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.

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.

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.

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)

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.

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.

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.

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

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

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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.

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

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.

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.

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

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.

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.

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.

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.

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

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.

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.

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.

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.

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...

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.

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

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

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.

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.

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

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.

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.

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.

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

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.

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.

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.

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

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)

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.

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.

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.

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

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

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...

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

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.

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.

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.

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

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)

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

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.

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...

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.

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

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)

Fault-tolerant computing systems

International Nuclear Information System (INIS)

Dal Cin, M.; Hohl, W.

1991-01-01

Tests, Diagnosis and Fault Treatment were chosen as the guiding themes of the conference. However, the scope of the conference included reliability, availability, safety and security issues in software and hardware systems as well. The sessions were organized for the conference which was completed by an industrial presentation: Keynote Address, Reconfiguration and Recover, System Level Diagnosis, Voting and Agreement, Testing, Fault-Tolerant Circuits, Array Testing, Modelling, Applied Fault Tolerance, Fault-Tolerant Arrays and Systems, Interconnection Networks, Fault-Tolerant Software. One paper has been indexed separately in the database. (orig./HP)

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)

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

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

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

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

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

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.

Diagnostic Neural Network Systems for the Electronic Circuits

International Nuclear Information System (INIS)

Mohamed, A.H.

2014-01-01

Neural Networks is one of the most important artificial intelligent approaches for solving the diagnostic processes. This research concerns with uses the neural networks for diagnosis of the electronic circuits. Modern electronic systems contain both the analog and digital circuits. But, diagnosis of the analog circuits suffers from great complexity due to their nonlinearity. To overcome this problem, the proposed system introduces a diagnostic system that uses the neural network to diagnose both the digital and analog circuits. So, it can face the new requirements for the modern electronic systems. A fault dictionary method was implemented in the system. Experimental results are presented on three electronic systems. They are: artificial kidney, wireless network and personal computer systems. The proposed system has improved the performance of the diagnostic systems when applied for these practical cases

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

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

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

Active Fault Isolation in MIMO Systems

DEFF Research Database (Denmark)

Niemann, Hans Henrik; Poulsen, Niels Kjølstad

2014-01-01

isolation is based directly on the input/output s ignals applied for the fault detection. It is guaranteed that the fault group includes the fault that had occurred in the system. The second step is individual fault isolation in the fault group . Both types of isolation are obtained by applying dedicated......Active fault isolation of parametric faults in closed-loop MIMO system s are considered in this paper. The fault isolation consists of two steps. T he first step is group- wise fault isolation. Here, a group of faults is isolated from other pos sible faults in the system. The group-wise fault...

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.

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.

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.

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...

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

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.

Solar system fault detection

Science.gov (United States)

Farrington, R.B.; Pruett, J.C. Jr.

1984-05-14

A fault detecting apparatus and method are provided for use with an active solar system. The apparatus provides an indication as to whether one or more predetermined faults have occurred in the solar system. The apparatus includes a plurality of sensors, each sensor being used in determining whether a predetermined condition is present. The outputs of the sensors are combined in a pre-established manner in accordance with the kind of predetermined faults to be detected. Indicators communicate with the outputs generated by combining the sensor outputs to give the user of the solar system and the apparatus an indication as to whether a predetermined fault has occurred. Upon detection and indication of any predetermined fault, the user can take appropriate corrective action so that the overall reliability and efficiency of the active solar system are increased.

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.

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....

Fault tolerant computing systems

International Nuclear Information System (INIS)

Randell, B.

1981-01-01

Fault tolerance involves the provision of strategies for error detection damage assessment, fault treatment and error recovery. A survey is given of the different sorts of strategies used in highly reliable computing systems, together with an outline of recent research on the problems of providing fault tolerance in parallel and distributed computing systems. (orig.)

Architecting Fault-Tolerant Software Systems

NARCIS (Netherlands)

Sözer, Hasan

2009-01-01

The increasing size and complexity of software systems makes it hard to prevent or remove all possible faults. Faults that remain in the system can eventually lead to a system failure. Fault tolerance techniques are introduced for enabling systems to recover and continue operation when they are

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.

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

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

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

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...

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.

On the description of fault-tolerant systems

International Nuclear Information System (INIS)

Syrbe, M.

1980-01-01

Various demands by increasing complexity and the disposability of new technologies, like the One-chip-microcomputer and fiber optics, lead to control systems, which are built as decentralized distributed multi-microcomputersystems. They realize not only new control functions but they also open possibilities to increase availability by fault-tolerance. The design or the selection and lay-out of such systems require a quantitative description of these systems. This is possible on the bases of the set of hardware and software moduls of the system by the use of queuing models, reliability nets and diagnostic graphs. This is shown by an example of a practically applied Really Distributed Computer Control System (RDC-System). Computer aided methods for these system descriptions are emphasized. (orig.) [de

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.

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

Guaranteed Cost Fault-Tolerant Control for Networked Control Systems with Sensor Faults

Directory of Open Access Journals (Sweden)

Qixin Zhu

2015-01-01

Full Text Available For the large scale and complicated structure of networked control systems, time-varying sensor faults could inevitably occur when the system works in a poor environment. Guaranteed cost fault-tolerant controller for the new networked control systems with time-varying sensor faults is designed in this paper. Based on time delay of the network transmission environment, the networked control systems with sensor faults are modeled as a discrete-time system with uncertain parameters. And the model of networked control systems is related to the boundary values of the sensor faults. Moreover, using Lyapunov stability theory and linear matrix inequalities (LMI approach, the guaranteed cost fault-tolerant controller is verified to render such networked control systems asymptotically stable. Finally, simulations are included to demonstrate the theoretical results.

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.

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.

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

Fuzzy fault diagnosis system of MCFC

Institute of Scientific and Technical Information of China (English)

Wang Zhenlei; Qian Feng; Cao Guangyi

2005-01-01

A kind of fault diagnosis system of molten carbonate fuel cell (MCFC) stack is proposed in this paper. It is composed of a fuzzy neural network (FNN) and a fault diagnosis element. FNN is able to deal with the information of the expert knowledge and the experiment data efficiently. It also has the ability to approximate any smooth system. FNN is used to identify the fault diagnosis model of MCFC stack. The fuzzy fault decision element can diagnose the state of the MCFC generating system, normal or fault, and can decide the type of the fault based on the outputs of FNN model and the MCFC system. Some simulation experiment results are demonstrated in this paper.

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.

Long term fault system reorganization of convergent and strike-slip systems

Science.gov (United States)

Cooke, M. L.; McBeck, J.; Hatem, A. E.; Toeneboehn, K.; Beyer, J. L.

2017-12-01

Laboratory and numerical experiments representing deformation over many earthquake cycles demonstrate that fault evolution includes episodes of fault reorganization that optimize work on the fault system. Consequently, the mechanical and kinematic efficiencies of fault systems do not increase monotonically through their evolution. New fault configurations can optimize the external work required to accommodate deformation, suggesting that changes in system efficiency can drive fault reorganization. Laboratory evidence and numerical results show that fault reorganization within accretion, strike-slip and oblique convergent systems is associated with increasing efficiency due to increased fault slip (frictional work and seismic energy) and commensurate decreased off-fault deformation (internal work and work against gravity). Between episodes of fault reorganization, fault systems may become less efficient as they produce increasing off fault deformation. For example, laboratory and numerical experiments show that the interference and interaction between different fault segments may increase local internal work or that increasing convergence can increase work against gravity produced by a fault system. This accumulation of work triggers fault reorganization as stored work provides the energy required to grow new faults that reorganize the system to a more efficient configuration. The results of laboratory and numerical experiments reveal that we should expect crustal fault systems to reorganize following periods of increasing inefficiency, even in the absence of changes to the tectonic regime. In other words, fault reorganization doesn't require a change in tectonic loading. The time frame of fault reorganization depends on fault system configuration, strain rate and processes that relax stresses within the crust. For example, stress relaxation may keep pace with stress accumulation, which would limit the increase in the internal work and gravitational work so that

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.

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)

Fault trees for diagnosis of system fault conditions

International Nuclear Information System (INIS)

Lambert, H.E.; Yadigaroglu, G.

1977-01-01

Methods for generating repair checklists on the basis of fault tree logic and probabilistic importance are presented. A one-step-ahead optimization procedure, based on the concept of component criticality, minimizing the expected time to diagnose system failure is outlined. Options available to the operator of a nuclear power plant when system fault conditions occur are addressed. A low-pressure emergency core cooling injection system, a standby safeguard system of a pressurized water reactor power plant, is chosen as an example illustrating the methods presented

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...

Data-based fault-tolerant control for affine nonlinear systems with actuator faults.

Science.gov (United States)

Xie, Chun-Hua; Yang, Guang-Hong

2016-09-01

This paper investigates the fault-tolerant control (FTC) problem for unknown nonlinear systems with actuator faults including stuck, outage, bias and loss of effectiveness. The upper bounds of stuck faults, bias faults and loss of effectiveness faults are unknown. A new data-based FTC scheme is proposed. It consists of the online estimations of the bounds and a state-dependent function. The estimations are adjusted online to compensate automatically the actuator faults. The state-dependent function solved by using real system data helps to stabilize the system. Furthermore, all signals in the resulting closed-loop system are uniformly bounded and the states converge asymptotically to zero. Compared with the existing results, the proposed approach is data-based. Finally, two simulation examples are provided to show the effectiveness of the proposed approach. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

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.

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.

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

Synthesis of Fault-Tolerant Embedded Systems

DEFF Research Database (Denmark)

Eles, Petru; Izosimov, Viacheslav; Pop, Paul

2008-01-01

This work addresses the issue of design optimization for fault- tolerant hard real-time systems. In particular, our focus is on the handling of transient faults using both checkpointing with rollback recovery and active replication. Fault tolerant schedules are generated based on a conditional...... process graph representation. The formulated system synthesis approaches decide the assignment of fault-tolerance policies to processes, the optimal placement of checkpoints and the mapping of processes to processors, such that multiple transient faults are tolerated, transparency requirements...

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.

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)

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...

High-Intensity Radiated Field Fault-Injection Experiment for a Fault-Tolerant Distributed Communication System

Science.gov (United States)

Yates, Amy M.; Torres-Pomales, Wilfredo; Malekpour, Mahyar R.; Gonzalez, Oscar R.; Gray, W. Steven

2010-01-01

Safety-critical distributed flight control systems require robustness in the presence of faults. In general, these systems consist of a number of input/output (I/O) and computation nodes interacting through a fault-tolerant data communication system. The communication system transfers sensor data and control commands and can handle most faults under typical operating conditions. However, the performance of the closed-loop system can be adversely affected as a result of operating in harsh environments. In particular, High-Intensity Radiated Field (HIRF) environments have the potential to cause random fault manifestations in individual avionic components and to generate simultaneous system-wide communication faults that overwhelm existing fault management mechanisms. This paper presents the design of an experiment conducted at the NASA Langley Research Center's HIRF Laboratory to statistically characterize the faults that a HIRF environment can trigger on a single node of a distributed flight control system.

Subaru FATS (fault tracking system)

Science.gov (United States)

Winegar, Tom W.; Noumaru, Junichi

2000-07-01

The Subaru Telescope requires a fault tracking system to record the problems and questions that staff experience during their work, and the solutions provided by technical experts to these problems and questions. The system records each fault and routes it to a pre-selected 'solution-provider' for each type of fault. The solution provider analyzes the fault and writes a solution that is routed back to the fault reporter and recorded in a 'knowledge-base' for future reference. The specifications of our fault tracking system were unique. (1) Dual language capacity -- Our staff speak both English and Japanese. Our contractors speak Japanese. (2) Heterogeneous computers -- Our computer workstations are a mixture of SPARCstations, Macintosh and Windows computers. (3) Integration with prime contractors -- Mitsubishi and Fujitsu are primary contractors in the construction of the telescope. In many cases, our 'experts' are our contractors. (4) Operator scheduling -- Our operators spend 50% of their work-month operating the telescope, the other 50% is spent working day shift at the base facility in Hilo, or day shift at the summit. We plan for 8 operators, with a frequent rotation. We need to keep all operators informed on the current status of all faults, no matter the operator's location.

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.

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

Fault tolerant control design for hybrid systems

Energy Technology Data Exchange (ETDEWEB)

Yang, Hao; Jiang, Bin [Nanjing University of Aeronautics and Astronautics, Nanjing (China); Cocquempot, Vincent [Universite des Sciences et Technologies de Lille, Villeneuve d' Ascq (France)

2010-07-01

This book intends to provide the readers a good understanding on how to achieve Fault Tolerant Control goal of Hybrid Systems. The book can be used as a reference for the academic research on Fault Tolerant Control and Hybrid Systems or used in Ph.D. study of control theory and engineering. The knowledge background for this monograph would be some undergraduate and graduate courses on Fault Diagnosis and Fault Tolerant Control theory, linear system theory, nonlinear system theory, Hybrid Systems theory and Discrete Event System theory. (orig.)

Active fault diagnosis in closed-loop systems

DEFF Research Database (Denmark)

Niemann, Hans Henrik; Poulsen, Niels Kjølstad

2005-01-01

Active fault diagnosis (AFD) of parametric faults is considered in connection with closed loop feedback systems. AFD involves auxiliary signals applied on the closed loop system. A fault signature matrix is introduced in connection with AFD and it is shown that if a limited number of faults can...

Study of fault diagnosis software design for complex system based on fault tree

International Nuclear Information System (INIS)

Yuan Run; Li Yazhou; Wang Jianye; Hu Liqin; Wang Jiaqun; Wu Yican

2012-01-01

Complex systems always have high-level reliability and safety requirements, and same does their diagnosis work. As a great deal of fault tree models have been acquired during the design and operation phases, a fault diagnosis method which combines fault tree analysis with knowledge-based technology has been proposed. The prototype of fault diagnosis software has been realized and applied to mobile LIDAR system. (authors)

Active fault detection in MIMO systems

DEFF Research Database (Denmark)

Niemann, Hans Henrik; Poulsen, Niels Kjølstad

2014-01-01

The focus in this paper is on active fault detection (AFD) for MIMO systems with parametric faults. The problem of design of auxiliary inputs with respect to detection of parametric faults is investigated. An analysis of the design of auxiliary inputs is given based on analytic transfer functions...... from auxiliary input to residual outputs. The analysis is based on a singular value decomposition of these transfer functions Based on this analysis, it is possible to design auxiliary input as well as design of the associated residual vector with respect to every single parametric fault in the system...... such that it is possible to detect these faults....

Fault Diagnosis and Fault-tolerant Control of Modular Multi-level Converter High-voltage DC System

DEFF Research Database (Denmark)

Liu, Hui; Ma, Ke; Wang, Chao

2016-01-01

of failures and lower the reliability of the MMC-HVDC system. Therefore, research on the fault diagnosis and fault-tolerant control of MMC-HVDC system is of great significance in order to enhance the reliability of the system. This paper provides a comprehensive review of fault diagnosis and fault handling...

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.

Statistical fault detection in photovoltaic systems

KAUST Repository

Garoudja, Elyes

2017-05-08

Faults in photovoltaic (PV) systems, which can result in energy loss, system shutdown or even serious safety breaches, are often difficult to avoid. Fault detection in such systems is imperative to improve their reliability, productivity, safety and efficiency. Here, an innovative model-based fault-detection approach for early detection of shading of PV modules and faults on the direct current (DC) side of PV systems is proposed. This approach combines the flexibility, and simplicity of a one-diode model with the extended capacity of an exponentially weighted moving average (EWMA) control chart to detect incipient changes in a PV system. The one-diode model, which is easily calibrated due to its limited calibration parameters, is used to predict the healthy PV array\\'s maximum power coordinates of current, voltage and power using measured temperatures and irradiances. Residuals, which capture the difference between the measurements and the predictions of the one-diode model, are generated and used as fault indicators. Then, the EWMA monitoring chart is applied on the uncorrelated residuals obtained from the one-diode model to detect and identify the type of fault. Actual data from the grid-connected PV system installed at the Renewable Energy Development Center, Algeria, are used to assess the performance of the proposed approach. Results show that the proposed approach successfully monitors the DC side of PV systems and detects temporary shading.

