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Sample records for plant diagnosis system

  1. 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

  2. Plant experience with an expert system for alarm diagnosis

    International Nuclear Information System (INIS)

    Gimmy, K.L.

    1986-01-01

    An expert system called Diagnosis of Multiple Alarms (DMA) is in routine use at four nuclear reactors operated by the DuPont Company. The system is wired to plant alarm annunciators and does event-tree analysis to see if a pattern exists. Any diagnosis is displayed to the plant operator and the corrective procedure to be followed is also identified. The display is automatically superseded if a higher priority diagnosis is made. The system is integrated with operator training and procedures. Operating results have been positive. DMA has diagnosed several hard-to-locate small leaks. There have been some false diagnosis, and realistic plant environments must be considered in such expert systems. 2 refs., 5 figs

  3. A fault diagnosis system for nuclear power plant operation

    International Nuclear Information System (INIS)

    Ohga, Yukiharu; Hayashi, Yoshiharu; Yuchi, Hiroyuki; Utena, Shunsuke; Maeda, Akihiko

    2002-01-01

    A fault diagnosis system has been developed to support operators in nuclear power plants. In the system various methods are combined to get a diagnosis result which provides better detection sensitivity and result reliability. The system is composed of an anomaly detection part with diagnosis modules, an integration part which obtains the diagnosis result by combining results from each diagnosis module, and a prediction part with state prediction and estimation modules. For the anomaly detection part, three kinds of modules are prepared: plant signal processing, early fault detection and event identification modules. The plant signal processing module uses wavelet transform and chaos technologies as well as fast Fourier transform (FFT) to analyze vibration sensor signals and to detect signal anomaly. The early fault detection module uses the neural network model of a plant subprocess to estimate the process variable values assuming normal conditions, and to detect an anomaly by comparing the measured and estimated values. The event identification module identifies the kind of occurring event by using the neural network and knowledge processing. In the integration part the diagnosis is performed by using knowledge processing. The knowledge for diagnosis is structured based on the means-ends abstraction hierarchy to simplify knowledge input and maintenance. In the prediction part, the prediction module predicts the future changes of process variables and plant interlock statuses and the estimation module estimates the values of unmeasurable variables. A prototype system has been developed and the system performance was evaluated. The evaluation results show that the developed technologies are effective to improve the human-machine system for plant operation. (author)

  4. A knowledge based system for plant diagnosis

    International Nuclear Information System (INIS)

    Motoda, H.; Yamada, N.; Yoshida, K.

    1984-01-01

    A knowledge based system for plant diagnosis is proposed in which both event-oriented and function-oriented knowledge are used. For the proposed system to be of practical use, these two types of knowledge are represented by mutually nested four frames, i.e. the component, causality, criteriality, and simulator frames, and production rules. The system provides fast inference capability for use as both a production system and a formal reasoning system, with uncertainty of knowledge taken into account in the former. Event-oriented knowledge is used in both diagnosis and guidance and function-oriented knowledge, in diagnosis only. The inference capability required is forward chaining in the former and resolution in the latter. The causality frame guides in the use of event-oriented knowledge, whereas the criteriality frame does so for function-oriented knowledge. Feedback nature of the plant requires the best first search algorithm that uses histories in the resolution process. The inference program is written in Lisp and the plant simulator and the process I/O control programs in Fortran. Fast data transfer between these two languages is realized by enhancing the memory management capability of Lisp to control the numerical data in the global memory. Simulation applications to a BWR plant demonstrated its diagnostic capability

  5. Development of distributed plant monitoring and diagnosis system at Monju

    International Nuclear Information System (INIS)

    Okusa, Kyoichi; Tamayama, Kiyoshi; Kitamura, Tomomi

    2003-01-01

    In a nuclear plant, it is required to detect an anomaly as early as possible and to inhibit adverse consequences. This requirement is especially important for a prototype Fast Breeder Reactor Monju. Therefore, a monitoring and diagnosis system is required to be developed for Monju plant equipments. In these days, such a monitoring and diagnosis system can be realized using Web technology with rationalized system resources due to the remarkable progress of computer network technology. Then, we developed a Web based platform for the monitoring and diagnosis system of Monju. Distributed architecture, standardization and highly flexible system structure have been taken account of in the development. This newly developed platform and prototype monitoring and diagnosis systems have been validated. Prototype monitoring and diagnosis systems on the platform acquire Monju plant data and display the data on client computers using Monju intranet with acceptable delay times. The prototype monitoring and diagnosis systems for Monju have been developed on the platform and the whole system has been validated. (author)

  6. Experience on a BWR plant diagnosis system

    International Nuclear Information System (INIS)

    Tanabe, A.; Kawai, K.; Hashimoto, Y.

    1981-01-01

    It is important to watch plant dynamics and equipment condition for avoiding a big transient or avoiding damage to a system by equipment failure. After the TMI accident the necessity of a diagnosis system has been recognized and such development activities have become of primary importance in many organizations. A diagnosis system has two kinds of function. One is the early detection of an anomaly before detection by a conventional instrumentation system. The other is appropriate instruction after alarm or scram has occurred. The authors have been developing the former system by a noise analysis technique and a feasibility study has been undertaken in recent years as a joint research programme of several electric power companies and the Toshiba Corporation. A prototype diagnosis system has been installed on a BWR plant in Japan. This diagnosis system concerns reactor core, jet pumps and three main control systems. Many data from normal operation have been accumulated using this system and a variation pattern of normal noise data is clarified. On this basis, anomally detection criteria have been determined using statistical decision theory. It is confirmed that this system performance is satisfactory, and that the system will be of great use for surveillance of core and control systems without artificial disturbances. (author)

  7. Water chemistry diagnosis system for nuclear power plants

    International Nuclear Information System (INIS)

    Igarashi, Hiroo; Koya, Hiroshi; Osumi, Katsumi.

    1990-01-01

    The water quality control for the BWRs in Japan has advanced rapidly recently, and as to the dose reduction due to the decrease of radioactivity, Japan takes the position leading the world. In the background of the advanced water quality control like this and the increase of nuclear power plants in operation, the automation of arranging a large quantity of water quality control information and the heightening of its reliability have been demanded. Hitachi group developed the water quality synthetic control system which comprises the water quality data management system to process a large quantity of water quality data with a computer and the water quality diagnosis system to evaluate the state of operation of the plants by the minute change of water quality and to carry out the operational guide in the aspect of water quality control. To this water quality diagnosis system, high speed fuzzy inference is applied in order to do rapid diagnosis with fuzzy data. The trend of development of water quality control system, the construction of the water quality synthetic control system, the configuration of the water quality diagnosis system and the development of algorithm and the improvement of the reliability of maintenance are reported. (K.I.)

  8. Expert environment for the development of nuclear power plants failure diagnosis systems

    International Nuclear Information System (INIS)

    Guido, P.N.; Oggianu, S.; Etchepareborda, A.; Fernandez, O.

    1996-01-01

    The present work explores some of the developing stages of an Expert Environment for plant failures Diagnosis Systems starting from Knowledge Based Systems. We present a prototype that carries out an inspection of anomalous symptoms and a diagnosis process based on a Plant Abnormality Model of a PHWR secondary system

  9. A diagnosis system for plant operation support

    International Nuclear Information System (INIS)

    Sundheimer, S.; Lorenzetti, J.; Lamana, C.

    1990-01-01

    The present article describes a diagnosis system for abnormal power plant events. The design is modular and uses a shell written in C languaje and a knowledge basis that can be changed easily. At present the system works with a reduced knowledge for primary and secondery leacks. The mitigation procedure is being written with the help of operation staff

  10. Design of a fault diagnosis system for next generation nuclear power plants

    International Nuclear Information System (INIS)

    Zhao, K.; Upadhyaya, B.R.; Wood, R.T.

    2004-01-01

    A new design approach for fault diagnosis is developed for next generation nuclear power plants. In the nuclear reactor design phase, data reconciliation is used as an efficient tool to determine the measurement requirements to achieve the specified goal of fault diagnosis. In the reactor operation phase, the plant measurements are collected to estimate uncertain model parameters so that a high fidelity model can be obtained for fault diagnosis. The proposed algorithm of fault detection and isolation is able to combine the strength of first principle model based fault diagnosis and the historical data based fault diagnosis. Principal component analysis on the reconciled data is used to develop a statistical model for fault detection. The updating of the principal component model based on the most recent reconciled data is a locally linearized model around the current plant measurements, so that it is applicable to any generic nonlinear systems. The sensor fault diagnosis and process fault diagnosis are decoupled through considering the process fault diagnosis as a parameter estimation problem. The developed approach has been applied to the IRIS helical coil steam generator system to monitor the operational performance of individual steam generators. This approach is general enough to design fault diagnosis systems for the next generation nuclear power plants. (authors)

  11. Expert systems application to plant diagnosis and sensor data validation

    International Nuclear Information System (INIS)

    Hashemi, S.; Hajek, B.K.; Miller, D.W.; Chandrasekaran, B.; Josephson, J.R.

    1986-01-01

    In a nuclear power plant, over 2000 alarms and displays are available to the operator. For any given set of alarms and displays, the operator must be able to diagnose and correct the problem (s) quickly and accurately. At the same time, the operator is expected to distinguish the plant system faults from instrumentation channel failures and drifts. Needs for plant operator aids have been considered since the accident at TMI. Many of these aids are of the form of the Safety Parameter Display Systems and offer improved methods of displaying otherwise available data to the operator in a more concise and summarized format. diagnosis, however, remains a desirable objective of an operator aid. At The Ohio State University, faculty and students in nuclear engineering and computer science have evaluated this problem. The results of these studies have shown that plant diagnosis and sensor data validation must be considered as one integral problem and cannot be isolated from one another. Otherwise, an incorrect diagnosis based on faulty instrument information might be provided to the operator. In this study, the Knowlege Based System (KBS) technology is being incorporated to accomplish a final goal of an intelligent operator aid system

  12. Water quality diagnosis system for power plant

    International Nuclear Information System (INIS)

    Igarashi, Hiroo; Fukumoto, Toshihiko

    1991-01-01

    An AI diagnose system for the water quality control of a BWR type reactor is divided into a general diagnosing section for generally classifying the water quality conditions of the plant depending on a causal relation between the symptom of the water quality abnormality and its causes, generally diagnosing the position and the cause of the abnormality and ranking the items considered to be the cause, and a detail diagnosing section for a further diagnosis based on the result of the diagnosis in the former section. The general diagnosing section provides a plurality of threshold values showing the extent of the abnormality depending on the cause to the causal relation between the causes and the forecast events previously formed depending on the data of process sensors in the plant. Since the diagnosis for the abnormality and normality is given not only as an ON or OFF mode but also as the extent thereof, it can enter the detailed diagnosis in the most plausible order, based on a plurality of estimated causes, to enable to find the case and take a counter-measure in an early stage. (N.H.)

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

    International Nuclear Information System (INIS)

    Liu Yongkuo; Xie Chunli; Cheng Shouyu; Xia Hong

    2011-01-01

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

  14. Method for fault diagnosis of digital control systems in nuclear power plant

    International Nuclear Information System (INIS)

    Suzuki, Satoshi; Nagaoka, Yukio; Ohga, Yukiharu; Ito, Tetsuo

    1990-01-01

    This paper presents a method for localizing faulty components of control systems by replaceable parts such as print boards and cables, in a large scale plant like a nuclear power plant. Most of today's control systems form a distributed configuration including many digital controllers interconnected by data communication networks. Usually, to localize the faulty components in nuclear plant control systems, suspected faulty components are narrowed down by executing manual tests to examine whether the objects are normal or abnormal based on design documents and personnel know-how, besides the uses of self-diagnosis functions built into the control systems. In the present method, procedures of various tests including the know-how and checking of self-diagnosis functions are provided as knowledge of tests. The tests to be executed is determined by considering failure probabilities of objects, and easiness and effectiveness of testing. Then, the suspects are narrowed down sequentially based on the test result. In checking feasibility of this diagnosis method for a simulated control system, intended faults are satisfactorily localized. This method is confirmed to be practicable for diagnosis of large scale digital control systems. (author)

  15. Building and application of the performance diagnosis system for nuclear power plants

    International Nuclear Information System (INIS)

    Ono, S.; Kanbara, K.; Sugawara, Y.

    2010-01-01

    To achieve a low-carbon society, we promote utilization of nuclear energy, which plays a zero-emission power generation. Therefore the nuclear power plants have been imposed a stable supply of electricity. The condition based maintenance (CBM) is effective in order to maintain a stable operation of the nuclear power plants. We built the performance diagnosis system based on the heat and mass balance calculation as one of supporting tools for the CBM. Moreover we note that the performance diagnosis system is built for steam turbine cycle operating with saturated steam conditions. (author)

  16. A fundamental study on nuclear power plant diagnosis system

    International Nuclear Information System (INIS)

    Yoshimura, Sei-ichi; Fujimoto, Junzo

    1987-01-01

    Diagnosis of nuclear power plant is a large application field of knowledge engineering. But, the study examples are few and the diagnosis method is not established yet. This report describes the diagnosis method using cross correlation coefficients and describes the knowledge acquisition method of undefined transients in order to enhance the system performance. The usefulness of the system was verified by putting some data into the system. Main results are as follows. (1) Diagnosis method. Some transients are selected by the first judgement and one of them is identified by the second judgement using the cross correlation. (2) Knowledge aquisition method. When putting new data into the knowledge-base, the system indicates the inconsistency by arranging the aquired data, and the operators input new transient names and corresponding manipulation methods after analyzing the indicated results. (3) Usefulness of the system. Freedwater controller failures(2 transients), 2 recirculation pumps trip and a dummy datum combined 2 transients(one is feedwater controller failure and one is 2 recirculation pumps trip) were put into the system. It was proved that the system identified the transients correctly and it indicated the first hit and the inconsisency of the transients in the course of knowledge acquisition. (author)

  17. Plant diagnosis device

    International Nuclear Information System (INIS)

    Tozuka, Shin-ichi.

    1996-01-01

    Standard data approximately defined are inputted as 1:1 functional data between at least two or more plant data and each of plant data are inputted. Diagnosis data corresponding to each of process data are formed based on the functional data. Limit value data to be a threshold value which determines whether the diagnosis data are in a predetermined state or not are formed. The diagnosis data and the limit value data are displayed in a recognizable state. If diagnosis data of a plurality of plants are displayed simultaneously, all of the plant data are substantially the same value with one standard datum if the plant is in a normal state. When abnormality should occur in the plant, the difference between the diagnosis data and the standard data is remarkable, and the difference between the diagnosis data of other normal plant data and the standard data are also made remarkably, accordingly, the display of a plurality of diagnosis data is scattered thereby capable of diagnosing the abnormality of the plant. (N.H.)

  18. Development of an accident diagnosis system using a dynamic neural network for nuclear power plants

    International Nuclear Information System (INIS)

    Lee, Seung Jun; Kim, Jong Hyun; Seong, Poong Hyun

    2004-01-01

    In this work, an accident diagnosis system using the dynamic neural network is developed. In order to help the plant operators to quickly identify the problem, perform diagnosis and initiate recovery actions ensuring the safety of the plant, many operator support system and accident diagnosis systems have been developed. Neural networks have been recognized as a good method to implement an accident diagnosis system. However, conventional accident diagnosis systems that used neural networks did not consider a time factor sufficiently. If the neural network could be trained according to time, it is possible to perform more efficient and detailed accidents analysis. Therefore, this work suggests a dynamic neural network which has different features from existing dynamic neural networks. And a simple accident diagnosis system is implemented in order to validate the dynamic neural network. After training of the prototype, several accident diagnoses were performed. The results show that the prototype can detect the accidents correctly with good performances

  19. Information interfaces for process plant diagnosis

    International Nuclear Information System (INIS)

    Lind, M.

    1984-02-01

    The paper describes a systematic approach to the design of information interfaces for operator support in diagnosing complex systems faults. The need of interpreting primary measured plant variables within the framework of different system representations organized into an abstraction hierarchy is identified from an analysis of the problem of diagnosing complex systems. A formalized approach to the modelling of production systems, called Multilevel Flow Modelling, is described. A MFM model specifies plant control requirements and the associated need for plant information and provide a consistent context for the interpretation of real time plant signals in diagnosis of malfunctions. The use of MFM models as a basis for functional design of the plant instrumentation system is outlined, and the use of knowledge Based (Expert) Systems for the design of man-machine interfaces is mentioned. Such systems would allow an active user participation in diagnosis and thus provide the basis for cooperative problem solving. 14 refs. (author)

  20. A real-time expert system for nuclear power plant failure diagnosis and operational guide

    International Nuclear Information System (INIS)

    Naito, N.; Sakuma, A.; Shigeno, K.; Mori, N.

    1987-01-01

    A real-time expert system (DIAREX) has been developed to diagnose plant failure and to offer a corrective operational guide for boiling water reactor (BWR) power plants. The failure diagnosis model used in DIAREX was systematically developed, based mainly on deep knowledge, to cover heuristics. Complex paradigms for knowledge representation were adopted, i.e., the process representation language and the failure propagation tree. The system is composed of a knowledge base, knowledge base editor, preprocessor, diagnosis processor, and display processor. The DIAREX simulation test has been carried out for many transient scenarios, including multiple failures, using a real-time full-scope simulator modeled after the 1100-MW(electric) BWR power plant. Test results showed that DIAREX was capable of diagnosing a plant failure quickly and of providing a corrective operational guide with a response time fast enough to offer valuable information to plant operators

  1. Development of Plant Control Diagnosis Technology and Increasing Its Applications

    Science.gov (United States)

    Kugemoto, Hidekazu; Yoshimura, Satoshi; Hashizume, Satoru; Kageyama, Takashi; Yamamoto, Toru

    A plant control diagnosis technology was developed to improve the performance of plant-wide control and maintain high productivity of plants. The control performance diagnosis system containing this technology picks out the poor performance loop, analyzes the cause, and outputs the result on the Web page. Meanwhile, the PID tuning tool is used to tune extracted loops from the control performance diagnosis system. It has an advantage of tuning safely without process changes. These systems are powerful tools to do Kaizen (continuous improvement efforts) step by step, coordinating with the operator. This paper describes a practical technique regarding the diagnosis system and its industrial applications.

  2. Diagnosis of faults in EDF power plants: From monitoring to diagnosis

    International Nuclear Information System (INIS)

    Joussellin, A.; Chevalier, R.

    1994-01-01

    Electricite de France is constantly in search of means to improve safety and availability in its nuclear power plants. To this end, EDF has designed new monitoring systems for the major components of its units: for turbogenerator and inlet valves monitoring, for reactor coolant pumps monitoring, for internal structures monitoring and for loose parts detection. New techniques for signal acquisition and processing for diagnosis are used and all these monitoring systems are designed with the same general concept on monitoring. Simultaneously, a workstation for monitoring and aid in diagnosis (PSAD) is under development. It will integrate every monitoring system and will constitute an indispensable tool for plant personnel, enabling them to diagnose the condition of plant equipment, and providing them with high efficiency and user-friendly tools. The PSAD will have a flexible architecture, guaranteeing optimum distribution of computing power to make it available where it is needed

  3. Diagnosis techniques of the computerized operator support system (COSS) for PWR plants

    International Nuclear Information System (INIS)

    Tani, Mamoru; Yoshimura, Tokuji; Morimoto, Haruki; Fujiwara, Toshitaka; Okamoto, Yoshizo; Masui, Takao.

