanical properties. The change with respect to time in the presence of an influencing factor, more often a stress (electrical) is referred to as ageing. The deterioration of insulating material plays an important role in the assessing the condition of electrical equipments. The systematic diagnostic tests are also part of the maintenance program to ensure the continued serviceability of electrical equipments, by replacing or repairing the components likely to fail, as revealed by the test. Diagnostic tests are carried out on various electrical equipments for detection of incipient fault, location and judging their severity. (author)

  20. Use of Fuzzy Logic Systems for Assessment of Primary Faults

    Science.gov (United States)

    Petrović, Ivica; Jozsa, Lajos; Baus, Zoran

    2015-09-01

    In electric power systems, grid elements are often subjected to very complex and demanding disturbances or dangerous operating conditions. Determining initial fault or cause of those states is a difficult task. When fault occurs, often it is an imperative to disconnect affected grid element from the grid. This paper contains an overview of possibilities for using fuzzy logic in an assessment of primary faults in the transmission grid. The tool for this task is SCADA system, which is based on information of currents, voltages, events of protection devices and status of circuit breakers in the grid. The function model described with the membership function and fuzzy logic systems will be presented in the paper. For input data, diagnostics system uses information of protection devices tripping, states of circuit breakers and measurements of currents and voltages before and after faults.

  1. Distributed Fault-Tolerant Control of Networked Uncertain Euler-Lagrange Systems Under Actuator Faults.

    Science.gov (United States)

    Chen, Gang; Song, Yongduan; Lewis, Frank L

    2016-05-03

    This paper investigates the distributed fault-tolerant control problem of networked Euler-Lagrange systems with actuator and communication link faults. An adaptive fault-tolerant cooperative control scheme is proposed to achieve the coordinated tracking control of networked uncertain Lagrange systems on a general directed communication topology, which contains a spanning tree with the root node being the active target system. The proposed algorithm is capable of compensating for the actuator bias fault, the partial loss of effectiveness actuation fault, the communication link fault, the model uncertainty, and the external disturbance simultaneously. The control scheme does not use any fault detection and isolation mechanism to detect, separate, and identify the actuator faults online, which largely reduces the online computation and expedites the responsiveness of the controller. To validate the effectiveness of the proposed method, a test-bed of multiple robot-arm cooperative control system is developed for real-time verification. Experiments on the networked robot-arms are conduced and the results confirm the benefits and the effectiveness of the proposed distributed fault-tolerant control algorithms.

  2. A study on the development of an automatic fault diagnosis system for testing NPP digital electronic circuits

    International Nuclear Information System (INIS)

    Kim, Dae Sik

    1993-02-01

    This paper describes a study on the development of an automatic fault diagnosis system for testing digital electronic circuits of nuclear power plants. Compared with the other conventional fault diagnosis systems, the system described in this paper uses Artificial Intelligence technique of model based reasoning and corroboration, which makes fault diagnosis much more efficient. In order to reduce the testing time, an optimal testing set which means a minimal testing set to determine whether or not the circuit is fault-free and to locate the faulty gate was derived. Compared with the testing using an exhaustive testing set, the testing using the optimal testing set makes fault diagnosis much more fast. Since the system diagnoses the circuit boards bases only on input and output signals, it can be further developed for on-line testing. The system was implemented on a microprocessor and was applied for Universal Circuit board testing of the Solid State protection System in nuclear power plants

  3. The ground fault detection system for the Tore Supra toroidal pump limiter

    International Nuclear Information System (INIS)

    Zunino, K.; Cara, P.; Fejoz, P.; Hourtoule, J.; Loarer, T.; Pomaro, N.; Santagiustina, A.; Spuig, P.; Villecroze, F.

    2003-01-01

    The toroidal pump limiter (TPL) of Tore Supra is electrically insulated from the vacuum-vessel, to allow its polarization at a voltage of up to 1 kV. In order to monitor continuously the integrity of the TPL electrical insulation, an electronic diagnostic system called TPL ground fault detection system (GFDS) has been developed. The paper will report on the design and the operation experience of the GFD system and on the evolution of the TPL grounding

  4. Determining on-fault magnitude distributions for a connected, multi-fault system

    Science.gov (United States)

    Geist, E. L.; Parsons, T.

    2017-12-01

    A new method is developed to determine on-fault magnitude distributions within a complex and connected multi-fault system. A binary integer programming (BIP) method is used to distribute earthquakes from a 10 kyr synthetic regional catalog, with a minimum magnitude threshold of 6.0 and Gutenberg-Richter (G-R) parameters (a- and b-values) estimated from historical data. Each earthquake in the synthetic catalog can occur on any fault and at any location. In the multi-fault system, earthquake ruptures are allowed to branch or jump from one fault to another. The objective is to minimize the slip-rate misfit relative to target slip rates for each of the faults in the system. Maximum and minimum slip-rate estimates around the target slip rate are used as explicit constraints. An implicit constraint is that an earthquake can only be located on a fault (or series of connected faults) if it is long enough to contain that earthquake. The method is demonstrated in the San Francisco Bay area, using UCERF3 faults and slip-rates. We also invoke the same assumptions regarding background seismicity, coupling, and fault connectivity as in UCERF3. Using the preferred regional G-R a-value, which may be suppressed by the 1906 earthquake, the BIP problem is deemed infeasible when faults are not connected. Using connected faults, however, a solution is found in which there is a surprising diversity of magnitude distributions among faults. In particular, the optimal magnitude distribution for earthquakes that participate along the Peninsula section of the San Andreas fault indicates a deficit of magnitudes in the M6.0- 7.0 range. For the Rodgers Creek-Hayward fault combination, there is a deficit in the M6.0- 6.6 range. Rather than solving this as an optimization problem, we can set the objective function to zero and solve this as a constraint problem. Among the solutions to the constraint problem is one that admits many more earthquakes in the deficit magnitude ranges for both faults

  5. Recent developments of ECE diagnostics at JET

    Energy Technology Data Exchange (ETDEWEB)

    Luna, E. de la; Sanchez, J. [Association Euratom-Ciemat para Fusion, Ciemant (Spain); Cientoli, C.; Blanchard, P.; Joffrin, E.; Mazon, D. [Association Euratom-ENEA sulla Fusione, IFP-CNR, Milano (Italy); Riva, M.; Zerbini, M. [Association Euratom-ENEA sulla Fusione Centro Ricerche Energia Frascati (Italy); Conway, G. [IPP-Euratom Association, Garching (Germany); Felton, R.; Fessey, J.; Gowers, C. [Euratom/UKAEA Fusion Association, Culham Science Centre, Abingdon (United Kingdom); Murari, A. [Consorzio RFX, Association Euratom-ENEA sulla Fusione, Padova (Italy)

    2004-07-01

    In JET, two types of ECE (electron cyclotron emission) instruments are routinely operated to provide electron temperature measurements: a Michelson interferometer and a heterodyne radiometer. ECE diagnostics are able to provide time-resolved electron temperature profiles with high spatial and temporal resolution, and have proven to play a fundamental role in the investigation and development of internal transport barriers (ITBs) in JET. In this paper we report on the major upgrade of the ECE diagnostics systems currently in progress at JET. Diagnostic developments include an upgrade of the multi-channel heterodyne radiometer, aimed at extending the radial region over which T{sub e} measurement can be performed, and the installation of a new Michelson interferometer with fast scanning capability, to improve the frequency and temporal resolution of the multi-harmonic ECE measurements at JET. Moreover, a future extension of the ECE system, an oblique ECE diagnostic to measure the ECE spectra at different angles with respect to the normal to the magnetic field, is being developed. This diagnostic is expected to give valuable insight into the interpretation of ECE measurements in high T{sub e}-plasmas and should be available for measurements once JET resumes operation in 2005.In this paper, the recent developments in the JET ECE diagnostic system will be described and illustrated with some recent results, with an emphasis on issues related with calibration stability, high-Te plasmas and ITB studies. Some of these issues will be discussed in the context of ITER.

  6. Modification of Duval Triangle for Diagnostic Transformer Fault through a Procedure of Dissolved Gases Analysis

    Directory of Open Access Journals (Sweden)

    Sobhy Serry Dessouky

    2016-08-01

        The evaluation is carried out on DGA data obtained from three different groups of transformers. A Matlab program was developed to automate the evaluation of  Duval Triangle graph to numerical modification, Also the fault gases can be generated due to oil decomposing effected by transformer over excitation which increasing thetransformer exciting current lead to rising the temperature inside transformer core beside the other causes.

  7. Efficient Probabilistic Diagnostics for Electrical Power Systems

    Science.gov (United States)

    Mengshoel, Ole J.; Chavira, Mark; Cascio, Keith; Poll, Scott; Darwiche, Adnan; Uckun, Serdar

    2008-01-01

    We consider in this work the probabilistic approach to model-based diagnosis when applied to electrical power systems (EPSs). Our probabilistic approach is formally well-founded, as it based on Bayesian networks and arithmetic circuits. We investigate the diagnostic task known as fault isolation, and pay special attention to meeting two of the main challenges . model development and real-time reasoning . often associated with real-world application of model-based diagnosis technologies. To address the challenge of model development, we develop a systematic approach to representing electrical power systems as Bayesian networks, supported by an easy-to-use speci.cation language. To address the real-time reasoning challenge, we compile Bayesian networks into arithmetic circuits. Arithmetic circuit evaluation supports real-time diagnosis by being predictable and fast. In essence, we introduce a high-level EPS speci.cation language from which Bayesian networks that can diagnose multiple simultaneous failures are auto-generated, and we illustrate the feasibility of using arithmetic circuits, compiled from Bayesian networks, for real-time diagnosis on real-world EPSs of interest to NASA. The experimental system is a real-world EPS, namely the Advanced Diagnostic and Prognostic Testbed (ADAPT) located at the NASA Ames Research Center. In experiments with the ADAPT Bayesian network, which currently contains 503 discrete nodes and 579 edges, we .nd high diagnostic accuracy in scenarios where one to three faults, both in components and sensors, were inserted. The time taken to compute the most probable explanation using arithmetic circuits has a small mean of 0.2625 milliseconds and standard deviation of 0.2028 milliseconds. In experiments with data from ADAPT we also show that arithmetic circuit evaluation substantially outperforms joint tree propagation and variable elimination, two alternative algorithms for diagnosis using Bayesian network inference.

  8. Implementing artificial neural networks in nuclear power plants diagnostic systems: issues and challenges

    International Nuclear Information System (INIS)

    Boger, Z.

    1998-01-01

    A recent review of artificial intelligence applications in nuclear power plants (NPP) diagnostics and fault detection finds that mostly expert systems (ES) and artificial neural networks (ANN) techniques were researched and proposed, but the number of actual implementations in NPP diagnostics systems is very small. It lists the perceived obstacles to the ANN-based system acceptance and implementation. This paper analyses this list. Some of ANN limitations relate to 'quantitative' difficulties of designing and training large-scale ANNs. The availability of an efficient large-scale ANN training algorithm may alleviate most of these concerns. Other perceived drawbacks refer to the 'qualitative' aspects of ANN acceptance - how and when can we rely on the quality of the advice given by the ANN model. Several techniques are available that help to brighten the 'black box' image of the ANN. Analysis of the trained ANN can identify the significant inputs. Calculation of the Causal Indices may reveal the magnitude and sign of the influence of each input on each output. Both these techniques increase the confidence of the users when they conform to known knowledge, or point to plausible relationships. Analysis of the behavior of the neurons in the hidden layer can identify false ANN classification when presented with noisy or corrupt data. Auto-associative NN can identify faulty sensors or data. Two examples of the ANN capabilities as possible diagnostic tools are given, using NPP data, one classifying internal reactor disturbances by neutron noise spectra analysis, the other identifying the faults causes of several transients. To use these techniques the ANN developers need large amount of training data of as many transients as possible. Such data is routinely generated in NPP simulators during the periodic qualification of NPP operators. The IAEA can help by encouraging the saving and distributing the transient data to developers of ANN diagnostic system, to serve as

  9. Development of a component centered fault monitoring and diagnosis knowledge based system for space power system

    Science.gov (United States)

    Lee, S. C.; Lollar, Louis F.

    1988-01-01

    The overall approach currently being taken in the development of AMPERES (Autonomously Managed Power System Extendable Real-time Expert System), a knowledge-based expert system for fault monitoring and diagnosis of space power systems, is discussed. The system architecture, knowledge representation, and fault monitoring and diagnosis strategy are examined. A 'component-centered' approach developed in this project is described. Critical issues requiring further study are identified.

  10. Dynamic modeling of gearbox faults: A review

    Science.gov (United States)

    Liang, Xihui; Zuo, Ming J.; Feng, Zhipeng

    2018-01-01

    Gearbox is widely used in industrial and military applications. Due to high service load, harsh operating conditions or inevitable fatigue, faults may develop in gears. If the gear faults cannot be detected early, the health will continue to degrade, perhaps causing heavy economic loss or even catastrophe. Early fault detection and diagnosis allows properly scheduled shutdowns to prevent catastrophic failure and consequently result in a safer operation and higher cost reduction. Recently, many studies have been done to develop gearbox dynamic models with faults aiming to understand gear fault generation mechanism and then develop effective fault detection and diagnosis methods. This paper focuses on dynamics based gearbox fault modeling, detection and diagnosis. State-of-art and challenges are reviewed and discussed. This detailed literature review limits research results to the following fundamental yet key aspects: gear mesh stiffness evaluation, gearbox damage modeling and fault diagnosis techniques, gearbox transmission path modeling and method validation. In the end, a summary and some research prospects are presented.

  11. Layered Fault Management Architecture

    National Research Council Canada - National Science Library

    Sztipanovits, Janos

    2004-01-01

    ... UAVs or Organic Air Vehicles. The approach of this effort was to analyze fault management requirements of formation flight for fleets of UAVs, and develop a layered fault management architecture which demonstrates significant...

  12. Diagnostic Analyzer for Gearboxes (DAG): User's Guide. Version 3.1 for Microsoft Windows 3.1

    Science.gov (United States)

    Jammu, Vinay B.; Kourosh, Danai

    1997-01-01

    This documentation describes the Diagnostic Analyzer for Gearboxes (DAG) software for performing fault diagnosis of gearboxes. First, the user would construct a graphical representation of the gearbox using the gear, bearing, shaft, and sensor tools contained in the DAG software. Next, a set of vibration features obtained by processing the vibration signals recorded from the gearbox using a signal analyzer is required. Given this information, the DAG software uses an unsupervised neural network referred to as the Fault Detection Network (FDN) to identify the occurrence of faults, and a pattern classifier called Single Category-Based Classifier (SCBC) for abnormality scaling of individual vibration features. The abnormality-scaled vibration features are then used as inputs to a Structure-Based Connectionist Network (SBCN) for identifying faults in gearbox subsystems and components. The weights of the SBCN represent its diagnostic knowledge and are derived from the structure of the gearbox graphically presented in DAG. The outputs of SBCN are fault possibility values between 0 and 1 for individual subsystems and components in the gearbox with a 1 representing a definite fault and a 0 representing normality. This manual describes the steps involved in creating the diagnostic gearbox model, along with the options and analysis tools of the DAG software.

  13. A Combined Fault Diagnosis Method for Power Transformer in Big Data Environment

    Directory of Open Access Journals (Sweden)

    Yan Wang

    2017-01-01

    Full Text Available The fault diagnosis method based on dissolved gas analysis (DGA is of great significance to detect the potential faults of the transformer and improve the security of the power system. The DGA data of transformer in smart grid have the characteristics of large quantity, multiple types, and low value density. In view of DGA big data’s characteristics, the paper first proposes a new combined fault diagnosis method for transformer, in which a variety of fault diagnosis models are used to make a preliminary diagnosis, and then the support vector machine is used to make the second diagnosis. The method adopts the intelligent complementary and blending thought, which overcomes the shortcomings of single diagnosis model in transformer fault diagnosis, and improves the diagnostic accuracy and the scope of application of the model. Then, the training and deployment strategy of the combined diagnosis model is designed based on Storm and Spark platform, which provides a solution for the transformer fault diagnosis in big data environment.

  14. Model-based Diagnostics for Propellant Loading Systems

    Data.gov (United States)

    National Aeronautics and Space Administration — The loading of spacecraft propellants is a complex, risky operation. Therefore, diagnostic solutions are neces- sary to quickly identify when a fault occurs, so that...

  15. Combined expert system/neural networks method for process fault diagnosis

    Science.gov (United States)

    Reifman, Jaques; Wei, Thomas Y. C.

    1995-01-01

    A two-level hierarchical approach for process fault diagnosis is an operating system employs a function-oriented approach at a first level and a component characteristic-oriented approach at a second level, where the decision-making procedure is structured in order of decreasing intelligence with increasing precision. At the first level, the diagnostic method is general and has knowledge of the overall process including a wide variety of plant transients and the functional behavior of the process components. An expert system classifies malfunctions by function to narrow the diagnostic focus to a particular set of possible faulty components that could be responsible for the detected functional misbehavior of the operating system. At the second level, the diagnostic method limits its scope to component malfunctions, using more detailed knowledge of component characteristics. Trained artificial neural networks are used to further narrow the diagnosis and to uniquely identify the faulty component by classifying the abnormal condition data as a failure of one of the hypothesized components through component characteristics. Once an anomaly is detected, the hierarchical structure is used to successively narrow the diagnostic focus from a function misbehavior, i.e., a function oriented approach, until the fault can be determined, i.e., a component characteristic-oriented approach.

  16. Combined expert system/neural networks method for process fault diagnosis

    Science.gov (United States)

    Reifman, J.; Wei, T.Y.C.

    1995-08-15

    A two-level hierarchical approach for process fault diagnosis of an operating system employs a function-oriented approach at a first level and a component characteristic-oriented approach at a second level, where the decision-making procedure is structured in order of decreasing intelligence with increasing precision. At the first level, the diagnostic method is general and has knowledge of the overall process including a wide variety of plant transients and the functional behavior of the process components. An expert system classifies malfunctions by function to narrow the diagnostic focus to a particular set of possible faulty components that could be responsible for the detected functional misbehavior of the operating system. At the second level, the diagnostic method limits its scope to component malfunctions, using more detailed knowledge of component characteristics. Trained artificial neural networks are used to further narrow the diagnosis and to uniquely identify the faulty component by classifying the abnormal condition data as a failure of one of the hypothesized components through component characteristics. Once an anomaly is detected, the hierarchical structure is used to successively narrow the diagnostic focus from a function misbehavior, i.e., a function oriented approach, until the fault can be determined, i.e., a component characteristic-oriented approach. 9 figs.

  17. New development in relay protection for smart grid : new principles of fault distinction

    Energy Technology Data Exchange (ETDEWEB)

    Zhang, B.; Hao, Z. [Xi' an Jiaotong Univ., Xian (China); Klimek, A. [Powertech Labs Inc., Surrey, BC (Canada); Bo, Z. [Alstom Grid Automation (United Kingdom)

    2010-07-01

    China is planning to integrate a smart grid into a proposed 750/1000 kV transmission network. However, the performance of the protection relay must be assured in order to have this kind of transmitting capacity. There are many protection strategies that address the many demands of a smart grid, including ultra-high-speed transient-based fault discrimination; new co-ordination principles of main and back-up protection to suit the diversification of the power network; optimal co-ordination between relay protection; and autoreclosure to enhance robustness of the power network. There are also new developments in protection early warning and tripping functions in the protection concepts based on wide area information. This paper presented the principles, algorithms and techniques of single-ended, transient-based and ultra-high-speed protection for extra-high voltage (EHV) transmission lines, buses, DC transmission lines and faulted line selection for non-solid earthed networks. Test results have verified that the proposed methods can determine fault characteristics with ultra-high-speed (5 ms), and that the new principles of fault discrimination can satisfy the demand of EHV systems within a smart grid. High speed Digital Signal Processor (DSP) embedded system techniques combined with optical sensors provide the ability to record and compute detailed fault transients. This technology makes it possible to implement protection principles based on transient information. Due to the inconsistent nature of the wave impedance for various power apparatuses and the reflection and refraction characteristics of their interconnection points, the fault transients contain abundant information about the fault location and type. It is possible to construct ultra high speed and more sensitive AC, DC and busbar main protection through the correct analysis of such information. 23 refs., 6 figs.

  18. Research on Model-Based Fault Diagnosis for a Gas Turbine Based on Transient Performance

    Directory of Open Access Journals (Sweden)

    Detang Zeng

    2018-01-01

    Full Text Available It is essential to monitor and to diagnose faults in rotating machinery with a high thrust–weight ratio and complex structure for a variety of industrial applications, for which reliable signal measurements are required. However, the measured values consist of the true values of the parameters, the inertia of measurements, random errors and systematic errors. Such signals cannot reflect the true performance state and the health state of rotating machinery accurately. High-quality, steady-state measurements are necessary for most current diagnostic methods. Unfortunately, it is hard to obtain these kinds of measurements for most rotating machinery. Diagnosis based on transient performance is a useful tool that can potentially solve this problem. A model-based fault diagnosis method for gas turbines based on transient performance is proposed in this paper. The fault diagnosis consists of a dynamic simulation model, a diagnostic scheme, and an optimization algorithm. A high-accuracy, nonlinear, dynamic gas turbine model using a modular modeling method is presented that involves thermophysical properties, a component characteristic chart, and system inertial. The startup process is simulated using this model. The consistency between the simulation results and the field operation data shows the validity of the model and the advantages of transient accumulated deviation. In addition, a diagnostic scheme is designed to fulfill this process. Finally, cuckoo search is selected to solve the optimization problem in fault diagnosis. Comparative diagnostic results for a gas turbine before and after washing indicate the improved effectiveness and accuracy of the proposed method of using data from transient processes, compared with traditional methods using data from the steady state.

  19. Fault morphology of the lyo Fault, the Median Tectonic Line Active Fault System

    OpenAIRE

    後藤, 秀昭

    1996-01-01

    In this paper, we investigated the various fault features of the lyo fault and depicted fault lines or detailed topographic map. The results of this paper are summarized as follows; 1) Distinct evidence of the right-lateral movement is continuously discernible along the lyo fault. 2) Active fault traces are remarkably linear suggesting that the angle of fault plane is high. 3) The lyo fault can be divided into four segments by jogs between left-stepping traces. 4) The mean slip rate is 1.3 ~ ...

  20. A Modular Neural Network Scheme Applied to Fault Diagnosis in Electric Power Systems

    Directory of Open Access Journals (Sweden)

    Agustín Flores

    2014-01-01

    Full Text Available This work proposes a new method for fault diagnosis in electric power systems based on neural modules. With this method the diagnosis is performed by assigning a neural module for each type of component comprising the electric power system, whether it is a transmission line, bus or transformer. The neural modules for buses and transformers comprise two diagnostic levels which take into consideration the logic states of switches and relays, both internal and back-up, with the exception of the neural module for transmission lines which also has a third diagnostic level which takes into account the oscillograms of fault voltages and currents as well as the frequency spectrums of these oscillograms, in order to verify if the transmission line had in fact been subjected to a fault. One important advantage of the diagnostic system proposed is that its implementation does not require the use of a network configurator for the system; it does not depend on the size of the power network nor does it require retraining of the neural modules if the power network increases in size, making its application possible to only one component, a specific area, or the whole context of the power system.

  1. Analytical Redundancy Design for Aeroengine Sensor Fault Diagnostics Based on SROS-ELM

    Directory of Open Access Journals (Sweden)

    Jun Zhou

    2016-01-01

    Full Text Available Analytical redundancy technique is of great importance to guarantee the reliability and safety of aircraft engine system. In this paper, a machine learning based aeroengine sensor analytical redundancy technique is developed and verified through hardware-in-the-loop (HIL simulation. The modified online sequential extreme learning machine, selective updating regularized online sequential extreme learning machine (SROS-ELM, is employed to train the model online and estimate sensor measurements. It selectively updates the output weights of neural networks according to the prediction accuracy and the norm of output weight vector, tackles the problems of singularity and ill-posedness by regularization, and adopts a dual activation function in the hidden nodes combing neural and wavelet theory to enhance prediction capability. The experimental results verify the good generalization performance of SROS-ELM and show that the developed analytical redundancy technique for aeroengine sensor fault diagnosis based on SROS-ELM is effective and feasible.

  2. Fault-Tolerant Vision for Vehicle Guidance in Agriculture

    DEFF Research Database (Denmark)

    Blas, Morten Rufus

    , and aiding sensors such as GPS provide means to detect and isolate single faults in the system. In addition, learning is employed to adapt the system to variational changes in the natural environment. 3D vision is enhanced by learning texture and color information. Intensity gradients on small neighborhoods...... dropout of 3D vision, faults in classification, or other defects, redundant information should be utilized. Such information can be used to diagnose faulty behavior and to temporarily continue operation with a reduced set of sensors when faults or artifacts occur. Additional sensors include GPS receivers...... and inertial sensors. To fully utilize the possibilities in 3D vision, the system must also be able to learn and adapt to changing environments. By learning features of the environment new diagnostic relations can be generated by creating redundant feed-forward information about crop location. Also, by mapping...

  3. Integrated Fault Diagnostics of Networks and IT Systems

    Data.gov (United States)

    National Aeronautics and Space Administration — The lecture of the Stanford-IVHM lecture series will give an overview of the approaches in building diagnostic solutions for networks and complex systems. The...

  4. The mechanics of fault-bend folding and tear-fault systems in the Niger Delta

    Science.gov (United States)

    Benesh, Nathan Philip

    This dissertation investigates the mechanics of fault-bend folding using the discrete element method (DEM) and explores the nature of tear-fault systems in the deep-water Niger Delta fold-and-thrust belt. In Chapter 1, we employ the DEM to investigate the development of growth structures in anticlinal fault-bend folds. This work was inspired by observations that growth strata in active folds show a pronounced upward decrease in bed dip, in contrast to traditional kinematic fault-bend fold models. Our analysis shows that the modeled folds grow largely by parallel folding as specified by the kinematic theory; however, the process of folding over a broad axial surface zone yields a component of fold growth by limb rotation that is consistent with the patterns observed in natural folds. This result has important implications for how growth structures can he used to constrain slip and paleo-earthquake ages on active blind-thrust faults. In Chapter 2, we expand our DEM study to investigate the development of a wider range of fault-bend folds. We examine the influence of mechanical stratigraphy and quantitatively compare our models with the relationships between fold and fault shape prescribed by the kinematic theory. While the synclinal fault-bend models closely match the kinematic theory, the modeled anticlinal fault-bend folds show robust behavior that is distinct from the kinematic theory. Specifically, we observe that modeled structures maintain a linear relationship between fold shape (gamma) and fault-horizon cutoff angle (theta), rather than expressing the non-linear relationship with two distinct modes of anticlinal folding that is prescribed by the kinematic theory. These observations lead to a revised quantitative relationship for fault-bend folds that can serve as a useful interpretation tool. Finally, in Chapter 3, we examine the 3D relationships of tear- and thrust-fault systems in the western, deep-water Niger Delta. Using 3D seismic reflection data and new

  5. Fault diagnosis of sensor networked structures with multiple faults using a virtual beam based approach

    Science.gov (United States)

    Wang, H.; Jing, X. J.

    2017-07-01

    This paper presents a virtual beam based approach suitable for conducting diagnosis of multiple faults in complex structures with limited prior knowledge of the faults involved. The "virtual beam", a recently-proposed concept for fault detection in complex structures, is applied, which consists of a chain of sensors representing a vibration energy transmission path embedded in the complex structure. Statistical tests and adaptive threshold are particularly adopted for fault detection due to limited prior knowledge of normal operational conditions and fault conditions. To isolate the multiple faults within a specific structure or substructure of a more complex one, a 'biased running' strategy is developed and embedded within the bacterial-based optimization method to construct effective virtual beams and thus to improve the accuracy of localization. The proposed method is easy and efficient to implement for multiple fault localization with limited prior knowledge of normal conditions and faults. With extensive experimental results, it is validated that the proposed method can localize both single fault and multiple faults more effectively than the classical trust index subtract on negative add on positive (TI-SNAP) method.

  6. CBDS: Constraint-based diagnostic system for malfunction identification in the nuclear power plant

    International Nuclear Information System (INIS)

    Ha, J.

    1992-01-01

    Traditional rule-based diagnostic expert systems use the experience of experts in the form of rules that associate symptoms with underlying faults. A commonly recognized failing of such systems is their narrow range of expertise and their inability to recognize problems outside this range of expertise. A model base diagnostic system isolating malfunctioning components-CBDS, the Constraint based Diagnostic System-has been developed. Since the intended behavior of a device is more predictable than unintended behaviors (faults), a model based system using the intended behavior has a potential to diagnose unexpected malfunctions by considering faults as open-quotes anything other than the intended behavior.close quotes As a knowledge base, the CBDS generates and decomposes a constraint network based on the structure and behavior model, which are represented symbolically in algebraic equations. Behaviors of generic components are organized in a component model library. Once the library is available, actual domain knowledge can be represented by declaring component types and their connections. To capture various plant knowledge, the mixed model was developed which allow the use of different parameter types in one equation by defining various operators. The CBDS uses the general idea of model based diagnosis. It detects a discrepancy between observation and prediction using constraint propagation, which carriers and accumulates the assumptions when parameter values are deduced. When measured plant parameters are asserted into a constraint network and are propagated through the network, a discrepancy will be detected if there exists any malfunctioning component. The CBDS was tested in the Recirculation Flow Control System of a BWR, and has been shown to be able to diagnose unexpected events

  7. Democratizing molecular diagnostics for the developing world.

    Science.gov (United States)

    Abou Tayoun, Ahmad N; Burchard, Paul R; Malik, Imran; Scherer, Axel; Tsongalis, Gregory J

    2014-01-01

    Infectious diseases that are largely treatable continue to pose a tremendous burden on the developing world despite the availability of highly potent drugs. The high mortality and morbidity rates of these diseases are largely due to a lack of affordable diagnostics that are accessible to resource-limited areas and that can deliver high-quality results. In fact, modified molecular diagnostics for infectious diseases were rated as the top biotechnology to improve health in developing countries. In this review, we describe the characteristics of accessible molecular diagnostic tools and discuss the challenges associated with implementing such tools at low infrastructure sites. We highlight our experience as part of the "Grand Challenge" project supported by the Gates Foundation for addressing global health inequities and describe issues and solutions associated with developing adequate technologies or molecular assays needed for broad access in the developing world. We believe that sharing this knowledge will facilitate the development of new molecular technologies that are extremely valuable for improving global health.

  8. Application of fault current limiters

    Energy Technology Data Exchange (ETDEWEB)

    Neumann, A.

    2007-11-30

    This report presents the results of a study commissioned by the Department for Business, Enterprise and Industry (BERR; formerly the Department of Trade and Industry) into the application of fault current limiters in the UK. The study reviewed the current state of fault current limiter (FCL) technology and regulatory position in relation to all types of current limiters. It identified significant research and development work with respect to medium voltage FCLs and a move to high voltage. Appropriate FCL technologies being developed include: solid state breakers; superconducting FCLs (including superconducting transformers); magnetic FCLs; and active network controllers. Commercialisation of these products depends on successful field tests and experience, plus material development in the case of high temperature superconducting FCL technologies. The report describes FCL techniques, the current state of FCL technologies, practical applications and future outlook for FCL technologies, distribution fault level analysis and an outline methodology for assessing the materiality of the fault level problem. A roadmap is presented that provides an 'action agenda' to advance the fault level issues associated with low carbon networks.

  9. An artificial neural network ensemble method for fault diagnosis of proton exchange membrane fuel cell system

    International Nuclear Information System (INIS)

    Shao, Meng; Zhu, Xin-Jian; Cao, Hong-Fei; Shen, Hai-Feng

    2014-01-01

    The commercial viability of PEMFC (proton exchange membrane fuel cell) systems depends on using effective fault diagnosis technologies in PEMFC systems. However, many researchers have experimentally studied PEMFC (proton exchange membrane fuel cell) systems without considering certain fault conditions. In this paper, an ANN (artificial neural network) ensemble method is presented that improves the stability and reliability of the PEMFC systems. In the first part, a transient model giving it flexibility in application to some exceptional conditions is built. The PEMFC dynamic model is built and simulated using MATLAB. In the second, using this model and experiments, the mechanisms of four different faults in PEMFC systems are analyzed in detail. Third, the ANN ensemble for the fault diagnosis is built and modeled. This model is trained and tested by the data. The test result shows that, compared with the previous method for fault diagnosis of PEMFC systems, the proposed fault diagnosis method has higher diagnostic rate and generalization ability. Moreover, the partial structure of this method can be altered easily, along with the change of the PEMFC systems. In general, this method for diagnosis of PEMFC has value for certain applications. - Highlights: • We analyze the principles and mechanisms of the four faults in PEMFC (proton exchange membrane fuel cell) system. • We design and model an ANN (artificial neural network) ensemble method for the fault diagnosis of PEMFC system. • This method has high diagnostic rate and strong generalization ability

  10. Fault Management Assistant (FMA), Phase I

    Data.gov (United States)

    National Aeronautics and Space Administration — S&K Aerospace (SKA) proposes to develop the Fault Management Assistant (FMA) to aid project managers and fault management engineers in developing better and more...

  11. Active Fault-Tolerant Control for Wind Turbine with Simultaneous Actuator and Sensor Faults

    Directory of Open Access Journals (Sweden)

    Lei Wang

    2017-01-01

    Full Text Available The purpose of this paper is to show a novel fault-tolerant tracking control (FTC strategy with robust fault estimation and compensating for simultaneous actuator sensor faults. Based on the framework of fault-tolerant control, developing an FTC design method for wind turbines is a challenge and, thus, they can tolerate simultaneous pitch actuator and pitch sensor faults having bounded first time derivatives. The paper’s key contribution is proposing a descriptor sliding mode method, in which for establishing a novel augmented descriptor system, with which we can estimate the state of system and reconstruct fault by designing descriptor sliding mode observer, the paper introduces an auxiliary descriptor state vector composed by a system state vector, actuator fault vector, and sensor fault vector. By the optimized method of LMI, the conditions for stability that estimated error dynamics are set up to promote the determination of the parameters designed. With this estimation, and designing a fault-tolerant controller, the system’s stability can be maintained. The effectiveness of the design strategy is verified by implementing the controller in the National Renewable Energy Laboratory’s 5-MW nonlinear, high-fidelity wind turbine model (FAST and simulating it in MATLAB/Simulink.

  12. Late quaternary faulting along the Death Valley-Furnace Creek fault system, California and Nevada

    International Nuclear Information System (INIS)

    Brogan, G.E.; Kellogg, K.S.; Terhune, C.L.; Slemmons, D.B.