Energy-efficient fault-tolerant systems

CERN Document Server

Mathew, Jimson; Pradhan, Dhiraj K

2013-01-01

This book describes the state-of-the-art in energy efficient, fault-tolerant embedded systems. It covers the entire product lifecycle of electronic systems design, analysis and testing and includes discussion of both circuit and system-level approaches. Readers will be enabled to meet the conflicting design objectives of energy efficiency and fault-tolerance for reliability, given the up-to-date techniques presented.

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.

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.

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.

Abstractions for Fault-Tolerant Distributed System Verification

Science.gov (United States)

Pike, Lee S.; Maddalon, Jeffrey M.; Miner, Paul S.; Geser, Alfons

2004-01-01

Four kinds of abstraction for the design and analysis of fault tolerant distributed systems are discussed. These abstractions concern system messages, faults, fault masking voting, and communication. The abstractions are formalized in higher order logic, and are intended to facilitate specifying and verifying such systems in higher order theorem provers.

Software fault tolerance in computer operating systems

Science.gov (United States)

Iyer, Ravishankar K.; Lee, Inhwan

1994-01-01

This chapter provides data and analysis of the dependability and fault tolerance for three operating systems: the Tandem/GUARDIAN fault-tolerant system, the VAX/VMS distributed system, and the IBM/MVS system. Based on measurements from these systems, basic software error characteristics are investigated. Fault tolerance in operating systems resulting from the use of process pairs and recovery routines is evaluated. Two levels of models are developed to analyze error and recovery processes inside an operating system and interactions among multiple instances of an operating system running in a distributed environment. The measurements show that the use of process pairs in Tandem systems, which was originally intended for tolerating hardware faults, allows the system to tolerate about 70% of defects in system software that result in processor failures. The loose coupling between processors which results in the backup execution (the processor state and the sequence of events occurring) being different from the original execution is a major reason for the measured software fault tolerance. The IBM/MVS system fault tolerance almost doubles when recovery routines are provided, in comparison to the case in which no recovery routines are available. However, even when recovery routines are provided, there is almost a 50% chance of system failure when critical system jobs are involved.

Active fault diagnosis in closed-loop uncertain systems

DEFF Research Database (Denmark)

Niemann, Hans Henrik

2006-01-01

Fault diagnosis of parametric faults in closed-loop uncertain systems by using an auxiliary input vector is considered in this paper, i.e. active fault diagnosis (AFD). The active fault diagnosis is based directly on the socalled fault signature matrix, related to the YJBK (Youla, Jabr, Bongiorno...... and Kucera) parameterization. Conditions are given for exact detection and isolation of parametric faults in closed-loop uncertain systems....

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

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.

Active Fault Diagnosis in Sampled-data Systems

DEFF Research Database (Denmark)

Niemann, Hans Henrik; Poulsen, Niels Kjølstad

2015-01-01

The focus in this paper is on active fault diagnosis (AFD) in closed-loop sampleddata systems. Applying the same AFD architecture as for continuous-time systems does not directly result in the same set of closed-loop matrix transfer functions. For continuous-time systems, the LFT (linear fractional...... transformation) structure in the connection between the parametric faults and the matrix transfer function (also known as the fault signature matrix) applied for AFD is not directly preserved for sampled-data system. As a consequence of this, the AFD methods cannot directly be applied for sampled-data systems....... Two methods are considered in this paper to handle the fault signature matrix for sampled-data systems such that standard AFD methods can be applied. The first method is based on a discretization of the system such that the LFT structure is preserved resulting in the same LFT structure in the fault...

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

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

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

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...

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....

Fault prediction for nonlinear stochastic system with incipient faults based on particle filter and nonlinear regression.

Science.gov (United States)

Ding, Bo; Fang, Huajing

2017-05-01

This paper is concerned with the fault prediction for the nonlinear stochastic system with incipient faults. Based on the particle filter and the reasonable assumption about the incipient faults, the modified fault estimation algorithm is proposed, and the system state is estimated simultaneously. According to the modified fault estimation, an intuitive fault detection strategy is introduced. Once each of the incipient fault is detected, the parameters of which are identified by a nonlinear regression method. Then, based on the estimated parameters, the future fault signal can be predicted. Finally, the effectiveness of the proposed method is verified by the simulations of the Three-tank system. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

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...

SENSORS FAULT DIAGNOSIS ALGORITHM DESIGN OF A HYDRAULIC SYSTEM

Directory of Open Access Journals (Sweden)

Matej ORAVEC

2017-06-01

Full Text Available This article presents the sensors fault diagnosis system design for the hydraulic system, which is based on the group of the three fault estimation filters. These filters are used for estimation of the system states and sensors fault magnitude. Also, this article briefly stated the hydraulic system state control design with integrator, which is important assumption for the fault diagnosis system design. The sensors fault diagnosis system is implemented into the Matlab/Simulink environment and it is verified using the controlled hydraulic system simulation model. Verification of the designed fault diagnosis system is realized by series of experiments, which simulates sensors faults. The results of the experiments are briefly presented in the last part of this article.

Quantitative evaluation of fault coverage for digitalized systems in NPPs using simulated fault injection method

International Nuclear Information System (INIS)

Kim, Suk Joon

2004-02-01

Even though digital systems have numerous advantages such as precise processing of data, enhanced calculation capability over the conventional analog systems, there is a strong restriction on the application of digital systems to the safety systems in nuclear power plants (NPPs). This is because we do not fully understand the reliability of digital systems, and therefore we cannot guarantee the safety of digital systems. But, as the need for introduction of digital systems to safety systems in NPPs increasing, the need for the quantitative analysis on the safety of digital systems is also increasing. NPPs, which are quite conservative in terms of safety, require proving the reliability of digital systems when applied them to the NPPs. Moreover, digital systems which are applied to the NPPs are required to increase the overall safety of NPPs. however, it is very difficult to evaluate the reliability of digital systems because they include the complex fault processing mechanisms at various levels of the systems. Software is another obstacle in reliability assessment of the systems that requires ultra-high reliability. In this work, the fault detection coverage for the digital system is evaluated using simulated fault injection method. The target system is the Local Coincidence Logic (LCL) processor in Digital Plant Protection System (DPPS). However, as the LCL processor is difficult to design equally for evaluating the fault detection coverage, the LCL system has to be simplified. The simulations for evaluating the fault detection coverage of components are performed by dividing into two cases and the failure rates of components are evaluated using MIL-HDBK-217F. Using these results, the fault detection coverage of simplified LCL system is evaluated. In the experiments, heartbeat signals were just emitted at regular interval after executing logic without self-checking algorithm. When faults are injected into the simplified system, fault occurrence can be detected by

Geophysical Characterization of the Hilton Creek Fault System

Science.gov (United States)

Lacy, A. K.; Macy, K. P.; De Cristofaro, J. L.; Polet, J.

2016-12-01

The Long Valley Caldera straddles the eastern edge of the Sierra Nevada Batholith and the western edge of the Basin and Range Province, and represents one of the largest caldera complexes on Earth. The caldera is intersected by numerous fault systems, including the Hartley Springs Fault System, the Round Valley Fault System, the Long Valley Ring Fault System, and the Hilton Creek Fault System, which is our main region of interest. The Hilton Creek Fault System appears as a single NW-striking fault, dipping to the NE, from Davis Lake in the south to the southern rim of the Long Valley Caldera. Inside the caldera, it splays into numerous parallel faults that extend toward the resurgent dome. Seismicity in the area increased significantly in May 1980, following a series of large earthquakes in the vicinity of the caldera and a subsequent large earthquake swarm which has been suggested to be the result of magma migration. A large portion of the earthquake swarms in the Long Valley Caldera occurs on or around the Hilton Creek Fault splays. We are conducting an interdisciplinary geophysical study of the Hilton Creek Fault System from just south of the onset of splay faulting, to its extension into the dome of the caldera. Our investigation includes ground-based magnetic field measurements, high-resolution total station elevation profiles, Structure-From-Motion derived topography and an analysis of earthquake focal mechanisms and statistics. Preliminary analysis of topographic profiles, of approximately 1 km in length, reveals the presence of at least three distinct fault splays within the caldera with vertical offsets of 0.5 to 1.0 meters. More detailed topographic mapping is expected to highlight smaller structures. We are also generating maps of the variation in b-value along different portions of the Hilton Creek system to determine whether we can detect any transition to more swarm-like behavior towards the North. We will show maps of magnetic anomalies, topography

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)

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

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

Fault management and systems knowledge

Science.gov (United States)

2016-12-01

Pilots are asked to manage faults during flight operations. This leads to the training question of the type and depth of system knowledge required to respond to these faults. Based on discussions with multiple airline operators, there is agreement th...

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)

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...

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)

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.

Modeling and Fault Simulation of Propellant Filling System

International Nuclear Information System (INIS)

Jiang Yunchun; Liu Weidong; Hou Xiaobo

2012-01-01

Propellant filling system is one of the key ground plants in launching site of rocket that use liquid propellant. There is an urgent demand for ensuring and improving its reliability and safety, and there is no doubt that Failure Mode Effect Analysis (FMEA) is a good approach to meet it. Driven by the request to get more fault information for FMEA, and because of the high expense of propellant filling, in this paper, the working process of the propellant filling system in fault condition was studied by simulating based on AMESim. Firstly, based on analyzing its structure and function, the filling system was modular decomposed, and the mathematic models of every module were given, based on which the whole filling system was modeled in AMESim. Secondly, a general method of fault injecting into dynamic system was proposed, and as an example, two typical faults - leakage and blockage - were injected into the model of filling system, based on which one can get two fault models in AMESim. After that, fault simulation was processed and the dynamic characteristics of several key parameters were analyzed under fault conditions. The results show that the model can simulate effectively the two faults, and can be used to provide guidance for the filling system maintain and amelioration.

Observer-based Fault Detection and Isolation for Nonlinear Systems

DEFF Research Database (Denmark)

Lootsma, T.F.

With the rise in automation the increase in fault detectionand isolation & reconfiguration is inevitable. Interest in fault detection and isolation (FDI) for nonlinear systems has grown significantly in recent years. The design of FDI is motivated by the need for knowledge about occurring faults...... in fault-tolerant control systems (FTC systems). The idea of FTC systems is to detect, isolate, and handle faults in such a way that the systems can still perform in a required manner. One prefers reduced performance after occurrence of a fault to the shut down of (sub-) systems. Hence, the idea of fault......-output decoupling is described. It is a new idea based on the solution of the input-output decoupling problem. The idea is to include FDI considerations already during the control design....

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.

Observer-Based Fault Estimation and Accomodation for Dynamic Systems

CERN Document Server

Zhang, Ke; Shi, Peng

2013-01-01

Due to the increasing security and reliability demand of actual industrial process control systems, the study on fault diagnosis and fault tolerant control of dynamic systems has received considerable attention. Fault accommodation (FA) is one of effective methods that can be used to enhance system stability and reliability, so it has been widely and in-depth investigated and become a hot topic in recent years. Fault detection is used to monitor whether a fault occurs, which is the first step in FA. On the basis of fault detection, fault estimation (FE) is utilized to determine online the magnitude of the fault, which is a very important step because the additional controller is designed using the fault estimate. Compared with fault detection, the design difficulties of FE would increase a lot, so research on FE and accommodation is very challenging. Although there have been advancements reported on FE and accommodation for dynamic systems, the common methods at the present stage have design difficulties, whi...

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)

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)

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

The Morelia-Acambay Fault System

Science.gov (United States)

Velázquez Bucio, M.; Soria-Caballero, D.; Garduño-Monroy, V.; Mennella, L.

2013-05-01

The Trans-Mexican Volcanic Belt (TMVB) is one of the most actives and representative zones of Mexico geologically speaking. Research carried out in this area gives stratigraphic, seismologic and historical evidence of its recent activity during the quaternary (Martinez and Nieto, 1990). Specifically the Morelia-Acambay faults system (MAFS) consist in a series of normal faults of dominant direction E - W, ENE - WSW y NE - SW which is cut in center west of the Trans-Mexican Volcanic Belt. This fault system appeared during the early Miocene although the north-south oriented structures are older and have been related to the activity of the tectonism inherited from the "Basin and Range" system, but that were reactivated by the east- west faults. It is believed that the activity of these faults has contributed to the creation and evolution of the longed lacustrine depressions such as: Chapala, Zacapu, Cuitzeo, Maravatio y Acambay also the location of monogenetic volcanoes that conformed the Michoacan-Guanajuato volcanic field (MGVF) and tend to align in the direction of the SFMA dominant effort. In a historical time different segments of the MAFS have been the epicenter of earthquakes from moderated to strong magnitude like the events of 1858 in Patzcuaro, Acambay in 1912, 1979 in Maravatio and 2007 in Morelia, among others. Several detailed analysis and semi-detailed analysis through a GIS platform based in the vectorial archives and thematic charts 1:50 000 scaled from the data base of the INEGI which has allowed to remark the influence of the MAFS segments about the morphology of the landscape and the identification of other structures related to the movement of the existent faults like fractures, alignments, collapses and others from the zone comprehended by the northwest of Morelia in Michoacán to the East of Acambay, Estado de México. Such analysis suggests that the fault segments possess a normal displacement plus a left component. In addition it can be

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.

Smart intimation and location of faults in distribution system

Science.gov (United States)

Hari Krishna, K.; Srinivasa Rao, B.

2018-04-01

Location of faults in the distribution system is one of the most complicated problems that we are facing today. Identification of fault location and severity of fault within a short time is required to provide continuous power supply but fault identification and information transfer to the operator is the biggest challenge in the distribution network. This paper proposes a fault location method in the distribution system based on Arduino nano and GSM module with flame sensor. The main idea is to locate the fault in the distribution transformer by sensing the arc coming out from the fuse element. The biggest challenge in the distribution network is to identify the location and the severity of faults under different conditions. Well operated transmission and distribution systems will play a key role for uninterrupted power supply. Whenever fault occurs in the distribution system the time taken to locate and eliminate the fault has to be reduced. The proposed design was achieved with flame sensor and GSM module. Under faulty condition, the system will automatically send an alert message to the operator in the distribution system, about the abnormal conditions near the transformer, site code and its exact location for possible power restoration.

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.

Results of an electrical power system fault study (CDDF)

Science.gov (United States)

Dugal-Whitehead, N. R.; Johnson, Y. B.

1993-01-01

This report gives the results of an electrical power system fault study which has been conducted over the last 2 and one-half years. First, the results of the literature search into electrical power system faults in space and terrestrial power system applications are reported. A description of the intended implementations of the power system faults into the Large Autonomous Spacecraft Electrical Power System (LASEPS) breadboard is then presented. Then, the actual implementation of the faults into the breadboard is discussed along with a discussion describing the LASEPS breadboard. Finally, the results of the injected faults and breadboard failures are discussed.

Fault Detection for Shipboard Monitoring and Decision Support Systems

DEFF Research Database (Denmark)

Lajic, Zoran; Nielsen, Ulrik Dam

2009-01-01

In this paper a basic idea of a fault-tolerant monitoring and decision support system will be explained. Fault detection is an important part of the fault-tolerant design for in-service monitoring and decision support systems for ships. In the paper, a virtual example of fault detection...... will be presented for a containership with a real decision support system onboard. All possible faults can be simulated and detected using residuals and the generalized likelihood ratio (GLR) algorithm....

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

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.

Fault detection and fault-tolerant control for nonlinear systems

CERN Document Server

Li, Linlin

2016-01-01

Linlin Li addresses the analysis and design issues of observer-based FD and FTC for nonlinear systems. The author analyses the existence conditions for the nonlinear observer-based FD systems to gain a deeper insight into the construction of FD systems. Aided by the T-S fuzzy technique, she recommends different design schemes, among them the L_inf/L_2 type of FD systems. The derived FD and FTC approaches are verified by two benchmark processes. Contents Overview of FD and FTC Technology Configuration of Nonlinear Observer-Based FD Systems Design of L2 nonlinear Observer-Based FD Systems Design of Weighted Fuzzy Observer-Based FD Systems FTC Configurations for Nonlinear Systems< Application to Benchmark Processes Target Groups Researchers and students in the field of engineering with a focus on fault diagnosis and fault-tolerant control fields The Author Dr. Linlin Li completed her dissertation under the supervision of Prof. Steven X. Ding at the Faculty of Engineering, University of Duisburg-Essen, Germany...