    1985-01-01

    Aiming at the enhancement of abnormal plant operation reliability, COSS has been developed through the support of the Japanese ministry of International Trade and Industry. The validation test was performed by the plant operators using a plant simulator and the result shows that COSS is useful as operator support aids during abnormal plant conditions. This paper presents two methods of diagnosis used in the COSS. (1) Cause-Consequence Tree: This is a logical treewise expression between cause and it's effect to plant variables. When plant variables exceed the predetermined values of alarm, diagnosis is performed by CCT. (2) Model reference method: In this method, the plant dynamic model is applied as a reference. Diagnosis is performed by comparing the measured values with the output values of the corresponding model. (author)

  4. Diagnosis of faults in EDF power plants: from monitoring to diagnosis

    International Nuclear Information System (INIS)

    Joussellin, A.

    1994-06-01

    Electricite de France is constantly is search of means to improve safety and availability in its nuclear power plants. To this end, EDF has designed new monitoring systems for the major components of its units: for turbogenerator and inlet valves monitoring, for reactor coolant pumps monitoring, for internal structures monitoring and for loose parts detection. New techniques for signal acquisition and processing for diagnosis are used and all these monitoring systems are designed with the same general concept on monitoring. Simultaneously, a workstation for monitoring and aid in diagnosis (PSAD) is under development. It will integrate every monitoring system and will constitute an indispensable tool for plant personnel, enabling them to diagnose the condition of plant equipment, and providing them with high efficiency and user-friendly tools. The PSAD will have a flexible architecture, guaranteeing optimum distribution of computing power to make it available where it is needed. (author). 5 figs., 4 refs

  5. PSAD-a monitoring and aid to diagnosis system participating in saving on maintenance and operation costs and for plant life extension

    International Nuclear Information System (INIS)

    Brasseur, S.; Morel, J.; Joussellin, A.

    1997-01-01

    Monitoring nuclear plants components enable to save on operation and maintenance costs by reducing incidents gravity and casual plant stoppages thank to early detection and fast diagnosis. Improving the knowledge of the behaviour of the plant will also allow to optimize maintenance and to increase plant life. In order to improve monitoring and diagnosis capabilities in nuclear power plants. Electricite de France (EDF) is extending the existing data processing chains towards automatic aided interpretation and diagnosis. Therefore, EDF has designed an integrated monitoring and diagnosis assistance system: PSAD-Poste de Surveillance et d'Aide au Diagnostic, including several monitoring functions of the main components. It integrates on-line monitoring, off-line diagnosis and knowledge based systems. PSAD stations provide homogeneous aids to diagnosis which enable plant personnel to pinpoint the mechanical behaviour of plant equipment. The objective of PSAD is to provide them with high-efficiency and user-friendly tools which can considerabily free them from routine tasks. The first version of the prototype is working on a French Plant. This version includes the software host structure and two monitoring functions: the Reactor Coolant Pumps and the Turbo-generator Monitoring functions. Internal Structures Monitoring function and Loose Parts Detection are still under development and should be integrated into PSAD prototype in 1998

  6. Management Index Systems and Energy Efficiency Diagnosis Model for Power Plant: Cases in China

    Directory of Open Access Journals (Sweden)

    Jing-Min Wang

    2016-01-01

    Full Text Available In recent years, the energy efficiency of thermal power plant largely contributes to that of the industry. A thorough understanding of influencing factors, as well as the establishment of scientific and comprehensive diagnosis model, plays a key role in the operational efficiency and competitiveness for the thermal power plant. Referring to domestic and abroad researches towards energy efficiency management, based on Cloud model and data envelopment analysis (DEA model, a qualitative and quantitative index system and a comprehensive diagnostic model (CDM are construed. To testify rationality and usability of CDM, case studies of large-scaled Chinese thermal power plants have been conducted. In this case, CDM excavates such qualitative factors as technology, management, and so forth. The results shows that, compared with conventional model, which only considered production running parameters, the CDM bears better adaption to reality. It can provide entities with efficient instruments for energy efficiency diagnosis.

  7. Nuclear Power Plants Fault Diagnosis Method Based on Data Fusion

    International Nuclear Information System (INIS)

    Xie Chunli; Liu Yongkuo; Xia Hong

    2009-01-01

    The data fusion is a method suit for complex system fault diagnosis such as nuclear power plants, which is multisource information processing technology. This paper uses data fusion information hierarchical thinking and divides nuclear power plants fault diagnosis into three levels. Data level adopts data mining method to handle data and reduction attributes. Feature level uses three parallel neural networks to deal with attributes of data level reduction and the outputs of three networks are as the basic probability assignment of Dempster-Shafer (D-S) evidence theory. The improved D-S evidence theory synthesizes the outputs of neural networks in decision level, which conquer the traditional D-S evidence theory limitation which can't dispose conflict information. The diagnosis method was tested using correlation data of literature. The test results indicate that the data fusion diagnosis system can diagnose nuclear power plants faults accurately and the method has application value. (authors)

  8. A belief network approach for development of a nuclear power plant diagnosis system

    Energy Technology Data Exchange (ETDEWEB)

    Hwang, I K; Kim, J T; Lee, D Y; Jung, C H; Kim, J Y; Lee, J S; Ham, C S [Korea Atomic Energy Research Institute, Taejon (Korea, Republic of)

    1999-12-31

    Belief network (or Bayesian network) based on Bayes` rule in probabilistic theory can be applied to the reasoning of diagnostic system. This paper describes the basic theory of concept and feasibility of using the network for diagnosis of nuclear power plants. An example shows that the probabilities of root causes of a failure are calculated from the measured or believed evidences. 6 refs., 3 figs. (Author)

  9. A belief network approach for development of a nuclear power plant diagnosis system

    Energy Technology Data Exchange (ETDEWEB)

    Hwang, I. K.; Kim, J. T.; Lee, D. Y.; Jung, C. H.; Kim, J. Y.; Lee, J. S.; Ham, C. S. [Korea Atomic Energy Research Institute, Taejon (Korea, Republic of)

    1998-12-31

    Belief network (or Bayesian network) based on Bayes` rule in probabilistic theory can be applied to the reasoning of diagnostic system. This paper describes the basic theory of concept and feasibility of using the network for diagnosis of nuclear power plants. An example shows that the probabilities of root causes of a failure are calculated from the measured or believed evidences. 6 refs., 3 figs. (Author)

  10. Remote diagnosis system for control and instrumentation systems

    International Nuclear Information System (INIS)

    Ito, Tetsuo; Suzuki, Satoshi; Nagaoka, Yukio.

    1990-01-01

    Control and instrumentation (C and I) systems for nuclear power plants tend to consist of many distributed digital controllers connected with transmission networks. Important parts of the C and I systems are redundantly constructed so that the failure of a component does not readily have a critical effect on the plant operation. It is necessary, however, to localize the faulty component for establishing better availability and maintainability of the plant. To diagnose failure of the C and I systems effectively, a remote diagnosis system is required that diagnoses anomalies of their controllers remotely from a central control room and identifies the fault location. Various fault diagnosis methods that apply artificial intelligence have been proposed for electronic circuits. Their knowledge bases are classified into two categories. One is rule-based knowledge, describing relations between anomaly phenomena and causes. The other is structure-based knowledge, which represents the configuration and functions of diagnosed objects. Though the latter is more suitable for deep inference, it is difficult to use for describing the detailed structure of large-scaled digital C and I systems. Then, a fault diagnosis system was developed that uses both knowledge bases and offers substantial man/machine interface functions for practical use

  11. A new method of knowledge processing for equipment diagnosis of nuclear power plants

    International Nuclear Information System (INIS)

    Fujii, M.; Fukumoto, A.; Tai, I.; Morioka, T.

    1987-01-01

    In this work, the authors complete the development of a new knowledge processing method and representation for equipment diagnosis of nuclear power plants and evaluate its functions by applying to the maintenance and diagnosis support system of the reactor instrumentation. This knowledge processing method system is based on the Cause Generation and Checking concept and has sufficient performance not only in the diagnosis function but also in the man-machine interfacing function. The maintenance and diagnosis support system based on this method leads to the possibility for users to diagnose various phenomena occurred in an objective equipment to the considerable extent by consulting with the system, even if they don't have enough knowledge. With this system, it becomes easy for operators or plant engineers to take immediate actions to counteract against the abnormality. The maintainability of the equipments is improved and MTTR (Mean Time To Repair) is expected to be shorter. This new knowledge processing method is proved to be suited for fault diagnosis of the equipments of nuclear power plants

  12. Systematic methodology for diagnosis of water hammer in LWR power plants

    International Nuclear Information System (INIS)

    Safwat, H.H.; Arastu, A.H.; Husaini, S.M.

    1990-01-01

    The paper gives the dimensions of the knowledge base that is necessary to carry out a diagnosis of water hammer susceptibility/root cause analyses for Pressurized Water Reactor (PWR) and Boiling Water Reactor (BWR) nuclear power plant systems. After introducing some fundamentals, water hammer phenomena are described. Situations where each phenomenon is encountered are given and analytical models capable of simulating the phenomena are referenced. Water hammer events in operating plants and their inclusion in the knowledge base is discussed. The diagnostic methodology is presented through an application on a system in a typical light water reactor plant. The methodology presented serves as a possible foundation for the creation of an expert water hammer diagnosis system. (orig.)

  13. 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)

  14. Application of artificial intelligence for nuclear power plant surveillance and diagnosis problems

    International Nuclear Information System (INIS)

    Monnier, B.; Ricard, B.; Doutre, J.L.; Martin-Mattei, C.; Fernandes, A.

    1991-01-01

    This paper presents three expert systems in the field of surveillance and diagnosis of nuclear power plants. Each application is described from the point of view of knowledge modeling. Then, a general knowledge model is proposed for a class of diagnosis problems. At the end, the paper shows the future frame of the surveillance of the nuclear power plant main components at EDF in which the greatest part of those expert systems will run

  15. A Survey of a Remote Diagnosis Center for Nuclear Power Plants

    International Nuclear Information System (INIS)

    Choi, Yoo Rark; Lee, Jae Cheol; Kim, Jae Hee

    2005-01-01

    Methodologies for remote diagnosis have been developed and applied to medical care and lots of industrial fields. Modern science technologies such as a fast network, high computing power, sensing technology and advanced robot engineering make it possible to diagnose remote targets. Nuclear power plant(NPP) has highly connected network enabling systems. The systems (accumulated data analysis systems, alarm systems, main control panel, NPP database systems and so on) are connected with each other through a network. But remote diagnosis researches for a NPP have been developed individually. Efficient monitoring power, convenient management and a costcutting of the diagnosis will be provided through integration of the remote diagnosis technologies. The result of the integration can be represented as a remote diagnosis center. We propose an architecture of the remote diagnosis center for a NPP in this paper

  16. Expert systems with fuzzy logic for intelligent diagnosis and control of nuclear power plants

    International Nuclear Information System (INIS)

    Abdelhai, M.I.; Upadhyaya, B.R.

    1990-01-01

    A model-based production-rule analysis system was developed for the tracking and diagnosis of the condition of a reactor coolant system (RCS) using a fuzzy logic algorithm. Since nuclear power plants are large and complex systems, it is natural that vagueness, uncertainty, and imprecision are introduced to such systems. Even in fully automated power plants, the critical diagnostic and control changes must be made by operators who usually express their diagnostic and control strategies linguistically as sets of heuristic decision rules. Therefore, additional imprecisions are introduced into the systems because of the imprecise nature of such qualitative strategies when they are converted into quantitative rules. Such problems, in which the source of imprecision is the absence of sharply defined criteria of class membership, could be dealt with using fuzzy set theory. Hence, a fuzzy logic algorithm could be initiated to implement a known heuristic whenever the given information is vague and qualitative, and it will allow operators to introduce certain linguistic assertions and commands to diagnose and control the system

  17. A new diagnosis method using alarm annunciation for nuclear power plants

    International Nuclear Information System (INIS)

    Ozaki, Yoshihiko; Suda, Kazunori; Ozawa, Kenji

    1997-01-01

    We discuss the methodology diversity for diagnosis reasoning in an autonomous operation system, and propose a new diagnosis method using an alarm annunciation system. The combination of annunciated alarms is expected to be peculiar to the anomalous phenomenon or accident. Moreover, as the state of affairs is developing, each appearance of the pattern is changing with time peculiarly to each anomaly or accident. The matter is utilized for the new diagnosis method. The patterns of annunciated alarms with progress of the events are prepared in advance under the condition of the anomalies or accidents by use of a plant simulator. The diagnostic reasoning can be done by comparing the obtained combination of annunciated alarms with the reference templates by using pattern matching method. On the other hand, we have another method, called COBWEB used for conceptual classification in cognitive science, to reason for diagnosis. We have carried out the experiments using the loop type LMFBR plant simulator to obtain the various combinations of annunciated alarms with progress of the events under the conditions of anomalies and accidents. The examined cases were related to the anomalies and accidents in the water/steam system of the LMFBR power plant. The simulation examination showed that each change of the pattern of annunciated alarms is specific to each anomaly or accident, and we have applied the pattern matching technique and COBWEB methods into the diagnostic reasoning using annunciated alarms. We could show the capability of these two methods to reason and focus among various candidates of causes of anomalies with gradually improved conviction degree as time passes from the occurrence of anomalies. It was also confirmed that these methods are effective in diagnosis reasoning as a way the operators are doing the diagnosis reasoning in existing plants. (author)

  18. Automated derivation of failure symptoms for diagnosis of nuclear plant

    International Nuclear Information System (INIS)

    Washio, T.; Kitamura, M.; Kotajima, K.; Sugiyama, K.

    1986-01-01

    A method of automated derivation of failure symptoms was developed as an approach to computer-aided failure diagnosis in a nuclear power plant. The automated derivation is realized using a knowledge representation called the semantic network (S-net). The purpose of this paper is to demonstrate the applicability of the S-net representation as a basic tool for deriving failure symptoms. If one can generate symptoms automatically, the computer-aided plant safety analysis and diagnosis can be performed easily by evaluating the influence of the failures on the whole plant. A specific description format called a 'network list' was introduced to implement the knowledge of the structure of the plant. The failure symptoms are derived automatically, based on the knowledge of the structure of the plant, using a PROLOG-based database handling system. This approach allows us to derive the failure symptoms of the plant without using conventional event-chain models (e.g. a cause-consequence tree) which are subject to human errors in their design and implementation. Applicability of this method was evaluated with a simulation model of the dynamics of the secondary system of a PWR. (author)

  19. Information diversification for intelligent diagnosis of nuclear plants

    International Nuclear Information System (INIS)

    Furukawa, Hiroshi; Kuchimura, Keiji; Kitamura, Masaharu; Washio, Takashi.

    1995-01-01

    A general framework for future development of intelligent operator support systems in nuclear plants is proposed in this paper. The central idea in the framework is the decision-making through consensus among multiple agents, each conducting diagnosis on the basis of mutually different, i.e. diverse, principle by focusing dissimilar symptoms obtained from the plant. The applicability and credibility of the operator support system are expected to be significantly improved by implementing the proposed scheme. The effectiveness of diversification in symptom description independently of the effect of reasoning methods was mainly evaluated in this paper. A prototype system was developed for the subtask of fault diagnosis by multiple neural networks emulating the diagnostic agents. The advantage of the proposed framework, together with the related technique of symptom diversification and consensus, was clearly demonstrated through numerical evaluations simulating anomalies in a pressurized water reactor. The obtained results validate, at least to same extent, the present claim of combining multiple and diverse perspectives for reliable decision-making in high-hazard artifacts. (author)

  20. A new diagnosis method using alarm annunciation for FBR power plants

    International Nuclear Information System (INIS)

    Ozaki, Y.; Suda, K.; Yoshikawa, S.; Ozawa, K.

    1997-01-01

    We discuss the methodology diversity for diagnosis reasoning in autonomous operation system, and propose a new diagnosis method using alarm annunciation system. The methodology diversity is assured by preparing plural agents, each of which is based on its own different methodology, therefore, it is expected for the reliability in diagnosis to be improved. Meanwhile, the combination of annunciated alarms is expected to be peculiar to the anomalous phenomenon or accident. Moreover, as the state of affairs is developing, each appearance of the pattern is changing with time peculiarly to each anomaly or accident. The matter is utilized for the new diagnosis method. The patterns of annunciated alarms with progress of the events are prepared in advance under the condition of the anomalies or accidents by use of plant simulatory. The diagnostic reasoning can be done by comparing the obtained combination of annunciated alarms with the reference templates, pattern matching method. On the other hand, we have another method, called as COBWEB used for conceptual classification in cognitive science, to reason for diagnosis. We have carried out the experiments using the loop type LMFBR plant simulator to obtain the various combinations of annunciated alarms with progress of the events under the conditions of anomalies and accidents. The examined cases were related to the anomalies and accidents in the water/steam system of the LMFBR power plant. We have obtained the conclusions that it is effective to reason the causes of anomalies using the annunciated alarms. We are going to apply the pattern matching technique or COBWEB method into the diagnostic reasoning to confirm the performance of the proposed diagnosis method based on the alarm annunciation. (author). 5 refs, 14 figs

  1. CSRL application to nuclear power plant diagnosis and sensor data validation

    International Nuclear Information System (INIS)

    Hashemi, S.; Punch, W.F. III; Hajek, B.K.

    1988-01-01

    During operational abnormalities, plant operators rely on the information provided by the plant sensors and associated alarms. The sensors' usefulness however, is quickly diminished by their large number and the extremely difficult task of interpreting and comprehending the provided information. Malfunction diagnosis can be further complicated by the existence of conflicting data which can lead to an incorrect diagnostic conclusion. Thus, the value of an operator aid to assist plant personnel in interpreting the available data and diagnosing the plant malfunctions is obvious. Recent work at the Ohio State University Laboratory for Artificial Intelligence Research (OSU-LAIR) and the Nuclear Engineering department has concentrated on the problem of performing expert system diagnosis using potentially invalid sensor data. That is, the authors have been developing expert systems 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. The domain of Boiling Water Nuclear Power Plants was chosen as a test domain to show usefulness of the ideas under real world conditions

  2. CSRL application to nuclear power plant diagnosis and sensor data validation

    International Nuclear Information System (INIS)

    Hashemi, S.; Punch, W.F. III; Hajek, B.K.