    1991-01-01

    The Death Valley-Furnace Creek fault system, in California and Nevada, has a variety of impressive late Quaternary neotectonic features that record a long history of recurrent earthquake-induced faulting. Although no neotectonic features of unequivocal historical age are known, paleoseismic features from multiple late Quaternary events of surface faulting are well developed throughout the length of the system. Comparison of scarp heights to amount of horizontal offset of stream channels and the relationships of both scarps and channels to the ages of different geomorphic surfaces demonstrate that Quaternary faulting along the northwest-trending Furnace Creek fault zone is predominantly right lateral, whereas that along the north-trending Death Valley fault zone is predominantly normal. These observations are compatible with tectonic models of Death Valley as a northwest- trending pull-apart basin

  13. Development of a Methodology for Hydrogeological Characterization of Faults: Progress of the Project in Berkeley, California

    Science.gov (United States)

    Goto, J.; Moriya, T.; Yoshimura, K.; Tsuchi, H.; Karasaki, K.; Onishi, T.; Ueta, K.; Tanaka, S.; Kiho, K.

    2010-12-01

    The Nuclear Waste Management Organization of Japan (NUMO), in collaboration with Lawrence Berkeley National Laboratory (LBNL), has carried out a project to develop an efficient and practical methodology to characterize hydrologic property of faults since 2007, exclusively for the early stage of siting a deep underground repository. A preliminary flowchart of the characterization program and a classification scheme of fault hydrology based on the geological feature have been proposed. These have been tested through the field characterization program on the Wildcat Fault in Berkeley, California. The Wildcat Fault is a relatively large non-active strike-slip fault which is believed to be a subsidiary of the active Hayward Fault. Our classification scheme assumes the contrasting hydrologic features between the linear northern part and the split/spread southern part of the Wildcat Fault. The field characterization program to date has been concentrated in and around the LBNL site on the southern part of the fault. Several lines of electrical and reflection seismic surveys, and subsequent trench investigations, have revealed the approximate distribution and near-surface features of the Wildcat Fault (see also Onishi, et al. and Ueta, et al.). Three 150m deep boreholes, WF-1 to WF-3, have been drilled on a line normal to the trace of the fault in the LBNL site. Two vertical holes were placed to characterize the undisturbed Miocene sedimentary formations at the eastern and western sides of the fault (WF-1 and WF-2 respectively). WF-2 on the western side intersected the rock formation, which was expected only in WF-1, and several of various intensities. Therefore, WF-3, originally planned as inclined to penetrate the fault, was replaced by the vertical hole further to the west. It again encountered unexpected rocks and faults. Preliminary results of in-situ hydraulic tests suggested that the transmissivity of WF-1 is ten to one hundred times higher than WF-2. The monitoring

  14. On-Line Fault Detection in Wind Turbine Transmission System using Adaptive Filter and Robust Statistical Features

    Directory of Open Access Journals (Sweden)

    Mark Frogley

    2013-01-01

    Full Text Available To reduce the maintenance cost, avoid catastrophic failure, and improve the wind transmission system reliability, online condition monitoring system is critical important. In the real applications, many rotating mechanical faults, such as bearing surface defect, gear tooth crack, chipped gear tooth and so on generate impulsive signals. When there are these types of faults developing inside rotating machinery, each time the rotating components pass over the damage point, an impact force could be generated. The impact force will cause a ringing of the support structure at the structural natural frequency. By effectively detecting those periodic impulse signals, one group of rotating machine faults could be detected and diagnosed. However, in real wind turbine operations, impulsive fault signals are usually relatively weak to the background noise and vibration signals generated from other healthy components, such as shaft, blades, gears and so on. Moreover, wind turbine transmission systems work under dynamic operating conditions. This will further increase the difficulties in fault detection and diagnostics. Therefore, developing advanced signal processing methods to enhance the impulsive signals is in great needs.In this paper, an adaptive filtering technique will be applied for enhancing the fault impulse signals-to-noise ratio in wind turbine gear transmission systems. Multiple statistical features designed to quantify the impulsive signals of the processed signal are extracted for bearing fault detection. The multiple dimensional features are then transformed into one dimensional feature. A minimum error rate classifier will be designed based on the compressed feature to identify the gear transmission system with defect. Real wind turbine vibration signals will be used to demonstrate the effectiveness of the presented methodology.

  15. Functional Fault Model Development Process to Support Design Analysis and Operational Assessment

    Science.gov (United States)

    Melcher, Kevin J.; Maul, William A.; Hemminger, Joseph A.

    2016-01-01

    A functional fault model (FFM) is an abstract representation of the failure space of a given system. As such, it simulates the propagation of failure effects along paths between the origin of the system failure modes and points within the system capable of observing the failure effects. As a result, FFMs may be used to diagnose the presence of failures in the modeled system. FFMs necessarily contain a significant amount of information about the design, operations, and failure modes and effects. One of the important benefits of FFMs is that they may be qualitative, rather than quantitative and, as a result, may be implemented early in the design process when there is more potential to positively impact the system design. FFMs may therefore be developed and matured throughout the monitored system's design process and may subsequently be used to provide real-time diagnostic assessments that support system operations. This paper provides an overview of a generalized NASA process that is being used to develop and apply FFMs. FFM technology has been evolving for more than 25 years. The FFM development process presented in this paper was refined during NASA's Ares I, Space Launch System, and Ground Systems Development and Operations programs (i.e., from about 2007 to the present). Process refinement took place as new modeling, analysis, and verification tools were created to enhance FFM capabilities. In this paper, standard elements of a model development process (i.e., knowledge acquisition, conceptual design, implementation & verification, and application) are described within the context of FFMs. Further, newer tools and analytical capabilities that may benefit the broader systems engineering process are identified and briefly described. The discussion is intended as a high-level guide for future FFM modelers.

  16. Methods for Probabilistic Fault Diagnosis: An Electrical Power System Case Study

    Science.gov (United States)

    Ricks, Brian W.; Mengshoel, Ole J.

    2009-01-01

    Health management systems that more accurately and quickly diagnose faults that may occur in different technical systems on-board a vehicle will play a key role in the success of future NASA missions. We discuss in this paper the diagnosis of abrupt continuous (or parametric) faults within the context of probabilistic graphical models, more specifically Bayesian networks that are compiled to arithmetic circuits. This paper extends our previous research, within the same probabilistic setting, on diagnosis of abrupt discrete faults. Our approach and diagnostic algorithm ProDiagnose are domain-independent; however we use an electrical power system testbed called ADAPT as a case study. In one set of ADAPT experiments, performed as part of the 2009 Diagnostic Challenge, our system turned out to have the best performance among all competitors. In a second set of experiments, we show how we have recently further significantly improved the performance of the probabilistic model of ADAPT. While these experiments are obtained for an electrical power system testbed, we believe they can easily be transitioned to real-world systems, thus promising to increase the success of future NASA missions.

  17. Overview of condition monitoring and operation control of electric power conversion systems in direct-drive wind turbines under faults

    Science.gov (United States)

    Huang, Shoudao; Wu, Xuan; Liu, Xiao; Gao, Jian; He, Yunze

    2017-09-01

    Electric power conversion system (EPCS), which consists of a generator and power converter, is one of the most important subsystems in a direct-drive wind turbine (DD-WT). However, this component accounts for the most failures (approximately 60% of the total number) in the entire DD-WT system according to statistical data. To improve the reliability of EPCSs and reduce the operation and maintenance cost of DD-WTs, numerous researchers have studied condition monitoring (CM) and fault diagnostics (FD). Numerous CM and FD techniques, which have respective advantages and disadvantages, have emerged. This paper provides an overview of the CM, FD, and operation control of EPCSs in DD-WTs under faults. After introducing the functional principle and structure of EPCS, this survey discusses the common failures in wind generators and power converters; briefly reviewed CM and FD methods and operation control of these generators and power converters under faults; and discussed the grid voltage faults related to EPCSs in DD-WTs. These theories and their related technical concepts are systematically discussed. Finally, predicted development trends are presented. The paper provides a valuable reference for developing service quality evaluation methods and fault operation control systems to achieve high-performance and high-intelligence DD-WTs.

  18. Fault tolerant control based on active fault diagnosis

    DEFF Research Database (Denmark)

    Niemann, Hans Henrik

    2005-01-01

    An active fault diagnosis (AFD) method will be considered in this paper in connection with a Fault Tolerant Control (FTC) architecture based on the YJBK parameterization of all stabilizing controllers. The architecture consists of a fault diagnosis (FD) part and a controller reconfiguration (CR......) part. The FTC architecture can be applied for additive faults, parametric faults, and for system structural changes. Only parametric faults will be considered in this paper. The main focus in this paper is on the use of the new approach of active fault diagnosis in connection with FTC. The active fault...... diagnosis approach is based on including an auxiliary input in the system. A fault signature matrix is introduced in connection with AFD, given as the transfer function from the auxiliary input to the residual output. This can be considered as a generalization of the passive fault diagnosis case, where...

  19. Early fault detection and on-line diagnosis in real-time environments

    Directory of Open Access Journals (Sweden)

    Andreas Bye

    1993-01-01

    Full Text Available This paper describes an approach to fault detection and diagnosis involving the simultaneous employment of quantitative and qualitative reasoning techniques. We show that early identification of process anomalies by means of a separate fault detection module paves the way for a fast and accuratc follow-up diagnosis. The diagnosis task is dramatically simplified because the diagnostic inferences can be performed at the soonest possible time: when the detection module first spots deviations between its calculated reference points and the corresponding measurements from the process.

  20. Fault diagnosis method based on FFT-RPCA-SVM for Cascaded-Multilevel Inverter.

    Science.gov (United States)

    Wang, Tianzhen; Qi, Jie; Xu, Hao; Wang, Yide; Liu, Lei; Gao, Diju

    2016-01-01

    Thanks to reduced switch stress, high quality of load wave, easy packaging and good extensibility, the cascaded H-bridge multilevel inverter is widely used in wind power system. To guarantee stable operation of system, a new fault diagnosis method, based on Fast Fourier Transform (FFT), Relative Principle Component Analysis (RPCA) and Support Vector Machine (SVM), is proposed for H-bridge multilevel inverter. To avoid the influence of load variation on fault diagnosis, the output voltages of the inverter is chosen as the fault characteristic signals. To shorten the time of diagnosis and improve the diagnostic accuracy, the main features of the fault characteristic signals are extracted by FFT. To further reduce the training time of SVM, the feature vector is reduced based on RPCA that can get a lower dimensional feature space. The fault classifier is constructed via SVM. An experimental prototype of the inverter is built to test the proposed method. Compared to other fault diagnosis methods, the experimental results demonstrate the high accuracy and efficiency of the proposed method. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

  1. Artificial intelligence applications to nuclear reactor diagnostics

    International Nuclear Information System (INIS)

    Lee, J.C.; Hassberger, J.A.; Wehe, D.K.

    1987-01-01

    The authors research into applications of artificial intelligence to nuclear reactor diagnostics involves three main areas. In the first area, the authors combine reactor simulation models and expert systems to diagnose the state of the plant. The second area examines ways in which the rule or knowledge base of an intelligent controller can be generated systematically from either fault trees or acquired plant data. Third, efforts are described to develop the capabilities to validate these techniques in a realistic reactor setting. The techniques are applicable to all reactor types, including fast reactors

  2. Scissoring Fault Rupture Properties along the Median Tectonic Line Fault Zone, Southwest Japan

    Science.gov (United States)

    Ikeda, M.; Nishizaka, N.; Onishi, K.; Sakamoto, J.; Takahashi, K.

    2017-12-01

    The Median Tectonic Line fault zone (hereinafter MTLFZ) is the longest and most active fault zone in Japan. The MTLFZ is a 400-km-long trench parallel right-lateral strike-slip fault accommodating lateral slip components of the Philippine Sea plate oblique subduction beneath the Eurasian plate [Fitch, 1972; Yeats, 1996]. Complex fault geometry evolves along the MTLFZ. The geomorphic and geological characteristics show a remarkable change through the MTLFZ. Extensional step-overs and pull-apart basins and a pop-up structure develop in western and eastern parts of the MTLFZ, respectively. It is like a "scissoring fault properties". We can point out two main factors to form scissoring fault properties along the MTLFZ. One is a regional stress condition, and another is a preexisting fault. The direction of σ1 anticlockwise rotate from N170°E [Famin et al., 2014] in the eastern Shikoku to Kinki areas and N100°E [Research Group for Crustral Stress in Western Japan, 1980] in central Shikoku to N85°E [Onishi et al., 2016] in western Shikoku. According to the rotation of principal stress directions, the western and eastern parts of the MTLFZ are to be a transtension and compression regime, respectively. The MTLFZ formed as a terrain boundary at Cretaceous, and has evolved with a long active history. The fault style has changed variously, such as left-lateral, thrust, normal and right-lateral. Under the structural condition of a preexisting fault being, the rupture does not completely conform to Anderson's theory for a newly formed fault, as the theory would require either purely dip-slip motion on the 45° dipping fault or strike-slip motion on a vertical fault. The fault rupture of the 2013 Barochistan earthquake in Pakistan is a rare example of large strike-slip reactivation on a relatively low angle dipping fault (thrust fault), though many strike-slip faults have vertical plane generally [Avouac et al., 2014]. In this presentation, we, firstly, show deep subsurface

  3. Two sides of a fault: Grain-scale analysis of pore pressure control on fault slip.

    Science.gov (United States)

    Yang, Zhibing; Juanes, Ruben

    2018-02-01

    Pore fluid pressure in a fault zone can be altered by natural processes (e.g., mineral dehydration and thermal pressurization) and industrial operations involving subsurface fluid injection and extraction for the development of energy and water resources. However, the effect of pore pressure change on the stability and slip motion of a preexisting geologic fault remains poorly understood; yet, it is critical for the assessment of seismic hazard. Here, we develop a micromechanical model to investigate the effect of pore pressure on fault slip behavior. The model couples fluid flow on the network of pores with mechanical deformation of the skeleton of solid grains. Pore fluid exerts pressure force onto the grains, the motion of which is solved using the discrete element method. We conceptualize the fault zone as a gouge layer sandwiched between two blocks. We study fault stability in the presence of a pressure discontinuity across the gouge layer and compare it with the case of continuous (homogeneous) pore pressure. We focus on the onset of shear failure in the gouge layer and reproduce conditions where the failure plane is parallel to the fault. We show that when the pressure is discontinuous across the fault, the onset of slip occurs on the side with the higher pore pressure, and that this onset is controlled by the maximum pressure on both sides of the fault. The results shed new light on the use of the effective stress principle and the Coulomb failure criterion in evaluating the stability of a complex fault zone.

  4. Two sides of a fault: Grain-scale analysis of pore pressure control on fault slip

    Science.gov (United States)

    Yang, Zhibing; Juanes, Ruben

    2018-02-01

    Pore fluid pressure in a fault zone can be altered by natural processes (e.g., mineral dehydration and thermal pressurization) and industrial operations involving subsurface fluid injection and extraction for the development of energy and water resources. However, the effect of pore pressure change on the stability and slip motion of a preexisting geologic fault remains poorly understood; yet, it is critical for the assessment of seismic hazard. Here, we develop a micromechanical model to investigate the effect of pore pressure on fault slip behavior. The model couples fluid flow on the network of pores with mechanical deformation of the skeleton of solid grains. Pore fluid exerts pressure force onto the grains, the motion of which is solved using the discrete element method. We conceptualize the fault zone as a gouge layer sandwiched between two blocks. We study fault stability in the presence of a pressure discontinuity across the gouge layer and compare it with the case of continuous (homogeneous) pore pressure. We focus on the onset of shear failure in the gouge layer and reproduce conditions where the failure plane is parallel to the fault. We show that when the pressure is discontinuous across the fault, the onset of slip occurs on the side with the higher pore pressure, and that this onset is controlled by the maximum pressure on both sides of the fault. The results shed new light on the use of the effective stress principle and the Coulomb failure criterion in evaluating the stability of a complex fault zone.

  5. Fault detection and isolation in systems with parametric faults

    DEFF Research Database (Denmark)

    Stoustrup, Jakob; Niemann, Hans Henrik

    1999-01-01

    The problem of fault detection and isolation of parametric faults is considered in this paper. A fault detection problem based on parametric faults are associated with internal parameter variations in the dynamical system. A fault detection and isolation method for parametric faults is formulated...

  6. Heterogeneity in the Fault Damage Zone: a Field Study on the Borrego Fault, B.C., Mexico

    Science.gov (United States)

    Ostermeijer, G.; Mitchell, T. M.; Dorsey, M. T.; Browning, J.; Rockwell, T. K.; Aben, F. M.; Fletcher, J. M.; Brantut, N.

    2017-12-01

    The nature and distribution of damage around faults, and its impacts on fault zone properties has been a hot topic of research over the past decade. Understanding the mechanisms that control the formation of off fault damage can shed light on the processes during the seismic cycle, and the nature of fault zone development. Recent published work has identified three broad zones of damage around most faults based on the type, intensity, and extent of fracturing; Tip, Wall, and Linking damage. Although these zones are able to adequately characterise the general distribution of damage, little has been done to identify the nature of damage heterogeneity within those zones, often simplifying the distribution to fit log-normal linear decay trends. Here, we attempt to characterise the distribution of fractures that make up the wall damage around seismogenic faults. To do so, we investigate an extensive two dimensional fracture network exposed on a river cut platform along the Borrego Fault, BC, Mexico, 5m wide, and extending 20m from the fault core into the damage zone. High resolution fracture mapping of the outcrop, covering scales ranging three orders of magnitude (cm to m), has allowed for detailed observations of the 2D damage distribution within the fault damage zone. Damage profiles were obtained along several 1D transects perpendicular to the fault and micro-damage was examined from thin-sections at various locations around the outcrop for comparison. Analysis of the resulting fracture network indicates heterogeneities in damage intensity at decimetre scales resulting from a patchy distribution of high and low intensity corridors and clusters. Such patchiness may contribute to inconsistencies in damage zone widths defined along 1D transects and the observed variability of fracture densities around decay trends. How this distribution develops with fault maturity and the scaling of heterogeneities above and below the observed range will likely play a key role in

  7. Comparison of Cenozoic Faulting at the Savannah River Site to Fault Characteristics of the Atlantic Coast Fault Province: Implications for Fault Capability

    International Nuclear Information System (INIS)

    Cumbest, R.J.

    2000-01-01

    This study compares the faulting observed on the Savannah River Site and vicinity with the faults of the Atlantic Coastal Fault Province and concludes that both sets of faults exhibit the same general characteristics and are closely associated. Based on the strength of this association it is concluded that the faults observed on the Savannah River Site and vicinity are in fact part of the Atlantic Coastal Fault Province. Inclusion in this group means that the historical precedent established by decades of previous studies on the seismic hazard potential for the Atlantic Coastal Fault Province is relevant to faulting at the Savannah River Site. That is, since these faults are genetically related the conclusion of ''not capable'' reached in past evaluations applies.In addition, this study establishes a set of criteria by which individual faults may be evaluated in order to assess their inclusion in the Atlantic Coast Fault Province and the related association of the ''not capable'' conclusion

  8. Entropy-Based Voltage Fault Diagnosis of Battery Systems for Electric Vehicles

    Directory of Open Access Journals (Sweden)

    Peng Liu

    2018-01-01

    Full Text Available The battery is a key component and the major fault source in electric vehicles (EVs. Ensuring power battery safety is of great significance to make the diagnosis more effective and predict the occurrence of faults, for the power battery is one of the core technologies of EVs. This paper proposes a voltage fault diagnosis detection mechanism using entropy theory which is demonstrated in an EV with a multiple-cell battery system during an actual operation situation. The preliminary analysis, after collecting and preprocessing the typical data periods from Operation Service and Management Center for Electric Vehicle (OSMC-EV in Beijing, shows that overvoltage fault for Li-ion batteries cell can be observed from the voltage curves. To further locate abnormal cells and predict faults, an entropy weight method is established to calculate the objective weight, which reduces the subjectivity and improves the reliability. The result clearly identifies the abnormity of cell voltage. The proposed diagnostic model can be used for EV real-time diagnosis without laboratory testing methods. It is more effective than traditional methods based on contrastive analysis.

  9. The role of bed-parallel slip in the development of complex normal fault zones

    Science.gov (United States)

    Delogkos, Efstratios; Childs, Conrad; Manzocchi, Tom; Walsh, John J.; Pavlides, Spyros

    2017-04-01

    Normal faults exposed in Kardia lignite mine, Ptolemais Basin, NW Greece formed at the same time as bed-parallel slip-surfaces, so that while the normal faults grew they were intermittently offset by bed-parallel slip. Following offset by a bed-parallel slip-surface, further fault growth is accommodated by reactivation on one or both of the offset fault segments. Where one fault is reactivated the site of bed-parallel slip is a bypassed asperity. Where both faults are reactivated, they propagate past each other to form a volume between overlapping fault segments that displays many of the characteristics of relay zones, including elevated strains and transfer of displacement between segments. Unlike conventional relay zones, however, these structures contain either a repeated or a missing section of stratigraphy which has a thickness equal to the throw of the fault at the time of the bed-parallel slip event, and the displacement profiles along the relay-bounding fault segments have discrete steps at their intersections with bed-parallel slip-surfaces. With further increase in displacement, the overlapping fault segments connect to form a fault-bound lens. Conventional relay zones form during initial fault propagation, but with coeval bed-parallel slip, relay-like structures can form later in the growth of a fault. Geometrical restoration of cross-sections through selected faults shows that repeated bed-parallel slip events during fault growth can lead to complex internal fault zone structure that masks its origin. Bed-parallel slip, in this case, is attributed to flexural-slip arising from hanging-wall rollover associated with a basin-bounding fault outside the study area.

  10. A Method for Aileron Actuator Fault Diagnosis Based on PCA and PGC-SVM

    Directory of Open Access Journals (Sweden)

    Wei-Li Qin

    2016-01-01

    Full Text Available Aileron actuators are pivotal components for aircraft flight control system. Thus, the fault diagnosis of aileron actuators is vital in the enhancement of the reliability and fault tolerant capability. This paper presents an aileron actuator fault diagnosis approach combining principal component analysis (PCA, grid search (GS, 10-fold cross validation (CV, and one-versus-one support vector machine (SVM. This method is referred to as PGC-SVM and utilizes the direct drive valve input, force motor current, and displacement feedback signal to realize fault detection and location. First, several common faults of aileron actuators, which include force motor coil break, sensor coil break, cylinder leakage, and amplifier gain reduction, are extracted from the fault quadrantal diagram; the corresponding fault mechanisms are analyzed. Second, the data feature extraction is performed with dimension reduction using PCA. Finally, the GS and CV algorithms are employed to train a one-versus-one SVM for fault classification, thus obtaining the optimal model parameters and assuring the generalization of the trained SVM, respectively. To verify the effectiveness of the proposed approach, four types of faults are introduced into the simulation model established by AMESim and Simulink. The results demonstrate its desirable diagnostic performance which outperforms that of the traditional SVM by comparison.

  11. How fault evolution changes strain partitioning and fault slip rates in Southern California: Results from geodynamic modeling

    Science.gov (United States)

    Ye, Jiyang; Liu, Mian

    2017-08-01

    In Southern California, the Pacific-North America relative plate motion is accommodated by the complex southern San Andreas Fault system that includes many young faults (faults and their impact on strain partitioning and fault slip rates are important for understanding the evolution of this plate boundary zone and assessing earthquake hazard in Southern California. Using a three-dimensional viscoelastoplastic finite element model, we have investigated how this plate boundary fault system has evolved to accommodate the relative plate motion in Southern California. Our results show that when the plate boundary faults are not optimally configured to accommodate the relative plate motion, strain is localized in places where new faults would initiate to improve the mechanical efficiency of the fault system. In particular, the Eastern California Shear Zone, the San Jacinto Fault, the Elsinore Fault, and the offshore dextral faults all developed in places of highly localized strain. These younger faults compensate for the reduced fault slip on the San Andreas Fault proper because of the Big Bend, a major restraining bend. The evolution of the fault system changes the apportionment of fault slip rates over time, which may explain some of the slip rate discrepancy between geological and geodetic measurements in Southern California. For the present fault configuration, our model predicts localized strain in western Transverse Ranges and along the dextral faults across the Mojave Desert, where numerous damaging earthquakes occurred in recent years.

  12. SDEM modelling of fault-propagation folding

    DEFF Research Database (Denmark)

    Clausen, O.R.; Egholm, D.L.; Poulsen, Jane Bang

    2009-01-01

    and variations in Mohr-Coulomb parameters including internal friction. Using SDEM modelling, we have mapped the propagation of the tip-line of the fault, as well as the evolution of the fold geometry across sedimentary layers of contrasting rheological parameters, as a function of the increased offset......Understanding the dynamics and kinematics of fault-propagation-folding is important for evaluating the associated hydrocarbon play, for accomplishing reliable section balancing (structural reconstruction), and for assessing seismic hazards. Accordingly, the deformation style of fault-propagation...... a precise indication of when faults develop and hence also the sequential evolution of secondary faults. Here we focus on the generation of a fault -propagated fold with a reverse sense of motion at the master fault, and varying only the dip of the master fault and the mechanical behaviour of the deformed...

  13. Fault Injection and Monitoring Capability for a Fault-Tolerant Distributed Computation System

    Science.gov (United States)

    Torres-Pomales, Wilfredo; Yates, Amy M.; Malekpour, Mahyar R.

    2010-01-01

    The Configurable Fault-Injection and Monitoring System (CFIMS) is intended for the experimental characterization of effects caused by a variety of adverse conditions on a distributed computation system running flight control applications. A product of research collaboration between NASA Langley Research Center and Old Dominion University, the CFIMS is the main research tool for generating actual fault response data with which to develop and validate analytical performance models and design methodologies for the mitigation of fault effects in distributed flight control systems. Rather than a fixed design solution, the CFIMS is a flexible system that enables the systematic exploration of the problem space and can be adapted to meet the evolving needs of the research. The CFIMS has the capabilities of system-under-test (SUT) functional stimulus generation, fault injection and state monitoring, all of which are supported by a configuration capability for setting up the system as desired for a particular experiment. This report summarizes the work accomplished so far in the development of the CFIMS concept and documents the first design realization.

  14. In Depth Diagnostics for RF System Operation in the PEP-II B Factory

    International Nuclear Information System (INIS)

    Van Winkle, Daniel; Fox, John; Teytelman, Dmitry; SLAC

    2005-01-01

    The PEP-II RF systems incorporate numerous feedback loops in the low-level processing for impedance control and operating point regulation. The interaction of the multiple loops with the beam is complicated, and the systems incorporate online diagnostic tools to configure the feedback loops as well as to record fault files in the case of an RF abort. Rapid and consistent analysis of the RF-related beam aborts and other failures is critical to the reliable operation of the B-Factory, especially at the recently achieved high beam currents. Procedures and algorithms used to extract diagnostic information from time domain fault files are presented and illustrated via example interpretations of PEP-II fault file data. Example faults presented will highlight the subtle interpretation required to determine the root cause. Some such examples are: abort kicker firing asynchronously, klystron and cavity arcs, beam loss leading to longitudinal instability, tuner read back jumps and poorly configured low-level RF feedback loop

  15. Reverse fault growth and fault interaction with frictional interfaces: insights from analogue models

    Science.gov (United States)

    Bonanno, Emanuele; Bonini, Lorenzo; Basili, Roberto; Toscani, Giovanni; Seno, Silvio

    2017-04-01

    The association of faulting and folding is a common feature in mountain chains, fold-and-thrust belts, and accretionary wedges. Kinematic models are developed and widely used to explain a range of relationships between faulting and folding. However, these models may result not to be completely appropriate to explain shortening in mechanically heterogeneous rock bodies. Weak layers, bedding surfaces, or pre-existing faults placed ahead of a propagating fault tip may influence the fault propagation rate itself and the associated fold shape. In this work, we employed clay analogue models to investigate how mechanical discontinuities affect the propagation rate and the associated fold shape during the growth of reverse master faults. The simulated master faults dip at 30° and 45°, recalling the range of the most frequent dip angles for active reverse faults that occurs in nature. The mechanical discontinuities are simulated by pre-cutting the clay pack. For both experimental setups (30° and 45° dipping faults) we analyzed three different configurations: 1) isotropic, i.e. without precuts; 2) with one precut in the middle of the clay pack; and 3) with two evenly-spaced precuts. To test the repeatability of the processes and to have a statistically valid dataset we replicate each configuration three times. The experiments were monitored by collecting successive snapshots with a high-resolution camera pointing at the side of the model. The pictures were then processed using the Digital Image Correlation method (D.I.C.), in order to extract the displacement and shear-rate fields. These two quantities effectively show both the on-fault and off-fault deformation, indicating the activity along the newly-formed faults and whether and at what stage the discontinuities (precuts) are reactivated. To study the fault propagation and fold shape variability we marked the position of the fault tips and the fold profiles for every successive step of deformation. Then we compared

  16. Quaternary fault in Hwalseong-ri, Oedong-up, Gyeongju, Korea.

    Energy Technology Data Exchange (ETDEWEB)

    Ryoo, Chung-Ryul; Chwae, Uee-Chan; Choi, Sung-Ja [Korea Institute of Geoscience and Mineral Resources, Taejeon(Korea); Son, Moon [Pusan National University, Pusan(Korea)

    2001-09-01

    We describe a Quaternary fault occurring in Hwalseong-ri, Oedong-up, Gyeongju in the eastern part of Ulsan Fault Zone, Korea. This fault (Hwalseongri Fault) is developed around the contact between the early Tertiary granite and the Quaternary gravel layer. Four different faults are distinguished from west to east: (1) fault within Quaternary gravel layer, (2) fault between Quaternary gravel layer and granite, (3) fault between Quaternary gravel layer overlying granite and granite, (4) fault between granite and Quaternary layer. General strike of the fault zone vary from NNW to NE, dipping to east. Two striations, E-W and N-S, are developed. The former is related mainly to the reverse faulting, and the latter to the sinistral shearing. This fault zone was reactivated, and considered as a positive flower structure mainly by the results of the E-W compression in the southeastern part of the Korean Peninsula during Quaternary. (author). 45 refs., 6 figs.

  17. Expert system for fast reactor diagnostic

    International Nuclear Information System (INIS)

    Parcy, J.P.

    1982-09-01

    A general description of expert systems is given. The operation of a fast reactor is reviewed. The expert system to the diagnosis of breakdowns limited to the reactor core. The structure of the system is described: specification of the diagnostics; structure of the data bank and evaluation of the rules; specification of the prediagnostics and evaluation; explanation of the diagnostics; time evolution of the system; comparison with other expert systems. Applications to some cases of faults are finally presented [fr

  18. Analytical Approaches to Guide SLS Fault Management (FM) Development

    Science.gov (United States)

    Patterson, Jonathan D.

    2012-01-01

    Extensive analysis is needed to determine the right set of FM capabilities to provide the most coverage without significantly increasing the cost, reliability (FP/FN), and complexity of the overall vehicle systems. Strong collaboration with the stakeholders is required to support the determination of the best triggers and response options. The SLS Fault Management process has been documented in the Space Launch System Program (SLSP) Fault Management Plan (SLS-PLAN-085).

  19. Experimental Investigation for Fault Diagnosis Based on a Hybrid Approach Using Wavelet Packet and Support Vector Classification

    Directory of Open Access Journals (Sweden)

    Pengfei Li

    2014-01-01

    Full Text Available To deal with the difficulty to obtain a large number of fault samples under the practical condition for mechanical fault diagnosis, a hybrid method that combined wavelet packet decomposition and support vector classification (SVC is proposed. The wavelet packet is employed to decompose the vibration signal to obtain the energy ratio in each frequency band. Taking energy ratios as feature vectors, the pattern recognition results are obtained by the SVC. The rolling bearing and gear fault diagnostic results of the typical experimental platform show that the present approach is robust to noise and has higher classification accuracy and, thus, provides a better way to diagnose mechanical faults under the condition of small fault samples.

  20. Characterization of the San Andreas Fault near Parkfield, California by fault-zone trapped waves

    Science.gov (United States)

    Li, Y.; Vidale, J.; Cochran, E.

    2003-04-01

    In October, 2002, coordinated by the Pre-EarthScope/SAFOD, we conducted an extensive seismic experiment at the San Andreas fault (SAF), Parkfield to record fault-zone trapped waves generated by explosions and microearthquakes using dense linear seismic arrays of 52 PASSCAL 3-channel REFTEKs deployed across and along the fault zone. We detonated 3 explosions within and out of the fault zone during the experiment, and also recorded other 13 shots of PASO experiment of UWM/RPI (Thurber and Roecker) detonated around the SAFOD drilling site at the same time. We observed prominent fault-zone trapped waves with large amplitudes and long duration following S waves at stations close to the main fault trace for sources located within and close to the fault zone. Dominant frequencies of trapped waves are 2-3 Hz for near-surface explosions and 4-5 Hz for microearthquakes. Fault-zone trapped waves are relatively weak on the north strand of SAF for same sources. In contrast, seismograms registered for both the stations and shots far away from the fault zone show a brief S wave and lack of trapped waves. These observations are consistent with previous findings of fault-zone trapped waves at the SAF [Li et al., 1990; 1997], indicating the existence of a well-developed low-velocity waveguide along the main fault strand (principal slip plan) of the SAF. The data from denser arrays and 3-D finite-difference simulations of fault-zone trapped waves allowed us to delineate the internal structure, segmentation and physical properties of the SAF with higher resolution. The trapped-wave inferred waveguide on the SAF Parkfield segment is ~150 m wide at surface and tapers to ~100 m at seismogenic depth, in which Q is 20-50 and S velocities are reduced by 30-40% from wall-rock velocities, with the greater velocity reduction at the shallow depth and to southeast of the 1966 M6 epicenter. We interpret this low-velocity waveguide on the SAF main strand as being the remnant of damage zone caused

  1. Off-fault tip splay networks: a genetic and generic property of faults indicative of their long-term propagation, and a major component of off-fault damage

    Science.gov (United States)

    Perrin, C.; Manighetti, I.; Gaudemer, Y.

    2015-12-01

    Faults grow over the long-term by accumulating displacement and lengthening, i.e., propagating laterally. We use fault maps and fault propagation evidences available in literature to examine geometrical relations between parent faults and off-fault splays. The population includes 47 worldwide crustal faults with lengths from millimeters to thousands of kilometers and of different slip modes. We show that fault splays form adjacent to any propagating fault tip, whereas they are absent at non-propagating fault ends. Independent of parent fault length, slip mode, context, etc, tip splay networks have a similar fan shape widening in direction of long-term propagation, a similar relative length and width (~30 and ~10 % of parent fault length, respectively), and a similar range of mean angles to parent fault (10-20°). Tip splays more commonly develop on one side only of the parent fault. We infer that tip splay networks are a genetic and a generic property of faults indicative of their long-term propagation. We suggest that they represent the most recent damage off-the parent fault, formed during the most recent phase of fault lengthening. The scaling relation between parent fault length and width of tip splay network implies that damage zones enlarge as parent fault length increases. Elastic properties of host rocks might thus be modified at large distances away from a fault, up to 10% of its length. During an earthquake, a significant fraction of coseismic slip and stress is dissipated into the permanent damage zone that surrounds the causative fault. We infer that coseismic dissipation might occur away from a rupture zone as far as a distance of 10% of the length of its causative fault. Coseismic deformations and stress transfers might thus be significant in broad regions about principal rupture traces. This work has been published in Comptes Rendus Geoscience under doi:10.1016/j.crte.2015.05.002 (http://www.sciencedirect.com/science/article/pii/S1631071315000528).

