WorldWideScience

Sample records for expert fault diagnostics

  1. Expert system for fault diagnostic in electronic devices

    Energy Technology Data Exchange (ETDEWEB)

    Benedetti, G

    1984-03-01

    Troubleshooting of electronic devices and highly complex PCBS (printed circuit boards) is an area where expert systems can be used. In addition to the difficulties intrinsic to this area it is also impossible to integrate the amount of knowledge based on experience in a traditional model. 8 references.

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

    Science.gov (United States)

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

    1990-01-01

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

  3. 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

  4. 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.

  5. 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

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

    International Nuclear Information System (INIS)

    Masoudifar, M.; AghaAmini, M.

    2001-01-01

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

  7. 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.

  8. 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.

  9. 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.

  10. BWR recirculation pump diagnostic expert system

    International Nuclear Information System (INIS)

    Chiang, S.C.; Morimoto, C.N.; Torres, M.R.

    2004-01-01

    At General Electric (GE), an on-line expert system to support maintenance decisions for BWR recirculation pumps for nuclear power plants has been developed. This diagnostic expert system is an interactive on-line system that furnishes diagnostic information concerning BWR recirculation pump operational problems. It effectively provides the recirculation pump diagnostic expertise in the plant control room continuously 24 hours a day. The expert system is interfaced to an on-line monitoring system, which uses existing plant sensors to acquire non-safety related data in real time. The expert system correlates and evaluates process data and vibration data by applying expert rules to determine the condition of a BWR recirculation pump system by applying knowledge based rules. Any diagnosis will be automatically displayed, indicating which pump may have a problem, the category of the problem, and the degree of concern expressed by the validity index and color hierarchy. The rules incorporate the expert knowledge from various technical sources such as plant experience, engineering principles, and published reports. These rules are installed in IF-THEN formats and the resulting truth values are also expressed in fuzzy terms and a certainty factor called a validity index. This GE Recirculation Pump Expert System uses industry-standard software, hardware, and network access to provide flexible interfaces with other possible data acquisition systems. Gensym G2 Real-Time Expert System is used for the expert shell and provides the graphical user interface, knowledge base, and inference engine capabilities. (author)

  11. 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)

  12. 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)

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

    Science.gov (United States)

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

    2017-11-01

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

  14. Case-Based Fault Diagnostic System

    International Nuclear Information System (INIS)

    Mohamed, A.H.

    2014-01-01

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

  15. Diagnostic expert system in the PF LINAC

    International Nuclear Information System (INIS)

    Abe, Isamu; Nakahara, Kazuo; Kitamura, Masaharu.

    1992-01-01

    A prototype diagnostic expert system (ES) was developed for the Photon Factory 2.5-GeV electron/positron LINAC injector system. The ES has been on-lined with the conventional linac computer network for receiving real data. This project was undertaken in an attempt to reduce the linac operator's mental workload, diagnosis duties, and to explore Artificial Intelligence (AI) technologies. The outlook for ES and its problems, and what has been achieved are outlined in this presentation. (author)

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

    Energy Technology Data Exchange (ETDEWEB)

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

    1997-08-15

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

  17. REXS : A financial risk diagnostic expert system

    Directory of Open Access Journals (Sweden)

    W. Richter

    2012-01-01

    Full Text Available

    ENGLISH ABSTRACT: Artificial intelligence techniques are rapidly emerging as important contributors to more effective management. One of the greatest growth areas probably lies in the use of Expert System methodology for supporting managerial decision processes.
    Existing Decision Support Systems often attempt to apply analytical techniques in combination with traditional data access and retrieval functions. One of the problems usually encountered while developing such decision support systems is the need to transform an unstructured problem environment into a structured analytical model. Using an expert system approach to strategic decision making in such unstructured problem environments may provide significant advantages.
    The financial Risk diagnostic EXpert System (REXS concentrates on Financial Risk Analysis. Based on a Forecasting Model the system will, with the support of several expert system knowledge bases, attempt to evaluate the financial risk of a business and provide guidelines for improvement.

    AFRIKAANSE OPSOMMING: Tegnieke gebaseer op Kunsmatige Intelligensie toon tans die belofte om belangrike bydraes te maak tot meerBestaande Besluitsteunstelsels poog dikwels om analitiese tegnieke en lradisionele datatoegang- en onttrekkingsfunksies te kombineer. Een van die probleme wat gewoonlik ondervind word gedurende die ontwikkeling van '0 besluitsteunstelsel bestaan uit die behoefte om 'n ongestruktueerde probleemomgewing te transformeer na 'n gestruktueerde analitiese model. 'n Ekspertstelselbenadering lot strategiese besluitneming in 'n ongeSlruktureerde probleemomgewing mag betekenisvolle voordele inhou.
    Die "financial Risk diagnostic EXpert System (REXS" konsentreer op fmansiele risiko-analise. Uitgaande vanaf 'n Vooruitskattingsmode~ en deur gebruik te maak van verskeie ekspertstelselkennisbasisse, poog die stelsel om die fmansiele risiko van 'n onderneming te evalueer en riglyne vir moontlike verbetering

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

    International Nuclear Information System (INIS)

    Liang Jie; Cai Qi; Chu Zhuli; Wang Haiping

    2013-01-01

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

  19. Atom and the fault: experts, earthquakes, and nuclear power

    International Nuclear Information System (INIS)

    Meehan, R.L.

    1984-01-01

    A narrative account of the geology expert's role in an environmental controversy focuses on the problem of siting nuclear power plants near geologic faults and the conflicting testimony delivered by equally sincere consultants. The author examines the problem of faults and their significance to reactor safety, and concludes that part of the controversy and regulatory indecision are due to the lack of an accepted scientific standard for risk. He explores the historical and social role of the principal professional groups (geologists and engineers) in the debate, and concludes that concerns at some sites were warranted. Scientific advocacy, he feels, serves a useful function in the hearing process, and that the representation for intervenors has been generally good. 18 references, 10 figures

  20. Model of critical diagnostic reasoning: achieving expert clinician performance.

    Science.gov (United States)

    Harjai, Prashant Kumar; Tiwari, Ruby

    2009-01-01

    Diagnostic reasoning refers to the analytical processes used to determine patient health problems. While the education curriculum and health care system focus on training nurse clinicians to accurately recognize and rescue clinical situations, assessments of non-expert nurses have yielded less than satisfactory data on diagnostic competency. The contrast between the expert and non-expert nurse clinician raises the important question of how differences in thinking may contribute to a large divergence in accurate diagnostic reasoning. This article recognizes superior organization of one's knowledge base, using prototypes, and quick retrieval of pertinent information, using similarity recognition as two reasons for the expert's superior diagnostic performance. A model of critical diagnostic reasoning, using prototypes and similarity recognition, is proposed and elucidated using case studies. This model serves as a starting point toward bridging the gap between clinical data and accurate problem identification, verification, and management while providing a structure for a knowledge exchange between expert and non-expert clinicians.

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

    NARCIS (Netherlands)

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

    2012-01-01

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

  2. 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.

  3. 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.

  4. 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.

  5. 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

  6. An expert system for diesel generator diagnostics

    International Nuclear Information System (INIS)

    Bley, D.C.; Read, J.W.; Kaplan, S.; Liming, J.K.; Brosee, N.M.; Hanley, D.W.

    1987-01-01

    The idea of developing artificial intelligence (AI) systems to capture the knowledge of human experts is receiving much attention these days. The idea is even more attractive when important expertise resides within a single individual, especially one who is nearing retirement and who has not otherwise recorded or passed along his important knowledge and thought processes. The diesel generators at Pilgrim Nuclear Power Station have performed exceptionally well, primarily due to the care and attention of one man. Therefore, the authors are constructing an expert system for the diagnosis of diesel generator problems at Pilgrim. This paper includes a description of the expert system design and operation, examples from the knowledge base, and sample diagnoses, so the reader can observe the process in action

  7. 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.

  8. 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

  9. Fault-tolerant and Diagnostic Methods for Navigation

    DEFF Research Database (Denmark)

    Blanke, Mogens

    2003-01-01

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

  10. An on-line diagnostic expert system

    International Nuclear Information System (INIS)

    Felkel, L.

    1987-01-01

    As experience with on-line information systems, experts systems and artificial intelligence tools grows, the authors retreat from the first euphoria that AI could help them solve the problem they were unable to solve with conventional programming. The major effort of the development time goes into building the knowledge-base. There is no such thing as a generic knowledge-base for nuclear power plants as there is, for example, for the diagnosis of a Boeing 747 aircraft. AI-methods, tools and hardware are still in a state which does not optimally lend itself to real-time application. The ability of developing prototype systems to investigate variants otherwise too costly to justify is one advantage that the authors gladly accept. Last, but no least the tools provide a flexible and adaptable user interface (desktop window systems) etc. The development of such tools in a project would be prohibitive and room for experimentation would be limited

  11. SIDES - Segment Interconnect Diagnostic Expert System

    International Nuclear Information System (INIS)

    Booth, A.W.; Forster, R.; Gustafsson, L.; Ho, N.

    1989-01-01

    It is well known that the FASTBUS Segment Interconnect (SI) provides a communication path between two otherwise independent, asynchronous bus segments. The SI is probably the most important module in any FASTBUS data acquisition network since it's failure to function can cause whole segments of the network to be inaccessible and sometimes inoperable. This paper describes SIDES, an intelligent program designed to diagnose SI's both in situ as they operate in a data acquisition network, and in the laboratory in an acceptance/repair environment. The paper discusses important issues such as knowledge acquisition; extracting knowledge from human experts and other knowledge sources. SIDES can benefit high energy physics experiments, where SI problems can be diagnosed and solved more quickly. Equipment pool technicians can also benefit from SIDES, first by decreasing the number of SI's erroneously turned in for repair, and secondly as SIDES acts as an intelligent assistant to the technician in the diagnosis and repair process

  12. An Embedded Rule-Based Diagnostic Expert System in Ada

    Science.gov (United States)

    Jones, Robert E.; Liberman, Eugene M.

    1992-01-01

    Ada is becoming an increasingly popular programming language for large Government-funded software projects. Ada with it portability, transportability, and maintainability lends itself well to today's complex programming environment. In addition, expert systems have also assumed a growing role in providing human-like reasoning capability expertise for computer systems. The integration is discussed of expert system technology with Ada programming language, especially a rule-based expert system using an ART-Ada (Automated Reasoning Tool for Ada) system shell. NASA Lewis was chosen as a beta test site for ART-Ada. The test was conducted by implementing the existing Autonomous Power EXpert System (APEX), a Lisp-based power expert system, in ART-Ada. Three components, the rule-based expert systems, a graphics user interface, and communications software make up SMART-Ada (Systems fault Management with ART-Ada). The rules were written in the ART-Ada development environment and converted to Ada source code. The graphics interface was developed with the Transportable Application Environment (TAE) Plus, which generates Ada source code to control graphics images. SMART-Ada communicates with a remote host to obtain either simulated or real data. The Ada source code generated with ART-Ada, TAE Plus, and communications code was incorporated into an Ada expert system that reads the data from a power distribution test bed, applies the rule to determine a fault, if one exists, and graphically displays it on the screen. The main objective, to conduct a beta test on the ART-Ada rule-based expert system shell, was achieved. The system is operational. New Ada tools will assist in future successful projects. ART-Ada is one such tool and is a viable alternative to the straight Ada code when an application requires a rule-based or knowledge-based approach.

  13. Reactor accident diagnostic expert system: DISKET

    International Nuclear Information System (INIS)

    Yoshida, Kazuo; Yokobayashi, Masao

    1989-11-01

    A reactor accident diagnostic system DISKET has been developed to identify the cause and the type of an abnormal transient of a nuclear power plant. The system is based on the knowledge engineering and consists of an inference engine IERIAS and a knowledge base. The main features of DISKET are the following: Time-varying characteristics of transient can be treated and knowledge base can be divided into several knowledge units to handle a lot of rules effectively. This report has been provided for the convenience of DISKET's users and consists of three parts. The first part is the description of the whole system, the details of the knowledge base of DISKET are described in the second part, and how to use the DISKET system is explained in the third part. (author)

  14. A fault diagnosis and operation advising cooperative expert system based on multi-agent technology

    Energy Technology Data Exchange (ETDEWEB)

    Zhao, W.; Bai, X.; Ding, J.; Fang, Z.; Li, Z. [China Electric Power Research Inst., Haidian District, Beijing (China)

    2006-07-01

    Power systems are becoming more and more complex. In addition, the amount of real-time alarm messages from the supervisory control and data acquisition, energy management systems and wide area measurement systems about switchgear and protection are also increasing to a point far beyond the operator's capacity to digest the information. Research and development of a fault diagnosis system is necessary for the timely identification of fault or malfunctioning devices and for realizing the automation functions of dynamic supervisory control system. The prevailing fault diagnosis approaches in power systems include the expert system, artificial neural network, and fault diagnosis based on optimal theory. This paper discussed the advantages and disadvantages of each of these approaches for diagnosing faults. The paper also proposed a new fault diagnosis and operational processing approach based on a cooperative expert system combined with a multi-agent architecture. For solving complex and correlative faults, the cooperative expert system can overcome the deficiency of a single expert system. It can be used not only for diagnosing complex faults in real time but also in providing timely operational advice. The proposed system has been used successfully in a district power grid in China's Shangdong province for a year. 9 refs., 4 figs.

  15. An expert system for the quantification of fault rates in construction fall accidents.

    Science.gov (United States)

    Talat Birgonul, M; Dikmen, Irem; Budayan, Cenk; Demirel, Tuncay

    2016-01-01

    Expert witness reports, prepared with the aim of quantifying fault rates among parties, play an important role in a court's final decision. However, conflicting fault rates assigned by different expert witness boards lead to iterative objections raised by the related parties. This unfavorable situation mainly originates due to the subjectivity of expert judgments and unavailability of objective information about the causes of accidents. As a solution to this shortcoming, an expert system based on a rule-based system was developed for the quantification of fault rates in construction fall accidents. The aim of developing DsSafe is decreasing the subjectivity inherent in expert witness reports. Eighty-four inspection reports prepared by the official and authorized inspectors were examined and root causes of construction fall accidents in Turkey were identified. Using this information, an evaluation form was designed and submitted to the experts. Experts were asked to evaluate the importance level of the factors that govern fall accidents and determine the fault rates under different scenarios. Based on expert judgments, a rule-based expert system was developed. The accuracy and reliability of DsSafe were tested with real data as obtained from finalized court cases. DsSafe gives satisfactory results.

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

    Directory of Open Access Journals (Sweden)

    Chwan-Lu Tseng

    2014-01-01

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

  17. Eight meeting of the ITER diagnostic expert group

    International Nuclear Information System (INIS)

    Costley, A.E.; Young, K.M.

    1998-01-01

    The 8. Meeting of the ITER Diagnostics Expert Group which was held in San Diego, February 1998 had two main technical goals: to discuss the status and plans for developing kinetic control, and to review the current status of the design of the magnetic system

  18. Design of a real-time fault diagnosis expert system for the EAST cryoplant

    Energy Technology Data Exchange (ETDEWEB)

    Zhou Zhiwei, E-mail: zzw@ipp.ac.cn [Institute of Plasma Physics, Chinese Academy of Sciences, Hefei, Anhui (China); Zhuang Ming, E-mail: zhm@ipp.ac.cn [Institute of Plasma Physics, Chinese Academy of Sciences, Hefei, Anhui (China); Lu Xiaofei, E-mail: luxf1212@mail.ustc.edu.cn [Institute of Plasma Physics, Chinese Academy of Sciences, Hefei, Anhui (China); Hu Liangbing, E-mail: huliangbing@ipp.ac.cn [Institute of Plasma Physics, Chinese Academy of Sciences, Hefei, Anhui (China); Xia Genhai, E-mail: xgh@ipp.ac.cn [Institute of Plasma Physics, Chinese Academy of Sciences, Hefei, Anhui (China)

    2012-12-15

    Highlights: Black-Right-Pointing-Pointer An expert system of real-time fault diagnosis for EAST cryoplant is designed. Black-Right-Pointing-Pointer Knowledge base is built via fault tree analysis based on our fault experience. Black-Right-Pointing-Pointer It can make up the deficiency of safety monitoring in cryogenic DCS. Black-Right-Pointing-Pointer It can help operators to find the fault causes and give operation suggestion. Black-Right-Pointing-Pointer It plays a role of operators training in certain degree. - Abstract: The EAST cryoplant consists of a 2 kW/4 K helium refrigerator and a helium distribution system. It is a complex process system which involves many process variables and cryogenic equipments. Each potential fault or abnormal event may influence stability and safety of the cryogenic system, thereby disturbing the fusion experiment. The cryogenic control system can monitor the process data and detect process alarms, but it is difficult to effectively diagnose the fault causes and provide operation suggestions to operators when anomalies occur. Therefore, a real-time fault diagnosis expert system is essential for a safe and steady operation of EAST cryogenic system. After a brief description of the EAST cryoplant and its control system, the structure design of the cryogenic fault diagnosis expert system is proposed. Based on the empirical knowledge, the fault diagnosis model is built adopting fault tree analysis method which considers the uncertainty. The knowledge base and the inference machine are presented in detail. A cross-platform integrated development environment Qt Creator and MySQL database have been used to develop the system. The proposed expert system has a fine graphic user interface for monitoring and operation. Preliminary test was conducted and the results found to be satisfactory.

  19. Design of a real-time fault diagnosis expert system for the EAST cryoplant

    International Nuclear Information System (INIS)

    Zhou Zhiwei; Zhuang Ming; Lu Xiaofei; Hu Liangbing; Xia Genhai

    2012-01-01

    Highlights: ► An expert system of real-time fault diagnosis for EAST cryoplant is designed. ► Knowledge base is built via fault tree analysis based on our fault experience. ► It can make up the deficiency of safety monitoring in cryogenic DCS. ► It can help operators to find the fault causes and give operation suggestion. ► It plays a role of operators training in certain degree. - Abstract: The EAST cryoplant consists of a 2 kW/4 K helium refrigerator and a helium distribution system. It is a complex process system which involves many process variables and cryogenic equipments. Each potential fault or abnormal event may influence stability and safety of the cryogenic system, thereby disturbing the fusion experiment. The cryogenic control system can monitor the process data and detect process alarms, but it is difficult to effectively diagnose the fault causes and provide operation suggestions to operators when anomalies occur. Therefore, a real-time fault diagnosis expert system is essential for a safe and steady operation of EAST cryogenic system. After a brief description of the EAST cryoplant and its control system, the structure design of the cryogenic fault diagnosis expert system is proposed. Based on the empirical knowledge, the fault diagnosis model is built adopting fault tree analysis method which considers the uncertainty. The knowledge base and the inference machine are presented in detail. A cross-platform integrated development environment Qt Creator and MySQL database have been used to develop the system. The proposed expert system has a fine graphic user interface for monitoring and operation. Preliminary test was conducted and the results found to be satisfactory.

  20. Telecontrol - Expert systems. Real-time monitoring and remote diagnostic

    Energy Technology Data Exchange (ETDEWEB)

    Lam, A.

    1996-09-01

    The role of expert systems in programming simple and complex tasks in utilities companies was discussed with examples from B.C. Hydro, where expert systems have been used in such diverse applications as an in-house programmable logic controller (PLC) training course, and a machine audit on a 150 MW steam turbine generating unit at their Burrard Thermal Generating Plant. The PLC tutoring program uses expert system technology for the air blast circuit breakers` air drier system, for individualized on-site training. The steam turbine audits (an eight-month long project) were performed remotely by dialing an on-site computer configured with customized expert software. Details of these, and other potential applications, such as transformer monitoring and diagnostics, circuit breaker performance analysis, and information management, were described.

  1. [Development of expert diagnostic system for common respiratory diseases].

    Science.gov (United States)

    Xu, Wei-hua; Chen, You-ling; Yan, Zheng

    2014-03-01

    To develop an internet-based expert diagnostic system for common respiratory diseases. SaaS system was used to build architecture; pattern of forward reasoning was applied for inference engine design; ASP.NET with C# from the tool pack of Microsoft Visual Studio 2005 was used for website-interview medical expert system.The database of the system was constructed with Microsoft SQL Server 2005. The developed expert system contained large data memory and high efficient function of data interview and data analysis for diagnosis of various diseases.The users were able to perform this system to obtain diagnosis for common respiratory diseases via internet. The developed expert system may be used for internet-based diagnosis of various respiratory diseases,particularly in telemedicine setting.

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

    International Nuclear Information System (INIS)

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

    1990-01-01

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

  3. 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.

  4. Study of expert system of fault diagnosis for nuclear power plant

    International Nuclear Information System (INIS)

    Chen Zhihui; Xia Hong; Liu Miao

    2005-01-01

    Based on the fault features of Nuclear Power Plant, the ES (expert system) of fault diagnosis has been programmed. The knowledge in the ES adopts the production systems, which can express the certain and uncertain knowledge. For certain knowledge, the simple reasoning mechanism of prepositional logic is adopted. For the uncertain knowledge, CF (certain factor) is used to express the uncertain, thus to set up the reasoning mechanism. In order to solve the 'bottleneck' problem for knowledge acquisition, rough set theory is incorporated into the fault diagnose system and the reduction algorithm based on the discernibility matrix is improved. In the improved algorithm, the measure of attribute importance first calculate the attribute which have the same value in the same decision-sort, then calculate the degrees of attribute in the discernibility matrix. Several different faults have been diagnosed on some emulator with this expert system. (authors)

  5. 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.

  6. 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)

  7. Expert system application to fault diagnosis and procedure synthesis

    International Nuclear Information System (INIS)

    Hajek, B.K.; Hashemi, S.; Bhatnagar, R.; Miller, D.W.; Stasenko, J.

    1987-01-01

    Two knowledge based systems have been developed to detect plant faults, to validate sensor data in a nuclear power plant, and to synthesize procedures to assure safety goals are met when a transient occurs. These two systems are being combined into a single system through a Plant Status Monitoring System (PSMS) and a common data base accessed by all the components of the integrated system. The system is designed to sit on top of an existing Safety Parameter Display System (SPDS), and to use the existing data acquisition and data control software of the SPDS. The integrated system will communicate with the SPDS software through a single database. This database will receive sensor values and equipment status indications in a form acceptable to the knowledge based system and according to an update plan designed specifically for the system

  8. Neural network based expert system for fault diagnosis of particle accelerators

    International Nuclear Information System (INIS)

    Dewidar, M.M.

    1997-01-01

    Particle accelerators are generators that produce beams of charged particles, acquiring different energies, depending on the accelerator type. The MGC-20 cyclotron is a cyclic particle accelerator used for accelerating protons, deuterons, alpha particles, and helium-3 to different energies. Its applications include isotope production, nuclear reaction, and mass spectroscopy studies. It is a complicated machine, it consists of five main parts, the ion source, the deflector, the beam transport system, the concentric and harmonic coils, and the radio frequency system. The diagnosis of this device is a very complex task. it depends on the conditions of 27 indicators of the control panel of the device. The accurate diagnosis can lead to a high system reliability and save maintenance costs. so an expert system for the cyclotron fault diagnosis is necessary to be built. In this thesis , a hybrid expert system was developed for the fault diagnosis of the MGC-20 cyclotron. Two intelligent techniques, multilayer feed forward back propagation neural network and the rule based expert system, are integrated as a pre-processor loosely coupled model to build the proposed hybrid expert system. The architecture of the developed hybrid expert system consists of two levels. The first level is two feed forward back propagation neural networks, used for isolating the faulty part of the cyclotron. The second level is the rule based expert system, used for troubleshooting the faults inside the isolated faulty part. 4-6 tabs., 4-5 figs., 36 refs

  9. 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)

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

    CERN Document Server

    Girone, Mario; Pezzetti, Marco

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

  11. 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.

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

    NARCIS (Netherlands)

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

    2015-01-01

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

  13. 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.

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

    Science.gov (United States)

    Xu, Jiuping; Zhong, Zhengqiang; Xu, Lei

    2015-10-01

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

  15. Research on alarm triggered fault-diagnosis expert system for U-shaped tube breaking accident of steam generators

    International Nuclear Information System (INIS)

    Qian Hong; Luo Jianbo; Jin Weixiao; Zhou Jinming; Wang Du

    2015-01-01

    According to the U-shaped tube breaking accident of steam generator (SGTR), this paper designs a fault-diagnosis expert system based on the alarm triggering. By analyzing the fault mechanism of SGTR accidents, the fault symptom is obtained. The parameters of the belief rule are set up based on the simulation experiment. The information fusion is conducted on the fault-diagnosis results from multiple expert systems to obtain the final diagnose result. The test result shows that the expert system can diagnose the SGTR accident accurately and rapidly, and provide with the operation guidance. (authors)

  16. The structure of expert diagnostic knowledge in occupational medicine.

    Science.gov (United States)

    Harber, P; McCoy, J M; Shimozaki, S; Coffman, P; Bailey, K

    1991-01-01

    Development of an artificial intelligence expert system for diagnosing occupational lung disease requires explicit specification of the structure of knowledge necessary in clinical occupational medicine independent of the process by which the knowledge is utilized. Furthermore, explicit recognition of sources of uncertainty is necessary. Seven categories of knowledge define the diagnostic knowledge base in occupational pulmonary medicine. These include four objects (jobs, industries, exposures, and diseases) and three relationships between pairs of objects. This analysis demonstrates some of the unique aspects of occupational medicine expertise.

  17. Development of the Diagnostic Expert System for Tea Processing

    Science.gov (United States)

    Yoshitomi, Hitoshi; Yamaguchi, Yuichi

    A diagnostic expert system for tea processing which can presume the cause of the defect of the processed tea was developed to contribute to the improvement of tea processing. This system that consists of some programs can be used through the Internet. The inference engine, the core of the system adopts production system which is well used on artificial intelligence, and is coded by Prolog as the artificial intelligence oriented language. At present, 176 rules for inference have been registered on this system. The system will be able to presume better if more rules are added to the system.

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

    International Nuclear Information System (INIS)

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

    2009-01-01

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

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2010-05-30

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

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

    International Nuclear Information System (INIS)

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

    1996-01-01

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

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

    International Nuclear Information System (INIS)

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

    1997-01-01

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

  2. Simulation-based expert system for nuclear reactor control and diagnostics. Progress report

    International Nuclear Information System (INIS)

    Lee, J.C.; Martin, W.R.

    1986-01-01

    This research concerns the development of artificial intelligence (AI) techniques suitable for application to the diagnostics and control of nuclear power plant systems. The overall objective of the current effort is to build a prototype simulation-based expert system for diagnosing accidents in nuclear reactors. The system is being designed to analyze plant data heuristically using fuzzy logic to form a set of hypotheses about a particular transient. Hypothesis testing, fault magnitude estimation and transient analysis is performed using simulation programs to model plant behavior. An adaptive learning technique has been developed for achieving accurate simulations of plant dynamics using low-order physical models of plant components. The results of the diagnostics and simulation analysis of the plant transient are to be analyzed by an expert system for final diagnoses and control guidance. To date, significant progress has been made toward achieving the primary goals of this project. Based on a critical safety functions approach, an overall design for the nuclear plant expert system has been developed. The methodology for performing diagnostic reasoning on plant signals has been developed and the algorithms implemented and tested. A methodology for utilizing the information contained in the physical models of plant components has also been developed. This work included the derivation of a unique Kalman filtering algorithm for using power plant data to systematically improve on-line simulations through the judicious adjustment of key model parameters. A few simulation models of key plant components have been developed and implemented to demonstrate the method on a realistic accident scenario. The chosen transient is a loss of feed flow exasperated by a stuck open relief valve, similar to the initiating event of the Three Mile Island Unit 2 accident in 1979

  3. The integration of expert-defined importance factors to enrich Bayesian Fault Tree Analysis

    International Nuclear Information System (INIS)

    Darwish, Molham; Almouahed, Shaban; Lamotte, Florent de

    2017-01-01

    This paper proposes an analysis of a hybrid Bayesian-Importance model for system designers to improve the quality of services related to Active Assisted Living Systems. The proposed model is based on two factors: failure probability measure of different service components and, an expert defined degree of importance that each component holds for the success of the corresponding service. The proposed approach advocates the integration of expert-defined importance factors to enrich the Bayesian Fault Tree Analysis (FTA) approach. The evaluation of the proposed approach is conducted using the Fault Tree Analysis formalism where the undesired state of a system is analyzed using Boolean logic mechanisms to combine a series of lower-level events.

  4. Intelligent monitoring of water chemistry - Diagnostic expert system DIWATM

    International Nuclear Information System (INIS)

    Metzner, W.; Streit, K.

    2002-01-01

    For fast and comprehensive evaluation of power plant water chemistry conditions and reliable diagnosis in the event of disturbances considerable advantages are provided by employment of the Diagnostic Expert System DIWA. The interface to the process control system (I and C) and the integration of the DIWA system in the office PC network are the preconditions that DIWA operates as a monitoring system in real time. The performance of diagnosis, which are processed by a fuzzy-logic-supported knowledge base ensures not only the detection of all disturbances but also different analyses of the plant operation mode. By editing the knowledge base the Al of the system can increase without system programming. (authors)

  5. 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)

  6. 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)

  7. 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.

  8. 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...

  9. Diagnostic probability function for acute coronary heart disease garnered from experts' tacit knowledge.

    Science.gov (United States)

    Steurer, Johann; Held, Ulrike; Miettinen, Olli S

    2013-11-01

    Knowing about a diagnostic probability requires general knowledge about the way in which the probability depends on the diagnostic indicators involved in the specification of the case at issue. Diagnostic probability functions (DPFs) are generally unavailable at present. Our objective was to illustrate how diagnostic experts' case-specific tacit knowledge about diagnostic probabilities could be garnered in the form of DPFs. Focusing on diagnosis of acute coronary heart disease (ACHD), we presented doctors with extensive experience in hospitals' emergency departments a set of hypothetical cases specified in terms of an inclusive set of diagnostic indicators. We translated the medians of these experts' case-specific probabilities into a logistic DPF for ACHD. The principal result was the experts' typical diagnostic probability for ACHD as a joint function of the set of diagnostic indicators. A related result of note was the finding that the experts' probabilities in any given case had a surprising degree of variability. Garnering diagnostic experts' case-specific tacit knowledge about diagnostic probabilities in the form of DPFs is feasible to accomplish. Thus, once the methodology of this type of work has been "perfected," practice-guiding diagnostic expert systems can be developed. Copyright © 2013 Elsevier Inc. All rights reserved.

  10. 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.

  11. Strategies for adding adaptive learning mechanisms to rule-based diagnostic expert systems

    Science.gov (United States)

    Stclair, D. C.; Sabharwal, C. L.; Bond, W. E.; Hacke, Keith

    1988-01-01

    Rule-based diagnostic expert systems can be used to perform many of the diagnostic chores necessary in today's complex space systems. These expert systems typically take a set of symptoms as input and produce diagnostic advice as output. The primary objective of such expert systems is to provide accurate and comprehensive advice which can be used to help return the space system in question to nominal operation. The development and maintenance of diagnostic expert systems is time and labor intensive since the services of both knowledge engineer(s) and domain expert(s) are required. The use of adaptive learning mechanisms to increment evaluate and refine rules promises to reduce both time and labor costs associated with such systems. This paper describes the basic adaptive learning mechanisms of strengthening, weakening, generalization, discrimination, and discovery. Next basic strategies are discussed for adding these learning mechanisms to rule-based diagnostic expert systems. These strategies support the incremental evaluation and refinement of rules in the knowledge base by comparing the set of advice given by the expert system (A) with the correct diagnosis (C). Techniques are described for selecting those rules in the in the knowledge base which should participate in adaptive learning. The strategies presented may be used with a wide variety of learning algorithms. Further, these strategies are applicable to a large number of rule-based diagnostic expert systems. They may be used to provide either immediate or deferred updating of the knowledge base.

  12. Adaptive neural network/expert system that learns fault diagnosis for different structures

    Science.gov (United States)

    Simon, Solomon H.

    1992-08-01

    Corporations need better real-time monitoring and control systems to improve productivity by watching quality and increasing production flexibility. The innovative technology to achieve this goal is evolving in the form artificial intelligence and neural networks applied to sensor processing, fusion, and interpretation. By using these advanced Al techniques, we can leverage existing systems and add value to conventional techniques. Neural networks and knowledge-based expert systems can be combined into intelligent sensor systems which provide real-time monitoring, control, evaluation, and fault diagnosis for production systems. Neural network-based intelligent sensor systems are more reliable because they can provide continuous, non-destructive monitoring and inspection. Use of neural networks can result in sensor fusion and the ability to model highly, non-linear systems. Improved models can provide a foundation for more accurate performance parameters and predictions. We discuss a research software/hardware prototype which integrates neural networks, expert systems, and sensor technologies and which can adapt across a variety of structures to perform fault diagnosis. The flexibility and adaptability of the prototype in learning two structures is presented. Potential applications are discussed.

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

    Directory of Open Access Journals (Sweden)

    E. L. Ntantis

    2016-01-01

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

  14. Problem-solving strategies in psychiatry: differences between experts and novices in diagnostic accuracy and reasoning.

    Science.gov (United States)

    Gabriel, Adel; Violato, Claudio

    2013-01-01

    The purpose of this study was to examine and compare diagnostic success and its relationship with the diagnostic reasoning process between novices and experts in psychiatry. Nine volunteers, comprising five expert psychiatrists and four clinical clerks, completed a think-aloud protocol while attempting to make a DSM-IV (Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition) diagnosis of a selected case with both Axis I and Axis III diagnoses. Expert psychiatrists made significantly more successful diagnoses for both the primary psychiatric and medical diagnoses than clinical clerks. Expert psychiatrists also gave fewer differential options. Analyzing the think-aloud protocols, expert psychiatrists were much more organized, made fewer mistakes, and utilized significantly less time to access their knowledge than clinical clerks. Both novices and experts seemed to use the hypothetic-deductive and scheme-inductive approaches to diagnosis. However, experts utilized hypothetic-deductive approaches significantly more often than novices. The hypothetic-deductive diagnostic strategy was utilized more than the scheme-inductive approach by both expert psychiatrists and clinical clerks. However, a specific relationship between diagnostic reasoning and diagnostic success could not be identified in this small pilot study. The author recommends a larger study that would include a detailed analysis of the think-aloud protocols.

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

    Science.gov (United States)

    Lu, Feng; Huang, Jinquan; Xing, Yaodong

    2012-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Yaodong Xing

    2012-08-01

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

  17. An investigation into the use of ''expert systems'' for system-wide diagnostics

    International Nuclear Information System (INIS)

    Booth, A.W.; Carroll, J.T.

    1987-01-01

    This paper has explained how expert systems function and how they might be used to provide a FASTBUS system-wide diagnostic program. The authors propose that the system be used to diagnose the FASTBUS system at FERMILAB's CDF experiment. There are many important areas which have not been addressed in great detail in this paper (such as the roles of the knowledge engineer and the expert during the knowledge acquisition phase), but the central idea of the embodiment of an expert skill in a computer is clear. Development of a system-wide diagnostic program requires building knowledge from all our system experts, into the system. To expand the expert system beyond its network diagnostic ability, to include finding faulty modules would be worthwhile. Having an ''intelligent'' assistant who is on shift 24 hours each day would relieve the ''real'' experts from laborious, time-consuming and sometimes repetitive tasks undertaken during the debugging process. The system could also provide a testbed for evaluation and comparison when considering future expert-system applications such as ''run-control'' and ''data analysis''. In the context of a system-wide diagnostic program, an ''expert system'' is not intended to replace human experts but simply to help them. It is envisaged that there will always be important interaction between the human expert and the ''expert system''. The incremental development of the ''expert system'' should ensure that it is useful in the short term (by debugging to the S.I./segment level for example), and even more useful in the medium to longer term as it acquires more and more knowledge and the ability to debug to the module level. Expert systems exist and are working successfully in many problem domains. See the bibliography for examples of ''expert systems'' built in the high energy physics environment

  18. Expert system for fault diagnosis in process control valves using fuzzy-logic

    International Nuclear Information System (INIS)

    Carneiro, Alvaro L.G.; Porto Junior, Almir C.S.

    2013-01-01

    The models of asset maintenance of a process plant basically are classified in corrective maintenance, preventive, predictive and proactive (online). The corrective maintenance is the elementary and most obvious way of the maintenance models. The preventive maintenance consists in a fault prevention work, based on statistical studies that can lead to low efficiency or even an unexpected shutdown of the plant. Predictive maintenance aims to prevent equipment or systems failures through monitoring and tracking of parameters, allowing continuous operation as long as possible. The proactive maintenance usually includes predictive maintenance, emphasizing the root cause analysis of the failure. The maintenance predictive/proactive planning frequently uses software that integrates data from different systems, which facilitates a quick and effective decision- making. In nuclear plants this model has an important role regarding the reliability of equipment and systems. The main focus of this work is to study the development of a model of non-intrusive monitoring and diagnosis applied to process control valves using artificial intelligence by fuzzy logic technique, contributing in the development of predictive methodologies identifying faults in incipient state. The control valve analyzed belongs to a steam plant which simulates the secondary circuit of a PWR nuclear reactor - Pressurized Water Reactor. This study makes use of MATLAB language through the fuzzy logic toolbox which uses the method of inference Mamdani, acting by fuzzy conjunction, through Triangular Norms (t-norm) and Triangular Conorms (t-conorm). As input variables are used air pressure and displacement of the valve stem. Input data coming into the fuzzy system by graph of the automation system Delta V ® available in the plant, which receives a signal of electric current from an 'intelligent' positioned installed on the valve. The output variable is the 'status' of the valve. Through a rule base

  19. Expert system for fault diagnosis in process control valves using fuzzy-logic

    Energy Technology Data Exchange (ETDEWEB)

    Carneiro, Alvaro L.G., E-mail: carneiro@ipen.br [Instituto de Pesquisas Energeticas e Nucleares (IPEN/CNEN-SP), Sao Paulo, SP (Brazil); Porto Junior, Almir C.S., E-mail: almir@ctmsp.mar.mil.br [Centro Tecnologico da Marinha em Sao Paulo (CIANA/CTMSP), Ipero, SP (Brazil). Centro de Instrucao e Adestramento Nuclear de ARAMAR

    2013-07-01

    The models of asset maintenance of a process plant basically are classified in corrective maintenance, preventive, predictive and proactive (online). The corrective maintenance is the elementary and most obvious way of the maintenance models. The preventive maintenance consists in a fault prevention work, based on statistical studies that can lead to low efficiency or even an unexpected shutdown of the plant. Predictive maintenance aims to prevent equipment or systems failures through monitoring and tracking of parameters, allowing continuous operation as long as possible. The proactive maintenance usually includes predictive maintenance, emphasizing the root cause analysis of the failure. The maintenance predictive/proactive planning frequently uses software that integrates data from different systems, which facilitates a quick and effective decision- making. In nuclear plants this model has an important role regarding the reliability of equipment and systems. The main focus of this work is to study the development of a model of non-intrusive monitoring and diagnosis applied to process control valves using artificial intelligence by fuzzy logic technique, contributing in the development of predictive methodologies identifying faults in incipient state. The control valve analyzed belongs to a steam plant which simulates the secondary circuit of a PWR nuclear reactor - Pressurized Water Reactor. This study makes use of MATLAB language through the fuzzy logic toolbox which uses the method of inference Mamdani, acting by fuzzy conjunction, through Triangular Norms (t-norm) and Triangular Conorms (t-conorm). As input variables are used air pressure and displacement of the valve stem. Input data coming into the fuzzy system by graph of the automation system Delta V ® available in the plant, which receives a signal of electric current from an 'intelligent' positioned installed on the valve. The output variable is the 'status' of the valve. Through a

  20. An expert system for vibration based diagnostics of rotating machines

    International Nuclear Information System (INIS)

    Korteniemi, A.