    1987-01-01

    During operational abnormalities, plant operators rely on the information provided by the plant sensors and associated alarms. The sensors' usefulness however, is quickly diminished by their large number and the extremely difficult task of interpreting and comprehending the provided information. Malfunction diagnosis can be further complicated by the existence of conflicting data which can lead to an incorrect diagnostic conclusion. Thus, the value of an operator aid to assist plant personnel in interpreting the available data and diagnosing the plant malfunctions is obvious. Recent work at the Ohio State University Laboratory for Artificial Intelligence Research (OSU-LAIR) and the Nuclear Engineering Department has concentrated on the problem of performing expert system diagnosis using potentially invalid sensor data. Expert systems have 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, CSRL, that allows domain experts to create a diagnostic system that will be, to some degree, tolerant of bad data. The domain of Boiling Water Nuclear Power Plants was chosen as a test domain to show usefulness of the ideas under real world conditions

  3. Surveillance and fault diagnosis for power plants in the Netherlands: operational experience

    International Nuclear Information System (INIS)

    Turkcan, E.; Ciftcioglu, O.; Hagen, T.H.J.J. van der

    1998-01-01

    Nuclear Power Plant (NPP) surveillance and fault diagnosis systems in Dutch Borssele (PWR) and Dodewaard (BWR) power plants are summarized. Deterministic and stochastic models and artificial intelligence (AI) methodologies effectively process the information from the sensors. The processing is carried out by means of methods and algorithms that are collectively referred to Power Reactor Noise Fault Diagnosis. Two main schemes used are failure detection and instrument fault detection. In addition to conventional and advanced modern fault diagnosis methodologies involved, also the applications of emerging technologies in Dutch reactors are given and examples from operational experience are presented. (author)

  4. Nuclear power plant pressurizer fault diagnosis using fuzzy signed-digraph and spurious faults elimination methods

    International Nuclear Information System (INIS)

    Park, Joo Hyun

    1994-02-01

    In this work, the Fuzzy Signed Digraph(FSD) method which has been researched for the fault diagnosis of industrial process plant systems is improved and applied to the fault diagnosis of the Kori-2 nuclear power plant pressurizer. A method for spurious faults elimination is also suggested and applied to the fault diagnosis. By using these methods, we could diagnose the multi-faults of the pressurizer and could also eliminate the spurious faults of the pressurizer caused by other subsystems. Besides the multi-fault diagnosis and system-wide diagnosis capabilities, the proposed method has many merits such as real-time diagnosis capability, independency of fault pattern, direct use of sensor values, and transparency of the fault propagation to the operators

  5. Nuclear power plant pressurizer fault diagnosis using fuzzy signed-digraph and spurious faults elimination methods

    International Nuclear Information System (INIS)

    Park, Joo Hyun; Seong, Poong Hyun

    1994-01-01

    In this work, the Fuzzy Signed Digraph (FSD) method which has been researched for the fault diagnosis of industrial process plant systems is improved and applied to the fault diagnosis of the Kori-2 nuclear power plant pressurizer. A method for spurious faults elimination is also suggested and applied to the fault diagnosis. By using these methods, we could diagnose the multi-faults of the pressurizer and could also eliminate the spurious faults of the pressurizer caused by other subsystems. Besides the multi-fault diagnosis and system-wide diagnosis capabilities, the proposed method has many merits such as real-time diagnosis capability, independency of fault pattern, direct use of sensor values, and transparency of the fault propagation to the operators. (Author)

  6. Development of diagnosis and maintenance support system for nuclear power plants with flexible inference function and knowledge base edition support function

    International Nuclear Information System (INIS)

    Fujii, Makoto; Seki, Eiji; Tai, Ichiro; Morioka, Toshihiko

    1988-01-01

    For the reliable and efficient diagnosis and inspection work of the nuclear power plant equipments, 'Diagnosis and Maintenance Support System' has been developed. This system has functions to assist operators or engineers to observe and evaluate equipment conditions based on the experts' knowledge. These functions are carried out through dialogue between the system and users. This system has two subsystems: diagnosis subsystem and knowledge base edition support subsystem. To achieve the functions of diagnosis subsystem, a new method of knowledge processing for equipment diagnosis is adopted. This method is based on the concept of 'Cause Generation and Checking'. Knowledge for diagnosis is represented with modularized production rules. And each rule module consists of four different type rules with hierarchical structure. With this approach, the system is equipped with sufficient performance not only in diagnosis function but also in flexible man-machine interface. Knowledge base edition support subsystem (Graphical Rule Editor) is provided for this system. This editor has functions to display and edit the contents of knowledge base with tree structures through the graphic display. With these functions, the efficiency of constructing expert system is highly improved. By applying this system to the maintenance support of neutron monitoring system, it is proved that this system has satisfactory performance as a diagnosis and maintenance support system. (author)

  7. Development of a Real-Time Microchip PCR System for Portable Plant Disease Diagnosis

    Science.gov (United States)

    Kim, Hyun Soo; Cifci, Osman S.; Vaughn-Diaz, Vanessa L.; Ma, Bo; Kim, Sungman; Abdel-Raziq, Haron; Ong, Kevin; Jo, Young-Ki; Gross, Dennis C.; Shim, Won-Bo; Han, Arum

    2013-01-01

    Rapid and accurate detection of plant pathogens in the field is crucial to prevent the proliferation of infected crops. Polymerase chain reaction (PCR) process is the most reliable and accepted method for plant pathogen diagnosis, however current conventional PCR machines are not portable and require additional post-processing steps to detect the amplified DNA (amplicon) of pathogens. Real-time PCR can directly quantify the amplicon during the DNA amplification without the need for post processing, thus more suitable for field operations, however still takes time and require large instruments that are costly and not portable. Microchip PCR systems have emerged in the past decade to miniaturize conventional PCR systems and to reduce operation time and cost. Real-time microchip PCR systems have also emerged, but unfortunately all reported portable real-time microchip PCR systems require various auxiliary instruments. Here we present a stand-alone real-time microchip PCR system composed of a PCR reaction chamber microchip with integrated thin-film heater, a compact fluorescence detector to detect amplified DNA, a microcontroller to control the entire thermocycling operation with data acquisition capability, and a battery. The entire system is 25×16×8 cm3 in size and 843 g in weight. The disposable microchip requires only 8-µl sample volume and a single PCR run consumes 110 mAh of power. A DNA extraction protocol, notably without the use of liquid nitrogen, chemicals, and other large lab equipment, was developed for field operations. The developed real-time microchip PCR system and the DNA extraction protocol were used to successfully detect six different fungal and bacterial plant pathogens with 100% success rate to a detection limit of 5 ng/8 µl sample. PMID:24349341

  8. Development of a real-time microchip PCR system for portable plant disease diagnosis.

    Directory of Open Access Journals (Sweden)

    Chiwan Koo

    Full Text Available Rapid and accurate detection of plant pathogens in the field is crucial to prevent the proliferation of infected crops. Polymerase chain reaction (PCR process is the most reliable and accepted method for plant pathogen diagnosis, however current conventional PCR machines are not portable and require additional post-processing steps to detect the amplified DNA (amplicon of pathogens. Real-time PCR can directly quantify the amplicon during the DNA amplification without the need for post processing, thus more suitable for field operations, however still takes time and require large instruments that are costly and not portable. Microchip PCR systems have emerged in the past decade to miniaturize conventional PCR systems and to reduce operation time and cost. Real-time microchip PCR systems have also emerged, but unfortunately all reported portable real-time microchip PCR systems require various auxiliary instruments. Here we present a stand-alone real-time microchip PCR system composed of a PCR reaction chamber microchip with integrated thin-film heater, a compact fluorescence detector to detect amplified DNA, a microcontroller to control the entire thermocycling operation with data acquisition capability, and a battery. The entire system is 25 × 16 × 8 cm(3 in size and 843 g in weight. The disposable microchip requires only 8-µl sample volume and a single PCR run consumes 110 mAh of power. A DNA extraction protocol, notably without the use of liquid nitrogen, chemicals, and other large lab equipment, was developed for field operations. The developed real-time microchip PCR system and the DNA extraction protocol were used to successfully detect six different fungal and bacterial plant pathogens with 100% success rate to a detection limit of 5 ng/8 µl sample.

  9. Neural networks and their application to nuclear power plant diagnosis

    International Nuclear Information System (INIS)

    Reifman, J.

    1997-01-01

    The authors present a survey of artificial neural network-based computer systems that have been proposed over the last decade for the detection and identification of component faults in thermal-hydraulic systems of nuclear power plants. The capabilities and advantages of applying neural networks as decision support systems for nuclear power plant operators and their inherent characteristics are discussed along with their limitations and drawbacks. The types of neural network structures used and their applications are described and the issues of process diagnosis and neural network-based diagnostic systems are identified. A total of thirty-four publications are reviewed

  10. Development and assessment of an Al expert system for the monitoring and diagnosis of nuclear power plants

    International Nuclear Information System (INIS)

    Takeuchi, K.; Gagnon, A.; Cheung, A.C.; Meyer, P.E.

    1988-01-01

    Due to the rapid progress in microcomputer and software development, artificial intelligence (AI) expert systems of practical value can be built into microcomputers. An expert system for nuclear plant surveillance, diagnostics, and prognostics was developed using the Texas Instruments AI shell, Personal Consultant Plus (PC-plus) on an IBM PCAT. This expert system runs in a surveillance mode to find an abnormal operating condition. Once an abnormal behavior is found,it switches to a diagnostics mode to identify the cause of difficult, such as steam generator tube rupture (SGTR) and leak. Then, the prognostics mode can be activated to predict the consequences. For this purpose, the knowledge of experts at Westinghouse for nuclear safety has been collected and processed to construct parameters and rules within the framework of a logic tree. The expert system may be used in an on-line mode via a connection to the plant computer, safety parameter display system, or a plant simulator. In addition to evaluating the diagnosis of an event and providing appropriate information required to generate an event report, this tool can also be used to review the normal recorded plant data daily to assure that no abnormal events have occurred. A limited assessment of the expert system was performed and is presented

  11. Expert system for maintenance of nuclear power plants

    International Nuclear Information System (INIS)

    Ito, Tetsuo; Kasahara, Takayasu; Watanabe, Takao; Matsuki, Tsutomu.

    1989-01-01

    The basic function of the expert system which supports the maintenance works such as the diagnosis of nuclear power plants and the planning of maintenance works was developed. For the maintenance of large scale plants like nuclear power plants, much manpower is required. Consequently, it has been desired to develop the system for improving the maintainability by utilizing the expertise and empirical knowledge of skilled engineers. This system comprises the subsystems for aiding plant diagnosis and maintenance work planning. The former diagnoses the contents of out of order based on the knowledge base, and thereafter, guides the method of taking measures using simulator. The latter establishes the plan by using the method of limiting branching together so that the maintenance works do not interfere mutually or do not affect the operation. Hereafter, it is intended to improve the man-machine condition and expand knowledge aiming at the practical use. The outline of the system, the constitution of subsystems, the example of plant diagnosis, the support of plant maintenance work planning and so on are reported. (K.I.)

  12. Intelligent System for Diagnosis of a Three-Phase Separator

    Directory of Open Access Journals (Sweden)

    Irina Ioniţă

    2016-03-01

    Full Text Available Intelligent systems for diagnosis have been used in a variety of domains: financial evaluation, credit scoring problem, identification of software and hardware problems of mechanical and electronic equipment, medical diagnosis, fault detection in gas-oil production plants etc. The goal of diagnosis systems is to classify the observed symptoms as being caused by some diagnosis class while advising systems perform such a classification and offer corrective remedies (recommendations. The current paper discuss the opportunity to combine more intelligent techniques and methodologies (intelligent agents, data mining and expert systems to increase the accuracy of results obtained from the diagnosis of a three-phase separator. The results indicate that the diagnosis hybrid system benefits from the advantages of each module component: intelligent agent module, data mining module and expert system module.

  13. Flow modelling of plant processes for fault diagnosis

    International Nuclear Information System (INIS)

    Praetorius, N.; Duncan, K.D.

    1989-01-01

    Flow and its interruption or degradation is seen by many people in industry to be the essential problem in fault diagnonsis. It is this observation which has motivated the representation of a complex simulation of a process plant presented here. The display system we have developed represents the mass and energy flow functions of the plant and the relationship between such flow functions. In this report we shall mainly discuss how such representation seems to provide opportunities to design alarm systems as an integral part of the flow function representation itself and to solve two of the most intricate problems in diagnosis, namely the problem of symptom referral and the problem of confuseable faults. (author)

  14. Optimal testing input sets for reduced diagnosis time of nuclear power plant digital electronic circuits

    International Nuclear Information System (INIS)

    Kim, D.S.; Seong, P.H.

    1994-01-01

    This paper describes the optimal testing input sets required for the fault diagnosis of the nuclear power plant digital electronic circuits. With the complicated systems such as very large scale integration (VLSI), nuclear power plant (NPP), and aircraft, testing is the major factor of the maintenance of the system. Particularly, diagnosis time grows quickly with the complexity of the component. In this research, for reduce diagnosis time the authors derived the optimal testing sets that are the minimal testing sets required for detecting the failure and for locating of the failed component. For reduced diagnosis time, the technique presented by Hayes fits best for the approach to testing sets generation among many conventional methods. However, this method has the following disadvantages: (a) it considers only the simple network (b) it concerns only whether the system is in failed state or not and does not provide the way to locate the failed component. Therefore the authors have derived the optimal testing input sets that resolve these problems by Hayes while preserving its advantages. When they applied the optimal testing sets to the automatic fault diagnosis system (AFDS) which incorporates the advanced fault diagnosis method of artificial intelligence technique, they found that the fault diagnosis using the optimal testing sets makes testing the digital electronic circuits much faster than that using exhaustive testing input sets; when they applied them to test the Universal (UV) Card which is a nuclear power plant digital input/output solid state protection system card, they reduced the testing time up to about 100 times

  15. Diagnostic system for combine cycle power plant

    International Nuclear Information System (INIS)

    Shimizu, Yujiro; Nomura, Masumi; Tanaka, Satoshi; Ito, Ryoji; Kita, Yoshiyuki

    2000-01-01

    We developed the Diagnostic System for Combined Cycle Power Plant which enables inexperienced operators as well as experienced operators to cope with abnormal conditions of Combined Cycle Power Plant. The features of this system are the Estimate of Emergency Level for Operation and the Prediction of Subsequent Abnormality, adding to the Diagnosis of Cause and the Operation Guidance. Moreover in this system, Diagnosis of Cause was improved by using our original method and support screens can be displayed for educational means in normal condition as well. (Authors)

  16. Algebraic approach for the diagnosis of turbine cycles in nuclear power plants

    International Nuclear Information System (INIS)

    Heo, Gyunyoung; Chang, Soon Heung

    2005-01-01

    According to plant operating staff's practical needs, authors proposed a diagnosis model to identify the performance degradation of steam turbine cycles in nuclear power plants (NPPs). The essential idea of this study is how to identify the intrinsically degraded component which causes electric loss. Authors found that there were not so many turbine cycle diagnosis applications in NPPs currently because of technical, financial, or social characteristics of the plant. So a great part of the diagnosis has been dependent on operating staff's experience and knowledge. However as economic competition becomes severe, the efficiency staffs is asking for reliable and practical advisory tools. For the solution of these shortcomings, authors proposed a simple and intuitive diagnosis concept based on the superposition rule of degradation phenomena, which can be derived by simple algebra and correlation analysis. Though the superposition rule is not so significant statistically, almost all of the performance indices under normal operation are fairly compatible with this model. Authors developed a prototype model of quantitative root-cause diagnosis and validated the background theory using the simulated data. The turbine cycle advisory system using this model was applied to Gori NPP units 3 and 4

  17. Application of non-monotonic logic to failure diagnosis of nuclear power plant

    International Nuclear Information System (INIS)

    Takahashi, M.; Kitamura, M.; Sugiyama, K.

    1989-01-01

    A prototype diagnosis system for nuclear power plants was developed based on Truth Maintenance systems: TMS and Dempster-Shafer probability theory. The purpose of this paper is to establish basic technique for more intelligent, man-computer cooperative diagnosis system. The developed system is capable of carrying out the diagnostic inference under the imperfect observation condition with the help of the proposed belief revision procedure with TMS and the systematic uncertainty treatment with Dempster-Shafer theory. The usefulness and potentiality of the present non-monotonic logic were demonstrated through simulation experiments

  18. An expert system for corrosion rate monitoring and diagnosis in the heating circuits of nuclear power plants

    International Nuclear Information System (INIS)

    Balducelli, C.; Conte, E.; Federico, A.G.; Tripi, A.; Ronchetti, C.

    1988-01-01

    The radiation field of out of core components of a water reactor primary plant depends on corrosion product equilibria. The computer programs that try to simulate the behaviour of the corrosion products and the radiation build up didn't provide good results, especially in describing several different plants with the same program. In order to obtain better results the authors decided to use a different approach, building an expert system, which performs on-line corrosion rate monitoring by means of a number of probes connected to an automatic corrosimeter, evaluates expected corrosion rate values and behaviours, and, if there are discrepancies, performs a diagnosis, providing suggestions to overcome the difficulty. (author)

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

    International Nuclear Information System (INIS)

    Liu Yongkuo; Liu Zhen; Wu Xiaotian

    2014-01-01

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

  20. The diagnosis of plant pathogenic bacteria: a state of art.

    Science.gov (United States)

    Scala, Valeria; Pucci, Nicoletta; Loreti, Stefania

    2018-03-01

    Plant protection plays an important role in agriculture for the food quality and quantity. The diagnosis of plant diseases and the identification of the pathogens are essential prerequisites for their understanding and control. Among the plant pests, the bacterial pathogens have devastating effects on plant productivity and yield. Different techniques (microscopy, serology, biochemical, physiological, molecular tools and culture propagation) are currently used to detect and identify bacterial pathogens. Detection and identification are critical steps for the appropriate application of phytosanitary measures. The "harmonization of phytosanitary regulations and all other areas of official plant protection action" mean the good practices for plant protection and plant material certification. The prevention of diseases progression and spread by early detection are a valuable strategy for proper pest management and disease control. For this purpose, innovative methods aim achieving results within a shorter time and higher performance, to provide rapidly, accurately and reliably diagnosis. In this review, we focus on the techniques for plant bacterial diagnosis and on the regulations for harmonizing plant protection issue.

  1. ''PSAD'' on-line monitoring and aid to diagnosis workstation: a monitoring tool for EDF power plants

    International Nuclear Information System (INIS)

    Morel, J.; Mazalerat, J.M.; Monnier, B.; Cordier, R.

    1993-01-01

    Like other electricity utilities, Electricite de France seeks to enhance the safety and availability of its nuclear power plants. To this end, for over ten years EDF has been installing on each plant unit two monitoring systems of its own design, one to monitor the primary cooling system, and the other, the turbogenerator set. Since the beginning of this project, widespread progress has been made in techniques of signal acquisition and processing, and in diagnosis using artificial intelligence methods. EDF has decided to call on these advanced techniques in developing its new-generation monitoring equipment, and to integrate them in its development of a workstation for on-line monitoring and diagnosis-support (PSAD: Poste de Surveillance et d'Aide au Diagnostic). PSAD will be a tool for on-line monitoring of the main components in nuclear power plants (initially the main coolant pumps and turbogenerator sets, and soon thereafter, monitoring of internal structures, detection of loose parts in the primary cooling system, etc.). PSAD will provide plant personnel with indispensable support in their diagnosis of the condition of plant equipment. It will integrate user-friendly, high-performance systems that also free the operator from many day-to-day tasks. PSAD will have a flexible architecture, for optimum distribution of the computing power where it is most needed, thereby improving the quality of the data. This paper presents the project objectives and describes work currently under way to implement EDF's diagnosis-support strategy for the years to come. (authors). 5 figs., 6 refs

  2. A generic task approach to a real time nuclear power plant fault diagnosis and advisory system

    International Nuclear Information System (INIS)

    Hajek, B.K.; Miller, D.W.; Bhatnagar, R.; Stasenko, J.E.; Punch, W.F. III; Yamada, N.