  2. Aircraft engine sensor fault diagnostics using an on-line OBEM update method.

    Directory of Open Access Journals (Sweden)

    Xiaofeng Liu

    Full Text Available This paper proposed a method to update the on-line health reference baseline of the On-Board Engine Model (OBEM to maintain the effectiveness of an in-flight aircraft sensor Fault Detection and Isolation (FDI system, in which a Hybrid Kalman Filter (HKF was incorporated. Generated from a rapid in-flight engine degradation, a large health condition mismatch between the engine and the OBEM can corrupt the performance of the FDI. Therefore, it is necessary to update the OBEM online when a rapid degradation occurs, but the FDI system will lose estimation accuracy if the estimation and update are running simultaneously. To solve this problem, the health reference baseline for a nonlinear OBEM was updated using the proposed channel controller method. Simulations based on the turbojet engine Linear-Parameter Varying (LPV model demonstrated the effectiveness of the proposed FDI system in the presence of substantial degradation, and the channel controller can ensure that the update process finishes without interference from a single sensor fault.

  3. Motor Fault Diagnosis Based on Short-time Fourier Transform and Convolutional Neural Network

    Science.gov (United States)

    Wang, Li-Hua; Zhao, Xiao-Ping; Wu, Jia-Xin; Xie, Yang-Yang; Zhang, Yong-Hong

    2017-11-01

    With the rapid development of mechanical equipment, the mechanical health monitoring field has entered the era of big data. However, the method of manual feature extraction has the disadvantages of low efficiency and poor accuracy, when handling big data. In this study, the research object was the asynchronous motor in the drivetrain diagnostics simulator system. The vibration signals of different fault motors were collected. The raw signal was pretreated using short time Fourier transform (STFT) to obtain the corresponding time-frequency map. Then, the feature of the time-frequency map was adaptively extracted by using a convolutional neural network (CNN). The effects of the pretreatment method, and the hyper parameters of network diagnostic accuracy, were investigated experimentally. The experimental results showed that the influence of the preprocessing method is small, and that the batch-size is the main factor affecting accuracy and training efficiency. By investigating feature visualization, it was shown that, in the case of big data, the extracted CNN features can represent complex mapping relationships between signal and health status, and can also overcome the prior knowledge and engineering experience requirement for feature extraction, which is used by traditional diagnosis methods. This paper proposes a new method, based on STFT and CNN, which can complete motor fault diagnosis tasks more intelligently and accurately.

  4. On-line experimental validation of a model-based diagnostic algorithm dedicated to a solid oxide fuel cell system

    Science.gov (United States)

    Polverino, Pierpaolo; Esposito, Angelo; Pianese, Cesare; Ludwig, Bastian; Iwanschitz, Boris; Mai, Andreas

    2016-02-01

    In the current energetic scenario, Solid Oxide Fuel Cells (SOFCs) exhibit appealing features which make them suitable for environmental-friendly power production, especially for stationary applications. An example is represented by micro-combined heat and power (μ-CHP) generation units based on SOFC stacks, which are able to produce electric and thermal power with high efficiency and low pollutant and greenhouse gases emissions. However, the main limitations to their diffusion into the mass market consist in high maintenance and production costs and short lifetime. To improve these aspects, the current research activity focuses on the development of robust and generalizable diagnostic techniques, aimed at detecting and isolating faults within the entire system (i.e. SOFC stack and balance of plant). Coupled with appropriate recovery strategies, diagnosis can prevent undesired system shutdowns during faulty conditions, with consequent lifetime increase and maintenance costs reduction. This paper deals with the on-line experimental validation of a model-based diagnostic algorithm applied to a pre-commercial SOFC system. The proposed algorithm exploits a Fault Signature Matrix based on a Fault Tree Analysis and improved through fault simulations. The algorithm is characterized on the considered system and it is validated by means of experimental induction of faulty states in controlled conditions.

  5. Simultaneous-Fault Diagnosis of Automotive Engine Ignition Systems Using Prior Domain Knowledge and Relevance Vector Machine

    Directory of Open Access Journals (Sweden)

    Chi-Man Vong

    2013-01-01

    Full Text Available Engine ignition patterns can be analyzed to identify the engine fault according to both the specific prior domain knowledge and the shape features of the patterns. One of the challenges in ignition system diagnosis is that more than one fault may appear at a time. This kind of problem refers to simultaneous-fault diagnosis. Another challenge is the acquisition of a large amount of costly simultaneous-fault ignition patterns for constructing the diagnostic system because the number of the training patterns depends on the combination of different single faults. The above problems could be resolved by the proposed framework combining feature extraction, probabilistic classification, and decision threshold optimization. With the proposed framework, the features of the single faults in a simultaneous-fault pattern are extracted and then detected using a new probabilistic classifier, namely, pairwise coupling relevance vector machine, which is trained with single-fault patterns only. Therefore, the training dataset of simultaneous-fault patterns is not necessary. Experimental results show that the proposed framework performs well for both single-fault and simultaneous-fault diagnoses and is superior to the existing approach.

  6. A Framework to Debug Diagnostic Matrices

    Science.gov (United States)

    Kodal, Anuradha; Robinson, Peter; Patterson-Hine, Ann

    2013-01-01

    Diagnostics is an important concept in system health and monitoring of space operations. Many of the existing diagnostic algorithms utilize system knowledge in the form of diagnostic matrix (D-matrix, also popularly known as diagnostic dictionary, fault signature matrix or reachability matrix) gleaned from physical models. But, sometimes, this may not be coherent to obtain high diagnostic performance. In such a case, it is important to modify this D-matrix based on knowledge obtained from other sources such as time-series data stream (simulated or maintenance data) within the context of a framework that includes the diagnostic/inference algorithm. A systematic and sequential update procedure, diagnostic modeling evaluator (DME) is proposed to modify D-matrix and wrapper logic considering least expensive solution first. This iterative procedure includes conditions ranging from modifying 0s and 1s in the matrix, or adding/removing the rows (failure sources) columns (tests). We will experiment this framework on datasets from DX challenge 2009.

  7. From fault classification to fault tolerance for multi-agent systems

    CERN Document Server

    Potiron, Katia; Taillibert, Patrick

    2013-01-01

    Faults are a concern for Multi-Agent Systems (MAS) designers, especially if the MAS are built for industrial or military use because there must be some guarantee of dependability. Some fault classification exists for classical systems, and is used to define faults. When dependability is at stake, such fault classification may be used from the beginning of the system's conception to define fault classes and specify which types of faults are expected. Thus, one may want to use fault classification for MAS; however, From Fault Classification to Fault Tolerance for Multi-Agent Systems argues that

  8. Development of Fault Detection and Diagnosis Schemes for Industrial Refrigeration Systems

    DEFF Research Database (Denmark)

    Thybo, C.; Izadi-Zamanabadi, Roozbeh

    2004-01-01

    The success of a fault detection and diagnosis (FDD) scheme depends not alone on developing an advanced detection scheme. To enable successful deployment in industrial applications, an economically optimal development of FDD schemes are required. This paper reviews and discusses the gained...... experiences achieved by employing a combination of various techniques, methods, and algorithms, which are proposed by academia, on an industrial application. The main focus is on sharing the "lessons learned" from developing and employing Faulttolerant functionalities to a controlled process in order to meet...... the industrial needs while satisfying economically motivated constraints....

  9. Summary: beyond fault trees to fault graphs

    International Nuclear Information System (INIS)

    Alesso, H.P.; Prassinos, P.; Smith, C.F.

    1984-09-01

    Fault Graphs are the natural evolutionary step over a traditional fault-tree model. A Fault Graph is a failure-oriented directed graph with logic connectives that allows cycles. We intentionally construct the Fault Graph to trace the piping and instrumentation drawing (P and ID) of the system, but with logical AND and OR conditions added. Then we evaluate the Fault Graph with computer codes based on graph-theoretic methods. Fault Graph computer codes are based on graph concepts, such as path set (a set of nodes traveled on a path from one node to another) and reachability (the complete set of all possible paths between any two nodes). These codes are used to find the cut-sets (any minimal set of component failures that will fail the system) and to evaluate the system reliability

  10. Diagnostic development and support of MHD (magnetohydrodynamics) test facilities

    Energy Technology Data Exchange (ETDEWEB)

    1989-07-01

    Mississippi State University (MSU) is developing diagnostic instruments for Magnetohydrodynamics (MHD) power train data acquisition and for support of MHD component development test facilities. Microprocessor-controlled optical instruments, initially developed for HRSR support, are being refined, and new systems to measure temperatures and gas-seed-slag stream characteristics are being developed. To further data acquisition and analysis capabilities, the diagnostic systems are being interfaced with MHD Energy Center computers. Technical support for the diagnostic needs of the national MHD research effort is being provided. MSU personnel will also cooperate with government agencies and private industries to improve the transformation of research and development results into processes, products and services applicable to their needs.

  11. Fault-related clay authigenesis along the Moab Fault: Implications for calculations of fault rock composition and mechanical and hydrologic fault zone properties

    Science.gov (United States)

    Solum, J.G.; Davatzes, N.C.; Lockner, D.A.

    2010-01-01

    The presence of clays in fault rocks influences both the mechanical and hydrologic properties of clay-bearing faults, and therefore it is critical to understand the origin of clays in fault rocks and their distributions is of great importance for defining fundamental properties of faults in the shallow crust. Field mapping shows that layers of clay gouge and shale smear are common along the Moab Fault, from exposures with throws ranging from 10 to ???1000 m. Elemental analyses of four locations along the Moab Fault show that fault rocks are enriched in clays at R191 and Bartlett Wash, but that this clay enrichment occurred at different times and was associated with different fluids. Fault rocks at Corral and Courthouse Canyons show little difference in elemental composition from adjacent protolith, suggesting that formation of fault rocks at those locations is governed by mechanical processes. Friction tests show that these authigenic clays result in fault zone weakening, and potentially influence the style of failure along the fault (seismogenic vs. aseismic) and potentially influence the amount of fluid loss associated with coseismic dilation. Scanning electron microscopy shows that authigenesis promotes that continuity of slip surfaces, thereby enhancing seal capacity. The occurrence of the authigenesis, and its influence on the sealing properties of faults, highlights the importance of determining the processes that control this phenomenon. ?? 2010 Elsevier Ltd.

  12. Faults in Linux

    DEFF Research Database (Denmark)

    Palix, Nicolas Jean-Michel; Thomas, Gaël; Saha, Suman

    2011-01-01

    In 2001, Chou et al. published a study of faults found by applying a static analyzer to Linux versions 1.0 through 2.4.1. A major result of their work was that the drivers directory contained up to 7 times more of certain kinds of faults than other directories. This result inspired a number...... of development and research efforts on improving the reliability of driver code. Today Linux is used in a much wider range of environments, provides a much wider range of services, and has adopted a new development and release model. What has been the impact of these changes on code quality? Are drivers still...... a major problem? To answer these questions, we have transported the experiments of Chou et al. to Linux versions 2.6.0 to 2.6.33, released between late 2003 and early 2010. We find that Linux has more than doubled in size during this period, but that the number of faults per line of code has been...

  13. Spatial analysis of hypocenter to fault relationships for determining fault process zone width in Japan

    International Nuclear Information System (INIS)

    Arnold, Bill Walter; Roberts, Barry L.; McKenna, Sean Andrew; Coburn, Timothy C.

    2004-01-01

    Preliminary investigation areas (PIA) for a potential repository of high-level radioactive waste must be evaluated by NUMO with regard to a number of qualifying factors. One of these factors is related to earthquakes and fault activity. This study develops a spatial statistical assessment method that can be applied to the active faults in Japan to perform such screening evaluations. This analysis uses the distribution of seismicity near faults to define the width of the associated process zone. This concept is based on previous observations of aftershock earthquakes clustered near active faults and on the assumption that such seismic activity is indicative of fracturing and associated impacts on bedrock integrity. Preliminary analyses of aggregate data for all of Japan confirmed that the frequency of earthquakes is higher near active faults. Data used in the analysis were obtained from NUMO and consist of three primary sources: (1) active fault attributes compiled in a spreadsheet, (2) earthquake hypocenter data, and (3) active fault locations. Examination of these data revealed several limitations with regard to the ability to associate fault attributes from the spreadsheet to locations of individual fault trace segments. In particular, there was no direct link between attributes of the active faults in the spreadsheet and the active fault locations in the GIS database. In addition, the hypocenter location resolution in the pre-1983 data was less accurate than for later data. These pre-1983 hypocenters were eliminated from further analysis

  14. Spatial analysis of hypocenter to fault relationships for determining fault process zone width in Japan.

    Energy Technology Data Exchange (ETDEWEB)

    Arnold, Bill Walter; Roberts, Barry L.; McKenna, Sean Andrew; Coburn, Timothy C. (Abilene Christian University, Abilene, TX)

    2004-09-01

    Preliminary investigation areas (PIA) for a potential repository of high-level radioactive waste must be evaluated by NUMO with regard to a number of qualifying factors. One of these factors is related to earthquakes and fault activity. This study develops a spatial statistical assessment method that can be applied to the active faults in Japan to perform such screening evaluations. This analysis uses the distribution of seismicity near faults to define the width of the associated process zone. This concept is based on previous observations of aftershock earthquakes clustered near active faults and on the assumption that such seismic activity is indicative of fracturing and associated impacts on bedrock integrity. Preliminary analyses of aggregate data for all of Japan confirmed that the frequency of earthquakes is higher near active faults. Data used in the analysis were obtained from NUMO and consist of three primary sources: (1) active fault attributes compiled in a spreadsheet, (2) earthquake hypocenter data, and (3) active fault locations. Examination of these data revealed several limitations with regard to the ability to associate fault attributes from the spreadsheet to locations of individual fault trace segments. In particular, there was no direct link between attributes of the active faults in the spreadsheet and the active fault locations in the GIS database. In addition, the hypocenter location resolution in the pre-1983 data was less accurate than for later data. These pre-1983 hypocenters were eliminated from further analysis.

  15. A gas turbine diagnostic approach with transient measurements.

    OpenAIRE

    Li, Y. G.

    2003-01-01

    Most gas turbine performance analysis based diagnostic methods use the information from steady state measurements. Unfortunately, steady state measurement may not be obtained easily in some situations, and some types of gas turbine fault contribute little to performance deviation at steady state operating conditions but significantly during transient processes. Therefore, gas turbine diagnostics with transient measurement is superior to that with steady state measurement. In this paper, an ac...

  16. Fault Analysis in Solar Photovoltaic Arrays

    Science.gov (United States)

    Zhao, Ye

    Fault analysis in solar photovoltaic (PV) arrays is a fundamental task to increase reliability, efficiency and safety in PV systems. Conventional fault protection methods usually add fuses or circuit breakers in series with PV components. But these protection devices are only able to clear faults and isolate faulty circuits if they carry a large fault current. However, this research shows that faults in PV arrays may not be cleared by fuses under some fault scenarios, due to the current-limiting nature and non-linear output characteristics of PV arrays. First, this thesis introduces new simulation and analytic models that are suitable for fault analysis in PV arrays. Based on the simulation environment, this thesis studies a variety of typical faults in PV arrays, such as ground faults, line-line faults, and mismatch faults. The effect of a maximum power point tracker on fault current is discussed and shown to, at times, prevent the fault current protection devices to trip. A small-scale experimental PV benchmark system has been developed in Northeastern University to further validate the simulation conclusions. Additionally, this thesis examines two types of unique faults found in a PV array that have not been studied in the literature. One is a fault that occurs under low irradiance condition. The other is a fault evolution in a PV array during night-to-day transition. Our simulation and experimental results show that overcurrent protection devices are unable to clear the fault under "low irradiance" and "night-to-day transition". However, the overcurrent protection devices may work properly when the same PV fault occurs in daylight. As a result, a fault under "low irradiance" and "night-to-day transition" might be hidden in the PV array and become a potential hazard for system efficiency and reliability.

  17. Fast architecture-level synthesis of fault-tolerant flow-based microfluidic biochips

    DEFF Research Database (Denmark)

    Huang, Wei Lun; Gupta, Ankur; Roy, Sudip

    2017-01-01

    Microfluidic-based lab-on-a-chips have emerged as a popular technology for implementation of different biochemical test protocols used in medical diagnostics. However, in the manufacturing process or during operation of such chips, some faults may occur that leads to damage of the chip, which...

  18. Demonstration of artificial intelligence technology for transit railcar diagnostics

    Science.gov (United States)

    1999-01-01

    This report will be of interest to railcar maintenance professionals concerned with improving railcar maintenance fault-diagnostic capabilities through the use of artificial intelligence (AI) technologies. It documents the results of a demonstration ...

  19. Optimal Sequential Diagnostic Strategy Generation Considering Test Placement Cost for Multimode Systems

    Directory of Open Access Journals (Sweden)

    Shigang Zhang

    2015-10-01

    Full Text Available Sequential fault diagnosis is an approach that realizes fault isolation by executing the optimal test step by step. The strategy used, i.e., the sequential diagnostic strategy, has great influence on diagnostic accuracy and cost. Optimal sequential diagnostic strategy generation is an important step in the process of diagnosis system construction, which has been studied extensively in the literature. However, previous algorithms either are designed for single mode systems or do not consider test placement cost. They are not suitable to solve the sequential diagnostic strategy generation problem considering test placement cost for multimode systems. Therefore, this problem is studied in this paper. A formulation is presented. Two algorithms are proposed, one of which is realized by system transformation and the other is newly designed. Extensive simulations are carried out to test the effectiveness of the algorithms. A real-world system is also presented. All the results show that both of them have the ability to solve the diagnostic strategy generation problem, and they have different characteristics.

  20. Optimal Sequential Diagnostic Strategy Generation Considering Test Placement Cost for Multimode Systems

    Science.gov (United States)

    Zhang, Shigang; Song, Lijun; Zhang, Wei; Hu, Zheng; Yang, Yongmin

    2015-01-01

    Sequential fault diagnosis is an approach that realizes fault isolation by executing the optimal test step by step. The strategy used, i.e., the sequential diagnostic strategy, has great influence on diagnostic accuracy and cost. Optimal sequential diagnostic strategy generation is an important step in the process of diagnosis system construction, which has been studied extensively in the literature. However, previous algorithms either are designed for single mode systems or do not consider test placement cost. They are not suitable to solve the sequential diagnostic strategy generation problem considering test placement cost for multimode systems. Therefore, this problem is studied in this paper. A formulation is presented. Two algorithms are proposed, one of which is realized by system transformation and the other is newly designed. Extensive simulations are carried out to test the effectiveness of the algorithms. A real-world system is also presented. All the results show that both of them have the ability to solve the diagnostic strategy generation problem, and they have different characteristics. PMID:26457709

  1. An effort allocation model considering different budgetary constraint on fault detection process and fault correction process

    Directory of Open Access Journals (Sweden)

    Vijay Kumar

    2016-01-01

    Full Text Available Fault detection process (FDP and Fault correction process (FCP are important phases of software development life cycle (SDLC. It is essential for software to undergo a testing phase, during which faults are detected and corrected. The main goal of this article is to allocate the testing resources in an optimal manner to minimize the cost during testing phase using FDP and FCP under dynamic environment. In this paper, we first assume there is a time lag between fault detection and fault correction. Thus, removal of a fault is performed after a fault is detected. In addition, detection process and correction process are taken to be independent simultaneous activities with different budgetary constraints. A structured optimal policy based on optimal control theory is proposed for software managers to optimize the allocation of the limited resources with the reliability criteria. Furthermore, release policy for the proposed model is also discussed. Numerical example is given in support of the theoretical results.

  2. Developing seismogenic source models based on geologic fault data

    Science.gov (United States)

    Haller, Kathleen M.; Basili, Roberto

    2011-01-01

    Calculating seismic hazard usually requires input that includes seismicity associated with known faults, historical earthquake catalogs, geodesy, and models of ground shaking. This paper will address the input generally derived from geologic studies that augment the short historical catalog to predict ground shaking at time scales of tens, hundreds, or thousands of years (e.g., SSHAC 1997). A seismogenic source model, terminology we adopt here for a fault source model, includes explicit three-dimensional faults deemed capable of generating ground motions of engineering significance within a specified time frame of interest. In tectonically active regions of the world, such as near plate boundaries, multiple seismic cycles span a few hundred to a few thousand years. In contrast, in less active regions hundreds of kilometers from the nearest plate boundary, seismic cycles generally are thousands to tens of thousands of years long. Therefore, one should include sources having both longer recurrence intervals and possibly older times of most recent rupture in less active regions of the world rather than restricting the model to include only Holocene faults (i.e., those with evidence of large-magnitude earthquakes in the past 11,500 years) as is the practice in tectonically active regions with high deformation rates. During the past 15 years, our institutions independently developed databases to characterize seismogenic sources based on geologic data at a national scale. Our goal here is to compare the content of these two publicly available seismogenic source models compiled for the primary purpose of supporting seismic hazard calculations by the Istituto Nazionale di Geofisica e Vulcanologia (INGV) and the U.S. Geological Survey (USGS); hereinafter we refer to the two seismogenic source models as INGV and USGS, respectively. This comparison is timely because new initiatives are emerging to characterize seismogenic sources at the continental scale (e.g., SHARE in the

  3. HOT Faults", Fault Organization, and the Occurrence of the Largest Earthquakes

    Science.gov (United States)

    Carlson, J. M.; Hillers, G.; Archuleta, R. J.

    2006-12-01

    We apply the concept of "Highly Optimized Tolerance" (HOT) for the investigation of spatio-temporal seismicity evolution, in particular mechanisms associated with largest earthquakes. HOT provides a framework for investigating both qualitative and quantitative features of complex feedback systems that are far from equilibrium and punctuated by rare, catastrophic events. In HOT, robustness trade-offs lead to complexity and power laws in systems that are coupled to evolving environments. HOT was originally inspired by biology and engineering, where systems are internally very highly structured, through biological evolution or deliberate design, and perform in an optimum manner despite fluctuations in their surroundings. Though faults and fault systems are not designed in ways comparable to biological and engineered structures, feedback processes are responsible in a conceptually comparable way for the development, evolution and maintenance of younger fault structures and primary slip surfaces of mature faults, respectively. Hence, in geophysical applications the "optimization" approach is perhaps more aptly replaced by "organization", reflecting the distinction between HOT and random, disorganized configurations, and highlighting the importance of structured interdependencies that evolve via feedback among and between different spatial and temporal scales. Expressed in the terminology of the HOT concept, mature faults represent a configuration optimally organized for the release of strain energy; whereas immature, more heterogeneous fault networks represent intermittent, suboptimal systems that are regularized towards structural simplicity and the ability to generate large earthquakes more easily. We discuss fault structure and associated seismic response pattern within the HOT concept, and outline fundamental differences between this novel interpretation to more orthodox viewpoints like the criticality concept. The discussion is flanked by numerical simulations of a

  4. Fault Severity Evaluation and Improvement Design for Mechanical Systems Using the Fault Injection Technique and Gini Concordance Measure

    Directory of Open Access Journals (Sweden)

    Jianing Wu

    2014-01-01

    Full Text Available A new fault injection and Gini concordance based method has been developed for fault severity analysis for multibody mechanical systems concerning their dynamic properties. The fault tree analysis (FTA is employed to roughly identify the faults needed to be considered. According to constitution of the mechanical system, the dynamic properties can be achieved by solving the equations that include many types of faults which are injected by using the fault injection technique. Then, the Gini concordance is used to measure the correspondence between the performance with faults and under normal operation thereby providing useful hints of severity ranking in subsystems for reliability design. One numerical example and a series of experiments are provided to illustrate the application of the new method. The results indicate that the proposed method can accurately model the faults and receive the correct information of fault severity. Some strategies are also proposed for reliability improvement of the spacecraft solar array.

  5. The Fault Detection, Localization, and Tolerant Operation of Modular Multilevel Converters with an Insulated Gate Bipolar Transistor (IGBT Open Circuit Fault

    Directory of Open Access Journals (Sweden)

    Wei Li

    2018-04-01

    Full Text Available Reliability is one of the critical issues for a modular multilevel converter (MMC since it consists of a large number of series-connected power electronics submodules (SMs. In this paper, a complete control strategy including fault detection, localization, and tolerant operation is proposed for the MMC under an insulated gate bipolar transistor (IGBT open circuit fault. According to the output characteristics of the SM with the open-circuit fault of IGBT, a fault detection method based on the circulating current and output current observation is used. In order to further precisely locate the position of the faulty SM, a fault localization method based on the SM capacitor voltage observation is developed. After the faulty SM is isolated, the continuous operation of the converter is ensured by adopting the fault-tolerant strategy based on the use of redundant modules. To verify the proposed fault detection, fault localization, and fault-tolerant operation strategies, a 900 kVA MMC system under the conditions of an IGBT open circuit is developed in the Matlab/Simulink platform. The capabilities of rapid detection, precise positioning, and fault-tolerant operation of the investigated detection and control algorithms are also demonstrated.

  6. Development on multifunctional phased-array fault inspection technology. Aiming at integrity on internals in nuclear power plant reactors

    International Nuclear Information System (INIS)

    Komura, Ichiro; Hirasawa, Taiji; Nagai, Satoshi; Naruse, Katsuhiko

    2002-01-01

    On nuclear power plants sharing an important role in Japanese energy policy, their higher safety and reliability than the other plants are required, and their non-destructive inspection occupies important position for information means to judge their integrity. And, for a part of responses to recent rationalization of the plant operation and increase of aged plants, requirements and positioning onto the non-destructive inspection technology also change. As a result, not only concept on allowable fault sizes is adopted, but also inspection on reactor internals without conventional regulation is obliged to require for size evaluation (sizing) with higher precision to use for secure detection and integrity evaluation of the faults than sizes determined for every internals. For requirement with such higher levels for fault detection and sizing, and for requirement for effective inspection, phased-array supersonic wave fault inspection method is one of the methods with high potential power. Here were introduced on principles and characteristics of the phased-array supersonic wave fault inspection method, and on various fault inspection methods and functions mainly developed for reactor internals inspection. (G.K.)

  7. Automated diagnostics scoping study. Final report

    Energy Technology Data Exchange (ETDEWEB)

    Quadrel, R.W.; Lash, T.A.

    1994-06-01

    The objective of the Automated Diagnostics Scoping Study was to investigate the needs for diagnostics in building operation and to examine some of the current technologies in automated diagnostics that can address these needs. The study was conducted in two parts. In the needs analysis, the authors interviewed facility managers and engineers at five building sites. In the technology survey, they collected published information on automated diagnostic technologies in commercial and military applications as well as on technologies currently under research. The following describe key areas that the authors identify for the research, development, and deployment of automated diagnostic technologies: tools and techniques to aid diagnosis during building commissioning, especially those that address issues arising from integrating building systems and diagnosing multiple simultaneous faults; technologies to aid diagnosis for systems and components that are unmonitored or unalarmed; automated capabilities to assist cause-and-effect exploration during diagnosis; inexpensive, reliable sensors, especially those that expand the current range of sensory input; technologies that aid predictive diagnosis through trend analysis; integration of simulation and optimization tools with building automation systems to optimize control strategies and energy performance; integration of diagnostic, control, and preventive maintenance technologies. By relating existing technologies to perceived and actual needs, the authors reached some conclusions about the opportunities for automated diagnostics in building operation. Some of a building operator`s needs can be satisfied by off-the-shelf hardware and software. Other needs are not so easily satisfied, suggesting directions for future research. Their conclusions and suggestions are offered in the final section of this study.

  8. Fault tolerant operation of switched reluctance machine

    Science.gov (United States)

    Wang, Wei

    The energy crisis and environmental challenges have driven industry towards more energy efficient solutions. With nearly 60% of electricity consumed by various electric machines in industry sector, advancement in the efficiency of the electric drive system is of vital importance. Adjustable speed drive system (ASDS) provides excellent speed regulation and dynamic performance as well as dramatically improved system efficiency compared with conventional motors without electronics drives. Industry has witnessed tremendous grow in ASDS applications not only as a driving force but also as an electric auxiliary system for replacing bulky and low efficiency auxiliary hydraulic and mechanical systems. With the vast penetration of ASDS, its fault tolerant operation capability is more widely recognized as an important feature of drive performance especially for aerospace, automotive applications and other industrial drive applications demanding high reliability. The Switched Reluctance Machine (SRM), a low cost, highly reliable electric machine with fault tolerant operation capability, has drawn substantial attention in the past three decades. Nevertheless, SRM is not free of fault. Certain faults such as converter faults, sensor faults, winding shorts, eccentricity and position sensor faults are commonly shared among all ASDS. In this dissertation, a thorough understanding of various faults and their influence on transient and steady state performance of SRM is developed via simulation and experimental study, providing necessary knowledge for fault detection and post fault management. Lumped parameter models are established for fast real time simulation and drive control. Based on the behavior of the faults, a fault detection scheme is developed for the purpose of fast and reliable fault diagnosis. In order to improve the SRM power and torque capacity under faults, the maximum torque per ampere excitation are conceptualized and validated through theoretical analysis and

  9. Rated-voltage enhancement by fast-breaking of the fault current for a resistive superconducting fault current limiter component

    International Nuclear Information System (INIS)

    Park, C.-R.; Kim, M.-J.; Yu, S.-D.; Yim, S.-W.; Kim, H.-R.; Hyun, O.-B.

    2010-01-01

    Performance of a resistive superconducting fault current limiter (SFCL) component is usually limited by temperature rise associated with energy input by fault current application during a fault. Therefore, it is expected that short application of the fault current may enhance the power ratings of the component. This can be accomplished by a combination of a HTS component and a mechanical switch. The fast switch (FS) developed recently enables the fault duration to be as short as 1/2 cycle after a fault. Various second-generation (2G) high temperature superconductors (HTS) and YBCO thin films have been tested. The relation between the rated voltage V and the fault duration time t was found to be V 2 ∼ t -1 . Based upon the relation, we predict that when the FS break the fault current within 1/2 cycle after a fault, the amount of HTS components required to build an SFCL can be reduced by as much as about 60%, of that when breaking the fault current at three cycles.

  10. Fault tolerant control for uncertain systems with parametric faults

    DEFF Research Database (Denmark)

    Niemann, Hans Henrik; Poulsen, Niels Kjølstad

    2006-01-01

    A fault tolerant control (FTC) architecture based on active fault diagnosis (AFD) and the YJBK (Youla, Jarb, Bongiorno and Kucera)parameterization is applied in this paper. Based on the FTC architecture, fault tolerant control of uncertain systems with slowly varying parametric faults...... is investigated. Conditions are given for closed-loop stability in case of false alarms or missing fault detection/isolation....

  11. LAMPF first-fault identifier for fast transient faults

    International Nuclear Information System (INIS)

    Swanson, A.R.; Hill, R.E.

    1979-01-01

    The LAMPF accelerator is presently producing 800-MeV proton beams at 0.5 mA average current. Machine protection for such a high-intensity accelerator requires a fast shutdown mechanism, which can turn off the beam within a few microseconds of the occurrence of a machine fault. The resulting beam unloading transients cause the rf systems to exceed control loop tolerances and consequently generate multiple fault indications for identification by the control computer. The problem is to isolate the primary fault or cause of beam shutdown while disregarding as many as 50 secondary fault indications that occur as a result of beam shutdown. The LAMPF First-Fault Identifier (FFI) for fast transient faults is operational and has proven capable of first-fault identification. The FFI design utilized features of the Fast Protection System that were previously implemented for beam chopping and rf power conservation. No software changes were required

  12. Scaling-Up the Functional Diagnostic Systems

    International Nuclear Information System (INIS)

    Mohamed, A.H.

    2008-01-01

    Functional diagnostic systems received a lot of attention in the last decade. They have proven their powerful for diagnosis the new faults of some complex systems. But, they still have some complexity in both the representation and reasoning about the large-scale systems. This paper introduces a new functional diagnostic system that can divide its small functions into main and auxiliary ones. This process enables the diagnostic system to scale -up the representation of the tested system and simplify the diagnostic mechanism tasks. Thus, it can improve both the representation and reasoning complexity. Also,it can decrease the required analysis, cost, and time. Proposed system can be applied for a wide area of the large-scale systems. It has been proven its acceptance to be applied practically for the Complex real-time systems

  13. The effect of information types on diagnostic strategies in the information aid

    International Nuclear Information System (INIS)

    Kim, Jong Hyun; Seong, Poong Hyun

    2007-01-01

    Through experiments, this paper investigates the compatibility of information types with the diagnostic strategy in information aid. Compatibility with operator strategies is an important requirement for information aiding systems in nuclear power plants (NPPs). This paper used three typical types of information aids for MCR operators to investigate the effect of the aids on diagnostic strategies: 'alarm (A),' 'hypothesis on faults (H),' and 'hypothesis on faults and expected symptoms (HS).' The experimental results indicate that the effectiveness of information aid types can vary, dependent on the strategies subjects employ. The results also show that the HS aid improved the diagnosis performance in the hypothesis-and-test strategy

  14. A study on quantification of unavailability of DPPS with fault tolerant techniques considering fault tolerant techniques' characteristics

    International Nuclear Information System (INIS)

    Kim, B. G.; Kang, H. G.; Kim, H. E.; Seung, P. H.; Kang, H. G.; Lee, S. J.

    2012-01-01

    With the improvement of digital technologies, digital I and C systems have included more various fault tolerant techniques than conventional analog I and C systems have, in order to increase fault detection and to help the system safely perform the required functions in spite of the presence of faults. So, in the reliability evaluation of digital systems, the fault tolerant techniques (FTTs) and their fault coverage must be considered. To consider the effects of FTTs in a digital system, there have been several studies on the reliability of digital model. Therefore, this research based on literature survey attempts to develop a model to evaluate the plant reliability of the digital plant protection system (DPPS) with fault tolerant techniques considering detection and process characteristics and human errors. Sensitivity analysis is performed to ascertain important variables from the fault management coverage and unavailability based on the proposed model

  15. Why the 2002 Denali fault rupture propagated onto the Totschunda fault: implications for fault branching and seismic hazards

    Science.gov (United States)

    Schwartz, David P.; Haeussler, Peter J.; Seitz, Gordon G.; Dawson, Timothy E.