    1990-01-01

    Very often changes in the mechanical condition of the rotating machinery can be observed as changes in its vibration. This paper presents an expert system for vibration-based diagnosis of rotating machines by describing the architecture of the developed prototype system. The importance of modelling the problem solving knowledge as well as the domain knowledge is emphasized by presenting the knowledge in several levels

  1. 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.

  2. The development of the intelligent diagnostic expert system for high power dye-laser MOPA system

    International Nuclear Information System (INIS)

    Liu Lianhua; Yang Wenxi; Zhang Xiaowei; Dan Yongjun

    2014-01-01

    A intelligent diagnostic expert system was required to simulate the expert thinking process of solving problem in experiment and to real-time judge the running state of the experiment system. The intelligent diagnostic expert system for dye-laser MOPA system was build with the modular design of separated knowledge base and inference engine, the RETE algorithm rules match, the asynchronous operation, and multithreading technology. The experiment result indicated that the system could real-time analysis and diagnose the running state of dye-laser MOPA system with advantages of high diagnosis efficiency, good instantaneity and strong expansibility. (authors)

  3. 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.

  4. Twelfth meeting of the ITER physics expert group on diagnostics

    International Nuclear Information System (INIS)

    Costley, A.E.; Donne, A.J.H.

    2000-01-01

    The main technical objectives of the meeting were to review the present status of ITER and to determine any required changes in the specifications for plasma measurements; to review the progress and develop plans for meeting the goals of the voluntary R and D tasks approved by the ITER Physics Committee within the Parties; to review and plan the work of the five specialists electronic working groups, and to hear reports of ITER relevant diagnostic developments in the Party Laboratories and assess their possible application to ITER

  5. Risk perception of diagnostic and therapeutic radiological applications. Comparison of experts and the public

    Energy Technology Data Exchange (ETDEWEB)

    Arranz, L. [Hospital Ramon y Cajal, Madrid (Spain); Macias, M.T. [CSIC, Madrid (Spain); Prades, A.; Sola, R. [Ciemat, Madrid (Spain); Martinez-Arias, R. [Universidad Complutense, Madrid (Spain)

    2000-05-01

    Recent research has found many differences between experts and lay people in judgements of radiological risks. However, most of these studies were carried out on experts from nuclear power plants, regulatory bodies etc. This paper analyses the differences among several groups of 'experts' coming from the Health area and the lay people. A survey was designed to assess the perceived seriousness of seven diagnostic and therapeutic applications: conventional diagnostic radiology, computed tomography, chemotherapy, ecography examinations, radiotherapy, and diagnostic and therapeutic nuclear medicine. The questionnaire was distributed to samples of experts (professionals exposed to ionizing radiations, and other health professionals), and outpatients. All samples were selected from ten countries: Argentine, Brazil, Colombia, Cuba, Ecuador, Mexico, Panama, Peru, Uruguay, and Spain, thanks to the collaboration of the different National Radioprotection Societies of the above mentioned countries, and of other concerned professionals (in case they didn't have any association at the time). The following comparisons will be presented: 1) Differences between experts' and the public; 2) differences among several groups of 'experts'; 3) within the 'expert' sample, differences between perceived seriousness as a patient and as a professional at risk; 4) within the public sample, individual differences related to some socio-demographic variables. A cross-cultural analysis of the above mentioned comparisons will also be carried out. (author)

  6. Risk perception of diagnostic and therapeutic radiological applications. Comparison of experts and the public

    International Nuclear Information System (INIS)

    Arranz, L.; Macias, M.T.; Prades, A.; Sola, R.; Martinez-Arias, R.

    2000-01-01

    Recent research has found many differences between experts and lay people in judgements of radiological risks. However, most of these studies were carried out on experts from nuclear power plants, regulatory bodies etc. This paper analyses the differences among several groups of 'experts' coming from the Health area and the lay people. A survey was designed to assess the perceived seriousness of seven diagnostic and therapeutic applications: conventional diagnostic radiology, computed tomography, chemotherapy, ecography examinations, radiotherapy, and diagnostic and therapeutic nuclear medicine. The questionnaire was distributed to samples of experts (professionals exposed to ionizing radiations, and other health professionals), and outpatients. All samples were selected from ten countries: Argentine, Brazil, Colombia, Cuba, Ecuador, Mexico, Panama, Peru, Uruguay, and Spain, thanks to the collaboration of the different National Radioprotection Societies of the above mentioned countries, and of other concerned professionals (in case they didn't have any association at the time). The following comparisons will be presented: 1) Differences between experts' and the public; 2) differences among several groups of 'experts'; 3) within the 'expert' sample, differences between perceived seriousness as a patient and as a professional at risk; 4) within the public sample, individual differences related to some socio-demographic variables. A cross-cultural analysis of the above mentioned comparisons will also be carried out. (author)

  7. DIAMS revisited: Taming the variety of knowledge in fault diagnosis expert systems

    Science.gov (United States)

    Haziza, M.; Ayache, S.; Brenot, J.-M.; Cayrac, D.; Vo, D.-P.

    1994-01-01

    The DIAMS program, initiated in 1986, led to the development of a prototype expert system, DIAMS-1 dedicated to the Telecom 1 Attitude and Orbit Control System, and to a near-operational system, DIAMS-2, covering a whole satellite (the Telecom 2 platform and its interfaces with the payload), which was installed in the Satellite Control Center in 1993. The refinement of the knowledge representation and reasoning is now being studied, focusing on the introduction of appropriate handling of incompleteness, uncertainty and time, and keeping in mind operational constraints. For the latest generation of the tool, DIAMS-3, a new architecture has been proposed, that enables the cooperative exploitation of various models and knowledge representations. On the same baseline, new solutions enabling higher integration of diagnostic systems in the operational environment and cooperation with other knowledge intensive systems such as data analysis, planning or procedure management tools have been introduced.

  8. Photolithography diagnostic expert systems: a systematic approach to problem solving in a wafer fabrication facility

    Science.gov (United States)

    Weatherwax Scott, Caroline; Tsareff, Christopher R.

    1990-06-01

    One of the main goals of process engineering in the semiconductor industry is to improve wafer fabrication productivity and throughput. Engineers must work continuously toward this goal in addition to performing sustaining and development tasks. To accomplish these objectives, managers must make efficient use of engineering resources. One of the tools being used to improve efficiency is the diagnostic expert system. Expert systems are knowledge based computer programs designed to lead the user through the analysis and solution of a problem. Several photolithography diagnostic expert systems have been implemented at the Hughes Technology Center to provide a systematic approach to process problem solving. This systematic approach was achieved by documenting cause and effect analyses for a wide variety of processing problems. This knowledge was organized in the form of IF-THEN rules, a common structure for knowledge representation in expert system technology. These rules form the knowledge base of the expert system which is stored in the computer. The systems also include the problem solving methodology used by the expert when addressing a problem in his area of expertise. Operators now use the expert systems to solve many process problems without engineering assistance. The systems also facilitate the collection of appropriate data to assist engineering in solving unanticipated problems. Currently, several expert systems have been implemented to cover all aspects of the photolithography process. The systems, which have been in use for over a year, include wafer surface preparation (HMDS), photoresist coat and softbake, align and expose on a wafer stepper, and develop inspection. These systems are part of a plan to implement an expert system diagnostic environment throughout the wafer fabrication facility. In this paper, the systems' construction is described, including knowledge acquisition, rule construction, knowledge refinement, testing, and evaluation. The roles

  9. 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.

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2010-10-15

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

  11. A proof-of-concept transient diagnostic expert system for BWRs [Boiling Water Reactors

    International Nuclear Information System (INIS)

    Yoshida, K.; Naser, J.A.

    1988-05-01

    A proof-of-concept transient diagnostic expert system has been developed to identify the cause and the type of an abnormal transient in a boiling water nuclear power plant. For this expert system development, the calculational results of the simulation code RETRAN were used as the knowledge source. The knowledge extracted from the RETRAN analyses was transformed into IF-THEN rules in the knowledge base for the expert system. An important feature of this expert system is the introduction of certainty factors to allow diagnosis even in the cases where data may be either missing or marked as invalid. To increase the capability of this diagnostic system to distinguish between similiar transients, backward chaining reasoning is used to support the forward chaining reasoning with certainty factors. Through this effort, it has been demonstrated that an expert system can be successfully used to create a transient diagnostic system. It has also successfully demonstrated that RETRAN can be used as the knowledge source for developing the knowledge base of the diagnostic system

  12. Post-glacial faulting in the Lansjaerv area, Northern Sweden. Comments from the expert group on a field visit at the Molberget post-glacial fault area, 1991

    International Nuclear Information System (INIS)

    Stanfors, R.; Ericsson, L.O.

    1993-05-01

    Post-glacial faults have been recognized in the northern Baltic shield for several decades. It is important to evaluate whether such neotectonic movements can lead to new fracturing or decisively alter the geohydrological or geohydrochemical situation around a final repository for spent nuclear fuel. The post-glacial Lansjaerv fault was chosen for an interdisciplinary study because of its relative accessibility. The goals of the study were to assess the mechanisms that caused present day scraps, to clarify the extent of any recent fracturing and to clarify the extent of any ongoing movements. All these objectives were reasonably met through a series of studies, which have been performed by SKB during 1986-1992 in two phases. This report gives a summary of the first phase of the Lansjaerv study (1986-1989) and describes achievements that have been gained during the second phase of the study. As a final of the field-work in the Lansjaerv area a meeting combined with a field excursion was arranged by SKB in June 1991 for a group of international experts. Comments from the expert group on the excursion and the overall Lansjaerv project are presented. One of the major conclusions is that the Lansjaerv post-glacial fault reactivated pre-existing old structures and that the causes of the post-glacial movements is a combination of plate tectonics and deglaciation

  13. Hierarchical mixture of experts and diagnostic modeling approach to reduce hydrologic model structural uncertainty: STRUCTURAL UNCERTAINTY DIAGNOSTICS

    Energy Technology Data Exchange (ETDEWEB)

    Moges, Edom [Civil and Environmental Engineering Department, Washington State University, Richland Washington USA; Demissie, Yonas [Civil and Environmental Engineering Department, Washington State University, Richland Washington USA; Li, Hong-Yi [Hydrology Group, Pacific Northwest National Laboratory, Richland Washington USA

    2016-04-01

    In most water resources applications, a single model structure might be inadequate to capture the dynamic multi-scale interactions among different hydrological processes. Calibrating single models for dynamic catchments, where multiple dominant processes exist, can result in displacement of errors from structure to parameters, which in turn leads to over-correction and biased predictions. An alternative to a single model structure is to develop local expert structures that are effective in representing the dominant components of the hydrologic process and adaptively integrate them based on an indicator variable. In this study, the Hierarchical Mixture of Experts (HME) framework is applied to integrate expert model structures representing the different components of the hydrologic process. Various signature diagnostic analyses are used to assess the presence of multiple dominant processes and the adequacy of a single model, as well as to identify the structures of the expert models. The approaches are applied for two distinct catchments, the Guadalupe River (Texas) and the French Broad River (North Carolina) from the Model Parameter Estimation Experiment (MOPEX), using different structures of the HBV model. The results show that the HME approach has a better performance over the single model for the Guadalupe catchment, where multiple dominant processes are witnessed through diagnostic measures. Whereas, the diagnostics and aggregated performance measures prove that French Broad has a homogeneous catchment response, making the single model adequate to capture the response.

  14. 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.

  15. Reasoning process characteristics in the diagnostic skills of beginner, competent, and expert dentists.

    Science.gov (United States)

    Crespo, Kathleen E; Torres, José E; Recio, María E

    2004-12-01

    The purpose of this study was to evaluate qualitative differences in the diagnostic reasoning process at different developmental stages of expertise. A qualitative design was used to study cognitive processes that characterize the diagnosis of oral disease at the stages of beginner (five junior students who had passed the NBDE I), competent (five GPR first-year residents), and expert dentists (five general dentists with ten or more years of experience). Individually, each participant was asked to determine the diagnosis of an oral condition based on a written clinical case, using the think aloud technique and retrospective reports. A subsequent interview was conducted to obtain the participants' diagnostic process model and pathophysiology of the case. The analysis of the verbal protocols indicated that experts referred to the patient's sociomedical context more frequently, demonstrated better organization of ideas, could determine key clinical findings, and had an ability to plan for the search of pertinent information. Fewer diagnostic hypotheses were formulated by participants who used forward reasoning, independent of the stage of development. Beginners requested additional diagnostic aids (radiographs, laboratory tests) more frequently than the competent/expert dentists. Experts recalled typical experiences with patients, while competent/beginner dentists recalled information from didactic courses. Experts evidenced cognitive diagnostic schemas that integrate pathophysiology of disease, while competent and beginner participants had not achieved this integration. We conclude that expert performance is a combination of a knowledge base, reasoning skills, and an accumulation of experiences with patients that is qualitatively different from that of competent and beginner dentists. It is important for dental education to emphasize the teaching of cognitive processes and to incorporate a wide variety of clinical experiences in addition to the teaching of

  16. 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...

  17. Fuzzy Concurrent Object Oriented Expert System for Fault Diagnosis in 8085 Microprocessor Based System Board

    OpenAIRE

    Mr.D. V. Kodavade; Dr. Mrs.S.D.Apte

    2014-01-01

    With the acceptance of artificial intelligence paradigm, a number of successful artificial intelligence systems were created. Fault diagnosis in microprocessor based boards needs lot of empirical knowledge and expertise and is a true artificial intelligence problem. Research on fault diagnosis in microprocessor based system boards using new fuzzy-object oriented approach is presented in this paper. There are many uncertain situations observed during fault diagnosis. These uncertain situations...

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

    Directory of Open Access Journals (Sweden)

    S. A. Bornyakov

    2017-01-01

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

  19. 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

  20. Vibration-based Fault Diagnostic of a Spur Gearbox

    Directory of Open Access Journals (Sweden)

    Hartono Dennis

    2016-01-01

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

  1. FTREX Testing Report (Fault Tree Reliability Evaluation eXpert) Version 1.5

    International Nuclear Information System (INIS)

    Jung, Woo Sik

    2009-07-01

    In order to verify FTREX functions and to confirm the correctness of FTREX 1.5, various tests were performed 1.fault trees with negates 2.fault trees with house events 3.fault trees with multiple tops 4.fault trees with logical loops 5.fault trees with initiators, house events, negates, logical loops, and flag events By using the automated cutest propagation test, the FTREX 1.5 functions are verified. FTREX version 1.3 and later versions have capability to perform bottom-up cutset-propagation test in order check cutest status. FTREX 1.5 always generates the proper minimal cut sets. All the output cutsets of the tested problems are MCSs (Minimal Cut Sets) and have no non-minimal cutsets and improper cutsets. The improper cutsets are those that have no effect to top, have multiple initiators, or have disjoint events A * -A

  2. 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)

  3. Expert system applications in support of system diagnostics and prognostics at EBR-II

    International Nuclear Information System (INIS)

    Lehto, W.K.; Gross, K.C.

    1989-01-01

    Expert systems have been developed to aid in the monitoring and diagnostics of the Experimental Breeder Reactor-II (EBR-II) at the Idaho National Engineering Laboratory (INEL) in Idaho Falls, Idaho. Systems have been developed for failed fuel surveillance and diagnostics and reactor coolant pump monitoring and diagnostics. A third project is being done jointly by ANL-W and EG ampersand G Idaho to develop a transient analysis system to enhance overall plant diagnostic and prognostic capability. The failed fuel surveillance and diagnosis system monitors, processes, and interprets information from nine key plant sensors. It displays to the reactor operator diagnostic information needed to make proper decisions regarding technical specification conformance during reactor operation with failed fuel. 8 refs., 9 figs., 2 tabs

  4. 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.

  5. 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...

  6. 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

  7. 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.

  8. Expert System for Diagnostics and Status Monitoring of NPP Water Chemistry Condition

    International Nuclear Information System (INIS)

    Shvedova, M.N.; Kritski, V.G.; Zakharova, S.V.; Nikolaev, F.V.; Benediktov, V.B.

    2002-01-01

    Water chemistry condition (WCC) has been the subject of constant study and improvement up to the present day. It is connected with the presence of a direct relationship between the violation of water chemistry regulation on the one hand and components reliability of the circuit's equipment and cost-effectiveness of their operation on the other. It dictates the necessity to apply different optimization methods in the field of monitoring and use of information - analytical and diagnostic systems to assess WCC quality, control and support. By now NPP experts have broad experience in revealing and removing the causes of WCC disturbances. However this knowledge is often of an intuitive, non-classified nature, scattered among various working documents, which makes their transfer difficult. Based on what has been mentioned above, special attention is currently being paid to the problem of creating expert diagnostic systems for supporting the optimum WCC. The existing developments in this field (DIWA, Smart chem Works, the water quality control system at the Onagava NPP etc. [1,3,4,5] are based on wide use of experts' knowledge. Such expert diagnostic systems for supporting WCC refer to the new generation of intellectual control methods, which allow the incorporation of the latest achievements both in the field of water chemistry simulation and in the field of artificial intelligence and computer technologies. LI 'VNIPIET' employees have, for several years, been developing an expert diagnostic system for supporting WCC and status monitoring of RBMK - reactor NPPs [2]. This system has not only conveniently organized the traditional functions of information acquisition and storage, a complete presentation of information in the form of tables, graphs of a dynamical changes of parameters and formation regular reports, diagnostic functions and issuing recommendations on WCC correction, but it also allows the assessment of confidence in the diagnosis made, relying on a wide

  9. 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.

  10. 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.

  11. 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

  12. An integrated real-time diagnostic concept using expert systems, qualitative reasoning and quantitative analysis

    International Nuclear Information System (INIS)

    Edwards, R.M.; Lee, K.Y.; Kumara, S.; Levine, S.H.

    1989-01-01

    An approach for an integrated real-time diagnostic system is being developed for inclusion as an integral part of a power plant automatic control system. In order to participate in control decisions and automatic closed loop operation, the diagnostic system must operate in real-time. Thus far, an expert system with real-time capabilities has been developed and installed on a subsystem at the Experimental Breeder Reactor (EBR-II) in Idaho, USA. Real-time simulation testing of advanced power plant concepts at the Pennsylvania State University has been developed and was used to support the expert system development and installation at EBR-II. Recently, the US National Science Foundation (NSF) and the US Department of Energy (DOE) have funded a Penn State research program to further enhance application of real-time diagnostic systems by pursuing implementation in a distributed power plant computer system including microprocessor based controllers. This paper summarizes past, current, planned, and possible future approaches to power plant diagnostic systems research at Penn State. 34 refs., 9 figs

  13. 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

  14. A diagnostic expert system for a boiling water reactor using a dynamic model

    International Nuclear Information System (INIS)

    Sonoda, Y.; Kanemoto, S.; Imaruoka, H.

    1990-01-01

    A diagnostic expert system for abnormal disturbances in a BWR (Boiling Water Reactor) plant has been developed. The peculiar feature of this system is a diagnostic method which combines artificial intelligence technique with numerical analysis technique. The system has three diagnostic functions, 1) identification of anomaly position (device or sensor), 2) identification of anomaly mode and 3) identification of anomaly cause. Function 1) is implemented as follows. First, a hypothesis about anomaly propagation paths is built up by qualitative reasoning, using knowledge of causal relations among observed signals. Next, the abnormal device or sensor is found by applying model reference method and fuzzy set theory to test the hypothesis, using knowledge of plant structure and function, heuristic strategy of diagnosis and module type dynamic simulator. This simulator is composed of basic transfer function modules. The simulation model for the testing region is built up automatically, according to the requirement from the diagnostic task. Function 2) means identification of dynamic characteristics for an anomaly. It is realized by tuning model parameters so as to reproduce the abnormal signal behavior using the non-linear programing method. Function 3) derives probable anomaly causes from heuristic rules between anomaly mode and cause. A basic plant dynamic model was built up and adjusted to dynamic characteristics for one BWR plant (1100MWe). In order to verify the diagnostic functions of this system, data for several abnormal events was compiled by modifying this model. The diagnostic functions were proved useful, through the simulated abnormal data

  15. Expert system for diagnostics and status monitoring of NPP water chemistry condition

    International Nuclear Information System (INIS)

    Shvedova, M.N.; Kritski, V.G.; Zakharova, S.V.; Benediktov, V.B.; Nikolaev, F.V.

    2002-01-01

    Water chemistry condition (WCC) has been the subject of constant study and improvement up to the present day. It is connected with the presence of a direct relationship between the violation of water chemistry regulation on the one hand and components reliability of the circuit's equipment and cost-effectiveness of their operation on the other. It dictates the necessity to apply different optimization methods in the field of monitoring and use of information analytical and diagnostic systems to assess WCC quality, control and support. LI ''VNIPIET'' employees have, for several years, been developing an expert diagnostic system for supporting WCC and status monitoring of RBMK - reactor NPPs [2]. This system has not only conveniently organized the traditional functions of information acquisition and storage, a complete presentation of information in the form of tables, graphs of a dynamical changes of parameters and formation regular reports, diagnostic functions and issuing recommendations on WCC correction, but it also allows the assessment of confidence in the diagnosis made, relying on a wide range of numerical estimates, which were calculated by the use of expert data, and to make a credible prediction of an existing situation development. (authors)

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

    Science.gov (United States)

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

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

  17. 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.

  18. Diagnostic technology and an expert system for photovoltaic systems using the learning method

    Energy Technology Data Exchange (ETDEWEB)

    Yagi, Yasuhiro; Kishi, Hitoshi; Hagihara, Ryuzou; Tanaka, Toshiya; Kozuma, Shinichi; Ishida, Takeo; Waki, Masahiro; Tanaka, Makoto; Kiyama, Seiichi [SANYO Electric Co. Ltd., New Materials Research Center, Moriguchi City, Osaka (Japan)

    2003-02-01

    Diagnostic technology for photovoltaic (PV) systems was developed, using the learning method to take each site's conditions into account. This technology employs diagnostic criteria databases to analyze data acquired from the PV systems. These criteria are updated monthly for each site using analyzed data. To check the shadows on the PV modules and pyranometer, the sophisticated verification method was also applied to this technology. After the diagnosis, a basket method provides maintenance advice for the PV systems. Based on the results of precise diagnoses, this expert system offers quick and proper maintenance advice within a few minutes. This technology is highly useful, because it greatly simplifies the servicing and maintenance of PV systems. (Author)

  19. A prototype expert system to support the development of a fault-tree analysis software for nuclear reactor safety

    International Nuclear Information System (INIS)

    Mesko, L.

    1990-01-01

    The project called EMERIS is designed to provide a material testing nuclear reactor and experimental loops with a software for the 'acquisition, evaluation and archivation of measured data during the operation of the experimental facility'. The project which gives job a team has a duration of two years and involves three Vax compatible TPA-type computers and many smaller computers for data digitalization and graphical workstations. The detailed description of the project is not the task of the paper. One of its modules, however, plays an important role in the considerations. Namely the module for distrubance analysis (DA) which is planned to perform a rule based on-line evaluation of numerous predefined fault trees in an expert system like environment

  20. Expert Meeting Report: HVAC Fault Detection, DIagnosis, and Repair/Replacement

    Energy Technology Data Exchange (ETDEWEB)

    Springer, David [Alliance for Residential Building Innovation (ARBI), Davis, CA (United States)

    2016-05-01

    The concept for the expert meeting described in this report was to bring together most of the stakeholders in the area of FDD, including academic researchers, manufacturers, educators, program managers and implementers, representatives of standards organizations, utilities, HVAC contractors, and home performance contractors to identify the major gaps and to develop ideas about what can be done to capitalize on the residential HVAC efficiency resource.

  1. Expert Meeting Report: HVAC Fault Detection, Diagnosis, and Repair/Replacement

    Energy Technology Data Exchange (ETDEWEB)

    Springer, David [Alliance for Residential Building Innovation (ARBI), Davis, CA (United States). Davis Energy Group

    2016-05-01

    The concept for the expert meeting described in this report was to bring together most of the stakeholders in the area of FDD, including academic researchers, manufacturers, educators, program managers and implementers, representatives of standards organizations, utilities, HVAC contractors, and home performance contractors to identify the major gaps and to develop ideas about what can be done to capitalize on the residential HVAC efficiency resource.

  2. Development of a diagnostic expert system for eddy current data analysis using applied artificial intelligence methods

    International Nuclear Information System (INIS)

    Upadhyaya, B.R.; Yan, W.; Henry, G.

    1999-01-01

    A diagnostic expert system that integrates database management methods, artificial neural networks, and decision-making using fuzzy logic has been developed for the automation of steam generator eddy current test (ECT) data analysis. The new system, known as EDDYAI, considers the following key issues: (1) digital eddy current test data calibration, compression, and representation; (2) development of robust neural networks with low probability of misclassification for flaw depth estimation; (3) flaw detection using fuzzy logic; (4) development of an expert system for database management, compilation of a trained neural network library, and a decision module; and (5) evaluation of the integrated approach using eddy current data. The implementation to field test data includes the selection of proper feature vectors for ECT data analysis, development of a methodology for large eddy current database management, artificial neural networks for flaw depth estimation, and a fuzzy logic decision algorithm for flaw detection. A large eddy current inspection database from the Electric Power Research Institute NDE Center is being utilized in this research towards the development of an expert system for steam generator tube diagnosis. The integration of ECT data pre-processing as part of the data management, fuzzy logic flaw detection technique, and tube defect parameter estimation using artificial neural networks are the fundamental contributions of this research. (orig.)

  3. Development of a diagnostic expert system for eddy current data analysis using applied artificial intelligence methods

    Energy Technology Data Exchange (ETDEWEB)

    Upadhyaya, B.R.; Yan, W. [Tennessee Univ., Knoxville, TN (United States). Dept. of Nuclear Engineering; Behravesh, M.M. [Electric Power Research Institute, Palo Alto, CA (United States); Henry, G. [EPRI NDE Center, Charlotte, NC (United States)

    1999-09-01

    A diagnostic expert system that integrates database management methods, artificial neural networks, and decision-making using fuzzy logic has been developed for the automation of steam generator eddy current test (ECT) data analysis. The new system, known as EDDYAI, considers the following key issues: (1) digital eddy current test data calibration, compression, and representation; (2) development of robust neural networks with low probability of misclassification for flaw depth estimation; (3) flaw detection using fuzzy logic; (4) development of an expert system for database management, compilation of a trained neural network library, and a decision module; and (5) evaluation of the integrated approach using eddy current data. The implementation to field test data includes the selection of proper feature vectors for ECT data analysis, development of a methodology for large eddy current database management, artificial neural networks for flaw depth estimation, and a fuzzy logic decision algorithm for flaw detection. A large eddy current inspection database from the Electric Power Research Institute NDE Center is being utilized in this research towards the development of an expert system for steam generator tube diagnosis. The integration of ECT data pre-processing as part of the data management, fuzzy logic flaw detection technique, and tube defect parameter estimation using artificial neural networks are the fundamental contributions of this research. (orig.)

  4. OPAD: An expert system for research reactor operations and fault diagnosis using probabilistic safety assessment tools

    International Nuclear Information System (INIS)

    Verma, A.K.; Varde, P.V.; Sankar, S.; Prakash, P.

    1996-01-01

    A prototype Knowledge Based (KB) operator Adviser (OPAD) system has been developed for 100 MW(th) Heavy Water moderated, cooled and Natural Uranium fueled research reactor. The development objective of this system is to improve reliability of operator action and hence the reactor safety at the time of crises as well as normal operation. The jobs performed by this system include alarm analysis, transient identification, reactor safety status monitoring, qualitative fault diagnosis and procedure generation in reactor operation. In order to address safety objectives at various stages of the Operator Adviser (OPAD) system development the Knowledge has been structured using PSA tools/information in an shell environment. To demonstrate the feasibility of using a combination of KB approach with PSA for operator adviser system, salient features of some of the important modules (viz. FUELEX, LOOPEX and LOCAEX) have been discussed. It has been found that this system can serve as an efficient operator support system

  5. Application Of The CSRL Language To The Design Of Diagnostic Expert Systems: The Moodis Experience, A Preliminary Report

    Science.gov (United States)

    Bravos, Angelo; Hill, Howard; Choca, James; Bresolin, Linda B.; Bresolin, Michael J.

    1986-03-01

    Computer technology is rapidly becoming an inseparable part of many health science specialties. Recently, a new area of computer technology, namely Artificial Intelligence, has been applied toward assisting the medical experts in their diagnostic and therapeutic decision making process. MOODIS is an experimental diagnostic expert system which assists Psychiatry specialists in diagnosing human Mood Disorders, better known as Affective Disorders. Its diagnostic methodology is patterned after MDX, a diagnostic expert system developed at LAIR (Laboratory for Artificial Intelligence Research) of Ohio State University. MOODIS is implemented in CSRL (Conceptual Structures Representation Language) also developed at LAIR. This paper describes MOODIS in terms of conceptualization and requirements, and discusses why the MDX approach and CSRL were chosen.

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

    Science.gov (United States)

    Kong, Changduk; Lim, Semyeong; Kim, Keunwoo

    2013-03-01

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

  7. 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.

  8. 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)

  9. A framework for an on-line diagnostic expert system with intelligent sensor validation

    International Nuclear Information System (INIS)

    Kim, Young Jin

    1997-01-01

    This paper outlines a framework for performing two different but inter-related functions in diagnosis, i.e. sensor validation and reasoning under uncertainty. Sensor validation plays a vital role in the ability of the overall system to correctly determine the state of a plant monitored by imperfect sensors (Sopocy, 1990). Two subsystems, Algorithmic(ASV) and Heuristic(HSV) Sensor Validation, separate activities according to the degree of plant knowledge required and represent Sensor Validation Expert System when combined. Uncertain information in sensory values is represented through probability assignments on three discrete states, High, Normal, and Low, and additional sensor confidence measures in ASV. HSV exploits deeper knowledge about parameter interaction within the plant to cull sensor faults from the data stream. Finally the modified probability distributions and validated data are used as input to the reasoning scheme which is the run-time version of the influence diagram. The influence diagram represents the backbone of reasoning under uncertainty in Influence Diagram Knowledge Base. (author)

  10. A diagnostic expert system for NPP based on hybrid knowledge approach

    International Nuclear Information System (INIS)

    Yang, Joon On; Chang, Soon Heung

    1989-01-01

    This paper describes a diagnostic expert system, HYPOSS (Hybrid Knowledge Based Plant Operation Supporting System), which has been developed to support operators' decision making during the transients of nuclear power plant. HYPOSS adopts the hybrid knowledge approach which combines shallow and deep knowledge to couple the merits of both approaches. In HYPOSS, four types of knowledge are used according to the steps of diagnosis procedure: structural, functional, behavioral and heuristic knowledge. The structural and functional knowledge is represented by three fundamental primitives and five types of functions respectively. The behavioral knowledge is represented using constraints. The inference procedure is based on the human problem solving behavior modeled in HYPOSS. For the validation of HYPOSS, several tests have been performed based on the data produced by a plant simulator. The results of validation studies showed a good applicability of HYPOSS to the anomaly diagnosis of nuclear power plant

  11. An expert system for fault management assistance on a space sleep experiment

    Science.gov (United States)

    Atamer, A.; Delaney, M.; Young, L. R.

    2002-01-01

    The expert system, Principal Investigator-in-a-box, or [PI], was designed to assist astronauts or other operators in performing experiments outside their expertise. Currently, the software helps astronauts calibrate instruments for a Sleep and Respiration Experiment without contact with the investigator on the ground. It flew on the Space Shuttle missions STS-90 and STS-95. [PI] displays electrophysiological signals in real time, alerts astronauts via the indicator lights when a poor signal quality is detected, and advises astronauts how to restore good signal quality. Thirty subjects received training on the sleep instrumentation and the [PI] interface. A beneficial effects of [PI] and training reduced troubleshooting time. [PI] benefited subjects on the most difficult scenarios, even though its lights were not 100% accurate. Further, questionnaires showed that most subjects preferred monitoring waveforms with [PI] assistance rather than monitoring waveforms alone. This study addresses problems of complex troubleshooting and the extended time between training and execution that is common to many human operator situations on earth such as in power plant operation, and marine exploration.

  12. System diagnostic builder: a rule-generation tool for expert systems that do intelligent data evaluation

    Science.gov (United States)

    Nieten, Joseph L.; Burke, Roger

    1993-03-01

    The system diagnostic builder (SDB) is an automated knowledge acquisition tool using state- of-the-art artificial intelligence (AI) technologies. The SDB uses an inductive machine learning technique to generate rules from data sets that are classified by a subject matter expert (SME). Thus, data is captured from the subject system, classified by an expert, and used to drive the rule generation process. These rule-bases are used to represent the observable behavior of the subject system, and to represent knowledge about this system. The rule-bases can be used in any knowledge based system which monitors or controls a physical system or simulation. The SDB has demonstrated the utility of using inductive machine learning technology to generate reliable knowledge bases. In fact, we have discovered that the knowledge captured by the SDB can be used in any number of applications. For example, the knowledge bases captured from the SMS can be used as black box simulations by intelligent computer aided training devices. We can also use the SDB to construct knowledge bases for the process control industry, such as chemical production, or oil and gas production. These knowledge bases can be used in automated advisory systems to ensure safety, productivity, and consistency.

  13. 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

  14. PRODIAG: Combined expert system/neural network for process fault diagnosis. Volume 1, Theory

    Energy Technology Data Exchange (ETDEWEB)

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

    1995-09-01

    The function of the PRODIAG code is to diagnose on-line the root cause of a thermal-hydraulic (T-H) system transient with trace back to the identification of the malfunctioning component using the T-H instrumentation signals exclusively. The code methodology is based on the Al techniques of automated reasoning/expert systems (ES) and artificial neural networks (ANN). The research and development objective is to develop a generic code methodology which would be plant- and T-H-system-independent. For the ES part the only plant or T-H system specific code requirements would be implemented through input only and at that only through a Piping and Instrumentation Diagram (PID) database. For the ANN part the only plant or T-H system specific code requirements would be through the ANN training data for normal component characteristics and the same PID database information. PRODIAG would, therefore, be generic and portable from T-H system to T-H system and from plant to plant without requiring any code-related modifications except for the PID database and the ANN training with the normal component characteristics. This would give PRODIAG the generic feature which numerical simulation plant codes such as TRAC or RELAP5 have. As the code is applied to different plants and different T-H systems, only the connectivity information, the operating conditions and the normal component characteristics are changed, and the changes are made entirely through input. Verification and validation of PRODIAG would, be T-H system independent and would be performed only ``once``.

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2006-06-15

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

  16. The application of expert systems and neural networks to gas turbine prognostics and diagnostics

    Energy Technology Data Exchange (ETDEWEB)

    DePold, H.R.; Gass, F.D.

    1999-10-01

    Condition monitoring of engine gas generators plays an essential role in airline fleet management. Adaptive diagnostic systems are becoming available that interpret measured data, furnish diagnosis of problems, provide a prognosis of engine health for planning purposes, and rank engines for scheduled maintenance. More than four hundred operations worldwide currently use versions of the first or second generation diagnostic tools. Development of a third generation system is underway which will provide additional system enhancements and combine the functions of the existing tools. Proposed enhancements include the use of artificial intelligence to automate, improve the quality of the analysis, provide timely alerts, and the use of an Internet link for collaboration. One objective of these enhancements is to have the intelligent system do more of the analysis and decision making, while continuing to support the depth of analysis currently available at experienced operations. This paper presents recent developments in technology and strategies in engine condition monitoring including: (1) application of statistical analysis and artificial neural network filters to improve data quality, (2) neural networks for trend change detection, and classification to diagnose performance change, and (3) expert systems to diagnose, provide alerts and to rank maintenance action recommendations.