Algorithmic acquisition of diagnostic patterns in district heating billing system

International Nuclear Information System (INIS)

Kiluk, Sebastian

2012-01-01

An application of algorithmic exploration of billing data is examined for fault detection, diagnosis (FDD) based on evaluation of present state and detection of unexpected changes in energy efficiency of buildings. Large data sets from district heating (DH) billing systems are used for construction of feature space, diagnostic rules and classification of the buildings according to their energy efficiency properties. The algorithmic approach automates discovering knowledge about common, thus accepted changes in buildings’ properties, in equipment and in habitants’ behavior reflecting progress in technology and life style. In this article implementation of Data Mining and Knowledge Discovery (DMKD) method in supervision system with exemplary results based on real data is presented. Crucial steps of data processing influencing diagnostic results are described in details.

Designing fault-tolerant real-time computer systems with diversified bus architecture for nuclear power plants

International Nuclear Information System (INIS)

Behera, Rajendra Prasad; Murali, N.; Satya Murty, S.A.V.

2014-01-01

Fault-tolerant real-time computer (FT-RTC) systems are widely used to perform safe operation of nuclear power plants (NPP) and safe shutdown in the event of any untoward situation. Design requirements for such systems need high reliability, availability, computational ability for measurement via sensors, control action via actuators, data communication and human interface via keyboard or display. All these attributes of FT-RTC systems are required to be implemented using best known methods such as redundant system design using diversified bus architecture to avoid common cause failure, fail-safe design to avoid unsafe failure and diagnostic features to validate system operation. In this context, the system designer must select efficient as well as highly reliable diversified bus architecture in order to realize fault-tolerant system design. This paper presents a comparative study between CompactPCI bus and Versa Module Eurocard (VME) bus architecture for designing FT-RTC systems with switch over logic system (SOLS) for NPP. (author)

Computer aided fault tree construction for electrical systems

International Nuclear Information System (INIS)

Fussell, J.B.

1975-01-01

A technique is presented for automated construction of the Boolean failure logic diagram, called the fault tree, for electrical systems. The method is a technique for synthesizing a fault tree from system-independent component characteristics. Terminology is defined and heuristic examples are given for all phases of the model. The computer constructed fault trees are in conventional format, use conventional symbols, and are deductively constructed from the main failure of interest to the individual component failures. The synthesis technique is generally applicable to automated fault tree construction for other types of systems

Posbist fault tree analysis of coherent systems

International Nuclear Information System (INIS)

Huang, H.-Z.; Tong Xin; Zuo, Ming J.

2004-01-01

When the failure probability of a system is extremely small or necessary statistical data from the system is scarce, it is very difficult or impossible to evaluate its reliability and safety with conventional fault tree analysis (FTA) techniques. New techniques are needed to predict and diagnose such a system's failures and evaluate its reliability and safety. In this paper, we first provide a concise overview of FTA. Then, based on the posbist reliability theory, event failure behavior is characterized in the context of possibility measures and the structure function of the posbist fault tree of a coherent system is defined. In addition, we define the AND operator and the OR operator based on the minimal cut of a posbist fault tree. Finally, a model of posbist fault tree analysis (posbist FTA) of coherent systems is presented. The use of the model for quantitative analysis is demonstrated with a real-life safety system

An expert system for turbogenerator diagnostics

International Nuclear Information System (INIS)

Bessenyei, Z.; Tomcsanyi, T.; Toth, Z.; Laczay, I.

1992-01-01

In 1990, an expert system for turbo-generator diagnostics (EST-D) was installed at the 3rd and 4th units of the Paks NPP (Hungary). The expert system is strongly integrated to the ARGUS II vibration monitoring and diagnostics system. The system works on IBM PC AT. The VEIKI's and the NPP's human experts were interviewed to fill up the knowledgebase. The system is able to identify 13 different faults of the parts of a turbogenerator. The knowledgebase consists of ca 200 rules. The rules were built in and the system was verified and validated using a model of the turbines and using the experiences gathered with ARGUS II during the last 3 years. The maintenance personnel is authorized to modify and/or extend the knowledgebase. The input data for evaluation come from measured vibration patterns produced by the ARGUS II system, database of events, and maintenance data input by the maintenance personnel. The expert system is based on the modified GENESYS 2.1 shell (developed by SZAMALK, Hungary). Some limitations from PC application were eliminated, and a new, independent explanation module and man-machine interface were developed. Using this man-machine interface, one of the basic goals of the expert system developments was achieved: the human experts contribution is not necessary for diagnoses. The operator of the diagnostics system is able to produce the reports of diagnoses. Of course the interface allows the human experts to see the diagnoses through. It should be mentioned, at the beginning of 1991, we installed a similar expert system at the 1st 1000 MW WWER type unit of the Kalinin NPP (Soviet Union). In this paper, the operation of the EST-D, the man-machine interface and the operational experiences of the first 4 months work are explained. 2 refs., 14 figs

H infinity Integrated Fault Estimation and Fault Tolerant Control of Discrete-time Piecewise Linear Systems

DEFF Research Database (Denmark)

Tabatabaeipour, Seyed Mojtaba; Bak, Thomas

2012-01-01

In this paper we consider the problem of fault estimation and accommodation for discrete time piecewise linear systems. A robust fault estimator is designed to estimate the fault such that the estimation error converges to zero and H∞ performance of the fault estimation is minimized. Then, the es...

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...

Handbook of technical diagnostics fundamentals and application to structures and systems

CERN Document Server

2013-01-01

This book presents concepts, methods and techniques to examine symptoms of faults and failures of structures, systems and components and to monitor functional performance and structural integrity. The book is organized in five parts. Part A introduces the scope and application of technical diagnostics and gives a comprehensive overview of the physics of failure. Part B presents all relevant methods and techniques for diagnostics and monitoring: from stress, strain, vibration analysis, nondestructive evaluation, thermography and industrial radiology to computed tomography and subsurface microstructural analysis. Part C cores the principles and concepts of technical failure analysis, illustrates case studies, and outlines machinery diagnostics with an emphasis on tribological systems. Part D describes the application of structural health monitoring and performance control to plants and the technical infrastructure, including buildings, bridges, pipelines, electric power stations, offshore wind structures, and r...

Passive Fault-tolerant Control of Discrete-time Piecewise Affine Systems against Actuator Faults

DEFF Research Database (Denmark)

Tabatabaeipour, Seyed Mojtaba; Izadi-Zamanabadi, Roozbeh; Bak, Thomas

2012-01-01

In this paper, we propose a new method for passive fault-tolerant control of discrete time piecewise affine systems. Actuator faults are considered. A reliable piecewise linear quadratic regulator (LQR) state feedback is designed such that it can tolerate actuator faults. A sufficient condition f...... is illustrated on a numerical example and a two degree of freedom helicopter....

The Trans-Rocky Mountain Fault System - A Fundamental Precambrian Strike-Slip System

Science.gov (United States)

Sims, P.K.

2009-01-01

Recognition of a major Precambrian continental-scale, two-stage conjugate strike-slip fault system - here designated as the Trans-Rocky Mountain fault system - provides new insights into the architecture of the North American continent. The fault system consists chiefly of steep linear to curvilinear, en echelon, braided and branching ductile-brittle shears and faults, and local coeval en echelon folds of northwest strike, that cut indiscriminately across both Proterozoic and Archean cratonic elements. The fault system formed during late stages of two distinct tectonic episodes: Neoarchean and Paleoproterozoic orogenies at about 2.70 and 1.70 billion years (Ga). In the Archean Superior province, the fault system formed (about 2.70-2.65 Ga) during a late stage of the main deformation that involved oblique shortening (dextral transpression) across the region and progressed from crystal-plastic to ductile-brittle deformation. In Paleoproterozoic terranes, the fault system formed about 1.70 Ga, shortly following amalgamation of Paleoproterozoic and Archean terranes and the main Paleoproterozoic plastic-fabric-producing events in the protocontinent, chiefly during sinistral transpression. The postulated driving force for the fault system is subcontinental mantle deformation, the bottom-driven deformation of previous investigators. This model, based on seismic anisotropy, invokes mechanical coupling and subsequent shear between the lithosphere and the asthenosphere such that a major driving force for plate motion is deep-mantle flow.

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.

EKF-based fault detection for guided missiles flight control system

Science.gov (United States)

Feng, Gang; Yang, Zhiyong; Liu, Yongjin

2017-03-01

The guided missiles flight control system is essential for guidance accuracy and kill probability. It is complicated and fragile. Since actuator faults and sensor faults could seriously affect the security and reliability of the system, fault detection for missiles flight control system is of great significance. This paper deals with the problem of fault detection for the closed-loop nonlinear model of the guided missiles flight control system in the presence of disturbance. First, set up the fault model of flight control system, and then design the residual generation based on the extended Kalman filter (EKF) for the Eulerian-discrete fault model. After that, the Chi-square test was selected for the residual evaluation and the fault detention task for guided missiles closed-loop system was accomplished. Finally, simulation results are provided to illustrate the effectiveness of the approach proposed in the case of elevator fault separately.

Bond graph model-based fault diagnosis of hybrid systems

CERN Document Server

Borutzky, Wolfgang

2015-01-01

This book presents a bond graph model-based approach to fault diagnosis in mechatronic systems appropriately represented by a hybrid model. The book begins by giving a survey of the fundamentals of fault diagnosis and failure prognosis, then recalls state-of-art developments referring to latest publications, and goes on to discuss various bond graph representations of hybrid system models, equations formulation for switched systems, and simulation of their dynamic behavior. The structured text: • focuses on bond graph model-based fault detection and isolation in hybrid systems; • addresses isolation of multiple parametric faults in hybrid systems; • considers system mode identification; • provides a number of elaborated case studies that consider fault scenarios for switched power electronic systems commonly used in a variety of applications; and • indicates that bond graph modelling can also be used for failure prognosis. In order to facilitate the understanding of fault diagnosis and the presented...

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.

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.

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.

Faults and Diagnosis Systems in Power Converters

DEFF Research Database (Denmark)

Lee, Kyo-Beum; Choi, Uimin

2014-01-01

A power converter is needed in almost all kinds of renewable energy systems and drive systems. It is used both for controlling the renewable source and for interfacing with the load, which can be grid-connected or working in standalone mode. Further, it drives the motors efficiently. Increasing...... efforts have been put into making these systems better in terms of reliability in order to achieve high power source availability, reduce the cost of energy and also increase the reliability of overall systems. Among the components used in power converters, a power device and a capacitor fault occurs most...... frequently. Therefore, it is important to monitor the power device and capacitor fault to increase the reliability of power electronics. In this chapter, the diagnosis methods for power device fault will be discussed by dividing into open- and short-circuit faults. Then, the condition monitoring methods...

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.

Fault tolerant controllers for sampled-data systems

DEFF Research Database (Denmark)

Niemann, Hans Henrik; Stoustrup, Jakob

2004-01-01

A general compensator architecture for fault tolerant control (FTC) for sampled-data systems is proposed. The architecture is based on the YJBK parameterization of all stabilizing controllers, and uses the dual YJBK parameterization to quantify the performance of the fault tolerant system. The FTC...

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.

Statistical fault detection in photovoltaic systems

KAUST Repository

Garoudja, Elyes; Harrou, Fouzi; Sun, Ying; Kara, Kamel; Chouder, Aissa; Silvestre, Santiago

2017-01-01

and efficiency. Here, an innovative model-based fault-detection approach for early detection of shading of PV modules and faults on the direct current (DC) side of PV systems is proposed. This approach combines the flexibility, and simplicity of a one-diode model

System control module diagnostic Expert Assistant

Science.gov (United States)

Flores, Luis M.; Hansen, Roger F.

1990-01-01

The Orbiter EXperiments (OEX) Program was established by NASA's Office of Aeronautics and Space Technology (OAST) to accomplish the precise data collection necessary to support a complete and accurate assessment of Space Transportation System (STS) Orbiter performance during all phases of a mission. During a mission, data generated by the various experiments are conveyed to the OEX System Control Module (SCM) which arranges for and monitors storage of the data on the OEX tape recorder. The SCM Diagnostic Expert Assistant (DEA) is an expert system which provides on demand advice to technicians performing repairs of a malfunctioning SCM. The DEA is a self-contained, data-driven knowledge-based system written in the 'C' Language Production System (CLIPS) for a portable micro-computer of the IBM PC/XT class. The DEA reasons about SCM hardware faults at multiple levels; the most detailed layer of encoded knowledge of the SCM is a representation of individual components and layouts of the custom-designed component boards.

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

Comparing Different Fault Identification Algorithms in Distributed Power System

Science.gov (United States)

Alkaabi, Salim

A power system is a huge complex system that delivers the electrical power from the generation units to the consumers. As the demand for electrical power increases, distributed power generation was introduced to the power system. Faults may occur in the power system at any time in different locations. These faults cause a huge damage to the system as they might lead to full failure of the power system. Using distributed generation in the power system made it even harder to identify the location of the faults in the system. The main objective of this work is to test the different fault location identification algorithms while tested on a power system with the different amount of power injected using distributed generators. As faults may lead the system to full failure, this is an important area for research. In this thesis different fault location identification algorithms have been tested and compared while the different amount of power is injected from distributed generators. The algorithms were tested on IEEE 34 node test feeder using MATLAB and the results were compared to find when these algorithms might fail and the reliability of these methods.

Distributed Fault Detection for a Class of Nonlinear Stochastic Systems

Directory of Open Access Journals (Sweden)

Bingyong Yan

2014-01-01

Full Text Available A novel distributed fault detection strategy for a class of nonlinear stochastic systems is presented. Different from the existing design procedures for fault detection, a novel fault detection observer, which consists of a nonlinear fault detection filter and a consensus filter, is proposed to detect the nonlinear stochastic systems faults. Firstly, the outputs of the nonlinear stochastic systems act as inputs of a consensus filter. Secondly, a nonlinear fault detection filter is constructed to provide estimation of unmeasurable system states and residual signals using outputs of the consensus filter. Stability analysis of the consensus filter is rigorously investigated. Meanwhile, the design procedures of the nonlinear fault detection filter are given in terms of linear matrix inequalities (LMIs. Taking the influence of the system stochastic noises into consideration, an outstanding feature of the proposed scheme is that false alarms can be reduced dramatically. Finally, simulation results are provided to show the feasibility and effectiveness of the proposed fault detection approach.

Chaos Synchronization Based Novel Real-Time Intelligent Fault Diagnosis for Photovoltaic Systems

Directory of Open Access Journals (Sweden)

Chin-Tsung Hsieh

2014-01-01

Full Text Available The traditional solar photovoltaic fault diagnosis system needs two to three sets of sensing elements to capture fault signals as fault features and many fault diagnosis methods cannot be applied with real time. The fault diagnosis method proposed in this study needs only one set of sensing elements to intercept the fault features of the system, which can be real-time-diagnosed by creating the fault data of only one set of sensors. The aforesaid two points reduce the cost and fault diagnosis time. It can improve the construction of the huge database. This study used Matlab to simulate the faults in the solar photovoltaic system. The maximum power point tracker (MPPT is used to keep a stable power supply to the system when the system has faults. The characteristic signal of system fault voltage is captured and recorded, and the dynamic error of the fault voltage signal is extracted by chaos synchronization. Then, the extension engineering is used to implement the fault diagnosis. Finally, the overall fault diagnosis system only needs to capture the voltage signal of the solar photovoltaic system, and the fault type can be diagnosed instantly.

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)

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.

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.

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

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

Fault Analysis of ITER Coil Power Supply System

International Nuclear Information System (INIS)

Song, In Ho; Jun, Tao; Benfatto, Ivone

2009-01-01

The ITER magnet coils are all designed using superconductors with high current carrying capability. The Toroidal Field (TF) coils operate in a steadystate mode with a current of 68 kA and discharge the stored energy in case of quench with using 9 interleaved Fast Discharge Units (FDUs). The Central Solenoid (CS) coils and Poloidal Field (PF) coils operate in a pulse mode with currents of up to 45 kA and require fast variation of currents inducing more than 10 kV during normal operation on the coil terminals using Switching Network (SN) systems (CSs, PF1 and 6) and Booster and VS converters (PF2 to 5), which are series connected to Main converters. SN and FDU systems comprise high current DC circuit breakers and resistors for generating high voltage (SN) and to dissipate magnetic energy (FDUs). High transient voltages can arise due to the switching operation of SN and FD and the characteristics of resistors and stray components of DC distribution systems. Also, faults in power supply control such as shorts or grounding faults can produce higher voltages between terminals and between terminal and ground. Therefore, the design of the coil insulation, coil terminal regions, feeders, feed throughs, pipe breaks and instrumentation must take account of these high voltages during normal and abnormal conditions. Voltage insulation level can be defined and it is necessary to test the coils at higher voltages, to be sure of reliable performance during the lifetime of operation. This paper describes the fault analysis of the TF, CS and PF coil power supply systems, taking account of the stray parameter of the power supply and switching systems and inductively coupled superconducting coil models. Resistor grounding systems are included in the simulation model and all fault conditions such as converter hardware and software faults, switching system hardware and software faults, DC short circuits and single grounding faults are simulated. The occurrence of two successive faults

Fault tolerance of the NIF power conditioning system

International Nuclear Information System (INIS)

Larson, D.W.; Anderson, R.; Boyes, J.