    2012-01-01

    The propagation of the rupture of the Mw7.9 Denali fault earthquake from the central Denali fault onto the Totschunda fault has provided a basis for dynamic models of fault branching in which the angle of the regional or local prestress relative to the orientation of the main fault and branch plays a principal role in determining which fault branch is taken. GeoEarthScope LiDAR and paleoseismic data allow us to map the structure of the Denali-Totschunda fault intersection and evaluate controls of fault branching from a geological perspective. LiDAR data reveal the Denali-Totschunda fault intersection is structurally simple with the two faults directly connected. At the branch point, 227.2 km east of the 2002 epicenter, the 2002 rupture diverges southeast to become the Totschunda fault. We use paleoseismic data to propose that differences in the accumulated strain on each fault segment, which express differences in the elapsed time since the most recent event, was one important control of the branching direction. We suggest that data on event history, slip rate, paleo offsets, fault geometry and structure, and connectivity, especially on high slip rate-short recurrence interval faults, can be used to assess the likelihood of branching and its direction. Analysis of the Denali-Totschunda fault intersection has implications for evaluating the potential for a rupture to propagate across other types of fault intersections and for characterizing sources of future large earthquakes.

  16. Industrial Cost-Benefit Assessment for Fault-tolerant Control Systems

    DEFF Research Database (Denmark)

    Thybo, C.; Blanke, M.

    1998-01-01

    Economic aspects are decisive for industrial acceptance of research concepts including the promising ideas in fault tolerant control. Fault tolerance is the ability of a system to detect, isolate and accommodate a fault, such that simple faults in a sub-system do not develop into failures....... The objective of this paper is to help, in the early product development state, to find the economical most suitable scheme. A salient result is that with increased customer awareness of total cost of ownership, new products can benefit significantly from applying fault tolerant control principles....

  17. Artificial neural network application for space station power system fault diagnosis

    Science.gov (United States)

    Momoh, James A.; Oliver, Walter E.; Dias, Lakshman G.

    1995-01-01

    This study presents a methodology for fault diagnosis using a Two-Stage Artificial Neural Network Clustering Algorithm. Previously, SPICE models of a 5-bus DC power distribution system with assumed constant output power during contingencies from the DDCU were used to evaluate the ANN's fault diagnosis capabilities. This on-going study uses EMTP models of the components (distribution lines, SPDU, TPDU, loads) and power sources (DDCU) of Space Station Alpha's electrical Power Distribution System as a basis for the ANN fault diagnostic tool. The results from the two studies are contrasted. In the event of a major fault, ground controllers need the ability to identify the type of fault, isolate the fault to the orbital replaceable unit level and provide the necessary information for the power management expert system to optimally determine a degraded-mode load schedule. To accomplish these goals, the electrical power distribution system's architecture can be subdivided into three major classes: DC-DC converter to loads, DC Switching Unit (DCSU) to Main bus Switching Unit (MBSU), and Power Sources to DCSU. Each class which has its own electrical characteristics and operations, requires a unique fault analysis philosophy. This study identifies these philosophies as Riddles 1, 2 and 3 respectively. The results of the on-going study addresses Riddle-1. It is concluded in this study that the combination of the EMTP models of the DDCU, distribution cables and electrical loads yields a more accurate model of the behavior and in addition yielded more accurate fault diagnosis using ANN versus the results obtained with the SPICE models.

  18. How is tectonic slip partitioned from the Alpine Fault to the Marlborough Fault System? : results from the Hope Fault

    International Nuclear Information System (INIS)

    Langridge, R.M.

    2004-01-01

    This report contains data from research undertaken by the author on the Hope Fault from 2000-2004. This report provides an opportunity to include data that was additional to or newer than work that was published in other places. New results from studies along the Hurunui section of the Hope Fault, additional to that published in Langridge and Berryman (2005) are presented here. This data includes tabulated data of fault location and description measurements, a graphical representation of this data in diagrammatic form along the length of the fault and new radiocarbon dates from the current EQC funded project. The new data show that the Hurunui section of the Hope Fault has the capability to yield further data on fault slip rate, earthquake displacements, and paleoseismicity. New results from studies at the Greenburn Stream paleoseismic site additional to that published in Langridge et al. (2003) are presented here. This includes a new log of the deepened west wall of Trench 2, a log of the west wall of Trench 1, and new radiocarbon dates from the second phase of dating undertaken at the Greenburn Stream site. The new data show that this site has the capability to yield further data on the paleoseismicity of the Conway segment of the Hope Fault. Through a detailed analysis of all three logged walls at the site and the new radiocarbon dates, it may, in combination with data from the nearby Clarence Reserve site of Pope (1994), be possible to develop a good record of the last 5 events on the Conway segment. (author). 12 refs., 12 figs

  19. Development of process diagnostic techniques for piping and equipment

    International Nuclear Information System (INIS)

    Yotsutsuji, Mitoshi

    1987-01-01

    The thing required for using the facilities composing a plant for a long period without anxiety is to quantitatively grasp the quantities of the present condition of the facilities and to take the necessary measures beforehand. For this purpose, the diagnostic techniques for quickly and accurately detect the quantities of the condition of facilities are necessary, and the development of process diagnostic techniques has been desired. The process diagnostic techniques mentioned here mean those for diagnosing the contamination, clogging and performance of towers, tanks, heat exchangers and others. Idemitsu Engineering Co. had developed a simplified diagnostic equipment for detecting the state of fouling in piping in 1982, which is the gamma ray transmission diagnosis named Scale Checker. By further improving it, the process diagnostic techniques for piping and equipment were developed. In this report, the course of development and examination, the principle of detection, the constitution and the examination of remodeling of the Scale Checker are reported. As the cases of process diagnosis in plant facilities, the diagnosis of the clogging in process piping and the diagnosis of the performance of a distillation tower were carried out. The contents of the diagnosis and the results of those cases are explained. (Kako, I.)

  20. An easy-to-use diagnostic system development shell

    Science.gov (United States)

    Tsai, L. C.; Ross, J. B.; Han, C. Y.; Wee, W. G.

    1987-01-01

    The Diagnostic System Development Shell (DSDS), an expert system development shell for diagnostic systems, is described. The major objective of building the DSDS is to create a very easy to use and friendly environment for knowledge engineers and end-users. The DSDS is written in OPS5 and CommonLisp. It runs on a VAX/VMS system. A set of domain independent, generalized rules is built in the DSDS, so the users need not be concerned about building the rules. The facts are explicitly represented in a unified format. A powerful check facility which helps the user to check the errors in the created knowledge bases is provided. A judgement facility and other useful facilities are also available. A diagnostic system based on the DSDS system is question driven and can call or be called by other knowledge based systems written in OPS5 and CommonLisp. A prototype diagnostic system for diagnosing a Philips constant potential X-ray system has been built using the DSDS.

  1. Intelligent fault diagnosis of rolling bearing based on kernel neighborhood rough sets and statistical features

    Energy Technology Data Exchange (ETDEWEB)

    Zhu, Xiao Ran; Zhang, You Yun; Zhu, Yong Sheng [Xi' an Jiaotong Univ., Xi' an (China)

    2012-09-15

    Intelligent fault diagnosis benefits from efficient feature selection. Neighborhood rough sets are effective in feature selection. However, determining the neighborhood value accurately remains a challenge. The wrapper feature selection algorithm is designed by combining the kernel method and neighborhood rough sets to self-adaptively select sensitive features. The combination effectively solves the shortcomings in selecting the neighborhood value in the previous application process. The statistical features of time and frequency domains are used to describe the characteristic of the rolling bearing to make the intelligent fault diagnosis approach work. Three classification algorithms, namely, classification and regression tree (CART), commercial version 4.5 (C4.5), and radial basis function support vector machines (RBFSVM), are used to test UCI datasets and 10 fault datasets of rolling bearing. The results indicate that the diagnostic approach presented could effectively select the sensitive fault features and simultaneously identify the type and degree of the fault.

  2. Intelligent fault diagnosis of rolling bearing based on kernel neighborhood rough sets and statistical features

    International Nuclear Information System (INIS)

    Zhu, Xiao Ran; Zhang, You Yun; Zhu, Yong Sheng

    2012-01-01

    Intelligent fault diagnosis benefits from efficient feature selection. Neighborhood rough sets are effective in feature selection. However, determining the neighborhood value accurately remains a challenge. The wrapper feature selection algorithm is designed by combining the kernel method and neighborhood rough sets to self-adaptively select sensitive features. The combination effectively solves the shortcomings in selecting the neighborhood value in the previous application process. The statistical features of time and frequency domains are used to describe the characteristic of the rolling bearing to make the intelligent fault diagnosis approach work. Three classification algorithms, namely, classification and regression tree (CART), commercial version 4.5 (C4.5), and radial basis function support vector machines (RBFSVM), are used to test UCI datasets and 10 fault datasets of rolling bearing. The results indicate that the diagnostic approach presented could effectively select the sensitive fault features and simultaneously identify the type and degree of the fault

  3. Deep Fault Recognizer: An Integrated Model to Denoise and Extract Features for Fault Diagnosis in Rotating Machinery

    Directory of Open Access Journals (Sweden)

    Xiaojie Guo

    2016-12-01

    Full Text Available Fault diagnosis in rotating machinery is significant to avoid serious accidents; thus, an accurate and timely diagnosis method is necessary. With the breakthrough in deep learning algorithm, some intelligent methods, such as deep belief network (DBN and deep convolution neural network (DCNN, have been developed with satisfactory performances to conduct machinery fault diagnosis. However, only a few of these methods consider properly dealing with noises that exist in practical situations and the denoising methods are in need of extensive professional experiences. Accordingly, rethinking the fault diagnosis method based on deep architectures is essential. Hence, this study proposes an automatic denoising and feature extraction method that inherently considers spatial and temporal correlations. In this study, an integrated deep fault recognizer model based on the stacked denoising autoencoder (SDAE is applied to both denoise random noises in the raw signals and represent fault features in fault pattern diagnosis for both bearing rolling fault and gearbox fault, and trained in a greedy layer-wise fashion. Finally, the experimental validation demonstrates that the proposed method has better diagnosis accuracy than DBN, particularly in the existing situation of noises with superiority of approximately 7% in fault diagnosis accuracy.

  4. Neuroadaptive Fault-Tolerant Control of Nonlinear Systems Under Output Constraints and Actuation Faults.

    Science.gov (United States)

    Zhao, Kai; Song, Yongduan; Shen, Zhixi

    2018-02-01

    In this paper, a neuroadaptive fault-tolerant tracking control method is proposed for a class of time-delay pure-feedback systems in the presence of external disturbances and actuation faults. The proposed controller can achieve prescribed transient and steady-state performance, despite uncertain time delays and output constraints as well as actuation faults. By combining a tangent barrier Lyapunov-Krasovskii function with the dynamic surface control technique, the neural network unit in the developed control scheme is able to take its action from the very beginning and play its learning/approximating role safely during the entire system operational envelope, leading to enhanced control performance without the danger of violating compact set precondition. Furthermore, prescribed transient performance and output constraints are strictly ensured in the presence of nonaffine uncertainties, external disturbances, and undetectable actuation faults. The control strategy is also validated by numerical simulation.

  5. Active fault tolerance control of a wind turbine system using an unknown input observer with an actuator fault

    Directory of Open Access Journals (Sweden)

    Li Shanzhi

    2018-03-01

    Full Text Available This paper proposes a fault tolerant control scheme based on an unknown input observer for a wind turbine system subject to an actuator fault and disturbance. Firstly, an unknown input observer for state estimation and fault detection using a linear parameter varying model is developed. By solving linear matrix inequalities (LMIs and linear matrix equalities (LMEs, the gains of the unknown input observer are obtained. The convergence of the unknown input observer is also analysed with Lyapunov theory. Secondly, using fault estimation, an active fault tolerant controller is applied to a wind turbine system. Finally, a simulation of a wind turbine benchmark with an actuator fault is tested for the proposed method. The simulation results indicate that the proposed FTC scheme is efficient.

  6. Effects of Fault Displacement on Emplacement Drifts

    International Nuclear Information System (INIS)

    Duan, F.

    2000-01-01

    The purpose of this analysis is to evaluate potential effects of fault displacement on emplacement drifts, including drip shields and waste packages emplaced in emplacement drifts. The output from this analysis not only provides data for the evaluation of long-term drift stability but also supports the Engineered Barrier System (EBS) process model report (PMR) and Disruptive Events Report currently under development. The primary scope of this analysis includes (1) examining fault displacement effects in terms of induced stresses and displacements in the rock mass surrounding an emplacement drift and (2 ) predicting fault displacement effects on the drip shield and waste package. The magnitude of the fault displacement analyzed in this analysis bounds the mean fault displacement corresponding to an annual frequency of exceedance of 10 -5 adopted for the preclosure period of the repository and also supports the postclosure performance assessment. This analysis is performed following the development plan prepared for analyzing effects of fault displacement on emplacement drifts (CRWMS M and O 2000). The analysis will begin with the identification and preparation of requirements, criteria, and inputs. A literature survey on accommodating fault displacements encountered in underground structures such as buried oil and gas pipelines will be conducted. For a given fault displacement, the least favorable scenario in term of the spatial relation of a fault to an emplacement drift is chosen, and the analysis is then performed analytically. Based on the analysis results, conclusions are made regarding the effects and consequences of fault displacement on emplacement drifts. Specifically, the analysis will discuss loads which can be induced by fault displacement on emplacement drifts, drip shield and/or waste packages during the time period of postclosure

  7. Progress in development of the advanced Thomson scattering diagnostics

    International Nuclear Information System (INIS)

    Hatae, T; Naito, O; Howard, J; Ebizuka, N; Yoshida, H; Nakatsuka, M; Fujita, H; Kajita, S; Narihara, K; Yamada, I; Funaba, H; Hirano, Y; Koguchi, H

    2010-01-01

    We have been studied the advanced Thomson scattering diagnostics from viewpoints of new concepts, laser technology and spectrum analysis. This paper summarizes results of development on technologies for advanced Thomson scattering diagnostics.

  8. A study of diagnostics expert system for accelerator applications

    International Nuclear Information System (INIS)

    Tyagi, Y.; Banerji, Anil; Kotaiah, S.

    2003-01-01

    Knowledge based techniques are proving to be useful in a number of problem domains which typically requires human expertise. Expert systems employing knowledge based techniques are a recent product of artificial intelligence. Methods developed in the artificial intelligence area can be applied with success for certain classes of problems in accelerator. Accelerators are complex devices with thousands of components. The number of possible faults or problems that can appear is enormous. A diagnostics expert system can provide great help in finding and diagnosing problems in Indus-II accelerator sub-systems. (author)

  9. Fault tree handbook

    International Nuclear Information System (INIS)

    Haasl, D.F.; Roberts, N.H.; Vesely, W.E.; Goldberg, F.F.

    1981-01-01

    This handbook describes a methodology for reliability analysis of complex systems such as those which comprise the engineered safety features of nuclear power generating stations. After an initial overview of the available system analysis approaches, the handbook focuses on a description of the deductive method known as fault tree analysis. The following aspects of fault tree analysis are covered: basic concepts for fault tree analysis; basic elements of a fault tree; fault tree construction; probability, statistics, and Boolean algebra for the fault tree analyst; qualitative and quantitative fault tree evaluation techniques; and computer codes for fault tree evaluation. Also discussed are several example problems illustrating the basic concepts of fault tree construction and evaluation

  10. Managing Space System Faults: Coalescing NASA's Views

    Science.gov (United States)

    Muirhead, Brian; Fesq, Lorraine

    2012-01-01

    Managing faults and their resultant failures is a fundamental and critical part of developing and operating aerospace systems. Yet, recent studies have shown that the engineering "discipline" required to manage faults is not widely recognized nor evenly practiced within the NASA community. Attempts to simply name this discipline in recent years has been fraught with controversy among members of the Integrated Systems Health Management (ISHM), Fault Management (FM), Fault Protection (FP), Hazard Analysis (HA), and Aborts communities. Approaches to managing space system faults typically are unique to each organization, with little commonality in the architectures, processes and practices across the industry.

  11. Fault isolability conditions for linear systems with additive faults

    DEFF Research Database (Denmark)

    Niemann, Hans Henrik; Stoustrup, Jakob

    2006-01-01

    In this paper, we shall show that an unlimited number of additive single faults can be isolated under mild conditions if a general isolation scheme is applied. Multiple faults are also covered. The approach is algebraic and is based on a set representation of faults, where all faults within a set...

  12. Development of PETAL diagnostics: PETAPhys project

    Science.gov (United States)

    Raffestin, D.; Boutoux, G.; Baggio, J.; Batani, D.; Blanchot, N.; Bretheau, D.; Hulin, S.; D'Humieres, E.; Granet, F.; Longhi, Th.; Meyer, Ch.; Moreno, Q.; Nuter, R.; Rault, J.; Tikhonchuk, V.; Universite de Bordeaux/Celia Team; CEA. DAM/Cesta Team

    2017-10-01

    Beginning of autumn 2017, PETAL, a Petawatt laser beam, will be operated for experiments on the LMJ facility at the CEA/ Cesta research center. The PETAPhys project provides a support to the qualification phase of the PETAL laser operation. Within the PETAPhys project, we are developing two simple and robust diagnostics permitting both to characterize the focal spot of the PETAL beam and to measure the hard X-ray spectrum at each shot. The first diagnostic consists in optical imaging of the PETAL beam focal spot in the spectral range of the second and third harmonic radiation emitted from the target. The second diagnostic is a hard X-ray dosimeter consisting in a stack of imaging plates (IP) and filters, either placed inside a re-entrant tube or inserted close to target. Numerical simulations as well as experiments on small scale facilities have been performed to design these diagnostics. If available, preliminary results from PETAL experiments will be discussed. We acknowledge the financial support from the French National Research Agency (ANR) in the framework of ``the investments for the future'' Programme IdEx Bordeaux-LAPHIA (ANR-10-IDEX-03-02).

  13. Fault detection and fault tolerant control of a smart base isolation system with magneto-rheological damper

    International Nuclear Information System (INIS)

    Wang, Han; Song, Gangbing

    2011-01-01

    Fault detection and isolation (FDI) in real-time systems can provide early warnings for faulty sensors and actuator signals to prevent events that lead to catastrophic failures. The main objective of this paper is to develop FDI and fault tolerant control techniques for base isolation systems with magneto-rheological (MR) dampers. Thus, this paper presents a fixed-order FDI filter design procedure based on linear matrix inequalities (LMI). The necessary and sufficient conditions for the existence of a solution for detecting and isolating faults using the H ∞ formulation is provided in the proposed filter design. Furthermore, an FDI-filter-based fuzzy fault tolerant controller (FFTC) for a base isolation structure model was designed to preserve the pre-specified performance of the system in the presence of various unknown faults. Simulation and experimental results demonstrated that the designed filter can successfully detect and isolate faults from displacement sensors and accelerometers while maintaining excellent performance of the base isolation technology under faulty conditions

  14. A summary of the active fault investigation in the extension sea area of Kikugawa fault and the Nishiyama fault , N-S direction fault in south west Japan

    Science.gov (United States)

    Abe, S.

    2010-12-01

    In this study, we carried out two sets of active fault investigation by the request from Ministry of Education, Culture, Sports, Science and Technology in the sea area of the extension of Kikugawa fault and the Nishiyama fault. We want to clarify the five following matters about both active faults based on those results. (1)Fault continuity of the land and the sea. (2) The length of the active fault. (3) The division of the segment. (4) Activity characteristics. In this investigation, we carried out a digital single channel seismic reflection survey in the whole area of both active faults. In addition, a high-resolution multichannel seismic reflection survey was carried out to recognize the detailed structure of a shallow stratum. Furthermore, the sampling with the vibrocoring to get information of the sedimentation age was carried out. The reflection profile of both active faults was extremely clear. The characteristics of the lateral fault such as flower structure, the dispersion of the active fault were recognized. In addition, from analysis of the age of the stratum, it was recognized that the thickness of the sediment was extremely thin in Holocene epoch on the continental shelf in this sea area. It was confirmed that the Kikugawa fault extended to the offing than the existing results of research by a result of this investigation. In addition, the width of the active fault seems to become wide toward the offing while dispersing. At present, we think that we can divide Kikugawa fault into some segments based on the distribution form of the segment. About the Nishiyama fault, reflection profiles to show the existence of the active fault was acquired in the sea between Ooshima and Kyushu. From this result and topographical existing results of research in Ooshima, it is thought that Nishiyama fault and the Ooshima offing active fault are a series of structure. As for Ooshima offing active fault, the upheaval side changes, and a direction changes too. Therefore, we

  15. Fault detection for piecewise affine systems with application to ship propulsion systems.

    Science.gov (United States)

    Yang, Ying; Linlin, Li; Ding, Steven X; Qiu, Jianbin; Peng, Kaixiang

    2017-09-09

    In this paper, the design approach of non-synchronized diagnostic observer-based fault detection (FD) systems is investigated for piecewise affine processes via continuous piecewise Lyapunov functions. Considering that the dynamics of piecewise affine systems in different regions can be considerably different, the weighting matrices are used to weight the residual of each region, so as to optimize the fault detectability. A numerical example and a case study on a ship propulsion system are presented in the end to demonstrate the effectiveness of the proposed results. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

  16. A Comparison of Hybrid Approaches for Turbofan Engine Gas Path Fault Diagnosis

    Science.gov (United States)

    Lu, Feng; Wang, Yafan; Huang, Jinquan; Wang, Qihang

    2016-09-01

    A hybrid diagnostic method utilizing Extended Kalman Filter (EKF) and Adaptive Genetic Algorithm (AGA) is presented for performance degradation estimation and sensor anomaly detection of turbofan engine. The EKF is used to estimate engine component performance degradation for gas path fault diagnosis. The AGA is introduced in the integrated architecture and applied for sensor bias detection. The contributions of this work are the comparisons of Kalman Filters (KF)-AGA algorithms and Neural Networks (NN)-AGA algorithms with a unified framework for gas path fault diagnosis. The NN needs to be trained off-line with a large number of prior fault mode data. When new fault mode occurs, estimation accuracy by the NN evidently decreases. However, the application of the Linearized Kalman Filter (LKF) and EKF will not be restricted in such case. The crossover factor and the mutation factor are adapted to the fitness function at each generation in the AGA, and it consumes less time to search for the optimal sensor bias value compared to the Genetic Algorithm (GA). In a word, we conclude that the hybrid EKF-AGA algorithm is the best choice for gas path fault diagnosis of turbofan engine among the algorithms discussed.

  17. Diagnostics development for E-beam excited air channels

    Science.gov (United States)

    Eckstrom, D. J.; Dickenson, J. S.

    1982-02-01

    As the tempo of development of particle beam weapons increases, more detailed diagnostics of the interaction of the particle beam with the atmosphere are being proposed and implemented. Some of these diagnostics involve probing of the excited air channel with visible wavelength laser radiation. Examples include the use of visible wavelength interferometry to measure electron density profiles in the nose of the beam Ri81 and Stark shift measurements to determine self-induced electric fields Hi81, DR81. In these diagnostics, the change in laser intensity due to the desired diagnostic effect can be quite small, leading to the possibility that other effects, such as gas phase absorption, could seriously interfere with the measurement.

  18. Fault finder

    Science.gov (United States)

    Bunch, Richard H.

    1986-01-01

    A fault finder for locating faults along a high voltage electrical transmission line. Real time monitoring of background noise and improved filtering of input signals is used to identify the occurrence of a fault. A fault is detected at both a master and remote unit spaced along the line. A master clock synchronizes operation of a similar clock at the remote unit. Both units include modulator and demodulator circuits for transmission of clock signals and data. All data is received at the master unit for processing to determine an accurate fault distance calculation.

  19. Automatic fault tracing of active faults in the Sutlej valley (NW-Himalayas, India)

    Science.gov (United States)

    Janda, C.; Faber, R.; Hager, C.; Grasemann, B.

    2003-04-01

    In the Sutlej Valley the Lesser Himalayan Crystalline Sequence (LHCS) is actively extruding between the Munsiari Thrust (MT) at the base, and the Karcham Normal Fault (KNF) at the top. The clear evidences for ongoing deformation are brittle faults in Holocene lake deposits, hot springs activity near the faults and dramatically younger cooling ages within the LHCS (Vannay and Grasemann, 2001). Because these brittle fault zones obviously influence the morphology in the field we developed a new method for automatically tracing the intersections of planar fault geometries with digital elevation models (Faber, 2002). Traditional mapping techniques use structure contours (i.e. lines or curves connecting points of equal elevation on a geological structure) in order to construct intersections of geological structures with topographic maps. However, even if the geological structure is approximated by a plane and therefore structure contours are equally spaced lines, this technique is rather time consuming and inaccurate, because errors are cumulative. Drawing structure contours by hand makes it also impossible to slightly change the azimuth and dip direction of the favoured plane without redrawing everything from the beginning on. However, small variations of the fault position which are easily possible by either inaccuracies of measurement in the field or small local variations in the trend and/or dip of the fault planes can have big effects on the intersection with topography. The developed method allows to interactively view intersections in a 2D and 3D mode. Unlimited numbers of planes can be moved separately in 3 dimensions (translation and rotation) and intersections with the topography probably following morphological features can be mapped. Besides the increase of efficiency this method underlines the shortcoming of classical lineament extraction ignoring the dip of planar structures. Using this method, areas of active faulting influencing the morphology, can be

  20. A Statistical Parameter Analysis and SVM Based Fault Diagnosis Strategy for Dynamically Tuned Gyroscopes

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    Gyro's fault diagnosis plays a critical role in inertia navigation systems for higher reliability and precision. A new fault diagnosis strategy based on the statistical parameter analysis (SPA) and support vector machine(SVM) classification model was proposed for dynamically tuned gyroscopes (DTG). The SPA, a kind of time domain analysis approach, was introduced to compute a set of statistical parameters of vibration signal as the state features of DTG, with which the SVM model, a novel learning machine based on statistical learning theory (SLT), was applied and constructed to train and identify the working state of DTG. The experimental results verify that the proposed diagnostic strategy can simply and effectively extract the state features of DTG, and it outperforms the radial-basis function (RBF) neural network based diagnostic method and can more reliably and accurately diagnose the working state of DTG.

  1. The Sorong Fault Zone, Indonesia: Mapping a Fault Zone Offshore

    Science.gov (United States)

    Melia, S.; Hall, R.

    2017-12-01

    The Sorong Fault Zone is a left-lateral strike-slip fault zone in eastern Indonesia, extending westwards from the Bird's Head peninsula of West Papua towards Sulawesi. It is the result of interactions between the Pacific, Caroline, Philippine Sea, and Australian Plates and much of it is offshore. Previous research on the fault zone has been limited by the low resolution of available data offshore, leading to debates over the extent, location, and timing of movements, and the tectonic evolution of eastern Indonesia. Different studies have shown it north of the Sula Islands, truncated south of Halmahera, continuing to Sulawesi, or splaying into a horsetail fan of smaller faults. Recently acquired high resolution multibeam bathymetry of the seafloor (with a resolution of 15-25 meters), and 2D seismic lines, provide the opportunity to trace the fault offshore. The position of different strands can be identified. On land, SRTM topography shows that in the northern Bird's Head the fault zone is characterised by closely spaced E-W trending faults. NW of the Bird's Head offshore there is a fold and thrust belt which terminates some strands. To the west of the Bird's Head offshore the fault zone diverges into multiple strands trending ENE-WSW. Regions of Riedel shearing are evident west of the Bird's Head, indicating sinistral strike-slip motion. Further west, the ENE-WSW trending faults turn to an E-W trend and there are at least three fault zones situated immediately south of Halmahera, north of the Sula Islands, and between the islands of Sanana and Mangole where the fault system terminates in horsetail strands. South of the Sula islands some former normal faults at the continent-ocean boundary with the North Banda Sea are being reactivated as strike-slip faults. The fault zone does not currently reach Sulawesi. The new fault map differs from previous interpretations concerning the location, age and significance of different parts of the Sorong Fault Zone. Kinematic

  2. Industrial Cost-Benefit Assessment for Fault-tolerant Control Systems

    DEFF Research Database (Denmark)

    Thybo, Claus; Blanke, Mogens

    1998-01-01

    Economic aspects are decisive for industrial acceptance of research concepts including the promising ideas in fault tolerant control. Fault tolerance is the ability of a system to detect, isolate and accommodate a fault, such that simple faults in a sub-system do not develop into failures...... at a system level. In a design phase for an industrial system, possibilities span from fail safe design where any single point failure is accommodated by hardware, over fault-tolerant design where selected faults are handled without extra hardware, to fault-ignorant design where no extra precaution is taken...

  3. Enhanced DET-Based Fault Signature Analysis for Reliable Diagnosis of Single and Multiple-Combined Bearing Defects

    Directory of Open Access Journals (Sweden)

    In-Kyu Jeong

    2015-01-01

    Full Text Available To early identify cylindrical roller bearing failures, this paper proposes a comprehensive bearing fault diagnosis method, which consists of spectral kurtosis analysis for finding the most informative subband signal well representing abnormal symptoms about the bearing failures, fault signature calculation using this subband signal, enhanced distance evaluation technique- (EDET- based fault signature analysis that outputs the most discriminative fault features for accurate diagnosis, and identification of various single and multiple-combined cylindrical roller bearing defects using the simplified fuzzy adaptive resonance map (SFAM. The proposed comprehensive bearing fault diagnosis methodology is effective for accurate bearing fault diagnosis, yielding an average classification accuracy of 90.35%. In this paper, the proposed EDET specifically addresses shortcomings in the conventional distance evaluation technique (DET by accurately estimating the sensitivity of each fault signature for each class. To verify the efficacy of the EDET-based fault signature analysis for accurate diagnosis, a diagnostic performance comparison is carried between the proposed EDET and the conventional DET in terms of average classification accuracy. In fact, the proposed EDET achieves up to 106.85% performance improvement over the conventional DET in average classification accuracy.

  4. Dynamics Modeling and Analysis of Local Fault of Rolling Element Bearing

    Directory of Open Access Journals (Sweden)

    Lingli Cui

    2015-01-01

    Full Text Available This paper presents a nonlinear vibration model of rolling element bearings with 5 degrees of freedom based on Hertz contact theory and relevant bearing knowledge of kinematics and dynamics. The slipping of ball, oil film stiffness, and the nonlinear time-varying stiffness of the bearing are taken into consideration in the model proposed here. The single-point local fault model of rolling element bearing is introduced into the nonlinear model with 5 degrees of freedom according to the loss of the contact deformation of ball when it rolls into and out of the local fault location. The functions of spall depth corresponding to defects of different shapes are discussed separately in this paper. Then the ode solver in Matlab is adopted to perform a numerical solution on the nonlinear vibration model to simulate the vibration response of the rolling elements bearings with local fault. The simulation signals analysis results show a similar behavior and pattern to that observed in the processed experimental signals of rolling element bearings in both time domain and frequency domain which validated the nonlinear vibration model proposed here to generate typical rolling element bearings local fault signals for possible and effective fault diagnostic algorithms research.

  5. Bayesian based Diagnostic Model for Condition based Maintenance of Offshore Wind Farms

    DEFF Research Database (Denmark)

    Asgarpour, Masoud; Sørensen, John Dalsgaard

    2018-01-01

    Operation and maintenance costs are a major contributor to the Levelized Cost of Energy for electricity produced by offshore wind and can be significantly reduced if existing corrective actions are performed as efficiently as possible and if future corrective actions are avoided by performing...... sufficient preventive actions. This paper presents an applied and generic diagnostic model for fault detection and condition based maintenance of offshore wind components. The diagnostic model is based on two probabilistic matrices; first, a confidence matrix, representing the probability of detection using...... for a wind turbine component based on vibration, temperature, and oil particle fault detection methods. The last part of the paper will have a discussion of the case study results and present conclusions....

  6. Recording real case data of earth faults in distribution lines

    Energy Technology Data Exchange (ETDEWEB)

    Haenninen, S. [VTT Energy, Espoo (Finland)

    1996-12-31

    The most common fault type in the electrical distribution networks is the single phase to earth fault. According to the earlier studies, for instance in Nordic countries, about 80 % of all faults are of this type. To develop the protection and fault location systems, it is important to obtain real case data of disturbances and faults which occur in the networks. For example, the earth fault initial transients can be used for earth fault location. The aim of this project was to collect and analyze real case data of the earth fault disturbances in the medium voltage distribution networks (20 kV). Therefore, data of fault occurrences were recorded at two substations, of which one has an unearthed and the other a compensated neutral, measured as follows: (a) the phase currents and neutral current for each line in the case of low fault resistance (b) the phase voltages and neutral voltage from the voltage measuring bay in the case of low fault resistance (c) the neutral voltage and the components of 50 Hz at the substation in the case of high fault resistance. In addition, the basic data of the fault occurrences were collected (data of the line, fault location, cause and so on). The data will be used in the development work of fault location and earth fault protection systems

  7. Recording real case data of earth faults in distribution lines

    Energy Technology Data Exchange (ETDEWEB)

    Haenninen, S [VTT Energy, Espoo (Finland)

    1997-12-31

    The most common fault type in the electrical distribution networks is the single phase to earth fault. According to the earlier studies, for instance in Nordic countries, about 80 % of all faults are of this type. To develop the protection and fault location systems, it is important to obtain real case data of disturbances and faults which occur in the networks. For example, the earth fault initial transients can be used for earth fault location. The aim of this project was to collect and analyze real case data of the earth fault disturbances in the medium voltage distribution networks (20 kV). Therefore, data of fault occurrences were recorded at two substations, of which one has an unearthed and the other a compensated neutral, measured as follows: (a) the phase currents and neutral current for each line in the case of low fault resistance (b) the phase voltages and neutral voltage from the voltage measuring bay in the case of low fault resistance (c) the neutral voltage and the components of 50 Hz at the substation in the case of high fault resistance. In addition, the basic data of the fault occurrences were collected (data of the line, fault location, cause and so on). The data will be used in the development work of fault location and earth fault protection systems

  8. Development of advanced diagnostic technologies for motor-operated valves

    International Nuclear Information System (INIS)

    Hegi, Kotaro; Shimizu, Shunichi; Higuma, Koji; Nishino, Koji; Osaki, Kenji; Watanabe, Kazumi; Hamano, Frank

    2010-01-01

    As use of condition-based maintenance is allowed in the new regulatory inspection system employed in Japan's nuclear power plants in 2009, development of advanced diagnostic technologies for motor-operated valves (MOVs) is now required. This report discusses advanced technologies in valve-setup verification, valve performance evaluation, monitoring of valve/actuator conditions by performance diagnostic system and moreover detection of stem crack by ultrasonic diagnostic system. (author)

  9. Wind turbine fault detection and fault tolerant control

    DEFF Research Database (Denmark)

    Odgaard, Peter Fogh; Johnson, Kathryn

    2013-01-01

    In this updated edition of a previous wind turbine fault detection and fault tolerant control challenge, we present a more sophisticated wind turbine model and updated fault scenarios to enhance the realism of the challenge and therefore the value of the solutions. This paper describes...