  17. 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

  18. Diagnostic strategy and timing of intervention in infected necrotizing pancreatitis: an international expert survey and case vignette study

    NARCIS (Netherlands)

    van Grinsven, J. (Janneke); S. van Brunschot (Sandra); P. Fockens (Paul); J. van Grinsven (Janneke); O.J. Bakker (Olaf ); van Santvoort, H.C. (Hjalmar C.); T.L. Bollen (Thomas); M.A. Boermeester (Marja); C.H.J. van Eijck (Casper); M.G. Besselink (Marc); M.J. Bruno (Marco); C.H. Dejong (Cees); K.D. Horvath (Karen); van Eijck, C.H. (Casper H.); H. van Goor (Harry); H.G. Gooszen (Hein); Horvath, K.D. (Karen D.); K.P. van Lienden (Krijn); Abdelhafez, M.; Andersson, R.; Andren-Sandberg, A.; Ashley, S.; M.C. van Baal (Mark); Baron, T.; C. Bassi (Claudio); Bradley, E.; M.W. Buchler (M.); V.C. Cappendijk; Carter, R.; Charnley, R.; Coelho, D.; Connor, S.; Dellinger, P.; C. Dervenis (Christos); J. Devière (J.); Doctor, N.; Dudeja, V.; En-qiang, M.; Escourrou, J.; Fagenholz, P.; Farkas, G.; Forsmark, C.; Freeman, M.; P.C. Freeny (Patrick); French, J.; H. Friess; Gardner, T.; Goetzinger, P.; J.W. Haveman; S. Hofker (Sijbrand); Imrie, C.; Isaji, S.; Isenmann, R.; E. Klar (Ernst); J.S. Laméris (Johan ); M. Lerch (M.); P. Lévy (Philippe); Lillemoe, K.; Löhr, M.; J. Mayerle (Julia); Mayumi, T.; Mittal, A.; Moessner, J.; Morgan, D.; K.J. Mortele (Koenraad); Nealon, W.; J.P. Neoptolemos (John); V.B. Nieuwenhuijs (Vincent); Nordback, I.; Olah, A.; K. Oppong (K.); Padbury, R.; Papachristou, G.; Parks, R.; J.-W. Poley (Jan-Werner); Radenkovic, D.; Raraty, M.; Rau, B.; V. Rebours (Vinciane); Rische, S.; Runzi, M.; Sainani, N.; Sarr, M.; Schaapherder, S.; S. Seewald (Stefan); Seifert, H.; Shimosegawa, T.; Silverman, S.; Singh, V.; Siriwardena, A.; Steinberg, W.; Sutton, R.; Takeda, K.; R. Timmer (Robin); Vege, S.; R.P. Voermans (Rogier); J.J. De Waele (Jan J.); Wang, C. (Ch.); Warshaw, A.; J. Werner (Jens Martin); B.L. Weusten (Bas); Whitcomb, D.; Wig, J.; Windsor, J.; Zyromski, N.

    2016-01-01

    textabstractBackground The optimal diagnostic strategy and timing of intervention in infected necrotizing pancreatitis is subject to debate. We performed a survey on these topics amongst a group of international expert pancreatologists. Methods An online survey including case vignettes was sent to

  19. Quantifying Novice and Expert Differences in Visual Diagnostic Reasoning in Veterinary Pathology Using Eye-Tracking Technology.

    Science.gov (United States)

    Warren, Amy L; Donnon, Tyrone L; Wagg, Catherine R; Priest, Heather; Fernandez, Nicole J

    2018-01-18

    Visual diagnostic reasoning is the cognitive process by which pathologists reach a diagnosis based on visual stimuli (cytologic, histopathologic, or gross imagery). Currently, there is little to no literature examining visual reasoning in veterinary pathology. The objective of the study was to use eye tracking to establish baseline quantitative and qualitative differences between the visual reasoning processes of novice and expert veterinary pathologists viewing cytology specimens. Novice and expert participants were each shown 10 cytology images and asked to formulate a diagnosis while wearing eye-tracking equipment (10 slides) and while concurrently verbalizing their thought processes using the think-aloud protocol (5 slides). Compared to novices, experts demonstrated significantly higher diagnostic accuracy (preasoning and script-inductive knowledge structures with system 2 (analytic) reasoning to verify their diagnosis.

  20. A diagnostic expert system for the nuclear power plant b ased on the hybrid knowledge approach

    International Nuclear Information System (INIS)

    Yang, J.O.; Chang, S.H.

    1989-01-01

    A diagnostic expert system, the hybrid knowledge based plant operation supporting system (HYPOSS), which has been developed to support operators' decisionmaking during the transients of the nuclear power plant, is described. HYPOSS adopts the hybrid knowledge approach, which combines both shallow and deep knowledge to take advantage of the merits of both approaches. In HYPOSS, four types of knowledge are used according to the steps of diagnosis procedure. They are structural, functional, behavioral, and heuristic knowledge. The structural and functional knowledge is represented by three fundamental primitives and five types of functions, respectively. The behavioral knowledge is represented using constraints. The inference procedure is based on the human problem-solving behavior modeled in HYPOSS. The event-based operational guidelines are provided to the operator according to the diagnosed results. If the exact anomalies cannot be identified while some of the critical safety functions are challenged, the function-based operational guidelines are provided to the operator. For the validation of HYPOSS, several tests have been performed based on the data produced by a plant simulator. The results of validation studies show good applicability of HYPOSS to the anomaly diagnosis of nuclear power plant

  1. Expert system for assisting the diagnostic and localisation of breakdowns on the fuel elements loading machine

    International Nuclear Information System (INIS)

    Merlin, J.; Pradal, B.

    1990-01-01

    An expert system is developed in order to minimize the time lost through breakdowns of the fuel loading device. The expert system developed by FRAMATOME uses MAINTEX software. The expert systems MACHA and SEDMAC were designed respectively for use on 1300 MWe and 900 MWe loading machines [fr

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

    Science.gov (United States)

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

    2017-05-01

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

  3. 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

  4. Design and implementation of real-time diagnostic expert system in nuclear power plant

    International Nuclear Information System (INIS)

    Zhang Yan; Zhou Zhiwei; Dong Xiuchen

    2006-01-01

    In order to decrease the probability of malfunctions in nuclear power plant, a real-time expert system to be applied to malfunction diagnosis was designed. Based on the expert system theory the system converts the expert knowledge for diagnosing failures into the rules stored in database, and it can display real-time information of the abnormal symptoms, perform real-time diagnosis of malfunctions and suggest the operation actions related to malfunctions, etc. The results indicate that several typical malfunctions in nuclear power plant are diagnosed automatically and the corresponding operation schedules are given out by present expert system. (authors)

  5. The Development of Expertise in Radiology: In Chest Radiograph Interpretation, "Expert" Search Pattern May Predate "Expert" Levels of Diagnostic Accuracy for Pneumothorax Identification.

    Science.gov (United States)

    Kelly, Brendan S; Rainford, Louise A; Darcy, Sarah P; Kavanagh, Eoin C; Toomey, Rachel J

    2016-07-01

    Purpose To investigate the development of chest radiograph interpretation skill through medical training by measuring both diagnostic accuracy and eye movements during visual search. Materials and Methods An institutional exemption from full ethical review was granted for the study. Five consultant radiologists were deemed the reference expert group, and four radiology registrars, five senior house officers (SHOs), and six interns formed four clinician groups. Participants were shown 30 chest radiographs, 14 of which had a pneumothorax, and were asked to give their level of confidence as to whether a pneumothorax was present. Receiver operating characteristic (ROC) curve analysis was carried out on diagnostic decisions. Eye movements were recorded with a Tobii TX300 (Tobii Technology, Stockholm, Sweden) eye tracker. Four eye-tracking metrics were analyzed. Variables were compared to identify any differences between groups. All data were compared by using the Friedman nonparametric method. Results The average area under the ROC curve for the groups increased with experience (0.947 for consultants, 0.792 for registrars, 0.693 for SHOs, and 0.659 for interns; P = .009). A significant difference in diagnostic accuracy was found between consultants and registrars (P = .046). All four eye-tracking metrics decreased with experience, and there were significant differences between registrars and SHOs. Total reading time decreased with experience; it was significantly lower for registrars compared with SHOs (P = .046) and for SHOs compared with interns (P = .025). Conclusion Chest radiograph interpretation skill increased with experience, both in terms of diagnostic accuracy and visual search. The observed level of experience at which there was a significant difference was higher for diagnostic accuracy than for eye-tracking metrics. (©) RSNA, 2016 Online supplemental material is available for this article.

  6. Scratching the surface of tomorrow's diagnostics: the Editor-in-Chief's opinion at the 15th year of Expert Review of Molecular Diagnostics.

    Science.gov (United States)

    Lorincz, Attila; Raison, Claire

    2015-01-01

    Interview with Attila Lorincz by Claire Raison (Commissioning Editor) To mark the beginning of the 15th year of Expert Review of Molecular Diagnostics, the journal's Editor-in-Chief shares his expert knowledge on translational diagnostics, his opinion on recent controversies and his predictions for molecular diagnostics in 2015 and beyond. Attila Lorincz received his doctorate from Trinity College, Dublin, Republic of Ireland, and went on to become a research fellow at the University of California, Santa Barbara, CA, USA. During Professor Lorincz's research on human papillomavirus (HPV), he found several important and novel carcinogenic HPV types and pioneered the use of HPV DNA testing for clinical diagnostics. In 1988, Professor Lorincz's team produced the first HPV test to be FDA-approved for patients and in 2003, for general population cervical precancer screening. Now Professor of Molecular Epidemiology at the Centre for Cancer Prevention, Queen Mary University of London, UK, he and his team are furthering translational research into DNA methylation assays for cancer risk prediction.

  7. A Study on Satellite Diagnostic Expert Systems Using Case-Based Approach

    Directory of Open Access Journals (Sweden)

    Young-Tack Park

    1997-06-01

    Full Text Available Many research works are on going to monitor and diagnose diverse malfunctions of satellite systems as the complexity and number of satellites increase. Currently, many works on monitoring and diagnosis are carried out by human experts but there are needs to automate much of the routine works of them. Hence, it is necessary to study on using expert systems which can assist human experts routine work by doing automatically, thereby allow human experts devote their expertise more critical and important areas of monitoring and diagnosis. In this paper, we are employing artificial intelligence techniques to model human experts' knowledge and inference the constructed knowledge. Especially, case-based approaches are used to construct a knowledge base to model human expert capabilities which use previous typical exemplars. We have designed and implemented a prototype case-based system for diagnosing satellite malfunctions using cases. Our system remembers typical failure cases and diagnoses a current malfunction by indexing the case base. Diverse methods are used to build a more user friendly interface which allows human experts can build a knowledge base in as easy way.

  8. 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.

  9. Understanding diagnostic variability in breast pathology: lessons learned from an expert consensus review panel

    Science.gov (United States)

    Allison, Kimberly H; Reisch, Lisa M; Carney, Patricia A; Weaver, Donald L; Schnitt, Stuart J; O’Malley, Frances P; Geller, Berta M; Elmore, Joann G

    2015-01-01

    Aims To gain a better understanding of the reasons for diagnostic variability, with the aim of reducing the phenomenon. Methods and results In preparation for a study on the interpretation of breast specimens (B-PATH), a panel of three experienced breast pathologists reviewed 336 cases to develop consensus reference diagnoses. After independent assessment, cases coded as diagnostically discordant were discussed at consensus meetings. By the use of qualitative data analysis techniques, transcripts of 16 h of consensus meetings for a subset of 201 cases were analysed. Diagnostic variability could be attributed to three overall root causes: (i) pathologist-related; (ii) diagnostic coding/study methodology-related; and (iii) specimen-related. Most pathologist-related root causes were attributable to professional differences in pathologists’ opinions about whether the diagnostic criteria for a specific diagnosis were met, most frequently in cases of atypia. Diagnostic coding/study methodology-related root causes were primarily miscategorizations of descriptive text diagnoses, which led to the development of a standardized electronic diagnostic form (BPATH-Dx). Specimen-related root causes included artefacts, limited diagnostic material, and poor slide quality. After re-review and discussion, a consensus diagnosis could be assigned in all cases. Conclusions Diagnostic variability is related to multiple factors, but consensus conferences, standardized electronic reporting formats and comments on suboptimal specimen quality can be used to reduce diagnostic variability. PMID:24511905

  10. Expert system strategies for the diagnostic in a particle physics experiment

    International Nuclear Information System (INIS)

    D'Antone, I.; Mandrioli, G.; Matteuzzi, P.

    1990-01-01

    The maintenance of a particle detector functionality requires the knowledge of more experts: physicists and engineers for the detector and the electronic system. The integration of different knowledges and experiences can be easily done using an Expert System. A real-time Expert System allows us to diagnose the detector and data acquisition system anomalies; it makes an on-line diagnosis and, if an abnormal condition is identified, takes the appropriate action to reduce the unavailability of the apparatus. A method based on structural and behavioral reasoning is considered. Reasoning on the structure and on the functionality of the apparatus all the possible failures that can explain the sensor readings are searched. The behaviour of the apparatus components are described in qualitative terms to write the rules for the expert system

  11. 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

  12. 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

  13. 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.

  14. A simulation-based expert system for nuclear power plant diagnostics

    International Nuclear Information System (INIS)

    Hassberger, J.A.; Lee, J.C.

    1989-01-01

    An expert system for diagnosing operational transients in a nuclear power plant is discussed. Hypothesis and test is used as the problem-solving strategy with hypotheses generated by an expert system that monitors the plant for patterns of data symptomatic of known failure modes. Fuzzy logic is employed as the inferencing mechanism with two complementary implication schemes to handle scenarios involving competing failures. Hypothesis testing is performed. An artificial intelligence framework based on a critical functions approach is used to deal with the complexity of a nuclear plant. A prototype system for diagnosing transients in the reactor coolant system of a pressurized water reactor has been developed to test the algorithms described here. Results are presented for the diagnosis of data from the Three Mile Island Unit 2 loss-of-feedwater/small-break loss-of-collant accident

  15. Validation of DIVA: an expert system for the diagnostic of turbo-generator vibrations

    International Nuclear Information System (INIS)

    Chevalier, R.; Ricard, B.; Tiarri, J.P.; Bonnet, J.C.

    1990-01-01

    The project presented in this paper concerns the development of an expert system dealing with the diagnosis of turbo-generator vibrations. DIVA - Diagnosis of Shaft Line Vibrations - is a joint project which is carried out by ALSTHOM, Electricite de France and Laboratoire de Marcoussis, research centre of CGE. This article first presents the organisation of the system and then the goals and results of the tests already achieved [fr

  16. An approach to build a knowledge base for reactor accident diagnostic expert system

    International Nuclear Information System (INIS)

    Yoshida, K.; Fujii, M.; Fujiki, K.; Yokobayashi, M.; Kohsaka, A.; Aoyagi, T.; Hirota, Y.

    1987-01-01

    In the development of a rule based expert system, one of the key issues is how to acquire knowledge and to build knowledge base (KB). On building the KB of DISKET, which is an expert system for nuclear reactor accident diagnosis developed in JAERI, several problems have been experienced as follows. To write rules is a time consuming task, and it is difficult to keep the objectivity and consistency of rules as the number of rules increase. Further, certainty factors (CFs) must be often determined according to engineering judgment, i.e., empirically or intuitively. A systematic approach was attempted to handle these difficulties and to build an objective KB efficiently. The approach described in this paper is based on the concept that a prototype KB, colloquially speaking an initial guess, should first be generated in a systematic way and then is to be modified and/or improved by human experts for practical use. Statistical methods, principally Factor Analysis, were used as the systematic way to build a prototype KB for the DISKET using a PWR plant simulator data. The source information is a number of data obtained from the simulation of transients, such as the status of components and annunciator etc., and major process parameters like pressures, temperatures and so on

  17. 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.

  18. Studying the effects of operators' problem solving behaviour when using a diagnostic expert system developed for the nuclear industry

    International Nuclear Information System (INIS)

    Holmstroem, C.B.O.; Volden, F.S.; Endestad, T.

    1992-01-01

    This paper describes an experiment with the purpose to also illustrate and discuss some of the methodological problems when empirically studying problem solving. The experiment which was the second in a series, conducted at the OECD Halden Reactor Project, aimed to assess the effect on nuclear power plant operators diagnostic behaviour when using a rule-based diagnostic expert system. The rule-based expert system used in the experiment is called DISKET (Diagnosis System Using Knowledge Engineering Technique) and was originally developed by the Japan Atomic Energy Research Institute (JAERI). The experiment was performed in the Halden man-machine laboratory using a full scope pressurized water reactor simulator. Existing data collection methods and experimental design principles includes possibilities but also limitations. This is discussed and experiences are presented. Operator performance in terms of quality of diagnosis is improved by the use of DISKET. The use of the DISKET system also influences operators problem solving behaviour. The main difference between the two experimental conditions can be characterized as while the DISKET users during the diagnosis process are following a strategy which is direct and narrowed, the non-DISKET users are using a much broader and less focused search when trying to diagnose a disturbance. (author)

  19. Summary of the eleventh meeting of the ITER diagnostic expert group

    International Nuclear Information System (INIS)

    Costley, A.E.; Donne, A.J.H.

    1999-01-01

    The main technical objectives of the meeting were (i) to review and update the measurement capabilities to meet the anticipated needs of the ITER-FEAT; (ii) to review the progress and plans in meeting the goals of the voluntary R and D tasks; and (iii) to hear reports of ITER relevant diagnostic developments

  20. A prototype expert system for fault analysis, alarm handling and operator advising in a PWR nuclear power plant

    International Nuclear Information System (INIS)

    Gondran, M.; Ancelin, J.; Hery, J.F.; Laleuf, J.C.; Legaud, P.

    1986-01-01

    This paper successively describes the methodological advantages of the expert-systems approach and then two major applications of it that are under development in Electricite de France: assistance in alarms and operational management, and computer-assisted reliability. Topics considered include man-machine systems, human factors engineering, reactor operation, artificial intelligence, and decision making

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

    Directory of Open Access Journals (Sweden)

    Ahmed TOUMI

    2009-12-01

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

  2. System Diagnostic Builder - A rule generation tool for expert systems that do intelligent data evaluation. [applied to Shuttle Mission Simulator

    Science.gov (United States)

    Nieten, Joseph; Burke, Roger

    1993-01-01

    Consideration is given to the System Diagnostic Builder (SDB), an automated knowledge acquisition tool using state-of-the-art AI technologies. The SDB employs an inductive machine learning technique to generate rules from data sets that are classified by a subject matter expert. Thus, data are captured from the subject system, classified, and used to drive the rule generation process. These rule bases are used to represent the observable behavior of the subject system, and to represent knowledge about this system. The knowledge bases captured from the Shuttle Mission Simulator can be used as black box simulations by the Intelligent Computer Aided Training devices. The SDB can also be used to construct knowledge bases for the process control industry, such as chemical production or oil and gas production.

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

    Directory of Open Access Journals (Sweden)

    Sobhy Serry Dessouky

    2016-08-01

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

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

    Directory of Open Access Journals (Sweden)

    G.H. Kusumadevi

    2015-09-01

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

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

    Science.gov (United States)

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

    2017-09-01

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

  6. 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.

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

    Directory of Open Access Journals (Sweden)

    Jun Zhou

    2016-01-01

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

  8. Vibration monitoring and fault diagnostics of a 45 kW motor

    International Nuclear Information System (INIS)

    Hafeez, T.; Ahmed, A.; Chohan, G.Y.

    2003-01-01

    Overheating, high noise and vibrations were observed in a 45 kW induction motor of a chilled water pump in an air conditioning plant. The vibration amplitudes along with phase angles were obtained with the help of a data collector. The vibration spectra obtained was further analyzed to diagnose the problem. The user had reported high vibrations in motor since the day of its installation. The frequency peaks and phase data has revealed the possibility of structural resonance, and misalignment in rotor bearing assembly. The problem of eccentric housing bore on non-drive end NDE that resulted in the misalignment of motor shaft in housing assembly. The spectra and phase data is presented and discussed to diagnose the motor problems. The re-monitoring of motor after rectification of manufacturing fault has confirmed the right diagnoses. (author)

  9. A Computer-Based, Interactive Videodisc Job Aid and Expert System for Electron Beam Lithography Integration and Diagnostic Procedures.

    Science.gov (United States)

    Stevenson, Kimberly

    This master's thesis describes the development of an expert system and interactive videodisc computer-based instructional job aid used for assisting in the integration of electron beam lithography devices. Comparable to all comprehensive training, expert system and job aid development require a criterion-referenced systems approach treatment to…

  10. 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

  11. Tuberculosis-Diagnostic Expert System: an architecture for translating patients information from the web for use in tuberculosis diagnosis.

    Science.gov (United States)

    Osamor, Victor C; Azeta, Ambrose A; Ajulo, Oluseyi O

    2014-12-01

    Over 1.5-2 million tuberculosis deaths occur annually. Medical professionals are faced with a lot of challenges in delivering good health-care with unassisted automation in hospitals where there are several patients who need the doctor's attention. To automate the pre-laboratory screening process against tuberculosis infection to aid diagnosis and make it fast and accessible to the public via the Internet. The expert system we have built is designed to also take care of people who do not have access to medical experts, but would want to check their medical status. A rule-based approach has been used, and unified modeling language and the client-server architecture technique were applied to model the system and to develop it as a web-based expert system for tuberculosis diagnosis. Algorithmic rules in the Tuberculosis-Diagnosis Expert System necessitate decision coverage where tuberculosis is either suspected or not suspected. The architecture consists of a rule base, knowledge base, and patient database. These units interact with the inference engine, which receives patient' data through the Internet via a user interface. We present the architecture of the Tuberculosis-Diagnosis Expert System and its implementation. We evaluated it for usability to determine the level of effectiveness, efficiency and user satisfaction. The result of the usability evaluation reveals that the system has a usability of 4.08 out of a scale of 5. This is an indication of a more-than-average system performance. Several existing expert systems have been developed for the purpose of supporting different medical diagnoses, but none is designed to translate tuberculosis patients' symptomatic data for online pre-laboratory screening. Our Tuberculosis-Diagnosis Expert System is an effective solution for the implementation of the needed web-based expert system diagnosis. © The Author(s) 2013.

  12. Diagnostic accuracy of semi-automatic quantitative metrics as an alternative to expert reading of CT myocardial perfusion in the CORE320 study.

    Science.gov (United States)

    Ostovaneh, Mohammad R; Vavere, Andrea L; Mehra, Vishal C; Kofoed, Klaus F; Matheson, Matthew B; Arbab-Zadeh, Armin; Fujisawa, Yasuko; Schuijf, Joanne D; Rochitte, Carlos E; Scholte, Arthur J; Kitagawa, Kakuya; Dewey, Marc; Cox, Christopher; DiCarli, Marcelo F; George, Richard T; Lima, Joao A C

    2018-04-03

    To determine the diagnostic accuracy of semi-automatic quantitative metrics compared to expert reading for interpretation of computed tomography perfusion (CTP) imaging. The CORE320 multicenter diagnostic accuracy clinical study enrolled patients between 45 and 85 years of age who were clinically referred for invasive coronary angiography (ICA). Computed tomography angiography (CTA), CTP, single photon emission computed tomography (SPECT), and ICA images were interpreted manually in blinded core laboratories by two experienced readers. Additionally, eight quantitative CTP metrics as continuous values were computed semi-automatically from myocardial and blood attenuation and were combined using logistic regression to derive a final quantitative CTP metric score. For the reference standard, hemodynamically significant coronary artery disease (CAD) was defined as a quantitative ICA stenosis of 50% or greater and a corresponding perfusion defect by SPECT. Diagnostic accuracy was determined by area under the receiver operating characteristic curve (AUC). Of the total 377 included patients, 66% were male, median age was 62 (IQR: 56, 68) years, and 27% had prior myocardial infarction. In patient based analysis, the AUC (95% CI) for combined CTA-CTP expert reading and combined CTA-CTP semi-automatic quantitative metrics was 0.87(0.84-0.91) and 0.86 (0.83-0.9), respectively. In vessel based analyses the AUC's were 0.85 (0.82-0.88) and 0.84 (0.81-0.87), respectively. No significant difference in AUC was found between combined CTA-CTP expert reading and CTA-CTP semi-automatic quantitative metrics in patient based or vessel based analyses(p > 0.05 for all). Combined CTA-CTP semi-automatic quantitative metrics is as accurate as CTA-CTP expert reading to detect hemodynamically significant CAD. Copyright © 2018 Society of Cardiovascular Computed Tomography. Published by Elsevier Inc. All rights reserved.

  13. 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

  14. Conscious thought beats deliberation without attention in diagnostic decision-making: at least when you are an expert.

    Science.gov (United States)

    Mamede, Sílvia; Schmidt, Henk G; Rikers, Remy M J P; Custers, Eugene J F M; Splinter, Ted A W; van Saase, Jan L C M

    2010-11-01

    Contrary to what common sense makes us believe, deliberation without attention has recently been suggested to produce better decisions in complex situations than deliberation with attention. Based on differences between cognitive processes of experts and novices, we hypothesized that experts make in fact better decisions after consciously thinking about complex problems whereas novices may benefit from deliberation-without-attention. These hypotheses were confirmed in a study among doctors and medical students. They diagnosed complex and routine problems under three conditions, an immediate-decision condition and two delayed conditions: conscious thought and deliberation-without-attention. Doctors did better with conscious deliberation when problems were complex, whereas reasoning mode did not matter in simple problems. In contrast, deliberation-without-attention improved novices' decisions, but only in simple problems. Experts benefit from consciously thinking about complex problems; for novices thinking does not help in those cases.

  15. Evaluation of tuberculosis diagnostics in children: 1. Proposed clinical case definitions for classification of intrathoracic tuberculosis disease. Consensus from an expert panel.

    Science.gov (United States)

    Graham, Stephen M; Ahmed, Tahmeed; Amanullah, Farhana; Browning, Renee; Cardenas, Vicky; Casenghi, Martina; Cuevas, Luis E; Gale, Marianne; Gie, Robert P; Grzemska, Malgosia; Handelsman, Ed; Hatherill, Mark; Hesseling, Anneke C; Jean-Philippe, Patrick; Kampmann, Beate; Kabra, Sushil Kumar; Lienhardt, Christian; Lighter-Fisher, Jennifer; Madhi, Shabir; Makhene, Mamodikoe; Marais, Ben J; McNeeley, David F; Menzies, Heather; Mitchell, Charles; Modi, Surbhi; Mofenson, Lynne; Musoke, Philippa; Nachman, Sharon; Powell, Clydette; Rigaud, Mona; Rouzier, Vanessa; Starke, Jeffrey R; Swaminathan, Soumya; Wingfield, Claire

    2012-05-15

    There is a critical need for improved diagnosis of tuberculosis in children, particularly in young children with intrathoracic disease as this represents the most common type of tuberculosis in children and the greatest diagnostic challenge. There is also a need for standardized clinical case definitions for the evaluation of diagnostics in prospective clinical research studies that include children in whom tuberculosis is suspected but not confirmed by culture of Mycobacterium tuberculosis. A panel representing a wide range of expertise and child tuberculosis research experience aimed to develop standardized clinical research case definitions for intrathoracic tuberculosis in children to enable harmonized evaluation of new tuberculosis diagnostic technologies in pediatric populations. Draft definitions and statements were proposed and circulated widely for feedback. An expert panel then considered each of the proposed definitions and statements relating to clinical definitions. Formal group consensus rules were established and consensus was reached for each statement. The definitions presented in this article are intended for use in clinical research to evaluate diagnostic assays and not for individual patient diagnosis or treatment decisions. A complementary article addresses methodological issues to consider for research of diagnostics in children with suspected tuberculosis.

  16. Evaluation of Tuberculosis Diagnostics in Children: 1. Proposed Clinical Case Definitions for Classification of Intrathoracic Tuberculosis Disease. Consensus From an Expert Panel

    Science.gov (United States)

    Graham, Stephen M.; Ahmed, Tahmeed; Amanullah, Farhana; Browning, Renee; Cardenas, Vicky; Casenghi, Martina; Cuevas, Luis E.; Gale, Marianne; Gie, Robert P.; Grzemska, Malgosia; Handelsman, Ed; Hatherill, Mark; Hesseling, Anneke C.; Jean-Philippe, Patrick; Kampmann, Beate; Kabra, Sushil Kumar; Lienhardt, Christian; Lighter-Fisher, Jennifer; Madhi, Shabir; Makhene, Mamodikoe; Marais, Ben J.; McNeeley, David F.; Menzies, Heather; Mitchell, Charles; Modi, Surbhi; Mofenson, Lynne; Musoke, Philippa; Nachman, Sharon; Powell, Clydette; Rigaud, Mona; Rouzier, Vanessa; Starke, Jeffrey R.; Swaminathan, Soumya; Wingfield, Claire

    2012-01-01

    There is a critical need for improved diagnosis of tuberculosis in children, particularly in young children with intrathoracic disease as this represents the most common type of tuberculosis in children and the greatest diagnostic challenge. There is also a need for standardized clinical case definitions for the evaluation of diagnostics in prospective clinical research studies that include children in whom tuberculosis is suspected but not confirmed by culture of Mycobacterium tuberculosis. A panel representing a wide range of expertise and child tuberculosis research experience aimed to develop standardized clinical research case definitions for intrathoracic tuberculosis in children to enable harmonized evaluation of new tuberculosis diagnostic technologies in pediatric populations. Draft definitions and statements were proposed and circulated widely for feedback. An expert panel then considered each of the proposed definitions and statements relating to clinical definitions. Formal group consensus rules were established and consensus was reached for each statement. The definitions presented in this article are intended for use in clinical research to evaluate diagnostic assays and not for individual patient diagnosis or treatment decisions. A complementary article addresses methodological issues to consider for research of diagnostics in children with suspected tuberculosis. PMID:22448023

  17. Laserjet Printer Troubleshooting Expert System | Adesola | West ...

    African Journals Online (AJOL)

    This paper model an expert system called LAPTEX for troubleshooting LaserJet printers' faults. Today, with the innumerable advances in information technologies, computerizing printer's fault troubleshooting and identifying faults is far becoming so vital. Also, printers' fault detection is a complicated process that requires a ...

  18. 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.

  19. Classification of neuropathic pain in cancer patients: A Delphi expert survey report and EAPC/IASP proposal of an algorithm for diagnostic criteria.

    Science.gov (United States)

    Brunelli, Cinzia; Bennett, Michael I; Kaasa, Stein; Fainsinger, Robin; Sjøgren, Per; Mercadante, Sebastiano; Løhre, Erik T; Caraceni, Augusto

    2014-12-01

    Neuropathic pain (NP) in cancer patients lacks standards for diagnosis. This study is aimed at reaching consensus on the application of the International Association for the Study of Pain (IASP) special interest group for neuropathic pain (NeuPSIG) criteria to the diagnosis of NP in cancer patients and on the relevance of patient-reported outcome (PRO) descriptors for the screening of NP in this population. An international group of 42 experts was invited to participate in a consensus process through a modified 2-round Internet-based Delphi survey. Relevant topics investigated were: peculiarities of NP in patients with cancer, IASP NeuPSIG diagnostic criteria adaptation and assessment, and standardized PRO assessment for NP screening. Median consensus scores (MED) and interquartile ranges (IQR) were calculated to measure expert consensus after both rounds. Twenty-nine experts answered, and good agreement was found on the statement "the pathophysiology of NP due to cancer can be different from non-cancer NP" (MED=9, IQR=2). Satisfactory consensus was reached for the first 3 NeuPSIG criteria (pain distribution, history, and sensory findings; MEDs⩾8, IQRs⩽3), but not for the fourth one (diagnostic test/imaging; MED=6, IQR=3). Agreement was also reached on clinical examination by soft brush or pin stimulation (MEDs⩾7 and IQRs⩽3) and on the use of PRO descriptors for NP screening (MED=8, IQR=3). Based on the study results, a clinical algorithm for NP diagnostic criteria in cancer patients with pain was proposed. Clinical research on PRO in the screening phase and on the application of the algorithm will be needed to examine their effectiveness in classifying NP in cancer patients. Copyright © 2014 International Association for the Study of Pain. Published by Elsevier B.V. All rights reserved.

  20. Comprehensive Diagnostic Assessment of Health Status of Patients with Asthma or COPD : A Delphi Panel Study among Dutch Experts

    NARCIS (Netherlands)

    van den Akker, Edmée F M M; van't Hul, Alex J.; Birnie, Erwin; Chavannes, Niels H.; Rutten-van Mölken, Maureen P M H; In't Veen, Johannes C C M

    2017-01-01

    A comprehensive diagnostic assessment is needed to improve understanding of the health status of patients with chronic obstructive pulmonary disease (COPD) or asthma. Therefore, this study investigated which components and subsequent instruments should be part of a holistic assessment in secondary

  1. An innovative modular device and wireless control system enabling thermal and pressure sensors using FPGA on real-time fault diagnostics of steam turbine functional deterioration

    Science.gov (United States)

    Devi, S.; Saravanan, M.

    2018-03-01

    It is necessary that the condition of the steam turbines is continuously monitored on a scheduled basis for the safe operation of the steam turbines. The review showed that steam turbine fault detection and operation maintenance system (STFDOMS) is gaining importance recently. In this paper, novel hardware architecture is proposed for STFDOMS that can be communicated through the GSM network. Arduino is interfaced with the FPGA so as to transfer the message. The design has been simulated using the Verilog programming language and implemented in hardware using FPGA. The proposed system is shown to be a simple, cost effective and flexible and thereby making it suitable for the maintenance of steam turbines. This system forewarns the experts to access to data messages and take necessary action in a short period with great accuracy. The hardware developed is promised as a real-time test bench, specifically for investigations of long haul effects with different parameter settings.

  2. Diagnostics

    DEFF Research Database (Denmark)

    Donné, A.J.H.; Costley, A.E.; Barnsley, R.

    2007-01-01

    of the measurements—time and spatial resolutions, etc—will in some cases be more stringent. Many of the measurements will be used in the real time control of the plasma driving a requirement for very high reliability in the systems (diagnostics) that provide the measurements. The implementation of diagnostic systems...... on ITER is a substantial challenge. Because of the harsh environment (high levels of neutron and gamma fluxes, neutron heating, particle bombardment) diagnostic system selection and design has to cope with a range of phenomena not previously encountered in diagnostic design. Extensive design and R......&D is needed to prepare the systems. In some cases the environmental difficulties are so severe that new diagnostic techniques are required. The starting point in the development of diagnostics for ITER is to define the measurement requirements and develop their justification. It is necessary to include all...

  3. How and when do expert emergency physicians generate and evaluate diagnostic hypotheses? A qualitative study using head-mounted video cued-recall interviews.

    Science.gov (United States)

    Pelaccia, Thierry; Tardif, Jacques; Triby, Emmanuel; Ammirati, Christine; Bertrand, Catherine; Dory, Valérie; Charlin, Bernard

    2014-12-01

    The ability to make a diagnosis is a crucial skill in emergency medicine. Little is known about the way emergency physicians reach a diagnosis. This study aims to identify how and when, during the initial patient examination, emergency physicians generate and evaluate diagnostic hypotheses. We carried out a qualitative research project based on semistructured interviews with emergency physicians. The interviews concerned management of an emergency situation during routine medical practice. They were associated with viewing the video recording of emergency situations filmed in an "own-point-of-view" perspective. The emergency physicians generated an average of 5 diagnostic hypotheses. Most of these hypotheses were generated before meeting the patient or within the first 5 minutes of the meeting. The hypotheses were then rank ordered within the context of a verification procedure based on identifying key information. These tasks were usually accomplished without conscious effort. No hypothesis was completely confirmed or refuted until the results of investigations were available. The generation and rank ordering of diagnostic hypotheses is based on the activation of cognitive processes, enabling expert emergency physicians to process environmental information and link it to past experiences. The physicians seemed to strive to avoid the risk of error by remaining aware of the possibility of alternative hypotheses as long as they did not have the results of investigations. Understanding the diagnostic process used by emergency physicians provides interesting ideas for training residents in a specialty in which the prevalence of reasoning errors leading to incorrect diagnoses is high. Copyright © 2014 American College of Emergency Physicians. Published by Elsevier Inc. All rights reserved.

  4. A first-principles generic methodology for representing the knowledge base of a process diagnostic expert system

    International Nuclear Information System (INIS)

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

    1990-01-01

    In this paper we present a methodology for identifying faulty component candidates of process malfunctions through basic physical principles of conservation, functional classification of components and information from the process schematics. The basic principles of macroscopic balance of mass, momentum and energy in thermal hydraulic control volumes are applied in a novel approach to incorporate deep knowledge into the knowledge base. Additional deep knowledge is incorporated through the functional classification of process components according to their influence in disturbing the macroscopic balance equations. Information from the process schematics is applied to identify the faulty component candidates after the type of imbalance in the control volumes is matched against the functional classification of the components. Except for the information from the process schematics, this approach is completely general and independent of the process under consideration. The use of basic first-principles, which are physically correct, and the process-independent architecture of the diagnosis procedure allow for the verification and validation of the system. A prototype process diagnosis expert system is developed and a test problem is presented to identify faulty component candidates in the presence of a single failure in a hypothetical balance of plant of a liquid metal nuclear reactor plant

  5. Target Product Profile for a Diagnostic Assay to Differentiate between Bacterial and Non-Bacterial Infections and Reduce Antimicrobial Overuse in Resource-Limited Settings: An Expert Consensus.

    Directory of Open Access Journals (Sweden)

    Sabine Dittrich

    Full Text Available Acute fever is one of the most common presenting symptoms globally. In order to reduce the empiric use of antimicrobial drugs and improve outcomes, it is essential to improve diagnostic capabilities. In the absence of microbiology facilities in low-income settings, an assay to distinguish bacterial from non-bacterial causes would be a critical first step. To ensure that patient and market needs are met, the requirements of such a test should be specified in a target product profile (TPP. To identify minimal/optimal characteristics for a bacterial vs. non-bacterial fever test, experts from academia and international organizations with expertise in infectious diseases, diagnostic test development, laboratory medicine, global health, and health economics were convened. Proposed TPPs were reviewed by this working group, and consensus characteristics were defined. The working group defined non-severely ill, non-malaria infected children as the target population for the desired assay. To provide access to the most patients, the test should be deployable to community health centers and informal health settings, and staff should require 90% and >80% for sensitivity and specificity, respectively. Other key characteristics, to account for the challenging environment at which the test is targeted, included: i time-to-result <10 min (but maximally <2 hrs; ii storage conditions at 0-40°C, ≤90% non-condensing humidity with a minimal shelf life of 12 months; iii operational conditions of 5-40°C, ≤90% non-condensing humidity; and iv minimal sample collection needs (50-100μL, capillary blood. This expert approach to define assay requirements for a bacterial vs. non-bacterial assay should guide product development, and enable targeted and timely efforts by industry partners and academic institutions.

  6. Image-based medical expert teleconsultation in acute care of injuries. A systematic review of effects on information accuracy, diagnostic validity, clinical outcome, and user satisfaction.