    1988-01-01

    A generic task toolkit developed at The Ohio State University Laboratory for Artificial Intelligence Research (LAIR) has been used in the development of an aid for operators of nuclear power plants. The toolkit consists of high level programming tools that enable knowledge to be used in accordance with its need. That is, if diagnosis is the need, a framework for performing diagnosis is provided. The operator aid provides for monitoring the conditions in the plant, detecting abnormal events, and providing the operator with guidance and advice through procedures on what path should be followed to mitigate the consequences. 8 refs., 5 figs

  3. Process fault diagnosis using knowledge-based systems

    International Nuclear Information System (INIS)

    Sudduth, A.L.

    1991-01-01

    Advancing technology in process plants has led to increased need for computer based process diagnostic systems to assist the operator. One approach to this problem is to use an embedded knowledge based system to interpret measurement signals. Knowledge based systems using only symptom based rules are inadequate for real time diagnosis of dynamic systems; therefore a model based approach is necessary. Though several forms of model based reasoning have been proposed, the use of qualitative causal models incorporating first principles knowledge of process behavior structure, and function appear to have the most promise as a robust modeling methodology. In this paper the structure of a diagnostic system is described which uses model based reasoning and conventional numerical methods to perform process diagnosis. This system is being applied to emergency diesel generator system in nuclear stations

  4. Simulation study of a system for diagnosis of nuclear power plant operation

    International Nuclear Information System (INIS)

    Wakabayashi, J.; Fukumoto, A.

    1981-01-01

    A diagnostic system of the nuclear power plant operation is proposed and the applicability of this system to the actual plant has been verified by computer simulation. A typical pressurized water reactor plant simulator was made by an analog computer and the diagnostic system was made by a digital computer. The observed signals obtained from the actual plant are simulated by superposing the equivalent observation noises generated by the digital computer on the sampled signals obtained from the plant simulator. 8 refs

  5. Data-driven design of fault diagnosis systems nonlinear multimode processes

    CERN Document Server

    Haghani Abandan Sari, Adel

    2014-01-01

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

  6. Diagnosis aids with artificial intelligence in the PSAD system

    International Nuclear Information System (INIS)

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

    1996-01-01

    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 this sophisticated monitoring and data processing system requires the addition of analysis and diagnosis assistance capabilities. Diagnostic knowledge based systems have thus been added to the functions monitored in PSAD: DIVA for turbine generators, and DIAPO for reactor coolant pumps. These systems rely on a representation of the diagnostic reasoning process of experts and of supporting knowledge. Diagnosis in both systems is performed through an abductive 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 of this paper. In a second part, DIVA and DIAPO specific elements are described. (authors)

  7. 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)

  8. Expert System For Diagnosis Pest And Disease In Fruit Plants

    Science.gov (United States)

    Dewanto, Satrio; Lukas, Jonathan

    2014-03-01

    This paper discussed the development of an expert system to diagnose pests and diseases on fruit plants. Rule base method was used to store the knowledge from experts and literatures. Control technique using backward chain and started from the symptoms to get conclusions about the pests and diseases that occur. Development of the system has been performed using software Corvid Exsys developed by Exsys company. Results showed that the development of this expert system can be used to assist users in identifying the type of pests and diseases on fruit plants. Further development and possibility of using internet for this system are proposed.

  9. Intelligent system for a remote diagnosis of a photovoltaic solar power plant

    International Nuclear Information System (INIS)

    Sanz-Bobi, M A; San Roque, A Muñoz; Marcos, A de; Bada, M

    2012-01-01

    Usually small and mid-sized photovoltaic solar power plants are located in rural areas and typically they operate unattended. Some technicians are in charge of the supervision of these plants and, if an alarm is automatically issued, they try to investigate the problem and correct it. Sometimes these anomalies are detected some hours or days after they begin. Also the analysis of the causes once the anomaly is detected can take some additional time. All these factors motivated the development of a methodology able to perform continuous and automatic monitoring of the basic parameters of a photovoltaic solar power plant in order to detect anomalies as soon as possible, to diagnose their causes, and to immediately inform the personnel in charge of the plant. The methodology proposed starts from the study of the most significant failure modes of a photovoltaic plant through a FMEA and using this information, its typical performance is characterized by the creation of its normal behaviour models. They are used to detect the presence of a failure in an incipient or current form. Once an anomaly is detected, an automatic and intelligent diagnosis process is started in order to investigate the possible causes. The paper will describe the main features of a software tool able to detect anomalies and to diagnose them in a photovoltaic solar power plant.

  10. On-line acoustic monitoring of EDF nuclear plants in operation and loose-part diagnosis

    International Nuclear Information System (INIS)

    Morel, J.L.; Puyal, C.

    1991-05-01

    In order to detect incipient failures in nuclear power plant components, EDF has now put into operation more than 50 loose-part monitoring systems, on its 900 MW and 1 300 MW units. This paper first reviews the experience gained on the 900 MW reactors in recent years. It then focuses on the 1 300 MW loose part monitoring system (IDEAL) and to the tools developed for the diagnosis off site within a specific Expertise Laboratory at the Research and Development Division. New studies have been undertaken within the Monitoring and Aid to Diagnosis Station (PSAD) in order to extend the capabilities of loose part diagnosis on site. The new tools here presented integrate the recent progress in acquisition technology (SMART system) and in artificial intelligence (MIGRE expert system)

  11. The degradation diagnosis of low voltage cables used at nuclear power plants

    International Nuclear Information System (INIS)

    Yamamoto, Toshio; Ashida, Tetsuya; Ikeda, Takeshi; Yasuhara, Takeshi; Takechi, Kei; Araki, Shogo

    2001-01-01

    Low voltage cables which have been used for the supply of electric power and the propagation of control signals in nuclear power plants must be sound for safe and stable operation. The long use of nuclear power plants has been reviewed, and the degradation diagnosis to estimate the soundness of low voltage cables has been emphasized. Mitsubishi Cable Industries has established a degradation diagnosis method of cables which convert the velocity of ultrasonic wave in the surface layer of the cable insulation or jacket into breaking elongation, and has developed a degradation diagnosis equipment of low voltage cables used at nuclear power plants in cooperation with Mitsubishi Heavy Industries. This equipment can be moved by an ultrasonic probe by sequential control and measure the ultrasonic velocity automatically. It is capable of a fast an sensitive diagnosis of the cables. We report the outline of this degradation diagnosis equipment and an example of the adaptability estimation at an actual nuclear power plant. (author)

  12. Chemistry management system for nuclear power plants

    International Nuclear Information System (INIS)

    Nagasawa, Katsumi; Maeda, Katsuji

    1998-01-01

    Recently, the chemistry management in the nuclear power plants has been changing from the problem solution to the predictive diagnosis and maintenance. It is important to maintain the integrity of plant operation by an adequate chemistry control. For these reasons, many plant operation data and chemistry analysis data should be collected and treated effectively to evaluate chemistry condition of the nuclear power plants. When some indications of chemistry anomalies occur, quick and effective root cause evaluation and countermeasures should be required. The chemistry management system has been developed as to provide sophisticate chemistry management in the nuclear power plants. This paper introduces the concept and functions of the chemistry management system for the nuclear power plants. (author)

  13. An application of first-principles diagnosis to a thermalhydraulic system

    International Nuclear Information System (INIS)

    Lapointe, P.A.; Chung, J.

    1990-03-01

    Recent advances in computer technology, such as artificial intelligence and interactive multimedia, offer significant new opportunities to enhance nuclear plant safety and improve the performance of the operations staff. Atomic Energy of Canada Limited is developing a framework on which newer approaches to operator support systems will be implemented. A prototype system has been developed for plant information access and display, on-line advice and diagnosis, and interactive operating procedures; it is called the Operator Companion. This paper describes the work performed for the development of the fault detection and diagnostic module within the Operator Companion. An early prototype of the module was developed for a small heat transfer circuit. A qualitative physics representation coupled with first-principles diagnosis using constraint suspension was utilized. Temporal information was required; it was integrated into the diagnosis using a type of directed graph to record event dependencies. This graph dynamically altered the qualitative model to reflect changes in the system over time. Although not completely formal, out method has successfully integrated the time diagnostic information to permit the identification of the faulty components and limit the number of spurious candidates in the tests performed. This paper summarizes the qualitative diagnosis concepts, describes the special temporal reasoning scheme developed, and presents a summary of the results obtained

  14. Semi-Supervised Classification for Fault Diagnosis in Nuclear Power Plants

    International Nuclear Information System (INIS)

    Ma, Jian Ping; Jiang, Jin

    2014-01-01

    Pattern classification methods have become important tools for fault diagnosis in industrial systems. However, it is normally difficult to obtain reliable labeled data to train a supervised pattern classification model for applications in a nuclear power plant (NPP). However, unlabeled data easily become available through increased deployment of supervisory, control, and data acquisition (SCADA) systems. In this paper, a fault diagnosis scheme based on semi-supervised classification (SSC) method is developed with specific applications for NPP. In this scheme, newly measured plant data are treated as unlabeled data. They are integrated with selected labeled data to train a SSC model which is then used to estimate labels of the new data. Compared to exclusive supervised approaches, the proposed scheme requires significantly less number of labeled data to train a classifier. Furthermore, it is shown that higher degree of uncertainties in the labeled data can be tolerated. The developed scheme has been validated using the data generated from a desktop NPP simulator and also from a physical NPP simulator using a graph-based SSC algorithm. Two case studies have been used in the validation process. In the first case study, three faults have been simulated on the desktop simulator. These faults have all been classified successfully with only four labeled data points per fault case. In the second case, six types of fault are simulated on the physical NPP simulator. All faults have been successfully diagnosed. The results have demonstrated that SSC is a promising tool for fault diagnosis

  15. The Operator's Diagnosis Task under Abnormal Operating Conditions in Industrial Process Plant

    DEFF Research Database (Denmark)

    Goodstein, L.P.; Pedersen, O.M.; Rasmussen, Jens

    1974-01-01

    Analysis of serious accidents in connection with the operation of technical installations demonstrate that the diagnosis task which confronts personnel under non-normal plant conditions is a critical one. This report presents a preliminary outline of characteristic traits connected with the task...... of diagnosis for use in discussions of (a) the studies which are necessary in order to formulate the operator's diagnostic procedures and (b) the possibilities which exists for supporting these procedures through appropriate data processing and display in the control system. At the same time, attempts are made...

  16. Research on method of nuclear power plant operation fault diagnosis based on a combined artificial neural network

    International Nuclear Information System (INIS)

    Liu Feng; Yu Ren; Li Fengyu; Zhang Meng

    2007-01-01

    To solve the online real-time diagnosis problem of the nuclear power plant in operating condition, a method based on a combined artificial neural network is put forward in the paper. Its main principle is: using the BP neural network for the fast group diagnosis, and then using the RBF neural network for distinguishing and verifying the diagnostic result. The accuracy of the method is verified using the simulation values of the key parameters in normal status and malfunction status of a nuclear power plant. The results show that the method combining the advantages of the two neural networks can not only diagnose the learned faults in similar power level of the nuclear power plant quickly and accurately, but also can identify the faults in different power status, as well as the unlearned faults. The outputs of the diagnosis system are in form of the reliability of the faults, and are changing with the lasting of the operation time of the plant. This makes the diagnosis results be more acceptable to operators. (authors)

  17. Plant Lectins as Medical Tools against Digestive System Cancers.

    Science.gov (United States)

    Estrada-Martínez, Laura Elena; Moreno-Celis, Ulisses; Cervantes-Jiménez, Ricardo; Ferriz-Martínez, Roberto Augusto; Blanco-Labra, Alejandro; García-Gasca, Teresa

    2017-07-03

    Digestive system cancers-those of the esophagus, stomach, small intestine, colon-rectum, liver, and pancreas-are highly related to genetics and lifestyle. Most are considered highly mortal due to the frequency of late diagnosis, usually in advanced stages, caused by the absence of symptoms or masked by other pathologies. Different tools are being investigated in the search of a more precise diagnosis and treatment. Plant lectins have been studied because of their ability to recognize and bind to carbohydrates, exerting a variety of biological activities on animal cells, including anticancer activities. The present report integrates existing information on the activity of plant lectins on various types of digestive system cancers, and surveys the current state of research into their properties for diagnosis and selective treatment.

  18. Early detection and diagnosis of disturbances in nuclear power plants

    International Nuclear Information System (INIS)

    Bjorlo, T.J.; Berg, O.; Grini, R.E.; Yokobayashi, M.

    1987-01-01

    The surveillance and control of nuclear power plants comprises a number of tasks and functions which have to be shared between the operators and the control and instrumentation systems. The trend in control room design towards a higher degree of computerization of the control and instrumentation systems and replacement of conventional instrument panels by VDU-based man-machine communication systems opens possibilities for improving the support given to the operators in their cognitive tasks. At the OECD Halden Reactor Project these possibilities are explored through a research and development programme centered around the NORS/HAMMLAB experimental control room facility. The full-scale PWR simulator, NORS, coupled with the HAlden Man-Machine LABoratory (HAMMLAB), which includes the experimental control room as well as an established research methodology and staff, constitutes a unique basis ofr the design, development and validation of operator support systems, as well as for more basic operator performance experimentation. The aim of the system development work at the Halden Project is to design, build and validate computer-based systems which can assist and support the operations in their various tasks and through this improve the total performance and safety of complex plant operation. Currently, the Halden Project is developing an integrated disturbance handling system for use at nuclear power plants. This paper describes the activities on fault detection and diagnosis within this development project

  19. Transient diagnosis system using quantum-inspired computing and Minkowski distance

    Energy Technology Data Exchange (ETDEWEB)

    Nicolau, Andressa dos Santos; Schirru, Roberto, E-mail: andressa@lmp.ufrj.b, E-mail: schirru@lmp.ufrj.b [Federal University of Rio de Janeiro (PEN/COPPE/UFRJ), Rio de Janeiro, RJ (Brazil). Nuclear Engineering Program

    2011-07-01

    This paper proposes a diagnosis system model for identification of transient in a PWR nuclear power plant, optimized by the Quantum Inspired Evolutionary Algorithm - QEA in order to help nuclear power plant operator reduce his cognitive load and increase his available time to maintain the plant operating in a safe condition. This method was developed in order to be able to recognize the normal condition and three accidents of the design basis list of the nuclear power plant Angra 2, postulated in the Final Safety Analysis Report (FSAR). This System compares the similarly distance between the set of variables of the anomalous event, in a given time t, and the centroids of the design-basis transient variables. The lower similarly distance indicates the class of the transient to which the anomalous event belongs. The QEA was then used to find the best position of the centroids of each class of the selected transients. Such positions maximize the number of the correct classifications. Unlike the diagnosis system proposed in the literature, Minkowski distance was employed to calculate the similarity distance. The signatures of four transients were submitted to 1% and 2% of noise, and tested with prototype vector found by QEA. The results showed that the present transient diagnostic system was successfully implemented in the nuclear accident identification problem and was compatible with the techniques presented in the literature. (author)

  20. Transient diagnosis system using quantum-inspired computing and Minkowski distance

    International Nuclear Information System (INIS)

    Nicolau, Andressa dos Santos; Schirru, Roberto

    2011-01-01

    This paper proposes a diagnosis system model for identification of transient in a PWR nuclear power plant, optimized by the Quantum Inspired Evolutionary Algorithm - QEA in order to help nuclear power plant operator reduce his cognitive load and increase his available time to maintain the plant operating in a safe condition. This method was developed in order to be able to recognize the normal condition and three accidents of the design basis list of the nuclear power plant Angra 2, postulated in the Final Safety Analysis Report (FSAR). This System compares the similarly distance between the set of variables of the anomalous event, in a given time t, and the centroids of the design-basis transient variables. The lower similarly distance indicates the class of the transient to which the anomalous event belongs. The QEA was then used to find the best position of the centroids of each class of the selected transients. Such positions maximize the number of the correct classifications. Unlike the diagnosis system proposed in the literature, Minkowski distance was employed to calculate the similarity distance. The signatures of four transients were submitted to 1% and 2% of noise, and tested with prototype vector found by QEA. The results showed that the present transient diagnostic system was successfully implemented in the nuclear accident identification problem and was compatible with the techniques presented in the literature. (author)

  1. Plant Lectins as Medical Tools against Digestive System Cancers

    Directory of Open Access Journals (Sweden)

    Laura Elena Estrada-Martínez

    2017-07-01

    Full Text Available Digestive system cancers—those of the esophagus, stomach, small intestine, colon-rectum, liver, and pancreas—are highly related to genetics and lifestyle. Most are considered highly mortal due to the frequency of late diagnosis, usually in advanced stages, caused by the absence of symptoms or masked by other pathologies. Different tools are being investigated in the search of a more precise diagnosis and treatment. Plant lectins have been studied because of their ability to recognize and bind to carbohydrates, exerting a variety of biological activities on animal cells, including anticancer activities. The present report integrates existing information on the activity of plant lectins on various types of digestive system cancers, and surveys the current state of research into their properties for diagnosis and selective treatment.

  2. Control of power plants and power systems. Proceedings

    International Nuclear Information System (INIS)

    Canales-Ruiz, R.

    1996-01-01

    The 88 papers in this volume constitute the proceedings of the International Federation of Automatic Control Symposium held in Mexico in 1995. The broad areas which they cover are: self tuning control; power plant operations; dynamic stability; fuzzy logic applications; power plants modelling; artificial intelligence applications; power plants simulation; voltage control; control of hydro electric units; state estimation; fault diagnosis and monitoring systems; system expansion and operation planning; security assessment; economic dispatch and optimal load flow; adaptive control; distribution; transient stability and preventive control; modelling and control of nuclear plant; knowledge data bases for automatic learning methods applied to power system dynamic security assessment; control of combined cycle units; power control centres. Separate abstracts have been prepared for the three papers relating to nuclear power plants. (UK)

  3. Expert System for Diagnosis of Hepatitis B Ibrahim Mailafiya, Fatima ...

    African Journals Online (AJOL)

    the rice plant appearing during their life span. [1]. ... use of intelligent systems such as fuzzy logic, artificial neural network and genetic algorithm have been developed [5]. ... The liver being the ..... doctors but to assist them in the quality ... P.Santosh Kumar Patra, An Expert System for Diagnosis of Human diseases, 2010.

  4. A knowledge-based operator advisor system for integration of fault detection, control, and diagnosis to enhance the safe and reliable operation of nuclear power plants

    International Nuclear Information System (INIS)

    Bhatnagar, R.