  10. A compendium of computer codes in fault tree analysis

    International Nuclear Information System (INIS)

    Lydell, B.

    1981-03-01

    In the past ten years principles and methods for a unified system reliability and safety analysis have been developed. Fault tree techniques serve as a central feature of unified system analysis, and there exists a specific discipline within system reliability concerned with the theoretical aspects of fault tree evaluation. Ever since the fault tree concept was established, computer codes have been developed for qualitative and quantitative analyses. In particular the presentation of the kinetic tree theory and the PREP-KITT code package has influenced the present use of fault trees and the development of new computer codes. This report is a compilation of some of the better known fault tree codes in use in system reliability. Numerous codes are available and new codes are continuously being developed. The report is designed to address the specific characteristics of each code listed. A review of the theoretical aspects of fault tree evaluation is presented in an introductory chapter, the purpose of which is to give a framework for the validity of the different codes. (Auth.)

  11. Structural setting and kinematics of Nubian fault system, SE Western Desert, Egypt: An example of multi-reactivated intraplate strike-slip faults

    Science.gov (United States)

    Sakran, Shawky; Said, Said Mohamed

    2018-02-01

    Detailed surface geological mapping and subsurface seismic interpretation have been integrated to unravel the structural style and kinematic history of the Nubian Fault System (NFS). The NFS consists of several E-W Principal Deformation Zones (PDZs) (e.g. Kalabsha fault). Each PDZ is defined by spectacular E-W, WNW and ENE dextral strike-slip faults, NNE sinistral strike-slip faults, NE to ENE folds, and NNW normal faults. Each fault zone has typical self-similar strike-slip architecture comprising multi-scale fault segments. Several multi-scale uplifts and basins were developed at the step-over zones between parallel strike-slip fault segments as a result of local extension or contraction. The NNE faults consist of right-stepping sinistral strike-slip fault segments (e.g. Sin El Kiddab fault). The NNE sinistral faults extend for long distances ranging from 30 to 100 kms and cut one or two E-W PDZs. Two nearly perpendicular strike-slip tectonic regimes are recognized in the NFS; an inactive E-W Late Cretaceous - Early Cenozoic dextral transpression and an active NNE sinistral shear.

  12. Normal Fault and Tensile Fissure Network Development Around an Off-Axis Silica-Rich Volcanic Dome of the Alarcon Rise, Southern Gulf of California

    Science.gov (United States)

    Contreras, J.; Vega-Ramirez, L. A.; Spelz, R. M.; Portner, R. A.; Clague, D. A.

    2017-12-01

    The Monterey Bay Aquarium Research Institute collected in 2012 and 2015 high-resolution (1 m horizontal/0.2 m vertical) bathymetry data in the southern Gulf of California using an autonomous underwater vehicle (AUV) that bring to light an extensive array of normal faults and fissures cutting lava domes and smaller volcanic cones, pillow mounds and lava sheet flows of variable compositions along the Alarcon rise. Active faulting and fissure growth in the transition between the neovolcanic zone and adjacent axial summit trough, in a 6.9 x 1.5 km2 area at the NE segment of the rise, developed at some point between 6 Ka B.P. (14C) and the present time. We performed a population analysis of fracture networks imaged by the AUV that reveal contrasting scaling attributes between mode I (opening) and mode III (shearing) extensional structures. Opening-mode fractures are spatially constrained to narrow bands 400 m wide. The youngest set developed on pillow lavas 800 yr old (14C) of the neovolcanic zone. Regions of normal fault propagation by anti-plane shearing alternate with the tensile-fracture growth areas. This provides evidence for permutations in space of the stress field across the ridge axis. Moreover, fault-length frequency plots for both fracture networks show that opening-mode fractures are best fit using an exponential relationship whereas normal faults are best fit using a power-law relationship. These size distributions indicate tensile fractures rapidly reached a saturated state in which large fractures (102 m) accommodate most of the strain and appear to be constrained to a thin mechanical/thermal layer. Faults, by contrast, have slowly evolved to a state of self-organization characterized by growth by linkage with neighboring faults in the strike direction forming fault arrays with a maximum length of 2km. We also analyzed the development of faults in the vicinity of an off-axis rhyolitic dome. We find that faults have asymmetric, half-restricted slip

  13. Cryogenic systems advanced monitoring, fault diagnostics, and predictive maintenance

    CERN Document Server

    Arpaia, Pasquale; Inglese, Vitaliano; Pezzetti, Marco

    2018-01-01

    Cryogenics, the study and technology of materials and systems at very low temperature, is widely used for sensors and instruments requiring very highly precise measurements with low electrical resistance, especially for measurements of materials and energies at a very small scale. Thus, the need to understand how instruments operate and perform over time at temperatures below -2920 F (-1800 C) is critical, for applications from Magnetic Resonance Imaging (MRI) to Nuclear Magnetic Resonance Spectroscopy to instrumentation for particle accelerators of all kinds. This book brings to the reader guidance learned from work at the European Laboratory for Nuclear Research (CERN), and its large scale particle accelerator in Switzerland to help engineers and technicians implement best practices in instrumentation at cryogenic temperatures, including a better understanding of fault detection and predictive maintenance. Special problems with devices like flow meters, pressure gauges, and temperature gauges when operating...

  14. Development trends for diagnostic systems in nuclear power plants

    International Nuclear Information System (INIS)

    Kunze, U.; Pohl, U.

    1998-01-01

    Monitoring systems used in nuclear power plants have made remarkable progress over the past four or five years. Development has followed the trends and changes in philosophy for the purpose of monitoring systems in nuclear power plants: They are no longer expected to fulfill only safety tasks, the plant personnel require information on which to base condition-oriented maintenance. A new generation of monitoring and diagnostic systems has been developed by Siemens recently. This new generation, called Series '95, is PC-based. An overview is given for the KUeS '95 loose parts diagnostic system, the SUeS '95 vibration monitoring system, the FLUeS leak detection system and the SIPLUG valve diagnostics system. The objectives behind the development of these new systems are both safety-related and economic. The new systems improve the reliability and quality of monitoring techniques and incorporate better detection and diagnostic capabilities. Progress has also been made in automation of the systems so as to reduce routine work, give higher sensitivity for the monitoring task and reduce the scope of maintenance. (author)

  15. Training for Skill in Fault Diagnosis

    Science.gov (United States)

    Turner, J. D.

    1974-01-01

    The Knitting, Lace and Net Industry Training Board has developed a training innovation called fault diagnosis training. The entire training process concentrates on teaching based on the experiences of troubleshooters or any other employees whose main tasks involve fault diagnosis and rectification. (Author/DS)

  16. Fault Diagnosis Method for a Mine Hoist in the Internet of Things Environment.

    Science.gov (United States)

    Li, Juanli; Xie, Jiacheng; Yang, Zhaojian; Li, Junjie

    2018-06-13

    To reduce the difficulty of acquiring and transmitting data in mining hoist fault diagnosis systems and to mitigate the low efficiency and unreasonable reasoning process problems, a fault diagnosis method for mine hoisting equipment based on the Internet of Things (IoT) is proposed in this study. The IoT requires three basic architectural layers: a perception layer, network layer, and application layer. In the perception layer, we designed a collaborative acquisition system based on the ZigBee short distance wireless communication technology for key components of the mine hoisting equipment. Real-time data acquisition was achieved, and a network layer was created by using long-distance wireless General Packet Radio Service (GPRS) transmission. The transmission and reception platforms for remote data transmission were able to transmit data in real time. A fault diagnosis reasoning method is proposed based on the improved Dezert-Smarandache Theory (DSmT) evidence theory, and fault diagnosis reasoning is performed. Based on interactive technology, a humanized and visualized fault diagnosis platform is created in the application layer. The method is then verified. A fault diagnosis test of the mine hoisting mechanism shows that the proposed diagnosis method obtains complete diagnostic data, and the diagnosis results have high accuracy and reliability.

  17. "3D_Fault_Offsets," a Matlab Code to Automatically Measure Lateral and Vertical Fault Offsets in Topographic Data: Application to San Andreas, Owens Valley, and Hope Faults

    Science.gov (United States)

    Stewart, N.; Gaudemer, Y.; Manighetti, I.; Serreau, L.; Vincendeau, A.; Dominguez, S.; Mattéo, L.; Malavieille, J.

    2018-01-01

    Measuring fault offsets preserved at the ground surface is of primary importance to recover earthquake and long-term slip distributions and understand fault mechanics. The recent explosion of high-resolution topographic data, such as Lidar and photogrammetric digital elevation models, offers an unprecedented opportunity to measure dense collections of fault offsets. We have developed a new Matlab code, 3D_Fault_Offsets, to automate these measurements. In topographic data, 3D_Fault_Offsets mathematically identifies and represents nine of the most prominent geometric characteristics of common sublinear markers along faults (especially strike slip) in 3-D, such as the streambed (minimum elevation), top, free face and base of channel banks or scarps (minimum Laplacian, maximum gradient, and maximum Laplacian), and ridges (maximum elevation). By calculating best fit lines through the nine point clouds on either side of the fault, the code computes the lateral and vertical offsets between the piercing points of these lines onto the fault plane, providing nine lateral and nine vertical offset measures per marker. Through a Monte Carlo approach, the code calculates the total uncertainty on each offset. It then provides tools to statistically analyze the dense collection of measures and to reconstruct the prefaulted marker geometry in the horizontal and vertical planes. We applied 3D_Fault_Offsets to remeasure previously published offsets across 88 markers on the San Andreas, Owens Valley, and Hope faults. We obtained 5,454 lateral and vertical offset measures. These automatic measures compare well to prior ones, field and remote, while their rich record provides new insights on the preservation of fault displacements in the morphology.

  18. Design and development of an automated D.C. ground fault detection and location system for Cirus

    International Nuclear Information System (INIS)

    Marik, S.K.; Ramesh, N.; Jain, J.K.; Srivastava, A.P.

    2002-01-01

    Full text: The original design of Cirus safety system provided for automatic detection of ground fault in class I D.C. power supply system and its annunciation followed by delayed reactor trip. Identification of a faulty section was required to be done manually by switching off various sections one at a time thus requiring a lot of shutdown time to identify the faulty section. Since class I power supply is provided for safety control system, quick detection and location of ground faults in this supply is necessary as these faults have potential to bypass safety interlocks and hence the need for a new system for automatic location of a faulty section. Since such systems are not readily available in the market, in-house efforts were made to design and develop a plant-specific system, which has been installed and commissioned

  19. A computer-aided diagnostic and troubleshooting system for fuel cell power plants

    International Nuclear Information System (INIS)

    Unkle, C.R.

    1990-10-01

    This Interactive Computer-Aided Troubleshooting System (ICATS) was designed as a troubleshooting aid for the Tokyo Electric Power Company (TEPCO) 11-megawatt dc Module (DCM). ICATS represents an integration of the System Testability and Maintenance Program (STAMP reg-sign) and the Portable Interactive Troubleshooter (POINTER trademark) software packages developed by ARINC Research Corporation. ICATS was designed to aid in the fault isolation of shutdown conditions that may occur in the DCM during on-load operations and start-up, and hold conditions that may occur during start-up. ICATS may also be used to help fault-isolate a return-to-standby condition occurring from on-load operation of the DCM. This report describes the development of ICATS and the ICATS functional design. The unique features of STAMP and POINTER, which allow for diagnostic aids to be designed for systems not yet built and operating, are also described. 10 refs., 21 figs., 6 tabs

  20. How do horizontal, frictional discontinuities affect reverse fault-propagation folding?

    Science.gov (United States)

    Bonanno, Emanuele; Bonini, Lorenzo; Basili, Roberto; Toscani, Giovanni; Seno, Silvio

    2017-09-01

    The development of new reverse faults and related folds is strongly controlled by the mechanical characteristics of the host rocks. In this study we analyze the impact of a specific kind of anisotropy, i.e. thin mechanical and frictional discontinuities, in affecting the development of reverse faults and of the associated folds using physical scaled models. We perform analog modeling introducing one or two initially horizontal, thin discontinuities above an initially blind fault dipping at 30° in one case, and 45° in another, and then compare the results with those obtained from a fully isotropic model. The experimental results show that the occurrence of thin discontinuities affects both the development and the propagation of new faults and the shape of the associated folds. New faults 1) accelerate or decelerate their propagation depending on the location of the tips with respect to the discontinuities, 2) cross the discontinuities at a characteristic angle (∼90°), and 3) produce folds with different shapes, resulting not only from the dip of the new faults but also from their non-linear propagation history. Our results may have direct impact on future kinematic models, especially those aimed to reconstruct the tectonic history of faults that developed in layered rocks or in regions affected by pre-existing faults.

  1. Imaging of Subsurface Faults using Refraction Migration with Fault Flooding

    KAUST Repository

    Metwally, Ahmed Mohsen Hassan

    2017-05-31

    We propose a novel method for imaging shallow faults by migration of transmitted refraction arrivals. The assumption is that there is a significant velocity contrast across the fault boundary that is underlain by a refracting interface. This procedure, denoted as refraction migration with fault flooding, largely overcomes the difficulty in imaging shallow faults with seismic surveys. Numerical results successfully validate this method on three synthetic examples and two field-data sets. The first field-data set is next to the Gulf of Aqaba and the second example is from a seismic profile recorded in Arizona. The faults detected by refraction migration in the Gulf of Aqaba data were in agreement with those indicated in a P-velocity tomogram. However, a new fault is detected at the end of the migration image that is not clearly seen in the traveltime tomogram. This result is similar to that for the Arizona data where the refraction image showed faults consistent with those seen in the P-velocity tomogram, except it also detected an antithetic fault at the end of the line. This fault cannot be clearly seen in the traveltime tomogram due to the limited ray coverage.

  2. Imaging of Subsurface Faults using Refraction Migration with Fault Flooding

    KAUST Repository

    Metwally, Ahmed Mohsen Hassan; Hanafy, Sherif; Guo, Bowen; Kosmicki, Maximillian Sunflower

    2017-01-01

    We propose a novel method for imaging shallow faults by migration of transmitted refraction arrivals. The assumption is that there is a significant velocity contrast across the fault boundary that is underlain by a refracting interface. This procedure, denoted as refraction migration with fault flooding, largely overcomes the difficulty in imaging shallow faults with seismic surveys. Numerical results successfully validate this method on three synthetic examples and two field-data sets. The first field-data set is next to the Gulf of Aqaba and the second example is from a seismic profile recorded in Arizona. The faults detected by refraction migration in the Gulf of Aqaba data were in agreement with those indicated in a P-velocity tomogram. However, a new fault is detected at the end of the migration image that is not clearly seen in the traveltime tomogram. This result is similar to that for the Arizona data where the refraction image showed faults consistent with those seen in the P-velocity tomogram, except it also detected an antithetic fault at the end of the line. This fault cannot be clearly seen in the traveltime tomogram due to the limited ray coverage.

  3. [Development of the lung cancer diagnostic system].

    Science.gov (United States)

    Lv, You-Jiang; Yu, Shou-Yi

    2009-07-01

    To develop a lung cancer diagnosis system. A retrospective analysis was conducted in 1883 patients with primary lung cancer or benign pulmonary diseases (pneumonia, tuberculosis, or pneumonia pseudotumor). SPSS11.5 software was used for data processing. For the relevant factors, a non-factor Logistic regression analysis was used followed by establishment of the regression model. Microsoft Visual Studio 2005 system development platform and VB.Net corresponding language were used to develop the lung cancer diagnosis system. The non-factor multi-factor regression model showed a goodness-of-fit (R2) of the model of 0.806, with a diagnostic accuracy for benign lung diseases of 92.8%, a diagnostic accuracy for lung cancer of 89.0%, and an overall accuracy of 90.8%. The model system for early clinical diagnosis of lung cancer has been established.

  4. Development of kink bands in granodiorite: Effect of mechanical heterogeneities, fault geometry, and friction

    Science.gov (United States)

    Chheda, T. D.; Nevitt, J. M.; Pollard, D. D.

    2014-12-01

    The formation of monoclinal right-lateral kink bands in Lake Edison granodiorite (central Sierra Nevada, CA) is investigated through field observations and mechanics based numerical modeling. Vertical faults act as weak surfaces within the granodiorite, and vertical granodiorite slabs bounded by closely-spaced faults curve into a kink. Leucocratic dikes are observed in association with kinking. Measurements were made on maps of Hilgard, Waterfall, Trail Fork, Kip Camp (Pollard and Segall, 1983b) and Bear Creek kink bands (Martel, 1998). Outcrop scale geometric parameters such as fault length andspacing, kink angle, and dike width are used to construct a representative geometry to be used in a finite element model. Three orders of fault were classified, length = 1.8, 7.2 and 28.8 m, and spacing = 0.3, 1.2 and 3.6 m, respectively. The model faults are oriented at 25° to the direction of shortening (horizontal most compressive stress), consistent with measurements of wing crack orientations in the field area. The model also includes a vertical leucocratic dike, oriented perpendicular to the faults and with material properties consistent with aplite. Curvature of the deformed faults across the kink band was used to compare the effects of material properties, strain, and fault and dike geometry. Model results indicate that the presence of the dike, which provides a mechanical heterogeneity, is critical to kinking in these rocks. Keeping properties of the model granodiorite constant, curvature increased with decrease in yield strength and Young's modulus of the dike. Curvature increased significantly as yield strength decreased from 95 to 90 MPa, and below this threshold value, limb rotation for the kink band was restricted to the dike. Changing Poisson's ratio had no significant effect. The addition of small faults between bounding faults, decreasing fault spacing or increasing dike width increases the curvature. Increasing friction along the faults decreases slip, so

  5. Fault diagnosis and fault-tolerant finite control set-model predictive control of a multiphase voltage-source inverter supplying BLDC motor.

    Science.gov (United States)

    Salehifar, Mehdi; Moreno-Equilaz, Manuel

    2016-01-01

    Due to its fault tolerance, a multiphase brushless direct current (BLDC) motor can meet high reliability demand for application in electric vehicles. The voltage-source inverter (VSI) supplying the motor is subjected to open circuit faults. Therefore, it is necessary to design a fault-tolerant (FT) control algorithm with an embedded fault diagnosis (FD) block. In this paper, finite control set-model predictive control (FCS-MPC) is developed to implement the fault-tolerant control algorithm of a five-phase BLDC motor. The developed control method is fast, simple, and flexible. A FD method based on available information from the control block is proposed; this method is simple, robust to common transients in motor and able to localize multiple open circuit faults. The proposed FD and FT control algorithm are embedded in a five-phase BLDC motor drive. In order to validate the theory presented, simulation and experimental results are conducted on a five-phase two-level VSI supplying a five-phase BLDC motor. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

  6. Diagnosis and Fault-Tolerant Control for Thruster-Assisted Position Mooring System

    DEFF Research Database (Denmark)

    Nguyen, Trong Dong; Blanke, Mogens; Sørensen, Asgeir

    2007-01-01

    Development of fault-tolerant control systems is crucial to maintain safe operation of o®shore installations. The objective of this paper is to develop a fault- tolerant control for thruster-assisted position mooring (PM) system with faults occurring in the mooring lines. Faults in line......'s pretension or line breaks will degrade the performance of the positioning of the vessel. Faults will be detected and isolated through a fault diagnosis procedure. When faults are detected, they can be accommodated through the control action in which only parameter of the controlled plant has to be updated...... to cope with the faulty condition. Simulations will be carried out to verify the advantages of the fault-tolerant control strategy for the PM system....

  7. Architecture of thrust faults with alongstrike variations in fault-plane dip: anatomy of the Lusatian Fault, Bohemian Massif

    Czech Academy of Sciences Publication Activity Database

    Coubal, Miroslav; Adamovič, Jiří; Málek, Jiří; Prouza, V.

    2014-01-01

    Roč. 59, č. 3 (2014), s. 183-208 ISSN 1802-6222 Institutional support: RVO:67985831 ; RVO:67985891 Keywords : fault architecture * fault plane geometry * drag structures * thrust fault * sandstone * Lusatian Fault Subject RIV: DB - Geology ; Mineralogy Impact factor: 1.405, year: 2014

  8. Fault Diagnosis and Fault-Tolerant Control of Wind Turbines via a Discrete Time Controller with a Disturbance Compensator

    Directory of Open Access Journals (Sweden)

    Yolanda Vidal

    2015-05-01

    Full Text Available This paper develops a fault diagnosis (FD and fault-tolerant control (FTC of pitch actuators in wind turbines. This is accomplished by combining a disturbance compensator with a controller, both of which are formulated in the discrete time domain. The disturbance compensator has a dual purpose: to estimate the actuator fault (which is used by the FD algorithm and to design the discrete time controller to obtain an FTC. That is, the pitch actuator faults are estimated, and then, the pitch control laws are appropriately modified to achieve an FTC with a comparable behavior to the fault-free case. The performance of the FD and FTC schemes is tested in simulations with the aero-elastic code FAST.

  9. Laboratory development and testing of spacecraft diagnostics

    Science.gov (United States)

    Amatucci, William; Tejero, Erik; Blackwell, Dave; Walker, Dave; Gatling, George; Enloe, Lon; Gillman, Eric

    2017-10-01

    The Naval Research Laboratory's Space Chamber experiment is a large-scale laboratory device dedicated to the creation of large-volume plasmas with parameters scaled to realistic space plasmas. Such devices make valuable contributions to the investigation of space plasma phenomena under controlled, reproducible conditions, allowing for the validation of theoretical models being applied to space data. However, in addition to investigations such as plasma wave and instability studies, such devices can also make valuable contributions to the development and testing of space plasma diagnostics. One example is the plasma impedance probe developed at NRL. Originally developed as a laboratory diagnostic, the sensor has now been flown on a sounding rocket, is included on a CubeSat experiment, and will be included on the DoD Space Test Program's STP-H6 experiment on the International Space Station. In this talk, we will describe how the laboratory simulation of space plasmas made this development path possible. Work sponsored by the US Naval Research Laboratory Base Program.

  10. Collection and analysis of existing information on applicability of investigation methods for estimation of beginning age of faulting in present faulting pattern

    International Nuclear Information System (INIS)

    Doke, Ryosuke; Yasue, Ken-ichi; Tanikawa, Shin-ichi; Nakayasu, Akio; Niizato, Tadafumi; Tanaka, Takenobu; Aoki, Michinori; Sekiya, Ayako

    2011-12-01

    In the field of R and D programs of a geological disposal of high level radioactive waste, it is great importance to develop a set of investigation and analysis techniques for the assessment of long-term geosphere stability over a geological time, which means that any changes of geological environment will not significantly impact on the long-term safety of a geological disposal system. In Japanese archipelago, crustal movements are so active that uplift and subsidence are remarkable in recent several hundreds of thousands of years. Therefore, it is necessary to assess the long-term geosphere stability taking into account a topographic change caused by crustal movements. One of the factors for the topographic change is the movement of an active fault, which is a geological process to release a strain accumulated by plate motion. A beginning age of the faulting in the present faulting pattern suggests the beginning age of neotectonic activities around the active fault, and also provides basic information to identifying the stage of a geomorphic development of mountains. Therefore, the age of faulting in the present faulting pattern is important information to estimate a topographic change in the future on the mountain regions of Japan. In this study, existing information related to methods for the estimation of the beginning age of the faulting in the present faulting pattern on the active fault were collected and reviewed. A principle of method, noticing points and technical know-hows in the application of the methods, data uncertainty, and so on were extracted from the existing information. Based on these extracted information, task-flows indicating working process on the estimation of the beginning age for the faulting of the active fault were illustrated on each method. Additionally, the distribution map of the beginning age with accuracy of faulting in the present faulting pattern on the active fault was illustrated. (author)

  11. Automatic vibration monitoring system for the diagnostic inspection of the WWER-440 type nuclear power plants

    International Nuclear Information System (INIS)

    Hollo, E.; Siklossy, P.; Toth, Zs.

    1982-01-01

    In the Hungarian Research Institute for Electric Power Industry (VEIKI) an automatic vibration monitoring system for diagnostics and inspection of nuclear power plants of type WWER-440 was developed. The paper summarizes the results of this work and investigates the use of mechanical vibrations and oscillations induced by flow for fault diagnosis. The design of the hardware system, the present software possibilities, the laboratory experiments and the guidelines for future software developments are also described in detail. (A.L.)

  12. Quaternary faulting in the Tatra Mountains, evidence from cave morphology and fault-slip analysis

    Directory of Open Access Journals (Sweden)

    Szczygieł Jacek

    2015-06-01

    Full Text Available Tectonically deformed cave passages in the Tatra Mts (Central Western Carpathians indicate some fault activity during the Quaternary. Displacements occur in the youngest passages of the caves indicating (based on previous U-series dating of speleothems an Eemian or younger age for those faults, and so one tectonic stage. On the basis of stress analysis and geomorphological observations, two different mechanisms are proposed as responsible for the development of these displacements. The first mechanism concerns faults that are located above the valley bottom and at a short distance from the surface, with fault planes oriented sub-parallel to the slopes. The radial, horizontal extension and vertical σ1 which is identical with gravity, indicate that these faults are the result of gravity sliding probably caused by relaxation after incision of valleys, and not directly from tectonic activity. The second mechanism is tilting of the Tatra Mts. The faults operated under WNW-ESE oriented extension with σ1 plunging steeply toward the west. Such a stress field led to normal dip-slip or oblique-slip displacements. The faults are located under the valley bottom and/or opposite or oblique to the slopes. The process involved the pre-existing weakest planes in the rock complex: (i in massive limestone mostly faults and fractures, (ii in thin-bedded limestone mostly inter-bedding planes. Thin-bedded limestones dipping steeply to the south are of particular interest. Tilting toward the N caused the hanging walls to move under the massif and not toward the valley, proving that the cause of these movements was tectonic activity and not gravity.

  13. Research of fault activity in Japan

    International Nuclear Information System (INIS)

    Nohara, T.; Nakatsuka, N.; Takeda, S.

    2004-01-01

    Six hundreds and eighty earthquakes causing significant damage have been recorded since the 7. century in Japan. It is important to recognize faults that will or are expected to be active in future in order to help reduce earthquake damage, estimate earthquake damage insurance and siting of nuclear facilities. Such faults are called 'active faults' in Japan, the definition of which is a fault that has moved intermittently for at least several hundred thousand years and is expected to continue to do so in future. Scientific research of active faults has been ongoing since the 1930's. Many results indicated that major earthquakes and fault movements in shallow crustal regions in Japan occurred repeatedly at existing active fault zones during the past. After the 1995 Southern Hyogo Prefecture Earthquake, 98 active fault zones were selected for fundamental survey, with the purpose of efficiently conducting an active fault survey in 'Plans for Fundamental Seismic Survey and Observation' by the headquarters for earthquake research promotion, which was attached to the Prime Minister's office of Japan. Forty two administrative divisions for earthquake disaster prevention have investigated the distribution and history of fault activity of 80 active fault zones. Although earthquake prediction is difficult, the behaviour of major active faults in Japan is being recognised. Japan Nuclear Cycle Development Institute (JNC) submitted a report titled 'H12: Project to Establish the. Scientific and Technical Basis for HLW Disposal in Japan' to the Atomic Energy Commission (AEC) of Japan for official review W. The Guidelines, which were defined by AEC, require the H12 Project to confirm the basic technical feasibility of safe HLW disposal in Japan. In this report the important issues relating to fault activity were described that are to understand the characteristics of current fault movements and the spatial extent and magnitude of the effects caused by these movements, and to

  14. Fault-tolerant Control of Inverter-fed Induction Motor Drives

    DEFF Research Database (Denmark)

    Thybo, C.

    . A description of the different frequency converter components, including models of the inverter, sensors and controllers was given, followed by a fault mode and effect analysis, which points out the potential fault modes of the design. Among the listed fault modes, two were found to be of particular practical...... University, was used as a framework for this work. A short review of the development cycle, including methods for generating and evaluating residuals, was presented. A cost-benefit analysis was proposed, as an extension to the FTC development cycle, to provide a better background for selecting the fault...... bilinear observers. A brief description of threshold- and statistical change detection was included with focus on mean value change detection in a noisy residual. The detection of encoder sensor faults was analysed and three approaches, for encoder fault detection, were proposed. The reference band...

  15. A fault-tolerant software strategy for digital systems

    Science.gov (United States)

    Hitt, E. F.; Webb, J. J.

    1984-01-01

    Techniques developed for producing fault-tolerant software are described. Tolerance is required because of the impossibility of defining fault-free software. Faults are caused by humans and can appear anywhere in the software life cycle. Tolerance is effected through error detection, damage assessment, recovery, and fault treatment, followed by return of the system to service. Multiversion software comprises two or more versions of the software yielding solutions which are examined by a decision algorithm. Errors can also be detected by extrapolation from previous results or by the acceptability of results. Violations of timing specifications can reveal errors, or the system can roll back to an error-free state when a defect is detected. The software, when used in flight control systems, must not impinge on time-critical responses. Efforts are still needed to reduce the costs of developing the fault-tolerant systems.

  16. Vibration Diagnostics as an effective Tool for Testing Engines of Internal Combustion

    Directory of Open Access Journals (Sweden)

    Ferenc Dömötör

    2017-10-01

    Full Text Available There are several methods of automotive diagnostics used in services to detect a large variety of faults and damages of various parts of engines of internal combustion. Undoubtedly, they are effective, but they are simply unable to find all types of mechanical faults occurring during the operation. This is the reason why authors of this paper tried to use a special tool, which has been proven for years for detecting faults of rolling element bearing in rotating machinery. During their research, the authors tried to find valuable results by measuring vibration of various parts of engines. Three items were tested, a Diesel engine and two Otto motors. A large number of measurements have been taken at various speed, at different points, in different directions, with different parameter setup, etc. However, there was one setup which has been applied to all three engines. It is the measurement setup of vibration velocity, in the frequency range of 2 Hz-300 Hz. Valuable consequences have been found regarding the clogging of the air filters and the exhaust systems. As a conclusion the authors expressed their opinion, that, apart from the traditional diagnostic methods used in services, vibration measurements can also be useful, especially for detecting faults of rolling element bearings.

  17. Robust Mpc for Actuator–Fault Tolerance Using Set–Based Passive Fault Detection and Active Fault Isolation

    Directory of Open Access Journals (Sweden)

    Xu Feng

    2017-03-01

    Full Text Available In this paper, a fault-tolerant control (FTC scheme is proposed for actuator faults, which is built upon tube-based model predictive control (MPC as well as set-based fault detection and isolation (FDI. In the class of MPC techniques, tubebased MPC can effectively deal with system constraints and uncertainties with relatively low computational complexity compared with other robust MPC techniques such as min-max MPC. Set-based FDI, generally considering the worst case of uncertainties, can robustly detect and isolate actuator faults. In the proposed FTC scheme, fault detection (FD is passive by using invariant sets, while fault isolation (FI is active by means of MPC and tubes. The active FI method proposed in this paper is implemented by making use of the constraint-handling ability of MPC to manipulate the bounds of inputs.

  18. Development of an equipment diagnostic system that evaluates sensor drift

    International Nuclear Information System (INIS)

    Kanada, Masaki; Arita, Setsuo; Tada, Nobuo; Yokota, Katsuo

    2011-01-01

    The importance of condition monitoring technology for equipment has increased with the introduction of condition-based maintenance in nuclear power plants. We are developing a diagnostic system using process signals for plant equipment, such as pumps and motors. It is important to enable the diagnostic system to distinguish sensor drift and equipment failure. We have developed a sensor drift diagnostic method that combines some highly correlative sensor signals by using the MT (Mahalanobis-Taguchi) method. Furthermore, we have developed an equipment failure diagnostic method that measures the Mahalanobis distance from the normal state of equipment by the MT method. These methods can respectively detect sensor drift and equipment failure, but there are the following problems. In the sensor drift diagnosis, there is a possibility of misjudging the sensor drift when the equipment failure occurs and the process signal changes because the behavior of the process signal is the same as that of the sensor drift. Oppositely, in the equipment failure diagnosis, there is a possibility of misjudging the equipment failure when the sensor drift occurs because the sensor drift influences the change of process signal. To solve these problems, we propose a diagnostic method combining the sensor drift diagnosis and the equipment failure diagnosis by the MT method. Firstly, the sensor drift values are estimated by the sensor drift diagnosis, and the sensor drift is removed from the process signal. It is necessary to judge the validity of the estimated sensor drift values before removing the sensor drift from the process signal. We developed a method for judging the validity of the estimated sensor drift values by using the drift distribution based on the sensor calibration data. And then, the equipment failure is diagnosed by using the process signals after removal of the sensor drifts. To verify the developed diagnostic system, several sets of simulation data based on abnormal cases

  19. Testing of high-impedance fault relays

    Energy Technology Data Exchange (ETDEWEB)

    Nagpal, M. [Powertech Labs., Inc., Surrey, BC (Canada)

    1995-11-01

    A test system and protocol was developed for the testing of high-impedance fault (HIF) detection devices. A technique was established for point-by-point addition of fault and load currents, the resultant was used for testing the performance of the devices in detecting HIFs in the presence of load current. The system used digitized data from recorded faults and normal currents to generate analog test signals for high-impedance fault detection relays. A test apparatus was built with a 10 kHz band-width and playback duration of 30 minutes on 6 output channels for testing purposes. Three devices which have recently become available were tested and their performance was evaluated based on their respective test results.

  20. A Review of Frequency Response Analysis Methods for Power Transformer Diagnostics

    Directory of Open Access Journals (Sweden)

    Saleh Alsuhaibani

    2016-10-01

    Full Text Available Power transformers play a critical role in electric power networks. Such transformers can suffer failures due to multiple stresses and aging. Thus, assessment of condition and diagnostic techniques are of great importance for improving power network reliability and service continuity. Several techniques are available to diagnose the faults within the power transformer. Frequency response analysis (FRA method is a powerful technique for diagnosing transformer winding deformation and several other types of problems that are caused during manufacture, transportation, installation and/or service life. This paper provides a comprehensive review on FRA methods and their applications in diagnostics and fault identification for power transformers. The paper discusses theory and applications of FRA methods as well as various issues and challenges faced in the application of this method.

  1. A fault detection and diagnosis in a PWR steam generator

    International Nuclear Information System (INIS)

    Park, Seung Yub

    1991-01-01

    The purpose of this study is to develop a fault detection and diagnosis scheme that can monitor process fault and instrument fault of a steam generator. The suggested scheme consists of a Kalman filter and two bias estimators. Method of detecting process and instrument fault in a steam generator uses the mean test on the residual sequence of Kalman filter, designed for the unfailed system, to make a fault decision. Once a fault is detected, two bias estimators are driven to estimate the fault and to discriminate process fault and instrument fault. In case of process fault, the fault diagnosis of outlet temperature, feed-water heater and main steam control valve is considered. In instrument fault, the fault diagnosis of steam generator's three instruments is considered. Computer simulation tests show that on-line prompt fault detection and diagnosis can be performed very successfully.(Author)

  2. On-line surveillance system for Borssele nuclear power plant monitoring and diagnostics

    International Nuclear Information System (INIS)

    Tuerkcan, E.; Ciftcioglu, Oe.