    Directory of Open Access Journals (Sweden)

    Marie Hasselberg

    Full Text Available OBJECTIVE: To systematically review the literature on image-based telemedicine for medical expert consultation in acute care of injuries, considering system, user, and clinical aspects. DESIGN: Systematic review of peer-reviewed journal articles. DATA SOURCES: Searches of five databases and in eligible articles, relevant reviews, and specialized peer-reviewed journals. ELIGIBILITY CRITERIA: Studies were included that covered teleconsultation systems based on image capture and transfer with the objective of seeking medical expertise for the diagnostic and treatment of acute injury care and that presented the evaluation of one or several aspects of the system based on empirical data. Studies of systems not under routine practice or including real-time interactive video conferencing were excluded. METHOD: The procedures used in this review followed the PRISMA Statement. Predefined criteria were used for the assessment of the risk of bias. The DeLone and McLean Information System Success Model was used as a framework to synthesise the results according to system quality, user satisfaction, information quality and net benefits. All data extractions were done by at least two reviewers independently. RESULTS: Out of 331 articles, 24 were found eligible. Diagnostic validity and management outcomes were often studied; fewer studies focused on system quality and user satisfaction. Most systems were evaluated at a feasibility stage or during small-scale pilot testing. Although the results of the evaluations were generally positive, biases in the methodology of evaluation were concerning selection, performance and exclusion. Gold standards and statistical tests were not always used when assessing diagnostic validity and patient management. CONCLUSIONS: Image-based telemedicine systems for injury emergency care tend to support valid diagnosis and influence patient management. The evidence relates to a few clinical fields, and has substantial methodological

  7. Image-based medical expert teleconsultation in acute care of injuries. A systematic review of effects on information accuracy, diagnostic validity, clinical outcome, and user satisfaction.

    Science.gov (United States)

    Hasselberg, Marie; Beer, Netta; Blom, Lisa; Wallis, Lee A; Laflamme, Lucie

    2014-01-01

    To systematically review the literature on image-based telemedicine for medical expert consultation in acute care of injuries, considering system, user, and clinical aspects. Systematic review of peer-reviewed journal articles. Searches of five databases and in eligible articles, relevant reviews, and specialized peer-reviewed journals. Studies were included that covered teleconsultation systems based on image capture and transfer with the objective of seeking medical expertise for the diagnostic and treatment of acute injury care and that presented the evaluation of one or several aspects of the system based on empirical data. Studies of systems not under routine practice or including real-time interactive video conferencing were excluded. The procedures used in this review followed the PRISMA Statement. Predefined criteria were used for the assessment of the risk of bias. The DeLone and McLean Information System Success Model was used as a framework to synthesise the results according to system quality, user satisfaction, information quality and net benefits. All data extractions were done by at least two reviewers independently. Out of 331 articles, 24 were found eligible. Diagnostic validity and management outcomes were often studied; fewer studies focused on system quality and user satisfaction. Most systems were evaluated at a feasibility stage or during small-scale pilot testing. Although the results of the evaluations were generally positive, biases in the methodology of evaluation were concerning selection, performance and exclusion. Gold standards and statistical tests were not always used when assessing diagnostic validity and patient management. Image-based telemedicine systems for injury emergency care tend to support valid diagnosis and influence patient management. The evidence relates to a few clinical fields, and has substantial methodological shortcomings. As in the case of telemedicine in general, user and system quality aspects are poorly

  8. 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)

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

    International Nuclear Information System (INIS)

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

    2012-01-01

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

  10. Real-Time Tele-Mentored Low Cost "Point-of-Care US" in the Hands of Paediatricians in the Emergency Department: Diagnostic Accuracy Compared to Expert Radiologists.

    Directory of Open Access Journals (Sweden)

    Floriana Zennaro

    Full Text Available The use of point-of-care ultrasonography (POC US in paediatrics is increasing. This study investigated the diagnostic accuracy of POC US in children accessing the emergency department (ED when performed by paediatricians under the remote guidance of radiologists (TELE POC.Children aged 0 to 18 years accessing the ED of a third level research hospital with eight possible clinical scenarios and without emergency/severity signs at the triage underwent three subsequent US tests: by a paediatrician guided remotely by a radiologist (TELE POC; by the same radiologist (UNBLIND RAD; by an independent blinded radiologist (BLIND RAD. Tele-radiology was implemented using low cost "commercial off-the-shelf" (COTS equipment and open-source software. Data were prospectively collected on predefined templates.Fifty-two children were enrolled, for a total of 170 ultrasound findings. Sensitivity, specificity, positive and negative predictive values of TELE POC were: 93.8, 99.7, 96.8, 99.4 when compared to UNBLIND RAD and 88.2, 99.7, 96.8, 98.7 when compared to BLIND RAD. The inter-observers agreement between the paediatricians and either the unblind or blind radiologist was excellent (k = 0.93. The mean duration of TELE POC was 6.3 minutes (95% CI 4.1 to 8.5. Technical difficulties occurred in two (3.8% cases. Quality of the transmission was rated as fair, good, very good and excellent in 7.7%, 15.4%, 42.3% and 34.6% of cases respectively, while in no case was it rated as poor.POC US performed by paediatricians in ED guided via tele-radiology by an expert radiologist (TELE POC produced reliable and timely diagnoses. Findings of this study, especially for the rarer conditions under evaluation, need further confirmation. Future research should investigate the overall benefits and the cost savings of using tele-ultrasound to perform US "at children's bedsides", under remote guidance of expert radiologists.

  11. 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.

  12. Expert systems

    International Nuclear Information System (INIS)

    Haldy, P.A.

    1988-01-01

    The definitions of the terms 'artificial intelligence' and 'expert systems', the methodology, areas of employment and limits of expert systems are discussed. The operation of an expert system is described, especially the presentation and organization of knowledge as well as interference and control. Methods and tools for expert system development are presented and their application in nuclear energy are briefly addressed. 7 figs., 2 tabs., 6 refs

  13. Expert Systems

    OpenAIRE

    Lucas, P.J.F.

    2005-01-01

    Expert systems mimic the problem-solving activity of human experts in specialized domains by capturing and representing expert knowledge. Expert systems include a knowledge base, an inference engine that derives conclusions from the knowledge, and a user interface. Knowledge may be stored as if-then rules, orusing other formalisms such as frames and predicate logic. Uncertain knowledge may be represented using certainty factors, Bayesian networks, Dempster-Shafer belief functions, or fuzzy se...

  14. EXPERT SYSTEMS

    OpenAIRE

    Georgiana Marin; Mihai Catalin Andrei

    2011-01-01

    In recent decades IT and computer systems have evolved rapidly in economic informatics field. The goal is to create user friendly information systems that respond promptly and accurately to requests. Informatics systems evolved into decision assisted systems, and such systems are converted, based on gained experience, in expert systems for creative problem solving that an organization is facing. Expert systems are aimed at rebuilding human reasoning on the expertise obtained from experts, sto...

  15. Expert System

    DEFF Research Database (Denmark)

    Hildebrandt, Thomas Troels; Cattani, Gian Luca

    2016-01-01

    An expert system is a computer system for inferring knowledge from a knowledge base, typically by using a set of inference rules. When the concept of expert systems was introduced at Stanford University in the early 1970s, the knowledge base was an unstructured set of facts. Today the knowledge b...... for the application of expert systems, but also raises issues regarding privacy and legal liability....

  16. 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.

  17. 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...

  18. Faults Images

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Through the study of faults and their effects, much can be learned about the size and recurrence intervals of earthquakes. Faults also teach us about crustal...

  19. Expert ease

    Energy Technology Data Exchange (ETDEWEB)

    1984-04-01

    Expert-ease allows the most inexperienced of computer users to build an expert system in a matter of hours. It is nothing more or less than a computer based problem-solving system. It allows the expert to preserve his or her knowledge in the form of rules, which can be applied to problems put to the system by the non-expert. The crucial piece of software at the heart of Expert-Ease extracts rules from data, and is called the analogue concept learning system. It was developed by Intelligent Terminals Ltd. and supplied to Export Software International to be incorporated into a commercially attractive package for business users. The resulting product runs on the Act Sirius and the IBM PC and compatibles. It is a well conceived and polished product with a popular appeal that should ensure widespread acceptance even at a cost of >1500 plus vat.

  20. 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

  1. Fault finder

    Science.gov (United States)

    Bunch, Richard H.

    1986-01-01

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

  2. 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

  3. 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

  4. Expert Witness

    African Journals Online (AJOL)

    Adele

    formal rules of evidence apply) to help it understand the issues of a case and ... statements on medical expert witness by professional representative bodies in .... determining the size of the financial settlement that may have to be made to the.

  5. Distributed bearing fault diagnosis based on vibration analysis

    Science.gov (United States)

    Dolenc, Boštjan; Boškoski, Pavle; Juričić, Đani

    2016-01-01

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

  6. Aspergillus antibody detection: diagnostic strategy and technical considerations from the Société Française de Mycologie Médicale (French Society for Medical Mycology) expert committee.

    Science.gov (United States)

    Persat, F; Hennequin, C; Gangneux, J P

    2017-04-01

    Until now, there has been no consensus on the best method for the detection of anti-Aspergillus antibodies, a key diagnostic tool for chronic aspergilloses. To better appreciate the usage of and confidence in these techniques, the Société Française de Mycologie Médicale (French Society for Medical Mycology; SFMM) performed a two-step survey of French experts. First, we administered an initial survey to French labs performing Aspergillus serology to depict usage of the different techniques available for Aspergillus serology. Second, an opinion poll was conducted of 40 experts via an online questionnaire. Each item was rated from 1 to 9 according to the level of agreement. The initial survey revealed that enzyme-linked immunosorbent assay (ELISA) (81%) and immunoelectrophoresis (IEP) (67%) were the most commonly used techniques for screening and confirmation, respectively. The distinction between screening and confirmation techniques was confirmed by the experts (median = 7) with a 44.2% variation coefficient. Only ELISA for screening and IEP and Western blot (WB) for confirmation were clearly considered valuable methods (median ≥8 with variation coefficients less than 30%). The use of a confirmation technique was recommended in the case of a positive result in a compatible clinical context (cystic fibrosis, for example) or during the patient's follow-up. In the case of discordant results between the screening and confirmation techniques, the experts recommended greater confidence in the results obtained with the confirmation technique. All experts emphasized the need to standardize Aspergillus serology techniques and to better define the place of each of them in the diagnosis of aspergillosis. © The Author 2016. Published by Oxford University Press on behalf of The International Society for Human and Animal Mycology. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

  7. 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.

  8. 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

  9. Development of an Expert System as a Diagnostic Support of Cervical Cancer in Atypical Glandular Cells, Based on Fuzzy Logics and Image Interpretation

    Directory of Open Access Journals (Sweden)

    Karem R. Domínguez Hernández

    2013-01-01

    Full Text Available Cervical cancer is the second largest cause of death among women worldwide. Nowadays, this disease is preventable and curable at low cost and low risk when an accurate diagnosis is done in due time, since it is the neoplasm with the highest prevention potential. This work describes the development of an expert system able to provide a diagnosis to cervical neoplasia (CN precursor injuries through the integration of fuzzy logics and image interpretation techniques. The key contribution of this research focuses on atypical cases, specifically on atypical glandular cells (AGC. The expert system consists of 3 phases: (1 risk diagnosis which consists of the interpretation of a patient’s clinical background and the risks for contracting CN according to specialists; (2 cytology images detection which consists of image interpretation (IM and the Bethesda system for cytology interpretation, and (3 determination of cancer precursor injuries which consists of in retrieving the information from the prior phases and integrating the expert system by means of a fuzzy logics (FL model. During the validation stage of the system, 21 already diagnosed cases were tested with a positive correlation in which 100% effectiveness was obtained. The main contribution of this work relies on the reduction of false positives and false negatives by providing a more accurate diagnosis for CN.

  10. Artificial intelligence applications to nuclear reactor diagnostics

    International Nuclear Information System (INIS)

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

    1987-01-01

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

  11. Clinical relevance of molecular diagnostics in gastrointestinal (GI) cancer: European Society of Digestive Oncology (ESDO) expert discussion and recommendations from the 17th European Society for Medical Oncology (ESMO)/World Congress on Gastrointestinal Cancer, Barcelona.

    Science.gov (United States)

    Baraniskin, Alexander; Van Laethem, Jean-Luc; Wyrwicz, Lucjan; Guller, Ulrich; Wasan, Harpreet S; Matysiak-Budnik, Tamara; Gruenberger, Thomas; Ducreux, Michel; Carneiro, Fatima; Van Cutsem, Eric; Seufferlein, Thomas; Schmiegel, Wolff

    2017-11-01

    In the epoch of precision medicine and personalised oncology, which aims to deliver the right treatment to the right patient, molecular genetic biomarkers are a topic of growing interest. The aim of this expert discussion and position paper is to review the current status of various molecular tests for gastrointestinal (GI) cancers and especially considering their significance for the clinical routine use. Opinion leaders and experts from diverse nationalities selected on scientific merit were asked to answer to a prepared set of questions about the current status of molecular diagnostics in different GI cancers. All answers were then discussed during a plenary session and reported here in providing a well-balanced reflection of both clinical expertise and updated evidence-based medicine. Preselected molecular genetic biomarkers that are described and disputed in the current medical literature in different GI cancers were debated, and recommendations for clinical routine practice were made whenever possible. Furthermore, the preanalytical variations were commented and proposals for quality controls of biospecimens were made. The current article summarises the recommendations of the expert committee regarding prognostic and predictive molecular genetic biomarkers in different entities of GI cancers. The briefly and comprehensively formulated guidelines should assist clinicians in the process of decision making in daily clinical practice. Copyright © 2017 Elsevier Ltd. All rights reserved.

  12. Integration of next-generation sequencing in clinical diagnostic molecular pathology laboratories for analysis of solid tumours; an expert opinion on behalf of IQN Path ASBL

    NARCIS (Netherlands)

    Deans, Zandra C.; Costa, Jose Luis; Cree, Ian; Dequeker, Els; Edsjo, Anders; Henderson, Shirley; Hummel, Michael; Ligtenberg, Marjolijn J. L.; Loddo, Marco; Machado, Jose Carlos; Marchetti, Antonio; Marquis, Katherine; Mason, Joanne; Normanno, Nicola; Rouleau, Etienne; Schuuring, Ed; Snelson, Keeda-Marie; Thunnissen, Erik; Tops, Bastiaan; Williams, Gareth; van Krieken, Han; Hall, Jacqueline A.

    The clinical demand for mutation detection within multiple genes from a single tumour sample requires molecular diagnostic laboratories to develop rapid, high-throughput, highly sensitive, accurate and parallel testing within tight budget constraints. To meet this demand, many laboratories employ

  13. Integration of next-generation sequencing in clinical diagnostic molecular pathology laboratories for analysis of solid tumours; an expert opinion on behalf of IQN Path ASBL

    NARCIS (Netherlands)

    Deans, Z.C.; Costa, J.L.; Cree, I.; Dequeker, E.; Edsjo, A.; Henderson, S.; Hummel, M.; Ligtenberg, M.J.L.; Loddo, M.; Machado, J.C.; Marchetti, A.; Marquis, K.; Mason, J.; Normanno, N.; Rouleau, E.; Schuuring, E.; Snelson, K.M.; Thunnissen, E.; Tops, B.B.; Williams, G.; Krieken, H. van; Hall, J.A.

    2017-01-01

    The clinical demand for mutation detection within multiple genes from a single tumour sample requires molecular diagnostic laboratories to develop rapid, high-throughput, highly sensitive, accurate and parallel testing within tight budget constraints. To meet this demand, many laboratories employ

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

    Science.gov (United States)

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

    2017-11-01

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

  15. Diagnostic Value of Senior Dental Students in Yazd About of Detection the Proximal Caries on Panoramic Radiographs Compared to Detection of Experts in 1394

    Directory of Open Access Journals (Sweden)

    E Romoozi

    2016-08-01

    Full Text Available Introduction: Tooth decay is the most common chronic disease of man in the world and dentists should receive the capability to accurately diagnose of tooth decay during the training courses. In addition to clinical examination, the panoramic view and intraoral radiography is usually used for the caries detection. Therefore, the detection of caries on X-ray images can have a role in treatment planning. Methods: In this analytical study, 10 panoramic radiographies that randomly selected, separately given to 30 senior dental students and 2 professors (in order to determine the gold standard. Data were analyzed using SPSS 17 software, diagnostic tables and indexes were prepared and the results were analyzed by Kappa test. Moreover, in order to determine the agreement between the professors and students about the depth of the decay the weighted kappa coefficient was used. Results: The kappa value about detection of presence or absence of proximal caries between professors and students's diagnosis was 0.428 (P value=0.001. Diagnostic sensitivity, specificity, positive predictive value and negative predictive value obtained by students in caries detection were %47, %91.9, %63 and %85.3, respectively. Coefficient of agreement in detection of depth diagnosis obtained by professors and students was 0.361(p value=0.000. Conclusion: The diagnostic capability of senior dental students about caries detection was fair and depth diagnosis was slight.

  16. Expert Systems: What Is an Expert System?

    Science.gov (United States)

    Duval, Beverly K.; Main, Linda

    1994-01-01

    Describes expert systems and discusses their use in libraries. Highlights include parts of an expert system; expert system shells; an example of how to build an expert system; a bibliography of 34 sources of information on expert systems in libraries; and a list of 10 expert system shells used in libraries. (Contains five references.) (LRW)

  17. Lithium-Ion Cell Fault Detection by Single-Point Impedance Diagnostic and Degradation Mechanism Validation for Series-Wired Batteries Cycled at 0 °C

    Directory of Open Access Journals (Sweden)

    Corey T. Love

    2018-04-01

    Full Text Available The utility of a single-point impedance-based technique to monitor the state-of-health of a pack of four 18650 lithium-ion cells wired in series (4S was demonstrated in a previous publication. This work broadens the applicability of the single-point monitoring technique to identify temperature induced faults within 4S packs at 0 °C by two distinct discharge cut-off thresholds: individual cell cut-off and pack voltage cut-off. The results show how the single-point technique applied to a 4S pack can identify cell faults induced by low temperature degradation when plotted on a unique state-of-health map. Cell degradation is validated through an extensive incremental capacity technique to quantify capacity loss due to low temperature cycling and investigate the underpinnings of cell failure.

  18. Medicolegal affairs. International Academy of Cytology Task Force summary. Diagnostic Cytology Towards the 21st Century: An International Expert Conference and Tutorial.

    Science.gov (United States)

    Frable, W J; Austin, R M; Greening, S E; Collins, R J; Hillman, R L; Kobler, T P; Koss, L G; Mitchell, H; Perey, R; Rosenthal, D L; Sidoti, M S; Somrak, T M

    1998-01-01

    Increasing litigation over alleged false negative cervical cytologic (CC) smears threatens the viability of this test for cervical cancer detection. The problem appears to be largely American but is beginning to appear in some other countries. In the vast majority of cases there is either a settlement or jury verdict for the plaintiff based largely on the testimony of expert witnesses. Cases are judged on an individual basis without significant consideration of the general performance of the CC smear in laboratories operating in compliance with a wide array of laboratory regulations and with documented and comprehensive quality control practices in place. It is acknowledged that there are problem laboratories and cytology practitioners. There is an emerging issue of automated preparation and screening devices and issues of informed patient consent. Cytology professionals have done an extraordinary and commendable job of educating the public about the benefits of the CC smear. We have been less successful and conscientious about explaining and defining the limitations of the CC test. There is a need for public and professional education as to the benefits and limitations of the CC smear for cervical cancer detection. The process suggested is to work with women's groups, public health agencies, government agencies, and state and national legislatures and to coordinate professional committees working on liability issues. Contextual information could be included with the CC smear report to indicate that a negative report confers a low probability of developing cervical cancer. It is suggested that appropriate language and a menu of statements be developed. Increased efforts should be directed to physician education with respect to informed consent concerning the benefits and limitations of CC smear testing and the application of new technology to improve smear accuracy. The process should include development of appropriate statements on the use of alternative

  19. 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

  20. Operational expert system applications in Europe

    CERN Document Server

    Zarri, Gian Piero

    1992-01-01

    Operational Expert System Applications in Europe describes the representative case studies of the operational expert systems (ESs) that are used in Europe.This compilation provides examples of operational ES that are realized in 10 different European countries, including countries not usually examined in the standard reviews of the field.This book discusses the decision support system using several artificial intelligence tools; expert systems for fault diagnosis on computerized numerical control (CNC) machines; and expert consultation system for personal portfolio management. The failure prob

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

    International Nuclear Information System (INIS)

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

    2001-01-01

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

  2. 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.

  3. 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

  4. Transforming the diagnosis of tuberculosis: an editorial board member's opinion at the 15th year of Expert Review of Molecular Diagnostics.

    Science.gov (United States)

    Pai, Madhukar; Raison, Claire

    2015-03-01

    Interview with Professor Madhukar Pai, MD, PhD by Claire Raison (Commissioning Editor). Professor Madhukar Pai did his medical training and community medicine residency in Vellore, India. He completed his PhD in epidemiology at the University of California, Berkeley (CA, USA) and a postdoctoral fellowship at the University of California, San Francisco (CA, USA). He is currently an associate professor of epidemiology at McGill University in Montreal (Canada). He serves as the Director of Global Health Programs, and as an Associate Director of the McGill International Tuberculosis Centre. In addition, he serves as a Consultant for the Bill & Melinda Gates Foundation. He also serves on the Scientific Advisory Committee of the Foundation for Innovative New Diagnostics, Geneva, Switzerland. His research is focused on improving the diagnosis and treatment of tuberculosis, especially in high-burden countries such as India and South Africa. His research is supported by grant funding from the Gates Foundation, Grand Challenges Canada and Canadian Institutes of Health Research. He has more than 200 peer-reviewed publications. He is recipient of the Union Scientific Prize, Chanchlani Global Health Research Award and Stars in Global Health award from Grand Challenges Canada, and is a member of the Royal Society of Canada.

  5. Computer-assisted detection of pulmonary nodules: evaluation of diagnostic performance using an expert knowledge-based detection system with variable reconstruction slice thickness settings

    International Nuclear Information System (INIS)

    Marten, Katharina; Grillhoesl, Andreas; Seyfarth, Tobias; Rummeny, Ernst J.; Engelke, Christoph; Obenauer, Silvia

    2005-01-01

    The purpose of this study was to evaluate the performance of a computer-assisted diagnostic (CAD) tool using various reconstruction slice thicknesses (RST). Image data of 20 patients undergoing multislice CT for pulmonary metastasis were reconstructed at 4.0, 2.0 and 0.75 mm RST and assessed by two blinded radiologists (R1 and R2) and CAD. Data were compared against an independent reference standard. Nodule subgroups (diameter >10, 4-10, <4 mm) were assessed separately. Statistical methods were the ROC analysis and Mann-Whitney Utest. CAD was outperformed by readers at 4.0 mm (Az = 0.18, 0.62 and 0.69 for CAD, R1 and R2, respectively; P<0.05), comparable at 2.0 mm (Az = 0.57, 0.70 and 0.69 for CAD, R1 and R2, respectively), and superior using 0.75 mm RST (Az = 0.80, 0.70 and 0.70 and sensitivity = 0.74, 0.53 and 0.53 for CAD, R1 and R2, respectively; P<0.05). Reader performances were significantly enhanced by CAD (Az = 0.93 and 0.95 for R1 + CAD and R2 + CAD, respectively, P<0.05). The CAD advantage was best for nodules <10 mm (detection rates = 93.3, 89.9, 47.9 and 47.9% for R1 + CAD, R2 + CAD, R1 and R2, respectively). CAD using 0.75 mm RST outperformed radiologists in nodules below 10 mm in diameter and should be used to replace a second radiologist. CAD is not recommended for 4.0 mm RST. (orig.)

  6. 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.

  7. Upgrade of the automatic analysis system in the TJ-II Thomson Scattering diagnostic: New image recognition classifier and fault condition detection

    NARCIS (Netherlands)

    Makili, L.; Vega, J.; Dormido-Canto, S.; Pastor, I.; Pereira, A.; Farias, G.; Portas, A.; Perez-Risco, D.; Rodriguez-Fernandez, M. C.; Busch, P.

    2010-01-01

    An automatic image classification system based on support vector machines (SVM) has been in operation for years in the TJ-II Thomson Scattering diagnostic. It recognizes five different types of images: CCD camera background, measurement of stray light without plasma or in a collapsed discharge,

  8. 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.

  9. Upgrade of the automatic analysis system in the TJ-II Thomson Scattering diagnostic: New image recognition classifier and fault condition detection

    International Nuclear Information System (INIS)

    Makili, L.; Vega, J.; Dormido-Canto, S.; Pastor, I.; Pereira, A.; Farias, G.; Portas, A.; Perez-Risco, D.; Rodriguez-Fernandez, M.C.; Busch, P.

    2010-01-01

    An automatic image classification system based on support vector machines (SVM) has been in operation for years in the TJ-II Thomson Scattering diagnostic. It recognizes five different types of images: CCD camera background, measurement of stray light without plasma or in a collapsed discharge, image during ECH phase, image during NBI phase and image after reaching the cut off density during ECH heating. Each kind of image implies the execution of different application software. Due to the fact that the recognition system is based on a learning system and major modifications have been carried out in both the diagnostic (optics) and TJ-II plasmas (injected power), the classifier model is no longer valid. A new SVM model has been developed with the current conditions. Also, specific error conditions in the data acquisition process can automatically be detected and managed now. The recovering process has been automated, thereby avoiding the loss of data in ensuing discharges.

  10. Upgrade of the automatic analysis system in the TJ-II Thomson Scattering diagnostic: New image recognition classifier and fault condition detection

    Energy Technology Data Exchange (ETDEWEB)

    Makili, L. [Dpto. Informatica y Automatica - UNED, Madrid (Spain); Vega, J. [Asociacion EURATOM/CIEMAT para Fusion, Madrid (Spain); Dormido-Canto, S., E-mail: sebas@dia.uned.e [Dpto. Informatica y Automatica - UNED, Madrid (Spain); Pastor, I.; Pereira, A. [Asociacion EURATOM/CIEMAT para Fusion, Madrid (Spain); Farias, G. [Dpto. Informatica y Automatica - UNED, Madrid (Spain); Portas, A.; Perez-Risco, D.; Rodriguez-Fernandez, M.C. [Asociacion EURATOM/CIEMAT para Fusion, Madrid (Spain); Busch, P. [FOM Institut voor PlasmaFysica Rijnhuizen, Nieuwegein (Netherlands)

    2010-07-15

    An automatic image classification system based on support vector machines (SVM) has been in operation for years in the TJ-II Thomson Scattering diagnostic. It recognizes five different types of images: CCD camera background, measurement of stray light without plasma or in a collapsed discharge, image during ECH phase, image during NBI phase and image after reaching the cut off density during ECH heating. Each kind of image implies the execution of different application software. Due to the fact that the recognition system is based on a learning system and major modifications have been carried out in both the diagnostic (optics) and TJ-II plasmas (injected power), the classifier model is no longer valid. A new SVM model has been developed with the current conditions. Also, specific error conditions in the data acquisition process can automatically be detected and managed now. The recovering process has been automated, thereby avoiding the loss of data in ensuing discharges.

  11. MO-DE-BRA-05: EUTEMPE-RX: Combining E-Learning and Face-To-Face Training to Build Expert Knowledge, Skills and Competences for Medical Physicists in Diagnostic and Interventional Radiology

    International Nuclear Information System (INIS)

    Bosmans, H; Van Peteghem, N; Creten, S; Mackenzie, A; Vano, E; Borowski, M; Christofides, S; Caruana, C

    2016-01-01

    Purpose: In 2013, the EURATOM authorities of the European Commission decided to support the Horizon2020 project submission ‘EUTEMPE-RX’ that aimed for a new set of course modules to train medical physicists in diagnostic and interventional radiology to expert level with small group deep learning. Each module would consist of 2 phases: an e-learning and a face-to-face phase, each phase requiring typically 40h of participant time. Methods: The European Federation (EFOMP) and 13 European partners, all of them selected for their excellent scientific and/or educational skills, led the 12 course modules. A quality manual ensured the quality of course content and organization. Educational workshops familiarized the teachers with e-learning techniques and methods for assessment. Content was set in accordance with the EC document RP174 that lists learning outcomes in terms of knowledge, skills and competences (KSCs) for different specialties and levels of medical physics. Surveys for stake holder satisfaction were prepared. Results: Today the course modules are being realized. The modules cover most of the KSCs in RP174 document. Teachers have challenged the participants with unique tasks: case studies in medical physics leadership, Monte Carlo simulation of a complete x-ray imaging chain, development of a task specific QA protocol, compilation of optimization plans, simulation tasks with anthropomorphic breast models, etc. Participants undertook practical sessions in modern hospitals and visited a synchrotron facility, a calibration lab, screening organizations, etc. Feedback form quality surveys was very positive and constructive. A sustainability plan has been worked out. Conclusion: The modules have enabled the participants to develop their KSCs and cope with challenges in medical physics. The sustainability plan will be implemented to continue the unique combined e-learning and face to face training at high level training in diagnostic and interventional radiology

  12. MO-DE-BRA-05: EUTEMPE-RX: Combining E-Learning and Face-To-Face Training to Build Expert Knowledge, Skills and Competences for Medical Physicists in Diagnostic and Interventional Radiology

    Energy Technology Data Exchange (ETDEWEB)

    Bosmans, H [University Hospitals Leuven, Leuven (Belgium); Van Peteghem, N; Creten, S [KU Leuven, Leuven, Vlaams Brabant (Belgium); Mackenzie, A [Royal Surrey County Hospital, Guildford, Surrey (United Kingdom); Vano, E [San Carlos University Hospital, Madrid (Spain); Borowski, M [Klinikum Braunschweig, Braunschweig (Germany); Christofides, S [Nicosia General Hospital, Nicosia (Cyprus); Caruana, C [University of Malta, Msida (Malta)

    2016-06-15

    Purpose: In 2013, the EURATOM authorities of the European Commission decided to support the Horizon2020 project submission ‘EUTEMPE-RX’ that aimed for a new set of course modules to train medical physicists in diagnostic and interventional radiology to expert level with small group deep learning. Each module would consist of 2 phases: an e-learning and a face-to-face phase, each phase requiring typically 40h of participant time. Methods: The European Federation (EFOMP) and 13 European partners, all of them selected for their excellent scientific and/or educational skills, led the 12 course modules. A quality manual ensured the quality of course content and organization. Educational workshops familiarized the teachers with e-learning techniques and methods for assessment. Content was set in accordance with the EC document RP174 that lists learning outcomes in terms of knowledge, skills and competences (KSCs) for different specialties and levels of medical physics. Surveys for stake holder satisfaction were prepared. Results: Today the course modules are being realized. The modules cover most of the KSCs in RP174 document. Teachers have challenged the participants with unique tasks: case studies in medical physics leadership, Monte Carlo simulation of a complete x-ray imaging chain, development of a task specific QA protocol, compilation of optimization plans, simulation tasks with anthropomorphic breast models, etc. Participants undertook practical sessions in modern hospitals and visited a synchrotron facility, a calibration lab, screening organizations, etc. Feedback form quality surveys was very positive and constructive. A sustainability plan has been worked out. Conclusion: The modules have enabled the participants to develop their KSCs and cope with challenges in medical physics. The sustainability plan will be implemented to continue the unique combined e-learning and face to face training at high level training in diagnostic and interventional radiology

  13. Upgrade of the Automatic Analysis System in the TJ-II Thomson Scattering Diagnostic: New Image Recognition Classifier and Fault Condition Detection

    Energy Technology Data Exchange (ETDEWEB)

    Makili, L.; Dormido-Canto, S. [UNED, Madrid (Spain); Vega, J.; Pastor, I.; Pereira, A.; Portas, A.; Perez-Risco, D.; Rodriguez-Fernandez, M. [Association EuratomCIEMAT para Fusion, Madrid (Spain); Busch, P. [FOM Instituut voor PlasmaFysica Rijnhuizen, Nieuwegein (Netherlands)

    2009-07-01

    Full text of publication follows: An automatic image classification system has been in operation for years in the TJ-II Thomson diagnostic. It recognizes five different types of images: CCD camera background, measurement of stray light without plasma or in a collapsed discharge, image during ECH phase, image during NBI phase and image after reaching the cut o density during ECH heating. Each kind of image implies the execution of different application software. Therefore, the classification system was developed to launch the corresponding software in an automatic way. The method to recognize the several classes was based on a learning system, in particular Support Vector Machines (SVM). Since the first implementation of the classifier, a relevant improvement has been accomplished in the diagnostic: a new notch filter is in operation, having a larger stray-light rejection at the ruby wavelength than the previous filter. On the other hand, its location in the optical system has been modified. As a consequence, the stray light pattern in the CCD image is located in a different position. In addition to these transformations, the power of neutral beams injected in the TJ-II plasma has been increased about a factor of 2. Due to the fact that the recognition system is based on a learning system and major modifications have been carried out in both the diagnostic (optics) and TJ-II plasmas (injected power), the classifier model is no longer valid. The creation of a new model (also based on SVM) under the present conditions has been necessary. Finally, specific error conditions in the data acquisition process can automatically be detected now. The recovering process can be automated, thereby avoiding the loss of data in ensuing discharges. (authors)

  14. Diagnostic reasoning strategies and diagnostic success.

    Science.gov (United States)

    Coderre, S; Mandin, H; Harasym, P H; Fick, G H

    2003-08-01

    Cognitive psychology research supports the notion that experts use mental frameworks or "schemes", both to organize knowledge in memory and to solve clinical problems. The central purpose of this study was to determine the relationship between problem-solving strategies and the likelihood of diagnostic success. Think-aloud protocols were collected to determine the diagnostic reasoning used by experts and non-experts when attempting to diagnose clinical presentations in gastroenterology. Using logistic regression analysis, the study found that there is a relationship between diagnostic reasoning strategy and the likelihood of diagnostic success. Compared to hypothetico-deductive reasoning, the odds of diagnostic success were significantly greater when subjects used the diagnostic strategies of pattern recognition and scheme-inductive reasoning. Two other factors emerged as independent determinants of diagnostic success: expertise and clinical presentation. Not surprisingly, experts outperformed novices, while the content area of the clinical cases in each of the four clinical presentations demonstrated varying degrees of difficulty and thus diagnostic success. These findings have significant implications for medical educators. It supports the introduction of "schemes" as a means of enhancing memory organization and improving diagnostic success.

  15. Application of Fault Tree Analysis and Fuzzy Neural Networks to Fault Diagnosis in the Internet of Things (IoT) for Aquaculture.

    Science.gov (United States)

    Chen, Yingyi; Zhen, Zhumi; Yu, Huihui; Xu, Jing

    2017-01-14

    In the Internet of Things (IoT) equipment used for aquaculture is often deployed in outdoor ponds located in remote areas. Faults occur frequently in these tough environments and the staff generally lack professional knowledge and pay a low degree of attention in these areas. Once faults happen, expert personnel must carry out maintenance outdoors. Therefore, this study presents an intelligent method for fault diagnosis based on fault tree analysis and a fuzzy neural network. In the proposed method, first, the fault tree presents a logic structure of fault symptoms and faults. Second, rules extracted from the fault trees avoid duplicate and redundancy. Third, the fuzzy neural network is applied to train the relationship mapping between fault symptoms and faults. In the aquaculture IoT, one fault can cause various fault symptoms, and one symptom can be caused by a variety of faults. Four fault relationships are obtained. Results show that one symptom-to-one fault, two symptoms-to-two faults, and two symptoms-to-one fault relationships can be rapidly diagnosed with high precision, while one symptom-to-two faults patterns perform not so well, but are still worth researching. This model implements diagnosis for most kinds of faults in the aquaculture IoT.

  16. Application of Fault Tree Analysis and Fuzzy Neural Networks to Fault Diagnosis in the Internet of Things (IoT for Aquaculture

    Directory of Open Access Journals (Sweden)

    Yingyi Chen

    2017-01-01

    Full Text Available In the Internet of Things (IoT equipment used for aquaculture is often deployed in outdoor ponds located in remote areas. Faults occur frequently in these tough environments and the staff generally lack professional knowledge and pay a low degree of attention in these areas. Once faults happen, expert personnel must carry out maintenance outdoors. Therefore, this study presents an intelligent method for fault diagnosis based on fault tree analysis and a fuzzy neural network. In the proposed method, first, the fault tree presents a logic structure of fault symptoms and faults. Second, rules extracted from the fault trees avoid duplicate and redundancy. Third, the fuzzy neural network is applied to train the relationship mapping between fault symptoms and faults. In the aquaculture IoT, one fault can cause various fault symptoms, and one symptom can be caused by a variety of faults. Four fault relationships are obtained. Results show that one symptom-to-one fault, two symptoms-to-two faults, and two symptoms-to-one fault relationships can be rapidly diagnosed with high precision, while one symptom-to-two faults patterns perform not so well, but are still worth researching. This model implements diagnosis for most kinds of faults in the aquaculture IoT.

  17. 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.

  18. Expert and competent non-expert visual cues during simulated diagnosis in intensive care.

    Science.gov (United States)

    McCormack, Clare; Wiggins, Mark W; Loveday, Thomas; Festa, Marino

    2014-01-01

    The aim of this study was to examine the information acquisition strategies of expert and competent non-expert intensive care physicians during two simulated diagnostic scenarios involving respiratory distress in an infant. Specifically, the information acquisition performance of six experts and 12 competent non-experts was examined using an eye-tracker during the initial 90 s of the assessment of the patient. The results indicated that, in comparison to competent non-experts, experts recorded longer mean fixations, irrespective of the scenario. When the dwell times were examined against specific areas of interest, the results revealed that competent non-experts recorded greater overall dwell times on the nurse, where experts recorded relatively greater dwell times on the head and face of the manikin. In the context of the scenarios, experts recorded differential dwell times, spending relatively more time on the head and face during the seizure scenario than during the coughing scenario. The differences evident between experts and competent non-experts were interpreted as evidence of the relative availability of task-specific cues or heuristics in memory that might direct the process of information acquisition amongst expert physicians. The implications are discussed for the training and assessment of diagnostic skills.

  19. Expert and Competent Non-Expert Visual Cues during Simulated Diagnosis in Intensive Care

    Directory of Open Access Journals (Sweden)

    Clare eMcCormack

    2014-08-01

    Full Text Available The aim of this study was to examine the information acquisition strategies of expert and competent non-expert intensive care physicians during two simulated diagnostic scenarios involving respiratory distress in an infant. Specifically, the information acquisition performance of six experts and 12 competent non-experts was examined using an eye tracker during the initial 90 seconds of the assessment of the patient. The results indicated that, in comparison to competent non-experts, experts recorded longer mean fixations, irrespective of the scenario. When the dwell times were examined against specific areas of interest, the results revealed that competent non-experts recorded greater overall dwell times on the nurse, where experts recorded relatively greater dwell times on the head and face of the manikin. In the context of the scenarios, experts recorded differential dwell times, spending relatively more time on the head and face during the seizure scenario than during the coughing scenario. The differences evident between experts and competent non-experts were interpreted as evidence of the relative availability of task-specific cues or heuristics in memory that might direct the process of information acquisition amongst expert physicians. The implications are discussed for the training and assessment of diagnostic skills.