1995-01-01

The tolerance of the circuit topology proposed for the National Ignition Facility (NIF) power conditioning system to specific fault conditions is investigated. A new pulsed power circuit is proposed for the NIF which is simpler and less expensive than previous ICF systems. The inherent fault modes of the new circuit are different from the conventional approach, and must be understood to ensure adequate NIF system reliability. A test-bed which simulates the NIF capacitor module design was constructed to study the circuit design. Measurements from test-bed experiments with induced faults are compared with results from a detailed circuit model. The model is validated by the measurements and used to predict the behavior of the actual NIF module during faults. The model can be used to optimize fault tolerance of the NIF module through an appropriate distribution of circuit inductance and resistance. The experimental and modeling results are presented, and fault performance is compared with the ratings of pulsed power components. Areas are identified which require additional investigation

Machinery Fault Diagnosis Using Two-Channel Analysis Method Based on Fictitious System Frequency Response Function

Directory of Open Access Journals (Sweden)

Kihong Shin

2015-01-01

Full Text Available Most existing techniques for machinery health monitoring that utilize measured vibration signals usually require measurement points to be as close as possible to the expected fault components of interest. This is particularly important for implementing condition-based maintenance since the incipient fault signal power may be too small to be detected if a sensor is located further away from the fault source. However, a measurement sensor is often not attached to the ideal point due to geometric or environmental restrictions. In such a case, many of the conventional diagnostic techniques may not be successfully applicable. In this paper, a two-channel analysis method is proposed to overcome such difficulty. It uses two vibration signals simultaneously measured at arbitrary points in a machine. The proposed method is described theoretically by introducing a fictitious system frequency response function. It is then verified experimentally for bearing fault detection. The results show that the suggested method may be a good alternative when ideal points for measurement sensors are not readily available.

Fault-tolerant Actuator System for Electrical Steering of Vehicles

DEFF Research Database (Denmark)

Sørensen, Jesper Sandberg; Blanke, Mogens

2006-01-01

is needed that meets this requirement. This paper studies the fault-tolerance properties of an electrical steering system. It presents a fault-tolerant architecture where a dedicated AC motor design used in conjunction with cheap voltage measurements can ensure detection of all relevant faults......Being critical to the safety of vehicles, the steering system is required to maintain the vehicles ability to steer until it is brought to halt, should a fault occur. With electrical steering becoming a cost-effective candidate for electrical powered vehicles, a fault-tolerant architecture...

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....

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

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.

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

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 ～ ...

Identifying Conventionally Sub-Seismic Faults in Polygonal Fault Systems

Science.gov (United States)

Fry, C.; Dix, J.

2017-12-01

Polygonal Fault Systems (PFS) are prevalent in hydrocarbon basins globally and represent potential fluid pathways. However the characterization of these pathways is subject to the limitations of conventional 3D seismic imaging; only capable of resolving features on a decametre scale horizontally and metres scale vertically. While outcrop and core examples can identify smaller features, they are limited by the extent of the exposures. The disparity between these scales can allow for smaller faults to be lost in a resolution gap which could mean potential pathways are left unseen. Here the focus is upon PFS from within the London Clay, a common bedrock that is tunnelled into and bears construction foundations for much of London. It is a continuation of the Ieper Clay where PFS were first identified and is found to approach the seafloor within the Outer Thames Estuary. This allows for the direct analysis of PFS surface expressions, via the use of high resolution 1m bathymetric imaging in combination with high resolution seismic imaging. Through use of these datasets surface expressions of over 1500 faults within the London Clay have been identified, with the smallest fault measuring 12m and the largest at 612m in length. The displacements over these faults established from both bathymetric and seismic imaging ranges from 30cm to a couple of metres, scales that would typically be sub-seismic for conventional basin seismic imaging. The orientations and dimensions of the faults within this network have been directly compared to 3D seismic data of the Ieper Clay from the offshore Dutch sector where it exists approximately 1km below the seafloor. These have typical PFS attributes with lengths of hundreds of metres to kilometres and throws of tens of metres, a magnitude larger than those identified in the Outer Thames Estuary. The similar orientations and polygonal patterns within both locations indicates that the smaller faults exist within typical PFS structure but are

Algorithmic fault tree construction by component-based system modeling

International Nuclear Information System (INIS)

Majdara, Aref; Wakabayashi, Toshio

2008-01-01

Computer-aided fault tree generation can be easier, faster and less vulnerable to errors than the conventional manual fault tree construction. In this paper, a new approach for algorithmic fault tree generation is presented. The method mainly consists of a component-based system modeling procedure an a trace-back algorithm for fault tree synthesis. Components, as the building blocks of systems, are modeled using function tables and state transition tables. The proposed method can be used for a wide range of systems with various kinds of components, if an inclusive component database is developed. (author)

Decentralized diagnostics based on a distributed micro-genetic algorithm for transducer networks monitoring large experimental systems.

Science.gov (United States)

Arpaia, P; Cimmino, P; Girone, M; La Commara, G; Maisto, D; Manna, C; Pezzetti, M

2014-09-01

Evolutionary approach to centralized multiple-faults diagnostics is extended to distributed transducer networks monitoring large experimental systems. Given a set of anomalies detected by the transducers, each instance of the multiple-fault problem is formulated as several parallel communicating sub-tasks running on different transducers, and thus solved one-by-one on spatially separated parallel processes. A micro-genetic algorithm merges evaluation time efficiency, arising from a small-size population distributed on parallel-synchronized processors, with the effectiveness of centralized evolutionary techniques due to optimal mix of exploitation and exploration. In this way, holistic view and effectiveness advantages of evolutionary global diagnostics are combined with reliability and efficiency benefits of distributed parallel architectures. The proposed approach was validated both (i) by simulation at CERN, on a case study of a cold box for enhancing the cryogeny diagnostics of the Large Hadron Collider, and (ii) by experiments, under the framework of the industrial research project MONDIEVOB (Building Remote Monitoring and Evolutionary Diagnostics), co-funded by EU and the company Del Bo srl, Napoli, Italy.

Transient fault tolerant control for vehicle brake-by-wire systems

International Nuclear Information System (INIS)

Huang, Shuang; Zhou, Chunjie; Yang, Lili; Qin, Yuanqing; Huang, Xiongfeng; Hu, Bowen

2016-01-01

Brake-by-wire (BBW) systems that have no mechanical linkage between the brake pedal and the brake mechanism are expected to improve vehicle safety through better braking capability. However, transient faults in BBW systems can cause dangerous driving situations. Most existing research in this area focuses on the brake control mechanism, but very few studies try to solve the problem associated with transient fault propagation and evolution in the brake control system hierarchy. In this paper, a hierarchical transient fault tolerant scheme with embedded intelligence and resilient coordination for BBW system is proposed based on the analysis of transient fault propagation characteristics. In this scheme, most transient faults are tackled rapidly by a signature-based detection method at the node level, and the remaining transient faults, which cannot be detected directly at the node level and could degrade the system performance through fault propagation and evolution, are detected and recovered through function and structure models at the system level. To jointly accommodate these BBW transient faults at the system level, a sliding mode control algorithm and a task reallocation strategy are designed. A simulation platform based on Architecture Analysis and Design Language (AADL) is established to evaluate the task reallocation strategy, and a hardware-in-the-loop simulation is carried out to validate the proposed scheme systematically. Experimental results show the effectiveness of this new approach to BBW systems. - Highlights: • We propose a hierarchical transient fault tolerant scheme for BBW systems. • A sliding mode algorithm and a task strategy are designed to tackle transient fault. • The effectiveness of the scheme is verified in both simulation and HIL environments.

Fault diagnosis for dynamic power system

International Nuclear Information System (INIS)

Thabet, A.; Abdelkrim, M.N.; Boutayeb, M.; Didier, G.; Chniba, S.

2011-01-01

The fault diagnosis problem for dynamic power systems is treated, the nonlinear dynamic model based on a differential algebraic equations is transformed with reduced index to a simple dynamic model. Two nonlinear observers are used for generating the fault signals for comparison purposes, one of them being an extended Kalman estimator and the other a new extended kalman filter with moving horizon with a study of convergence based on the choice of matrix of covariance of the noises of system and measurements. The paper illustrates a simulation study applied on IEEE 3 buses test system.

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

Event-Triggered Fault Detection of Nonlinear Networked Systems.

Science.gov (United States)

Li, Hongyi; Chen, Ziran; Wu, Ligang; Lam, Hak-Keung; Du, Haiping

2017-04-01

This paper investigates the problem of fault detection for nonlinear discrete-time networked systems under an event-triggered scheme. A polynomial fuzzy fault detection filter is designed to generate a residual signal and detect faults in the system. A novel polynomial event-triggered scheme is proposed to determine the transmission of the signal. A fault detection filter is designed to guarantee that the residual system is asymptotically stable and satisfies the desired performance. Polynomial approximated membership functions obtained by Taylor series are employed for filtering analysis. Furthermore, sufficient conditions are represented in terms of sum of squares (SOSs) and can be solved by SOS tools in MATLAB environment. A numerical example is provided to demonstrate the effectiveness of the proposed results.

Mesoscopic Structural Observations of Cores from the Chelungpu Fault System, Taiwan Chelungpu-Fault Drilling Project Hole-A, Taiwan

Directory of Open Access Journals (Sweden)

Hiroki Sone

2007-01-01

Full Text Available Structural characteristics of fault rocks distributed within major fault zones provide basic information in understanding the physical aspects of faulting. Mesoscopic structural observations of the drilledcores from Taiwan Chelungpu-fault Drilling Project Hole-A are reported in this article to describe and reveal the distribution of fault rocks within the Chelungpu Fault System.

Fault detection in finite frequency domain for Takagi-Sugeno fuzzy systems with sensor faults.

Science.gov (United States)

Li, Xiao-Jian; Yang, Guang-Hong

2014-08-01

This paper is concerned with the fault detection (FD) problem in finite frequency domain for continuous-time Takagi-Sugeno fuzzy systems with sensor faults. Some finite-frequency performance indices are initially introduced to measure the fault/reference input sensitivity and disturbance robustness. Based on these performance indices, an effective FD scheme is then presented such that the generated residual is designed to be sensitive to both fault and reference input for faulty cases, while robust against the reference input for fault-free case. As the additional reference input sensitivity for faulty cases is considered, it is shown that the proposed method improves the existing FD techniques and achieves a better FD performance. The theory is supported by simulation results related to the detection of sensor faults in a tunnel-diode circuit.

Fault detection for discrete-time switched systems with sensor stuck faults and servo inputs.

Science.gov (United States)

Zhong, Guang-Xin; Yang, Guang-Hong

2015-09-01

This paper addresses the fault detection problem of switched systems with servo inputs and sensor stuck faults. The attention is focused on designing a switching law and its associated fault detection filters (FDFs). The proposed switching law uses only the current states of FDFs, which guarantees the residuals are sensitive to the servo inputs with known frequency ranges in faulty cases and robust against them in fault-free case. Thus, the arbitrarily small sensor stuck faults, including outage faults can be detected in finite-frequency domain. The levels of sensitivity and robustness are measured in terms of the finite-frequency H- index and l2-gain. Finally, the switching law and FDFs are obtained by the solution of a convex optimization problem. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

Reconfigurability of Piecewise Affine Systems Against Actuator Faults

DEFF Research Database (Denmark)

Tabatabaeipour, Seyed Mojtaba; Gholami, Mehdi; Bak, Thomas

2011-01-01

In this paper, we consider the problem of recongurability of peicewise ane (PWA) systems. Actuator faults are considered. A system subject to a fault is considered as recongurable if it can be stabilized by a state feedback controller and the optimal cost of the performance of the systems...

Expert systems for real-time monitoring and fault diagnosis

Science.gov (United States)

Edwards, S. J.; Caglayan, A. K.

1989-01-01

Methods for building real-time onboard expert systems were investigated, and the use of expert systems technology was demonstrated in improving the performance of current real-time onboard monitoring and fault diagnosis applications. The potential applications of the proposed research include an expert system environment allowing the integration of expert systems into conventional time-critical application solutions, a grammar for describing the discrete event behavior of monitoring and fault diagnosis systems, and their applications to new real-time hardware fault diagnosis and monitoring systems for aircraft.

Robust Parametric Fault Estimation in a Hopper System

DEFF Research Database (Denmark)

Soltani, Mohsen; Izadi-Zamanabadi, Roozbeh; Wisniewski, Rafal

2012-01-01

The ability of diagnosis of the possible faults is a necessity for satellite launch vehicles during their mission. In this paper, a structural analysis method is employed to divide the complex propulsion system into simpler subsystems for fault diagnosis filter design. A robust fault diagnosis me...

A master system for power system fault phenomena

Energy Technology Data Exchange (ETDEWEB)

Yoo, Myung Ho; Jang, Sang Ho; Hong, Joon Hee; Min, Wan Ki; Yoo, Chang Hwan [Korea Electric Power Corp. (KEPCO), Taejon (Korea, Republic of). Research Center

1995-12-31

This report includes as follows - Real time digital simulator - Remote measuring, analyzing and reproducing system of power system fault data -Power system reduction method program using EMTP -Test system for protection device. (author). 22 refs., 38 figs.

Communication-based fault handling scheme for ungrounded distribution systems

International Nuclear Information System (INIS)

Yang, X.; Lim, S.I.; Lee, S.J.; Choi, M.S.

2006-01-01

The requirement for high quality and highly reliable power supplies has been increasing as a result of increasing demand for power. At the time of a fault occurrence in a distribution system, some protection method would be dedicated to fault section isolation and service restoration. However, if there are many outage areas when the protection method is performed, it is an inconvenience to the customer. A conventional method to determine a fault section in ungrounded systems requires many successive outage invocations. This paper proposed an efficient fault section isolation method and service restoration method for single line-to-ground fault in an ungrounded distribution system that was faster than the conventional one using the information exchange between connected feeders. The proposed algorithm could be performed without any power supply interruption and could decrease the number of switching operations, so that customers would not experience outages very frequently. The method involved the use of an intelligent communication method and a sequential switching control scheme. The proposed algorithm was also applied in both a single-tie and multi-tie distribution system. This proposed algorithm has been verified through fault simulations in a simple model of ungrounded multi-tie distribution system. The method proposed in this paper was proven to offer more efficient fault identification and much less outage time than the conventional method. The proposed method could contribute to a system design since it is valid in multi-tie systems. 5 refs., 2 tabs., 8 figs

Transient pattern analysis for fault detection and diagnosis of HVAC systems

International Nuclear Information System (INIS)

Cho, Sung-Hwan; Yang, Hoon-Cheol; Zaheer-uddin, M.; Ahn, Byung-Cheon

2005-01-01

Modern building HVAC systems are complex and consist of a large number of interconnected sub-systems and components. In the event of a fault, it becomes very difficult for the operator to locate and isolate the faulty component in such large systems using conventional fault detection methods. In this study, transient pattern analysis is explored as a tool for fault detection and diagnosis of an HVAC system. Several tests involving different fault replications were conducted in an environmental chamber test facility. The results show that the evolution of fault residuals forms clear and distinct patterns that can be used to isolate faults. It was found that the time needed to reach steady state for a typical building HVAC system is at least 50-60 min. This means incorrect diagnosis of faults can happen during online monitoring if the transient pattern responses are not considered in the fault detection and diagnosis analysis

Method and system for environmentally adaptive fault tolerant computing

Science.gov (United States)

Copenhaver, Jason L. (Inventor); Jeremy, Ramos (Inventor); Wolfe, Jeffrey M. (Inventor); Brenner, Dean (Inventor)

2010-01-01

A method and system for adapting fault tolerant computing. The method includes the steps of measuring an environmental condition representative of an environment. An on-board processing system's sensitivity to the measured environmental condition is measured. It is determined whether to reconfigure a fault tolerance of the on-board processing system based in part on the measured environmental condition. The fault tolerance of the on-board processing system may be reconfigured based in part on the measured environmental condition.