    1989-01-01

    A Knowledged-Based Operator Advisor System has been developed for enhancing the complex task of maintaining safe and reliable operation of nuclear power plants. The operator's activities have been organized into the four tasks of data interpretation for abstracting high level information from sensor data, plant state monitoring for identification of faults, plan execution for controlling the faults, and diagnosis for determination of root causes of faults. The Operator Advisor System is capable of identifying the abnormal functioning of the plant in terms of: (1) deviations from normality, (2) pre-enumerated abnormal events, and (3) safety threats. The classification of abnormal functioning into the three categories of deviations from normality, abnormal events, and safety threats allows the detection of faults at three levels of: (1) developing faults, (2) developed faults, and (3) safety threatening faults. After the identification of abnormal functioning the system will identify the procedures to be executed to mitigate the consequences of abnormal functioning and will help the operator by displaying the procedure steps and monitoring the success of actions taken. The system also is capable of diagnosing the root causes of abnormal functioning. The identification, and diagnosis of root causes of abnormal functioning are done in parallel to the task of procedure execution, allowing the detection of more critical safety threats while executing procedures to control abnormal events

  5. Noise diagnosis - a method for early detection of failures in a nuclear plant

    International Nuclear Information System (INIS)

    Brinckmann, H.F.

    1981-01-01

    Noise diagnosis constitutes one method for early detection of plant failures. The method is based on the fact that nearly all undesired processes in a nuclear power plant make a measurable contribution to the noise portion of signals. Well-known examples of undesired processes in pressurized water reactors include core-barrel movement, the vibration of control elements, the appearance of loose parts in the coolant flow, and the process of coolant boiling. Each of these processes has been implicated in past nuclear plant failures. In the German Democratic Republic (GDR) P. Liewers and his colleagues have introduced noise analysis systems into the primary circuit of WWER-440 pressurized water reactors (PWR). The most progressive version (RAS-II) has become a prototype for research and routine investigations. This system is described. (author)

  6. The plant-window system

    International Nuclear Information System (INIS)

    Wood, R.T.; Mullens, J.A.; Naser, J.A.

    1995-01-01

    Power plant data, and the information that can be derived from it, provide the link to the plant through which the operations, maintenance and engineering staff understand and manage plant performance. The increasing use of computer technology in the U.S. nuclear power industry has greatly expanded the capability to obtain, analyze, and present data about the plant to station personnel. However, it is necessary to transform the vast quantity of available data into clear, concise, and coherent information that can be readily accessed and used throughout the plant. This need can be met by an integrated computer workstation environment that provides the necessary information and software applications, in a manner that can be easily understood and used, to the proper users throughout the plant. As part of a Cooperative Research and Development Agreement with the Electric Power Research Institute, the Oak Ridge National Laboratory has developed functional requirements for a Plant-Wide Integrated Environment Distributed On Workstations (Plant-Window) System. The Plant-Window System (PWS) can serve the needs of operations, engineering, and maintenance personnel at nuclear power stations by providing integrated data and software applications (e.g., monitoring, analysis, diagnosis, and control applications) within a common environment. The PWS requirements identify functional capabilities and provide guidelines for standardized hardware, software, and display interfaces to define a flexible computer environment that permits a tailored implementation of workstation capabilities and facilitates future upgrades

  7. Fault diagnosis in nuclear power plants using an artificial neural network technique

    International Nuclear Information System (INIS)

    Chou, H.P.; Prock, J.; Bonfert, J.P.

    1993-01-01

    Application of artificial intelligence (AI) computational techniques, such as expert systems, fuzzy logic, and neural networks in diverse areas has taken place extensively. In the nuclear industry, the intended goal for these AI techniques is to improve power plant operational safety and reliability. As a computerized operator support tool, the artificial neural network (ANN) approach is an emerging technology that currently attracts a large amount of interest. The ability of ANNs to extract the input/output relation of a complicated process and the superior execution speed of a trained ANN motivated this study. The goal was to develop neural networks for sensor and process faults diagnosis with the potential of implementing as a component of a real-time operator support system LYDIA, early sensor and process fault detection and diagnosis

  8. [The design and development of a quality system for the diagnosis of exotic animal diseases at the National Centre for Animal and Plant Health in Cuba].

    Science.gov (United States)

    de Oca, N Montes; Villoch, A; Pérez Ruano, M

    2004-12-01

    A quality system for the diagnosis of exotic animal diseases was developed at the national centre for animal and plant health (CENSA), responsible for coordinating the clinical, epizootiological and laboratory diagnosis of causal agents of exotic animal diseases in Cuba. A model was designed on the basis of standard ISO 9001:2000 of the International Organization for Standardization (ISO), standard ISO/IEC 17025:1999 of ISO and the International Electrotechnical Commission, recommendations of the World Organisation for Animal Health (OIE) and other regulatory documents from international and national organisations that deal specifically with the treatment of emerging diseases. Twenty-nine standardised operating procedures were developed, plus 13 registers and a checklist to facilitate the evaluation of the system. The effectiveness of the quality system was confirmed in the differential diagnosis of classical swine fever at an animal virology laboratory in Cuba.

  9. EnergiTools(R) - a power plant performance monitoring and diagnosis tool

    International Nuclear Information System (INIS)

    Ancion, P.V.; Bastien, R.; Ringdahl, K.

    2000-01-01

    Westinghouse EnergiTools(R) is a performance diagnostic tool for power generation plants that combines the power of on-line process data acquisition with advanced diagnostics methodologies. The system uses analytical models based on thermodynamic principles combined with knowledge of component diagnostic experts. An issue in modeling expert knowledge is to have a framework that can represent and process uncertainty in complex systems. In such experiments, it is nearly impossible to build deterministic models for the effects of faults on symptoms. A methodology based on causal probabilistic graphs, more specifically on Bayesian belief networks, has been implemented in EnergiTools(R) to capture the fault-symptom relationships. The methodology estimates the likelihood of the various component failures using the fault-symptom relationships. The system also has the ability to use neural networks for processes that are difficult to model analytically. An application is the estimation of the reactor power in nuclear power plant by interpreting several plant indicators. EnergiTools(R) is used for the on-line performance monitoring and diagnostics at Vattenfall Ringhals nuclear power plants in Sweden. It has led to the diagnosis of various performance issues with plant components. Two case studies are presented. In the first case, an overestimate of the thermal power due to a faulty instrument was found, which led to a plant operation below its optimal power. The paper shows how the problem was discovered, using the analytical thermodynamic calculations. The second case shows an application of EnergiTools(R) for the diagnostic of a condenser failure using causal probabilistic graphs

  10. A study on the development of a expert system for diagnosing fossil power plants

    International Nuclear Information System (INIS)

    Baik, Young Min; Jeong, Hee Don; Shin, Eun Ju

    2009-01-01

    In order to analyze the causes of fossil power plant facilities due to a degradation and corrosion, artificial degraded materials composed of the facilities were manufactured. Various experiment were performed based on mechanical test, microstructure observation, hardness test, Electrochemical Potentiokinetic Reactivation test (EPR) and corrosion scale thickness measurement test. The master curves were write out using Larson-Miller parameter to evaluate the degree of degradation with the above diagnosis methods. These data were applied to materials database of fossil power plant diagnosis. Finally expert system on the fossil power plant diagnosis was developed using the master curves and diagnosis algorithms.

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

    International Nuclear Information System (INIS)

    Kim, Dae Sik

    1993-02-01

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

  12. Nuclear power plant fault-diagnosis using artificial neural networks

    International Nuclear Information System (INIS)

    Kim, Keehoon; Aljundi, T.L.; Bartlett, E.B.

    1992-01-01

    Artificial neural networks (ANNs) have been applied to various fields due to their fault and noise tolerance and generalization characteristics. As an application to nuclear engineering, we apply neural networks to the early recognition of nuclear power plant operational transients. If a transient or accident occurs, the network will advise the plant operators in a timely manner. More importantly, we investigate the ability of the network to provide a measure of the confidence level in its diagnosis. In this research an ANN is trained to diagnose the status of the San Onofre Nuclear Generation Station using data obtained from the plant's training simulator. Stacked generalization is then applied to predict the error in the ANN diagnosis. The data used consisted of 10 scenarios that include typical design basis accidents as well as less severe transients. The results show that the trained network is capable of diagnosing all 10 instabilities as well as providing a measure of the level of confidence in its diagnoses

  13. A study on the systematic framework to develop an effective diagnosis procedure of the nuclear power plants

    International Nuclear Information System (INIS)

    Park, Jin Kyun; Jung, Won Dea; Kim, Jae Whan; Ha, Jae Joo

    2003-11-01

    In complex systems, the importance of the diagnosis procedures has been well recognized, since identifying the nature of the on-going event should be preceded to determine successful countermeasures or remedial actions. Unfortunately, a systematic framework that can suggest a unified and consistent process for constructing useful diagnosis procedures seems to be scant. In this paper, the systematic framework that can provide a sound way in constructing a diagnosis procedure is suggested based on two kinds of technical bases, such as the decision-making strategies of human and the test sequencing technique. In addition, to demonstrate the appropriateness of the suggested framework, the diagnosis procedure of the reference nuclear power plant is reformed based on it. Various kinds of activities have been conducted to compare the reformed diagnosis procedure with the original one, and the results indicate that the operators' performance in the event diagnosis can be improved, when they used the reformed procedure. Thus, it is expected that the suggested framework can be applied to give a consistent process in constructing a useful diagnosis procedure that can play an important role in enhancing safety of the nuclear power plants

  14. A Web-Based Rice Plant Expert System Using Rule-Based Reasoning

    Directory of Open Access Journals (Sweden)

    Anton Setiawan Honggowibowo

    2009-12-01

    Full Text Available Rice plants can be attacked by various kinds of diseases which are possible to be determined from their symptoms. However, it is to recognize that to find out the exact type of disease, an agricultural expert’s opinion is needed, meanwhile the numbers of agricultural experts are limited and there are too many problems to be solved at the same time. This makes a system with a capability as an expert is required. This system must contain the knowledge of the diseases and symptom of rice plants as an agricultural expert has to have. This research designs a web-based expert system using rule-based reasoning. The rule are modified from the method of forward chaining inference and backward chaining in order to to help farmers in the rice plant disease diagnosis. The web-based rice plants disease diagnosis expert system has the advantages to access and use easily. With web-based features inside, it is expected that the farmer can accesse the expert system everywhere to overcome the problem to diagnose rice diseases.

  15. An expert system approach for safety diagnosis

    International Nuclear Information System (INIS)

    Erdmann, R.C.; Sun, B.K.H.

    1988-01-01

    An expert system was developed with the intent to provide real-time information about an accident to an operator who is in the process of diagnosing and bringing that accident under control. Explicit use was made of probabilistic risk analysis techniques and plant accident response information in constructing this system. The expert system developed contains 70 logic rules and provides contextual messages during simulated accident sequences and logic sequence information on the entire sequence in graphical form for accident diagnosis. The present analysis focuses on integrated control system-related transients with Babcock and Wilcox-type reactors. While the system developed here is limited in extent and was built for a composite reactor, it demonstrates that an expert system may enhance the operator's capability in the control room

  16. Development of water chemistry diagnosis system for BWR primary loop

    International Nuclear Information System (INIS)

    Nagase, Makoto; Asakura, Yamato; Sakagami, Masaharu; Uchida, Shunsuke; Ohsumi, Katsumi.

    1988-01-01

    The prototype of a water chemistry diagnosis system for BWR primary loop has been developed. Its purposes are improvement of water chemistry control and reduction of the work burden on plant chemistry personnel. It has three main features as follows. (1) Intensifying the observation of water chemistry conditions by variable sampling intervals based on the on-line measured data. (2) Early detection of water chemistry data trends using a second order regression curve which is calculated from the measured data, and then searching the cause of anomaly if anything (3) Diagnosis of Fe concentration in feedwater using model simulations, in order to lower the radiation level in the primary system. (author)

  17. EXPERIMENT BASED FAULT DIAGNOSIS ON BOTTLE FILLING PLANT WITH LVQ ARTIFICIAL NEURAL NETWORK ALGORITHM

    Directory of Open Access Journals (Sweden)

    Mustafa DEMETGÜL

    2008-01-01

    Full Text Available In this study, an artificial neural network is developed to find an error rapidly on pneumatic system. Also the ANN prevents the system versus the failure. The error on the experimental bottle filling plant can be defined without any interference using analog values taken from pressure sensors and linear potentiometers. The sensors and potentiometers are placed on different places of the plant. Neural network diagnosis faults on plant, where no bottle, cap closing cylinder B is not working, bottle cap closing cylinder C is not working, air pressure is not sufficient, water is not filling and low air pressure faults. The fault is diagnosed by artificial neural network with LVQ. It is possible to find an failure by using normal programming or PLC. The reason offing Artificial Neural Network is to give a information where the fault is. However, ANN can be used for different systems. The aim is to find the fault by using ANN simultaneously. In this situation, the error taken place on the pneumatic system is collected by a data acquisition card. It is observed that the algorithm is very capable program for many industrial plants which have mechatronic systems.

  18. A quality control method by ultrasonic vibration energy and diagnosis system at trimming process

    International Nuclear Information System (INIS)

    Suh, Chang Min; Song, Gil Ho; Pyoun, Young Shik

    2007-01-01

    In this paper, the characteristics in mechanical properties of ultrasonic cold forging treatment (UCFT) used for the trimming knife and the effects of ultrasonic vibration energy (UVE) into the trimming process on the state of the strip cutting face were studied. And a diagnosis system to quality control for trimming knife and strip cutting face was developed and installed in plant. By the plant application of UCFT, service life of knife was more increased over 100% than that of conventional knife and using the developed diagnosis system, the knife breakage and saw ear have been perfectly detected and quality control of trimming face is effectively obtained

  19. Automatic fault diagnosis in PV systems with distributed MPPT

    International Nuclear Information System (INIS)

    Solórzano, J.; Egido, M.A.

    2013-01-01

    Highlights: • An automatic failure diagnosis procedure for PV systems with DMPPT is presented. • The different failures diagnosed and their effects on the PV systems are described. • No use of irradiance and temperature sensors decreasing the cost of the system. • Voltage and current analysis to diagnose different failures. • Hot-spots, localized dirt, shading, module degradation and cable losses diagnosis. - Abstract: This work presents a novel procedure for fault diagnosis in PV systems with distributed maximum power point tracking at module level—power optimizers (DC/DC) or micro-inverters (DC/AC). Apart from the power benefits obtained when an irregular irradiance distribution is present, this type of systems permit the monitoring of the PV plant parameters at the module level: voltage and current at the working power point. With these parameters, a prototype diagnosis tool has been developed in Matlab and it has been experimentally verified in a real rooftop PV generator by applying different failures. The tool can diagnose the following failures: fixed object shading (with distance estimation), localized dirt, generalized dirt, possible hot-spots, module degradation and excessive losses in DC cables. In addition, it alerts the user of the power losses produced by each failure and classifies the failures by their severity. This system does not require the use of irradiance or temperature sensors, except for the generalized dirt failure, reducing the cost of installation, especially important in small PV systems

  20. Automated Diagnosis and Control of Complex Systems

    Science.gov (United States)

    Kurien, James; Plaunt, Christian; Cannon, Howard; Shirley, Mark; Taylor, Will; Nayak, P.; Hudson, Benoit; Bachmann, Andrew; Brownston, Lee; Hayden, Sandra; hide

    2007-01-01

    Livingstone2 is a reusable, artificial intelligence (AI) software system designed to assist spacecraft, life support systems, chemical plants, or other complex systems by operating with minimal human supervision, even in the face of hardware failures or unexpected events. The software diagnoses the current state of the spacecraft or other system, and recommends commands or repair actions that will allow the system to continue operation. Livingstone2 is an enhancement of the Livingstone diagnosis system that was flight-tested onboard the Deep Space One spacecraft in 1999. This version tracks multiple diagnostic hypotheses, rather than just a single hypothesis as in the previous version. It is also able to revise diagnostic decisions made in the past when additional observations become available. In such cases, Livingstone might arrive at an incorrect hypothesis. Re-architecting and re-implementing the system in C++ has increased performance. Usability has been improved by creating a set of development tools that is closely integrated with the Livingstone2 engine. In addition to the core diagnosis engine, Livingstone2 includes a compiler that translates diagnostic models written in a Java-like language into Livingstone2's language, and a broad set of graphical tools for model development.

  1. Development of knowledge-based operator support system for steam generator water leak events in FBR plants

    International Nuclear Information System (INIS)

    Arikawa, Hiroshi; Ida, Toshio; Matsumoto, Hiroyuki; Kishida, Masako

    1991-01-01

    A knowledge engineering approach to operation support system would be useful in maintaining safe and steady operation in nuclear plants. This paper describes a knowledge-based operation support system which assists the operators during steam generator water leak events in FBR plants. We have developed a real-time expert system. The expert system adopts hierarchical knowledge representation corresponding to the 'plant abnormality model'. A technique of signal validation which uses knowledge of symptom propagation are applied to diagnosis. In order to verify the knowledge base concerning steam generator water leak events in FBR plants, a simulator is linked to the expert system. It is revealed that diagnosis based on 'plant abnormality model' and signal validation using knowledge of symptom propagation could work successfully. Also, it is suggested that the expert system could be useful in supporting FBR plants operations. (author)

  2. Numerical model for thermoeconomic diagnosis in commercial transcritical/subcritical booster refrigeration systems

    International Nuclear Information System (INIS)

    Ommen, Torben; Elmegaard, Brian

    2012-01-01

    Highlights: ► A transcritical booster refrigeration plant is modelled. ► We examine changes in cost flow at different operation parameters. ► The use of characteristic curves for diagnosis is studied. - Abstract: Transcritical/subcritical booster refrigeration systems are increasingly installed and used in Danish supermarkets. The systems operate in both transcritical and subcritical conditions dependent on the heat rejection performance and the ambient conditions. The plant consists of one refrigerant cycle supplying refrigerant for evaporators in both chilled and frozen display cases. In the paper, thermoeconomic theory is used to establish the cost of cooling at each individual temperature level based on operating costs. With a high amount of operating systems, faulty operation becomes an economic, and environmental, interest. A general solution for evaluation of these systems is considered, with the objective to reduce cost and power consumption of malfunctioning equipment in operation. An analysis of the use of thermoeconomic diagnosis methods is required, as these methods may prove applicable. To accommodate the analysis, a numerical model of a transcritical booster refrigeration plant is considered in this paper. Additionally the characteristic curves method is applied to the high pressure compressor unit of the refrigeration plant. The approach successfully determine whether an anomaly is intrinsic or induced in the component when no uncertainties are introduced in the steady state model.

  3. New technologies in nuclear power plant monitoring and diagnosis

    International Nuclear Information System (INIS)

    Turkcan, E.; Verhoef, J.P.; Ciftcioglu, O.