  20. Optimal fault signal estimation

    NARCIS (Netherlands)

    Stoorvogel, Antonie Arij; Niemann, H.H.; Saberi, A.; Sannuti, P.

    2002-01-01

    We consider here both fault identification and fault signal estimation. Regarding fault identification, we seek either exact or almost fault identification. On the other hand, regarding fault signal estimation, we seek either $H_2$ optimal, $H_2$ suboptimal or Hinfinity suboptimal estimation. By

  1. 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

  2. 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.

  3. 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

  4. 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.

  5. Investigation of display issues relevant to the presentation of aircraft fault information

    Science.gov (United States)

    Allen, Donald M.

    1989-01-01

    This research, performed as a part of NASA Langley's Faultfinder project, investigated display implementation issues related to the introduction of real time fault diagnostic systems into next generation commercial aircraft. Three major issues were investigated: visual display styles for presenting fault related information to the crew, the form the output from the expert system should take, and methods for filtering fault related information for presentation to the crew. Twenty-four flight familiar male volunteers participated as subjects. Five subjects were NASA test pilots, six were Commercial Airline Pilots, seven were Air Force Lear Jet pilots, and six were NASA personnel familiar with flight (non-pilots). Subjects were presented with aircraft subsystem information on a CRT screen. They were required to identify the subsystems presented in a display and to remember the state (normal or abnormal) of subsystem parameter information contained in the display. The results of the study indicated that in the simpler experimental test cases (i.e., those involving single subsystem failures and composite hypothesis displays) subjects' performance did not differ across the different display formats. However, for the more complex cases (i.e., those involving multiple subsystem faults and multiple hypotheses displays), subjects' performance was superior in the text- and picture-based display formats compared to the symbol-based format. In addition, the findings suggest that a layered approached to information display is appropriate.

  6. 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.

  7. Expert systems and nuclear safety

    International Nuclear Information System (INIS)

    Beltracchi, L.

    1990-01-01

    The US Nuclear Regulatory Commission (NRC) and the Electric Power Research Institute have initiated a broad-based exploration of means to evaluate the potential applications of expert systems in the nuclear industry. This exploratory effort will assess the use of expert systems to augment the diagnostic and decision-making capabilities of personnel with the goal of enhancing productivity, reliability, and performance. The initial research effort is the development and documentation of guidelines for verifying and validating (V and V) expert systems. An initial application of expert systems in the nuclear industry is to aid operations and maintenance personnel in decision-making tasks. The scope of the decision aiding covers all types of cognitive behavior consisting of skill, rule, and knowledge-based behavior. For example, procedure trackers were designed and tested to support rule-based behavior. Further, these systems automate many of the tedious, error-prone human monitoring tasks, thereby reducing the potential for human error. The paper version of the procedure contains the knowledge base and the rules and thus serves as the basis of the design verification of the procedure tracker. Person-in-the-loop tests serve as the basis for the validation of a procedure tracker. When conducting validation tests, it is important to ascertain that the human retains the locus of control in the use of the expert system

  8. 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

  9. 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

  10. Medical Expert Systems Survey

    OpenAIRE

    Abu-Nasser, Bassem S.

    2017-01-01

    International audience; There is an increased interest in the area of Artificial Intelligence in general and expert systems in particular. Expert systems are rapidly growing technology. Expert systems are a branch of Artificial Intelligence which is having a great impact on many fields of human life. Expert systems use human expert knowledge to solve complex problems in many fields such as Health, science, engineering, business, and weather forecasting. Organizations employing the technology ...

  11. Expert system for the diagnosis of the condition and performance of centrifugal pumps

    Energy Technology Data Exchange (ETDEWEB)

    Jantunen, E; Vaehae-Pietilae, K; Pesonen, K [Technical Research Centre of Finland, Manufacturing Technology, Espoo (Finland)

    1998-12-31

    A brief description of the results of a study concerning the maintenance and downtime costs in Finnish pumping is given. The leakage of seals was found to be the fault that causes the highest downtime and maintenance costs. A small laboratory arrangement has been used to test the effectiveness of various condition monitoring methods. This information has been used in the development of a diagnostic expert system called CEPDIA, which can be used for diagnosing the condition of a pump and its components. The diagnosis is based on measuring results obtained from sensors and on information about maintenance actions carried out with the pump and its components. The principles of the CEPDIA expert system are described. A database is included in the system for handling and saving the measurement results, technical information on the pumps and maintenance actions carried out with the pumps. The diagnosis can also be based on vibration signature analysis, which is quite effective in determining which fault is the actual cause of malfunction of the pump or its components. CEPDIA can also be used to calculate of the efficiency of the electrical motor and the pump. CEPDIA has been tested in the diagnosis of 63 pumps. The average efficiency in pumping was less than 40 %, and more than 10 % of the pumps were pumping with less than 10 % efficiency. (orig.) 11 refs.

  12. Expert system for the diagnosis of the condition and performance of centrifugal pumps

    Energy Technology Data Exchange (ETDEWEB)

    Jantunen, E.; Vaehae-Pietilae, K.; Pesonen, K. [Technical Research Centre of Finland, Manufacturing Technology, Espoo (Finland)

    1997-12-31

    A brief description of the results of a study concerning the maintenance and downtime costs in Finnish pumping is given. The leakage of seals was found to be the fault that causes the highest downtime and maintenance costs. A small laboratory arrangement has been used to test the effectiveness of various condition monitoring methods. This information has been used in the development of a diagnostic expert system called CEPDIA, which can be used for diagnosing the condition of a pump and its components. The diagnosis is based on measuring results obtained from sensors and on information about maintenance actions carried out with the pump and its components. The principles of the CEPDIA expert system are described. A database is included in the system for handling and saving the measurement results, technical information on the pumps and maintenance actions carried out with the pumps. The diagnosis can also be based on vibration signature analysis, which is quite effective in determining which fault is the actual cause of malfunction of the pump or its components. CEPDIA can also be used to calculate of the efficiency of the electrical motor and the pump. CEPDIA has been tested in the diagnosis of 63 pumps. The average efficiency in pumping was less than 40 %, and more than 10 % of the pumps were pumping with less than 10 % efficiency. (orig.) 11 refs.

  13. 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

  14. Information Based Fault Diagnosis

    DEFF Research Database (Denmark)

    Niemann, Hans Henrik; Poulsen, Niels Kjølstad

    2008-01-01

    Fault detection and isolation, (FDI) of parametric faults in dynamic systems will be considered in this paper. An active fault diagnosis (AFD) approach is applied. The fault diagnosis will be investigated with respect to different information levels from the external inputs to the systems. These ...

  15. Knowledge-based fault diagnosis system for refuse collection vehicle

    International Nuclear Information System (INIS)

    Tan, CheeFai; Juffrizal, K.; Khalil, S. N.; Nidzamuddin, M. Y.

    2015-01-01

    The refuse collection vehicle is manufactured by local vehicle body manufacturer. Currently; the company supplied six model of the waste compactor truck to the local authority as well as waste management company. The company is facing difficulty to acquire the knowledge from the expert when the expert is absence. To solve the problem, the knowledge from the expert can be stored in the expert system. The expert system is able to provide necessary support to the company when the expert is not available. The implementation of the process and tool is able to be standardize and more accurate. The knowledge that input to the expert system is based on design guidelines and experience from the expert. This project highlighted another application on knowledge-based system (KBS) approached in trouble shooting of the refuse collection vehicle production process. The main aim of the research is to develop a novel expert fault diagnosis system framework for the refuse collection vehicle

  16. Knowledge-based fault diagnosis system for refuse collection vehicle

    Energy Technology Data Exchange (ETDEWEB)

    Tan, CheeFai; Juffrizal, K.; Khalil, S. N.; Nidzamuddin, M. Y. [Centre of Advanced Research on Energy, Universiti Teknikal Malaysia Melaka, Hang Tuah Jaya, Durian Tunggal, Melaka (Malaysia)

    2015-05-15

    The refuse collection vehicle is manufactured by local vehicle body manufacturer. Currently; the company supplied six model of the waste compactor truck to the local authority as well as waste management company. The company is facing difficulty to acquire the knowledge from the expert when the expert is absence. To solve the problem, the knowledge from the expert can be stored in the expert system. The expert system is able to provide necessary support to the company when the expert is not available. The implementation of the process and tool is able to be standardize and more accurate. The knowledge that input to the expert system is based on design guidelines and experience from the expert. This project highlighted another application on knowledge-based system (KBS) approached in trouble shooting of the refuse collection vehicle production process. The main aim of the research is to develop a novel expert fault diagnosis system framework for the refuse collection vehicle.

  17. Bayesian networks applied to process diagnostics. Applications in energy industry

    Energy Technology Data Exchange (ETDEWEB)

    Widarsson, Bjoern (ed.); Karlsson, Christer; Dahlquist, Erik [Maelardalen Univ., Vaesteraas (Sweden); Nielsen, Thomas D.; Jensen, Finn V. [Aalborg Univ. (Denmark)

    2004-10-01

    Uncertainty in process operation occurs frequently in heat and power industry. This makes it hard to find the occurrence of an abnormal process state from a number of process signals (measurements) or find the correct cause to an abnormality. Among several other methods, Bayesian Networks (BN) is a method to build a model which can handle uncertainty in both process signals and the process itself. The purpose of this project is to investigate the possibilities to use BN for fault detection and diagnostics in combined heat and power industries through execution of two different applications. Participants from Aalborg University represent the knowledge of BN and participants from Maelardalen University have the experience from modelling heat and power applications. The co-operation also includes two energy companies; Elsam A/S (Nordjyllandsverket) and Maelarenergi AB (Vaesteraas CHP-plant), where the two applications are made with support from the plant personnel. The project ended out in two quite different applications. At Nordjyllandsverket, an application based (due to the lack of process knowledge) on pure operation data is build with capability to detect an abnormal process state in a coal mill. Detection is made through a conflict analysis when entering process signals into a model built by analysing the operation database. The application at Maelarenergi is built with a combination of process knowledge and operation data and can detect various faults caused by the fuel. The process knowledge is used to build a causal network structure and the structure is then trained by data from the operation database. Both applications are made as off-online applications, but they are ready for being run on-line. The performance of fault detection and diagnostics are good, but a lack of abnormal process states with known cause reduces the evaluation possibilities. Advantages with combining expert knowledge of the process with operation data are the possibility to represent

  18. Recent advances in control and diagnostics development and application

    International Nuclear Information System (INIS)

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

    1989-01-01

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

  19. Vehicle fault diagnostics and management system

    Science.gov (United States)

    Gopal, Jagadeesh; Gowthamsachin

    2017-11-01

    This project is a kind of advanced automatic identification technology, and is more and more widely used in the fields of transportation and logistics. It looks over the main functions with like Vehicle management, Vehicle Speed limit and Control. This system starts with authentication process to keep itself secure. Here we connect sensors to the STM32 board which in turn is connected to the car through Ethernet cable, as Ethernet in capable of sending large amounts of data at high speeds. This technology involved clearly shows how a careful combination of software and hardware can produce an extremely cost-effective solution to a problem.

  20. 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

  1. Expert auditors’ services classification

    OpenAIRE

    Jolanta Wisniewska

    2013-01-01

    The profession of an expert auditor is a public trust occupation with a distinctive feature of taking responsibility for actions in the public interest. The main responsibility of expert auditors is performing financial auditing; however, expert auditors are prepared to carry out different tasks which encompass a wide plethora of financial and auditing services for different kinds of institutions and companies. The aim of the article is first of all the description of expert auditors’ service...

  2. Fault tree handbook

    International Nuclear Information System (INIS)

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

    1981-01-01

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

  3. Delegating Decisions to Experts

    Science.gov (United States)

    Li, Hao; Suen, Wing

    2004-01-01

    We present a model of delegation with self-interested and privately informed experts. A team of experts with extreme but opposite biases is acceptable to a wide range of decision makers with diverse preferences, but the value of expertise from such a team is low. A decision maker wants to appoint experts who are less partisan than he is in order…

  4. The commission of independent experts has labeled Mochovce as safe

    International Nuclear Information System (INIS)

    Grujbar, V.

    1998-01-01

    An independent commission of experts, appointed by IAEA, said that it did not find any faults concerning the integrity of the pressure vessel of the reactor in first block of the NPP Mochovce. The commission, comprising experts from the U.S.A., Belgium, Finland, Germany and Russia, was given the same documents as the Austrian mission, appointed by the office of the Austrian Chancellor, in May. The Austrian experts then expressed two serious concerns about the security of the first block in Mochovce.The experts of the IAEA agreed that the real condition of Mochovce is a lot better that shown in the technical documentation and they did not find any faults. IAEA was in this case, for the first time, an arbiter solving an international dispute about security of a NPP

  5. Fault Tolerant Feedback Control

    DEFF Research Database (Denmark)

    Stoustrup, Jakob; Niemann, H.

    2001-01-01

    An architecture for fault tolerant feedback controllers based on the Youla parameterization is suggested. It is shown that the Youla parameterization will give a residual vector directly in connection with the fault diagnosis part of the fault tolerant feedback controller. It turns out...... that there is a separation be-tween the feedback controller and the fault tolerant part. The closed loop feedback properties are handled by the nominal feedback controller and the fault tolerant part is handled by the design of the Youla parameter. The design of the fault tolerant part will not affect the design...... of the nominal feedback con-troller....

  6. Earthquakes and Tectonics Expert Judgment Elicitation Project

    International Nuclear Information System (INIS)

    Coppersmith, K.J.; Perman, R.C.; Youngs, R.R.

    1993-02-01

    This report summarizes the results of the Earthquakes and Tectonics Expert Judgement Excitation Project sponsored by the Electric Power Research Institute (EPRI). The objectives of this study were two-fold: (1) to demonstrate methods for the excitation of expert judgement, and (2) to quantify the uncertainties associated with earthquake and tectonics issues for use in the EPRI-HLW performance assessment. Specifically, the technical issue considered is the probability of differential fault displacement through the proposed repository at Yucca Mountain, Nevada. For this study, a strategy for quantifying uncertainties was developed that relies on the judgements of multiple experts. A panel of seven geologists and seismologists was assembled to quantify the uncertainties associated with earthquake and tectonics issues for the performance assessment model. A series of technical workshops focusing on these issues were conducted. Finally, each expert was individually interviewed in order to elicit his judgement regarding the technical issues and to provide the technical basis for his assessment. This report summarizes the methodologies used to elicit the judgements of the earthquakes and tectonics experts (termed ''specialists''), and summarizes the technical assessments made by the expert panel

  7. 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...

  8. Diagnostic dilemma

    DEFF Research Database (Denmark)

    Feldt-Rasmussen, Ulla; Dobrovolny, Robert; Nazarenko, Irina

    2011-01-01

    Fabry disease, an X-linked lysosomal storage disorder, results from the deficient activity of a-galactosidase A (a-Gal A). In affected males, the clinical diagnosis is confirmed by the markedly decreased a-Gal A activity. However, in female heterozygotes, the a-Gal A activity can range from low t...... on enzyme replacement therapy. Thus, gene dosage analyses can detect large deletions (>50bp) in suspect heterozygotes for X-linked and autosomal dominant diseases that are "sequencing cryptic," resolving molecular diagnostic dilemmas....... to normal due to random X-chromosomal inactivation, and diagnostic confirmation requires identification of the family's a-Gal A gene mutation. In a young female who had occasional acroparesthesias, corneal opacities, and 15 to 50% of the lower limit of normal leukocyte a-Gal A activity, a-Gal A sequencing...... in two expert laboratories did not identify a confirmatory mutation, presenting a diagnostic dilemma. A renal biopsy proved diagnostic and renewed efforts to detect an a-Gal A mutation. Subsequent gene dosage analyses identified a large a-Gal A deletion confirming her heterozygosity, and she was started...

  9. Expert status and performance.

    Directory of Open Access Journals (Sweden)

    Mark A Burgman

    Full Text Available Expert judgements are essential when time and resources are stretched or we face novel dilemmas requiring fast solutions. Good advice can save lives and large sums of money. Typically, experts are defined by their qualifications, track record and experience. The social expectation hypothesis argues that more highly regarded and more experienced experts will give better advice. We asked experts to predict how they will perform, and how their peers will perform, on sets of questions. The results indicate that the way experts regard each other is consistent, but unfortunately, ranks are a poor guide to actual performance. Expert advice will be more accurate if technical decisions routinely use broadly-defined expert groups, structured question protocols and feedback.

  10. A living PSA based on use of expert systems

    International Nuclear Information System (INIS)

    Ancelin, C.; Bouissou, M.; Le, P.; De Saint-Quentin, S.; Villatte, N.

    1989-01-01

    This paper presents the expert systems that are developed by EDF in the framework of the French PSA. Aimed at automatically generating reliability models (fault trees, state graphs....), these expert systems are used for the reliability studies of safety systems in the Paluel nuclear power plant. Beyond the description of the implemented method, this paper insists on the new approach proposed to the reliability engineer, when using artificial intelligence techniques

  11. A knowledge based on-line diagnostic system for the fast breeder reactor KNKII

    International Nuclear Information System (INIS)

    Eggert, H.; Scherer, K.P.; Stiller, P.

    1989-01-01

    In the nuclear research center at Karlsruhe, a diagnostic expert system is developed to supervise a fast breeder process (KNKII). The problem is to detect critical phases in the beginning state before fault propagation. The expert system itself is integrated in a computer network (realized by a local area network), where different computers are involved as special detection systems (for example acoustic noise, temperature noise, covergas monitoring and so on), which produce partial diagnoses, based on intelligent signal processing techniques like pattern recognition. Additional to the detection systems a process computer is integrated as well as a test computer, which simulates hypothetical and real fault data. On the logical top level the expert system manages the partial diagnoses of the detection systems with the operating data of the process computer and to produce a final diagnosis including the explanation part for operator support. The knowledge base is developed by typical Artificial Intelligence tools. Both fact based and rule based knowledge representations are stored in form of flavors and predications. The inference engine operates on a rule based approach. Specific detail knowledge, based on experience about any years, is available to influence the decision process by increasing or decreasing of the generated hypotheses. In a meta knowledge base, a rule master triggers the special domain experts and contributes the tasks to the specific rule complexes. Such a system management guarantees a problem solving strategy, which operates event triggered and situation specific in a local inference domain. (author). 3 refs, 6 figs, 2 tabs

  12. An expert fault diagnosis system for auto wire bond machine

    NARCIS (Netherlands)

    Tan, C.F.

    2007-01-01

    In the modern world, computing is essential in all aspects of manufacturing activity. Computers have brought to life terms like artificial intelligence, and have played a critical role in reinvention of manufacturing industry. In continuing quest to decrease the interval time between

  13. Thyroid diagnostics

    Energy Technology Data Exchange (ETDEWEB)

    Scriba, P C; Boerner, W; Emrich, S; Gutekunst, R; Herrmann, J; Horn, K; Klett, M; Krueskemper, H L; Pfannenstiel, P; Pickardt, C R

    1985-03-01

    None of the in-vitro and in-vivo methods listed permits on unambiguous diagnosis when applied alone, owing to the fact that similar or even identical findings are obtained for various individual parameters in different thyroid diseases. Further, especially the in-vitro tests are also subject to extrathyroidal effects which may mask the typical findings. The limited and varying specificity and sensitivity of the tests applied, as well as the falsification of results caused by the patients' idiosyncracies and the methodology, make it necessary to interpret and evaluate the in-vivo and in-vitro findings only if the clinical situation (anamnesis and physical examination) is known. For maximum diagnostic quality of the tests, the initial probability of the assumed type of thyroid disease must be increased (formulation of the clinical problem). The concepts of exclusion diagnosis and identification must be distinguished as well as the diagnosis of functional disturbances on the one hand and of thyroid diseases on the other. Both of this requires a qualified, specific and detailed anamnesis and examination procedure, and the clinical examination remains the obligatory basis of clinical diagnostics. In case of inexplicable discrepancies between the clinical manifestations and the findings obtained with specific methods, or between the findings obtained with a specific method, the patient should be referred to an expert institution, or the expert institution should be consulted.

  14. Thyroid diagnostics

    International Nuclear Information System (INIS)

    Scriba, P.C.; Boerner, W.; Emrich, S.; Gutekunst, R.; Herrmann, J.; Horn, K.; Klett, M.; Krueskemper, H.L.; Pfannenstiel, P.; Pickardt, C.R.; Reiners, C.; Reinwein, D.; Schleusener, H.

    1985-01-01

    None of the in-vitro and in-vivo methods listed permits on unambiguous diagnosis when applied alone, owing to the fact that similar or even identical findings are obtained for various individual parameters in different thyroid diseases. Further, especially the in-vitro tests are also subject to extrathyroidal effects which may mask the typical findings. The limited and varying specificity and sensitivity of the tests applied, as well as the falsification of results caused by the patients' idiosyncracies and the methodology, make it necessary to interpret and evaluate the in-vivo and in-vitro findings only if the clinical situation (anamnesis and physical examination) is known. For maximum diagnostic quality of the tests, the initial probability of the assumed type of thyroid disease must be increased (formulation of the clinical problem). The concepts of exclusion diagnosis and identification must be distinguished as well as the diagnosis of functional disturbances on the one hand and of thyroid diseases on the other. Both of this requires a qualified, specific and detailed anamnesis and examination procedure, and the clinical examination remains the obligatory basis of clinical diagnostics. In case of inexplicable discrepancies between the clinical manifestations and the findings obtained with specific methods, or between the findings obtained with a specific method, the patient should be referred to an expert institution, or the expert institution should be consulted. (orig./MG) [de

  15. Design of fault simulator

    Energy Technology Data Exchange (ETDEWEB)

    Gabbar, Hossam A. [Faculty of Energy Systems and Nuclear Science, University of Ontario Institute of Technology (UOIT), Ontario, L1H 7K4 (Canada)], E-mail: hossam.gabbar@uoit.ca; Sayed, Hanaa E.; Osunleke, Ajiboye S. [Okayama University, Graduate School of Natural Science and Technology, Division of Industrial Innovation Sciences Department of Intelligent Systems Engineering, Okayama 700-8530 (Japan); Masanobu, Hara [AspenTech Japan Co., Ltd., Kojimachi Crystal City 10F, Kojimachi, Chiyoda-ku, Tokyo 102-0083 (Japan)

    2009-08-15

    Fault simulator is proposed to understand and evaluate all possible fault propagation scenarios, which is an essential part of safety design and operation design and support of chemical/production processes. Process models are constructed and integrated with fault models, which are formulated in qualitative manner using fault semantic networks (FSN). Trend analysis techniques are used to map real time and simulation quantitative data into qualitative fault models for better decision support and tuning of FSN. The design of the proposed fault simulator is described and applied on experimental plant (G-Plant) to diagnose several fault scenarios. The proposed fault simulator will enable industrial plants to specify and validate safety requirements as part of safety system design as well as to support recovery and shutdown operation and disaster management.

  16. Iowa Bedrock Faults

    Data.gov (United States)

    Iowa State University GIS Support and Research Facility — This fault coverage locates and identifies all currently known/interpreted fault zones in Iowa, that demonstrate offset of geologic units in exposure or subsurface...

  17. Layered Fault Management Architecture

    National Research Council Canada - National Science Library

    Sztipanovits, Janos

    2004-01-01

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

  18. 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...

  19. 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.)

  20. Fault zone hydrogeology

    Science.gov (United States)

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

    2013-12-01

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

  1. Performance based fault diagnosis

    DEFF Research Database (Denmark)

    Niemann, Hans Henrik

    2002-01-01

    Different aspects of fault detection and fault isolation in closed-loop systems are considered. It is shown that using the standard setup known from feedback control, it is possible to formulate fault diagnosis problems based on a performance index in this general standard setup. It is also shown...

  2. Use of an on-line Fuzzy-logic expert system for water chemistry

    International Nuclear Information System (INIS)

    Fandrich, J.; Metzner, W.

    1998-01-01

    The requirements for availability and operating economy of power plants have become steadily more stringent over the last few years. In addition to technological advances (e.g. in the form of new design measures, processes and materials), manufacturers have also increasingly applied secondary measures to enhance the safety and operating economy of power plant units. These include ever more sophisticated process monitoring and analytical systems and, (in recent times) diagnostic systems which perform continuous assessment of the plant condition to allow imminent changes that cam lead to damage and faults to be detected at the earliest possible time. The following paper presents an expert system, based on Fuzzy logic, which is used to perform a wide variety of tasks in the field of NPP water chemistry diagnostics. Thanks to the general nature of the approach selected, the system kernel is identical for all solutions which were implemented despite the wide variety of tasks and their diverse needs. This would not have been possible without the development and application of powerful and flexible engineering tools which can provide solutions to different types of problems at no extra effort. It will be shown in which way the system builds up diagnoses from the collected on-line data via a system -specific and easy- to-learn language and several tools. The presented module DIWA (Diagnostic System of Water Chemistry) was directly derived from the DIGEST system (diagnostic expert system for turbomachinery), which was developed over the last few years at the Power Generation Group (KWU) of the Siemens AG. (author)

  3. Application of expert systems

    Energy Technology Data Exchange (ETDEWEB)

    Basden, A

    1983-11-01

    This article seeks to bring together a number of issues relevant to the application of expert systems by discussing their advantages and limitations, their roles and benefits, and the influence that real-life applications might have on the design of expert systems software. Part of the expert systems strategy of one major chemical company is outlined. Because it was in constructing one particular expert system that many of these issues became important this system is described briefly at the start of the paper and used to illustrate much of the later discussion. It is of the plausible-inference type and has application in the field of materials engineering. 22 references.

  4. Being an expert

    International Nuclear Information System (INIS)

    Brechet, Y.; Musseau, O.; Bruna, G.; Sperandio, M.; Roulleaux-Dugage, M.; Andrieux, S.; Metteau, L.

    2014-01-01

    This series of short articles are dedicated to the role of the expert in the enterprise. There is an important difference between a scientific counsellor and an expert, the expert, recognized by his peers, can speak publicly in his field of expertise but has a duty of transparency while the job of a scientific counsellor requires confidentiality. The making and the use of an expert in an enterprise requires a dedicated organization. The organization of the expertise in 5 enterprises in nuclear industry are considered: CEA (French Alternative Energies and Atomic Energy Commission), IRSN (Institute of Radioprotection and Nuclear Safety), AREVA, ANDRA (National Radioactive Waste Management Agency) and EDF (Electricity of France)

  5. 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.

  6. Diagnostic and Prognostic Models for Generator Step-Up Transformers

    Energy Technology Data Exchange (ETDEWEB)

    Vivek Agarwal; Nancy J. Lybeck; Binh T. Pham

    2014-09-01

    In 2014, the online monitoring (OLM) of active components project under the Light Water Reactor Sustainability program at Idaho National Laboratory (INL) focused on diagnostic and prognostic capabilities for generator step-up transformers. INL worked with subject matter experts from the Electric Power Research Institute (EPRI) to augment and revise the GSU fault signatures previously implemented in the Electric Power Research Institute’s (EPRI’s) Fleet-Wide Prognostic and Health Management (FW-PHM) Suite software. Two prognostic models were identified and implemented for GSUs in the FW-PHM Suite software. INL and EPRI demonstrated the use of prognostic capabilities for GSUs. The complete set of fault signatures developed for GSUs in the Asset Fault Signature Database of the FW-PHM Suite for GSUs is presented in this report. Two prognostic models are described for paper insulation: the Chendong model for degree of polymerization, and an IEEE model that uses a loading profile to calculates life consumption based on hot spot winding temperatures. Both models are life consumption models, which are examples of type II prognostic models. Use of the models in the FW-PHM Suite was successfully demonstrated at the 2014 August Utility Working Group Meeting, Idaho Falls, Idaho, to representatives from different utilities, EPRI, and the Halden Research Project.

  7. Knowledge Representation Using Multilevel Flow Model in Expert System

    International Nuclear Information System (INIS)

    Wang, Wenlin; Yang, Ming

    2015-01-01

    As for the knowledge representation, of course, there are a great many methods available for knowledge representation. These include frames, causal models, and many others. This paper presents a novel method called Multilevel Flow Model (MFM), which is used for knowledge representation in G2 expert system. Knowledge representation plays a vital role in constructing knowledge bases. Moreover, it also has impact on building of generic fault model as well as knowledge bases. The MFM is particularly useful to describe system knowledge concisely as domain map in expert system when domain experts are not available

  8. Knowledge Representation Using Multilevel Flow Model in Expert System

    Energy Technology Data Exchange (ETDEWEB)

    Wang, Wenlin; Yang, Ming [Harbin Engineering University, Harbin (China)

    2015-05-15

    As for the knowledge representation, of course, there are a great many methods available for knowledge representation. These include frames, causal models, and many others. This paper presents a novel method called Multilevel Flow Model (MFM), which is used for knowledge representation in G2 expert system. Knowledge representation plays a vital role in constructing knowledge bases. Moreover, it also has impact on building of generic fault model as well as knowledge bases. The MFM is particularly useful to describe system knowledge concisely as domain map in expert system when domain experts are not available.

  9. 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.

  10. Computer Based Expert Systems.

    Science.gov (United States)

    Parry, James D.; Ferrara, Joseph M.

    1985-01-01

    Claims knowledge-based expert computer systems can meet needs of rural schools for affordable expert advice and support and will play an important role in the future of rural education. Describes potential applications in prediction, interpretation, diagnosis, remediation, planning, monitoring, and instruction. (NEC)

  11. Real time expert systems

    International Nuclear Information System (INIS)

    Asami, Tohru; Hashimoto, Kazuo; Yamamoto, Seiichi

    1992-01-01

    Recently, aiming at the application to the plant control for nuclear reactors and traffic and communication control, the research and the practical use of the expert system suitable to real time processing have become conspicuous. In this report, the condition for the required function to control the object that dynamically changes within a limited time is presented, and the technical difference between the real time expert system developed so as to satisfy it and the expert system of conventional type is explained with the actual examples and from theoretical aspect. The expert system of conventional type has the technical base in the problem-solving equipment originating in STRIPS. The real time expert system is applied to the fields accompanied by surveillance and control, to which conventional expert system is hard to be applied. The requirement for the real time expert system, the example of the real time expert system, and as the techniques of realizing real time processing, the realization of interruption processing, dispersion processing, and the mechanism of maintaining the consistency of knowledge are explained. (K.I.)

  12. Expert systems: An overview

    International Nuclear Information System (INIS)

    Verdejo, F.

    1985-01-01

    The purpose of this article is to introduce readers to the basic principles of rule-based expert systems. Four topics are discussed in subsequent sections: (1) Definition; (2) Structure of an expert system; (3) State of the art and (4) Impact and future research. (orig.)

  13. Trendwatch combining expert opinion

    NARCIS (Netherlands)

    Hendrix, E.M.T.; Kornelis, M.; Pegge, S.M.; Galen, van M.A.

    2006-01-01

    In this study, focus is on a systematic way to detect future changes in trends that may effect the dynamics in the agro-food sector, and on the combination of opinions of experts. For the combination of expert opinions, the usefulness of multilevel models is investigated. Bayesian data analysis is

  14. Modeling of HVAC operational faults in building performance simulation

    International Nuclear Information System (INIS)

    Zhang, Rongpeng; Hong, Tianzhen

    2017-01-01

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

  15. TREDRA, Minimal Cut Sets Fault Tree Plot Program

    International Nuclear Information System (INIS)

    Fussell, J.B.

    1983-01-01

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

  16. An examination of expert systems activities within the nuclear industry

    International Nuclear Information System (INIS)

    Bernard, J.A.; Washio, Takashi.

    1988-01-01

    This paper provides an overview of a detailed evaluation that the authors recently completed on expert systems applications within the nuclear industry. That evaluation examined the motivation for utilizing expert systems, identified the areas to which they were being applied, and provided an assessment of their utility. Listed here are some of the salient findings of that report. (1) Utilities are developing their own artificial intelligence tools rather than using commercial products. (2) Few expert systems are being developed for the express purpose of capturing human expertise. (3) A number of successful expert systems have been developed to assist in plant design, management, and maintenance scheduling. (4) Interactive diagnostic systems are being developed for the analysis of physical processes that vary slowly. (5) Real-time diagnostic expert systems are currently at the cutting edge of the technology. (6) Operator adviser and emergency response expert systems constitute ∼25% of the total. (7) Research on the use of expert systems for reactor control is quite active. (8) Too few quantitative evaluations of the benefits of expert systems to reactor operators have been performed. The operator's need is for timely, factual information on plant status. Hence, the true challenge to expert systems is real-time diagnostics

  17. 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....

  18. Cafts: computer aided fault tree analysis

    International Nuclear Information System (INIS)

    Poucet, A.

    1985-01-01

    The fault tree technique has become a standard tool for the analysis of safety and reliability of complex system. In spite of the costs, which may be high for a complete and detailed analysis of a complex plant, the fault tree technique is popular and its benefits are fully recognized. Due to this applications of these codes have mostly been restricted to simple academic examples and rarely concern complex, real world systems. In this paper an interactive approach to fault tree construction is presented. The aim is not to replace the analyst, but to offer him an intelligent tool which can assist him in modeling complex systems. Using the CAFTS-method, the analyst interactively constructs a fault tree in two phases: (1) In a first phase he generates an overall failure logic structure of the system; the macrofault tree. In this phase, CAFTS features an expert system approach to assist the analyst. It makes use of a knowledge base containing generic rules on the behavior of subsystems and components; (2) In a second phase the macrofault tree is further refined and transformed in a fully detailed and quantified fault tree. In this phase a library of plant-specific component failure models is used

  19. 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.

  20. Optimization of a dynamic uncertain causality graph for fault diagnosis in nuclear power plant

    Institute of Scientific and Technical Information of China (English)

    Yue Zhao; Francesco Di Maio; Enrico Zio; Qin Zhang; Chun-Ling Dong; Jin-Ying Zhang

    2017-01-01

    Fault diagnostics is important for safe operation of nuclear power plants (NPPs).In recent years,data-driven approaches have been proposed and implemented to tackle the problem,e.g.,neural networks,fuzzy and neurofuzzy approaches,support vector machine,K-nearest neighbor classifiers and inference methodologies.Among these methods,dynamic uncertain causality graph (DUCG)has been proved effective in many practical cases.However,the causal graph construction behind the DUCG is complicate and,in many cases,results redundant on the symptoms needed to correctly classify the fault.In this paper,we propose a method to simplify causal graph construction in an automatic way.The method consists in transforming the expert knowledge-based DCUG into a fuzzy decision tree (FDT) by extracting from the DUCG a fuzzy rule base that resumes the used symptoms at the basis of the FDT.Genetic algorithm (GA) is,then,used for the optimization of the FDT,by performing a wrapper search around the FDT:the set of symptoms selected during the iterative search are taken as the best set of symptoms for the diagnosis of the faults that can occur in the system.The effectiveness of the approach is shown with respect to a DUCG model initially built to diagnose 23 faults originally using 262 symptoms of Unit-1 in the Ningde NPP of the China Guangdong Nuclear Power Corporation.The results show that the FDT,with GA-optimized symptoms and diagnosis strategy,can drive the construction of DUCG and lower the computational burden without loss of accuracy in diagnosis.

  1. Optimization of a dynamic uncertain causality graph for fault diagnosis in nuclear power plant

    Institute of Scientific and Technical Information of China (English)

    Yue Zhao; Francesco Di Maio; Enrico Zio; Qin Zhang; Chun-Ling Dong; Jin-Ying Zhang

    2017-01-01

    Fault diagnostics is important for safe operation of nuclear power plants (NPPs).In recent years,data-driven approaches have been proposed and implemented to tackle the problem,e.g.,neural networks,fuzzy and neurofuzzy approaches,support vector machine,K-nearest neighbor classifiers and inference methodologies.Among these methods,dynamic uncertain causality graph (DUCG) has been proved effective in many practical cases.However,the causal graph construction behind the DUCG is complicate and,in many cases,results redundant on the symptoms needed to correctly classify the fault.In this paper,we propose a method to simplify causal graph construction in an automatic way.The method consists in transforming the expert knowledge-based DCUG into a fuzzy decision tree (FDT) by extracting from the DUCG a fuzzy rule base that resumes the used symptoms at the basis of the FDT.Genetic algorithm (GA) is,then,used for the optimization of the FDT,by performing a wrapper search around the FDT:the set of symptoms selected during the iterative search are taken as the best set of symptoms for the diagnosis of the faults that can occur in the system.The effectiveness of the approach is shown with respect to a DUCG model initially built to diagnose 23 faults originally using 262 symptoms of Unit-1 in the Ningde NPP of the China Guangdong Nuclear Power Corporation.The results show that the FDT,with GA-optimized symptoms and diagnosis strategy,can drive the construction of DUCG and lower the computational burden without loss of accuracy in diagnosis.

  2. 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

  3. 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...

  4. The opinion of experts in the assessment of reliability in nuclear power plant operation

    International Nuclear Information System (INIS)

    Akersten, P.A.; Wirstad, J.

    1983-06-01

    An inventory of methods used for quantifying of the opinion of experts for use in fault tree evaluations is presented. A number of different methods are evaluated and future research is recommended for three, namely 1. Saatys Analytical Hierarchy Process. 2. Embreys SLIM-method with variations. 3. Methods for feed-back from the expert group during evaluation.(authors)

  5. Expert Panel Elicitation

    Energy Technology Data Exchange (ETDEWEB)

    Jensen, M. [Swedish Radiation Protection Authority, Stockholm (Sweden). Dept. of Waste Management and Environmental Protection; Hora, S.C. [Univ. of Hawaii, Hilo, HI (United States)

    2005-09-15

    Scientists are now frequently in a situation where data cannot be easily assessed, since they may have conflicting or uncertain sources. While expert judgment reflects private choices, it is possible both reduce the personal aspect as well as in crease confidence in the judgments by using formal protocols for choice and elicitation of experts. A full-scale elicitation made on seismicity following glaciation, now in its late phase and presented here in a preliminary form, illustrates the value of the technique and some essential issues in connection with the decision to launch such a project. The results show an unusual low variation between the experts.

  6. Experts on public trial

    DEFF Research Database (Denmark)

    Blok, Anders

    2007-01-01

    a case study of the May 2003 Danish consensus conference on environmental economics as a policy tool, the article reflects on the politics of expert authority permeating practices of public participation. Adopting concepts from the sociology of scientific knowledge (SSK), the conference is seen......-than-successful defense in the citizen perspective. Further, consensus conferences are viewed alternatively as "expert dissent conferences," serving to disclose a multiplicity of expert commitments. From this perspective, some challenges for democratizing expertise through future exercises in public participation...