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.

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.

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.

Fault Ride Through Capability Enhancement of a Large-Scale PMSG Wind System with Bridge Type Fault Current Limiters

Directory of Open Access Journals (Sweden)

ALAM, M. S.

2018-02-01

Full Text Available In this paper, bridge type fault current limiter (BFCL is proposed as a potential solution to the fault problems of permanent magnet synchronous generator (PMSG based large-scale wind energy system. As PMSG wind system is more vulnerable to disturbances, it is essential to guarantee the stability during severe disturbances by enhancing the fault ride through capability. BFCL controller has been designed to insert resistance and inductance during the inception of system disturbances in order to limit fault current. Constant capacitor voltage has been maintained by the grid voltage source converter (GVSC controller while current extraction or injection has been achieved by machine VSC (MVSC controller. Symmetrical and unsymmetrical faults have been applied in the system to show the effectiveness of the proposed BFCL solution. PMSG wind system, BFCL and their controllers have been implemented by real time hardware in loop (RTHIL setup with real time digital simulator (RTDS and dSPACE. Another significant feature of this work is that the performance of the proposed BFCL is compared with that of series dynamic braking resistor (SDBR. Comparative RTHIL implementation results show that the proposed BFCL is very efficient in improving system fault ride through capability by limiting the fault current and outperforms SDBR.

Meteoric water in normal fault systems: Oxygen and hydrogen isotopic measurements on authigenic phases in brittle fault rocks

Science.gov (United States)

Haines, S. H.; Anderson, R.; Mulch, A.; Solum, J. G.; Valley, J. W.; van der Pluijm, B. A.

2009-12-01

The nature of fluid circulation systems in normal fault systems is fundamental to understanding the nature of fluid movement within the upper crust, and has important implications for the on-going controversy about the strength of faults. Authigenic phases in clay gouges and fault breccias record the isotopic signature of the fluids they formed in equilibrium with, and can be used to understand the ‘plumbing system’ of brittle fault environments. We obtained paired oxygen and hydrogen isotopic measurements on authigenic illite and/or smectite in clay gouge from normal faults in two geologic environments, 1.) low-angle normal faults (Ruby Mountains detachment, NV; Badwater Turtleback, CA; Panamint range-front detachment; CA; Amargosa detachment; CA; Waterman Hills detachment, CA), and 2.) An intracratonic high-angle normal fault (Moab Fault, UT). All authigenic phases in these clay gouges are moderately light isotopically with respect to oxygen (illite δ18O -2.0 - + 11.5 ‰ SMOW, smectite δ18O +3.6 and 17.9 ‰) and very light isotopically with respect to hydrogen (illite δD -148 to -98 ‰ SMOW, smectite δD -147 to -92 ‰). Fluid compositions calculated from the authigenic clays at temperatures of 50 - 130 ○C (as indicated by clay mineralogy) indicate that both illite and smectite in normal fault clay gouge formed in the presence of near-pristine to moderately-evolved meteoric fluids and that igneous or metamorphic fluids are not involved in clay gouge formation in these normal fault settings. We also obtained paired oxygen and hydrogen isotopic measurements on chlorites derived from footwall chlorite breccias in 4 low-angle normal fault detachment systems (Badwater and Mormon Point Turtlebacks, CA, the Chemehuevi detachment, CA, and the Buckskin-Rawhide detachment, AZ). All chlorites are isotopically light to moderately light with respect to oxygen (δ18O +0.29 to +8.1 ‰ SMOW) and very light with respect to hydrogen (δD -97 to -113 ‰) and indicate

Model-based fault detection algorithm for photovoltaic system monitoring

KAUST Repository

Harrou, Fouzi

2018-02-12

Reliable detection of faults in PV systems plays an important role in improving their reliability, productivity, and safety. This paper addresses the detection of faults in the direct current (DC) side of photovoltaic (PV) systems using a statistical approach. Specifically, a simulation model that mimics the theoretical performances of the inspected PV system is designed. Residuals, which are the difference between the measured and estimated output data, are used as a fault indicator. Indeed, residuals are used as the input for the Multivariate CUmulative SUM (MCUSUM) algorithm to detect potential faults. We evaluated the proposed method by using data from an actual 20 MWp grid-connected PV system located in the province of Adrar, Algeria.

Fault Correspondence Analysis in Complex Electric Power Systems

Directory of Open Access Journals (Sweden)

WANG, C.

2015-02-01

Full Text Available Wide area measurement system (WAMS mainly serves for the requirement of time synchronization in complex electric power systems. The analysis and control of power system mostly depends on the measurement of state variables, and WAMS provides the basis for dynamic monitoring of power system by these measurements, which can also satisfy the demands of observable, controllable, real-time analysis and decision, self-adaptive etc. requested by smart grid. In this paper, based on the principles of fault correspondence analysis, by calculating row characteristic which represents nodal electrical information and column characteristic which represents acquisition time information, we will conduct intensive research on fault detection. The research results indicate that the fault location is determined by the first dimensional variable, and the occurrence time of fault is determined by the second dimensional variable. The research in this paper will contribute to the development of future smart grid.

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.

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.

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.

Energy-efficient fault tolerance in multiprocessor real-time systems

Science.gov (United States)

Guo, Yifeng

The recent progress in the multiprocessor/multicore systems has important implications for real-time system design and operation. From vehicle navigation to space applications as well as industrial control systems, the trend is to deploy multiple processors in real-time systems: systems with 4 -- 8 processors are common, and it is expected that many-core systems with dozens of processing cores will be available in near future. For such systems, in addition to general temporal requirement common for all real-time systems, two additional operational objectives are seen as critical: energy efficiency and fault tolerance. An intriguing dimension of the problem is that energy efficiency and fault tolerance are typically conflicting objectives, due to the fact that tolerating faults (e.g., permanent/transient) often requires extra resources with high energy consumption potential. In this dissertation, various techniques for energy-efficient fault tolerance in multiprocessor real-time systems have been investigated. First, the Reliability-Aware Power Management (RAPM) framework, which can preserve the system reliability with respect to transient faults when Dynamic Voltage Scaling (DVS) is applied for energy savings, is extended to support parallel real-time applications with precedence constraints. Next, the traditional Standby-Sparing (SS) technique for dual processor systems, which takes both transient and permanent faults into consideration while saving energy, is generalized to support multiprocessor systems with arbitrary number of identical processors. Observing the inefficient usage of slack time in the SS technique, a Preference-Oriented Scheduling Framework is designed to address the problem where tasks are given preferences for being executed as soon as possible (ASAP) or as late as possible (ALAP). A preference-oriented earliest deadline (POED) scheduler is proposed and its application in multiprocessor systems for energy-efficient fault tolerance is

Orion GN&C Fault Management System Verification: Scope And Methodology

Science.gov (United States)

Brown, Denise; Weiler, David; Flanary, Ronald

2016-01-01

In order to ensure long-term ability to meet mission goals and to provide for the safety of the public, ground personnel, and any crew members, nearly all spacecraft include a fault management (FM) system. For a manned vehicle such as Orion, the safety of the crew is of paramount importance. The goal of the Orion Guidance, Navigation and Control (GN&C) fault management system is to detect, isolate, and respond to faults before they can result in harm to the human crew or loss of the spacecraft. Verification of fault management/fault protection capability is challenging due to the large number of possible faults in a complex spacecraft, the inherent unpredictability of faults, the complexity of interactions among the various spacecraft components, and the inability to easily quantify human reactions to failure scenarios. The Orion GN&C Fault Detection, Isolation, and Recovery (FDIR) team has developed a methodology for bounding the scope of FM system verification while ensuring sufficient coverage of the failure space and providing high confidence that the fault management system meets all safety requirements. The methodology utilizes a swarm search algorithm to identify failure cases that can result in catastrophic loss of the crew or the vehicle and rare event sequential Monte Carlo to verify safety and FDIR performance requirements.

On fault propagation in deterioration of multi-component systems

International Nuclear Information System (INIS)

Liang, Zhenglin; Parlikad, Ajith Kumar; Srinivasan, Rengarajan; Rasmekomen, Nipat

2017-01-01

In extant literature, deterioration dependence among components can be modelled as inherent dependence and induced dependence. We find that the two types of dependence may co-exist and interact with each other in one multi-component system. We refer to this phenomenon as fault propagation. In practice, a fault induced by the malfunction of a non-critical component may further propagate through the dependence amongst critical components. Such fault propagation scenario happens in industrial assets or systems (bridge deck, and heat exchanging system). In this paper, a multi-layered vector-valued continuous-time Markov chain is developed to capture the characteristics of fault propagation. To obtain the mathematical tractability, we derive a partitioning rule to aggregate states with the same characteristics while keeping the overall aging behaviour of the multi-component system. Although the detailed information of components is masked by aggregated states, lumpability is attainable with the partitioning rule. It means that the aggregated process is stochastically equivalent to the original one and retains the Markov property. We apply this model on a heat exchanging system in oil refinery company. The results show that fault propagation has a more significant impact on the system's lifetime comparing with inherent dependence and induced dependence. - Highlights: • We develop a vector value continuous-time Markov chain to model the meta-dependent characteristic of fault propagation. • A partitioning rule is derived to reduce the state space and attain lumpability. • The model is applied on analysing the impact of fault propagation in a heat exchanging system.

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....

PCA Fault Feature Extraction in Complex Electric Power Systems

Directory of Open Access Journals (Sweden)

ZHANG, J.

2010-08-01

Full Text Available Electric power system is one of the most complex artificial systems in the world. The complexity is determined by its characteristics about constitution, configuration, operation, organization, etc. The fault in electric power system cannot be completely avoided. When electric power system operates from normal state to failure or abnormal, its electric quantities (current, voltage and angles, etc. may change significantly. Our researches indicate that the variable with the biggest coefficient in principal component usually corresponds to the fault. Therefore, utilizing real-time measurements of phasor measurement unit, based on principal components analysis technology, we have extracted successfully the distinct features of fault component. Of course, because of the complexity of different types of faults in electric power system, there still exists enormous problems need a close and intensive study.

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

Measurement and analysis of operating system fault tolerance

Science.gov (United States)

Lee, I.; Tang, D.; Iyer, R. K.

1992-01-01

This paper demonstrates a methodology to model and evaluate the fault tolerance characteristics of operational software. The methodology is illustrated through case studies on three different operating systems: the Tandem GUARDIAN fault-tolerant system, the VAX/VMS distributed system, and the IBM/MVS system. Measurements are made on these systems for substantial periods to collect software error and recovery data. In addition to investigating basic dependability characteristics such as major software problems and error distributions, we develop two levels of models to describe error and recovery processes inside an operating system and on multiple instances of an operating system running in a distributed environment. Based on the models, reward analysis is conducted to evaluate the loss of service due to software errors and the effect of the fault-tolerance techniques implemented in the systems. Software error correlation in multicomputer systems is also investigated.

Discrete Wavelet Transform for Fault Locations in Underground Distribution System

Science.gov (United States)

Apisit, C.; Ngaopitakkul, A.

2010-10-01

In this paper, a technique for detecting faults in underground distribution system is presented. Discrete Wavelet Transform (DWT) based on traveling wave is employed in order to detect the high frequency components and to identify fault locations in the underground distribution system. The first peak time obtained from the faulty bus is employed for calculating the distance of fault from sending end. The validity of the proposed technique is tested with various fault inception angles, fault locations and faulty phases. The result is found that the proposed technique provides satisfactory result and will be very useful in the development of power systems protection scheme.

An expert system for diagnostics and estimation of steam turbine components condition

Science.gov (United States)

Murmansky, B. E.; Aronson, K. E.; Brodov, Yu. M.

2017-11-01

The report describes an expert system of probability type for diagnostics and state estimation of steam turbine technological subsystems components. The expert system is based on Bayes’ theorem and permits to troubleshoot the equipment components, using expert experience, when there is a lack of baseline information on the indicators of turbine operation. Within a unified approach the expert system solves the problems of diagnosing the flow steam path of the turbine, bearings, thermal expansion system, regulatory system, condensing unit, the systems of regenerative feed-water and hot water heating. The knowledge base of the expert system for turbine unit rotors and bearings contains a description of 34 defects and of 104 related diagnostic features that cause a change in its vibration state. The knowledge base for the condensing unit contains 12 hypotheses and 15 evidence (indications); the procedures are also designated for 20 state parameters estimation. Similar knowledge base containing the diagnostic features and faults hypotheses are formulated for other technological subsystems of turbine unit. With the necessary initial information available a number of problems can be solved within the expert system for various technological subsystems of steam turbine unit: for steam flow path it is the correlation and regression analysis of multifactor relationship between the vibration parameters variations and the regime parameters; for system of thermal expansions it is the evaluation of force acting on the longitudinal keys depending on the temperature state of the turbine cylinder; for condensing unit it is the evaluation of separate effect of the heat exchange surface contamination and of the presence of air in condenser steam space on condenser thermal efficiency performance, as well as the evaluation of term for condenser cleaning and for tube system replacement and so forth. With a lack of initial information the expert system enables to formulate a diagnosis

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.

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.

Guideliness for system modeling: fault tree [analysis

Energy Technology Data Exchange (ETDEWEB)

Lee, Yoon Hwan; Yang, Joon Eon; Kang, Dae Il; Hwang, Mee Jeong

2004-07-01

This document, the guidelines for system modeling related to Fault Tree Analysis(FTA), is intended to provide the guidelines with the analyzer to construct the fault trees in the level of the capability category II of ASME PRA standard. Especially, they are to provide the essential and basic guidelines and the related contents to be used in support of revising the Ulchin 3 and 4 PSA model for risk monitor within the capability category II of ASME PRA standard. Normally the main objective of system analysis is to assess the reliability of system modeled by Event Tree Analysis (ETA). A variety of analytical techniques can be used for the system analysis, however, FTA method is used in this procedures guide. FTA is the method used for representing the failure logic of plant systems deductively using AND, OR or NOT gates. The fault tree should reflect all possible failure modes that may contribute to the system unavailability. This should include contributions due to the mechanical failures of the components, Common Cause Failures (CCFs), human errors and outages for testing and maintenance. This document identifies and describes the definitions and the general procedures of FTA and the essential and basic guidelines for reving the fault trees. Accordingly, the guidelines for FTA will be capable to guide the FTA to the level of the capability category II of ASME PRA standard.

Guideliness for system modeling: fault tree [analysis

International Nuclear Information System (INIS)

Lee, Yoon Hwan; Yang, Joon Eon; Kang, Dae Il; Hwang, Mee Jeong

2004-07-01

This document, the guidelines for system modeling related to Fault Tree Analysis(FTA), is intended to provide the guidelines with the analyzer to construct the fault trees in the level of the capability category II of ASME PRA standard. Especially, they are to provide the essential and basic guidelines and the related contents to be used in support of revising the Ulchin 3 and 4 PSA model for risk monitor within the capability category II of ASME PRA standard. Normally the main objective of system analysis is to assess the reliability of system modeled by Event Tree Analysis (ETA). A variety of analytical techniques can be used for the system analysis, however, FTA method is used in this procedures guide. FTA is the method used for representing the failure logic of plant systems deductively using AND, OR or NOT gates. The fault tree should reflect all possible failure modes that may contribute to the system unavailability. This should include contributions due to the mechanical failures of the components, Common Cause Failures (CCFs), human errors and outages for testing and maintenance. This document identifies and describes the definitions and the general procedures of FTA and the essential and basic guidelines for reving the fault trees. Accordingly, the guidelines for FTA will be capable to guide the FTA to the level of the capability category II of ASME PRA standard

Adaptive Observer-Based Fault-Tolerant Control Design for Uncertain Systems

Directory of Open Access Journals (Sweden)

Huaming Qian

2015-01-01

Full Text Available This study focuses on the design of the robust fault-tolerant control (FTC system based on adaptive observer for uncertain linear time invariant (LTI systems. In order to improve robustness, rapidity, and accuracy of traditional fault estimation algorithm, an adaptive fault estimation algorithm (AFEA using an augmented observer is presented. By utilizing a new fault estimator model, an improved AFEA based on linear matrix inequality (LMI technique is proposed to increase the performance. Furthermore, an observer-based state feedback fault-tolerant control strategy is designed, which guarantees the stability and performance of the faulty system. Moreover, the adaptive observer and the fault-tolerant controller are designed separately, whose performance can be considered, respectively. Finally, simulation results of an aircraft application are presented to illustrate the effectiveness of the proposed design methods.