    1996-01-01

    Several representative new technologies being introduce for monitoring and diagnosis in nuclear power plants (NPP) are presented in this paper. In Sec. 2, the Kalman filtering is briefly described and it relevance to conventional time series analysis methods are emphasized. In this respect, its NPP monitoring and fault diagnosis implementations are given and the important features are pointed out. In Sec. 3, the NN technology is briefly described and the scope is focused on the NPP monitoring and fault diagnosis implementations. In Sec. 4, the wavelet technology is briefly described and the utilization of this technology in Nuclear Technology is exemplified. In this respect, also the prospective role of this technology for real-time monitoring and fault diagnosis is revealed. (author). 33 refs, 6 figs

  4. New technologies in nuclear power plant monitoring and diagnosis

    Energy Technology Data Exchange (ETDEWEB)

    Turkcan, E; Verhoef, J P [Netherlands Energy Research Foundation (ECN), Petten (Netherlands); Ciftcioglu, O [Istanbul Technical Univ., Istanbul (Turkey). Nuclear Power Dept.

    1997-12-31

    Several representative new technologies being introduce for monitoring and diagnosis in nuclear power plants (NPP) are presented in this paper. In Sec. 2, the Kalman filtering is briefly described and it relevance to conventional time series analysis methods are emphasized. In this respect, its NPP monitoring and fault diagnosis implementations are given and the important features are pointed out. In Sec. 3, the NN technology is briefly described and the scope is focused on the NPP monitoring and fault diagnosis implementations. In Sec. 4, the wavelet technology is briefly described and the utilization of this technology in Nuclear Technology is exemplified. In this respect, also the prospective role of this technology for real-time monitoring and fault diagnosis is revealed. (author). 33 refs, 6 figs.

  5. 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)

  6. Residual life of technical systems; diagnosis, prediction and life extension

    International Nuclear Information System (INIS)

    Reinertsen, Rune

    1996-01-01

    The paper presents and discusses research related to residual life of non-repairable and repairable technical systems. Diagnosis of systems and extension of residual life of technical systems are also presented and discussed. This paper concludes that research published describing determination and extension of residual life as well as methods for diagnosis of non-repairable and repairable technical systems, is somewhat limited. Many papers have a rather pragmatic approach. The authors only describe special cases from their own plant and do not provide any explanation of a more academical nature. The other papers are mainly describing very specific applications of statistical models, leaving the more general case out of consideration. One of the main results of this paper is to point out these facts, and thereby identify the need for future research in this area

  7. Accident diagnosis system based on real-time decision tree expert system

    Science.gov (United States)

    Nicolau, Andressa dos S.; Augusto, João P. da S. C.; Schirru, Roberto

    2017-06-01

    Safety is one of the most studied topics when referring to power stations. For that reason, sensors and alarms develop an important role in environmental and human protection. When abnormal event happens, it triggers a chain of alarms that must be, somehow, checked by the control room operators. In this case, diagnosis support system can help operators to accurately identify the possible root-cause of the problem in short time. In this article, we present a computational model of a generic diagnose support system based on artificial intelligence, that was applied on the dataset of two real power stations: Angra1 Nuclear Power Plant and Santo Antônio Hydroelectric Plant. The proposed system processes all the information logged in the sequence of events before a shutdown signal using the expert's knowledge inputted into an expert system indicating the chain of events, from the shutdown signal to its root-cause. The results of both applications showed that the support system is a potential tool to help the control room operators identify abnormal events, as accidents and consequently increase the safety.

  8. A fault diagnosis system for PV power station based on global partitioned gradually approximation method

    Science.gov (United States)

    Wang, S.; Zhang, X. N.; Gao, D. D.; Liu, H. X.; Ye, J.; Li, L. R.

    2016-08-01

    As the solar photovoltaic (PV) power is applied extensively, more attentions are paid to the maintenance and fault diagnosis of PV power plants. Based on analysis of the structure of PV power station, the global partitioned gradually approximation method is proposed as a fault diagnosis algorithm to determine and locate the fault of PV panels. The PV array is divided into 16x16 blocks and numbered. On the basis of modularly processing of the PV array, the current values of each block are analyzed. The mean current value of each block is used for calculating the fault weigh factor. The fault threshold is defined to determine the fault, and the shade is considered to reduce the probability of misjudgments. A fault diagnosis system is designed and implemented with LabVIEW. And it has some functions including the data realtime display, online check, statistics, real-time prediction and fault diagnosis. Through the data from PV plants, the algorithm is verified. The results show that the fault diagnosis results are accurate, and the system works well. The validity and the possibility of the system are verified by the results as well. The developed system will be benefit for the maintenance and management of large scale PV array.

  9. Criteria of diversity evaluation for intelligent diagnosis of nuclear power plants

    International Nuclear Information System (INIS)

    Washio, Takashi; Sakuma, Masatake; Furukawa, Hiroshi; Kitamura, Masaharu.

    1995-01-01

    One of important problems of a current operation support system for a nuclear power plant is that the credibility of its resultant suggestions is not always high sufficiently. The authors have proposed an efficient remedy called 'Diversity Criteria' for this issue in the previous works. It employs a variety of information resources and reasoning mechanisms for the system to enhance its entire credibility. Within this framework, a complementary combination of the resources and mechanisms is desired. The work presented here proposes systematic and quantitative measures determining the appropriate combinations. First, concrete and systematic guidelines are proposed for the detailed criteria of 'Information Diversity' and 'Methodology Diversity'. Next, two concepts of 'Orthogonality of Identified Result' and 'Orthogonality of Utilized Symptom' are presented together with their quantitative measures. These guidelines and measures have been applied to an example of failure diagnosis of a nuclear power plant, and their efficiency has been clearly confirmed. (author)

  10. General digitalized system on nuclear power plants

    International Nuclear Information System (INIS)

    Akagi, Katsumi; Kadohara, Hozumi; Taniguchi, Manabu

    2000-01-01

    Hitherto, instrumentation control system in a PWR nuclear power plant has stepwisely adopted digital technology such as application of digital instrumentation control device to ordinary use (primary/secondary system control device, and so on), application of CRT display system to monitoring function, and so forth, to realize load reduction of an operator due to expansion of operation automation range, upgrading of reliability and maintenance due to self-diagnosis function, reduction of mass in cables due to multiple transfer, and upgrading of visual recognition due to information integration. In next term PWR plant instrumentation control system, under consideration of application practice of conventional digital technology, application of general digitalisation system to adopt digitalisation of overall instrumentation control system containing safety protection system, and central instrumentation system (new type of instrumentation system) and to intend to further upgrade economics, maintenance, operability/monitoring under security of reliability/safety is planned. And, together with embodiment of construction program of the next-term plant, verification at the general digitalisation proto-system aiming at establishment of basic technology on the system is carried out. Then, here was described on abstract of the general digitalisation system and characteristics of a digital type safety protection apparatus to be adopted in the next-term plant. (G.K.)

  11. The development of an automatic classification system of nuclear power plant states

    International Nuclear Information System (INIS)

    Mitomo, Nobuo; Matsuoka, Takeshi

    2000-01-01

    For the future autonomous plant, automatic control and diagnostics are being incorporated and operators are mainly engaged in the high levels of diagnosis and decision-making in emergencies. Therefore these matters will be performed through the Man-Machine Interface(MMI). Ship Research Institute has been carrying out the research on the MMI system for autonomous power plants. The automatic classification system of plant states is one of the functions of this MMI and the system utilizes COBWEB, which is known as a way of clustering data to acquire concepts. In this paper, many plant states produced by a plant simulator we examined in order to confirm the effectiveness of this system. The system has well classified plant states produced by a plant simulator. (author)

  12. Diagnosis function of safety status in the safety parameter display system (SPDS)

    International Nuclear Information System (INIS)

    Zhang Yuanfang

    1993-04-01

    An automatic diagnosis function of safety status for nuclear power plant adopted in the SPDS is introduced. To guarantee diagnosis diversification, two diagnosis criteria of a design basis accident monitoring and a critical safety function monitoring used in plant emergency operation are provided. As an extensive function, a parameter deviation monitoring used in plant normal operation is also provided

  13. Incipient multiple fault diagnosis in real time with applications to large-scale systems

    International Nuclear Information System (INIS)

    Chung, H.Y.; Bien, Z.; Park, J.H.; Seon, P.H.

    1994-01-01

    By using a modified signed directed graph (SDG) together with the distributed artificial neutral networks and a knowledge-based system, a method of incipient multi-fault diagnosis is presented for large-scale physical systems with complex pipes and instrumentations such as valves, actuators, sensors, and controllers. The proposed method is designed so as to (1) make a real-time incipient fault diagnosis possible for large-scale systems, (2) perform the fault diagnosis not only in the steady-state case but also in the transient case as well by using a concept of fault propagation time, which is newly adopted in the SDG model, (3) provide with highly reliable diagnosis results and explanation capability of faults diagnosed as in an expert system, and (4) diagnose the pipe damage such as leaking, break, or throttling. This method is applied for diagnosis of a pressurizer in the Kori Nuclear Power Plant (NPP) unit 2 in Korea under a transient condition, and its result is reported to show satisfactory performance of the method for the incipient multi-fault diagnosis of such a large-scale system in a real-time manner

  14. Soft computing for fault diagnosis in power plants

    International Nuclear Information System (INIS)

    Ciftcioglu, O.; Turkcan, E.

    1998-01-01

    Considering the advancements in the AI technology, there arises a new concept known as soft computing. It can be defined as the processing of uncertain information with the AI methods, that refers to explicitly the methods using neural networks, fuzzy logic and evolutionary algorithms. In this respect, soft computing is a new dimension in information processing technology where linguistic information can also be processed in contrast with the classical stochastic and deterministic treatments of data. On one hand it can process uncertain/incomplete information and on the other hand it can deal with non-linearity of large-scale systems where uncertainty is particularly relevant with respect to linguistic information and incompleteness is related to fault tolerance in fault diagnosis. In this perspective, the potential role of soft computing in power plant operation is presented. (author)

  15. An artificial intelligence system for assisting nuclear power plant operators in the diagnosis of and response to plant faults and transients

    International Nuclear Information System (INIS)

    Hajek, B.K.; Stasenko, J.E.; Bhatnagar, R.; Hashemi, S.

    1987-12-01

    This report discusses the Artificial Intelligence (AI) system being developed using the Conceptual Structures and Representation Language (CSRL) developed at the Ohio State University Laboratory for Artificial Intelligence Research (LAIR). This system combines three sub-systems which have been independently developed to perform the tasks of: detecting changes in the state of the plant that may lead to conditions requiring operator response, and then managing the actions taken by the other two subsystems; diagnosing the plant status independent of alarm states by analyzing the status of basic operating parameters such as flow rates, pressures, temperatures, and water levels, and providing a determination of the validity of sensor indications; and providing and/or synthesizing an appropriate procedure for the operator to follow to correct the transient or abnormal state of the plant. These three systems are tied into the main plant computers, including both the process computer and the safety parameter and display system computer, through the use of a compatible database. The architecture of the system is shown in Figure 1. The system is being developed using the Perry Nuclear Power Plant (a BWR/6) as the reference plant, and the General Electric ERIS and GEPAC Plus systems as key data sources. Scenarios are run on the Perry plant referenced simulator for testing of the AI system. Future testing plans call for the system to be interfaced directly to the Perry simulator

  16. An artificial intelligence system for assisting nuclear power plant operators in the diagnosis of the response to plant faults and transients

    International Nuclear Information System (INIS)

    Hajek, B.K.

    1987-01-01

    An artificial intelligence system is being developed using the Conceptual Structures and Representation Language (CSRL) developed at The Ohio State University Laboratory for Artificial Intelligence Research (LAIR). This system combines three subsystems, which have been independently developed to perform the following tasks: (1) detecting changes in the state of the plant that may lead to conditions requiring operator response and then managing the actions taken by the other two subsystems, (2) diagnosing the plant status independent of alarm states by analyzing the status of basic operating parameters, such as flow rates, pressures, temperatures, and water levels, and providing a determination of the validity of sensor indications, and (3) providing and/or synthesizing an appropriate procedure for the operator to follow to correct the transient of abnormal state of the plant. These three system are tied into the main plant computers, including both the process computer and the safety parameter and display system computer, through the use of a compatible data base. The system is being developed using the Perry Nuclear Power Plant (a BWR/6) as the reference plant, and the General Electric ERIS and GEPAC Plus systems as key data sources. Scenarios are run on by the Perry plant referenced simulator for testing of the artificial intelligence system. Future testing plans call for the system to be interfaced directly to the Perry simulator

  17. A study on the applications of expert systems and neural networks for the development of operator support systems in nuclear power plants

    International Nuclear Information System (INIS)

    Cheon, Se Woo

    1993-02-01

    In order to assist operators in effectively maintaining plant safety and to enhance plant availability, the need to develop operator support systems is growing to increase. The application of both expert system and neural network technologies to the operator support has the potential to increase the performance of these systems. A prototype integrated operator support system, called NSSS-DS, has been developed for multiple alarm processing, plant trip diagnosis, and the failure diagnosis of three main systems (a rod control system, reactor coolant pumps (RCPs) and a pressurizer) in the primary side of the Kori-2 nuclear power plant. This system diagnoses system malfunction quickly and offers appropriate guidance to operators. The system uses rule-based deduction with certainty factor operation. Diagnosis is performed using an establish-refine inference strategy. This strategy is to match a set of symptoms with a specific malfunction hypothesis in a predetermined structure of possible hypotheses. The diagnostic symptoms include alarms, indication lamps, parameter values and valve lineup that can be acquired at a main control room. The overall plant-wide diagnosis is performed at the main control part which can process multiple alarms and diagnose possible failure modes and failed systems in the plant. The method of alarm processing is the object-oriented approach in which each alarm can be represented as an active data element, an object. The alarm processing is performed using alarm processing meta rules and alarm processing frames. Also, the diagnosis of a plant trip can be performed at the main control part. The specific diagnosis of the three main systems can be performed followed by the diagnostic results of the main control part. The system also provides follow-up treatments to the operators. The application to these systems is described from the point of view of diagnostic strategies. For the applications of the neural network technology, two feasibility

  18. Rough set theory and its application in fault diagnosis in Nuclear Power Plant

    International Nuclear Information System (INIS)

    Chen Zhihui; Nuclear Power Inst. of China, Chengdu; Xia Hong; Huang Wei

    2006-01-01

    Rough Set theory is the mathematic theory that can express and deal with vague and uncertain data. There is complicated and uncertain data in the fault feature of Nuclear Power Plant, so that Rough Set theory can be introduced to analyze and process the historical data to find out the rule of fault diagnosis of Nuclear Power Plant. This paper introduces the Rough Set theory and Knowledge Acquisition briefly, and describes the reduction algorithm based on discernibility matrix and its application in the fault diagnosis to generate rules of diagnosis. Using these rules, three kinds of model faults have been diagnosed correctly. The conclusion can be drawn that this method can reduce the redundancy of the fault feature, simplify and optimize the rule of diagnosis. (authors)

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

    International Nuclear Information System (INIS)

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

    2016-01-01

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

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2016-02-15

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

  1. Plant Pest Detection Using an Artificial Nose System: A Review.

    Science.gov (United States)

    Cui, Shaoqing; Ling, Peter; Zhu, Heping; Keener, Harold M

    2018-01-28

    This paper reviews artificial intelligent noses (or electronic noses) as a fast and noninvasive approach for the diagnosis of insects and diseases that attack vegetables and fruit trees. The particular focus is on bacterial, fungal, and viral infections, and insect damage. Volatile organic compounds (VOCs) emitted from plants, which provide functional information about the plant's growth, defense, and health status, allow for the possibility of using noninvasive detection to monitor plants status. Electronic noses are comprised of a sensor array, signal conditioning circuit, and pattern recognition algorithms. Compared with traditional gas chromatography-mass spectrometry (GC-MS) techniques, electronic noses are noninvasive and can be a rapid, cost-effective option for several applications. However, using electronic noses for plant pest diagnosis is still in its early stages, and there are challenges regarding sensor performance, sampling and detection in open areas, and scaling up measurements. This review paper introduces each element of electronic nose systems, especially commonly used sensors and pattern recognition methods, along with their advantages and limitations. It includes a comprehensive comparison and summary of applications, possible challenges, and potential improvements of electronic nose systems for different plant pest diagnoses.

  2. Nuclear power plant monitoring and fault diagnosis methods based on the artificial intelligence technique

    International Nuclear Information System (INIS)

    Yoshikawa, S.; Saiki, A.; Ugolini, D.; Ozawa, K.

    1996-01-01

    The main objective of this paper is to develop an advanced diagnosis system based on the artificial intelligence technique to monitor the operation and to improve the operational safety of nuclear power plants. Three different methods have been elaborated in this study: an artificial neural network local diagnosis (NN ds ) scheme that acting at the component level discriminates between normal and abnormal transients, a model-based diagnostic reasoning mechanism that combines a physical causal network model-based knowledge compiler (KC) that generates applicable diagnostic rules from widely accepted physical knowledge compiler (KC) that generates applicable diagnostic rules from widely accepted physical knowledge. Although the three methods have been developed and verified independently, they are highly correlated and, when connected together, form a effective and robust diagnosis and monitoring tool. (authors)

  3. On-line surveillance system for Borssele nuclear power plant monitoring and diagnostics

    International Nuclear Information System (INIS)

    Tuerkcan, E.; Ciftcioglu, Oe.

    1993-08-01

    An operating on-line surveillance and diagnostic system is described where information processing for monitoring and fault diagnosis and plant maintenance are addressed. The surveillance system by means of its realtime multiprocessing, multitasking execution capabilities can perform plant-wide and wide-range monitoring for enhanced plant safety and operational reliability as well as enhanced maintenance. At the same time the system provides the possibilities for goal-oriented research and development such as estimation, filtering, verification and validation and neural networks. (orig./HP)

  4. Nuclear power plant pressurizer fault diagnosis using fuzzy signed-digraph method

    International Nuclear Information System (INIS)

    Park, Joo Hyun; Seong, Poong Hyun

    2004-01-01

    In this study, The Fuzzy Signed Digraph method which has been researched and applied to the chemical process is improved and applied to the fault diagnosis of the pressurizer in nuclear power plants. The Fuzzy Signed-Digraph (FSD) is the method which applies the fuzzy number to the Signed-Digraph (SDG) method. The current SDG methods have many merits as follows: (1) SDG method can directly use the value of sensors not the alarm to the fault diagnosis. (2) This method can diagnose the fault independent on the pattern. (3) This method can diagnose the faults fastly because the method uses the cause-effect relation instead of the complex control equation among the variables. But, they are not proper to be applied to the diagnosis of the multi-faults and to diagnose faults on real time. It is because the unmeasured nodes in those methods must be connected to each other in order to find out the single fault under the single-fault assumption. These methods need long CPU time and cannot be applied to the multi-faults diagnosis. We propose a method in which the values of the unmeasured nodes are calculated from the relations between the unmeasured nodes and the measured nodes. By using this method, the CPU time for diagnosis can be reduced. This CPU time reduction makes the real-time diagnosis possible. This method can also be applied for the multi-faults diagnosis. This method is applied to the diagnosis of the pressurizer of the nuclear power plant KORI-2 in Korea. (author)

  5. A qualitative diagnosis method for a continuous process monitor system

    International Nuclear Information System (INIS)

    Lucas, B.; Evrard, J.M.; Lorre, J.P.