  7. 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

  8. Distributed expert systems for nuclear reactor control

    International Nuclear Information System (INIS)

    Otaduy, P.J.

    1992-01-01

    A network of distributed expert systems is the heart of a prototype supervisory control architecture developed at the Oak Ridge National Laboratory (ORNL) for an advanced multimodular reactor. Eight expert systems encode knowledge on signal acquisition, diagnostics, safeguards, and control strategies in a hybrid rule-based, multiprocessing and object-oriented distributed computing environment. An interactive simulation of a power block consisting of three reactors and one turbine provides a realistic, testbed for performance analysis of the integrated control system in real-time. Implementation details and representative reactor transients are discussed

  9. 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

  10. Expert system for nuclear power plant feedwater system diagnosis

    International Nuclear Information System (INIS)

    Meguro, R.; Kinoshita, Y.; Sato, T.; Yokota, Y.; Yokota, M.

    1987-01-01

    The Expert System for Nuclear Power Plant Feedwater System Diagnosis has been developed to assist maintenance engineers in nuclear power plants. This system adopts the latest process computer TOSBAC G8050 and the expert system developing tool TDES2, and has a large scale knowledge base which consists of the expert knowledge and experience of engineers in many fields. The man-machine system, which has been developed exclusively for diagnosis, improves the man-machine interface and realizes the graphic displays of diagnostic process and path, stores diagnostic results and searches past reference

  11. Experts' meeting: Maintenance '83

    International Nuclear Information System (INIS)

    1983-01-01

    The brochure presents, in full wording, 20 papers read at the experts' meeting ''Maintenance '83'' in Wiesbaden. Most of the papers discuss reliability data (acquisition, evaluation, processing) of nearly all fields of industry. (RW) [de

  12. Industrial disasters - the expert systems solution

    International Nuclear Information System (INIS)

    Sachs, P.

    1986-01-01

    Six mistakes by the operators led to the accident at the Cherobyl nuclear reactor. These have been studied. It is suggested that an expert systems approach could prevent similar accidents. The expert system is a new approach to software programming where programs are required to perform intelligent analyses of complex situations. It separates the knowledge of a problem from the procedural code that performs the decision. An expert system will evaluate data and indicate a priority on alarms in real time. Now software systems can detect the cause of a problem in a process plant and present their findings to the operators in the control room. This should enable operators to make the correct decisions as they will know which underlying process faults are causing the alarms to operate. The Chernobyl post-mortem meeting made 13 proposals for improving safety. Two in particular are noted as relevant to expert advice systems; international collaboration on man-reactor relationships and a conference to explore the balance of automation and human action to minimise operating errors. (U.K.)

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

    Science.gov (United States)

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

    1988-01-01

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

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

    International Nuclear Information System (INIS)

    Martin, M.

    2000-01-01

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

  15. 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.

  16. 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

  17. Fault tree graphics

    International Nuclear Information System (INIS)

    Bass, L.; Wynholds, H.W.; Porterfield, W.R.

    1975-01-01

    Described is an operational system that enables the user, through an intelligent graphics terminal, to construct, modify, analyze, and store fault trees. With this system, complex engineering designs can be analyzed. This paper discusses the system and its capabilities. Included is a brief discussion of fault tree analysis, which represents an aspect of reliability and safety modeling

  18. How do normal faults grow?

    OpenAIRE

    Blækkan, Ingvild; Bell, Rebecca; Rotevatn, Atle; Jackson, Christopher; Tvedt, Anette

    2018-01-01

    Faults grow via a sympathetic increase in their displacement and length (isolated fault model), or by rapid length establishment and subsequent displacement accrual (constant-length fault model). To test the significance and applicability of these two models, we use time-series displacement (D) and length (L) data extracted for faults from nature and experiments. We document a range of fault behaviours, from sympathetic D-L fault growth (isolated growth) to sub-vertical D-L growth trajectorie...

  19. Characterization of leaky faults

    International Nuclear Information System (INIS)

    Shan, Chao.

    1990-05-01

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

  20. 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.

  1. 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.

  2. 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.

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

    Science.gov (United States)

    Du, Jun; Wang, Shaoping; Zhang, Haiyan

    2013-04-01

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

  4. Fault detection and reliability, knowledge based and other approaches

    International Nuclear Information System (INIS)

    Singh, M.G.; Hindi, K.S.; Tzafestas, S.G.

    1987-01-01

    These proceedings are split up into four major parts in order to reflect the most significant aspects of reliability and fault detection as viewed at present. The first part deals with knowledge-based systems and comprises eleven contributions from leading experts in the field. The emphasis here is primarily on the use of artificial intelligence, expert systems and other knowledge-based systems for fault detection and reliability. The second part is devoted to fault detection of technological systems and comprises thirteen contributions dealing with applications of fault detection techniques to various technological systems such as gas networks, electric power systems, nuclear reactors and assembly cells. The third part of the proceedings, which consists of seven contributions, treats robust, fault tolerant and intelligent controllers and covers methodological issues as well as several applications ranging from nuclear power plants to industrial robots to steel grinding. The fourth part treats fault tolerant digital techniques and comprises five contributions. Two papers, one on reactor noise analysis, the other on reactor control system design, are indexed separately. (author)

  5. Bevel Gearbox Fault Diagnosis using Vibration Measurements

    Directory of Open Access Journals (Sweden)

    Hartono Dennis

    2016-01-01

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

  6. Waste disposal experts meet

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1959-01-15

    Problems connected with the disposal into the sea of radioactive wastes from peaceful uses of atomic energy are being examined by a panel of experts, convened by the International Atomic Energy Agency. These experts from eight different countries held a first meeting at IAEA headquarters in Vienna from 4-9 December 1958, under the chairmanship of Dr. Harry Brynielsson, Director General of the Swedish Atomic Energy Company. The countries represented are: Canada, Czechoslovakia, France, Japan, Netherlands, United Kingdom and United States. The group will meet again in 1959. (author)

  7. Pathogenesis and diagnostic criteria for rickets and osteomalacia - proposal by an expert panel supported by Ministry of Health, Labour and Welfare, Japan, The Japanese Society for Bone and Mineral Research and The Japan Endocrine Society.

    Science.gov (United States)

    Fukumoto, Seiji; Ozono, Keiichi; Michigami, Toshimi; Minagawa, Masanori; Okazaki, Ryo; Sugimoto, Toshitsugu; Takeuchi, Yasuhiro; Matsumoto, Toshio

    2015-01-01

    Rickets and osteomalacia are diseases characterized by impaired mineralization of bone matrix. Recent investigations revealed that the causes for rickets and osteomalacia are quite variable. While these diseases can severely impair the quality of life of the affected patients, rickets and osteomalacia can be completely cured or at least respond to treatment when properly diagnosed and treated according to the specific causes. On the other hand, there are no standard criteria to diagnose rickets or osteomalacia nationally and internationally. Therefore, we summarize the definition and pathogenesis of rickets and osteomalacia, and propose the diagnostic criteria and a flowchart for the differential diagnosis of various causes for these diseases. We hope that these criteria and flowchart are clinically useful for the proper diagnosis and management of patients with these diseases.

  8. Pathogenesis and diagnostic criteria for rickets and osteomalacia--proposal by an expert panel supported by the Ministry of Health, Labour and Welfare, Japan, the Japanese Society for Bone and Mineral Research, and the Japan Endocrine Society.

    Science.gov (United States)

    Fukumoto, Seiji; Ozono, Keiichi; Michigami, Toshimi; Minagawa, Masanori; Okazaki, Ryo; Sugimoto, Toshitsugu; Takeuchi, Yasuhiro; Matsumoto, Toshio

    2015-09-01

    Rickets and osteomalacia are diseases characterized by impaired mineralization of bone matrix. Recent investigations have revealed that the causes of rickets and osteomalacia are quite variable. Although these diseases can severely impair the quality of life of affected patients, rickets and osteomalacia can be completely cured or at least respond to treatment when properly diagnosed and treated according to the specific causes. On the other hand, there are no standard criteria to diagnose rickets or osteomalacia nationally and internationally. Therefore, we summarize the definition and pathogenesis of rickets and osteomalacia, and propose diagnostic criteria and a flowchart for the differential diagnosis of various causes of these diseases. We hope that these criteria and the flowchart are clinically useful for the proper diagnosis and management of these diseases.

  9. Price competition between an expert and a non-expert

    OpenAIRE

    Bouckaert, J.M.C.; Degryse, H.A.

    1998-01-01

    This paper characterizes price competition between an expert and a non-expert. In contrast with the expert, the non-expert’s repair technology is not always successful. Consumers visit the expert after experiencing an unsuccessful match at the non-expert. This re-entry affects the behaviour of both sellers. For low enough probability of successful repair at the non-expert, all consumers first visit the non-expert, and a ‘timid-pricing’ equilibrium results. If the non-expert’s repair technolog...

  10. ECG Rhythm Analysis with Expert and Learner-Generated Schemas in Novice Learners

    Science.gov (United States)

    Blissett, Sarah; Cavalcanti, Rodrigo; Sibbald, Matthew

    2015-01-01

    Although instruction using expert-generated schemas is associated with higher diagnostic performance, implementation is resource intensive. Learner-generated schemas are an alternative, but may be limited by increases in cognitive load. We compared expert- and learner-generated schemas for learning ECG rhythm interpretation on diagnostic accuracy,…

  11. Fault isolability conditions for linear systems with additive faults

    DEFF Research Database (Denmark)

    Niemann, Hans Henrik; Stoustrup, Jakob

    2006-01-01

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

  12. 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.

  13. Fault Analysis in Cryptography

    CERN Document Server

    Joye, Marc

    2012-01-01

    In the 1970s researchers noticed that radioactive particles produced by elements naturally present in packaging material could cause bits to flip in sensitive areas of electronic chips. Research into the effect of cosmic rays on semiconductors, an area of particular interest in the aerospace industry, led to methods of hardening electronic devices designed for harsh environments. Ultimately various mechanisms for fault creation and propagation were discovered, and in particular it was noted that many cryptographic algorithms succumb to so-called fault attacks. Preventing fault attacks without

  14. Fuzzy probability based fault tree analysis to propagate and quantify epistemic uncertainty

    International Nuclear Information System (INIS)

    Purba, Julwan Hendry; Sony Tjahyani, D.T.; Ekariansyah, Andi Sofrany; Tjahjono, Hendro

    2015-01-01

    Highlights: • Fuzzy probability based fault tree analysis is to evaluate epistemic uncertainty in fuzzy fault tree analysis. • Fuzzy probabilities represent likelihood occurrences of all events in a fault tree. • A fuzzy multiplication rule quantifies epistemic uncertainty of minimal cut sets. • A fuzzy complement rule estimate epistemic uncertainty of the top event. • The proposed FPFTA has successfully evaluated the U.S. Combustion Engineering RPS. - Abstract: A number of fuzzy fault tree analysis approaches, which integrate fuzzy concepts into the quantitative phase of conventional fault tree analysis, have been proposed to study reliabilities of engineering systems. Those new approaches apply expert judgments to overcome the limitation of the conventional fault tree analysis when basic events do not have probability distributions. Since expert judgments might come with epistemic uncertainty, it is important to quantify the overall uncertainties of the fuzzy fault tree analysis. Monte Carlo simulation is commonly used to quantify the overall uncertainties of conventional fault tree analysis. However, since Monte Carlo simulation is based on probability distribution, this technique is not appropriate for fuzzy fault tree analysis, which is based on fuzzy probabilities. The objective of this study is to develop a fuzzy probability based fault tree analysis to overcome the limitation of fuzzy fault tree analysis. To demonstrate the applicability of the proposed approach, a case study is performed and its results are then compared to the results analyzed by a conventional fault tree analysis. The results confirm that the proposed fuzzy probability based fault tree analysis is feasible to propagate and quantify epistemic uncertainties in fault tree analysis

  15. Operation and Structure of an Artificial Intelligence Expert Consultative System for Reading and Learning.

    Science.gov (United States)

    Balajthy, Ernest

    1989-01-01

    The article examines decision-making expert systems and discusses their implications for diagnosis and prescription of reading difficulties. A detailed description of how a reading diagnostic expert system might operate to aid classroom teachers is followed by a discussion of advantages and limitations of expert systems for educational use.…

  16. Fault tolerant control based on active fault diagnosis

    DEFF Research Database (Denmark)

    Niemann, Hans Henrik

    2005-01-01

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

  17. Expert Systems Research.

    Science.gov (United States)

    Duda, Richard O.; Shortliffe, Edward H.

    1983-01-01

    Discusses a class of artificial intelligence computer programs (often called "expert systems" because they address problems normally thought to require human specialists for their solution) intended to serve as consultants for decision making. Also discusses accomplishments (including information systematization in medical diagnosis and…

  18. Computers Simulate Human Experts.

    Science.gov (United States)

    Roberts, Steven K.

    1983-01-01

    Discusses recent progress in artificial intelligence in such narrowly defined areas as medical and electronic diagnosis. Also discusses use of expert systems, man-machine communication problems, novel programing environments (including comments on LISP and LISP machines), and types of knowledge used (factual, heuristic, and meta-knowledge). (JN)

  19. Expert Cold Structure Development

    Science.gov (United States)

    Atkins, T.; Demuysere, P.

    2011-05-01

    The EXPERT Program is funded by ESA. The objective of the EXPERT mission is to perform a sub-orbital flight during which measurements of critical aero- thermodynamic phenomena will be obtained by using state-of-the-art instrumentation. As part of the EXPERT Flight Segment, the responsibility of the Cold Structure Development Design, Manufacturing and Validation was committed to the Belgian industrial team SONACA/SABCA. The EXPERT Cold Structure includes the Launcher Adapter, the Bottom Panel, the Upper Panel, two Cross Panels and the Parachute Bay. An additional Launcher Adapter was manufactured for the separation tests. The selected assembly definition and manufacturing technologies ( machined parts and sandwich panels) were dictated classically by the mass and stiffness, but also by the CoG location and the sensitive separation interface. Used as support for the various on-board equipment, the Cold Structure is fixed to but thermally uncoupled from the PM 1000 thermal shield. It is protect on its bottom panel by a thermal blanket. As it is a protoflight, analysis was the main tool for the verification. Low level stiffness and modal analysis tests have also been performed on the Cold Structure equipped with its ballast. It allowed to complete its qualification and to prepare SONACA/SABCA support for the system dynamic tests foreseen in 2011. The structure was finally coated with a thermal control black painting and delivered on time to Thales Alenia Space-Italy end of March 201.

  20. Diagnosing battery behavior with an expert system in Prolog

    International Nuclear Information System (INIS)

    Kirkwood, N.; Weeks, D.J.

    1986-01-01

    Power for the Hubble Space Telescope comes from a system of 20 solar panel assemblies (SPAs) and six nickel-cadmium batteries. The HST battery system is simulated by the HST Electrical Power System (EPS) testbed at Marshall Space Flight Center. The Nickel Cadmium Battery Expert System (NICBES) is being used to diagnose faults of the testbed system, evaluate battery status and provide decision support for the engineer. Extensive telemetry of system operating conditions is relayed through a DEC LSI-11, and sent on to an IBM PC-AT. A BASIC program running on the PC monitors the flow of data, figures cell divergence and recharge ratio and stores these values, along with other selected data, for use by the expert system. The expert system is implemented in the logic programming language Prolog. It has three modes of operation: fault diagnosis, status and advice, and decision support. An alert or failure of the system will trigger a diagnosis by the system to assist the operator. The operator can also request battery status information as well as a number of plots and histograms of recent battery behavior. Trends in EOC and EOD voltage, recharge ratio and divergence are used by the expert system in its analysis of battery status. A future enhancement to the system includes the statistical prediction of battery life. Incorporating learning into the expert system is another possible enhancement; This is a difficult task, but one which could promise great rewards in improved battery performance

  1. Deep learning for automated drivetrain fault detection

    DEFF Research Database (Denmark)

    Bach-Andersen, Martin; Rømer-Odgaard, Bo; Winther, Ole

    2018-01-01

    A novel data-driven deep-learning system for large-scale wind turbine drivetrain monitoring applications is presented. It uses convolutional neural network processing on complex vibration signal inputs. The system is demonstrated to learn successfully from the actions of human diagnostic experts...... the fleet-wide diagnostic model performance. The analysis also explores the time dependence of the diagnostic performance, providing a detailed view of the timeliness and accuracy of the diagnostic outputs across the different architectures. Deep architectures are shown to outperform the human analyst...... as well as shallow-learning architectures, and the results demonstrate that when applied in a large-scale monitoring system, machine intelligence is now able to handle some of the most challenging diagnostic tasks related to wind turbines....

  2. Applications of Expert Systems within the Scottish Electricity Supply Industry

    International Nuclear Information System (INIS)

    McWhirter, A.F.

    1990-01-01

    This paper describes the areas of application of Expert Systems within the South of Scotland Electricity Board (SSEB). The SSEB interest in Expert Systems was initiated by a fault in a conventional power station however the paper describes how the development associated with that work, has resulted in applications for the Nuclear Power Stations. The paper contrasts the cost benefits and project risks associated with the uses of probabilistic systems and concludes that the cost benefits of these are at present too low to justify their use in on-line applications

  3. SDG multiple fault diagnosis by real-time inverse inference

    International Nuclear Information System (INIS)

    Zhang Zhaoqian; Wu Chongguang; Zhang Beike; Xia Tao; Li Anfeng

    2005-01-01

    In the past 20 years, one of the qualitative simulation technologies, signed directed graph (SDG) has been widely applied in the field of chemical fault diagnosis. However, the assumption of single fault origin was usually used by many former researchers. As a result, this will lead to the problem of combinatorial explosion and has limited SDG to the realistic application on the real process. This is mainly because that most of the former researchers used forward inference engine in the commercial expert system software to carry out the inverse diagnosis inference on the SDG model which violates the internal principle of diagnosis mechanism. In this paper, we present a new SDG multiple faults diagnosis method by real-time inverse inference. This is a method of multiple faults diagnosis from the genuine significance and the inference engine use inverse mechanism. At last, we give an example of 65t/h furnace diagnosis system to demonstrate its applicability and efficiency

  4. SDG multiple fault diagnosis by real-time inverse inference

    Energy Technology Data Exchange (ETDEWEB)

    Zhang Zhaoqian; Wu Chongguang; Zhang Beike; Xia Tao; Li Anfeng

    2005-02-01

    In the past 20 years, one of the qualitative simulation technologies, signed directed graph (SDG) has been widely applied in the field of chemical fault diagnosis. However, the assumption of single fault origin was usually used by many former researchers. As a result, this will lead to the problem of combinatorial explosion and has limited SDG to the realistic application on the real process. This is mainly because that most of the former researchers used forward inference engine in the commercial expert system software to carry out the inverse diagnosis inference on the SDG model which violates the internal principle of diagnosis mechanism. In this paper, we present a new SDG multiple faults diagnosis method by real-time inverse inference. This is a method of multiple faults diagnosis from the genuine significance and the inference engine use inverse mechanism. At last, we give an example of 65t/h furnace diagnosis system to demonstrate its applicability and efficiency.

  5. Climate Prediction Center: ENSO Diagnostic Discussion

    Science.gov (United States)

    Organization Search Go Search the CPC Go Expert Assessments ENSO Diagnostic Discussion Archive About Us Our Assessments > ENSO Diagnostic Discussion El Niño/Southern Oscillation (ENSO) Diagnostic Discussion PDF : English Version Spanish Version Adobe PDF Reader (Click icon for Adobe PDF Reader) Word: English Version

  6. NuFTA: A CASE Tool for Automatic Software Fault Tree Analysis

    International Nuclear Information System (INIS)

    Yun, Sang Hyun; Lee, Dong Ah; Yoo, Jun Beom

    2010-01-01

    Software fault tree analysis (SFTA) is widely used for analyzing software requiring high-reliability. In SFTA, experts predict failures of system through HA-ZOP (Hazard and Operability study) or FMEA (Failure Mode and Effects Analysis) and draw software fault trees about the failures. Quality and cost of the software fault tree, therefore, depend on knowledge and experience of the experts. This paper proposes a CASE tool NuFTA in order to assist experts of safety analysis. The NuFTA automatically generate software fault trees from NuSCR formal requirements specification. NuSCR is a formal specification language used for specifying software requirements of KNICS RPS (Reactor Protection System) in Korea. We used the SFTA templates proposed by in order to generate SFTA automatically. The NuFTA also generates logical formulae summarizing the failure's cause, and we have a plan to use the formulae usefully through formal verification techniques

  7. Quaternary Fault Lines

    Data.gov (United States)

    Department of Homeland Security — This data set contains locations and information on faults and associated folds in the United States that are believed to be sources of M>6 earthquakes during the...

  8. Expert system for failures detection and non-monotonic reasoning

    International Nuclear Information System (INIS)

    Assis, Abilio de; Schirru, Roberto

    1997-01-01

    This paper presents the development of a shell denominated TIGER that has the purpose to serve as environment to the development of expert systems in diagnosis of faults in industrial complex plants. A model of knowledge representation and an inference engine based on non monotonic reasoning has been developed in order to provide flexibility in the representation of complex plants as well as performance to satisfy restrictions of real time. The TIGER is able to provide both the occurred fault and a hierarchical view of the several reasons that caused the fault to happen. As a validation of the developed shell a monitoring system of the critical safety functions of Angra-1 has been developed. 7 refs., 7 figs., 2 tabs

  9. Fault lubrication during earthquakes.

    Science.gov (United States)

    Di Toro, G; Han, R; Hirose, T; De Paola, N; Nielsen, S; Mizoguchi, K; Ferri, F; Cocco, M; Shimamoto, T

    2011-03-24

    The determination of rock friction at seismic slip rates (about 1 m s(-1)) is of paramount importance in earthquake mechanics, as fault friction controls the stress drop, the mechanical work and the frictional heat generated during slip. Given the difficulty in determining friction by seismological methods, elucidating constraints are derived from experimental studies. Here we review a large set of published and unpublished experiments (∼300) performed in rotary shear apparatus at slip rates of 0.1-2.6 m s(-1). The experiments indicate a significant decrease in friction (of up to one order of magnitude), which we term fault lubrication, both for cohesive (silicate-built, quartz-built and carbonate-built) rocks and non-cohesive rocks (clay-rich, anhydrite, gypsum and dolomite gouges) typical of crustal seismogenic sources. The available mechanical work and the associated temperature rise in the slipping zone trigger a number of physicochemical processes (gelification, decarbonation and dehydration reactions, melting and so on) whose products are responsible for fault lubrication. The similarity between (1) experimental and natural fault products and (2) mechanical work measures resulting from these laboratory experiments and seismological estimates suggests that it is reasonable to extrapolate experimental data to conditions typical of earthquake nucleation depths (7-15 km). It seems that faults are lubricated during earthquakes, irrespective of the fault rock composition and of the specific weakening mechanism involved.

  10. Vipava fault (Slovenia

    Directory of Open Access Journals (Sweden)

    Ladislav Placer

    2008-06-01

    Full Text Available During mapping of the already accomplished Razdrto – Senožeče section of motorway and geologic surveying of construction operations of the trunk road between Razdrto and Vipava in northwestern part of External Dinarides on the southwestern slope of Mt. Nanos, called Rebrnice, a steep NW-SE striking fault was recognized, situated between the Predjama and the Ra{a faults. The fault was named Vipava fault after the Vipava town. An analysis of subrecent gravitational slips at Rebrnice indicates that they were probably associated with the activity of this fault. Unpublished results of a repeated levelling line along the regional road passing across the Vipava fault zone suggest its possible present activity. It would be meaningful to verify this by appropriate geodetic measurements, and to study the actual gravitational slips at Rebrnice. The association between tectonics and gravitational slips in this and in similar extreme cases in the areas of Alps and Dinarides points at the need of complex studying of geologic proceses.

  11. AFTC Code for Automatic Fault Tree Construction: Users Manual

    International Nuclear Information System (INIS)

    Gopika Vinod; Saraf, R.K.; Babar, A.K.

    1999-04-01

    Fault Trees perform a predominant role in reliability and safety analysis of system. Manual construction of fault tree is a very time consuming task and moreover, it won't give a formalized result, since it relies highly on analysts experience and heuristics. This necessitates a computerised fault tree construction, which is still attracting interest of reliability analysts. AFTC software is a user friendly software model for constructing fault trees based on decision tables. Software is equipped with libraries of decision tables for components commonly used in various Nuclear Power Plant (NPP) systems. User is expected to make a nodal diagram of the system, for which fault tree is to be constructed, from the flow sheets available. The text nodal diagram goes as the sole input defining the system flow chart. AFTC software is a rule based expert system which draws the fault tree from the system flow chart and component decision tables. AFTC software gives fault tree in both text and graphic format. Help is provided as how to enter system flow chart and component decision tables. The software is developed in 'C' language. Software is verified with simplified version of the fire water system of an Indian PHWR. Code conversion will be undertaken to create a window based version. (author)

  12. Advanced features of the fault tree solver FTREX

    International Nuclear Information System (INIS)

    Jung, Woo Sik; Han, Sang Hoon; Ha, Jae Joo

    2005-01-01

    This paper presents advanced features of a fault tree solver FTREX (Fault Tree Reliability Evaluation eXpert). Fault tree analysis is one of the most commonly used methods for the safety analysis of industrial systems especially for the probabilistic safety analysis (PSA) of nuclear power plants. Fault trees are solved by the classical Boolean algebra, conventional Binary Decision Diagram (BDD) algorithm, coherent BDD algorithm, and Bayesian networks. FTREX could optionally solve fault trees by the conventional BDD algorithm or the coherent BDD algorithm and could convert the fault trees into the form of the Bayesian networks. The algorithm based on the classical Boolean algebra solves a fault tree and generates MCSs. The conventional BDD algorithm generates a BDD structure of the top event and calculates the exact top event probability. The BDD structure is a factorized form of the prime implicants. The MCSs of the top event could be extracted by reducing the prime implicants in the BDD structure. The coherent BDD algorithm is developed to overcome the shortcomings of the conventional BDD algorithm such as the huge memory requirements and a long run time

  13. 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.

  14. Expert PLSQL Practices

    CERN Document Server

    Beresniewicz, John

    2011-01-01

    Expert PL/SQL Practices is a book of collected wisdom on PL/SQL programming from some of the best and the brightest in the field. Each chapter is a deep-dive into a specific problem, technology, or feature set that you'll face as a PL/SQL programmer. Each author has chosen their topic out of the strong belief that what they share can make a positive difference in the quality and scalability of code that you write. The path to mastery begins with syntax and the mechanics of writing statements to make things happen. If you've reached that point with PL/SQL, then let the authors of Expert PL/SQL

  15. Bioethics for Technical Experts

    Science.gov (United States)

    Asano, Shigetaka

    Along with rapidly expanding applications of life science and technology, technical experts have been implicated more and more often with ethical, social, and legal problems than before. It should be noted that in this background there are scientific and social uncertainty elements which are inevitable during the progress of life science in addition to the historically-established social unreliability to scientists and engineers. In order to solve these problems, therefore, we should establish the social governance with ‘relief’ and ‘reliance’ which enables for both citizens and engineers to share the awareness of the issues, to design social orders and criterions based on hypothetical sense of values for bioethics, to carry out practical use management of each subject carefully, and to improve the sense of values from hypothetical to universal. Concerning these measures, the technical experts can learn many things from the present performance in the medical field.

  16. Expert tool use

    DEFF Research Database (Denmark)

    Thorndahl, Kathrine Liedtke; Ravn, Susanne

    2017-01-01

    on a case study of elite rope skipping, we argue that the phenomenological concept of incorporation does not suffice to adequately describe how expert tool users feel when interacting with their tools. By analyzing a combination of insights gained from participant observation of 11 elite rope skippers......According to some phenomenologists, a tool can be experienced as incorporated when, as a result of habitual use or deliberate practice, someone is able to manipulate it without conscious effort. In this article, we specifically focus on the experience of expertise tool use in elite sport. Based...... and autoethnographic material from one former elite skipper, we take some initial steps toward the development of a more nuanced understanding of the concept of incorporation; one that is able to accommodate the experiences of expert tool users. In sum, our analyses indicate that the possibility for experiencing...

  17. 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 ~ ...

  18. Knowledge acquisition and rapid protyping of an expert system: Dealing with real world problems

    Science.gov (United States)

    Bailey, Patrick A.; Doehr, Brett B.

    1988-01-01

    The knowledge engineering and rapid prototyping phases of an expert system that does fault handling for a Solid Amine, Water Desorbed CO2 removal assembly for the Environmental Control and Life Support System for space based platforms are addressed. The knowledge acquisition phase for this project was interesting because it could not follow the textbook examples. As a result of this, a variety of methods were used during the knowledge acquisition task. The use of rapid prototyping and the need for a flexible prototype suggested certain types of knowledge representation. By combining various techniques, a representative subset of faults and a method for handling those faults was achieved. The experiences should prove useful for developing future fault handling expert systems under similar constraints.

  19. 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

  20. ALICE Expert System

    CERN Document Server

    Ionita, C

    2014-01-01

    The ALICE experiment at CERN employs a number of human operators (shifters), who have to make sure that the experiment is always in a state compatible with taking Physics data. Given the complexity of the system and the myriad of errors that can arise, this is not always a trivial task. The aim of this paper is to describe an expert system that is capable of assisting human shifters in the ALICE control room. The system diagnoses potential issues and attempts to make smart recommendations for troubleshooting. At its core, a Prolog engine infers whether a Physics or a technical run can be started based on the current state of the underlying sub-systems. A separate C++ component queries certain SMI objects and stores their state as facts in a Prolog knowledge base. By mining the data stored in dierent system logs, the expert system can also diagnose errors arising during a run. Currently the system is used by the on-call experts for faster response times, but we expect it to be adopted as a standard tool by reg...

  1. ALICE Expert System

    International Nuclear Information System (INIS)

    Ionita, C; Carena, F

    2014-01-01

    The ALICE experiment at CERN employs a number of human operators (shifters), who have to make sure that the experiment is always in a state compatible with taking Physics data. Given the complexity of the system and the myriad of errors that can arise, this is not always a trivial task. The aim of this paper is to describe an expert system that is capable of assisting human shifters in the ALICE control room. The system diagnoses potential issues and attempts to make smart recommendations for troubleshooting. At its core, a Prolog engine infers whether a Physics or a technical run can be started based on the current state of the underlying sub-systems. A separate C++ component queries certain SMI objects and stores their state as facts in a Prolog knowledge base. By mining the data stored in different system logs, the expert system can also diagnose errors arising during a run. Currently the system is used by the on-call experts for faster response times, but we expect it to be adopted as a standard tool by regular shifters during the next data taking period

  2. HRP2 and pLDH-Based Rapid Diagnostic Tests, Expert Microscopy, and PCR for Detection of Malaria Infection during Pregnancy and at Delivery in Areas of Varied Transmission: A Prospective Cohort Study in Burkina Faso and Uganda.

    Directory of Open Access Journals (Sweden)

    Daniel J Kyabayinze

    Full Text Available Intermittent screening and treatment (IST of malaria during pregnancy has been proposed as an alternative to intermittent preventive treatment in pregnancy (IPTp, where IPTp is failing due to drug resistance. However, the antenatal parasitaemias are frequently very low, and the most appropriate screening test for IST has not been defined.We conducted a multi-center prospective study of 990 HIV-uninfected women attending ANC in two different malaria transmission settings at Tororo District Hospital, eastern Uganda and Colsama Health Center in western Burkina Faso. Women were enrolled in the study in the second or third trimester of pregnancy and followed to delivery, generating 2,597 blood samples for analysis. Screening tests included rapid diagnostic tests (RDTs targeting histidine-rich protein 2 (HRP2 and parasite lactate dehydrogenase (pLDH and microscopy, compared to nPCR as a reference standard. At enrolment, the proportion of pregnant women who were positive for P. falciparum by HRP2/pan pLDH RDT, Pf pLDH/pan pLDH RDT, microscopy and PCR was 38%, 29%, 36% and 44% in Uganda and 21%, 16%, 15% and 35% in Burkina Faso, respectively. All test positivity rates declined during follow-up. In comparison to PCR, the sensitivity of the HRP2/pan pLDH RDT, Pf pLDH/pan pLDH RDT and microscopy was 75.7%, 60.1% and 69.7% in Uganda, 55.8%, 42.6% and 55.8% in Burkina Faso respectively for all antenatal visits. Specificity was greater than 96% for all three tests. Comparison of accuracy using generalized estimating equation revealed that the HRP2- detecting RDT was the most accurate test in both settings.The study suggests that HRP2-based RDTs are the most appropriate point-of-care test currently available for use during pregnancy especially for symptomatic women, but will still miss some PCR-positive women. The clinical significance of these very low density infections needs to be better defined.

  3. Incorporating ''fuzzy'' data and logical relations in the design of expert systems for nuclear reactors

    International Nuclear Information System (INIS)

    Guth, M.A.S.

    1987-01-01

    This paper applies the method of assigning probability in Dempster-Shafer Theory (DST) to the components of rule-based expert systems used in the control of nuclear reactors. Probabilities are assigned to premises, consequences, and rules themselves. This paper considers how uncertainty can propagate through a system of Boolean equations, such as fault trees or expert systems. The probability masses assigned to primary initiating events in the expert system can be derived from observing a nuclear reactor in operation or based on engineering knowledge of the reactor parts. Use of DST mass assignments offers greater flexibility to the construction of expert systems

  4. Pitfalls in diagnostic radiology

    Energy Technology Data Exchange (ETDEWEB)

    Peh, Wilfred C.G. (ed.) [Khoo Teck Puat Hospital (Singapore). Dept. of Diagnostic Radiology

    2015-04-01

    Only textbook to focus primarily on the topic of pitfalls in diagnostic radiology. Highlights the pitfalls in a comprehensive and systematic manner. Written by experts in different imaging modalities and subspecialties from reputable centers across the world. The practice of diagnostic radiology has become increasingly complex, with the use of numerous imaging modalities and division into many subspecialty areas. It is becoming ever more difficult for subspecialist radiologists, general radiologists, and residents to keep up with the advances that are occurring year on year, and this is particularly true for less familiar topics. Failure to appreciate imaging pitfalls often leads to diagnostic error and misinterpretation, and potential medicolegal problems. Diagnostic errors may be due to various factors such as inadequate imaging technique, imaging artifacts, failure to recognize normal structures or variants, lack of correlation with clinical and other imaging findings, and poor training or inexperience. Many, if not most, of these factors are potentially recognizable, preventable, or correctable. This textbook, written by experts from reputable centers across the world, systematically and comprehensively highlights the pitfalls that may occur in diagnostic radiology. Both pitfalls specific to different modalities and techniques and those specific to particular organ systems are described with the help of numerous high-quality illustrations. Recognition of these pitfalls is crucial in helping the practicing radiologist to achieve a more accurate diagnosis.

  5. Pitfalls in diagnostic radiology

    International Nuclear Information System (INIS)

    Peh, Wilfred C.G.

    2015-01-01

    Only textbook to focus primarily on the topic of pitfalls in diagnostic radiology. Highlights the pitfalls in a comprehensive and systematic manner. Written by experts in different imaging modalities and subspecialties from reputable centers across the world. The practice of diagnostic radiology has become increasingly complex, with the use of numerous imaging modalities and division into many subspecialty areas. It is becoming ever more difficult for subspecialist radiologists, general radiologists, and residents to keep up with the advances that are occurring year on year, and this is particularly true for less familiar topics. Failure to appreciate imaging pitfalls often leads to diagnostic error and misinterpretation, and potential medicolegal problems. Diagnostic errors may be due to various factors such as inadequate imaging technique, imaging artifacts, failure to recognize normal structures or variants, lack of correlation with clinical and other imaging findings, and poor training or inexperience. Many, if not most, of these factors are potentially recognizable, preventable, or correctable. This textbook, written by experts from reputable centers across the world, systematically and comprehensively highlights the pitfalls that may occur in diagnostic radiology. Both pitfalls specific to different modalities and techniques and those specific to particular organ systems are described with the help of numerous high-quality illustrations. Recognition of these pitfalls is crucial in helping the practicing radiologist to achieve a more accurate diagnosis.

  6. Beam Instrumentation and Diagnostics

    CERN Document Server

    Strehl, Peter

    2006-01-01

    This treatise covers all aspects of the design and the daily operations of a beam diagnostic system for a large particle accelerator. A very interdisciplinary field, it involves contributions from physicists, electrical and mechanical engineers and computer experts alike so as to satisfy the ever-increasing demands for beam parameter variability for a vast range of operation modi and particles. The author draws upon 40 years of research and work, most of them spent as the head of the beam diagnostics group at GSI. He has illustrated the more theoretical aspects with many real-life examples that will provide beam instrumentation designers with ideas and tools for their work.

  7. PRODIAG -- Dynamic qualitative analysis for process fault diagnosis

    International Nuclear Information System (INIS)

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

    1995-01-01

    The authors present a method for handling the dynamic effects of process component malfunctions through time-independent rule-based diagnostic systems. The method's theory is discussed and a simplified version is implemented in the process diagnostic expert system PRODIAG. Simulation results from a full-scope operator training simulator of a nuclear power plant are used to illustrate the method

  8. Team building and diagnostic training

    International Nuclear Information System (INIS)

    Bulmer, S.

    1987-01-01

    While developing a commercial training program to improve teamwork in control room crews, General Electric's Nuclear Training Services made an important discovery. Traditional training methods for developing teamwork and enhancing diagnostics capabilities are incomplete. Traditional methods generally help, but fail to fulfill the long-term needs of most teams. Teamwork has been treated as a short-term performance problem. Traditional diagnostic training suffers from a similar problem. Too often, it covers only the basic principles of decision-making, ignoring the development of expert diagnostic capabilities. In response to this discovery, they have developed comprehensive training in Team Building and Diagnostics

  9. 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

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

    DEFF Research Database (Denmark)

    Hansen, Søren; Blanke, Mogens; Adrian, Jens

    2014-01-01

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

  11. 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.

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

    DEFF Research Database (Denmark)

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

    2009-01-01

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

  13. Expert systems and optimisation in process control

    International Nuclear Information System (INIS)

    Mamdani, A.; Efstathiou, J.