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

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...

A fault tolerant system by using distributed RTOS

International Nuclear Information System (INIS)

Ge Yingan; Liu Songqiang; Wang Yanfang

1999-01-01

The author describes the design and implementation of a prototypal distributed fault tolerant system, which is developed under QNX RTOS by networking two standard PCs. By using a watchdog timer for error detection, the system can be tolerant for fail silent and transient fault of a single node

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...

A new digital ground-fault protection system for generator-transformer unit

Energy Technology Data Exchange (ETDEWEB)

Zielichowski, Mieczyslaw; Szlezak, Tomasz [Institute of Electrical Power Engineering, Wroclaw University of Technology, Wybrzeze Wyspianskiego 27, 50370 Wroclaw (Poland)

2007-08-15

Ground faults are one of most often reasons of damages in stator windings of large generators. Under certain conditions, as a result of ground-fault protection systems maloperation, ground faults convert into high-current faults, causing severe failures in power system. Numerous publications in renowned journals and magazines testify about ground-fault matter importance and problems reported by exploitators confirm opinions, that some issues concerning ground-fault protection of large generators have not been solved yet or have been solved insufficiently. In this paper a new conception of a digital ground-fault protection system for stator winding of large generator was proposed. The process of intermittent arc ground fault in stator winding has been briefly discussed and actual ground-fault voltage waveforms were presented. A new relaying algorithm, based on third harmonic voltage measurement was also drawn and the methods of its implementation and testing were described. (author)

Model-based fault diagnosis in PEM fuel cell systems

Energy Technology Data Exchange (ETDEWEB)

Escobet, T; de Lira, S; Puig, V; Quevedo, J [Automatic Control Department (ESAII), Universitat Politecnica de Catalunya (UPC), Rambla Sant Nebridi 10, 08222 Terrassa (Spain); Feroldi, D; Riera, J; Serra, M [Institut de Robotica i Informatica Industrial (IRI), Consejo Superior de Investigaciones Cientificas (CSIC), Universitat Politecnica de Catalunya (UPC) Parc Tecnologic de Barcelona, Edifici U, Carrer Llorens i Artigas, 4-6, Planta 2, 08028 Barcelona (Spain)

2009-07-01

In this work, a model-based fault diagnosis methodology for PEM fuel cell systems is presented. The methodology is based on computing residuals, indicators that are obtained comparing measured inputs and outputs with analytical relationships, which are obtained by system modelling. The innovation of this methodology is based on the characterization of the relative residual fault sensitivity. To illustrate the results, a non-linear fuel cell simulator proposed in the literature is used, with modifications, to include a set of fault scenarios proposed in this work. Finally, it is presented the diagnosis results corresponding to these fault scenarios. It is remarkable that with this methodology it is possible to diagnose and isolate all the faults in the proposed set in contrast with other well known methodologies which use the binary signature matrix of analytical residuals and faults. (author)

An Online Fault Pre-warning System of the Rolling Mill Screw-down Device Based on Virtual Instrument

Directory of Open Access Journals (Sweden)

Qing Bai

2014-04-01

Full Text Available A traditional off-line screw-down monitoring system performs not well on real-time signal analysis or process, which cannot provide simultaneous fault pre-warning either. A diagnostic monitoring system as well as a remotely accessible graphic user interface is presented in this paper. The main objective of this work is to develop an online and available technique for monitoring the kinetic, hydrodynamic and electrical parameters of the rolling mill screw-down device, and analyze these figures to support online fault pre-warning. A series of transducers are installed in suitable locations to measure parameters decried above including the vibration acceleration of a rolling mill stand, the rolling force of a screw-down device, the stroke of a hydraulic cylinder, the system source pressure, the in-cylinder stress and the output value of an electro-hydraulic servo valve. An industrial personal computer picks up the information transformed by an extra high-speed data acquisition board embedded inside, processes the signals via a software designed by means of Laborary Virtual Instrument Engineering Workbench (LabVIEW and indicates fault conditions through the graphic user interface. Besides, the data of the overall system can be published over the Internet using LabVIEW Web Server capabilities. The results of experiments suggest that the system works well on real-time data acquisition and online fault pre- warning. The statistics saved contributes to the research of vibration performance and malfunction analysis of a rolling mill.

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.

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.

CONFIG - Adapting qualitative modeling and discrete event simulation for design of fault management systems

Science.gov (United States)

Malin, Jane T.; Basham, Bryan D.

1989-01-01

CONFIG is a modeling and simulation tool prototype for analyzing the normal and faulty qualitative behaviors of engineered systems. Qualitative modeling and discrete-event simulation have been adapted and integrated, to support early development, during system design, of software and procedures for management of failures, especially in diagnostic expert systems. Qualitative component models are defined in terms of normal and faulty modes and processes, which are defined by invocation statements and effect statements with time delays. System models are constructed graphically by using instances of components and relations from object-oriented hierarchical model libraries. Extension and reuse of CONFIG models and analysis capabilities in hybrid rule- and model-based expert fault-management support systems are discussed.

Results of an electrical power system fault study

Science.gov (United States)

Dugal-Whitehead, Norma R.; Johnson, Yvette B.

1992-01-01

NASA-Marshall conducted a study of electrical power system faults with a view to the development of AI control systems for a spacecraft power system breadboard. The results of this study have been applied to a multichannel high voltage dc spacecraft power system, the Large Autonomous Spacecraft Electrical Power System (LASEPS) breadboard. Some of the faults encountered in testing LASEPS included the shorting of a bus an a falloff in battery cell capacity.

Coulomb Stress Accumulation along the San Andreas Fault System

Science.gov (United States)

Smith, Bridget; Sandwell, David

2003-01-01

Stress accumulation rates along the primary segments of the San Andreas Fault system are computed using a three-dimensional (3-D) elastic half-space model with realistic fault geometry. The model is developed in the Fourier domain by solving for the response of an elastic half-space due to a point vector body force and analytically integrating the force from a locking depth to infinite depth. This approach is then applied to the San Andreas Fault system using published slip rates along 18 major fault strands of the fault zone. GPS-derived horizontal velocity measurements spanning the entire 1700 x 200 km region are then used to solve for apparent locking depth along each primary fault segment. This simple model fits remarkably well (2.43 mm/yr RMS misfit), although some discrepancies occur in the Eastern California Shear Zone. The model also predicts vertical uplift and subsidence rates that are in agreement with independent geologic and geodetic estimates. In addition, shear and normal stresses along the major fault strands are used to compute Coulomb stress accumulation rate. As a result, we find earthquake recurrence intervals along the San Andreas Fault system to be inversely proportional to Coulomb stress accumulation rate, in agreement with typical coseismic stress drops of 1 - 10 MPa. This 3-D deformation model can ultimately be extended to include both time-dependent forcing and viscoelastic response.

Fault trees for decision making in systems analysis

International Nuclear Information System (INIS)

Lambert, H.E.

1975-01-01

The application of fault tree analysis (FTA) to system safety and reliability is presented within the framework of system safety analysis. The concepts and techniques involved in manual and automated fault tree construction are described and their differences noted. The theory of mathematical reliability pertinent to FTA is presented with emphasis on engineering applications. An outline of the quantitative reliability techniques of the Reactor Safety Study is given. Concepts of probabilistic importance are presented within the fault tree framework and applied to the areas of system design, diagnosis and simulation. The computer code IMPORTANCE ranks basic events and cut sets according to a sensitivity analysis. A useful feature of the IMPORTANCE code is that it can accept relative failure data as input. The output of the IMPORTANCE code can assist an analyst in finding weaknesses in system design and operation, suggest the most optimal course of system upgrade, and determine the optimal location of sensors within a system. A general simulation model of system failure in terms of fault tree logic is described. The model is intended for efficient diagnosis of the causes of system failure in the event of a system breakdown. It can also be used to assist an operator in making decisions under a time constraint regarding the future course of operations. The model is well suited for computer implementation. New results incorporated in the simulation model include an algorithm to generate repair checklists on the basis of fault tree logic and a one-step-ahead optimization procedure that minimizes the expected time to diagnose system failure. (80 figures, 20 tables)

A Game-Theoretic approach to Fault Diagnosis of Hybrid Systems

Directory of Open Access Journals (Sweden)

Davide Bresolin

2011-06-01

Full Text Available Physical systems can fail. For this reason the problem of identifying and reacting to faults has received a large attention in the control and computer science communities. In this paper we study the fault diagnosis problem for hybrid systems from a game-theoretical point of view. A hybrid system is a system mixing continuous and discrete behaviours that cannot be faithfully modeled neither by using a formalism with continuous dynamics only nor by a formalism including only discrete dynamics. We use the well known framework of hybrid automata for modeling hybrid systems, and we define a Fault Diagnosis Game on them, using two players: the environment and the diagnoser. The environment controls the evolution of the system and chooses whether and when a fault occurs. The diagnoser observes the external behaviour of the system and announces whether a fault has occurred or not. Existence of a winning strategy for the diagnoser implies that faults can be detected correctly, while computing such a winning strategy corresponds to implement a diagnoser for the system. We will show how to determine the existence of a winning strategy, and how to compute it, for some decidable classes of hybrid automata like o-minimal hybrid automata.

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.

Fault Tolerant Control Systems

DEFF Research Database (Denmark)

Bøgh, S. A.

This thesis considered the development of fault tolerant control systems. The focus was on the category of automated processes that do not necessarily comprise a high number of identical sensors and actuators to maintain safe operation, but still have a potential for improving immunity to component...

Mine-hoist active fault tolerant control system and strategy

Energy Technology Data Exchange (ETDEWEB)

Wang, Z.; Wang, Y.; Meng, J.; Zhao, P.; Chang, Y. [China University of Mining and Technology, Xuzhou (China)] wzjsdstu@163.com

2005-06-01

Based on fault diagnosis and fault tolerant technologies, the mine-hoist active fault-tolerant control system (MAFCS) is presented with corresponding strategies, which includes the fault diagnosis module (FDM), the dynamic library (DL) and the fault-tolerant control model (FCM). When a fault is judged from some sensor by the FDM, FCM reconfigures the state of the MAFCS by calling the parameters from all sub libraries in DL, in order to ensure the reliability and safety of the mine hoist. The simulating result shows that MAFCS is of certain intelligence, which can adopt the corresponding control strategies according to different fault modes, even when there is quite a difference between the real data and the prior fault modes. 7 refs., 5 figs., 1 tab.

Model-based fault detection algorithm for photovoltaic system monitoring

KAUST Repository

Harrou, Fouzi; Sun, Ying; Saidi, Ahmed

2018-01-01

Reliable detection of faults in PV systems plays an important role in improving their reliability, productivity, and safety. This paper addresses the detection of faults in the direct current (DC) side of photovoltaic (PV) systems using a

Analysis and optimization of fault-tolerant embedded systems with hardened processors

DEFF Research Database (Denmark)

Izosimov, Viacheslav; Polian, Ilia; Pop, Paul

2009-01-01

In this paper we propose an approach to the design optimization of fault-tolerant hard real-time embedded systems, which combines hardware and software fault tolerance techniques. We trade-off between selective hardening in hardware and process reexecution in software to provide the required levels...... of fault tolerance against transient faults with the lowest-possible system costs. We propose a system failure probability (SFP) analysis that connects the hardening level with the maximum number of reexecutions in software. We present design optimization heuristics, to select the fault......-tolerant architecture and decide process mapping such that the system cost is minimized, deadlines are satisfied, and the reliability requirements are fulfilled....

Detector design for active fault diagnosis in closed-loop systems

DEFF Research Database (Denmark)

Sekunda, André Krabdrup; Niemann, Hans Henrik; Poulsen, Niels Kjølstad

2018-01-01

Fault diagnosis of closed-loop systems is extremely relevant for high-precision equipment and safety critical systems. Fault diagnosis is usually divided into 2 schemes: active and passive fault diagnosis. Recent studies have highlighted some advantages of active fault diagnosis based on dual Youla......-Jabr-Bongiorno-Kucera parameters. In this paper, a method for closed-loop active fault diagnosis based on statistical detectors is given using dual Youla-Jabr-Bongiorno-Kucera parameters. The goal of this paper is 2-fold. First, the authors introduce a method for measuring a residual signal subject to white noise. Second...

Application Research of Fault Tree Analysis in Grid Communication System Corrective Maintenance

Science.gov (United States)

Wang, Jian; Yang, Zhenwei; Kang, Mei

2018-01-01

This paper attempts to apply the fault tree analysis method to the corrective maintenance field of grid communication system. Through the establishment of the fault tree model of typical system and the engineering experience, the fault tree analysis theory is used to analyze the fault tree model, which contains the field of structural function, probability importance and so on. The results show that the fault tree analysis can realize fast positioning and well repairing of the system. Meanwhile, it finds that the analysis method of fault tree has some guiding significance to the reliability researching and upgrading f the system.

All-to-all sequenced fault detection system

Science.gov (United States)

Archer, Charles Jens; Pinnow, Kurt Walter; Ratterman, Joseph D.; Smith, Brian Edward

2010-11-02

An apparatus, program product and method enable nodal fault detection by sequencing communications between all system nodes. A master node may coordinate communications between two slave nodes before sequencing to and initiating communications between a new pair of slave nodes. The communications may be analyzed to determine the nodal fault.

Fault diagnosis of air conditioning systems based on qualitative bond graph

International Nuclear Information System (INIS)

Ghiaus, C.

1999-01-01

The bond graph method represents a unified approach for modeling engineering systems. The main idea is that power transfer bonds the components of a system. The bond graph model is the same for both quantitative representation, in which parameters have numerical values, and qualitative approach, in which they are classified qualitatively. To infer the cause of faults using a qualitative method, a system of qualitative equations must be solved. However, the characteristics of qualitative operators require specific methods for solving systems of equations having qualitative variables. This paper proposes both a method for recursively solving the qualitative system of equations derived from bond graph, and a bond graph model of a direct-expansion, mechanical vapor-compression air conditioning system. Results from diagnosing two faults in a real air conditioning system are presented and discussed. Occasionally, more than one fault candidate is inferred for the same set of qualitative values derived from measurements. In these cases, additional information is required to localize the fault. Fault diagnosis is initiated by a fault detection mechanism which also classifies the quantitative measurements into qualitative values; the fault detection is not presented here. (author)

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.

Effect Analysis of Faults in Digital I and C Systems of Nuclear Power Plants

Energy Technology Data Exchange (ETDEWEB)

Lee, Seung Jun; Jung, Won Dea [KAERI, Dajeon (Korea, Republic of); Kim, Man Cheol [Chung-Ang University, Seoul (Korea, Republic of)

2014-08-15

A reliability analysis of digital instrumentation and control (I and C) systems in nuclear power plants has been introduced as one of the important elements of a probabilistic safety assessment because of the unique characteristics of digital I and C systems. Digital I and C systems have various features distinguishable from those of analog I and C systems such as software and fault-tolerant techniques. In this work, the faults in a digital I and C system were analyzed and a model for representing the effects of the faults was developed. First, the effects of the faults in a system were analyzed using fault injection experiments. A software-implemented fault injection technique in which faults can be injected into the memory was used based on the assumption that all faults in a system are reflected in the faults in the memory. In the experiments, the effect of a fault on the system output was observed. In addition, the success or failure in detecting the fault by fault-tolerant functions included in the system was identified. Second, a fault tree model for representing that a fault is propagated to the system output was developed. With the model, it can be identified how a fault is propagated to the output or why a fault is not detected by fault-tolerant techniques. Based on the analysis results of the proposed method, it is possible to not only evaluate the system reliability but also identify weak points of fault-tolerant techniques by identifying undetected faults. The results can be reflected in the designs to improve the capability of fault-tolerant techniques.