    1993-01-01

    SEXTANT, an expert system for the analysis of transients, was built initially to study physical transients in nuclear reactors. It combines several knowledge bases concerning measurements, models and qualitative behavior of the plant with a generate-and-test mechanism and a set of numerical models of the physical process. The integration of an improved diagnosis method using a mixed model in SEXTANT in order to take into account the existence and the reliability of only a few number of sensors, the knowledge on failure and the possibility of non anticipated failures, is presented. This diagnosis method is based on two complementary qualitative models of the process and a methodology to build these models from a system description. 8 figs., 17 refs

  6. Development of condition monitoring and diagnosis system for standby diesel generator

    Energy Technology Data Exchange (ETDEWEB)

    Choi, Kwang Hee; Park, Jong Hyuck; Park, Jong Eun [Korea Electric Power Research Institute, Daejeon (Korea, Republic of)

    2009-05-15

    The emergency diesel generator (EDG) of the nuclear power plant is designed to supply the power to the nuclear on Station Black Out (SBO) condition. The operation reliability of onsite emergency diesel generator should be ensured by a condition monitoring system designed to monitor and analysis the condition of diesel generator. For this purpose, we have developed the online condition monitoring and diagnosis system for the wolsong unit 3 and 4 standby diesel generator including diesel engine performance. In this paper, technologies of condition monitoring and diagnosis system (SDG MDS) for the wolsong standby diesel generator are described. By using the condition monitoring module of the SDG MDS, performance monitoring function for major operating parameters of EDG reliability program required by Reg. guide 1.155 can be operated as on line monitoring system.

  7. Development of condition monitoring and diagnosis system for standby diesel generator

    International Nuclear Information System (INIS)

    Choi, Kwang Hee; Park, Jong Hyuck; Park, Jong Eun

    2009-01-01

    The emergency diesel generator (EDG) of the nuclear power plant is designed to supply the power to the nuclear on Station Black Out (SBO) condition. The operation reliability of onsite emergency diesel generator should be ensured by a condition monitoring system designed to monitor and analysis the condition of diesel generator. For this purpose, we have developed the online condition monitoring and diagnosis system for the wolsong unit 3 and 4 standby diesel generator including diesel engine performance. In this paper, technologies of condition monitoring and diagnosis system (SDG MDS) for the wolsong standby diesel generator are described. By using the condition monitoring module of the SDG MDS, performance monitoring function for major operating parameters of EDG reliability program required by Reg. guide 1.155 can be operated as on line monitoring system

  8. Development of failure diagnosis method based on transient information of nuclear power plant

    International Nuclear Information System (INIS)

    Washio, Takashi; Kitamura, Masaharu; Sugiyama, Kazusuke

    1987-01-01

    This paper proposes a new method of failure diagnosis of nuclear power plant (NPP). Transient behavior of the NPP includes ample failure information even for a limited period of time from the failure onset. We tried to develop a diagnosis system with high capability of identifying the failure cause and of estimating failure severeness. The Walsh function transformation of transient time series data and the reduction of the Walsh coefficients into ternary valued amplitude indicators were utilized to extract the essential characteristics of failure. The correspondences of the transient characteristics and causes were summarized in a failure symptom database. A method of ternary tree search using an information measure as a heuristic strategy was adopted to conduct the efficient retrieval of failure causes in the database. Through numerical experiments using a simulation model of a NPP, the diagnostic capability of the system was proved to be satisfactory. (author)

  9. Artificial Intelligence application to surveillance and diagnosis of nuclear power plants

    International Nuclear Information System (INIS)

    Brunet, E.; Monnier, B.; Zwingelstein, G.

    1986-01-01

    Acquisition and representation of knowledge are fundamental problems in Aritificial Intellegence and especially in expert system domain. In this article, the authors propose a conceptual model allowing to describe the universe the expert is working on when trying to make a diagnosis. The expert determines the descriptors and predicates with which he describes laws, states, objects involved in his reasoning. With this model, they are presenting design and development of Knowledge Acquisition Module allowing a dialogue in a specialized natural language used by the expert system to assist in the detection of loose parts in nuclear power plants. Using a classical lexical and syntactic analysis, they propose to associate grammatical semantic properties to the specialized language words. The method used allows the design of a sub expert system for understanding of the specialized natural language

  10. On the Analysis and Fault-Diagnosis Tools for Small-Scale Heat and Power Plants

    Energy Technology Data Exchange (ETDEWEB)

    Arriagada, Jaime

    2003-12-01

    been applied to different case studies in this thesis, either alone or in conjunction with heat and mass balance programs (HMBPs) -the state-of-the-art tool in the field today. This thesis presents both theoretical and experimental case studies which have been validated with data from simulations and real plants, respectively. The studied tasks include design, optimization, system identification, and fault diagnosis of small- and medium-size heat and power plants. Some results of these case studies are powerful hybrid models that speed up calculations and fault diagnosis systems capable of recognizing developing faults and delivering early warnings to the plant operator.

  11. Fuzzy logic utilization for the diagnosis of metallic loose part impact in nuclear power plant

    International Nuclear Information System (INIS)

    Oh, Y.-G.; Hong, H.-P.; Han, S.-J.; Chun, C.S.; Kim, B.-K.

    1996-01-01

    In consideration of the fuzzy nature of impact signals detected from the complex mechanical structures in a nuclear power plant under operation. Loose Part Monitoring System with a signal processing technique utilizing fuzzy logic is proposed. In the proposed Fuzzy Loose Part Monitoring System design, comprehensive relations among the impact signal features are taken into account in the fuzzy rule bases for the alarm discrimination and impact event diagnosis. Through the performance test with a mock-up facility, the proposed approach for the loose parts monitoring and diagnosis has been revealed to be effective not only in suppressing the false alarm generation but also in characterizing the metallic loose-part impact event, from the points of Possible Impacted-Area and Degree of Impact Magnitude

  12. Transient Diagnosis and Prognosis for Secondary System in Nuclear Power Plants

    Directory of Open Access Journals (Sweden)

    Sangjun Park

    2016-10-01

    Full Text Available This paper introduces the development of a transient monitoring system to detect the early stage of a transient, to identify the type of the transient scenario, and to inform an operator with the remaining time to turbine trip when there is no operator's relevant control. This study focused on the transients originating from a secondary system in nuclear power plants (NPPs, because the secondary system was recognized to be a more dominant factor to make unplanned turbine-generator trips which can ultimately result in reactor trips. In order to make the proposed methodology practical forward, all the transient scenarios registered in a simulator of a 1,000 MWe pressurized water reactor were archived in the transient pattern database. The transient patterns show plant behavior until turbine-generator trip when there is no operator's intervention. Meanwhile, the operating data periodically captured from a plant computer is compared with an individual transient pattern in the database and a highly matched section among the transient patterns enables isolation of the type of transient and prediction of the expected remaining time to trip. The transient pattern database consists of hundreds of variables, so it is difficult to speedily compare patterns and to draw a conclusion in a timely manner. The transient pattern database and the operating data are, therefore, converted into a smaller dimension using the principal component analysis (PCA. This paper describes the process of constructing the transient pattern database, dealing with principal components, and optimizing similarity measures.

  13. Simulation of a PWR power plant for process control and diagnosis

    International Nuclear Information System (INIS)

    Ravnsbjerg Nielsen, F.

    1991-12-01

    A computer model of a simplified pressurized nuclear power plant is developed with aim at studies concerning process control, diagnosis and decision making. The model includes the traditional PWR plant components, primary circuit with reactor, pressurizer and steam generator, steam circuit with steam line, turbine and condenser, interconnected with pumps, valves and controllers. The model can be used for calculation of transients for both normal operation and incidents such as turbine trip, loss of feedwater, run down of pumps or various valve failures. The computer model is not directed to any specific existing plant. For convenience and alleviation in implementation the physical description of many components are simplified to an extent where the qualitative behavior of the system is not violated. For computer memory economy a variety of thermodynamical functions for water and steam have been approximated with analytical expressions based on table values. The model is implemented in the C language and has been run on both the IBM PC and the SUN workstation. (au) 8 tabs., 25 ills., 10 refs

  14. A study on the systematic framework to develop effective diagnosis procedures of nuclear power plants

    International Nuclear Information System (INIS)

    Park, Jinkyun; Jung, Wondea

    2004-01-01

    In complex systems such as the nuclear and chemical industry, the importance of a diagnosis procedure has been well recognized, since identifying the nature of an on-going event should be preceded to determine successful countermeasures or remedial actions. Unfortunately, a systematic framework that can suggest a unified and consistent process for constructing useful diagnosis procedures seems to be scant. In this paper, the systematic framework that can provide a sound way in constructing a diagnosis procedure is suggested based on two kinds of technical bases, such as the decision-making strategies of human and the test sequencing technique. To demonstrate the appropriateness of suggested framework, the diagnosis procedure of the reference nuclear power plant is reformed based on it. Subjective ratings are conducted to compare reformed procedure with the original one, and results support that operators' performance in an event diagnosis could be improved. Thus, although well designed experiments are needed to draw a reliable conclusion, it is expected that suggested framework could be applied to provide a consistent process in constructing useful diagnosis procedures

  15. Fast diagnosis and treatment of cracklike defect injuriousness in PWR power plant equipment

    International Nuclear Information System (INIS)

    Benchimol, M.; Boneh, B.; Gilles, P.

    1983-08-01

    Defects detected in nuclear power plant components in the course of periodic inspections may have been formed during fabrication, at installation or in service. In order to accelerate decision-making subsequent to defect detection and increase the effectiveness of inspection programs, it is proposed in this paper that a package be prepared for each main system at the design stage to permit immediate diagnosis of defect injuriousness and to offer guidelines for mitigating action. The paper comprises: description of such a package, hereafter referred to as ''Defect Injuriousness Diagnosis and Treatment Package'' (DIDTP); breakdown of a DIDTP and demonstration of the computational methods used in its elaboration; presentation of the computer codes (ANODE, TITAN) used for automatic compilation of DIDTP's; example of DIDTP application

  16. Alpha Stable Distribution Based Morphological Filter for Bearing and Gear Fault Diagnosis in Nuclear Power Plant

    Directory of Open Access Journals (Sweden)

    Xinghui Zhang

    2015-01-01

    Full Text Available Gear and bearing play an important role as key components of rotating machinery power transmission systems in nuclear power plants. Their state conditions are very important for safety and normal operation of entire nuclear power plant. Vibration based condition monitoring is more complicated for the gear and bearing of planetary gearbox than those of fixed-axis gearbox. Many theoretical and engineering challenges in planetary gearbox fault diagnosis have not yet been resolved which are of great importance for nuclear power plants. A detailed vibration condition monitoring review of planetary gearbox used in nuclear power plants is conducted in this paper. A new fault diagnosis method of planetary gearbox gears is proposed. Bearing fault data, bearing simulation data, and gear fault data are used to test the new method. Signals preprocessed using dilation-erosion gradient filter and fast Fourier transform for fault information extraction. The length of structuring element (SE of dilation-erosion gradient filter is optimized by alpha stable distribution. Method experimental verification confirmed that parameter alpha is superior compared to kurtosis since it can reflect the form of entire signal and it cannot be influenced by noise similar to impulse.

  17. Development of nuclear power plant diagnosis technique using neural networks

    International Nuclear Information System (INIS)

    Horiguchi, Masahiro; Fukawa, Naohiro; Nishimura, Kazuo

    1991-01-01

    A nuclear power plant diagnosis technique has been developed, called transient phenomena analysis, which employs neural network. The neural networks identify malfunctioning equipment by recognizing the pattern of main plant parameters, making it possible to locate the cause of an abnormality when a plant is in a transient state. In a case where some piece of equipment shows abnormal behavior, many plant parameters either directly or indirectly related to that equipment change simultaneously. When an abrupt change in a plant parameter is detected, changes in the 49 main plant parameters are classified into three types and a characteristic change pattern consisting of 49 data is defined. The neural networks then judge the cause of the abnormality from this pattern. This neural-network-based technique can recognize 100 patterns that are characterized by the causes of plant abnormality. (author)

  18. Hydraulic Power Plant Machine Dynamic Diagnosis

    Directory of Open Access Journals (Sweden)

    Hans Günther Poll

    2006-01-01

    Full Text Available A method how to perform an entire structural and hydraulic diagnosis of prototype Francis power machines is presented and discussed in this report. Machine diagnosis of Francis units consists on a proper evaluation of acquired mechanical, thermal and hydraulic data obtained in different operating conditions of several rotary and non rotary machine components. Many different physical quantities of a Francis machine such as pressure, strains, vibration related data, water flow, air flow, position of regulating devices and displacements are measured in a synchronized way so that a relation of cause an effect can be developed for each operating condition and help one to understand all phenomena that are involved with such kind of machine. This amount of data needs to be adequately post processed in order to allow correct interpretation of the machine dynamics and finally these data must be compared with the expected calculated data not only to fine tuning the calculation methods but also to accomplish fully understanding of the influence of the water passages on such machines. The way how the power plant owner has to operate its Francis machines, many times also determined by a central dispatcher, has a high influence on the fatigue life time of the machine components. The diagnostic method presented in this report helps one to understand the importance of adequate operation to allow a low maintenance cost for the entire power plant. The method how to acquire these quantities is discussed in details together with the importance of correct sensor balancing, calibration and adequate correlation with the physical quantities. Typical results of the dynamic machine behavior, with adequate interpretation, obtained in recent measurement campaigns of some important hydraulic turbines were presented. The paper highlights the investigation focus of the hydraulic machine behavior and how to tailor the measurement strategy to accomplish all goals. Finally some

  19. Integration of artificial intelligence systems for nuclear power plants surveillance and diagnostics

    International Nuclear Information System (INIS)

    Chetry, Moon K.

    2012-01-01

    The objective of this program is to design, construct operate, test, and evaluate a prototype integrated monitoring and diagnostic system for a nuclear power plant. It is anticipated that this technology will have wide application to other complex systems (e.g., fossil power plants, chemical processing plants, and possibly air traffic control systems). Over the past decade, the University of Tennessee (UT) and others have carried out many projects utilizing various methodologies of artificial intelligence (expert systems, neural networks, fuzzy systems and genetic algorithms) to enhance the performance (safety, efficiency, reliability, and availability) of nuclear power plants. Investigations and studies have included a) instrumentation surveillance and calibration validation, b) inferential sensing to calibration of feed water venture flow during fouling, c) thermodynamic performance modeling with iterative improvement of plant heat rate, d) diagnosis of nuclear power plant transients

  20. Plant Pest Detection Using an Artificial Nose System: A Review

    Directory of Open Access Journals (Sweden)

    Shaoqing Cui

    2018-01-01

    Full Text Available This paper reviews artificial intelligent noses (or electronic noses as a fast and noninvasive approach for the diagnosis of insects and diseases that attack vegetables and fruit trees. The particular focus is on bacterial, fungal, and viral infections, and insect damage. Volatile organic compounds (VOCs emitted from plants, which provide functional information about the plant’s growth, defense, and health status, allow for the possibility of using noninvasive detection to monitor plants status. Electronic noses are comprised of a sensor array, signal conditioning circuit, and pattern recognition algorithms. Compared with traditional gas chromatography–mass spectrometry (GC-MS techniques, electronic noses are noninvasive and can be a rapid, cost-effective option for several applications. However, using electronic noses for plant pest diagnosis is still in its early stages, and there are challenges regarding sensor performance, sampling and detection in open areas, and scaling up measurements. This review paper introduces each element of electronic nose systems, especially commonly used sensors and pattern recognition methods, along with their advantages and limitations. It includes a comprehensive comparison and summary of applications, possible challenges, and potential improvements of electronic nose systems for different plant pest diagnoses.

  1. Model-Based Sensor Placement for Component Condition Monitoring and Fault Diagnosis in Fossil Energy Systems

    Energy Technology Data Exchange (ETDEWEB)

    Mobed, Parham [Texas Tech Univ., Lubbock, TX (United States); Pednekar, Pratik [West Virginia Univ., Morgantown, WV (United States); Bhattacharyya, Debangsu [West Virginia Univ., Morgantown, WV (United States); Turton, Richard [West Virginia Univ., Morgantown, WV (United States); Rengaswamy, Raghunathan [Texas Tech Univ., Lubbock, TX (United States)

    2016-01-29

    Design and operation of energy producing, near “zero-emission” coal plants has become a national imperative. This report on model-based sensor placement describes a transformative two-tier approach to identify the optimum placement, number, and type of sensors for condition monitoring and fault diagnosis in fossil energy system operations. The algorithms are tested on a high fidelity model of the integrated gasification combined cycle (IGCC) plant. For a condition monitoring network, whether equipment should be considered at a unit level or a systems level depends upon the criticality of the process equipment, its likeliness to fail, and the level of resolution desired for any specific failure. Because of the presence of a high fidelity model at the unit level, a sensor network can be designed to monitor the spatial profile of the states and estimate fault severity levels. In an IGCC plant, besides the gasifier, the sour water gas shift (WGS) reactor plays an important role. In view of this, condition monitoring of the sour WGS reactor is considered at the unit level, while a detailed plant-wide model of gasification island, including sour WGS reactor and the Selexol process, is considered for fault diagnosis at the system-level. Finally, the developed algorithms unify the two levels and identifies an optimal sensor network that maximizes the effectiveness of the overall system-level fault diagnosis and component-level condition monitoring. This work could have a major impact on the design and operation of future fossil energy plants, particularly at the grassroots level where the sensor network is yet to be identified. In addition, the same algorithms developed in this report can be further enhanced to be used in retrofits, where the objectives could be upgrade (addition of more sensors) and relocation of existing sensors.

  2. Technical diagnosis of industrial plants with radioisotopes

    International Nuclear Information System (INIS)

    Hartmann, G.

    1984-01-01

    A survey is given of the application of radioisotopes in technical diagnosis of industrial plants. Proceeding from the economic importance and the state of the art of radioisotope applications, the principles of tracer techniques are outlined including topical examples of application such as passage of coal through a steam generator, wear in impact crashing of coal, wear and corrosion in pipelines, testing the effective cross section of pipes, and investigations of microstructures. Limits and restrictions of applications are briefly discussed

  3. An operator support system for research reactor operations and fault diagnosis through a connectionist framework and PSA based knowledge based systems

    International Nuclear Information System (INIS)

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

    1998-01-01

    During reactor upset/abnormal conditions, emphasis is placed on the plant operator's ability to quickly identify the problem and perform diagnosis and initiate recovery action to ensure the safety of the plant. However, the reliability of human action is adversely affected at the time of crisis due to time stress and psychological factors. The availability of operational aids capable of monitoring the status of the plant and quickly identifying the deviation from normal operation is expected to significantly improve the operator reliability. The development of operator support systems using probabilistic safety assessment (PSA) techniques and information is finding wide application in nuclear plant operation. Often it is observed that most of the applications use a rule-based approach for diagnosis as well as safety status/transient conditions monitoring. A more efficient approach using artificial neural networks for safety status/transient condition monitoring and rule-based systems for diagnosis and emergency procedure generation has been applied for the development of a prototype operator adviser (OPAD) system for a 100 MW(th) heavy water moderated, cooled and natural uranium fueled research reactor. The development objective of this system is to improve the reliability of operator action and hence the reactor safety at the time of crisis as well as in normal operation. In order to address safety objectives at various stages of development of OPAD, the PSA techniques and tools have been used for knowledge representation. It has been demonstrated, with recall tests on the artificial neural network, that it can efficiently identify the reactor status in real-time scenario. This paper discusses various issues related to the development of an operator support system in a comprehensive way, right from the study of safety objectives, to data collection, to implementation of such a system

  4. Knowledge-based diagnosis for aerospace systems

    Science.gov (United States)

    Atkinson, David J.