    1993-08-01

    An operating on-line surveillance and diagnostic system is described where information processing for monitoring and fault diagnosis and plant maintenance are addressed. The surveillance system by means of its realtime multiprocessing, multitasking execution capabilities can perform plant-wide and wide-range monitoring for enhanced plant safety and operational reliability as well as enhanced maintenance. At the same time the system provides the possibilities for goal-oriented research and development such as estimation, filtering, verification and validation and neural networks. (orig./HP)

  3. An enhancement to the NA4 gear vibration diagnostic parameter

    Science.gov (United States)

    Decker, Harry J.; Handschuh, Robert F.; Zakrajsek, James J.

    1994-01-01

    A new vibration diagnostic parameter for health monitoring of gears, NA4*, is proposed and tested. A recently developed gear vibration diagnostic parameter NA4 outperformed other fault detection methods at indicating the start and initial progression of damage. However, in some cases, as the damage progressed, the sensitivity of the NA4 and FM4 parameters tended to decrease and no longer indicated damage. A new parameter, NA4* was developed by enhancing NA4 to improve the trending of the parameter. This allows for the indication of damage both at initiation and also as the damage progresses. The NA4* parameter was verified and compared to the NA4 and FM4 parameters using experimental data from single mesh spur and spiral bevel gear fatigue rigs. The primary failure mode for the test cases was naturally occurring tooth surface pitting. The NA4* parameter is shown to be a more robust indicator of damage.

  4. A Self-Reconstructing Algorithm for Single and Multiple-Sensor Fault Isolation Based on Auto-Associative Neural Networks

    Directory of Open Access Journals (Sweden)

    Hamidreza Mousavi

    2017-01-01

    Full Text Available Recently different approaches have been developed in the field of sensor fault diagnostics based on Auto-Associative Neural Network (AANN. In this paper we present a novel algorithm called Self reconstructing Auto-Associative Neural Network (S-AANN which is able to detect and isolate single faulty sensor via reconstruction. We have also extended the algorithm to be applicable in multiple fault conditions. The algorithm uses a calibration model based on AANN. AANN can reconstruct the faulty sensor using non-faulty sensors due to correlation between the process variables, and mean of the difference between reconstructed and original data determines which sensors are faulty. The algorithms are tested on a Dimerization process. The simulation results show that the S-AANN can isolate multiple faulty sensors with low computational time that make the algorithm appropriate candidate for online applications.

  5. Diagnostic and Prognostic Models for Generator Step-Up Transformers

    Energy Technology Data Exchange (ETDEWEB)

    Vivek Agarwal; Nancy J. Lybeck; Binh T. Pham

    2014-09-01

    In 2014, the online monitoring (OLM) of active components project under the Light Water Reactor Sustainability program at Idaho National Laboratory (INL) focused on diagnostic and prognostic capabilities for generator step-up transformers. INL worked with subject matter experts from the Electric Power Research Institute (EPRI) to augment and revise the GSU fault signatures previously implemented in the Electric Power Research Institute’s (EPRI’s) Fleet-Wide Prognostic and Health Management (FW-PHM) Suite software. Two prognostic models were identified and implemented for GSUs in the FW-PHM Suite software. INL and EPRI demonstrated the use of prognostic capabilities for GSUs. The complete set of fault signatures developed for GSUs in the Asset Fault Signature Database of the FW-PHM Suite for GSUs is presented in this report. Two prognostic models are described for paper insulation: the Chendong model for degree of polymerization, and an IEEE model that uses a loading profile to calculates life consumption based on hot spot winding temperatures. Both models are life consumption models, which are examples of type II prognostic models. Use of the models in the FW-PHM Suite was successfully demonstrated at the 2014 August Utility Working Group Meeting, Idaho Falls, Idaho, to representatives from different utilities, EPRI, and the Halden Research Project.

  6. Development of beam diagnostic devices for characterizing electron guns

    International Nuclear Information System (INIS)

    Bhattacharjee, D.; Tiwari, R.; Jayaprakash, D.; Mishra, R.L.; Sarukte, H.; Waghmare, A.; Thakur, N.; Dixit, K.P.

    2015-01-01

    The electron guns for the DC accelerators and RF Linacs are designed and developed at EBC/APPD/BARC, Kharghar. These electron guns need to be characterized for its design and performance. Two test benches were developed for characterizing the electron guns. Various beam diagnostic devices for measuring beam currents and beam sizes were developed. Conical faraday cup, segmented faraday cup, slit scanning bellows movement arrangement, multi-plate beam size measurement setup, multi- wire beam size measurement setup, Aluminum foil puncture assembly etc. were developed and used. The paper presents the in-house development of various beam diagnostics for characterizing electron guns and their use. (author)

  7. Nuclear power plant status diagnostics using a neural network with dynamic node architecture

    International Nuclear Information System (INIS)

    Basu, A.

    1992-01-01

    This thesis is part of an ongoing project at Iowa State University to develop ANN based fault diagnostic systems to detect and classify operational transients at nuclear power plants. The project envisages the deployment of such an advisor at Iowa Electric Light and Power Company's Duane Arnold Energy Center nuclear power plant located at Palo, IA. This advisor is expected to make status diagnosis in real time, thus providing the operators with more time for corrective measures

  8. Aeromagnetic anomalies over faulted strata

    Science.gov (United States)

    Grauch, V.J.S.; Hudson, Mark R.

    2011-01-01

    High-resolution aeromagnetic surveys are now an industry standard and they commonly detect anomalies that are attributed to faults within sedimentary basins. However, detailed studies identifying geologic sources of magnetic anomalies in sedimentary environments are rare in the literature. Opportunities to study these sources have come from well-exposed sedimentary basins of the Rio Grande rift in New Mexico and Colorado. High-resolution aeromagnetic data from these areas reveal numerous, curvilinear, low-amplitude (2–15 nT at 100-m terrain clearance) anomalies that consistently correspond to intrasedimentary normal faults (Figure 1). Detailed geophysical and rock-property studies provide evidence for the magnetic sources at several exposures of these faults in the central Rio Grande rift (summarized in Grauch and Hudson, 2007, and Hudson et al., 2008). A key result is that the aeromagnetic anomalies arise from the juxtaposition of magnetically differing strata at the faults as opposed to chemical processes acting at the fault zone. The studies also provide (1) guidelines for understanding and estimating the geophysical parameters controlling aeromagnetic anomalies at faulted strata (Grauch and Hudson), and (2) observations on key geologic factors that are favorable for developing similar sedimentary sources of aeromagnetic anomalies elsewhere (Hudson et al.).

  9. Computer modelling of superconductive fault current limiters

    Energy Technology Data Exchange (ETDEWEB)

    Weller, R.A.; Campbell, A.M.; Coombs, T.A.; Cardwell, D.A.; Storey, R.J. [Cambridge Univ. (United Kingdom). Interdisciplinary Research Centre in Superconductivity (IRC); Hancox, J. [Rolls Royce, Applied Science Division, Derby (United Kingdom)

    1998-05-01

    Investigations are being carried out on the use of superconductors for fault current limiting applications. A number of computer programs are being developed to predict the behavior of different `resistive` fault current limiter designs under a variety of fault conditions. The programs achieve solution by iterative methods based around real measured data rather than theoretical models in order to achieve accuracy at high current densities. (orig.) 5 refs.

  10. Fault diagnosis and fault-tolerant control and guidance for aerospace vehicles from theory to application

    CERN Document Server

    Zolghadri, Ali; Cieslak, Jerome; Efimov, Denis; Goupil, Philippe

    2014-01-01

    Fault Diagnosis and Fault-Tolerant Control and Guidance for Aerospace demonstrates the attractive potential of recent developments in control for resolving such issues as improved flight performance, self-protection and extended life of structures. Importantly, the text deals with a number of practically significant considerations: tuning, complexity of design, real-time capability, evaluation of worst-case performance, robustness in harsh environments, and extensibility when development or adaptation is required. Coverage of such issues helps to draw the advanced concepts arising from academic research back towards the technological concerns of industry. Initial coverage of basic definitions and ideas and a literature review gives way to a treatment of important electrical flight control system failures: the oscillatory failure case, runaway, and jamming. Advanced fault detection and diagnosis for linear and nonlinear systems are described. Lastly recovery strategies appropriate to remaining acuator/sensor/c...

  11. A Framework-Based Approach for Fault-Tolerant Service Robots

    Directory of Open Access Journals (Sweden)

    Heejune Ahn

    2012-11-01

    Full Text Available Recently the component-based approach has become a major trend in intelligent service robot development due to its reusability and productivity. The framework in a component-based system should provide essential services for application components. However, to our knowledge the existing robot frameworks do not yet support fault tolerance service. Moreover, it is often believed that faults can be handled only at the application level. In this paper, by extending the robot framework with the fault tolerance function, we argue that the framework-based fault tolerance approach is feasible and even has many benefits, including that: 1 the system integrators can build fault tolerance applications from non-fault-aware components; 2 the constraints of the components and the operating environment can be considered at the time of integration, which – cannot be anticipated eaily at the time of component development; 3 consistency in system reliability can be obtained even in spite of diverse application component sources. In the proposed construction, we build XML rule files defining the rules for probing and determining the fault conditions of each component, contamination cases from a faulty component, and the possible recovery and safety methods. The rule files are established by a system integrator and the fault manager in the framework controls the fault tolerance process according to the rules. We demonstrate that the fault-tolerant framework can incorporate widely accepted fault tolerance techniques. The effectiveness and real-time performance of the framework-based approach and its techniques are examined by testing an autonomous mobile robot in typical fault scenarios.

  12. Fault-Tolerant Approach for Modular Multilevel Converters under Submodule Faults

    DEFF Research Database (Denmark)

    Deng, Fujin; Tian, Yanjun; Zhu, Rongwu

    2016-01-01

    The modular multilevel converter (MMC) is attractive for medium- or high-power applications because of the advantages of its high modularity, availability, and high power quality. The fault-tolerant operation is one of the important issues for the MMC. This paper proposed a fault-tolerant approach...... for the MMC under submodule (SM) faults. The characteristic of the MMC with arms containing different number of healthy SMs under faults is analyzed. Based on the characteristic, the proposed approach can effectively keep the MMC operation as normal under SM faults. It can effectively improve the MMC...

  13. Application of artificial neural network for NHR fault diagnosis

    International Nuclear Information System (INIS)

    Yu Haitao; Zhang Liangju; Xu Xiangdong

    1999-01-01

    The author makes researches on 200 MW nuclear heating reactor (NHR) fault diagnosis system using artificial neural network, and use the tendency value and real value of the data under the accidents to train and test two BP networks respectively. The final diagnostic result is the combination of the results of the two networks. The compound system can enhance the accuracy and adaptability of the diagnosis comparing to the single network system

  14. Postglacial faulting and paleoseismicity in the Landsjaerv area, northern Sweden

    International Nuclear Information System (INIS)

    Lagerbaeck, R.

    1988-10-01

    Post-glacial fault scarps, up to about 20 m in height and forming a 50 km long fault set with a SSW-NNE orientation, occur in the Lansjaerv area in northern Sweden. By trenching across the fault scarps it has been possible to date fault movement relative to the Quaternary stratigraphy. It is concluded that the fault scarps generally developed as single event movements shortly after the deglaciation about 9000 years ago. At one location there are indications that minor fault movements may have occurred earlier during a previous glaciation but this is uncertain. The fault scarps are, at least partially, developed in strongly fractured and chemically weathered zones of presumed pre-Quaternary age. To judge from the appearance of the bedrock fault scarps, and the deformation of the Quaternary deposits, the faults are reverse and have dips between some 40-50 0 and the vertical. The faulting was co-seismic and earthquakes in the order of M 6.5-7.0, or higher, are inferred from fault dimensions and the distribution of seismically triggered landslides in a wider region. Distortions in different types of sediment, interpreted as caused by the influence of seismic shock, occur frequently in the area. Examples of these are briefly described. (orig.)

  15. Development and Test of Methods for Fault Detection and Isolation

    DEFF Research Database (Denmark)

    Jørgensen, R.B.

    Almost all industrial systemns are automated to ensure optimal production both in relation to energy consumtion and safety to equipment and humans. All working parts are individually subject to faults. This can lead to unacceptable economic loss or injury to people. This thesis deals with a monit......Almost all industrial systemns are automated to ensure optimal production both in relation to energy consumtion and safety to equipment and humans. All working parts are individually subject to faults. This can lead to unacceptable economic loss or injury to people. This thesis deals...

  16. Managing systems faults on the commercial flight deck: Analysis of pilots' organization and prioritization of fault management information

    Science.gov (United States)

    Rogers, William H.

    1993-01-01

    In rare instances, flight crews of commercial aircraft must manage complex systems faults in addition to all their normal flight tasks. Pilot errors in fault management have been attributed, at least in part, to an incomplete or inaccurate awareness of the fault situation. The current study is part of a program aimed at assuring that the types of information potentially available from an intelligent fault management aiding concept developed at NASA Langley called 'Faultfinde' (see Abbott, Schutte, Palmer, and Ricks, 1987) are an asset rather than a liability: additional information should improve pilot performance and aircraft safety, but it should not confuse, distract, overload, mislead, or generally exacerbate already difficult circumstances.

  17. Physics R and D in support of ITER/BPX diagnostic development

    International Nuclear Information System (INIS)

    Donne, A.J.H.; Boivin, R.; Costley, A.E.

    2003-01-01

    The development of diagnostics for a next step burning plasma experiment (BPX) is a major challenge. Within the International Tokamak Physics Activity (ITPA), one Topical Group (TG) specialises in diagnostics and aims to support the development and design of the needed systems. Several diagnostics issues have been identified as 'high priority' and form the focus of current work of the TG. The core of this paper is a presentation and discussion of recent progress in the field of these high priority research topics. Moreover, the status of the recently initiated International Diagnostic Database will be briefly described. (author)

  18. Fault diagnosis for engine air path with neural models and classifier ...

    African Journals Online (AJOL)

    A new FDI scheme is developed for automotive engines in this paper. The method uses an independent radial basis function (RBF) neural ... Five faults have been simulated on the MVEM, including three sensor faults, one component fault and one actuator fault. The three sensor faults considered are 10-20% changes ...

  19. Fault-tolerant Control of a Cyber-physical System

    Science.gov (United States)

    Roxana, Rusu-Both; Eva-Henrietta, Dulf

    2017-10-01

    Cyber-physical systems represent a new emerging field in automatic control. The fault system is a key component, because modern, large scale processes must meet high standards of performance, reliability and safety. Fault propagation in large scale chemical processes can lead to loss of production, energy, raw materials and even environmental hazard. The present paper develops a multi-agent fault-tolerant control architecture using robust fractional order controllers for a (13C) cryogenic separation column cascade. The JADE (Java Agent DEvelopment Framework) platform was used to implement the multi-agent fault tolerant control system while the operational model of the process was implemented in Matlab/SIMULINK environment. MACSimJX (Multiagent Control Using Simulink with Jade Extension) toolbox was used to link the control system and the process model. In order to verify the performance and to prove the feasibility of the proposed control architecture several fault simulation scenarios were performed.

  20. Dynamical instability produces transform faults at mid-ocean ridges.

    Science.gov (United States)

    Gerya, Taras

    2010-08-27

    Transform faults at mid-ocean ridges--one of the most striking, yet enigmatic features of terrestrial plate tectonics--are considered to be the inherited product of preexisting fault structures. Ridge offsets along these faults therefore should remain constant with time. Here, numerical models suggest that transform faults are actively developing and result from dynamical instability of constructive plate boundaries, irrespective of previous structure. Boundary instability from asymmetric plate growth can spontaneously start in alternate directions along successive ridge sections; the resultant curved ridges become transform faults within a few million years. Fracture-related rheological weakening stabilizes ridge-parallel detachment faults. Offsets along the transform faults change continuously with time by asymmetric plate growth and discontinuously by ridge jumps.

  1. FAULT-TOLERANT DESIGN FOR ADVANCED DIVERSE PROTECTION SYSTEM

    Directory of Open Access Journals (Sweden)

    YANG GYUN OH

    2013-11-01

    Full Text Available For the improvement of APR1400 Diverse Protection System (DPS design, the Advanced DPS (ADPS has recently been developed to enhance the fault tolerance capability of the system. Major fault masking features of the ADPS compared with the APR1400 DPS are the changes to the channel configuration and reactor trip actuation equipment. To minimize the fault occurrences within the ADPS, and to mitigate the consequences of common-cause failures (CCF within the safety I&C systems, several fault avoidance design features have been applied in the ADPS. The fault avoidance design features include the changes to the system software classification, communication methods, equipment platform, MMI equipment, etc. In addition, the fault detection, location, containment, and recovery processes have been incorporated in the ADPS design. Therefore, it is expected that the ADPS can provide an enhanced fault tolerance capability against the possible faults within the system and its input/output equipment, and the CCF of safety systems.

  2. Ontology-Based Method for Fault Diagnosis of Loaders.

    Science.gov (United States)

    Xu, Feixiang; Liu, Xinhui; Chen, Wei; Zhou, Chen; Cao, Bingwei

    2018-02-28

    This paper proposes an ontology-based fault diagnosis method which overcomes the difficulty of understanding complex fault diagnosis knowledge of loaders and offers a universal approach for fault diagnosis of all loaders. This method contains the following components: (1) An ontology-based fault diagnosis model is proposed to achieve the integrating, sharing and reusing of fault diagnosis knowledge for loaders; (2) combined with ontology, CBR (case-based reasoning) is introduced to realize effective and accurate fault diagnoses following four steps (feature selection, case-retrieval, case-matching and case-updating); and (3) in order to cover the shortages of the CBR method due to the lack of concerned cases, ontology based RBR (rule-based reasoning) is put forward through building SWRL (Semantic Web Rule Language) rules. An application program is also developed to implement the above methods to assist in finding the fault causes, fault locations and maintenance measures of loaders. In addition, the program is validated through analyzing a case study.

  3. Microstructural investigations on carbonate fault core rocks in active extensional fault zones from the central Apennines (Italy)

    Science.gov (United States)

    Cortinovis, Silvia; Balsamo, Fabrizio; Storti, Fabrizio

    2017-04-01

    -rounded), and (2) very fine-grained gouges (< 1 mm) localized along major and minor mirror-like slip surfaces. Damage zones mostly consist of fractured rocks and, locally, pulverized rocks. Collectively, field observations and laboratory analyses indicate that within the fault cores of the studied fault zones, grain size progressively decreases approaching the master slip surfaces. Furthermore, grain shape changes from very angular to sub-rounded clasts moving toward the master slip surfaces. These features suggest that the progressive evolution of grain size and shape distributions within fault cores may have determined the development of strain localization by the softening and cushioning effects of smaller particles in loose fault rocks.

  4. A new methodology for the computer-aided construction of fault trees

    International Nuclear Information System (INIS)

    Salem, S.L.; Apostolakis, G.E.; Okrent, D.

    1977-01-01

    A methodology for systematically constructing fault trees for general complex systems is developed. A means of modeling component behaviour via decision tables is presented, and a procedure, and a procedure for constructing and editing fault trees, either manually or by computer, is developed. The techniques employed result in a complete fault tree in standard form. In order to demonstrate the methodology, the computer program CAT was developed and is used to construct trees for a nuclear system. By analyzing and comparing these fault trees, several conclusions are reached. First, such an approach can be used to produce fault trees that accurately describe system behaviour. Second, multiple trees can be rapidly produced by defining various TOP events, including system success. Finally, the accuracy and utility of such trees is shown to depend upon the careful development of the decision table models by the analyst, and of the overall system definition itself. Thus the method is seen to be a tool for assisting in the work of fault tree construction rather than a replacement for the careful work of the fault tree analyst. (author)

  5. Development of the Alberta Diagnostic Reading Program.

    Science.gov (United States)

    Horvath, Frank G.; Machura, Shirley

    The development of the Alberta Diagnostic Reading Program (ADRP) was based on a current psycholinguistic theory that describes reading as a process in which the reader uses background information to communicate with the author. To ensure its usefulness and effectiveness, the developers of the ADRP sought the advice and direct involvement of many…

  6. The graphics-based human interface to the DISYS diagnostic/control guidance system at EBR-2

    International Nuclear Information System (INIS)

    Edwards, R.M.; Chavez, C.; Kamarthi, S.; Dharap, S.; Lindsay, R.W.; Staffon, J.

    1990-01-01

    An initial graphics based interface to the real-time DISYS diagnostic system has been developed using the multi-tasking capabilities of the UNIX operating system and X-Windows 11 Xlib graphics library. This system is interfaced to live plant data at the Experimental Breeder Reactor (EBR-2) for the Argon Cooling System of fuel handling operations and the steam plant. The interface includes an intelligent process schematic which highlights problematic components and sensors based on the results of the diagnostic computations. If further explanation of a faulted component is required, the user can call up a display of the diagnostic computations presented in a tree-like diagram. Numerical data on the process schematic and optional diagnostic tree are updated as new real-time data becomes available. The initial X-Windows 11 based interface will be further enhanced using VI Corporation DATAVIEWS graphical data base software. 5 refs., 6 figs

  7. A Quantitative Assessment of Factors Affecting the Technological Development and Adoption of Companion Diagnostics

    Directory of Open Access Journals (Sweden)

    Dee eLuo

    2016-01-01

    Full Text Available Rapid innovation in (epigenetics and biomarker sciences is driving a new drug development and product development pathway, with the personalized medicine era dominated by biologic therapeutics and companion diagnostics. Companion diagnostics (CDx are tests and assays that detect biomarkers and specific mutations to elucidate disease pathways, stratify patient populations, and target drug therapies. CDx can substantially influence the development and regulatory approval for certain high-risk biologics. However, despite the increasingly important role of companion diagnostics in the realization of personalized medicine, in the United States, there are only twenty-three Food and Drug Administration (FDA approved companion diagnostics on the market for eleven unique indications. Personalized medicines have great potential, yet their use is currently constrained. A major factor for this may lie in the increased complexity of the companion diagnostic and corresponding therapeutic development and adoption pathways. Understanding the market dynamics of companion diagnostic/therapeutic (CDx/Rx pairs is important to further development and adoption of personalized medicine. Therefore, data collected on a variety of factors may highlight incentives or disincentives driving the development of companion diagnostics. Statistical analysis for thirty-six hypotheses resulted in two significant relationships and thirty-four non-significant relationships. The sensitivity of the companion diagnostic was the only factor that significantly correlated with the price of the companion diagnostic. This result indicates that while there is regulatory pressure for the diagnostic and pharmaceutical industry to collaborate and co-develop companion diagnostics for the approval of personalized therapeutics, there seems to be a lack of parallel economic collaboration to incentivize development of companion diagnostics.

  8. A Quantitative Assessment of Factors Affecting the Technological Development and Adoption of Companion Diagnostics.

    Science.gov (United States)

    Luo, Dee; Smith, James A; Meadows, Nick A; Schuh, A; Manescu, Katie E; Bure, Kim; Davies, Benjamin; Horne, Rob; Kope, Mike; DiGiusto, David L; Brindley, David A

    2015-01-01

    Rapid innovation in (epi)genetics and biomarker sciences is driving a new drug development and product development pathway, with the personalized medicine era dominated by biologic therapeutics and companion diagnostics. Companion diagnostics (CDx) are tests and assays that detect biomarkers and specific mutations to elucidate disease pathways, stratify patient populations, and target drug therapies. CDx can substantially influence the development and regulatory approval for certain high-risk biologics. However, despite the increasingly important role of companion diagnostics in the realization of personalized medicine, in the USA, there are only 23 Food and Drug Administration (FDA) approved companion diagnostics on the market for 11 unique indications. Personalized medicines have great potential, yet their use is currently constrained. A major factor for this may lie in the increased complexity of the companion diagnostic and corresponding therapeutic development and adoption pathways. Understanding the market dynamics of companion diagnostic/therapeutic (CDx/Rx) pairs is important to further development and adoption of personalized medicine. Therefore, data collected on a variety of factors may highlight incentives or disincentives driving the development of companion diagnostics. Statistical analysis for 36 hypotheses resulted in two significant relationships and 34 non-significant relationships. The sensitivity of the companion diagnostic was the only factor that significantly correlated with the price of the companion diagnostic. This result indicates that while there is regulatory pressure for the diagnostic and pharmaceutical industry to collaborate and co-develop companion diagnostics for the approval of personalized therapeutics, there seems to be a lack of parallel economic collaboration to incentivize development of companion diagnostics.

  9. Stationary Wavelet Singular Entropy and Kernel Extreme Learning for Bearing Multi-Fault Diagnosis

    Directory of Open Access Journals (Sweden)

    Nibaldo Rodriguez

    2017-10-01

    Full Text Available The behavioural diagnostics of bearings play an essential role in the management of several rotation machine systems. However, current diagnostic methods do not deliver satisfactory results with respect to failures in variable speed rotational phenomena. In this paper, we consider the Shannon entropy as an important fault signature pattern. To compute the entropy, we propose combining stationary wavelet transform and singular value decomposition. The resulting feature extraction method, that we call stationary wavelet singular entropy (SWSE, aims to improve the accuracy of the diagnostics of bearing failure by finding a small number of high-quality fault signature patterns. The features extracted by the SWSE are then passed on to a kernel extreme learning machine (KELM classifier. The proposed SWSE-KELM algorithm is evaluated using two bearing vibration signal databases obtained from Case Western Reserve University. We compare our SWSE feature extraction method to other well-known methods in the literature such as stationary wavelet packet singular entropy (SWPSE and decimated wavelet packet singular entropy (DWPSE. The experimental results show that the SWSE-KELM consistently outperforms both the SWPSE-KELM and DWPSE-KELM methods. Further, our SWSE method requires fewer features than the other two evaluated methods, which makes our SWSE-KELM algorithm simpler and faster.

  10. Development of the Model of the System of Managerial Diagnostics of the Enterprise on the Basis of Improvement of Diagnostic Purposes

    Directory of Open Access Journals (Sweden)

    Grzegorz Pawlowski

    2017-11-01

    Full Text Available The purpose of the article is to develop a model of the system of managerial diagnostics of the enterprise on the basis of the improvement of diagnostic purposes. The developed model of the system of managerial diagnostics of the enterprise is a set of subjects (owners, managers, investors, specialists, etc., objects (management system, resources, technology, methods (a set of methods and means, business indicators and criteria (parameters that, when interacting, provide the achievement (efficient and effective of the diagnostic objectives of the system of the objectives of managerial diagnostics of the enterprise, taking into account the compliance of its competitive strategy of the state of the environment function of direct action (competitors, customers, suppliers, mediators, and other contact audiences in the context of improving the efficiency and developing the management. It is determined that the system of goals of the model of the system of managerial diagnostics of the enterprise (taking into account the ensuring of the compliance of the system of management with strategic goals and tactical tasks form the following key diagnostic objectives that require improvement on the basis of business indicators (parameters, namely: 1 diagnostics of the effectiveness of controlling the internal business processes of the enterprise; 2 diagnostics of the effectiveness of the typical organizational structure of enterprise management; 3 diagnostics of the efficiency of standardization of the work of linear and functional managers and specialists at the enterprise; 4 diagnostics of the enterprise in the areas of vocational education, labor activity and motivation, innovation work and social development; 5 diagnostics of the level of conflict in the team at the enterprise; 6 diagnostics of efficiency of use of information technologies in the management of the enterprise. The prospect of further research in this area is to improve the complex system of

  11. Quaternary faulting in the Tatra Mountains, evidence from cave morphology and fault-slip analysis

    OpenAIRE

    Szczygieł Jacek

    2015-01-01

    Tectonically deformed cave passages in the Tatra Mts (Central Western Carpathians) indicate some fault activity during the Quaternary. Displacements occur in the youngest passages of the caves indicating (based on previous U-series dating of speleothems) an Eemian or younger age for those faults, and so one tectonic stage. On the basis of stress analysis and geomorphological observations, two different mechanisms are proposed as responsible for the development of these displacements. The firs...

  12. Bringing diagnostics to developing countries: an interview with Rosanna Peeling.

    Science.gov (United States)

    Peeling, Rosanna

    2015-01-01

    Interview with Professor Rosanna Peeling, PhD by Claire Raison (Commissioning Editor) Professor Rosanna Peeling is Chair of Diagnostic Research at the London School of Hygiene and Tropical Medicine (London, UK) and founded the International Diagnostics Centre at the institution. Professor Peeling previously worked for the WHO in Geneva, Switzerland, and continues to work on innovations for molecular diagnostics for point-of-care use in developing countries, addressing challenges posed by lack of funding and resources, regulatory issues and under-developed healthcare systems in these locations. Here, she discusses her career, recent progress in the field and how connectivity will affect global healthcare.

  13. Fault displacement along the Naruto-South fault, the Median Tectonic Line active fault system in the eastern part of Shikoku, southwestern Japan

    OpenAIRE

    高田, 圭太; 中田, 高; 後藤, 秀昭; 岡田, 篤正; 原口, 強; 松木, 宏彰

    1998-01-01

    The Naruto-South fault is situated of about 1000m south of the Naruto fault, the Median Tectonic Line active fault system in the eastern part of Shikoku. We investigated fault topography and subsurface geology of this fault by interpretation of large scale aerial photographs, collecting borehole data and Geo-Slicer survey. The results obtained are as follows; 1) The Naruto-South fault runs on the Yoshino River deltaic plain at least 2.5 km long with fault scarplet. the Naruto-South fault is o...

  14. Laboratory scale micro-seismic monitoring of rock faulting and injection-induced fault reactivation

    Science.gov (United States)

    Sarout, J.; Dautriat, J.; Esteban, L.; Lumley, D. E.; King, A.

    2017-12-01

    The South West Hub CCS project in Western Australia aims to evaluate the feasibility and impact of geosequestration of CO2 in the Lesueur sandstone formation. Part of this evaluation focuses on the feasibility and design of a robust passive seismic monitoring array. Micro-seismicity monitoring can be used to image the injected CO2plume, or any geomechanical fracture/fault activity; and thus serve as an early warning system by measuring low-level (unfelt) seismicity that may precede potentially larger (felt) earthquakes. This paper describes laboratory deformation experiments replicating typical field scenarios of fluid injection in faulted reservoirs. Two pairs of cylindrical core specimens were recovered from the Harvey-1 well at depths of 1924 m and 2508 m. In each specimen a fault is first generated at the in situ stress, pore pressure and temperature by increasing the vertical stress beyond the peak in a triaxial stress vessel at CSIRO's Geomechanics & Geophysics Lab. The faulted specimen is then stabilized by decreasing the vertical stress. The freshly formed fault is subsequently reactivated by brine injection and increase of the pore pressure until slip occurs again. This second slip event is then controlled in displacement and allowed to develop for a few millimeters. The micro-seismic (MS) response of the rock during the initial fracturing and subsequent reactivation is monitored using an array of 16 ultrasonic sensors attached to the specimen's surface. The recorded MS events are relocated in space and time, and correlate well with the 3D X-ray CT images of the specimen obtained post-mortem. The time evolution of the structural changes induced within the triaxial stress vessel is therefore reliably inferred. The recorded MS activity shows that, as expected, the increase of the vertical stress beyond the peak led to an inclined shear fault. The injection of fluid and the resulting increase in pore pressure led first to a reactivation of the pre

  15. DIVA and DIAPO: two diagnostic knowledge based systems used for French nuclear power plants

    International Nuclear Information System (INIS)

    Porcheron, M.; Ricard, B.; Joussellin, A.

    1997-01-01

    In order to improve monitoring and diagnosis capabilities in nuclear power plants, Electricite de France (EDF) has designed an integrated monitoring and diagnosis assistance system: PSAD-Poste de Surveillance et d'Aide au Diagnostic. The development of such a sophisticated monitoring and data processing systems has emphasized the need for the addition of analysis and diagnosis assistance capabilities. Therefore, diagnostic knowledge based systems have been added to the functions monitored in PSAD: DIVA for turbine generators, and DIAPO for reactor coolant pumps. These systems were designed from a representation of the diagnostic reasoning process of experts and of the supporting knowledge. Diagnosis in both systems relies on an abduction reasoning process applied to component fault models and observations derived from their actual behavior, as provided by the monitoring functions. The basic theoretical elements of this diagnostic model are summarized in a first part. In a second part, DIVA and DIAPO specific elements are described

  16. Robust Fault Diagnosis Design for Linear Multiagent Systems with Incipient Faults

    Directory of Open Access Journals (Sweden)

    Jingping Xia

    2015-01-01

    Full Text Available The design of a robust fault estimation observer is studied for linear multiagent systems subject to incipient faults. By considering the fact that incipient faults are in low-frequency domain, the fault estimation of such faults is proposed for discrete-time multiagent systems based on finite-frequency technique. Moreover, using the decomposition design, an equivalent conclusion is given. Simulation results of a numerical example are presented to demonstrate the effectiveness of the proposed techniques.

  17. Self-triggering superconducting fault current limiter

    Science.gov (United States)

    Yuan, Xing [Albany, NY; Tekletsadik, Kasegn [Rexford, NY

    2008-10-21

    A modular and scaleable Matrix Fault Current Limiter (MFCL) that functions as a "variable impedance" device in an electric power network, using components made of superconducting and non-superconducting electrically conductive materials. The matrix fault current limiter comprises a fault current limiter module that includes a superconductor which is electrically coupled in parallel with a trigger coil, wherein the trigger coil is magnetically coupled to the superconductor. The current surge doing a fault within the electrical power network will cause the superconductor to transition to its resistive state and also generate a uniform magnetic field in the trigger coil and simultaneously limit the voltage developed across the superconductor. This results in fast and uniform quenching of the superconductors, significantly reduces the burnout risk associated with non-uniformity often existing within the volume of superconductor materials. The fault current limiter modules may be electrically coupled together to form various "n" (rows).times."m" (columns) matrix configurations.

  18. Survey of artificial intelligence methods for detection and identification of component faults in nuclear power plants

    International Nuclear Information System (INIS)

    Reifman, J.

    1997-01-01

    A comprehensive survey of computer-based systems that apply artificial intelligence methods to detect and identify component faults in nuclear power plants is presented. Classification criteria are established that categorize artificial intelligence diagnostic systems according to the types of computing approaches used (e.g., computing tools, computer languages, and shell and simulation programs), the types of methodologies employed (e.g., types of knowledge, reasoning and inference mechanisms, and diagnostic approach), and the scope of the system. The major issues of process diagnostics and computer-based diagnostic systems are identified and cross-correlated with the various categories used for classification. Ninety-five publications are reviewed

  19. Role of simulator training in developing teamwork and diagnostic skills

    International Nuclear Information System (INIS)

    Grimme, W.E.