Effect analysis of faults in digital I and C systems of nuclear power plants

International Nuclear Information System (INIS)

Lee, Seung Jun

2014-01-01

A reliability analysis of digital instrumentation and control (I and C) systems in nuclear power plants has been introduced as one of the important elements of a probabilistic safety assessment because of the unique characteristics of digital I and C systems. Digital I and C systems have various features distinguishable from those of analog I and C systems such as software and fault-tolerant techniques. In this work, the faults in a digital I and C system were analyzed and a model for representing the effects of the faults was developed. First, the effects of the faults in a system were analyzed using fault injection experiments. A software-implemented fault injection technique in which faults can be injected into the memory was used based on the assumption that all faults in a system are reflected in the faults in the memory. In the experiments, the effect of a fault on the system output was observed. In addition, the success or failure in detecting the fault by fault-tolerant functions included in the system was identified. Second, a fault tree model for representing that a fault is propagated to the system output was developed. With the model, it can be identified how a fault is propagated to the output or why a fault is not detected by fault-tolerant techniques. Based on the analysis results of the proposed method, it is possible to not only evaluate the system reliability but also identify weak points of fault-tolerant techniques by identifying undetected faults. The results can be reflected in the designs to improve the capability of fault-tolerant techniques. (author)

GOTRES: an expert system for fault detection and analysis

International Nuclear Information System (INIS)

Chung, D.T.; Modarres, M.

1989-01-01

This paper describes a deep-knowledge expert system shell for diagnosing faults in process operations. The expert program shell is called GOTRES (GOal TRee Expert System) and uses a goal tree-success tree deep-knowledge structure to model its knowledge-base. To demonstrate GOTRES, we have built an on-line fault diagnosis expert system for an experimental nuclear reactor facility using this shell. The expert system is capable of diagnosing fault conditions using system goal tree as well as utilizing accumulated operating knowledge to predict plant causal and temporal behaviours. The GOTRES shell has also been used for root-cause detection and analysis in a nuclear plant. (author)

Estimating Rates of Fault Insertion and Test Effectiveness in Software Systems

Science.gov (United States)

Nikora, A.; Munson, J.

1998-01-01

In developing a software system, we would like to estimate the total number of faults inserted into a software system, the residual fault content of that system at any given time, and the efficacy of the testing activity in executing the code containing the newly inserted faults.

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.

Methods for Fault Diagnosability Analysis of a Class of Affine Nonlinear Systems

Directory of Open Access Journals (Sweden)

Xiafu Peng

2015-01-01

Full Text Available The fault diagnosability analysis for a given model, before developing a diagnosis algorithm, can be used to answer questions like “can the fault fi be detected by observed states?” and “can it separate fault fi from fault fj by observed states?” If not, we should redesign the sensor placement. This paper deals with the problem of the evaluation of detectability and separability for the diagnosability analysis of affine nonlinear system. First, we used differential geometry theory to analyze the nonlinear system and proposed new detectability criterion and separability criterion. Second, the related matrix between the faults and outputs of the system and the fault separable matrix are designed for quantitative fault diagnosability calculation and fault separability calculation, respectively. Finally, we illustrate our approach to exemplify how to analyze diagnosability by a certain nonlinear system example, and the experiment results indicate the effectiveness of the fault evaluation methods.

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

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...

Identification of active fault using analysis of derivatives with vertical second based on gravity anomaly data (Case study: Seulimeum fault in Sumatera fault system)

Science.gov (United States)

Hududillah, Teuku Hafid; Simanjuntak, Andrean V. H.; Husni, Muhammad

2017-07-01

Gravity is a non-destructive geophysical technique that has numerous application in engineering and environmental field like locating a fault zone. The purpose of this study is to spot the Seulimeum fault system in Iejue, Aceh Besar (Indonesia) by using a gravity technique and correlate the result with geologic map and conjointly to grasp a trend pattern of fault system. An estimation of subsurface geological structure of Seulimeum fault has been done by using gravity field anomaly data. Gravity anomaly data which used in this study is from Topex that is processed up to Free Air Correction. The step in the Next data processing is applying Bouger correction and Terrin Correction to obtain complete Bouger anomaly that is topographically dependent. Subsurface modeling is done using the Gav2DC for windows software. The result showed a low residual gravity value at a north half compared to south a part of study space that indicated a pattern of fault zone. Gravity residual was successfully correlate with the geologic map that show the existence of the Seulimeum fault in this study space. The study of earthquake records can be used for differentiating the active and non active fault elements, this gives an indication that the delineated fault elements are active.

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.

A Fault Diagnosis Approach for the Hydraulic System by Artificial Neural Networks

OpenAIRE

Xiangyu He; Shanghong He

2014-01-01

Based on artificial neural networks, a fault diagnosis approach for the hydraulic system was proposed in this paper. Normal state samples were used as the training data to develop a dynamic general regression neural network (DGRNN) model. The trained DGRNN model then served as the fault determinant to diagnose test faults and the work condition of the hydraulic system was identified. Several typical faults of the hydraulic system were used to verify the fault diagnosis approach. Experiment re...

Active Fault Tolerant Control of Livestock Stable Ventilation System

DEFF Research Database (Denmark)

Gholami, Mehdi

2011-01-01

Modern stables and greenhouses are equipped with different components for providing a comfortable climate for animals and plant. A component malfunction may result in loss of production. Therefore, it is desirable to design a control system, which is stable, and is able to provide an acceptable d...... are not included, while due to the physical limitation, the input signal can not have any value. In continuing, a passive fault tolerant controller (PFTC) based on state feedback is proposed to track a reference signal while the control inputs are bounded....... of fault. Designing a fault tolerant control scheme for the climate control system. In the first step, a conceptual multi-zone model for climate control of a live-stock building is derived. The model is a nonlinear hybrid model. Hybrid systems contain both discrete and continuous components. The parameters...... affine (PWA) components such as dead-zones, saturation, etc or contain piecewise nonlinear models which is the case for the climate control systems of the stables. Fault tolerant controller (FTC) is based on a switching scheme between a set of predefined passive fault tolerant controller (PFTC...

Fault Tolerant Emergency Control to Preserve Power System Stability

DEFF Research Database (Denmark)

Pedersen, Andreas Søndergaard; Richter, Jan H.; Tabatabaeipour, Mojtaba

2016-01-01

This paper introduces a method for fault-masking and system reconfiguration in power transmission systems. The paper demonstrates how faults are handled by reconfiguring remaining controls through utilisation of wide-area measurement in real time. It is shown how reconfiguration can be obtained u...

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)

SIFT - Design and analysis of a fault-tolerant computer for aircraft control. [Software Implemented Fault Tolerant systems

Science.gov (United States)

Wensley, J. H.; Lamport, L.; Goldberg, J.; Green, M. W.; Levitt, K. N.; Melliar-Smith, P. M.; Shostak, R. E.; Weinstock, C. B.

1978-01-01

SIFT (Software Implemented Fault Tolerance) is an ultrareliable computer for critical aircraft control applications that achieves fault tolerance by the replication of tasks among processing units. The main processing units are off-the-shelf minicomputers, with standard microcomputers serving as the interface to the I/O system. Fault isolation is achieved by using a specially designed redundant bus system to interconnect the processing units. Error detection and analysis and system reconfiguration are performed by software. Iterative tasks are redundantly executed, and the results of each iteration are voted upon before being used. Thus, any single failure in a processing unit or bus can be tolerated with triplication of tasks, and subsequent failures can be tolerated after reconfiguration. Independent execution by separate processors means that the processors need only be loosely synchronized, and a novel fault-tolerant synchronization method is described.

Faulting and hydration of the Juan de Fuca plate system

Science.gov (United States)

Nedimović, Mladen R.; Bohnenstiehl, DelWayne R.; Carbotte, Suzanne M.; Pablo Canales, J.; Dziak, Robert P.

2009-06-01

Multichannel seismic observations provide the first direct images of crustal scale normal faults within the Juan de Fuca plate system and indicate that brittle deformation extends up to ~ 200 km seaward of the Cascadia trench. Within the sedimentary layering steeply dipping faults are identified by stratigraphic offsets, with maximum throws of 110 ± 10 m found near the trench. Fault throws diminish both upsection and seaward from the trench. Long-term throw rates are estimated to be 13 ± 2 mm/kyr. Faulted offsets within the sedimentary layering are typically linked to larger offset scarps in the basement topography, suggesting reactivation of the normal fault systems formed at the spreading center. Imaged reflections within the gabbroic igneous crust indicate swallowing fault dips at depth. These reflections require local alteration to produce an impedance contrast, indicating that the imaged fault structures provide pathways for fluid transport and hydration. As the depth extent of imaged faulting within this young and sediment insulated oceanic plate is primarily limited to approximately Moho depths, fault-controlled hydration appears to be largely restricted to crustal levels. If dehydration embrittlement is an important mechanism for triggering intermediate-depth earthquakes within the subducting slab, then the limited occurrence rate and magnitude of intraslab seismicity at the Cascadia margin may in part be explained by the limited amount of water imbedded into the uppermost oceanic mantle prior to subduction. The distribution of submarine earthquakes within the Juan de Fuca plate system indicates that propagator wake areas are likely to be more faulted and therefore more hydrated than other parts of this plate system. However, being largely restricted to crustal levels, this localized increase in hydration generally does not appear to have a measurable effect on the intraslab seismicity along most of the subducted propagator wakes at the Cascadia margin.

A Review Of Fault Tolerant Scheduling In Multicore Systems

Directory of Open Access Journals (Sweden)

Shefali Malhotra

2015-05-01

Full Text Available Abstract In this paper we have discussed about various fault tolerant task scheduling algorithm for multi core system based on hardware and software. Hardware based algorithm which is blend of Triple Modulo Redundancy and Double Modulo Redundancy in which Agricultural Vulnerability Factor is considered while deciding the scheduling other than EDF and LLF scheduling algorithms. In most of the real time system the dominant part is shared memory.Low overhead software based fault tolerance approach can be implemented at user-space level so that it does not require any changes at application level. Here redundant multi-threaded processes are used. Using those processes we can detect soft errors and recover from them. This method gives low overhead fast error detection and recovery mechanism. The overhead incurred by this method ranges from 0 to 18 for selected benchmarks. Hybrid Scheduling Method is another scheduling approach for real time systems. Dynamic fault tolerant scheduling gives high feasibility rate whereas task criticality is used to select the type of fault recovery method in order to tolerate the maximum number of faults.

Data-driven design of fault diagnosis systems nonlinear multimode processes

CERN Document Server

Haghani Abandan Sari, Adel

2014-01-01

In many industrial applications early detection and diagnosis of abnormal behavior of the plant is of great importance. During the last decades, the complexity of process plants has been drastically increased, which imposes great challenges in development of model-based monitoring approaches and it sometimes becomes unrealistic for modern large-scale processes. The main objective of Adel Haghani Abandan Sari is to study efficient fault diagnosis techniques for complex industrial systems using process historical data and considering the nonlinear behavior of the process. To this end, different methods are presented to solve the fault diagnosis problem based on the overall behavior of the process and its dynamics. Moreover, a novel technique is proposed for fault isolation and determination of the root-cause of the faults in the system, based on the fault impacts on the process measurements. Contents Process monitoring Fault diagnosis and fault-tolerant control Data-driven approaches and decision making Target...

Fault Detection and Isolation for Wind Turbine Electric Pitch System

DEFF Research Database (Denmark)

Zhu, Jiangsheng; Ma, Kuichao; Hajizadeh, Amin

2017-01-01

This paper presents a model-based fault detection and isolation scheme applied on electric pitch system of wind turbines. Pitch system is one of the most critical components due to its effect on the operational safety and the dynamics of wind turbines. Faults in this system should be precisely...... detected to prevent failures and decrease downtime. To detect faults of electric pitch actuators and sensors, an extended kalman filter (EKF) based multiple model adaptive estimation (MMAE) designed to estimate the states of the system. The proposed method is demonstrated in case studies. The simulation...

Reactor coolant pump monitoring and diagnostic system

International Nuclear Information System (INIS)

Singer, R.M.; Gross, K.C.; Walsh, M.; Humenik, K.E.

1990-01-01

In order to reliably and safely operate a nuclear power plant, it is necessary to continuously monitor the performance of numerous subsystems to confirm that the plant state is within its prescribed limits. An important function of a properly designed monitoring system is the detection of incipient faults in all subsystems (with the avoidance of false alarms) coupled with an information system that provides the operators with fault diagnosis, prognosis of fault progression and recommended (either automatic or prescriptive) corrective action. In this paper, such a system is described that has been applied to reactor coolant pumps. This system includes a sensitive pattern-recognition technique based upon the sequential probability ratio test (SPRT) that detects incipient faults from validated signals, an expert system embodying knowledge bases on pump and sensor performance, extensive hypertext files containing operating and emergency procedures as well as pump and sensor information and a graphical interface providing the operator with easily perceived information on the location and character of the fault as well as recommended corrective action. This system is in the prototype stage and is currently being validated utilizing data from a liquid-metal cooled fast reactor (EBR-II). 3 refs., 4 figs

Fault Adaptive Control of Overactuated Systems Using Prognostic Estimation

Data.gov (United States)

National Aeronautics and Space Administration — Most fault adaptive control research addresses the preservation of system stability or functionality in the presence of a specific failure (fault). This paper...

Evidence of a tectonic transient within the Idrija fault system in Western Slovenia

Science.gov (United States)

Vičič, Blaž; Costa, Giovanni; Aoudia, Abdelkrim

2017-04-01

Western Slovenia and North-eastern Italy are areas of medium rate seismicity with rare historic earthquakes of higher magnitudes. From mainly reverse component faulting in north-western part of the region where 1976 Friuli earthquakes took place, tectonic regime changes to mostly strike-slip faulting in the Dinaric region, continuing towards southeast. In the northern part of the Idrija fault system, which represent the broader Dinaric strike-slip system there were two strong earthquakes in the recent times - Mw=5.6 1998 and Mw=5.2 2004 earthquakes. Further to the south, along the Idrija fault system, Idrija fault is the causative fault of 1511 Mw=6.8 earthquake. The southeastern most part of the Idrija fault system produced a Mw=5.2 earthquake in 1926 and few historic Mw>4 earthquakes. Since 2004 Mw=5.2 earthquake, no stronger earthquakes were recorded in the region covered by dense seismic network. Seismicity is mostly concentrated in Friuli region and north-western part of Idrija fault system - mostly on the Ravne fault which is the causative fault for the 1998 and 2004 earthquakes. In the central part of the fault system no strong or moderate earthquakes were recorded, except of an earthquake along the Idrija fault in 2014 of magnitude 3.4. Low magnitude background seismicity is burst like with no apparent temporal or spatial distribution. Seismicity of the southern part of Idrija fault system is again a bit higher than in the central part of the fault system with earthquakes up to Mw=4.4 that happened in 2014. In this study, detailed analysis of the seismicity is performed with manual relocation of the seismicity in the period between 2006 and 2016. With manual inspection of the waveform data, slight temporal clustering of seismicity is observed. We use a template algorithm method to increase the detection rate of the seismicity. Templates of seismicity in the north-western and south-eastern part of Idrija fault system are created. The continuous waveform data

Fault tree analysis for reactor systems

International Nuclear Information System (INIS)

Crosetti, P.A.

1971-01-01

Reliability analysis is playing an increasingly important role in quantitative assessment of system performance for assuring nuclear safety, improving plant performance and plant life, and reducing plant operating costs. The complexity of today's nuclear plants warrant the use of techniques which will provide a comprehensive evaluation of systems in their total context. In particular, fault tree analysis with probability evaluation can play a key role in assuring nuclear safety, in improving plant performance and plant life, and in reducing plant operating costs. The technique provides an all inclusive, versatile mathematical tool for analyzing complex systems. Its application can include a complete plant as well as any of the systems and subsystems. Fault tree analysis provides an objective basis for analyzing system design, performing trade-off studies, analyzing common mode failures, demonstrating compliance with AEC requirements, and justifying system changes or additions. The logic of the approach makes it readily understandable and, therefore, it serves as an effective visibility tool for both engineering and management. (U.S.)