    1986-01-01

    This report brings together recent developments both in expert systems and in optimisation, and deals with current applications in industry. Part One is concerned with Artificial Intellegence in planning and scheduling and with rule-based control implementation. The tasks of control maintenance, rescheduling and planning are each discussed in relation to new theoretical developments, techniques available, and sample applications. Part Two covers model based control techniques in which the control decisions are used in a computer model of the process. Fault diagnosis, maintenance and trouble-shooting are just some of the activities covered. Part Three contains case studies of projects currently in progress, giving details of the software available and the likely future trends. One of these, on qualitative plant modelling as a basis for knowledge-based operator aids in nuclear power stations is indexed separately. (author)

  14. An expert system for sensor data validation and malfunction detection

    International Nuclear Information System (INIS)

    Hashemi, S.; Hajek, B.K.; Miller, D.W.

    1987-01-01

    Nuclear power plant operation and monitoring in general is a complex task which requires a large number of sensors, alarms and displays. At any instant in time, the operator is required to make a judgment about the state of the plant and to react accordingly. During abnormal situations, operators are further burdened with time constraints. The possibility of an undetected faulty instrumentation line, adds to the complexity of operators' reasoning tasks. Recent work at The Ohio State University Laboratory of Artificial Intelligence Research (LAIR) and the nuclear engineering program has concentrated on the problem of diagnostic expert systems performance and their applicability to the nuclear power plant domain. The authors have also been concerned about the diagnostic expert systems performance when using potentially invalid sensor data. Because of this research, they have developed an expert system that can perform diagnostic problem solving despite the existence of some conflicting data in the domain. This work has resulted in enhancement of a programming tool, CSRL, that allows domain experts to create a diagnostic system that will be to some degree, tolerant of bad data while performing diagnosis. This expert system is described here

  15. 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...

  16. Imaging spectroscopy: Earth and planetary remote sensing with the USGS Tetracorder and expert systems

    Science.gov (United States)

    Clark, Roger N.; Swayze, Gregg A.; Livo, K. Eric; Kokaly, Raymond F.; Sutley, Steve J.; Dalton, J. Brad; McDougal, Robert R.; Gent, Carol A.

    2003-01-01

    Imaging spectroscopy is a tool that can be used to spectrally identify and spatially map materials based on their specific chemical bonds. Spectroscopic analysis requires significantly more sophistication than has been employed in conventional broadband remote sensing analysis. We describe a new system that is effective at material identification and mapping: a set of algorithms within an expert system decision‐making framework that we call Tetracorder. The expertise in the system has been derived from scientific knowledge of spectral identification. The expert system rules are implemented in a decision tree where multiple algorithms are applied to spectral analysis, additional expert rules and algorithms can be applied based on initial results, and more decisions are made until spectral analysis is complete. Because certain spectral features are indicative of specific chemical bonds in materials, the system can accurately identify and map those materials. In this paper we describe the framework of the decision making process used for spectral identification, describe specific spectral feature analysis algorithms, and give examples of what analyses and types of maps are possible with imaging spectroscopy data. We also present the expert system rules that describe which diagnostic spectral features are used in the decision making process for a set of spectra of minerals and other common materials. We demonstrate the applications of Tetracorder to identify and map surface minerals, to detect sources of acid rock drainage, and to map vegetation species, ice, melting snow, water, and water pollution, all with one set of expert system rules. Mineral mapping can aid in geologic mapping and fault detection and can provide a better understanding of weathering, mineralization, hydrothermal alteration, and other geologic processes. Environmental site assessment, such as mapping source areas of acid mine drainage, has resulted in the acceleration of site cleanup, saving

  17. Process plant alarm diagnosis using synthesised fault tree knowledge

    International Nuclear Information System (INIS)

    Trenchard, A.J.

    1990-01-01

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

  18. Fault Detection for Industrial Processes

    Directory of Open Access Journals (Sweden)

    Yingwei Zhang

    2012-01-01

    Full Text Available A new fault-relevant KPCA algorithm is proposed. Then the fault detection approach is proposed based on the fault-relevant KPCA algorithm. The proposed method further decomposes both the KPCA principal space and residual space into two subspaces. Compared with traditional statistical techniques, the fault subspace is separated based on the fault-relevant influence. This method can find fault-relevant principal directions and principal components of systematic subspace and residual subspace for process monitoring. The proposed monitoring approach is applied to Tennessee Eastman process and penicillin fermentation process. The simulation results show the effectiveness of the proposed method.

  19. Use of expert systems in nuclear power plants

    International Nuclear Information System (INIS)

    Uhrig, R.E.

    1989-01-01

    The application of technologies, particularly expert systems, to the control room activities in a nuclear power plant has the potential to reduce operator error and increase plant safety, reliability, and efficiency. Furthermore, there are a large number of nonoperating activities (testing, routine maintenance, outage planning, equipment diagnostics, and fuel management) in which expert systems can increase the efficiency and effectiveness of overall plant and corporate operations. This document presents a number of potential applications of expert systems in the nuclear power field. 36 refs., 2 tabs

  20. Expert Oracle Exadata

    CERN Document Server

    Johnson, Randy

    2011-01-01

    Throughout history, advances in technology have come in spurts. A single great idea can often spur rapid change as the idea takes hold and is propagated, often in totally unexpected directions. Exadata embodies such a change in how we think about and manage relational databases. The key change lies in the concept of offloading SQL processing to the storage layer. That concept is a huge win, and its implementation in the form of Exadata is truly a game changer. Expert Oracle Exadata will give you a look under the covers at how the combination of hardware and software that comprise Exadata actua

  1. The naked experts

    International Nuclear Information System (INIS)

    Martin, B.

    1982-01-01

    In an article critical of experts, the cases argued for and against nuclear power are discussed under the headings: environmental hazards arising from the nuclear fuel cycle; proliferation of nuclear weapons capabilities via expansion of the nuclear power industry; political and social threats and restraints of a nuclear society (terrorism, reduction in civil liberties, centralised political and economic power); economic and employment disadvantages of nuclear power; impact of uranium mining on (Australian) aboriginal culture; inadequacy of nuclear power as a solution to energy problems; advantages of a 'soft energy path' based around conservation and renewable energy technologies. (U.K.)

  2. Employing expert systems for process control

    International Nuclear Information System (INIS)

    Ahrens, W.

    1987-01-01

    The characteristic features of expert systems are explained in detail, and the systems' application in process control engineering. Four points of main interest are there, namely: Applications for diagnostic tasks, for safety analyses, planning, and training and expert training. For the modelling of the technical systems involved in all four task fields mentioned above, an object-centred approach has shown to be the suitable method, as process control techniques are determined by technical objects that in principle are specified by data sheets, schematic representations, flow charts, and plans. The graphical surface allows these data to be taken into account, so that the object can be displayed in the way best suited to the individual purposes. (orig./GL) [de

  3. Fault tree analysis

    International Nuclear Information System (INIS)

    1981-09-01

    Suggestion are made concerning the method of the fault tree analysis, the use of certain symbols in the examination of system failures. This purpose of the fault free analysis is to find logical connections of component or subsystem failures leading to undesirable occurrances. The results of these examinations are part of the system assessment concerning operation and safety. The objectives of the analysis are: systematical identification of all possible failure combinations (causes) leading to a specific undesirable occurrance, finding of reliability parameters such as frequency of failure combinations, frequency of the undesirable occurrance or non-availability of the system when required. The fault tree analysis provides a near and reconstructable documentation of the examination. (orig./HP) [de

  4. 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...

  5. 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....

  6. 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.

  7. [Deontology of the medical expert].

    Science.gov (United States)

    Raszeja, S

    1995-09-01

    The authority of prosecuting organ to choose the expert, set his task and verify the following opinion is defined. The qualities of the medical expert and his duties are described, referring to: -his expertise; -his morality; -his ability to issue an independent (objective) opinion. Detailed rules, which can be ascribed to a specific medical expert's deontological code, are listed and explained.

  8. Computer hardware fault administration

    Science.gov (United States)

    Archer, Charles J.; Megerian, Mark G.; Ratterman, Joseph D.; Smith, Brian E.

    2010-09-14

    Computer hardware fault administration carried out in a parallel computer, where the parallel computer includes a plurality of compute nodes. The compute nodes are coupled for data communications by at least two independent data communications networks, where each data communications network includes data communications links connected to the compute nodes. Typical embodiments carry out hardware fault administration by identifying a location of a defective link in the first data communications network of the parallel computer and routing communications data around the defective link through the second data communications network of the parallel computer.

  9. Fault Tolerant Computer Architecture

    CERN Document Server

    Sorin, Daniel

    2009-01-01

    For many years, most computer architects have pursued one primary goal: performance. Architects have translated the ever-increasing abundance of ever-faster transistors provided by Moore's law into remarkable increases in performance. Recently, however, the bounty provided by Moore's law has been accompanied by several challenges that have arisen as devices have become smaller, including a decrease in dependability due to physical faults. In this book, we focus on the dependability challenge and the fault tolerance solutions that architects are developing to overcome it. The two main purposes

  10. Fault tolerant linear actuator

    Science.gov (United States)

    Tesar, Delbert

    2004-09-14

    In varying embodiments, the fault tolerant linear actuator of the present invention is a new and improved linear actuator with fault tolerance and positional control that may incorporate velocity summing, force summing, or a combination of the two. In one embodiment, the invention offers a velocity summing arrangement with a differential gear between two prime movers driving a cage, which then drives a linear spindle screw transmission. Other embodiments feature two prime movers driving separate linear spindle screw transmissions, one internal and one external, in a totally concentric and compact integrated module.

  11. Hybrid expert system

    International Nuclear Information System (INIS)

    Tsoukalas, L.; Ikonomopoulos, A.; Uhrig, R.E.

    1991-01-01

    This paper presents a methodology that couples rule-based expert systems using fuzzy logic, to pre-trained artificial neutral networks (ANN) for the purpose of transient identification in Nuclear Power Plants (NPP). In order to provide timely concise, and task-specific information about the may aspects of the transient and to determine the state of the system based on the interpretation of potentially noisy data a model-referenced approach is utilized. In it, the expert system performs the basic interpretation and processing of the model data, and pre-trained ANNs provide the model. having access to a set of neural networks that typify general categories of transients, the rule based system is able to perform identification functions. Membership functions - condensing information about a transient in a form convenient for a rule-based identification system characterizing a transient - are the output of neural computations. This allows the identification function to be performed with a speed comparable to or faster than that of the temporal evolution of the system. Simulator data form major secondary system pipe rupture is used to demonstrate the methodology. The results indicate excellent noise-tolerance for ANN's and suggest a new method for transient identification within the framework of Fuzzy Logic

  12. Wind turbine fault detection and fault tolerant control

    DEFF Research Database (Denmark)

    Odgaard, Peter Fogh; Johnson, Kathryn

    2013-01-01

    In this updated edition of a previous wind turbine fault detection and fault tolerant control challenge, we present a more sophisticated wind turbine model and updated fault scenarios to enhance the realism of the challenge and therefore the value of the solutions. This paper describes...

  13. 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...

  14. ESR dating of fault rocks

    International Nuclear Information System (INIS)

    Lee, Hee Kwon

    2002-03-01

    Past movement on faults can be dated by measurement of the intensity of ESR signals in quartz. These signals are reset by local lattice deformation and local frictional heating on grain contacts at the time of fault movement. The ESR signals then trow back as a result of bombardment by ionizing radiation from surrounding rocks. The age is obtained from the ratio of the equivalent dose, needed to produce the observed signal, to the dose rate. Fine grains are more completely reset during faulting, and a plot of age vs grain size shows a plateau for grains below critical size : these grains are presumed to have been completely zeroed by the last fault activity. We carried out ESR dating of fault rocks collected from the Yangsan fault system. ESR dates from the this fault system range from 870 to 240 ka. Results of this research suggest that long-term cyclic fault activity continued into the pleistocene

  15. Fault diagnosis of induction motors

    CERN Document Server

    Faiz, Jawad; Joksimović, Gojko

    2017-01-01

    This book is a comprehensive, structural approach to fault diagnosis strategy. The different fault types, signal processing techniques, and loss characterisation are addressed in the book. This is essential reading for work with induction motors for transportation and energy.

  16. ESR dating of fault rocks

    Energy Technology Data Exchange (ETDEWEB)

    Lee, Hee Kwon [Kangwon National Univ., Chuncheon (Korea, Republic of)

    2002-03-15

    Past movement on faults can be dated by measurement of the intensity of ESR signals in quartz. These signals are reset by local lattice deformation and local frictional heating on grain contacts at the time of fault movement. The ESR signals then trow back as a result of bombardment by ionizing radiation from surrounding rocks. The age is obtained from the ratio of the equivalent dose, needed to produce the observed signal, to the dose rate. Fine grains are more completely reset during faulting, and a plot of age vs grain size shows a plateau for grains below critical size : these grains are presumed to have been completely zeroed by the last fault activity. We carried out ESR dating of fault rocks collected from the Yangsan fault system. ESR dates from the this fault system range from 870 to 240 ka. Results of this research suggest that long-term cyclic fault activity continued into the pleistocene.

  17. Knowledge based diagnostics in nuclear power plants

    International Nuclear Information System (INIS)

    Baldeweg, F.; Fiedler, U.; Weiss, F.P.; Werner, M.

    1987-01-01

    In this paper a special process diagnostic system (PDS) is presented. It must be seen as the result of a long term work on computerized process surveillance and control; it includes a model based system for noise analysis of mechanical vibrations, which has recently been enhanced by using of knowledge based technique (expert systems). The paper discusses the process diagnostic frame concept and emphasize the vibration analysis expert system

  18. Introduction to fault tree analysis

    International Nuclear Information System (INIS)

    Barlow, R.E.; Lambert, H.E.

    1975-01-01

    An elementary, engineering oriented introduction to fault tree analysis is presented. The basic concepts, techniques and applications of fault tree analysis, FTA, are described. The two major steps of FTA are identified as (1) the construction of the fault tree and (2) its evaluation. The evaluation of the fault tree can be qualitative or quantitative depending upon the scope, extensiveness and use of the analysis. The advantages, limitations and usefulness of FTA are discussed

  19. Fault Tolerant Wind Farm Control

    DEFF Research Database (Denmark)

    Odgaard, Peter Fogh; Stoustrup, Jakob

    2013-01-01

    In the recent years the wind turbine industry has focused on optimizing the cost of energy. One of the important factors in this is to increase reliability of the wind turbines. Advanced fault detection, isolation and accommodation are important tools in this process. Clearly most faults are deal...... scenarios. This benchmark model is used in an international competition dealing with Wind Farm fault detection and isolation and fault tolerant control....

  20. Demonstration of artificial intelligence technology for transit railcar diagnostics

    Science.gov (United States)

    1999-01-01

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

  1. 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...

  2. Row fault detection system

    Science.gov (United States)

    Archer, Charles Jens [Rochester, MN; Pinnow, Kurt Walter [Rochester, MN; Ratterman, Joseph D [Rochester, MN; Smith, Brian Edward [Rochester, MN

    2008-10-14

    An apparatus, program product and method checks for nodal faults in a row of nodes by causing each node in the row to concurrently communicate with its adjacent neighbor nodes in the row. The communications are analyzed to determine a presence of a faulty node or connection.

  3. Fault isolation techniques

    Science.gov (United States)

    Dumas, A.

    1981-01-01

    Three major areas that are considered in the development of an overall maintenance scheme of computer equipment are described. The areas of concern related to fault isolation techniques are: the programmer (or user), company and its policies, and the manufacturer of the equipment.

  4. 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...

  5. Fault-Related Sanctuaries

    Science.gov (United States)

    Piccardi, L.

    2001-12-01

    Beyond the study of historical surface faulting events, this work investigates the possibility, in specific cases, of identifying pre-historical events whose memory survives in myths and legends. The myths of many famous sacred places of the ancient world contain relevant telluric references: "sacred" earthquakes, openings to the Underworld and/or chthonic dragons. Given the strong correspondence with local geological evidence, these myths may be considered as describing natural phenomena. It has been possible in this way to shed light on the geologic origin of famous myths (Piccardi, 1999, 2000 and 2001). Interdisciplinary researches reveal that the origin of several ancient sanctuaries may be linked in particular to peculiar geological phenomena observed on local active faults (like ground shaking and coseismic surface ruptures, gas and flames emissions, strong underground rumours). In many of these sanctuaries the sacred area is laid directly above the active fault. In a few cases, faulting has affected also the archaeological relics, right through the main temple (e.g. Delphi, Cnidus, Hierapolis of Phrygia). As such, the arrangement of the cult site and content of relative myths suggest that specific points along the trace of active faults have been noticed in the past and worshiped as special `sacred' places, most likely interpreted as Hades' Doors. The mythological stratification of most of these sanctuaries dates back to prehistory, and points to a common derivation from the cult of the Mother Goddess (the Lady of the Doors), which was largely widespread since at least 25000 BC. The cult itself was later reconverted into various different divinities, while the `sacred doors' of the Great Goddess and/or the dragons (offspring of Mother Earth and generally regarded as Keepers of the Doors) persisted in more recent mythologies. Piccardi L., 1999: The "Footprints" of the Archangel: Evidence of Early-Medieval Surface Faulting at Monte Sant'Angelo (Gargano, Italy

  6. Der Patient als Experte.

    Science.gov (United States)

    Dubs

    1998-01-01

    Patients as Experts: Determining Benefit by Using Assessments of Ability (ICIDH)When health economy and quality mangement are dealing with the cost-benefit relationship, to this day description, calculation, and assessment of the benefit are missing to a great extent. Deliberations in terms of cause and effect do not go beyond the model of pathogenesis (etiology - pathology - manifestation) and descriptions on the organ level (ICD). Only the international classification of impairments, disabilities, and handicaps (ICIDH) as a separate estimation of the resulting manifestations of illness on the levels of organ, individual, and society is capable to elucidate this benefit. It is the patient who is the expert to decide what he needs, what he wants, and what he can do, thus, evaluating on an individual level his loss of capability. The ICIDH is regarded as the key for the management of chronic diseases. The characteristics of being chronically ill require the integration of salutogenesis and the consideration of the hierarchy of needs. The specially developed MARA model serves as pragmatic basis for the description of the benefits of carried out and omitted interventions as changes of abilities by using the MARA curve (mean age-related ability) as ethical guideline. In quality circles the MARA model, which is based on ICIDH, hierarchy of needs and salutogenesis, can offer apatient-oriented basis of discussion for benefit assessments, and, in a pragmatical way, it can facilitate the introduction of evidence-based medicine. By the change of view from the organ level with multifactorial aspects to the individual level, in which the abilities can be understood as a monofactor, a high consensus potential between several participants of discussion in health service is possible.

  7. LAMPF first-fault identifier for fast transient faults

    International Nuclear Information System (INIS)

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

    1979-01-01

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

  8. Considerations in development of expert systems for real-time space applications

    Science.gov (United States)

    Murugesan, S.

    1988-01-01

    Over the years, demand on space systems has increased tremendously and this trend will continue for the near future. Enhanced capabilities of space systems, however, can only be met with increased complexity and sophistication of onboard and ground systems. Artificial Intelligence and expert system techniques have great potential in space applications. Expert systems could facilitate autonomous decision making, improve in-orbit fault diagnosis and repair, enhance performance and reduce reliance on ground support. However, real-time expert systems, unlike conventional off-line consultative systems, have to satisfy certain special stringent requirements before they could be used for onboard space applications. Challenging and interesting new environments are faced while developing expert system space applications. This paper discusses the special characteristics, requirements and typical life cycle issues for onboard expert systems. Further, it also describes considerations in design, development, and implementation which are particularly important to real-time expert systems for space applications.

  9. 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

  10. Hilar cholangiocarcinoma: expert consensus statement.

    Science.gov (United States)

    Mansour, John C; Aloia, Thomas A; Crane, Christopher H; Heimbach, Julie K; Nagino, Masato; Vauthey, Jean-Nicolas

    2015-08-01

    An American Hepato-Pancreato-Biliary Association (AHPBA)-sponsored consensus meeting of expert panellists met on 15 January 2014 to review current evidence on the management of hilar cholangiocarcinoma in order to establish practice guidelines and to agree consensus statements. It was established that the treatment of patients with hilar cholangiocarcinoma requires a coordinated, multidisciplinary approach to optimize the chances for both durable survival and effective palliation. An adequate diagnostic and staging work-up includes high-quality cross-sectional imaging; however, pathologic confirmation is not required prior to resection or initiation of a liver transplant trimodal treatment protocol. The ideal treatment for suitable patients with resectable hilar malignancy is resection of the intra- and extrahepatic bile ducts, as well as resection of the involved ipsilateral liver. Preoperative biliary drainage is best achieved with percutaneous transhepatic approaches and may be indicated for patients with cholangitis, malnutrition or hepatic insufficiency. Portal vein embolization is a safe and effective strategy for increasing the future liver remnant (FLR) and is particularly useful for patients with an FLR of hilar cholangiocarcinoma should be evaluated for a standard trimodal protocol incorporating external beam and endoluminal radiation therapy, systemic chemotherapy and liver transplantation. Post-resection chemoradiation should be offered to patients who show high-risk features on surgical pathology. Chemoradiation is also recommended for patients with locally advanced, unresectable hilar cancers. For patients with locally recurrent or metastatic hilar cholangiocarcinoma, first-line chemotherapy with gemcitabine and cisplatin is recommended based on multiple Phase II trials and a large randomized controlled trial including a heterogeneous population of patients with biliary cancers. © 2015 International Hepato-Pancreato-Biliary Association.

  11. 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)

  12. Fault rocks and uranium mineralization

    International Nuclear Information System (INIS)

    Tong Hangshou.

    1991-01-01

    The types of fault rocks, microstructural characteristics of fault tectonite and their relationship with uranium mineralization in the uranium-productive granite area are discussed. According to the synthetic analysis on nature of stress, extent of crack and microstructural characteristics of fault rocks, they can be classified into five groups and sixteen subgroups. The author especially emphasizes the control of cataclasite group and fault breccia group over uranium mineralization in the uranium-productive granite area. It is considered that more effective study should be made on the macrostructure and microstructure of fault rocks. It is of an important practical significance in uranium exploration

  13. Network Fault Diagnosis Using DSM

    Institute of Scientific and Technical Information of China (English)

    Jiang Hao; Yan Pu-liu; Chen Xiao; Wu Jing

    2004-01-01

    Difference similitude matrix (DSM) is effective in reducing information system with its higher reduction rate and higher validity. We use DSM method to analyze the fault data of computer networks and obtain the fault diagnosis rules. Through discretizing the relative value of fault data, we get the information system of the fault data. DSM method reduces the information system and gets the diagnosis rules. The simulation with the actual scenario shows that the fault diagnosis based on DSM can obtain few and effective rules.

  14. Development of a diagnostic expert system for secondary water chemistry

    International Nuclear Information System (INIS)

    Suganuma, S.; Ishikawa, S.; Kato, A.; Yamauchi, S.; Hattori, T.; Yoshikawa, T.; Miyamoto, S.

    1990-01-01

    Water chemistry control for the secondary side of the PWR plants is one of the most important tasks for maintaining the reliability of plant equipment and for extending the operating life of the plant. Water chemistry control should be maintained according to the plant chemist' considered judgement which is based on continual experienced observation. Mitsubishi Heavy Industries (MHI) has been developing a comprehensive data management and diagnosis system, which continuously observes the secondary water chemistry data with on-line monitors, immediately diagnosing causes whenever any symptoms of abnormality are detected and does the necessary data management, in order to support plant staff to controll water chemistry. This system has the following three basic functions: data management, diagnosis and simulation. This paper presents the outline of the total system, and then describes in detail the procedure of diagnosis, the structure of the knowledge and its validation process

  15. Using Expert Systems in Evaluation of the State of High Voltage Machine Insulation Systems

    Directory of Open Access Journals (Sweden)

    K. Záliš

    2000-01-01

    Full Text Available Expert systems are used for evaluating the actual state and future behavior of insulating systems of high voltage electrical machines and equipment. Several rule-based expert systems have been developed in cooperation with top diagnostic workplaces in the Czech Republic for this purpose. The IZOLEX expert system evaluates diagnostic measurement data from commonly used offline diagnostic methods for the diagnostic of high voltage insulation of rotating machines, non-rotating machines and insulating oils. The CVEX expert system evaluates the discharge activity on high voltage electrical machines and equipment by means of an off-line measurement. The CVEXON expert system is for evaluating the discharge activity by on-line measurement, and the ALTONEX expert system is the expert system for on-line monitoring of rotating machines. These developed expert systems are also used for educating students (in bachelor, master and post-graduate studies and in courses which are organized for practicing engineers and technicians and for specialists in the electrical power engineering branch. A complex project has recently been set up to evaluate the measurement of partial discharges. Two parallel expert systems for evaluating partial dischatge activity on high voltage electrical machines will work at the same time in this complex evaluating system.

  16. 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.

  17. Expert system in PNC, 5

    International Nuclear Information System (INIS)

    Tobita, Yoshimasa; Yamaguchi, Takashi; Matsumoto, Mitsuo; Ono, Kiyoshi.

    1990-01-01

    The computer code system which can evaluate the mass balance and cycle cost in nuclear fuel cycle has been developing a PNC using an artificial intelligence technique. This system is composed of the expert system, data base and analysis codes. The expert system is the most important one in the system and the content of the expert system is explained in this paper. The expert system has the three functions. The first is the function of understanding the meaning of user's questions by natural language, the second is the function of selecting the best way to solve the problem given by the user using the knowledge which is already installed in the system, and the last is the function of answering the questions. The knowledge of the experts installed in the expert system is represented by the frame-type rules. Therefore, the knowledge will be simply added to the system, and consequently the system will be easily extended. (author)

  18. Fault capability problem about seams in Shika NPP

    International Nuclear Information System (INIS)

    Katagawa, H.

    2016-01-01

    Against the opinion of the Nuclear Regulation Authority that insists that the on-site seams of Shika Nuclear Power Plant is fault, Hokuriku Electric Power Company shows the view that they are not the fault. Additional survey result was submitted by Hokuriku Electric Power Company, and the evaluation draft for it by the expert meeting of Nuclear Regulation Authority, as well as the peer review were published. The evaluation draft mentioned that the seams cannot be denied for the possibility to become active, and the peer review issued many evaluations different from the evaluation draft. This paper describes the contents of the evaluation draft and peer review summarized by Hokuriku Electric Power Company. Against the three major points of the evaluation draft, the peer review pointed out the defect of fact recognition in every issue of discussion that lacks in examination on the points that should have been checked, and questioned the eligibility of the contents of evaluation. Many of the suggestions and comments of the peer review were the contents that approved the on-site survey and the report at the expert meeting made by Hokuriku Electric Power Company. In addition, this paper summarizes the focal points of the evaluation draft, and points out the question for fault assumption and discrepancies in the case of existence of fault. Hokuriku Electric Power Company has published a rebuttal to the evaluation draft as the written opinion. (A.O.)

  19. A Diagnostic and Predictive Framework for Wind Turbine Drive Train Monitoring

    DEFF Research Database (Denmark)

    Bach-Andersen, Martin

    Vast amount of data are collected minute by minute from wind turbines around the world. This thesis represents a focused research effort into discovering new ways of processing these data streams in order to gain insights which can be used to lower the maintenance costs of wind turbines and increase......, early fault identification based on analysis of complex vibration patterns which is a domain previously reserved for human experts, is shown to be solved with high accuracy using deep learning architecture strained in a fully supervised sense from the data collected in a large scale wind turbine...... monitoring platform. The research shows a way towards a fully automatized data-driven wind turbine diagnostic processing system that is highly scalable and requires little or no feature engineering and system modeling....

  20. The First Expert CAI System

    Science.gov (United States)

    Feurzeig, Wallace

    1984-01-01

    The first expert instructional system, the Socratic System, was developed in 1964. One of the earliest applications of this system was in the area of differential diagnosis in clinical medicine. The power of the underlying instructional paradigm was demonstrated and the potential of the approach for valuably supplementing medical instruction was recognized. Twenty years later, despite further educationally significant advances in expert systems technology and enormous reductions in the cost of computers, expert instructional methods have found very little application in medical schools.

  1. 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.

  2. Surgical experts: born or made?

    Science.gov (United States)

    Sadideen, Hazim; Alvand, Abtin; Saadeddin, Munir; Kneebone, Roger

    2013-01-01

    The concept of surgical expertise and the processes involved in its development are topical, and there is a constant drive to identify reliable measures of expert performance in surgery. This review explores the notion of whether surgical experts are "born" or "made", with reference to educational theory and pertinent literature. Peer-reviewed publications, books, and online resources on surgical education, expertise and training were reviewed. Important themes and aspects of expertise acquisition were identified in order to better understand the concept of a surgical expert. The definition of surgical expertise and several important aspects of its development are highlighted. Innate talent plays an important role, but is insufficient on its own to produce a surgical expert. Multiple theories that explore motor skill acquisition and memory are relevant, and Ericsson's theory of the development of competence followed by deliberate self-practice has been especially influential. Psychomotor and non-technical skills are necessary for progression in the current climate in light of our training curricula; surgical experts are adaptive experts who excel in these. The literature suggests that surgical expertise is reached through practice; surgical experts are made, not born. A deeper understanding of the nature of expert performance and its development will ensure that surgical education training programmes are of the highest possible quality. Surgical educators should aim to develop an expertise-based approach, with expert performance as the benchmark. Copyright © 2013 Surgical Associates Ltd. Published by Elsevier Ltd. All rights reserved.

  3. Expert Systems for the Analytical Laboratory.

    Science.gov (United States)

    de Monchy, Allan R.; And Others

    1988-01-01

    Discusses two computer problem solving programs: rule-based expert systems and decision analysis expert systems. Explores the application of expert systems to automated chemical analyses. Presents six factors to consider before using expert systems. (MVL)

  4. Expert Systems as Tools for Technical Communicators.

    Science.gov (United States)

    Grider, Daryl A.

    1994-01-01

    Discusses expertise, what an expert system is, what an expert system shell is, what expert systems can and cannot do, knowledge engineering and technical communicators, and planning and managing expert system projects. (SR)

  5. Mapping on complex neutrosophic soft expert sets

    Science.gov (United States)

    Al-Quran, Ashraf; Hassan, Nasruddin

    2018-04-01

    We introduce the mapping on complex neutrosophic soft expert sets. Further, we investigated the basic operations and other related properties of complex neutrosophic soft expert image and complex neutrosophic soft expert inverse image of complex neutrosophic soft expert sets.

  6. System Experts and Decision Making Experts in Transdisciplinary Projects

    Science.gov (United States)

    Mieg, Harald A.

    2006-01-01

    Purpose: This paper aims at a better understanding of expert roles in transdisciplinary projects. Thus, the main purpose is the analysis of the roles of experts in transdisciplinary projects. Design/methodology/approach: The analysis of the ETH-UNS case studies from the point of view of the psychology of expertise and the sociology of professions…

  7. Online-Expert: An Expert System for Online Database Selection.

    Science.gov (United States)

    Zahir, Sajjad; Chang, Chew Lik

    1992-01-01

    Describes the design and development of a prototype expert system called ONLINE-EXPERT that helps users select online databases and vendors that meet users' needs. Search strategies are discussed; knowledge acquisition and knowledge bases are described; and the Analytic Hierarchy Process (AHP), a decision analysis technique that ranks databases,…

  8. Faults in Linux

    DEFF Research Database (Denmark)

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

    2011-01-01

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

  9. 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.

  10. Plutonium - the ultrapoison? An expert's opinion about an expert opinion

    International Nuclear Information System (INIS)

    Stoll, W.; Becker, K.

    1989-01-01

    In an expert opinion written by Professor H. Kuni, Marburg, for the North Rhine-Westphalian state government, plutonium is called by far the most dangerous element in the Periodic Table. The Marburg medical expert holds that even improved legal instruments are unable to warrant effective protection of the workers handling this material, in the light of the present standards of industrial safety, because of radiological conditions and measuring problems with plutonium isotopes. In this article by an internationally renowned expert in the field, the ideas expressed in the expert opinion about the toxicity of plutonium, the cause-and-effect relationship in radiation damage by plutonium, and recent findings about the toxicity are subjected to a critical review. On the basis of results of radiation protection and of case studies, the statements in the expert opinion are contrasted with facts which make them appear in a very different light. (orig./RB) [de

  11. The Sorong Fault Zone, Indonesia: Mapping a Fault Zone Offshore

    Science.gov (United States)

    Melia, S.; Hall, R.

    2017-12-01

    The Sorong Fault Zone is a left-lateral strike-slip fault zone in eastern Indonesia, extending westwards from the Bird's Head peninsula of West Papua towards Sulawesi. It is the result of interactions between the Pacific, Caroline, Philippine Sea, and Australian Plates and much of it is offshore. Previous research on the fault zone has been limited by the low resolution of available data offshore, leading to debates over the extent, location, and timing of movements, and the tectonic evolution of eastern Indonesia. Different studies have shown it north of the Sula Islands, truncated south of Halmahera, continuing to Sulawesi, or splaying into a horsetail fan of smaller faults. Recently acquired high resolution multibeam bathymetry of the seafloor (with a resolution of 15-25 meters), and 2D seismic lines, provide the opportunity to trace the fault offshore. The position of different strands can be identified. On land, SRTM topography shows that in the northern Bird's Head the fault zone is characterised by closely spaced E-W trending faults. NW of the Bird's Head offshore there is a fold and thrust belt which terminates some strands. To the west of the Bird's Head offshore the fault zone diverges into multiple strands trending ENE-WSW. Regions of Riedel shearing are evident west of the Bird's Head, indicating sinistral strike-slip motion. Further west, the ENE-WSW trending faults turn to an E-W trend and there are at least three fault zones situated immediately south of Halmahera, north of the Sula Islands, and between the islands of Sanana and Mangole where the fault system terminates in horsetail strands. South of the Sula islands some former normal faults at the continent-ocean boundary with the North Banda Sea are being reactivated as strike-slip faults. The fault zone does not currently reach Sulawesi. The new fault map differs from previous interpretations concerning the location, age and significance of different parts of the Sorong Fault Zone. Kinematic

  12. 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

  13. ESR dating of fault rocks

    International Nuclear Information System (INIS)

    Lee, Hee Kwon

    2003-02-01

    Past movement on faults can be dated by measurement of the intensity of ESR signals in quartz. These signals are reset by local lattice deformation and local frictional heating on grain contacts at the time of fault movement. The ESR signals then grow back as a result of bombardment by ionizing radiation from surrounding rocks. The age is obtained from the ratio of the equivalent dose, needed to produce the observed signal, to the dose rate. Fine grains are more completely reset during faulting, and a plot of age vs. grain size shows a plateau for grains below critical size; these grains are presumed to have been completely zeroed by the last fault activity. We carried out ESR dating of fault rocks collected near the Gori nuclear reactor. Most of the ESR signals of fault rocks collected from the basement are saturated. This indicates that the last movement of the faults had occurred before the Quaternary period. However, ESR dates from the Oyong fault zone range from 370 to 310 ka. Results of this research suggest that long-term cyclic fault activity of the Oyong fault zone continued into the Pleistocene

  14. Large earthquakes and creeping faults

    Science.gov (United States)

    Harris, Ruth A.

    2017-01-01

    Faults are ubiquitous throughout the Earth's crust. The majority are silent for decades to centuries, until they suddenly rupture and produce earthquakes. With a focus on shallow continental active-tectonic regions, this paper reviews a subset of faults that have a different behavior. These unusual faults slowly creep for long periods of time and produce many small earthquakes. The presence of fault creep and the related microseismicity helps illuminate faults that might not otherwise be located in fine detail, but there is also the question of how creeping faults contribute to seismic hazard. It appears that well-recorded creeping fault earthquakes of up to magnitude 6.6 that have occurred in shallow continental regions produce similar fault-surface rupture areas and similar peak ground shaking as their locked fault counterparts of the same earthquake magnitude. The behavior of much larger earthquakes on shallow creeping continental faults is less well known, because there is a dearth of comprehensive observations. Computational simulations provide an opportunity to fill the gaps in our understanding, particularly of the dynamic processes that occur during large earthquake rupture and arrest.

  15. ESR dating of fault rocks

    Energy Technology Data Exchange (ETDEWEB)

    Lee, Hee Kwon [Kangwon National Univ., Chuncheon (Korea, Republic of)

    2003-02-15

    Past movement on faults can be dated by measurement of the intensity of ESR signals in quartz. These signals are reset by local lattice deformation and local frictional heating on grain contacts at the time of fault movement. The ESR signals then grow back as a result of bombardment by ionizing radiation from surrounding rocks. The age is obtained from the ratio of the equivalent dose, needed to produce the observed signal, to the dose rate. Fine grains are more completely reset during faulting, and a plot of age vs. grain size shows a plateau for grains below critical size; these grains are presumed to have been completely zeroed by the last fault activity. We carried out ESR dating of fault rocks collected near the Gori nuclear reactor. Most of the ESR signals of fault rocks collected from the basement are saturated. This indicates that the last movement of the faults had occurred before the Quaternary period. However, ESR dates from the Oyong fault zone range from 370 to 310 ka. Results of this research suggest that long-term cyclic fault activity of the Oyong fault zone continued into the Pleistocene.

  16. Real-time fault diagnosis and fault-tolerant control

    OpenAIRE

    Gao, Zhiwei; Ding, Steven X.; Cecati, Carlo

    2015-01-01

    This "Special Section on Real-Time Fault Diagnosis and Fault-Tolerant Control" of the IEEE Transactions on Industrial Electronics is motivated to provide a forum for academic and industrial communities to report recent theoretic/application results in real-time monitoring, diagnosis, and fault-tolerant design, and exchange the ideas about the emerging research direction in this field. Twenty-three papers were eventually selected through a strict peer-reviewed procedure, which represent the mo...