    1987-01-01

    A review of the evolution of the control room team is necessary to understand team training needs. As control room responsibilities have increased and members have been added to the operating crews, teamwork and strong leadership has become crucial to the efficiency of these operating crews. In order to conduct effective team training in a simulated control room, it is essential that the fundamental principles of role definition and common team values are fully developed. The diagnostics model used to develop problem-solving skills must be adaptable to the dynamic environment of the control room. Once the fundamental principles of team building and a good diagnostics model are mastered, many training techniques using a simulator are available to perfect the development of team building and diagnostic skills

  20. Stafford fault system: 120 million year fault movement history of northern Virginia

    Science.gov (United States)

    Powars, David S.; Catchings, Rufus D.; Horton, J. Wright; Schindler, J. Stephen; Pavich, Milan J.

    2015-01-01

    The Stafford fault system, located in the mid-Atlantic coastal plain of the eastern United States, provides the most complete record of fault movement during the past ~120 m.y. across the Virginia, Washington, District of Columbia (D.C.), and Maryland region, including displacement of Pleistocene terrace gravels. The Stafford fault system is close to and aligned with the Piedmont Spotsylvania and Long Branch fault zones. The dominant southwest-northeast trend of strong shaking from the 23 August 2011, moment magnitude Mw 5.8 Mineral, Virginia, earthquake is consistent with the connectivity of these faults, as seismic energy appears to have traveled along the documented and proposed extensions of the Stafford fault system into the Washington, D.C., area. Some other faults documented in the nearby coastal plain are clearly rooted in crystalline basement faults, especially along terrane boundaries. These coastal plain faults are commonly assumed to have undergone relatively uniform movement through time, with average slip rates from 0.3 to 1.5 m/m.y. However, there were higher rates during the Paleocene–early Eocene and the Pliocene (4.4–27.4 m/m.y), suggesting that slip occurred primarily during large earthquakes. Further investigation of the Stafford fault system is needed to understand potential earthquake hazards for the Virginia, Maryland, and Washington, D.C., area. The combined Stafford fault system and aligned Piedmont faults are ~180 km long, so if the combined fault system ruptured in a single event, it would result in a significantly larger magnitude earthquake than the Mineral earthquake. Many structures most strongly affected during the Mineral earthquake are along or near the Stafford fault system and its proposed northeastward extension.

  1. Optimal fault signal estimation

    NARCIS (Netherlands)

    Stoorvogel, Antonie Arij; Niemann, H.H.; Saberi, A.; Sannuti, P.

    2002-01-01

    We consider here both fault identification and fault signal estimation. Regarding fault identification, we seek either exact or almost fault identification. On the other hand, regarding fault signal estimation, we seek either $H_2$ optimal, $H_2$ suboptimal or Hinfinity suboptimal estimation. By

  2. Non-Mutually Exclusive Deep Neural Network Classifier for Combined Modes of Bearing Fault Diagnosis

    Directory of Open Access Journals (Sweden)

    Bach Phi Duong

    2018-04-01

    Full Text Available The simultaneous occurrence of various types of defects in bearings makes their diagnosis more challenging owing to the resultant complexity of the constituent parts of the acoustic emission (AE signals. To address this issue, a new approach is proposed in this paper for the detection of multiple combined faults in bearings. The proposed methodology uses a deep neural network (DNN architecture to effectively diagnose the combined defects. The DNN structure is based on the stacked denoising autoencoder non-mutually exclusive classifier (NMEC method for combined modes. The NMEC-DNN is trained using data for a single fault and it classifies both single faults and multiple combined faults. The results of experiments conducted on AE data collected through an experimental test-bed demonstrate that the DNN achieves good classification performance with a maximum accuracy of 95%. The proposed method is compared with a multi-class classifier based on support vector machines (SVMs. The NMEC-DNN yields better diagnostic performance in comparison to the multi-class classifier based on SVM. The NMEC-DNN reduces the number of necessary data collections and improves the bearing fault diagnosis performance.

  3. Non-Mutually Exclusive Deep Neural Network Classifier for Combined Modes of Bearing Fault Diagnosis.

    Science.gov (United States)

    Duong, Bach Phi; Kim, Jong-Myon

    2018-04-07

    The simultaneous occurrence of various types of defects in bearings makes their diagnosis more challenging owing to the resultant complexity of the constituent parts of the acoustic emission (AE) signals. To address this issue, a new approach is proposed in this paper for the detection of multiple combined faults in bearings. The proposed methodology uses a deep neural network (DNN) architecture to effectively diagnose the combined defects. The DNN structure is based on the stacked denoising autoencoder non-mutually exclusive classifier (NMEC) method for combined modes. The NMEC-DNN is trained using data for a single fault and it classifies both single faults and multiple combined faults. The results of experiments conducted on AE data collected through an experimental test-bed demonstrate that the DNN achieves good classification performance with a maximum accuracy of 95%. The proposed method is compared with a multi-class classifier based on support vector machines (SVMs). The NMEC-DNN yields better diagnostic performance in comparison to the multi-class classifier based on SVM. The NMEC-DNN reduces the number of necessary data collections and improves the bearing fault diagnosis performance.

  4. Non-Mutually Exclusive Deep Neural Network Classifier for Combined Modes of Bearing Fault Diagnosis

    Science.gov (United States)

    Kim, Jong-Myon

    2018-01-01

    The simultaneous occurrence of various types of defects in bearings makes their diagnosis more challenging owing to the resultant complexity of the constituent parts of the acoustic emission (AE) signals. To address this issue, a new approach is proposed in this paper for the detection of multiple combined faults in bearings. The proposed methodology uses a deep neural network (DNN) architecture to effectively diagnose the combined defects. The DNN structure is based on the stacked denoising autoencoder non-mutually exclusive classifier (NMEC) method for combined modes. The NMEC-DNN is trained using data for a single fault and it classifies both single faults and multiple combined faults. The results of experiments conducted on AE data collected through an experimental test-bed demonstrate that the DNN achieves good classification performance with a maximum accuracy of 95%. The proposed method is compared with a multi-class classifier based on support vector machines (SVMs). The NMEC-DNN yields better diagnostic performance in comparison to the multi-class classifier based on SVM. The NMEC-DNN reduces the number of necessary data collections and improves the bearing fault diagnosis performance. PMID:29642466

  5. Physical and Transport Property Variations Within Carbonate-Bearing Fault Zones: Insights From the Monte Maggio Fault (Central Italy)

    Science.gov (United States)

    Trippetta, F.; Carpenter, B. M.; Mollo, S.; Scuderi, M. M.; Scarlato, P.; Collettini, C.

    2017-11-01

    The physical characterization of carbonate-bearing normal faults is fundamental for resource development and seismic hazard. Here we report laboratory measurements of density, porosity, Vp, Vs, elastic moduli, and permeability for a range of effective confining pressures (0.1-100 MPa), conducted on samples representing different structural domains of a carbonate-bearing fault. We find a reduction in porosity from the fault breccia (11.7% total and 6.2% connected) to the main fault plane (9% total and 3.5% connected), with both domains showing higher porosity compared to the protolith (6.8% total and 1.1% connected). With increasing confining pressure, P wave velocity evolves from 4.5 to 5.9 km/s in the fault breccia, is constant at 5.9 km/s approaching the fault plane and is low (4.9 km/s) in clay-rich fault domains. We find that while the fault breccia shows pressure sensitive behavior (a reduction in permeability from 2 × 10-16 to 2 × 10-17 m2), the cemented cataclasite close to the fault plane is characterized by pressure-independent behavior (permeability 4 × 10-17 m2). Our results indicate that the deformation processes occurring within the different fault structural domains influence the physical and transport properties of the fault zone. In situ Vp profiles match well the laboratory measurements demonstrating that laboratory data are valuable for implications at larger scale. Combining the experimental values of elastic moduli and frictional properties it results that at shallow crustal levels, M ≤ 1 earthquakes are less favored, in agreement with earthquake-depth distribution during the L'Aquila 2009 seismic sequence that occurred on carbonates.

  6. Software error masking effect on hardware faults

    International Nuclear Information System (INIS)

    Choi, Jong Gyun; Seong, Poong Hyun

    1999-01-01

    Based on the Very High Speed Integrated Circuit (VHSIC) Hardware Description Language (VHDL), in this work, a simulation model for fault injection is developed to estimate the dependability of the digital system in operational phase. We investigated the software masking effect on hardware faults through the single bit-flip and stuck-at-x fault injection into the internal registers of the processor and memory cells. The fault location reaches all registers and memory cells. Fault distribution over locations is randomly chosen based on a uniform probability distribution. Using this model, we have predicted the reliability and masking effect of an application software in a digital system-Interposing Logic System (ILS) in a nuclear power plant. We have considered four the software operational profiles. From the results it was found that the software masking effect on hardware faults should be properly considered for predicting the system dependability accurately in operation phase. It is because the masking effect was formed to have different values according to the operational profile

  7. Real-time fault diagnosis and fault-tolerant control

    OpenAIRE

    Gao, Zhiwei; Ding, Steven X.; Cecati, Carlo

    2015-01-01

    This "Special Section on Real-Time Fault Diagnosis and Fault-Tolerant Control" of the IEEE Transactions on Industrial Electronics is motivated to provide a forum for academic and industrial communities to report recent theoretic/application results in real-time monitoring, diagnosis, and fault-tolerant design, and exchange the ideas about the emerging research direction in this field. Twenty-three papers were eventually selected through a strict peer-reviewed procedure, which represent the mo...

  8. Fault Diagnosis in Condition of Sample Type Incompleteness Using Support Vector Data Description

    Directory of Open Access Journals (Sweden)

    Hui Yi

    2015-01-01

    Full Text Available Faulty samples are much harder to acquire than normal samples, especially in complicated systems. This leads to incompleteness for training sample types and furthermore a decrease of diagnostic accuracy. In this paper, the relationship between sample-type incompleteness and the classifier-based diagnostic accuracy is discussed first. Then, a support vector data description-based approach, which has taken the effects of sample-type incompleteness into consideration, is proposed to refine the construction of fault regions and increase the diagnostic accuracy for the condition of incomplete sample types. The effectiveness of the proposed method was validated on both a Gaussian distributed dataset and a practical dataset. Satisfactory results have been obtained.

  9. Design of a fault diagnosis system for next generation nuclear power plants

    International Nuclear Information System (INIS)

    Zhao, K.; Upadhyaya, B.R.; Wood, R.T.

    2004-01-01

    A new design approach for fault diagnosis is developed for next generation nuclear power plants. In the nuclear reactor design phase, data reconciliation is used as an efficient tool to determine the measurement requirements to achieve the specified goal of fault diagnosis. In the reactor operation phase, the plant measurements are collected to estimate uncertain model parameters so that a high fidelity model can be obtained for fault diagnosis. The proposed algorithm of fault detection and isolation is able to combine the strength of first principle model based fault diagnosis and the historical data based fault diagnosis. Principal component analysis on the reconciled data is used to develop a statistical model for fault detection. The updating of the principal component model based on the most recent reconciled data is a locally linearized model around the current plant measurements, so that it is applicable to any generic nonlinear systems. The sensor fault diagnosis and process fault diagnosis are decoupled through considering the process fault diagnosis as a parameter estimation problem. The developed approach has been applied to the IRIS helical coil steam generator system to monitor the operational performance of individual steam generators. This approach is general enough to design fault diagnosis systems for the next generation nuclear power plants. (authors)

  10. A Study on a Hybrid Approach for Diagnosing Faults in Nuclear Power Plant

    International Nuclear Information System (INIS)

    Yang, M.; Zhang, Z.J.; Peng, M.J.; Yan, S.Y.; Wang, H.; Ouyang, J.

    2006-01-01

    Proper and rapid identification of malfunctions is of premier importance for the safe operation of Nuclear Power Plants (NPP). Many monitoring or/and diagnosis methodologies based on artificial and computational intelligence have been proposed to aid operator to understand system problems, perform trouble-shooting action and reduce human error under serious pressure. However, because no single method is adequate to handle all requirements for diagnostic system, hybrid approaches where different methods work in conjunction to solve parts of the problem interest researchers greatly. In this study, Multilevel Flow Models (MFM) and Artificial Neural Network (ANN) are proposed and employed to develop a fault diagnosis system with the intention of improving the success rate of recognition on the one hand, and improving the understandability of diagnostic process and results on the other hand. Several simulation cases were conducted for evaluating the performance of the proposed diagnosis system. The simulation results validated the effectiveness of the proposed hybrid approach. (authors)

  11. Spectral negentropy based sidebands and demodulation analysis for planet bearing fault diagnosis

    Science.gov (United States)

    Feng, Zhipeng; Ma, Haoqun; Zuo, Ming J.

    2017-12-01

    Planet bearing vibration signals are highly complex due to intricate kinematics (involving both revolution and spinning) and strong multiple modulations (including not only the fault induced amplitude modulation and frequency modulation, but also additional amplitude modulations due to load zone passing, time-varying vibration transfer path, and time-varying angle between the gear pair mesh lines of action and fault impact force vector), leading to difficulty in fault feature extraction. Rolling element bearing fault diagnosis essentially relies on detection of fault induced repetitive impulses carried by resonance vibration, but they are usually contaminated by noise and therefor are hard to be detected. This further adds complexity to planet bearing diagnostics. Spectral negentropy is able to reveal the frequency distribution of repetitive transients, thus providing an approach to identify the optimal frequency band of a filter for separating repetitive impulses. In this paper, we find the informative frequency band (including the center frequency and bandwidth) of bearing fault induced repetitive impulses using the spectral negentropy based infogram. In Fourier spectrum, we identify planet bearing faults according to sideband characteristics around the center frequency. For demodulation analysis, we filter out the sensitive component based on the informative frequency band revealed by the infogram. In amplitude demodulated spectrum (squared envelope spectrum) of the sensitive component, we diagnose planet bearing faults by matching the present peaks with the theoretical fault characteristic frequencies. We further decompose the sensitive component into mono-component intrinsic mode functions (IMFs) to estimate their instantaneous frequencies, and select a sensitive IMF with an instantaneous frequency fluctuating around the center frequency for frequency demodulation analysis. In the frequency demodulated spectrum (Fourier spectrum of instantaneous frequency) of

  12. Fault kinematics and localised inversion within the Troms-Finnmark Fault Complex, SW Barents Sea

    Science.gov (United States)

    Zervas, I.; Omosanya, K. O.; Lippard, S. J.; Johansen, S. E.

    2018-04-01

    The areas bounding the Troms-Finnmark Fault Complex are affected by complex tectonic evolution. In this work, the history of fault growth, reactivation, and inversion of major faults in the Troms-Finnmark Fault Complex and the Ringvassøy Loppa Fault Complex is interpreted from three-dimensional seismic data, structural maps and fault displacement plots. Our results reveal eight normal faults bounding rotated fault blocks in the Troms-Finnmark Fault Complex. Both the throw-depth and displacement-distance plots show that the faults exhibit complex configurations of lateral and vertical segmentation with varied profiles. Some of the faults were reactivated by dip-linkages during the Late Jurassic and exhibit polycyclic fault growth, including radial, syn-sedimentary, and hybrid propagation. Localised positive inversion is the main mechanism of fault reactivation occurring at the Troms-Finnmark Fault Complex. The observed structural styles include folds associated with extensional faults, folded growth wedges and inverted depocentres. Localised inversion was intermittent with rifting during the Middle Jurassic-Early Cretaceous at the boundaries of the Troms-Finnmark Fault Complex to the Finnmark Platform. Additionally, tectonic inversion was more intense at the boundaries of the two fault complexes, affecting Middle Triassic to Early Cretaceous strata. Our study shows that localised folding is either a product of compressional forces or of lateral movements in the Troms-Finnmark Fault Complex. Regional stresses due to the uplift in the Loppa High and halokinesis in the Tromsø Basin are likely additional causes of inversion in the Troms-Finnmark Fault Complex.

  13. NASA Spacecraft Fault Management Workshop Results

    Science.gov (United States)

    Newhouse, Marilyn; McDougal, John; Barley, Bryan; Fesq, Lorraine; Stephens, Karen

    2010-01-01

    Fault Management is a critical aspect of deep-space missions. For the purposes of this paper, fault management is defined as the ability of a system to detect, isolate, and mitigate events that impact, or have the potential to impact, nominal mission operations. The fault management capabilities are commonly distributed across flight and ground subsystems, impacting hardware, software, and mission operations designs. The National Aeronautics and Space Administration (NASA) Discovery & New Frontiers (D&NF) Program Office at Marshall Space Flight Center (MSFC) recently studied cost overruns and schedule delays for 5 missions. The goal was to identify the underlying causes for the overruns and delays, and to develop practical mitigations to assist the D&NF projects in identifying potential risks and controlling the associated impacts to proposed mission costs and schedules. The study found that 4 out of the 5 missions studied had significant overruns due to underestimating the complexity and support requirements for fault management. As a result of this and other recent experiences, the NASA Science Mission Directorate (SMD) Planetary Science Division (PSD) commissioned a workshop to bring together invited participants across government, industry, academia to assess the state of the art in fault management practice and research, identify current and potential issues, and make recommendations for addressing these issues. The workshop was held in New Orleans in April of 2008. The workshop concluded that fault management is not being limited by technology, but rather by a lack of emphasis and discipline in both the engineering and programmatic dimensions. Some of the areas cited in the findings include different, conflicting, and changing institutional goals and risk postures; unclear ownership of end-to-end fault management engineering; inadequate understanding of the impact of mission-level requirements on fault management complexity; and practices, processes, and

  14. Clay mineral formation and fabric development in the DFDP-1B borehole, central Alpine Fault, New Zealand

    International Nuclear Information System (INIS)

    Schleicher, A.M.; Sutherland, R.; Townend, J.; Toy, V.G.; Van der Pluijm, B.A.

    2015-01-01

    Clay minerals are increasingly recognised as important controls on the state and mechanical behaviour of fault systems in the upper crust. Samples retrieved by shallow drilling from two principal slip zones within the central Alpine Fault, South Island, New Zealand, offer an excellent opportunity to investigate clay formation and fluid-rock interaction in an active fault zone. Two shallow boreholes, DFDP-1A (100.6 m deep) and DFDP-1B (151.4 m) were drilled in Phase 1 of the Deep Fault Drilling Project (DFDP-1) in 2011. We provide a mineralogical and textural analysis of clays in fault gouge extracted from the Alpine Fault. Newly formed smectitic clays are observed solely in the narrow zones of fault gouge in drill core, indicating that localised mineral reactions are restricted to the fault zone. The weak preferred orientation of the clay minerals in the fault gouge indicates minimal strain-driven modification of rock fabrics. While limited in extent, our results support observations from surface outcrops and faults systems elsewhere regarding the key role of clays in fault zones and emphasise the need for future, deeper drilling into the Alpine Fault in order to understand correlative mineralogies and fabrics as a function of higher temperature and pressure conditions. (author).

  15. Fault Ride-through Capability Enhancement of Voltage Source Converter-High Voltage Direct Current Systems with Bridge Type Fault Current Limiters

    Directory of Open Access Journals (Sweden)

    Md Shafiul Alam

    2017-11-01

    Full Text Available This paper proposes the use of bridge type fault current limiters (BFCLs as a potential solution to reduce the impact of fault disturbance on voltage source converter-based high voltage DC (VSC-HVDC systems. Since VSC-HVDC systems are vulnerable to faults, it is essential to enhance the fault ride-through (FRT capability with auxiliary control devices like BFCLs. BFCL controllers have been developed to limit the fault current during the inception of system disturbances. Real and reactive power controllers for the VSC-HVDC have been developed based on current control mode. DC link voltage control has been achieved by a feedback mechanism such that net power exchange with DC link capacitor is zero. A grid-connected VSC-HVDC system and a wind farm integrated VSC-HVDC system along with the proposed BFCL and associated controllers have been implemented in a real time digital simulator (RTDS. Symmetrical three phase as well as different types of unsymmetrical faults have been applied in the systems in order to show the effectiveness of the proposed BFCL solution. DC link voltage fluctuation, machine speed and active power oscillation have been greatly suppressed with the proposed BFCL. Another significant feature of this work is that the performance of the proposed BFCL in VSC-HVDC systems is compared to that of series dynamic braking resistor (SDBR. Comparative results show that the proposed BFCL is superior over SDBR in limiting fault current as well as improving system fault ride through (FRT capability.

  16. Statistical fault diagnosis of wind turbine drivetrain applied to a 5MW floating wind turbine

    Science.gov (United States)

    Ghane, Mahdi; Nejad, Amir R.; Blanke, Mogens; Gao, Zhen; Moan, Torgeir

    2016-09-01

    Deployment of large scale wind turbine parks, in particular offshore, requires well organized operation and maintenance strategies to make it as competitive as the classical electric power stations. It is important to ensure systems are safe, profitable, and cost-effective. In this regards, the ability to detect, isolate, estimate, and prognose faults plays an important role. One of the critical wind turbine components is the gearbox. Failures in the gearbox are costly both due to the cost of the gearbox itself and also due to high repair downtime. In order to detect faults as fast as possible to prevent them to develop into failure, statistical change detection is used in this paper. The Cumulative Sum Method (CUSUM) is employed to detect possible defects in the downwind main bearing. A high fidelity gearbox model on a 5-MW spar-type wind turbine is used to generate data for fault-free and faulty conditions of the bearing at the rated wind speed and the associated wave condition. Acceleration measurements are utilized to find residuals used to indirectly detect damages in the bearing. Residuals are found to be nonGaussian, following a t-distribution with multivariable characteristic parameters. The results in this paper show how the diagnostic scheme can detect change with desired false alarm and detection probabilities.

  17. Comparison of γ-ray intensity distribution around Hira fault with spatial pattern of major and/or sub fault system

    International Nuclear Information System (INIS)

    Nakanishi, Tatsuya; Mino, Kazuo; Ogasawara, Hiroshi; Katsura, Ikuo

    1999-01-01

    Major active faults generally consist of systems of a number of fractures with various dimensions, and contain a lot of ground water. Rn gas, moving with underground water, tends to accumulate along faults and emit γ-ray while it decays down to Pb through Bi. Therefore, it has been shown by a number of works that γ-ray intensity is generally high near the core of the major active fault and the γ-ray survey is one of the effective methods to look for the core of the major active fault. However, around the area near the tips of faults, a number of complicated sub-fault systems and the corresponding complicated geological structures are often seen and it has not been investigated well about what can be the relationship between the intensity distribution of γ-ray and the fault systems. In order to investigate the relationship in an area near the tips of major faults well, therefore, we carried out the γ-ray survey at about 1,100 sites in an area of about 2 km x 2 km that has the tips of the two major right lateral faults with significant thrusting components. We also investigated the lineaments by using the topographic map published in 1895 when artificial construction was seldom seen in the area and we can easily see the natural topography. In addition, we carried out the γ-ray survey in an area far from the fault tip to compare with the results in the area with the fault tips. Then: (1) we reconfirmed that in the case of the middle of the major active fault, γ-ray intensity is high in the limited area just adjacent to the core of the fault. (2) However, we found that in the case of the tip of the major active fault, high γ-ray intensity is seen in much wider area with clear lineaments that is inferred to be developed associated with the movement of the major faults. (author)

  18. Vibration sensor data denoising using a time-frequency manifold for machinery fault diagnosis.

    Science.gov (United States)

    He, Qingbo; Wang, Xiangxiang; Zhou, Qiang

    2013-12-27

    Vibration sensor data from a mechanical system are often associated with important measurement information useful for machinery fault diagnosis. However, in practice the existence of background noise makes it difficult to identify the fault signature from the sensing data. This paper introduces the time-frequency manifold (TFM) concept into sensor data denoising and proposes a novel denoising method for reliable machinery fault diagnosis. The TFM signature reflects the intrinsic time-frequency structure of a non-stationary signal. The proposed method intends to realize data denoising by synthesizing the TFM using time-frequency synthesis and phase space reconstruction (PSR) synthesis. Due to the merits of the TFM in noise suppression and resolution enhancement, the denoised signal would have satisfactory denoising effects, as well as inherent time-frequency structure keeping. Moreover, this paper presents a clustering-based statistical parameter to evaluate the proposed method, and also presents a new diagnostic approach, called frequency probability time series (FPTS) spectral analysis, to show its effectiveness in fault diagnosis. The proposed TFM-based data denoising method has been employed to deal with a set of vibration sensor data from defective bearings, and the results verify that for machinery fault diagnosis the method is superior to two traditional denoising methods.

  19. Fault Tolerant Computer Architecture

    CERN Document Server

    Sorin, Daniel

    2009-01-01

    For many years, most computer architects have pursued one primary goal: performance. Architects have translated the ever-increasing abundance of ever-faster transistors provided by Moore's law into remarkable increases in performance. Recently, however, the bounty provided by Moore's law has been accompanied by several challenges that have arisen as devices have become smaller, including a decrease in dependability due to physical faults. In this book, we focus on the dependability challenge and the fault tolerance solutions that architects are developing to overcome it. The two main purposes

  20. Development of a Real-Time Thermal Performance Diagnostic Monitoring system Using Self-Organizing Neural Network for Kori-2 Nuclear Power Unit

    International Nuclear Information System (INIS)

    Kang, Hyun Gook; Seong, Poong Hyun

    1996-01-01

    In this work, a PC-based thermal performance monitoring system is developed for the nuclear power plants. the system performs real-time thermal performance monitoring and diagnosis during plant operation. Specifically, a prototype for the Kori-2 nuclear power unit is developed and examined is very difficult because the system structure is highly complex and the components are very much inter-related. In this study, some major diagnostic performance parameters are selected in order to represent the thermal cycle effectively and to reduce the computing time. The Fuzzy ARTMAP, a self-organizing neural network, is used to recognize the characteristic pattern change of the performance parameters in abnormal situation. By examination, the algorithm is shown to be ale to detect abnormality and to identify the fault component or the change of system operation condition successfully. For the convenience of operators, a graphical user interface is also constructed in this work. 5 figs., 3 tabs., 11 refs. (Author)

  1. An impact analysis of the fault impedance on voltage sags

    Energy Technology Data Exchange (ETDEWEB)

    Ramos, Alessandro Candido Lopes [CELG - Companhia Energetica de Goias, Goiania, GO (Brazil). Generation and Transmission. System' s Operation Center], E-mail: alessandro.clr@celg.com.br; Batista, Adalberto Jose [Federal University of Goias (UFG), Goiania, GO (Brazil)], E-mail: batista@eee.ufg.br; Leborgne, Roberto Chouhy [Federal University of Rio Grande do Sul (UFRGS), Porto Alegre, RS (Brazil)], E-mail: rcl@ece.ufrgs.br; Emiliano, Pedro Henrique Mota, E-mail: ph@phph.com.br

    2009-07-01

    This paper presents an impact analysis of the fault impedance, in terms of its module and angle, on voltage sags caused by faults. Symmetrical and asymmetrical faults are simulated, at transmission and distribution lines, by using a frequency-domain fault simulation software called ANAFAS. Voltage sags are monitored at buses where sensitive end-users are connected. In order to overcome some intrinsic limitations of this software concerning its automatic execution for several cases, a computational tool was developed in Java programming language. This solution allows the automatic simulation of cases including the effect of the fault position, the fault type, and the proper fault impedance. The main conclusion is that the module and angle of the fault impedance can have a significant influence on voltage sag depending on the fault characteristics. (author)

  2. Development of a Hydrologic Characterization Technology for Fault Zones Phase II 2nd Report

    Energy Technology Data Exchange (ETDEWEB)

    Karasaki, Kenzi [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Doughty, Christine [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Gasperikova, Erika [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Peterson, John [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Conrad, Mark [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Cook, Paul [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Tiemi, Onishi [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)

    2011-03-31

    This is the 2nd report on the three-year program of the 2nd phase of the NUMO-LBNL collaborative project: Development of Hydrologic Characterization Technology for Fault Zones under NUMO-DOE/LBNL collaboration agreement. As such, this report is a compendium of the results by Kiho et al. (2011) and those by LBNL.

  3. Statistical Feature Extraction for Fault Locations in Nonintrusive Fault Detection of Low Voltage Distribution Systems

    Directory of Open Access Journals (Sweden)

    Hsueh-Hsien Chang

    2017-04-01

    Full Text Available This paper proposes statistical feature extraction methods combined with artificial intelligence (AI approaches for fault locations in non-intrusive single-line-to-ground fault (SLGF detection of low voltage distribution systems. The input features of the AI algorithms are extracted using statistical moment transformation for reducing the dimensions of the power signature inputs measured by using non-intrusive fault monitoring (NIFM techniques. The data required to develop the network are generated by simulating SLGF using the Electromagnetic Transient Program (EMTP in a test system. To enhance the identification accuracy, these features after normalization are given to AI algorithms for presenting and evaluating in this paper. Different AI techniques are then utilized to compare which identification algorithms are suitable to diagnose the SLGF for various power signatures in a NIFM system. The simulation results show that the proposed method is effective and can identify the fault locations by using non-intrusive monitoring techniques for low voltage distribution systems.

  4. Dynamics model for real time diagnostics of Triga RC-1 system

    International Nuclear Information System (INIS)

    Gadomski, A.M.; Nanni, V.; Meo, G.

    1988-01-01

    This paper presents dynamics model of TRIGA RC-1 reactor system. The model is dedicated to the real-time early fault detection during a reactor operation in one week exploitation cycle. The algorithms are specially suited for real-time, long time and also accelerated simulations with assumed diagnostic oriented accuracy. The approximations, modular structure, numerical methods and validation are discussed. The elaborated model will be build in the TRIGA Supervisor System and TRIGA Diagnostic Simulator

  5. Development of ITER diagnostics: Neutronic analysis and radiation hardness

    Energy Technology Data Exchange (ETDEWEB)

    Vukolov, Konstantin, E-mail: vukolov_KY@nrcki.ru; Borisov, Andrey; Deryabina, Natalya; Orlovskiy, Ilya

    2015-10-15

    Highlights: • Problems of ITER diagnostics caused by neutron radiation from hot DT plasma considered. • Careful neutronic analysis is necessary for ITER diagnostics development. • Effective nuclear shielding for ITER diagnostics in the 11th equatorial port plug proposed. • Requirements for study of radiation hardness of diagnostic elements defined. • Results of optical glasses irradiation tests in a fission reactor given. - Abstract: The paper is dedicated to the problems of ITER diagnostics caused by effects of radiation from hot DT plasma. An effective nuclear shielding must be arranged in diagnostic port plugs to meet the nuclear safety requirements and to provide reliable operation of the diagnostics. This task can be solved with the help of neutronic analysis of the diagnostics environment within the port plugs at the design stage. Problems of neutronic calculations are demonstrated for the 11th equatorial port plug. The numerical simulation includes the calculations of neutron fluxes in the port-plug and in the interspace. Options for nuclear shielding, such as tungsten collimator, boron carbide and water moderators, stainless steel and lead screens are considered. Data on neutron fluxes along diagnostic labyrinths allow to define radiation hardness requirements for the diagnostic components and to specify their materials. Options for windows and lenses materials for optical diagnostics are described. The results of irradiation of flint and silica glasses in nuclear reactor have shown that silica KU-1 and KS-4V retain transparency in visible range after neutron fluence of 10{sup 17} cm{sup −2}. Flints required for achromatic objectives have much less radiation hardness about 5 × 10{sup 14} n/cm{sup 2}.

  6. Probabilistic techniques using Monte Carlo sampling for multi- component system diagnostics

    International Nuclear Information System (INIS)

    Aumeier, S.E.; Lee, J.C.; Akcasu, A.Z.

    1995-01-01

    We outline the structure of a new approach at multi-component system fault diagnostics which utilizes detailed system simulation models, uncertain system observation data, statistical knowledge of system parameters, expert opinion, and component reliability data in an effort to identify incipient component performance degradations of arbitrary number and magnitude. The technique involves the use of multiple adaptive Kalman filters for fault estimation, the results of which are screened using standard hypothesis testing procedures to define a set of component events that could have transpired. Latin Hypercube sample each of these feasible component events in terms of uncertain component reliability data and filter estimates. The capabilities of the procedure are demonstrated through the analysis of a simulated small magnitude binary component fault in a boiling water reactor balance of plant. The results show that the procedure has the potential to be a very effective tool for incipient component fault diagnosis

  7. Fault diagnosis methods for district heating substations

    Energy Technology Data Exchange (ETDEWEB)

    Pakanen, J.; Hyvaerinen, J.; Kuismin, J.; Ahonen, M. [VTT Building Technology, Espoo (Finland). Building Physics, Building Services and Fire Technology

    1996-12-31

    A district heating substation is a demanding process for fault diagnosis. The process is nonlinear, load conditions of the district heating network change unpredictably and standard instrumentation is designed only for control and local monitoring purposes, not for automated diagnosis. Extra instrumentation means additional cost, which is usually not acceptable to consumers. That is why all conventional methods are not applicable in this environment. The paper presents five different approaches to fault diagnosis. While developing the methods, various kinds of pragmatic aspects and robustness had to be considered in order to achieve practical solutions. The presented methods are: classification of faults using performance indexing, static and physical modelling of process equipment, energy balance of the process, interactive fault tree reasoning and statistical tests. The methods are applied to a control valve, a heat excharger, a mud separating device and the whole process. The developed methods are verified in practice using simulation, simulation or field tests. (orig.) (25 refs.)

  8. Strong paleoearthquakes along the Talas-Fergana Fault, Kyrgyzstan

    Directory of Open Access Journals (Sweden)

    A.M. Korzhenkov

    2014-02-01

    Full Text Available The Talas-Fergana Fault, the largest strike-slip structure in Centred. Asia, forms an obliquely oriented boundary between the northeastern and southwestern parts of the Tianshan mountain belt. The fault underwent active right-lateral strike-slip during the Paleozoic, with right-lateral movements being rejuvenated in the Late Cenozoic. Tectonic movements along the intracontinental strike-slip faults contribute to absorb part of the regional crustal shortening linked to the India-Eurasia collision; knowledge of strike-slip motions along the Talas-Fergana Fault are necessary for a complete assessment of the active deformation of the Tianshan orogen. To improve our understanding of the intracontinental deformation of the Tianshan mountain belt and the occurrence of strong earthquakes along the whole length of the Talas-Fergana Fault, we identify features of relief arising during strong paleoearthquakes along the Talas-Fergana Fault, fault segmentation, the length of seismogenic ruptures, and the energy and age of ancient catastrophes. We show that during neotectonic time the fault developed as a dextral strike-slip fault, with possible dextral displacements spreading to secondary fault planes north of the main fault trace. We determine rates of Holocene and Late Pleistocene dextral movements, and our radiocarbon dating indicates tens of strong earthquakes occurring along the fault zone during arid interval of 15800 years. The reoccurrence of strong earthquakes along the Talas-Fergana Fault zone during the second half of the Holocene is about 300 years. The next strong earthquake along the fault will most probably occur along its southeastern chain during the next several decades. Seismotectonic deformation parameters indicate that M > 7 earthquakes with oscillation intensity I > IX have occurred.