The continuation of the Kazerun fault system across the Sanandaj-Sirjan zone (Iran)

Science.gov (United States)

Safaei, Homayon

2009-08-01

The Kazerun (or Kazerun-Qatar) fault system is a north-trending dextral strike-slip fault zone in the Zagros mountain belt of Iran. It probably originated as a structure in the Panafrican basement. This fault system played an important role in the sedimentation and deformation of the Phanerozoic cover sequence and is still seismically active. No previous studies have reported the continuation of this important and ancient fault system northward across the Sanandaj-Sirjan zone. The Isfahan fault system is a north-trending dextral strike-slip fault across the Sanandaj-Sirjan zone that passes west of Isfahan city and is here recognized for the first time. This important fault system is about 220 km long and is seismically active in the basement as well as the sedimentary cover sequence. This fault system terminates to the south near the Main Zagros Thrust and to the north at the southern boundary of the Urumieh-Dokhtar zone. The Isfahan fault system is the boundary between the northern and southern parts of Sanandaj-Sirjan zone, which have fundamentally different stratigraphy, petrology, geomorphology, and geodynamic histories. Similarities in the orientations, kinematics, and geologic histories of the Isfahan and Kazerun faults and the way they affect the magnetic basement suggest that they are related. In fact, the Isfahan fault is a continuation of the Kazerun fault across the Sanandaj-Sirjan zone that has been offset by about 50 km of dextral strike-slip displacement along the Main Zagros Thrust.

Structural Design of Systems with Safe Behavior under Single and Multiple Faults

DEFF Research Database (Denmark)

Blanke, Mogens; Staroswiecki, Marcel

2006-01-01

Handling of multiple simultaneous faults is a complex issue in fault-tolerant control. The design task is particularly made difficult by to the numerous different cases that need be analyzed. Aiming at safe fault-handling, this paper shows how structural analysis can be applied to find...... to structural analysis to disclose which faults could be isolated from a structural point of view using active fault isolation. Results from application on a marine control system illustrate the concepts....... the analytical redundancy relations for all relevant combinations of faults, and can cope with the complexity and size of a real system. Being essential for fault-tolerant control schemes that shall handle particular cases of faults/failures, fault isolation is addressed. The paper introduces an extension...

Component-based modeling of systems for automated fault tree generation

International Nuclear Information System (INIS)

Majdara, Aref; Wakabayashi, Toshio

2009-01-01

One of the challenges in the field of automated fault tree construction is to find an efficient modeling approach that can support modeling of different types of systems without ignoring any necessary details. In this paper, we are going to represent a new system of modeling approach for computer-aided fault tree generation. In this method, every system model is composed of some components and different types of flows propagating through them. Each component has a function table that describes its input-output relations. For the components having different operational states, there is also a state transition table. Each component can communicate with other components in the system only through its inputs and outputs. A trace-back algorithm is proposed that can be applied to the system model to generate the required fault trees. The system modeling approach and the fault tree construction algorithm are applied to a fire sprinkler system and the results are presented

Fault Detection and Isolation for a Supermarket Refrigeration System - Part One

DEFF Research Database (Denmark)

Yang, Zhenyu; Rasmussen, Karsten B.; Kieu, Anh T.

2011-01-01

Fault Detection and Isolation (FDI) using the Kalman Filter (KF) technique for a supermarket refrigeration system is explored. Four types of sensor fault scenarios, namely drift, offset, freeze and hard-over, are considered for two temperature sensors, and one type of parametric fault scenario, n....... The test results show that the EKF-based FDI method generally performances better and faster than the KF-based method does. However, both methods can not handle the isolation between sensor faults and parametric fault.......Fault Detection and Isolation (FDI) using the Kalman Filter (KF) technique for a supermarket refrigeration system is explored. Four types of sensor fault scenarios, namely drift, offset, freeze and hard-over, are considered for two temperature sensors, and one type of parametric fault scenario...... isolation purpose, a bank of KFs arranged by splitting measurements is constructed for sensor fault isolation, while the Multi-Model Adaptive Estimation (MMAE) method is employed to handle parametric fault isolation. All these approaches are extended and checked by using Extended KF technique afterwards...

Dead sea transform fault system reviews

CERN Document Server

Garfunkel, Zvi; Kagan, Elisa

2014-01-01

The Dead Sea transform is an active plate boundary connecting the Red Sea seafloor spreading system to the Arabian-Eurasian continental collision zone. Its geology and geophysics provide a natural laboratory for investigation of the surficial, crustal and mantle processes occurring along transtensional and transpressional transform fault domains on a lithospheric scale and related to continental breakup. There have been many detailed and disciplinary studies of the Dead Sea transform fault zone during the last?20 years and this book brings them together.This book is an updated comprehensive coverage of the knowledge, based on recent studies of the tectonics, structure, geophysics, volcanism, active tectonics, sedimentology and paleo and modern climate of the Dead Sea transform fault zone. It puts together all this new information and knowledge in a coherent fashion.

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.

Evaluation of digital fault-tolerant architectures for nuclear power plant control systems

International Nuclear Information System (INIS)

Battle, R.E.

1990-01-01

Four fault tolerant architectures were evaluated for their potential reliability in service as control systems of nuclear power plants. The reliability analyses showed that human- and software-related common cause failures and single points of failure in the output modules are dominant contributors to system unreliability. The four architectures are triple-modular-redundant (TMR), both synchronous and asynchronous, and also dual synchronous and asynchronous. The evaluation includes a review of design features, an analysis of the importance of coverage, and reliability analyses of fault tolerant systems. An advantage of fault-tolerant controllers over those not fault tolerant, is that fault-tolerant controllers continue to function after the occurrence of most single hardware faults. However, most fault-tolerant controllers have single hardware components that will cause system failure, almost all controllers have single points of failure in software, and all are subject to common cause failures. Reliability analyses based on data from several industries that have fault-tolerant controllers were used to estimate the mean-time-between-failures of fault-tolerant controllers and to predict those failures modes that may be important in nuclear power plants. 7 refs., 4 tabs

Fault tolerant control of systems with saturations

DEFF Research Database (Denmark)

Niemann, Hans Henrik

2013-01-01

This paper presents framework for fault tolerant controllers (FTC) that includes input saturation. The controller architecture known from FTC is based on the Youla-Jabr-Bongiorno-Kucera (YJBK) parameterization is extended to handle input saturation. Applying this controller architecture in connec......This paper presents framework for fault tolerant controllers (FTC) that includes input saturation. The controller architecture known from FTC is based on the Youla-Jabr-Bongiorno-Kucera (YJBK) parameterization is extended to handle input saturation. Applying this controller architecture...... in connection with faulty systems including input saturation gives an additional YJBK transfer function related to the input saturation. In the fault free case, this additional YJBK transfer function can be applied directly for optimizing the feedback loop around the input saturation. In the faulty case......, the design problem is a mixed design problem involved both parametric faults and input saturation....

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. .

Modeling of the fault-controlled hydrothermal ore-forming systems

International Nuclear Information System (INIS)

Pek, A.A.; Malkovsky, V.I.

1993-07-01

A necessary precondition for the formation of hydrothermal ore deposits is a strong focusing of hydrothermal flow as fluids move from the fluid source to the site of ore deposition. The spatial distribution of hydrothermal deposits favors the concept that such fluid flow focusing is controlled, for the most part, by regional faults which provide a low resistance path for hydrothermal solutions. Results of electric analog simulations, analytical solutions, and computer simulations of the fluid flow, in a fault-controlled single-pass advective system, confirm this concept. The influence of the fluid flow focusing on the heat and mass transfer in a single-pass advective system was investigated for a simplified version of the metamorphic model for the genesis of greenstone-hosted gold deposits. The spatial distribution of ore mineralization, predicted by computer simulation, is in reasonable agreement with geological observations. Computer simulations of the fault-controlled thermoconvective system revealed a complex pattern of mixing hydrothermal solutions in the model, which also simulates the development of the modern hydrothermal systems on the ocean floor. The specific feature of the model considered, is the development under certain conditions of an intra-fault convective cell that operates essentially independently of the large scale circulation. These and other results obtained during the study indicate that modeling of natural fault-controlled hydrothermal systems is instructive for the analysis of transport processes in man-made hydrothermal systems that could develop in geologic high-level nuclear waste repositories

Design of fault tolerant control system for steam generator using

Energy Technology Data Exchange (ETDEWEB)

Kim, Myung Ki; Seo, Mi Ro [Korea Electric Power Research Institute, Taejon (Korea, Republic of)

1998-12-31

A controller and sensor fault tolerant system for a steam generator is designed with fuzzy logic. A structure of the proposed fault tolerant redundant system is composed of a supervisor and two fuzzy weighting modulators. A supervisor alternatively checks a controller and a sensor induced performances to identify which part, a controller or a sensor, is faulty. In order to analyze controller induced performance both an error and a change in error of the system output are chosen as fuzzy variables. The fuzzy logic for a sensor induced performance uses two variables : a deviation between two sensor outputs and its frequency. Fuzzy weighting modulator generates an output signal compensated for faulty input signal. Simulations show that the proposed fault tolerant control scheme for a steam generator regulates well water level by suppressing fault effect of either controllers or sensors. Therefore through duplicating sensors and controllers with the proposed fault tolerant scheme, both a reliability of a steam generator control and sensor system and that of a power plant increase even more. 2 refs., 9 figs., 1 tab. (Author)

Novel fault tolerant modular system architecture for I and C applications

International Nuclear Information System (INIS)

Kumar, Ankit; Venkatesan, A.; Madhusoodanan, K.

2013-01-01

Novel fault tolerant 3U modular system architecture has been developed for safety related and safety critical I and C systems of the reactor. Design innovatively utilizes simplest multi-drop serial bus called Inter-Integrated Circuits (I 2 C) Bus for system operation with simplicity, fault tolerance and online maintainability (hot swap). I 2 C bus failure modes analysis was done and system design was hardened for possible failure modes. System backplane uses only passive components, dual redundant I 2 C buses, data consistency checks and geographical addressing scheme to tackle bus lock ups/stuck buses and bit flips in data transactions. Dual CPU active/standby redundancy architecture with hot swap implements tolerance for CPU software stuck up conditions and hardware faults. System cards implement hot swap for online maintainability, power supply fault containment, communication buses fault containment and I/O channel to channel isolation and independency. Typical applications for pure hardwired (without real time software) Core Temperature Monitoring System for FBRs, as a Universal Signal Conditioning System for safety related I and C systems and as a complete control system for non nuclear safety systems have also been discussed. (author)

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.

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.

Analytical Model-based Fault Detection and Isolation in Control Systems

DEFF Research Database (Denmark)

Vukic, Z.; Ozbolt, H.; Blanke, M.

1998-01-01

The paper gives an introduction and an overview of the field of fault detection and isolation for control systems. The summary of analytical (quantitative model-based) methodds and their implementation are presented. The focus is given to mthe analytical model-based fault-detection and fault...

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.

Automated fault tree analysis: the GRAFTER system

International Nuclear Information System (INIS)

Sancaktar, S.; Sharp, D.R.

1985-01-01

An inherent part of probabilistic risk assessment (PRA) is the construction and analysis of detailed fault trees. For this purpose, a fault tree computer graphics code named GRAFTER has been developed. The code system centers around the GRAFTER code. This code is used interactively to construct, store, update and print fault trees of small or large sizes. The SIMON code is used to provide data for the basic event probabilities. ENCODE is used to process the GRAFTER files to prepare input for the WAMCUT code. WAMCUT is used to quantify the top event probability and to identify the cutsets. This code system has been extensively used in various PRA projects. It has resulted in reduced manpower costs, increased QA capability, ease of documentation and it has simplified sensitivity analyses. Because of its automated nature, it is also suitable for LIVING PRA Studies which require updating and modifications during the lifetime of the plant. Brief descriptions and capabilities of the GRAFTER, SIMON and ENCODE codes are provided; an application of the GRAFTER system is outlined; and conclusions and comments on the code system are given

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

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.

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

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.

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

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

Hardwired interlock system with fault latchability and annunciation panel for electron accelerators

International Nuclear Information System (INIS)

Mukesh Kumar; Roychoudhury, P.; Nimje, V.T.

2011-01-01

A hard-wired interlock system is designed, developed, installed and tested to ensure healthy status for interlock signals, coming from the various sub-systems of electron accelerators as digital inputs. Each electron accelerator has approximately ninety-six interlock signals. Hardwired Interlock system consists of twelve-channel 19 inches rack mountable hard-wired interlock module of 4U height. Digital inputs are fed to the hard-wired interlock module in the form of 24V dc for logic 'TRUE' and 0V for logic 'FALSE'. These signals are flow signals to ensure cooling of the various sub-systems, signals from the klystron modulator system in RF Linac to ensure its healthy state to start, signals from high voltage system of DC accelerator, vacuum signals from vacuum system to ensure proper vacuum in the electron accelerator, door interlock signals, air flow signals, and area search and secure signals. This hard-wired interlock system ensures the safe start-up, fault annunciation and alarm, fault latchablity, and fail-safe operation of the electron accelerators. Safe start-up feature ensures that beam generation system can be made ON only when cooling of all the electron accelerator sub-systems are confirmed, all the fault signals of high voltage generation system are attended, proper vacuum is achieved inside the beam transport system, all the doors are closed and various areas have been searched and secured manually. Fault annunciation and alarm feature ensures that during the start up and operation of the electron accelerators, if any fault is there, that fault signal window keeps on flashing with red colour and alarm is sounded till the operator acknowledges the fault. Once acknowledged, flashing and alarm stops but display of the window in red colour remains till the operator clears the fault. Fault latchability feature ensures that if any fault has happened, accelerator cannot be started again till the operator resets that interlock signal. Fail-safe feature ensures

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

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)

3D Constraints On Fault Architecture and Strain Distribution of the Newport-Inglewood Rose Canyon and San Onofre Trend Fault Systems

Science.gov (United States)

Holmes, J. J.; Driscoll, N. W.; Kent, G. M.

2017-12-01

The Inner California Borderlands (ICB) is situated off the coast of southern California and northern Baja. The structural and geomorphic characteristics of the area record a middle Oligocene transition from subduction to microplate capture along the California coast. Marine stratigraphic evidence shows large-scale extension and rotation overprinted by modern strike-slip deformation. Geodetic and geologic observations indicate that approximately 6-8 mm/yr of Pacific-North American relative plate motion is accommodated by offshore strike-slip faulting in the ICB. The farthest inshore fault system, the Newport-Inglewood Rose Canyon (NIRC) Fault is a dextral strike-slip system that is primarily offshore for approximately 120 km from San Diego to the San Joaquin Hills near Newport Beach, California. Based on trenching and well data, the NIRC Fault Holocene slip rate is 1.5-2.0 mm/yr to the south and 0.5-1.0 mm/yr along its northern extent. An earthquake rupturing the entire length of the system could produce an Mw 7.0 earthquake or larger. West of the main segments of the NIRC Fault is the San Onofre Trend (SOT) along the continental slope. Previous work concluded that this is part of a strike-slip system that eventually merges with the NIRC Fault. Others have interpreted this system as deformation associated with the Oceanside Blind Thrust Fault purported to underlie most of the region. In late 2013, we acquired the first high-resolution 3D Parallel Cable (P-Cable) seismic surveys of the NIRC and SOT faults as part of the Southern California Regional Fault Mapping project. Analysis of stratigraphy and 3D mapping of this new data has yielded a new kinematic fault model of the area that provides new insight on deformation caused by interactions in both compressional and extensional regimes. For the first time, we can reconstruct fault interaction and investigate how strain is distributed through time along a typical strike-slip margin using 3D constraints on fault

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.

Fault Identification Algorithm Based on Zone-Division Wide Area Protection System

Directory of Open Access Journals (Sweden)

Xiaojun Liu

2014-04-01

Full Text Available As the power grid becomes more magnified and complicated, wide-area protection system in the practical engineering application is more and more restricted by the communication level. Based on the concept of limitedness of wide-area protection system, the grid with complex structure is divided orderly in this paper, and fault identification and protection action are executed in each divided zone to reduce the pressure of the communication system. In protection zone, a new wide-area protection algorithm based on positive sequence fault components directional comparison principle is proposed. The special associated intelligent electronic devices (IEDs zones which contain buses and transmission lines are created according to the installation location of the IEDs. When a fault occurs, with the help of the fault information collecting and sharing from associated zones with the fault discrimination principle defined in this paper, the IEDs can identify the fault location and remove the fault according to the predetermined action strategy. The algorithm will not be impacted by the load changes and transition resistance and also has good adaptability in open phase running power system. It can be used as a main protection, and it also can be taken into account for the back-up protection function. The results of cases study show that, the division method of the wide-area protection system and the proposed algorithm are effective.