  17. Method of fault diagnosis in nuclear power plant base on genetic algorithm and knowledge base

    International Nuclear Information System (INIS)

    Zhou Yangping; Zhao Bingquan

    2000-01-01

    Via using the knowledge base, combining Genetic Algorithm and classical probability and contraposing the characteristic of the fault diagnosis of NPP. The authors put forward a method of fault diagnosis. In the process of fault diagnosis, this method contact the state of NPP with the colony in GA and transform the colony to get the individual that adapts to the condition. On the 950MW full size simulator in Beijing NPP simulation training center, experimentation shows it has comparative adaptability to the imperfection of expert knowledge, illusive signal and other instance

  18. Evaluation of fault coverage for digitalized system in nuclear power plants using VHDL

    International Nuclear Information System (INIS)

    Kim, Suk Joon; Lee, Jun Suk; Seong, Poong Hyun

    2003-01-01

    Fault coverage of digital systems is found to be one of the most important factors in the safety analysis of nuclear power plants. Several axiomatic models for the estimation of fault coverage of digital systems have been proposed, but to apply those axiomatic models to real digital systems, parameters that the axiomatic models require should be approximated using analytic methods, empirical methods or expert opinions. In this paper, we apply the fault injection method to VHDL computer simulation model of a real digital system which provides the protection function to nuclear power plants, for the approximation of fault detection coverage of the digital system. As a result, the fault detection coverage of the digital system could be obtained

  19. The Design and Implementation of a Remote Fault Reasoning Diagnosis System for Meteorological Satellites Data Acquisition

    Directory of Open Access Journals (Sweden)

    Zhu Jie

    2017-01-01

    Full Text Available Under the background of the trouble shooting requirements of FENGYUN-3 (FY-3 meteorological satellites data acquisition in domestic and oversea ground stations, a remote fault reasoning diagnosis system is developed by Java 1.6 in eclipse 3.6 platform. The general framework is analyzed, the workflow is introduced. Based on the system, it can realize the remote and centralized monitoring of equipment running status in ground stations,triggering automatic fault diagnosis and rule based fault reasoning by parsing the equipment quality logs, generating trouble tickets and importing expert experience database, providing text and graphics query methods. Through the practical verification, the system can assist knowledge engineers in remote precise and rapid fault location with friendly graphical user interface, boost the fault diagnosis efficiency, enhance the remote monitoring ability of integrity operating control system. The system has a certain practical significance to improve reliability of FY-3 meteorological satellites data acquisition.

  20. Law for nuclear experts only

    Energy Technology Data Exchange (ETDEWEB)

    Wagner, H [Kernforschungszentrum Karlsruhe G.m.b.H. (Germany, F.R.)

    1980-02-01

    The Federal Ministry of the Interior is preparing an ordinance on expert consultants under the Atomic Energy Act which, among other topics, is to include legal norms for the criteria to be met by experts in terms of non-partisanship, training, capabilities, technical equipment and cooperation in expert organizations of members of various scientific and technical disciplines. A summary of general criteria relating to the qualification, selection and status of experts called in by the legislative and executive branches and by courts of law, which could be organized as a series of guidelines without any original qualities of legal norms, could be recommended in view of the increasing quantitative and qualitative importance of experts. However, passing an ordinance merely fixing and putting into concrete terms the image of an 'expert under the Atomic Energy Act' is intolerable, because the status of scientific and technical experts by far extends beyond the field of nuclear law in our industrial society characterized by a far reaching division of labor. Weak points in the organization of expert services are not confined to technology or nuclear power. Separate rules establishing legal norms are not convincing also for reasons of technology policy and legal policy as well as for those of social psychology and practice.

  1. Expert Systems in Reference Services.

    Science.gov (United States)

    Roysdon, Christine, Ed.; White, Howard D., Ed.

    1989-01-01

    Eleven articles introduce expert systems applications in library and information science, and present design and implementation issues of system development for reference services. Topics covered include knowledge based systems, prototype development, the use of artificial intelligence to remedy current system inadequacies, and an expert system to…

  2. Artificial Intelligence: The Expert Way.

    Science.gov (United States)

    Bitter, Gary G.

    1989-01-01

    Discussion of artificial intelligence (AI) and expert systems focuses on their use in education. Characteristics of good expert systems are explained; computer software programs that contain applications of AI are described, highlighting one used to help educators identify learning-disabled students; and the future of AI is discussed. (LRW)

  3. Imaging of Subsurface Faults using Refraction Migration with Fault Flooding

    KAUST Repository

    Metwally, Ahmed Mohsen Hassan

    2017-05-31

    We propose a novel method for imaging shallow faults by migration of transmitted refraction arrivals. The assumption is that there is a significant velocity contrast across the fault boundary that is underlain by a refracting interface. This procedure, denoted as refraction migration with fault flooding, largely overcomes the difficulty in imaging shallow faults with seismic surveys. Numerical results successfully validate this method on three synthetic examples and two field-data sets. The first field-data set is next to the Gulf of Aqaba and the second example is from a seismic profile recorded in Arizona. The faults detected by refraction migration in the Gulf of Aqaba data were in agreement with those indicated in a P-velocity tomogram. However, a new fault is detected at the end of the migration image that is not clearly seen in the traveltime tomogram. This result is similar to that for the Arizona data where the refraction image showed faults consistent with those seen in the P-velocity tomogram, except it also detected an antithetic fault at the end of the line. This fault cannot be clearly seen in the traveltime tomogram due to the limited ray coverage.

  4. Imaging of Subsurface Faults using Refraction Migration with Fault Flooding

    KAUST Repository

    Metwally, Ahmed Mohsen Hassan; Hanafy, Sherif; Guo, Bowen; Kosmicki, Maximillian Sunflower

    2017-01-01

    We propose a novel method for imaging shallow faults by migration of transmitted refraction arrivals. The assumption is that there is a significant velocity contrast across the fault boundary that is underlain by a refracting interface. This procedure, denoted as refraction migration with fault flooding, largely overcomes the difficulty in imaging shallow faults with seismic surveys. Numerical results successfully validate this method on three synthetic examples and two field-data sets. The first field-data set is next to the Gulf of Aqaba and the second example is from a seismic profile recorded in Arizona. The faults detected by refraction migration in the Gulf of Aqaba data were in agreement with those indicated in a P-velocity tomogram. However, a new fault is detected at the end of the migration image that is not clearly seen in the traveltime tomogram. This result is similar to that for the Arizona data where the refraction image showed faults consistent with those seen in the P-velocity tomogram, except it also detected an antithetic fault at the end of the line. This fault cannot be clearly seen in the traveltime tomogram due to the limited ray coverage.

  5. Support vector machine in machine condition monitoring and fault diagnosis

    Science.gov (United States)

    Widodo, Achmad; Yang, Bo-Suk

    2007-08-01

    Recently, the issue of machine condition monitoring and fault diagnosis as a part of maintenance system became global due to the potential advantages to be gained from reduced maintenance costs, improved productivity and increased machine availability. This paper presents a survey of machine condition monitoring and fault diagnosis using support vector machine (SVM). It attempts to summarize and review the recent research and developments of SVM in machine condition monitoring and diagnosis. Numerous methods have been developed based on intelligent systems such as artificial neural network, fuzzy expert system, condition-based reasoning, random forest, etc. However, the use of SVM for machine condition monitoring and fault diagnosis is still rare. SVM has excellent performance in generalization so it can produce high accuracy in classification for machine condition monitoring and diagnosis. Until 2006, the use of SVM in machine condition monitoring and fault diagnosis is tending to develop towards expertise orientation and problem-oriented domain. Finally, the ability to continually change and obtain a novel idea for machine condition monitoring and fault diagnosis using SVM will be future works.

  6. Staged-Fault Testing of Distance Protection Relay Settings

    Science.gov (United States)

    Havelka, J.; Malarić, R.; Frlan, K.

    2012-01-01

    In order to analyze the operation of the protection system during induced fault testing in the Croatian power system, a simulation using the CAPE software has been performed. The CAPE software (Computer-Aided Protection Engineering) is expert software intended primarily for relay protection engineers, which calculates current and voltage values during faults in the power system, so that relay protection devices can be properly set up. Once the accuracy of the simulation model had been confirmed, a series of simulations were performed in order to obtain the optimal fault location to test the protection system. The simulation results were used to specify the test sequence definitions for the end-to-end relay testing using advanced testing equipment with GPS synchronization for secondary injection in protection schemes based on communication. The objective of the end-to-end testing was to perform field validation of the protection settings, including verification of the circuit breaker operation, telecommunication channel time and the effectiveness of the relay algorithms. Once the end-to-end secondary injection testing had been completed, the induced fault testing was performed with three-end lines loaded and in service. This paper describes and analyses the test procedure, consisting of CAPE simulations, end-to-end test with advanced secondary equipment and staged-fault test of a three-end power line in the Croatian transmission system.

  7. Reflection group on 'Expert Culture'

    International Nuclear Information System (INIS)

    Eggermont, G.

    2000-01-01

    As part of SCK-CEN's social sciences and humanities programme, a reflection group on 'Expert Culture' was established. The objectives of the reflection group are: (1) to clarify the role of SCK-CEN experts; (2) to clarify the new role of expertise in the evolving context of risk society; (3) to confront external views and internal SCK-CEN experiences on expert culture; (4) to improve trust building of experts and credibility of SCK-CEN as a nuclear actor in society; (5) to develop a draft for a deontological code; (6) to integrate the approach in training on assertivity and communication; (7) to create an output for a topical day on the subject of expert culture. The programme, achievements and perspectives of the refection group are summarised

  8. Preserving experience through expert systems

    International Nuclear Information System (INIS)

    Jelinek, J.B.; Weidman, S.H.

    1989-01-01

    Expert systems technology, one of the branches in the field of computerized artificial intelligence, has existed for >30 yr but only recently has been made available on commercially standard hardware and software platforms. An expert system can be defined as any method of encoding knowledge by representing that knowledge as a collection of facts or objects. Decisions are made by the expert program by obtaining data about the problem or situation and correlating encoded facts (knowledge) to the data until a conclusion can be reached. Such conclusions can be relayed to the end user as expert advice. Realizing the potential of this technology, General Electric (GE) Nuclear Energy (GENE) has initiated a development program in expert systems applications; this technology offers the potential for packaging, distributing, and preserving nuclear experience in a software form. The paper discusses application fields, effective applications, and knowledge acquisition and knowledge verification

  9. Wilshire fault: Earthquakes in Hollywood?

    Science.gov (United States)

    Hummon, Cheryl; Schneider, Craig L.; Yeats, Robert S.; Dolan, James F.; Sieh, Kerry E.; Huftile, Gary J.

    1994-04-01

    The Wilshire fault is a potentially seismogenic, blind thrust fault inferred to underlie and cause the Wilshire arch, a Quaternary fold in the Hollywood area, just west of downtown Los Angeles, California. Two inverse models, based on the Wilshire arch, allow us to estimate the location and slip rate of the Wilshire fault, which may be illuminated by a zone of microearthquakes. A fault-bend fold model indicates a reverse-slip rate of 1.5-1.9 mm/yr, whereas a three-dimensional elastic-dislocation model indicates a right-reverse slip rate of 2.6-3.2 mm/yr. The Wilshire fault is a previously unrecognized seismic hazard directly beneath Hollywood and Beverly Hills, distinct from the faults under the nearby Santa Monica Mountains.

  10. What is Fault Tolerant Control

    DEFF Research Database (Denmark)

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

    2000-01-01

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

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

    Science.gov (United States)

    Daigle, Matthew; Roychoudhury, Indranil

    2010-01-01

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

  12. Development of an expert system for signal validation

    International Nuclear Information System (INIS)

    Qualls, A.L.; Uhrig, R.E.; Upadhyaya, B.R.

    1988-01-01

    Diagnosis of malfunctions in power plants has traditionally been in the domain of the process operator, who relies on training, experience, and reasoning ability to diagnose faults. The authors describe a method of signal validation using expert system technology, which detects possible anomalies in an instrument channel's output, similar to the procedure used by an operator. The system can be used to scan quickly over an array of sensor outputs and flag those that are observed to have possible anomalies. This system, when implemented in an operating power plant, could be used for continuous, on-line instrument anomaly detection with a minimum of computational effort

  13. 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.

  14. Vibration control, machine diagnostics

    International Nuclear Information System (INIS)

    1990-01-01

    Changing vibrations announce damage in the form of wear or cracks on components of, e.g., engine rotors, pumps, power plant turbo sets, rounding-up tools, or marine diesel engines. Therefore, machine diagnostics use frequency analyses, system tests, trend analyses as well as expert systems to localize or estimate the causes of these damages and malfunctions. Data acquisistion, including not only sensors, but also reliable and redundant data processing systems and analyzing systems, play an important role. The lectures pertaining to the data base are covered in detail. (DG) [de

  15. Advanced cloud fault tolerance system

    Science.gov (United States)

    Sumangali, K.; Benny, Niketa

    2017-11-01

    Cloud computing has become a prevalent on-demand service on the internet to store, manage and process data. A pitfall that accompanies cloud computing is the failures that can be encountered in the cloud. To overcome these failures, we require a fault tolerance mechanism to abstract faults from users. We have proposed a fault tolerant architecture, which is a combination of proactive and reactive fault tolerance. This architecture essentially increases the reliability and the availability of the cloud. In the future, we would like to compare evaluations of our proposed architecture with existing architectures and further improve it.

  16. Final Technical Report: PV Fault Detection Tool.

    Energy Technology Data Exchange (ETDEWEB)

    King, Bruce Hardison [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Jones, Christian Birk [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

    2015-12-01

    The PV Fault Detection Tool project plans to demonstrate that the FDT can (a) detect catastrophic and degradation faults and (b) identify the type of fault. This will be accomplished by collecting fault signatures using different instruments and integrating this information to establish a logical controller for detecting, diagnosing and classifying each fault.

  17. Human engineering in the design of expert systems for microcomputer system troubleshooting

    International Nuclear Information System (INIS)

    Easter, J.R.; Elm, W.C.

    1988-01-01

    The man-machine interfaces of the first generation of expert systems have usually received little or no explicit design effort. As a result, many of these systems when placed in their productive environment have only served to collect dust. One of the more aggravating attributes of such systems has been the demand that the user of such systems religiously follow the pre-determined and fixed problem solving path the domain expert designed in the expert system. Westinghouse has embarked on a program aimed at improving the productivity of the I and C maintenance staff responsible for caring for these new systems, the focus of which is the development of a computer based expert system to be used as a trouble-shooting aid. To date, Westinghouse has created a knowledge structure for such an expert system that describes the purposes or design objectives of the faulted microcomputer system

  18. Fault current limiter

    Science.gov (United States)

    Darmann, Francis Anthony

    2013-10-08

    A fault current limiter (FCL) includes a series of high permeability posts for collectively define a core for the FCL. A DC coil, for the purposes of saturating a portion of the high permeability posts, surrounds the complete structure outside of an enclosure in the form of a vessel. The vessel contains a dielectric insulation medium. AC coils, for transporting AC current, are wound on insulating formers and electrically interconnected to each other in a manner such that the senses of the magnetic field produced by each AC coil in the corresponding high permeability core are opposing. There are insulation barriers between phases to improve dielectric withstand properties of the dielectric medium.

  19. An expert system for sensor data validation and malfunction detection

    International Nuclear Information System (INIS)

    Hashemi, S.; Hajek, B.K.; Miller, D.W.

    1987-01-01

    Nuclear power plant operation and monitoring in general is a complex task which requires a large number of sensors, alarms and displays. At any instant in time, the operator is required to make a judgment about the state of the plant and to react accordingly. During abnormal situations, operators are further burdened with time constraints. The possibility of an undetected faulty instrumentation line, adds to the complexity of operators' reasoning tasks. Failure of human operators to cope with the conceptual complexity of abnormal situations often leads to more serious malfunctions and further damages to plant (TMI-2 as an example). During these abnormalities, operators rely on the information provided by the plant sensors and associated alarms. Their usefulness however, is quickly diminished by their large number and the extremely difficult task of interpreting and comprehending the information provided by them. The need for an aid to assist the operator in interpreting the available data and diagnosis of problems is obvious. Recent work at the Ohio State University Laboratory of Artificial Intelligence Research (LAIR) and the nuclear engineering program has concentrated on the problem of diagnostic expert systems performance and their applicability to the nuclear power plant domain. There has also been concern about the diagnostic expert systems performance when using potentially invalid sensor data. Because of this research, an expert system has been developed that can perform diagnostic problem solving despite the existence of some conflicting data in the domain. This work has resulted in enhancement of a programming tool, that allows domain experts to create a diagnostic system that will be to some degree, tolerant of bad data while performing diagnosis. This expert system is described here

  20. Expert software for accident identification

    International Nuclear Information System (INIS)

    Dobnikar, M.; Nemec, T.; Muehleisen, A.

    2003-01-01

    Each type of an accident in a Nuclear Power Plant (NPP) causes immediately after the start of the accident variations of physical parameters that are typical for that type of the accident thus enabling its identification. Examples of these parameter are: decrease of reactor coolant system pressure, increase of radiation level in the containment, increase of pressure in the containment. An expert software enabling a fast preliminary identification of the type of the accident in Krsko NPP has been developed. As input data selected typical parameters from Emergency Response Data System (ERDS) of the Krsko NPP are used. Based on these parameters the expert software identifies the type of the accident and also provides the user with appropriate references (past analyses and other documentation of such an accident). The expert software is to be used as a support tool by an expert team that forms in case of an emergency at Slovenian Nuclear Safety Administration (SNSA) with the task to determine the cause of the accident, its most probable scenario and the source term. The expert software should provide initial identification of the event, while the final one is still to be made after appropriate assessment of the event by the expert group considering possibility of non-typical events, multiple causes, initial conditions, influences of operators' actions etc. The expert software can be also used as an educational/training tool and even as a simple database of available accident analyses. (author)

  1. Expert systems and advanced automation for space missions operations

    Science.gov (United States)

    Durrani, Sajjad H.; Perkins, Dorothy C.; Carlton, P. Douglas

    1990-01-01

    Increased complexity of space missions during the 1980s led to the introduction of expert systems and advanced automation techniques in mission operations. This paper describes several technologies in operational use or under development at the National Aeronautics and Space Administration's Goddard Space Flight Center. Several expert systems are described that diagnose faults, analyze spacecraft operations and onboard subsystem performance (in conjunction with neural networks), and perform data quality and data accounting functions. The design of customized user interfaces is discussed, with examples of their application to space missions. Displays, which allow mission operators to see the spacecraft position, orientation, and configuration under a variety of operating conditions, are described. Automated systems for scheduling are discussed, and a testbed that allows tests and demonstrations of the associated architectures, interface protocols, and operations concepts is described. Lessons learned are summarized.

  2. Expert system for assisting the repair operations on the control racks of the control rods assembly in a 900 MW PWR type reactor

    International Nuclear Information System (INIS)

    Monnier, B.; Doutre, J.L.; Franco, A.

    1990-01-01

    The expert system presented was developed for assisting the repair operations on the control equipment of the control rod assembly in a PWR type reactor. The expert system allows the representation of expert knowledge and diagnostic reasoning. The objective of the expert system is to achieve the most precise diagnostic and localizing of the breakdown elements, by processing the data acquired during breakdown. The development steps, the structure and the applications of the expert system are summarized. The expert system operates in an IBM PC equipped with a AMAIA 8 Mo card. A time schedule of 18 months is predicted [fr

  3. 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...

  4. Intelligent programs-expert systems

    Energy Technology Data Exchange (ETDEWEB)

    Gledhill, V X

    1982-01-01

    In recent years, computer scientists have developed what are called expert systems. These programs have three fundamental components: a knowledge base, which changes with experience; an inference engine which enables the program to make decisions; and an interface that allows the program to communicate with the person using the system. Expert systems have been developed successfully in areas such as medical diagnosis, geology, and computer maintenance. This paper describes the evolution and basic principles of expert systems and give some examples of their use.

  5. Fault Management Design Strategies

    Science.gov (United States)

    Day, John C.; Johnson, Stephen B.

    2014-01-01

    Development of dependable systems relies on the ability of the system to determine and respond to off-nominal system behavior. Specification and development of these fault management capabilities must be done in a structured and principled manner to improve our understanding of these systems, and to make significant gains in dependability (safety, reliability and availability). Prior work has described a fundamental taxonomy and theory of System Health Management (SHM), and of its operational subset, Fault Management (FM). This conceptual foundation provides a basis to develop framework to design and implement FM design strategies that protect mission objectives and account for system design limitations. Selection of an SHM strategy has implications for the functions required to perform the strategy, and it places constraints on the set of possible design solutions. The framework developed in this paper provides a rigorous and principled approach to classifying SHM strategies, as well as methods for determination and implementation of SHM strategies. An illustrative example is used to describe the application of the framework and the resulting benefits to system and FM design and dependability.

  6. Application of expert systems in damage assessment of reinforced concrete structures

    International Nuclear Information System (INIS)

    Fazel Zarandi, M. H.; Sobhani, J.

    2003-01-01

    Expert systems are receiving great attentions in construction industry to support decision making processes in diagnostics, design, repair and rehabilitation of the structures. Although several expert systems have been examined in engineering since the 1970's, their applications in construction industry are rate. This was largely due to the lack of expert system tools available to represent the domain knowledge. Lack of flexibility, applicability, and robustness of the classical models, have forced the scientists to discover the ability of the expert systems in problem solving of civil engineering. This paper present an expert system for diagnosis the deterioration of concrete structures. This expert system emphasizes on cracking distress in reinforced concrete elements. A case study has been presented to examine and evaluate the proposed expert system. The system demonstrates a straightforward method for diagnosing the cause of reinforced concrete elements cracking

  7. Laserjet Printer Troubleshooting Expert System

    African Journals Online (AJOL)

    SOFTLINKS DIGITAL

    computerize the maintenance, and repair process of LaserJet printers, and give a time-based ... The method of fact-finding called knowledge acquisition which is a knowledge- .... Figure 2: Different Problem Modules of LaserJet Printer Faults.

  8. The introduction of compulsory compliance testing of medical diagnostic x-ray equipment in Western Australia

    International Nuclear Information System (INIS)

    Rafferty, M. W.; Jacob, C. S.

    1995-01-01

    Performance testing of medical diagnostic X-ray equipment can reveal equipment faults which, while not always clinically detectable, may contribute to reduced image quality and unnecessary radiation exposure of both patients and staff. Routine testing of such equipment is highly desirable to identify such faults and allows them to be rectified. The Radiological council of Western Australia is moving towards requiring compulsory compliance testing of all (new and existing) medical diagnostic X-ray equipment that all new mobile radiographic and new mammographic X-ray equipment be issued with a compliance test certificate as a prerequisite for registration. Workbooks which provide details of the tests required and recommended test methods have been prepared for medical radiographic (mobile and fixed), fluoroscopic and mammographic X-ray equipment. It is intended that future workbooks include details of the tests and methods for dental and computed tomography X-ray units. The workbooks are not limited to the compliance testing of items as specified in the Regulations, but include tests for other items such as film processing, darkrooms and image quality (for fluoroscopic equipment). Many of the workbook tests could be used within a regular quality assurance program for diagnostic X-ray equipment. Persons who conduct such compliance tests will need to be licensed and have all test certificates endorsed by a qualified expert. Suitable training and assessment of compliance testers will be required. Notification of such tests (including non-compliant items and corrective actions taken) will be required by the Radiological Council as a condition of equipment registration. 9 refs

  9. Expert robots in nuclear plants

    International Nuclear Information System (INIS)

    Byrd, J.S.; Fisher, J.J.; DeVries, K.R.; Martin, T.P.

    1987-01-01

    Expert robots enhance a safety and operations in nuclear plants. E.I. du Pont de Nemours and Company, Savannah River Laboratory, is developing expert mobile robots for deployment in nuclear applications at the Savannah River Plant. Knowledge-based expert systems are being evaluated to simplify operator control, to assist in navigation and manipulation functions, and to analyze sensory information. Development work using two research vehicles is underway to demonstrate semiautonomous, intelligence, expert robot system operation in process areas. A description of the mechanical equipment, control systems, and operating modes is presented, including the integration of onboard sensors. A control hierarchy that uses modest computational methods is being used to allow mobile robots to autonomously navigate and perform tasks in known environments without the need for large computer systems

  10. Expert Systems: An Introduction -46 ...

    Indian Academy of Sciences (India)

    Research Scientist in the. Knowledge Based. Computer Systems Group at NeST. He is one of the ... Expert systems encode human expertise in limited domains ... answers questions the user has and provides an explanation of its reasoning.

  11. Introducing Managers to Expert Systems.

    Science.gov (United States)

    Finlay, Paul N.; And Others

    1991-01-01

    Describes a short course to expose managers to expert systems, consisting of (1) introductory lecture; (2) supervised computer tutorial; (3) lecture and discussion about knowledge structuring and modeling; and (4) small group work on a case study using computers. (SK)

  12. Expert system in PNC, 6

    International Nuclear Information System (INIS)

    Tsubota, Koji

    1990-01-01

    The application of Artificial Intelligence (AI) as a tool for mineral exploration started only a decade ago. The systems that have been reported are in the most cases the expert systems that can simulate the decision of the experts or help numerical calculation for more reasonable and/or fast decision making. PNC started the development of the expert system for uranium exploration in 1983. Since then, KOGITO, a expert system to find the favorability of the target area, has been developed. Two years ago, the second generation development, Intelligent Research Environment and Support System, IRESS was initiated aiming at the establishment of a total support system for a project evaluation. We will review our effort for development of our system and introduce the application of the Data directed Numerical method as a new tool to Ahnemland area in Australia. (author)

  13. Cornell Mixing Zone Expert System

    Science.gov (United States)

    This page provides an overview Cornell Mixing Zone Expert System water quality modeling and decision support system designed for environmental impact assessment of mixing zones resulting from wastewater discharge from point sources

  14. Robust Trust in Expert Testimony

    Directory of Open Access Journals (Sweden)

    Christian Dahlman

    2015-05-01

    Full Text Available The standard of proof in criminal trials should require that the evidence presented by the prosecution is robust. This requirement of robustness says that it must be unlikely that additional information would change the probability that the defendant is guilty. Robustness is difficult for a judge to estimate, as it requires the judge to assess the possible effect of information that the he or she does not have. This article is concerned with expert witnesses and proposes a method for reviewing the robustness of expert testimony. According to the proposed method, the robustness of expert testimony is estimated with regard to competence, motivation, external strength, internal strength and relevance. The danger of trusting non-robust expert testimony is illustrated with an analysis of the Thomas Quick Case, a Swedish legal scandal where a patient at a mental institution was wrongfully convicted for eight murders.

  15. Expert opinion vs. empirical evidence

    Science.gov (United States)

    Herman, Rod A; Raybould, Alan

    2014-01-01

    Expert opinion is often sought by government regulatory agencies when there is insufficient empirical evidence to judge the safety implications of a course of action. However, it can be reckless to continue following expert opinion when a preponderance of evidence is amassed that conflicts with this opinion. Factual evidence should always trump opinion in prioritizing the information that is used to guide regulatory policy. Evidence-based medicine has seen a dramatic upturn in recent years spurred by examples where evidence indicated that certain treatments recommended by expert opinions increased death rates. We suggest that scientific evidence should also take priority over expert opinion in the regulation of genetically modified crops (GM). Examples of regulatory data requirements that are not justified based on the mass of evidence are described, and it is suggested that expertise in risk assessment should guide evidence-based regulation of GM crops. PMID:24637724

  16. Artificial Intelligence and Expert Systems.

    Science.gov (United States)

    Wilson, Harold O.; Burford, Anna Marie

    1990-01-01

    Delineates artificial intelligence/expert systems (AI/ES) concepts; provides an exposition of some business application areas; relates progress; and creates an awareness of the benefits, limitations, and reservations of AI/ES. (Author)

  17. Expert systems in clinical microbiology.

    Science.gov (United States)

    Winstanley, Trevor; Courvalin, Patrice

    2011-07-01

    This review aims to discuss expert systems in general and how they may be used in medicine as a whole and clinical microbiology in particular (with the aid of interpretive reading). It considers rule-based systems, pattern-based systems, and data mining and introduces neural nets. A variety of noncommercial systems is described, and the central role played by the EUCAST is stressed. The need for expert rules in the environment of reset EUCAST breakpoints is also questioned. Commercial automated systems with on-board expert systems are considered, with emphasis being placed on the "big three": Vitek 2, BD Phoenix, and MicroScan. By necessity and in places, the review becomes a general review of automated system performances for the detection of specific resistance mechanisms rather than focusing solely on expert systems. Published performance evaluations of each system are drawn together and commented on critically.

  18. Expert robots in nuclear plants

    International Nuclear Information System (INIS)

    Byrd, J.S.; Fisher, J.J.; DeVries, K.R.; Martin, T.P.

    1987-01-01

    Expert robots will enhance safety and operations in nuclear plants. E. I. du Pont de Nemours and Company, Savannah River Laboratory, is developing expert mobile robots for deployment in nuclear applications at the Savannah River Plant. Knowledge-based expert systems are being evaluated to simplify operator control, to assist in navigation and manipulation functions, and to analyze sensory information. Development work using two research vehicles is underway to demonstrate semiautonomous, intelligent, expert robot system operation in process areas. A description of the mechanical equipment, control systems, and operating modes is presented, including the integration of onboard sensors. A control hierarchy that uses modest computational methods is being used to allow mobile robots to autonomously navigate and perform tasks in known environments without the need for large computer systems

  19. Artificial intelligence methods for diagnostic

    International Nuclear Information System (INIS)

    Dourgnon-Hanoune, A.; Porcheron, M.; Ricard, B.

    1996-01-01

    To assist in diagnosis of its nuclear power plants, the Research and Development Division of Electricite de France has been developing skills in Artificial Intelligence for about a decade. Different diagnostic expert systems have been designed. Among them, SILEX for control rods cabinet troubleshooting, DIVA for turbine generator diagnosis, DIAPO for reactor coolant pump diagnosis. This know how in expert knowledge modeling and acquisition is direct result of experience gained during developments and of a more general reflection on knowledge based system development. We have been able to reuse this results for other developments such as a guide for auxiliary rotating machines diagnosis. (authors)

  20. Nickel Hydrogen Battery Expert System

    Science.gov (United States)

    Johnson, Yvette B.; Mccall, Kurt E.

    1992-01-01

    The Nickel Cadmium Battery Expert System-2, or 'NICBES-2', which was used by the NASA HST six-battery testbed, was subsequently converted into the Nickel Hydrogen Battery Expert System, or 'NICHES'. Accounts are presently given of this conversion process and future uses being contemplated for NICHES. NICHES will calculate orbital summary data at the end of each orbit, and store these files for trend analyses and rules-generation.

  1. Expert opinion vs. empirical evidence

    OpenAIRE

    Herman, Rod A; Raybould, Alan

    2014-01-01

    Expert opinion is often sought by government regulatory agencies when there is insufficient empirical evidence to judge the safety implications of a course of action. However, it can be reckless to continue following expert opinion when a preponderance of evidence is amassed that conflicts with this opinion. Factual evidence should always trump opinion in prioritizing the information that is used to guide regulatory policy. Evidence-based medicine has seen a dramatic upturn in recent years sp...

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

    Directory of Open Access Journals (Sweden)

    Wei-Li Qin

    2016-01-01

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

  3. Accelerometer having integral fault null

    Science.gov (United States)

    Bozeman, Richard J., Jr.

    1995-08-01

    An improved accelerometer is introduced. It comprises a transducer responsive to vibration in machinery which produces an electrical signal related to the magnitude and frequency of the vibration; and a decoding circuit responsive to the transducer signal which produces a first fault signal to produce a second fault signal in which ground shift effects are nullified.

  4. Experts in science and society

    CERN Document Server

    Gigerenzer, Gerd

    2004-01-01

    In today's complex world, we have come to rely increasingly on those who have expertise in specific areas and can bring their knowledge to bear on crucial social, political and scientific questions. Taking the viewpoint that experts are consulted when there is something important at stake for an individual, a group, or society at large, Experts in Science and Society explores expertise as a relational concept. How do experts balance their commitment to science with that to society? How does a society actually determine that a person has expertise? What personal traits are valued in an expert? From where does the expert derive authority? What makes new forms of expertise emerge? These and related questions are addressed from a wide range of areas in order to be inclusive, as well as to demonstrate similarities across areas. Likewise, in order to be culturally comparative, this volume includes examples and discussions of experts in different countries and even in different time periods. The topics include the r...

  5. Counselor Expert System | Debretsion | Zede Journal

    African Journals Online (AJOL)

    An expert system plays an important role on alleviating primarily shortage of experts in a specific area of interest. With the help of an expert system, personnel with little expertise can solve problems that require expert knowledge. In this paper all major aspects of an expert system development have been presented.

  6. 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.

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

    Science.gov (United States)

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

    2018-03-01

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

  8. Molecular Diagnostics

    OpenAIRE

    Choe, Hyonmin; Deirmengian, Carl A.; Hickok, Noreen J.; Morrison, Tiffany N.; Tuan, Rocky S.

    2015-01-01

    Orthopaedic infections are complex conditions that require immediate diagnosis and accurate identification of the causative organisms to facilitate appropriate management. Conventional methodologies for diagnosis of these infections sometimes lack accuracy or sufficient rapidity. Current molecular diagnostics are an emerging area of bench-to-bedside research in orthopaedic infections. Examples of promising molecular diagnostics include measurement of a specific biomarker in the synovial fluid...

  9. Fault isolatability conditions for linear systems

    DEFF Research Database (Denmark)

    Stoustrup, Jakob; Niemann, Henrik

    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...... the faults have occurred. The last step is a fault isolation (FI) of the faults occurring in a specific fault set, i.e. equivalent with the standard FI step. A simple example demonstrates how to turn the algebraic necessary and sufficient conditions into explicit algorithms for designing filter banks, which...

  10. ESR dating of the fault rocks

    International Nuclear Information System (INIS)

    Lee, Hee Kwon

    2005-01-01

    We carried out ESR dating of fault rocks collected near the nuclear reactor. The Upcheon fault zone is exposed close to the Ulzin nuclear reactor. The space-time pattern of fault activity on the Upcheon fault deduced from ESR dating of fault gouge can be summarised as follows : this fault zone was reactivated between fault breccia derived from Cretaceous sandstone and tertiary volcanic sedimentary rocks about 2 Ma, 1.5 Ma and 1 Ma ago. After those movements, the Upcheon fault was reactivated between Cretaceous sandstone and fault breccia zone about 800 ka ago. This fault zone was reactivated again between fault breccia derived form Cretaceous sandstone and Tertiary volcanic sedimentary rocks about 650 ka and after 125 ka ago. These data suggest that the long-term(200-500 k.y.) cyclic fault activity of the Upcheon fault zone continued into the Pleistocene. In the Ulzin area, ESR dates from the NW and EW trend faults range from 800 ka to 600 ka NE and EW trend faults were reactivated about between 200 ka and 300 ka ago. On the other hand, ESR date of the NS trend fault is about 400 ka and 50 ka. Results of this research suggest the fault activity near the Ulzin nuclear reactor fault activity continued into the Pleistocene. One ESR date near the Youngkwang nuclear reactor is 200 ka

  11. Application of artificial neural network for NHR fault diagnosis

    International Nuclear Information System (INIS)

    Yu Haitao; Zhang Liangju; Xu Xiangdong

    1999-01-01

    The author makes researches on 200 MW nuclear heating reactor (NHR) fault diagnosis system using artificial neural network, and use the tendency value and real value of the data under the accidents to train and test two BP networks respectively. The final diagnostic result is the combination of the results of the two networks. The compound system can enhance the accuracy and adaptability of the diagnosis comparing to the single network system

  12. 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

  13. Fault Current Characteristics of the DFIG under Asymmetrical Fault Conditions

    Directory of Open Access Journals (Sweden)

    Fan Xiao

    2015-09-01

    Full Text Available During non-severe fault conditions, crowbar protection is not activated and the rotor windings of a doubly-fed induction generator (DFIG are excited by the AC/DC/AC converter. Meanwhile, under asymmetrical fault conditions, the electrical variables oscillate at twice the grid frequency in synchronous dq frame. In the engineering practice, notch filters are usually used to extract the positive and negative sequence components. In these cases, the dynamic response of a rotor-side converter (RSC and the notch filters have a large influence on the fault current characteristics of the DFIG. In this paper, the influence of the notch filters on the proportional integral (PI parameters is discussed and the simplified calculation models of the rotor current are established. Then, the dynamic performance of the stator flux linkage under asymmetrical fault conditions is also analyzed. Based on this, the fault characteristics of the stator current under asymmetrical fault conditions are studied and the corresponding analytical expressions of the stator fault current are obtained. Finally, digital simulation results validate the analytical results. The research results are helpful to meet the requirements of a practical short-circuit calculation and the construction of a relaying protection system for the power grid with penetration of DFIGs.

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2012-09-15

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

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

    International Nuclear Information System (INIS)

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

    2012-01-01

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

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

    International Nuclear Information System (INIS)

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

    2012-01-01

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

  17. Arc fault detection system

    Science.gov (United States)

    Jha, K.N.

    1999-05-18

    An arc fault detection system for use on ungrounded or high-resistance-grounded power distribution systems is provided which can be retrofitted outside electrical switchboard circuits having limited space constraints. The system includes a differential current relay that senses a current differential between current flowing from secondary windings located in a current transformer coupled to a power supply side of a switchboard, and a total current induced in secondary windings coupled to a load side of the switchboard. When such a current differential is experienced, a current travels through a operating coil of the differential current relay, which in turn opens an upstream circuit breaker located between the switchboard and a power supply to remove the supply of power to the switchboard. 1 fig.

  18. Arc fault detection system

    Science.gov (United States)

    Jha, Kamal N.

    1999-01-01

    An arc fault detection system for use on ungrounded or high-resistance-grounded power distribution systems is provided which can be retrofitted outside electrical switchboard circuits having limited space constraints. The system includes a differential current relay that senses a current differential between current flowing from secondary windings located in a current transformer coupled to a power supply side of a switchboard, and a total current induced in secondary windings coupled to a load side of the switchboard. When such a current differential is experienced, a current travels through a operating coil of the differential current relay, which in turn opens an upstream circuit breaker located between the switchboard and a power supply to remove the supply of power to the switchboard.

  19. Probabilistic assessment of faults

    International Nuclear Information System (INIS)

    Foden, R.W.

    1987-01-01

    Probabilistic safety analysis (PSA) is the process by which the probability (or frequency of occurrence) of reactor fault conditions which could lead to unacceptable consequences is assessed. The basic objective of a PSA is to allow a judgement to be made as to whether or not the principal probabilistic requirement is satisfied. It also gives insights into the reliability of the plant which can be used to identify possible improvements. This is explained in the article. The scope of a PSA and the PSA performed by the National Nuclear Corporation (NNC) for the Heysham II and Torness AGRs and Sizewell-B PWR are discussed. The NNC methods for hazards, common cause failure and operator error are mentioned. (UK)

  20. 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.