  9. Multiple Soft Fault Diagnosis of Bjt Circuits

    Directory of Open Access Journals (Sweden)

    Tadeusiewicz Michał

    2014-12-01

    Full Text Available This paper deals with multiple soft fault diagnosis of nonlinear analog circuits comprising bipolar transistors characterized by the Ebers-Moll model. Resistances of the circuit and beta forward factor of a transistor are considered as potentially faulty parameters. The proposed diagnostic method exploits a strongly nonlinear set of algebraic type equations, which may possess multiple solutions, and is capable of finding different sets of the parameters values which meet the diagnostic test. The equations are written on the basis of node analysis and include DC voltages measured at accessible nodes, as well as some measured currents. The unknown variables are node voltages and the parameters which are considered as potentially faulty. The number of these parameters is larger than the number of the accessible nodes. To solve the set of equations the block relaxation method is used with different assignments of the variables to the blocks. Next, the solutions are corrected using the Newton-Raphson algorithm. As a result, one or more sets of the parameters values which satisfy the diagnostic test are obtained. The proposed approach is illustrated with a numerical example.

  10. Fault isolation techniques

    Science.gov (United States)

    Dumas, A.

    1981-01-01

    Three major areas that are considered in the development of an overall maintenance scheme of computer equipment are described. The areas of concern related to fault isolation techniques are: the programmer (or user), company and its policies, and the manufacturer of the equipment.

  11. Development and implementation of plant diagnostic skills training

    International Nuclear Information System (INIS)

    Iwatare, K.; Noji, K.

    2010-01-01

    It was learned from the July 2007 Chuetsu-oki Earthquake that a need exists for simulator training methods to be revised to include the assumption of multiple failures such as those which may occur during a large earthquake. At BWR Operator Training Center Corp., multiple failure team training which focuses on plant diagnostic skills (Plant Diagnostic Skills Training) has been developed and implemented since September 2008. The contents of this training along with the results are presented and considered in this paper. (author)

  12. Design of fault simulator

    Energy Technology Data Exchange (ETDEWEB)

    Gabbar, Hossam A. [Faculty of Energy Systems and Nuclear Science, University of Ontario Institute of Technology (UOIT), Ontario, L1H 7K4 (Canada)], E-mail: hossam.gabbar@uoit.ca; Sayed, Hanaa E.; Osunleke, Ajiboye S. [Okayama University, Graduate School of Natural Science and Technology, Division of Industrial Innovation Sciences Department of Intelligent Systems Engineering, Okayama 700-8530 (Japan); Masanobu, Hara [AspenTech Japan Co., Ltd., Kojimachi Crystal City 10F, Kojimachi, Chiyoda-ku, Tokyo 102-0083 (Japan)

    2009-08-15

    Fault simulator is proposed to understand and evaluate all possible fault propagation scenarios, which is an essential part of safety design and operation design and support of chemical/production processes. Process models are constructed and integrated with fault models, which are formulated in qualitative manner using fault semantic networks (FSN). Trend analysis techniques are used to map real time and simulation quantitative data into qualitative fault models for better decision support and tuning of FSN. The design of the proposed fault simulator is described and applied on experimental plant (G-Plant) to diagnose several fault scenarios. The proposed fault simulator will enable industrial plants to specify and validate safety requirements as part of safety system design as well as to support recovery and shutdown operation and disaster management.

  13. Striation and slickenline development on quartz fault surfaces at crustal conditions : Origin and effect on friction

    NARCIS (Netherlands)

    Toy, Virginia G.; Niemeijer, André; Renard, Francois; Morales, Luiz; Wirth, Richard

    Fragments of optically flat silica discs embedded in synthetic gouge were deformed to examine the relationship between the development of striations and slickenlines, and deformation mechanisms, conditions, and fault rheology. Experiments were performed under hydrothermal conditions in a rotary

  14. Product quality management based on CNC machine fault prognostics and diagnosis

    Science.gov (United States)

    Kozlov, A. M.; Al-jonid, Kh M.; Kozlov, A. A.; Antar, Sh D.

    2018-03-01

    This paper presents a new fault classification model and an integrated approach to fault diagnosis which involves the combination of ideas of Neuro-fuzzy Networks (NF), Dynamic Bayesian Networks (DBN) and Particle Filtering (PF) algorithm on a single platform. In the new model, faults are categorized in two aspects, namely first and second degree faults. First degree faults are instantaneous in nature, and second degree faults are evolutional and appear as a developing phenomenon which starts from the initial stage, goes through the development stage and finally ends at the mature stage. These categories of faults have a lifetime which is inversely proportional to a machine tool's life according to the modified version of Taylor’s equation. For fault diagnosis, this framework consists of two phases: the first one is focusing on fault prognosis, which is done online, and the second one is concerned with fault diagnosis which depends on both off-line and on-line modules. In the first phase, a neuro-fuzzy predictor is used to take a decision on whether to embark Conditional Based Maintenance (CBM) or fault diagnosis based on the severity of a fault. The second phase only comes into action when an evolving fault goes beyond a critical threshold limit called a CBM limit for a command to be issued for fault diagnosis. During this phase, DBN and PF techniques are used as an intelligent fault diagnosis system to determine the severity, time and location of the fault. The feasibility of this approach was tested in a simulation environment using the CNC machine as a case study and the results were studied and analyzed.

  15. A Roller Bearing Fault Diagnosis Method Based on LCD Energy Entropy and ACROA-SVM

    Directory of Open Access Journals (Sweden)

    HungLinh Ao

    2014-01-01

    Full Text Available This study investigates a novel method for roller bearing fault diagnosis based on local characteristic-scale decomposition (LCD energy entropy, together with a support vector machine designed using an Artificial Chemical Reaction Optimisation Algorithm, referred to as an ACROA-SVM. First, the original acceleration vibration signals are decomposed into intrinsic scale components (ISCs. Second, the concept of LCD energy entropy is introduced. Third, the energy features extracted from a number of ISCs that contain the most dominant fault information serve as input vectors for the support vector machine classifier. Finally, the ACROA-SVM classifier is proposed to recognize the faulty roller bearing pattern. The analysis of roller bearing signals with inner-race and outer-race faults shows that the diagnostic approach based on the ACROA-SVM and using LCD to extract the energy levels of the various frequency bands as features can identify roller bearing fault patterns accurately and effectively. The proposed method is superior to approaches based on Empirical Mode Decomposition method and requires less time.

  16. Development of X-ray tracer diagnostics for radiatively-driven ablator experiments

    International Nuclear Information System (INIS)

    MacFarlane, J.J.; Cohen, D.H.; Wang, P.; Moses, G.A.; Peterson, R.R.; Jaanimagi, P.A.; Langen, O.L.; Olson, R.E.; Murphy, T.J.; Magelssen, G.R.; Delamater, N.D.

    1999-01-01

    This report covers fiscal year 1998 of our ongoing project to develop tracer X-ray spectroscopic diagnostics for hohlraum environments. This effort focused on an experimental campaign carried out at OMEGA on 25--27 August 1998. This phase of the project heavily emphasized experimental design, diagnostic development, and target fabrication, as well as building up numerical models for the experiments. The spectral diagnostic under development involves using two thin (few 1000 Angstroem) mid-Z tracers in two witness plates mounted on the side of a hohlraum with the tracers' K a absorption features seen against an X-ray backlighter. The absorption data are used to sample the time-dependent, localized properties of each witness plate as a radiation wave ablates it. The experiments represented the first application of this diagnostic, in this case to side-by-side doped and undoped plastic to investigate the effects of capsule ablator dopants

  17. Fault zone architecture of a major oblique-slip fault in the Rawil depression, Western Helvetic nappes, Switzerland

    Science.gov (United States)

    Gasser, D.; Mancktelow, N. S.

    2009-04-01

    The Helvetic nappes in the Swiss Alps form a classic fold-and-thrust belt related to overall NNW-directed transport. In western Switzerland, the plunge of nappe fold axes and the regional distribution of units define a broad depression, the Rawil depression, between the culminations of Aiguilles Rouge massif to the SW and Aar massif to the NE. A compilation of data from the literature establishes that, in addition to thrusts related to nappe stacking, the Rawil depression is cross-cut by four sets of brittle faults: (1) SW-NE striking normal faults that strike parallel to the regional fold axis trend, (2) NW-SE striking normal faults and joints that strike perpendicular to the regional fold axis trend, and (3) WNW-ESE striking normal plus dextral oblique-slip faults as well as (4) WSW-ENE striking normal plus dextral oblique-slip faults that both strike oblique to the regional fold axis trend. We studied in detail a beautifully exposed fault from set 3, the Rezli fault zone (RFZ) in the central Wildhorn nappe. The RFZ is a shallow to moderately-dipping (ca. 30-60˚) fault zone with an oblique-slip displacement vector, combining both dextral and normal components. It must have formed in approximately this orientation, because the local orientation of fold axes corresponds to the regional one, as does the generally vertical orientation of extensional joints and veins associated with the regional fault set 2. The fault zone crosscuts four different lithologies: limestone, intercalated marl and limestone, marl and sandstone, and it has a maximum horizontal dextral offset component of ~300 m and a maximum vertical normal offset component of ~200 m. Its internal architecture strongly depends on the lithology in which it developed. In the limestone, it consists of veins, stylolites, cataclasites and cemented gouge, in the intercalated marls and limestones of anastomosing shear zones, brittle fractures, veins and folds, in the marls of anastomosing shear zones, pressure

  18. Efficient fault tree handling - the Asea-Atom approach

    International Nuclear Information System (INIS)

    Ericsson, G.; Knochenhauer, M.; Mills, R.

    1985-01-01

    In recent years there has been a trend in Swedish Probabilistic Safety Analysis (PSA) work towards coordination of the tools and methods used, in order to facilitate exchange of information and review. Thus, standardized methods for fault tree drawing and basic event coding have been developed as well as a number of computer codes for fault tree handling. The computer code used by Asea-Atom is called SUPER-TREE. As indicated by the name, the key feature is the concept of one super tree containing all the information necessary in the fault tree analysis, i.e. system fault trees, sequence fault trees and component data base. The code has proved to allow great flexibility in the choice of level of detail in the analysis

  19. Paleoseismology of Sinistral-Slip Fault System, Focusing on the Mae Chan Fault, on the Shan Plateau, SE Asia.

    Science.gov (United States)

    Curtiss, E. R.; Weldon, R. J.; Wiwegwin, W.; Weldon, E. M.

    2017-12-01

    The Shan Plateau, which includes portions of Myanmar, China, Thailand, Laos, and Vietnam lies between the dextral NS-trending Sagaing and SE-trending Red River faults and contains 14 active E-W sinistral-slip faults, including the Mae Chan Fault (MCF) in northern Thailand. The last ground-rupturing earthquake to occur on the broader sinistral fault system was the M6.8 Tarlay earthquake in Myanmar in March 2011 on the Nam Ma fault immediately north of the MCF the last earthquake to occur on the MCF was a M4.0 in the 5th century that destroyed the entire city of Wiang Yonok (Morley et al., 2011). We report on a trenching study of the MCF, which is part of a broader study to create a regional seismic hazard map of the entire Shan Plateau. By studying the MCF, which appears to be representative of the sinistral faults, and easy to work on, we hope to characterize both it and the other unstudied faults in the system. As part of a paleoseismology training course we dug two trenches at the Pa Tueng site on the MCF, within an offset river channel and the trenches exposed young sediment with abundant charcoal (in process of dating), cultural artifacts, and evidence for the last two (or three) ground-rupturing earthquakes on the fault. We hope to use the data from this site to narrow the recurrence interval, which is currently to be 2,000-4,000 years and the slip rate of 1-2 mm/year, being developed at other sites on the fault. By extrapolating the data of the MCF to the other faults we will have a better understanding of the whole fault system. Once we have characterized the MCF, we plan to use geomorphic offsets and strain rates from regional GPS to relatively estimate the activity of the other faults in this sinistral system.

  20. Computer-oriented approach to fault-tree construction

    International Nuclear Information System (INIS)

    Salem, S.L.; Apostolakis, G.E.; Okrent, D.

    1976-11-01

    A methodology for systematically constructing fault trees for general complex systems is developed and applied, via the Computer Automated Tree (CAT) program, to several systems. A means of representing component behavior by decision tables is presented. The method developed allows the modeling of components with various combinations of electrical, fluid and mechanical inputs and outputs. Each component can have multiple internal failure mechanisms which combine with the states of the inputs to produce the appropriate output states. The generality of this approach allows not only the modeling of hardware, but human actions and interactions as well. A procedure for constructing and editing fault trees, either manually or by computer, is described. The techniques employed result in a complete fault tree, in standard form, suitable for analysis by current computer codes. Methods of describing the system, defining boundary conditions and specifying complex TOP events are developed in order to set up the initial configuration for which the fault tree is to be constructed. The approach used allows rapid modifications of the decision tables and systems to facilitate the analysis and comparison of various refinements and changes in the system configuration and component modeling

  1. FADES: A tool for automated fault analysis of complex systems

    International Nuclear Information System (INIS)

    Wood, C.

    1990-01-01

    FADES is an Expert System for performing fault analyses on complex connected systems. By using a graphical editor to draw components and link them together the FADES system allows the analyst to describe a given system. The knowledge base created is used to qualitatively simulate the system behaviour. By inducing all possible component failures in the system and determining their effects, a set of facts is built up. These facts are then used to create Fault Trees, or FMEA tables. The facts may also be used for explanation effects and to generate diagnostic rules allowing system instrumentation to be optimised. The prototype system has been built and tested and is preently undergoing testing by users. All comments from these trials will be used to tailor the system to the requirements of the user so that the end product performs the exact task required

  2. Solving fault diagnosis problems linear synthesis techniques

    CERN Document Server

    Varga, Andreas

    2017-01-01

    This book addresses fault detection and isolation topics from a computational perspective. Unlike most existing literature, it bridges the gap between the existing well-developed theoretical results and the realm of reliable computational synthesis procedures. The model-based approach to fault detection and diagnosis has been the subject of ongoing research for the past few decades. While the theoretical aspects of fault diagnosis on the basis of linear models are well understood, most of the computational methods proposed for the synthesis of fault detection and isolation filters are not satisfactory from a numerical standpoint. Several features make this book unique in the fault detection literature: Solution of standard synthesis problems in the most general setting, for both continuous- and discrete-time systems, regardless of whether they are proper or not; consequently, the proposed synthesis procedures can solve a specific problem whenever a solution exists Emphasis on the best numerical algorithms to ...

  3. Eigenvector of gravity gradient tensor for estimating fault dips considering fault type

    Science.gov (United States)

    Kusumoto, Shigekazu

    2017-12-01

    The dips of boundaries in faults and caldera walls play an important role in understanding their formation mechanisms. The fault dip is a particularly important parameter in numerical simulations for hazard map creation as the fault dip affects estimations of the area of disaster occurrence. In this study, I introduce a technique for estimating the fault dip using the eigenvector of the observed or calculated gravity gradient tensor on a profile and investigating its properties through numerical simulations. From numerical simulations, it was found that the maximum eigenvector of the tensor points to the high-density causative body, and the dip of the maximum eigenvector closely follows the dip of the normal fault. It was also found that the minimum eigenvector of the tensor points to the low-density causative body and that the dip of the minimum eigenvector closely follows the dip of the reverse fault. It was shown that the eigenvector of the gravity gradient tensor for estimating fault dips is determined by fault type. As an application of this technique, I estimated the dip of the Kurehayama Fault located in Toyama, Japan, and obtained a result that corresponded to conventional fault dip estimations by geology and geomorphology. Because the gravity gradient tensor is required for this analysis, I present a technique that estimates the gravity gradient tensor from the gravity anomaly on a profile.

  4. Comparison of Two Classifiers; K-Nearest Neighbor and Artificial Neural Network, for Fault Diagnosis on a Main Engine Journal-Bearing

    Directory of Open Access Journals (Sweden)

    A. Moosavian

    2013-01-01

    Full Text Available Vibration analysis is an accepted method in condition monitoring of machines, since it can provide useful and reliable information about machine working condition. This paper surveys a new scheme for fault diagnosis of main journal-bearings of internal combustion (IC engine based on power spectral density (PSD technique and two classifiers, namely, K-nearest neighbor (KNN and artificial neural network (ANN. Vibration signals for three different conditions of journal-bearing; normal, with oil starvation condition and extreme wear fault were acquired from an IC engine. PSD was applied to process the vibration signals. Thirty features were extracted from the PSD values of signals as a feature source for fault diagnosis. KNN and ANN were trained by training data set and then used as diagnostic classifiers. Variable K value and hidden neuron count (N were used in the range of 1 to 20, with a step size of 1 for KNN and ANN to gain the best classification results. The roles of PSD, KNN and ANN techniques were studied. From the results, it is shown that the performance of ANN is better than KNN. The experimental results dèmonstrate that the proposed diagnostic method can reliably separate different fault conditions in main journal-bearings of IC engine.

  5. FAULT TOLERANCE IN JOB SCHEDULING THROUGH FAULT MANAGEMENT FRAMEWORK USING SOA IN GRID

    Directory of Open Access Journals (Sweden)

    V. Indhumathi

    2017-01-01

    Full Text Available The rapid development in computing resources has enhanced the recital of computers and abridged their costs. This accessibility of low cost prevailing computers joined with the fame of the Internet and high-speed networks has leaded the computing surroundings to be mapped from dispersed to grid environments. Grid is a kind of dispersed system which supports the allotment and harmonized exploit of geographically dispersed and multi-owner resources, autonomously from their physical form and site, in vibrant practical organizations that carve up the similar objective of decipher large-scale applications. Thus any type of failure can happen at any point of time and job running in grid environment might fail. Therefore fault tolerance is an imperative and demanding concern in grid computing as the steadiness of individual grid resources may not be guaranteed. In order to build computational grids more effectual and consistent fault tolerant system is required. In order to accomplish the user prospect in terms of recital and competence, the Grid system desires SOA Fault Management Framework for the sharing of tasks with fault tolerance. A Fault Management Framework endeavor to pick up the response time of user’s proposed applications by ensures maximal exploitation of obtainable resources. The main aim is to avert, if probable, the stipulation where some processors are congested by means of a set of tasks while others are flippantly loaded or even at leisure.

  6. Multiple-step fault estimation for interval type-II T-S fuzzy system of hypersonic vehicle with time-varying elevator faults

    Directory of Open Access Journals (Sweden)

    Jin Wang

    2017-03-01

    Full Text Available This article proposes a multiple-step fault estimation algorithm for hypersonic flight vehicles that uses an interval type-II Takagi–Sugeno fuzzy model. An interval type-II Takagi–Sugeno fuzzy model is developed to approximate the nonlinear dynamic system and handle the parameter uncertainties of hypersonic firstly. Then, a multiple-step time-varying additive fault estimation algorithm is designed to estimate time-varying additive elevator fault of hypersonic flight vehicles. Finally, the simulation is conducted in both aspects of modeling and fault estimation; the validity and availability of such method are verified by a series of the comparison of numerical simulation results.

  7. Fault Current Characteristics of the DFIG under Asymmetrical Fault Conditions

    Directory of Open Access Journals (Sweden)

    Fan Xiao

    2015-09-01

    Full Text Available During non-severe fault conditions, crowbar protection is not activated and the rotor windings of a doubly-fed induction generator (DFIG are excited by the AC/DC/AC converter. Meanwhile, under asymmetrical fault conditions, the electrical variables oscillate at twice the grid frequency in synchronous dq frame. In the engineering practice, notch filters are usually used to extract the positive and negative sequence components. In these cases, the dynamic response of a rotor-side converter (RSC and the notch filters have a large influence on the fault current characteristics of the DFIG. In this paper, the influence of the notch filters on the proportional integral (PI parameters is discussed and the simplified calculation models of the rotor current are established. Then, the dynamic performance of the stator flux linkage under asymmetrical fault conditions is also analyzed. Based on this, the fault characteristics of the stator current under asymmetrical fault conditions are studied and the corresponding analytical expressions of the stator fault current are obtained. Finally, digital simulation results validate the analytical results. The research results are helpful to meet the requirements of a practical short-circuit calculation and the construction of a relaying protection system for the power grid with penetration of DFIGs.

  8. Application of ENN-1 for Fault Diagnosis of Wind Power Systems

    Directory of Open Access Journals (Sweden)

    Meng-Hui Wang

    2012-01-01

    Full Text Available Maintaining a wind turbine and ensuring secure is not easy because of long-term exposure to the environment and high installation locations. Wind turbines need fully functional condition-monitoring and fault diagnosis systems that prevent accidents and reduce maintenance costs. This paper presents a simulator design for fault diagnosis of wind power systems and further proposes some fault diagnosis technologies such as signal analysis, feature selecting, and diagnosis methods. First, this paper uses a wind power simulator to produce fault conditions and features from the monitoring sensors. Then an extension neural network type-1- (ENN-1- based method is proposed to develop the core of the fault diagnosis system. The proposed system will benefit the development of real fault diagnosis systems with testing models that demonstrate satisfactory results.

  9. Leveling the playing field: bringing development of biomarkers and molecular diagnostics up to the standards for drug development.

    Science.gov (United States)

    Poste, George; Carbone, David P; Parkinson, David R; Verweij, Jaap; Hewitt, Stephen M; Jessup, J Milburn

    2012-03-15

    Molecular diagnostics are becoming increasingly important in clinical research to stratify or identify molecularly profiled patient cohorts for targeted therapies, to modify the dose of a therapeutic, and to assess early response to therapy or monitor patients. Molecular diagnostics can also be used to identify the pharmacogenetic risk of adverse drug reactions. The articles in this CCR Focus section on molecular diagnosis describe the development and use of markers to guide medical decisions regarding cancer patients. They define sources of preanalytic variability that need to be minimized, as well as the regulatory and financial challenges involved in developing diagnostics and integrating them into clinical practice. They also outline a National Cancer Institute program to assist diagnostic development. Molecular diagnostic clinical tests require rigor in their development and clinical validation, with sensitivity, specificity, and validity comparable to those required for the development of therapeutics. These diagnostics must be offered at a realistic cost that reflects both their clinical value and the costs associated with their development. When genome-sequencing technologies move into the clinic, they must be integrated with and traceable to current technology because they may identify more efficient and accurate approaches to drug development. In addition, regulators may define progressive drug approval for companion diagnostics that requires further evidence regarding efficacy and safety before full approval can be achieved. One way to accomplish this is to emphasize phase IV postmarketing, hypothesis-driven clinical trials with biological characterization that would permit an accurate definition of the association of low-prevalence gene alterations with toxicity or response in large cohorts.

  10. Incipient fault detection and identification in process systems using accelerating neural network learning

    International Nuclear Information System (INIS)

    Parlos, A.G.; Muthusami, J.; Atiya, A.F.

    1994-01-01

    The objective of this paper is to present the development and numerical testing of a robust fault detection and identification (FDI) system using artificial neural networks (ANNs), for incipient (slowly developing) faults occurring in process systems. The challenge in using ANNs in FDI systems arises because of one's desire to detect faults of varying severity, faults from noisy sensors, and multiple simultaneous faults. To address these issues, it becomes essential to have a learning algorithm that ensures quick convergence to a high level of accuracy. A recently developed accelerated learning algorithm, namely a form of an adaptive back propagation (ABP) algorithm, is used for this purpose. The ABP algorithm is used for the development of an FDI system for a process composed of a direct current motor, a centrifugal pump, and the associated piping system. Simulation studies indicate that the FDI system has significantly high sensitivity to incipient fault severity, while exhibiting insensitivity to sensor noise. For multiple simultaneous faults, the FDI system detects the fault with the predominant signature. The major limitation of the developed FDI system is encountered when it is subjected to simultaneous faults with similar signatures. During such faults, the inherent limitation of pattern-recognition-based FDI methods becomes apparent. Thus, alternate, more sophisticated FDI methods become necessary to address such problems. Even though the effectiveness of pattern-recognition-based FDI methods using ANNs has been demonstrated, further testing using real-world data is necessary

  11. Dynamics model for real time diagnostics of TRIGA RC-1 system

    International Nuclear Information System (INIS)

    Gadomski, A.M.; Nanni, V.; Meo, G.B.

    1986-01-01

    This paper presents dynamics model of TRIGA RC-1 reactor system. The model is dedicated to the real-time early fault detection during a reactor operation in one week exploitation cycle. The algorithms are specially suited for real-time, long time and also accelerated simulations with assumed diagnostic oriented accuracy. The approximations, modular structure, numerical methods and validation are discussed. The elaborated model will be build in the TRIGA Supervisory System and TRIGA Diagnostic Simulator. (author)

  12. Resistivity Structures of the Chelungpu Fault in the Taichung Area, Taiwan

    Directory of Open Access Journals (Sweden)

    Ping-Hu Cheng

    2006-01-01

    Full Text Available We conducted magnetotelluric prospecting in the Taichung area to investigate subsurface resistivity structures of the Chelungpu fault and the resistivity of rock formations. The results indicate that the Chelungpu fault is a complex fault system consisting of two major fault zones, several fracture zones, and back thrust. The two major fault zones, the basal and the Chi-Chi fault zone are about 800 m apart on the ground and converge to a narrow band at a depth of 3000 m. The fault zones are not smooth, composed of ramps and platforms with an average eastward dipping angle of 35° - 37° within the depth of 3000 m. In the shallower region, the basal fault zone has developed along the boundary of the Toukoshan Formation (resistivity: 200 - 400 Ω-m at the footwall and the Neogene formations on the hanging wall, where the Cholan Formation, the Chinshiu Shale, and the Kueichulai Formation have respective resistivity mainly in the ranges: 40 - 100, 8 - 60, and 50 - 150 Ω-m. While the Chi-Chi fault zone has developed along the weak layers of the Cholan Formation where resistivity is lower than the unsheared block.

  13. An Active Fault-Tolerant Control Method Ofunmanned Underwater Vehicles with Continuous and Uncertain Faults

    Directory of Open Access Journals (Sweden)

    Daqi Zhu

    2008-11-01

    Full Text Available This paper introduces a novel thruster fault diagnosis and accommodation system for open-frame underwater vehicles with abrupt faults. The proposed system consists of two subsystems: a fault diagnosis subsystem and a fault accommodation sub-system. In the fault diagnosis subsystem a ICMAC(Improved Credit Assignment Cerebellar Model Articulation Controllers neural network is used to realize the on-line fault identification and the weighting matrix computation. The fault accommodation subsystem uses a control algorithm based on weighted pseudo-inverse to find the solution of the control allocation problem. To illustrate the proposed method effective, simulation example, under multi-uncertain abrupt faults, is given in the paper.

  14. Adaptive robust fault-tolerant control for linear MIMO systems with unmatched uncertainties

    Science.gov (United States)

    Zhang, Kangkang; Jiang, Bin; Yan, Xing-Gang; Mao, Zehui

    2017-10-01

    In this paper, two novel fault-tolerant control design approaches are proposed for linear MIMO systems with actuator additive faults, multiplicative faults and unmatched uncertainties. For time-varying multiplicative and additive faults, new adaptive laws and additive compensation functions are proposed. A set of conditions is developed such that the unmatched uncertainties are compensated by actuators in control. On the other hand, for unmatched uncertainties with their projection in unmatched space being not zero, based on a (vector) relative degree condition, additive functions are designed to compensate for the uncertainties from output channels in the presence of actuator faults. The developed fault-tolerant control schemes are applied to two aircraft systems to demonstrate the efficiency of the proposed approaches.

  15. Information Based Fault Diagnosis

    DEFF Research Database (Denmark)

    Niemann, Hans Henrik; Poulsen, Niels Kjølstad

    2008-01-01

    Fault detection and isolation, (FDI) of parametric faults in dynamic systems will be considered in this paper. An active fault diagnosis (AFD) approach is applied. The fault diagnosis will be investigated with respect to different information levels from the external inputs to the systems. These ...

  16. Fault Tolerant Feedback Control

    DEFF Research Database (Denmark)

    Stoustrup, Jakob; Niemann, H.

    2001-01-01

    An architecture for fault tolerant feedback controllers based on the Youla parameterization is suggested. It is shown that the Youla parameterization will give a residual vector directly in connection with the fault diagnosis part of the fault tolerant feedback controller. It turns out...... that there is a separation be-tween the feedback controller and the fault tolerant part. The closed loop feedback properties are handled by the nominal feedback controller and the fault tolerant part is handled by the design of the Youla parameter. The design of the fault tolerant part will not affect the design...... of the nominal feedback con-troller....

  17. Study on vibration characteristics and fault diagnosis method of oil-immersed flat wave reactor in Arctic area converter station

    Science.gov (United States)

    Lai, Wenqing; Wang, Yuandong; Li, Wenpeng; Sun, Guang; Qu, Guomin; Cui, Shigang; Li, Mengke; Wang, Yongqiang

    2017-10-01

    Based on long term vibration monitoring of the No.2 oil-immersed fat wave reactor in the ±500kV converter station in East Mongolia, the vibration signals in normal state and in core loose fault state were saved. Through the time-frequency analysis of the signals, the vibration characteristics of the core loose fault were obtained, and a fault diagnosis method based on the dual tree complex wavelet (DT-CWT) and support vector machine (SVM) was proposed. The vibration signals were analyzed by DT-CWT, and the energy entropy of the vibration signals were taken as the feature vector; the support vector machine was used to train and test the feature vector, and the accurate identification of the core loose fault of the flat wave reactor was realized. Through the identification of many groups of normal and core loose fault state vibration signals, the diagnostic accuracy of the result reached 97.36%. The effectiveness and accuracy of the method in the fault diagnosis of the flat wave reactor core is verified.

  18. Progress on development of SPIDER diagnostics

    Science.gov (United States)

    Pasqualotto, R.; Agostini, M.; Barbisan, M.; Bernardi, M.; Brombin, M.; Cavazzana, R.; Croci, G.; Palma, M. Dalla; Delogu, R. S.; Gorini, G.; Lotto, L.; Muraro, A.; Peruzzo, S.; Pimazzoni, A.; Pomaro, N.; Rizzolo, A.; Serianni, G.; Spolaore, M.; Tardocchi, M.; Zaniol, B.; Zaupa, M.

    2017-08-01

    SPIDER experiment, the full size prototype of the beam source for the ITER heating neutral beam injector, has to demonstrate extraction and acceleration to 100 kV of a large negative ion hydrogen or deuterium beam with co-extracted electron fraction e-/D- SPIDER plant systems are being installed, the different diagnostic systems are in the procurement phase. Their final design is described here with a focus on some key solutions and most original and cost effective implementations. Thermocouples used to measure the power load distribution in the source and over the beam dump front surface will be efficiently fixed with proven technique and acquired through commercial and custom electronics. Spectroscopy needs to use well collimated lines of sight and will employ novel design spectrometers with higher efficiency and resolution and filtered detectors with custom built amplifiers. The electrostatic probes will be operated through electronics specifically developed to cope with the challenging environment of the RF source. The instrumented calorimeter STRIKE will use new CFC tiles, still under development. Two linear cameras, one built in house, have been tested as suitable for optical beam tomography. Some diagnostic components are off the shelf, others are custom developed: some of these are being prototyped or are under test before final production and installation, which will be completed before start of SPIDER operation.

  19. Semi-automatic mapping of fault rocks on a Digital Outcrop Model, Gole Larghe Fault Zone (Southern Alps, Italy)

    Science.gov (United States)

    Vho, Alice; Bistacchi, Andrea

    2015-04-01

    A quantitative analysis of fault-rock distribution is of paramount importance for studies of fault zone architecture, fault and earthquake mechanics, and fluid circulation along faults at depth. Here we present a semi-automatic workflow for fault-rock mapping on a Digital Outcrop Model (DOM). This workflow has been developed on a real case of study: the strike-slip Gole Larghe Fault Zone (GLFZ). It consists of a fault zone exhumed from ca. 10 km depth, hosted in granitoid rocks of Adamello batholith (Italian Southern Alps). Individual seismogenic slip surfaces generally show green cataclasites (cemented by the precipitation of epidote and K-feldspar from hydrothermal fluids) and more or less well preserved pseudotachylytes (black when well preserved, greenish to white when altered). First of all, a digital model for the outcrop is reconstructed with photogrammetric techniques, using a large number of high resolution digital photographs, processed with VisualSFM software. By using high resolution photographs the DOM can have a much higher resolution than with LIDAR surveys, up to 0.2 mm/pixel. Then, image processing is performed to map the fault-rock distribution with the ImageJ-Fiji package. Green cataclasites and epidote/K-feldspar veins can be quite easily separated from the host rock (tonalite) using spectral analysis. Particularly, band ratio and principal component analysis have been tested successfully. The mapping of black pseudotachylyte veins is more tricky because the differences between the pseudotachylyte and biotite spectral signature are not appreciable. For this reason we have tested different morphological processing tools aimed at identifying (and subtracting) the tiny biotite grains. We propose a solution based on binary images involving a combination of size and circularity thresholds. Comparing the results with manually segmented images, we noticed that major problems occur only when pseudotachylyte veins are very thin and discontinuous. After

  20. THE ACTIVE FAULTS OF EURASIA DATABASE

    Directory of Open Access Journals (Sweden)

    D. M. Bachmanov

    2017-01-01

    Full Text Available This paper describes the technique used to create and maintain the Active Faults of Eurasia Database (AFED based on the uniform format that ensures integrating the materials accumulated by many researchers, inclu­ding the authors of the AFED. The AFED includes the data on more than 20 thousand objects: faults, fault zones and associated structural forms that show the signs of latest displacements in the Late Pleistocene and Holocene. The geographical coordinates are given for each object. The AFED scale is 1:500000; the demonstration scale is 1:1000000. For each object, the AFED shows two kinds of characteristics: justification attributes, and estimated attributes. The justification attributes inform the AFED user about an object: the object’s name; morphology; kinematics; the amplitudes of displacement for different periods of time; displacement rates estimated from the amplitudes; the age of the latest recorded signs of activity, seismicity and paleoseismicity; the relationship of the given objects with the parameters of crustal earthquakes; etc. The sources of information are listed in the AFED appendix. The estimated attributes are represented by the system of indices reflecting the fault kinematics according to the classification of the faults by types, as accepted in structural geology, and includes three ranks of the Late Quaternary movements and four degrees of reliability of identifying the structures as active ones. With reference to the indices, the objects can be compared with each other, considering any of the attributes, or with any other digitized information. The comparison can be performed by any GIS software. The AFED is an efficient tool for obtaining the information on the faults and solving general problems, such as thematic mapping, determining the parameters of modern geodynamic processes, estima­ting seismic and other geodynamic hazards, identifying the tectonic development trends in the Pliocene–Quaternary stage of