    1988-01-01

    The need for automated diagnosis in aerospace systems and the approach of using knowledge-based systems are examined. Research issues in knowledge-based diagnosis which are important for aerospace applications are treated along with a review of recent relevant research developments in Artificial Intelligence. The design and operation of some existing knowledge-based diagnosis systems are described. The systems described and compared include the LES expert system for liquid oxygen loading at NASA Kennedy Space Center, the FAITH diagnosis system developed at the Jet Propulsion Laboratory, the PES procedural expert system developed at SRI International, the CSRL approach developed at Ohio State University, the StarPlan system developed by Ford Aerospace, the IDM integrated diagnostic model, and the DRAPhys diagnostic system developed at NASA Langley Research Center.

  5. New technologies in nuclear power plant monitoring and diagnosis

    International Nuclear Information System (INIS)

    Tuerkcan, E.; Ciftcioglu, Oe.

    1996-05-01

    The content of the present paper is as follows. In Sec. 2, the Kalman filtering is briefly described and its relevance to conventional time series analysis methods has been emphasized. In this respect, its NPP monitoring and fault diagnosis implementations are given and the important features are pointed out. In Sec. 3, the NN technology is briefly described and the scope is focused on the NPP monitoring and fault diagnosis implementations. The potentialities of this technology are pointed out. In Sec. 4, the wavelet technology is briefly described and the utilization of this technology in Nuclear Technology is demonstrated. In this respect, also the prospective role of this technology for real-time monitoring and fault diagnosis is revealed. Finally, the influence of the new technologies in reliable and cost effective plant operation viewpoint is discussed. (orig./WL)

  6. Experimental study on the operators' cognitive behavior analysis for the plant anomaly diagnosis

    International Nuclear Information System (INIS)

    Takahashi, Makoto; Kubo, Osamu; Yasuta, Akira

    1996-01-01

    In this paper, a method of human cognitive state estimation based on physiological measures has been applied to the analysis of cognitive behavior during anomaly diagnosis observed with nuclear power plant simulator. This method has also been combined with the conventional experimental protocol such as operational sequence and questionnaire results. The simulator experiments have been performed using plant experts and the results demonstrate that the cognitive state estimation method can be an effective way for understanding cognitive behavior during the anomaly diagnosis of the nuclear power plant. It has also been shown from the results that the combined use of the human cognitive state estimation and the conventional experimental protocol can provide effective information in decreasing the ambiguity of the analysis results. (author)

  7. PEM Fuel Cells with Bio-Ethanol Processor Systems A Multidisciplinary Study of Modelling, Simulation, Fault Diagnosis and Advanced Control

    CERN Document Server

    Feroldi, Diego; Outbib, Rachid

    2012-01-01

    An apparently appropriate control scheme for PEM fuel cells may actually lead to an inoperable plant when it is connected to other unit operations in a process with recycle streams and energy integration. PEM Fuel Cells with Bio-Ethanol Processor Systems presents a control system design that provides basic regulation of the hydrogen production process with PEM fuel cells. It then goes on to construct a fault diagnosis system to improve plant safety above this control structure. PEM Fuel Cells with Bio-Ethanol Processor Systems is divided into two parts: the first covers fuel cells and the second discusses plants for hydrogen production from bio-ethanol to feed PEM fuel cells. Both parts give detailed analyses of modeling, simulation, advanced control, and fault diagnosis. They give an extensive, in-depth discussion of the problems that can occur in fuel cell systems and propose a way to control these systems through advanced control algorithms. A significant part of the book is also given over to computer-aid...

  8. New expert system approach for the design of a diagnosis tool in a production plant

    Science.gov (United States)

    Mouss, H.; Mouss, D.; Scholz Reiter, B.

    2001-10-01

    The search for an increase in quality and speed of the diagnosis led to the reduction in the unavailability times of the production equipment. Thus, among the objectives of this study, need for operating on the level of the industrial sector of production through making of tools of assistance to the diagnosis of the abnormal operations, which are integrated into the environment of the system and allow the optimization of intervention times.

  9. Discrete event systems diagnosis and diagnosability

    CERN Document Server

    Sayed-Mouchaweh, Moamar

    2014-01-01

    Discrete Event Systems: Diagnosis and Diagnosability addresses the problem of fault diagnosis of Discrete Event Systems (DES). This book provides the basic techniques and approaches necessary for the design of an efficient fault diagnosis system for a wide range of modern engineering applications. The different techniques and approaches are classified according to several criteria such as: modeling tools (Automata, Petri nets) that is used to construct the model; the information (qualitative based on events occurrences and/or states outputs, quantitative based on signal processing and data analysis) that is needed to analyze and achieve the diagnosis; the decision structure (centralized, decentralized) that is required to achieve the diagnosis. The goal of this classification is to select the efficient method to achieve the fault diagnosis according to the application constraints. This book focuses on the centralized and decentralized event based diagnosis approaches using formal language and automata as mode...

  10. The UP3-UP2 800 reprocessing plants control systems. Use of tools for the diagnosis, the track of control softwares and the management of technical data

    International Nuclear Information System (INIS)

    Chabert, J.; Michon, J.C.

    1995-01-01

    After a rapid presentation of control systems architectures of the La Hague COGEMA reprocessing plants, details are given about the tools used to master the control and instrumentation softwares and technical data. The paper focusses more particularly on the CML (Software Maintenance Center) tool which manages the software versions installed on the driving system, on the SYDDEX tool devoted to the management of the control and instrumentation associated data and documents, and on the SAD tool used for diagnosis assistance. (J.S.). 5 figs

  11. 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

  12. Systems with artificial intelligence in nuclear power plant operation

    International Nuclear Information System (INIS)

    Bastl, W.; Felkel, L.

    1989-01-01

    The authors first summarize some developments made by GRS teams which can be regarded as the precursors of systems with artificial intelligence, and explain the basic characteristics of artificial intelligence, referring in particular to possible applications in nuclear engineering. The systems described are arranged in four groups according to applicability as follows: plant diagnosis and failure analysis, information systems and operating systems, control systems, assessment and decision aids. The working principle of the systems is explained by some examples giving details of the database and the interference processes. (orig./DG) [de

  13. Design characteristics of safety parameter display system for nuclear power plants

    International Nuclear Information System (INIS)

    Zhang Yuangfang

    1992-02-01

    The design features of safety parameter display system (SPDS) developed by Tsinghua University is introduced. Some new features have been added into the system functions and they are: (1) hierarchical display structure; (2) human factor in the display format design; (3)automatic diagnosis of safety status of nuclear power plant; (4) extension of SPDS use scope; (5) flexible hardware structure. The new approaches in the design are: (1)adopting the international design standards; (2) selecting safety parameters strictly; (3) developing software under multitask operating system; (4) using a nuclear power plant simulator to verify the SPDS design

  14. Integration of artificial intelligence systems for nuclear power plant surveillance and diagnostics

    International Nuclear Information System (INIS)

    Uhrig, R.E.; Hines, J.W.; Nelson, W.R.

    1998-01-01

    The objective of this program is to design, construct, operate, test, and evaluate a prototype integrated monitoring and diagnostic system for a nuclear power plant. It is anticipated that this technology will have wide application to other complex systems (e.g., fossil power plants, chemical processing plants, and possibly air traffic control systems). Over the past decade, the University of Tennessee (UT) and others have carried out many projects utilizing various methodologies of artificial intelligence (expert systems, neural networks, fuzzy systems, and genetic algorithms) to enhance the performance (safety, efficiency, reliability, and availability) of nuclear power plants. Investigations and studies have included a) instrumentation surveillance and calibration validation, b) inferential sensing to calibration of feedwater venturi flow during fouling, c) thermodynamic performance modeling with iterative improvement of plant beat rate, d) diagnosis of nuclear power plant transients, and e) increase in thermal power through monitoring of DNBR (Departure from Nucleate Boiling Regime). To increase the likelihood of these individual systems being used in a nuclear power plant, they must be integrated into a single system that operates virtually autonomously, collecting, interpreting, and providing information to the operators in a simple and understandable format. (author)

  15. Integration of artificial intelligence systems for nuclear power plant surveillance and diagnostics

    Energy Technology Data Exchange (ETDEWEB)

    Uhrig, R.E.; Hines, J.W.; Nelson, W.R.

    1998-07-01

    The objective of this program is to design, construct, operate, test, and evaluate a prototype integrated monitoring and diagnostic system for a nuclear power plant. It is anticipated that this technology will have wide application to other complex systems (e.g., fossil power plants, chemical processing plants, and possibly air traffic control systems). Over the past decade, the University of Tennessee (UT) and others have carried out many projects utilizing various methodologies of artificial intelligence (expert systems, neural networks, fuzzy systems, and genetic algorithms) to enhance the performance (safety, efficiency, reliability, and availability) of nuclear power plants. Investigations and studies have included a) instrumentation surveillance and calibration validation, b) inferential sensing to calibration of feedwater venturi flow during fouling, c) thermodynamic performance modeling with iterative improvement of plant beat rate, d) diagnosis of nuclear power plant transients, and e) increase in thermal power through monitoring of DNBR (Departure from Nucleate Boiling Regime). To increase the likelihood of these individual systems being used in a nuclear power plant, they must be integrated into a single system that operates virtually autonomously, collecting, interpreting, and providing information to the operators in a simple and understandable format. (author)

  16. [Hyperspectral remote sensing diagnosis models of rice plant nitrogen nutritional status].

    Science.gov (United States)

    Tan, Chang-Wei; Zhou, Qing-Bo; Qi, La; Zhuang, Heng-Yang

    2008-06-01

    The correlations of rice plant nitrogen content with raw hyperspectral reflectance, first derivative hyperspectral reflectance, and hyperspectral characteristic parameters were analyzed, and the hyperspectral remote sensing diagnosis models of rice plant nitrogen nutritional status with these remote sensing parameters as independent variables were constructed and validated. The results indicated that the nitrogen content in rice plant organs had a variation trend of stem plant nitrogen nutritional status, with the decisive coefficients (R2) being 0.7996 and 0.8606, respectively; while the model with vegetation index (SDr - SDb) / (SDr + SDb) as independent variable, i. e., y = 365.871 + 639.323 ((SDr - SDb) / (SDr + SDb)), was most fit rice plant nitrogen content, with R2 = 0.8755, RMSE = 0.2372 and relative error = 11.36%, being able to quantitatively diagnose the nitrogen nutritional status of rice.

  17. Development of expert system on personal computer for diagnosis of nuclear reactor malfunctions

    International Nuclear Information System (INIS)

    Kameyama, Takanori; Uekata, Tomomichi; Oka, Yoshiaki; Kondo, Shunsuke; Togo, Yasumasa

    1988-01-01

    An expert system on a personal computer has been developed for diagnosis of malfunction of the fast experimental reactor 'JOYO'. Prolog-KABA is used as the language. The system diagnoses the event which causes scram or set-back of the control rod after an alarm at steady state operation. The knowledge base (KB) consists of several sub-KBs and a meta-KB. Using the forward chaining, the meta-KB decides which sub-KB should be accessed. The cause of the malfunction is identified in the sub-KB using the backward chaining. The terms expressing the characteristics of the events are involved in the production rules as attributes in order to use the Prolog function of pattern matching and back-tracking for efficient inference. The total number of the rules in the system is about 400. The experiments using the plant simulator of 'JOYO' have shown that malfunctions are successfully identified by the diagnosis system. It takes about 10s for each diagnosis using the 16-bits personal computer, PC-9801 VM. (author)

  18. SEMPaC - an expert system prototype associated with safety parameter display system of a nuclear power plant

    International Nuclear Information System (INIS)

    Hirama, K.

    1989-01-01

    This work presents SEMPaC, an expert system prototype: it provides means to support diagnosis and to make decisions during abnormal transients that cause the trip of nuclear power plant. The system operation is associated with Safety Parameter Display System - SPDS that was recommended by U. S. Nuclear Regulatory Commission (NRC) after the Three-Mile Island (TMI) accident analysis. (author)

  19. β-characterization by irreversibility analysis: A thermoeconomic diagnosis method

    International Nuclear Information System (INIS)

    Zaleta-Aguilar, Alejandro; Olivares-Arriaga, Abraham; Cano-Andrade, Sergio; Rodriguez-Alejandro, David A.

    2016-01-01

    This paper presents a reconciliation methodology for the diagnosis of energy systems. The methodology is based on the characterization of irreversibilities in the components of an energy system. These irreversibilities can be attributed to malfunctions or dysfunctions. The characterization of irreversibilities as presented here makes possible to reconcile the Actual Operating Condition (AOC) versus the Reference Operating Condition (ROC) of the energy system in a real-time manner. The diagnosis methodology introduces a parameter β, which represents the total exergy or useful work of a component in terms of its inlet and output streams at either design (full-load) or off-design (partial-load) conditions. The methodology is applied to the diagnosis of an actual Natural Gas Combined Cycle (NGCC) power plant. Data for the model is obtained directly from the plant by monitoring its performance at every time; thus, a real-time thermodynamic diagnosis for the system is obtained. Results show that the methodology presented here is able to detect and quantify the deviations on the performance of the NGCC power plant during its real-time operation. Based on the detection and quantification of these deviations, the user is able to make recommendations to schedule maintenance on the components where the irreversibilities are present. - Highlights: • A new methodology for thermoeconomic diagnosis of energy systems is presented. • A parameter β is defined for characterization of the components of an energy system. • The β characterization methodology is tested in a real 420 MW NGCC power plant. • Results show that the complexity of a diagnosis analysis is reduced substantially.

  20. Development of advanced secondary chemistry monitoring system for Korea nuclear power plants

    International Nuclear Information System (INIS)

    Lee, Sang Hak; Kim, Chung Tae

    1997-01-01

    Water chemistry control is one of the most important tasks in order to maintain the reliability of plant equipments and extend the operating life of the plant. KEPCO and KOPEC developed a computerized tool for this purpose -ASCMS (advanced secondary chemistry monitoring system) which is able to monitor and diagnose the secondary water chemistry. A prototype system had been installed at KORI 3 nuclear power plant since April 1993 in order to evaluate the system performance. After the implementation of enhancements identified during the testing of the prototype, we have developed the advanced secondary monitoring system, ASCMS which is installed at 5 nuclear power plants and has been under operations since April 1997. The ASCMS comprises PC subsystem designed for data acquisition, data analysis, and data diagnosis. The ASCMS will provide overall information related to steam generator secondary side water chemistry problems and improve plant availability, reduce radiation exposure to workers, and reduce operating and maintenance costs. 6 figs

  1. Improved methods of online monitoring and prediction in condensate and feed water system of nuclear power plant

    International Nuclear Information System (INIS)

    Wang, Hang; Peng, Min-jun; Wu, Peng; Cheng, Shou-yu

    2016-01-01

    Highlights: • Different methods for online monitoring and diagnosis are summarized. • Numerical simulation modeling of condensate and feed water system in nuclear power plant are done by FORTRAN programming. • Integrated online monitoring and prediction methods have been developed and tested. • Online monitoring module, fault diagnosis module and trends prediction module can be verified with each other. - Abstract: Faults or accidents may occur in a nuclear power plant (NPP), but it is hard for operators to recognize the situation and take effective measures quickly. So, online monitoring, diagnosis and prediction (OMDP) is used to provide enough information to operators and improve the safety of NPPs. In this paper, distributed conservation equation (DCE) and artificial immunity system (AIS) are proposed for online monitoring and diagnosis. On this basis, quantitative simulation models and interactive database are combined to predict the trends and severity of faults. The effectiveness of OMDP in improving the monitoring and prediction of condensate and feed water system (CFWS) was verified through simulation tests.

  2. The Decision Support System in the Domain of Casting Defects Diagnosis

    Directory of Open Access Journals (Sweden)

    Wilk-Kołodziejczyk D.

    2014-08-01

    Full Text Available This article presents a computer system for the identification of casting defects using the methodology of Case-Based Reasoning. The system is a decision support tool in the diagnosis of defects in castings and is designed for small and medium-sized plants, where it is not possible to take advantage of multi-criteria data. Without access to complete process data, the diagnosis of casting defects requires the use of methods which process the information based on the experience and observations of a technologist responsible for the inspection of ready castings. The problem, known and studied for a long time, was decided to be solved with a computer system using a CBR (Case-Based Reasoning methodology. The CBR methodology not only allows using expert knowledge accumulated in the implementation phase, but also provides the system with an opportunity to “learn” by collecting new cases solved earlier by this system. The authors present a solution to the system of inference based on the accumulated cases, in which the main principle of operation is searching for similarities between the cases observed and cases stored in the knowledge base.

  3. Diagnosis in the Enterprise Management System

    Directory of Open Access Journals (Sweden)

    Skrynkovskyy Ruslan M.

    2016-08-01

    Full Text Available The aim of the article is to define the role and place of the diagnosis management system in the structure of the task system of the enterprise diagnosis. There suggested the essence of the concept of «diagnosis of the enterprise», which is understood as the process of identification, analysis and evaluation of the enterprise state and trends in its changes (changes of the state on the basis of relevant business indicators in order to develop recommendations on the elimination of problematic points and weaknesses in the functioning of the enterprise to ensure a qualitatively new level of its development and formation of prospects with consideration to the consequences of violation of the legislation in the field of economics and enterprise management and law (legal responsibility for the violation of the labor law, tax law, law on protection of economic competition, law on trade secret, etc.. It was found that the diagnosis in the system of enterprise management: 1 is a structural component (or a partial diagnosis task in a group of private diagnosis tasks in the system of diagnosis task of the enterprise activity; 2 as a sub-function of the control function (as a general function of management includes such components as: assessment (identification of key features, characteristics, parameters (indexes, indicators, properties; analysis (a thorough study of the structure, dynamics, trends, etc.; identification (involves determination of deviations of parameters from the criteria and/or standards, formulation of diagnosis. Prospects for further research in this direction are the development of methods for quantitative assessment of the effectiveness of the management system with the purpose of its introducing in practical activities of enterprises, namely in the processes of decision-making.

  4. Early fault detection and diagnosis for nuclear power plants

    International Nuclear Information System (INIS)

    Berg, O.; Grini, R.; Masao Yokobayashi

    1988-01-01

    Fault detection based on a number of reference models is demonstrated. This approach is characterized by the possibility of detecting faults before a traditional alarm system is triggered, even in dynamic situations. Further, by a proper decomposition scheme and use of available process measurements, the problem area can be confined to the faulty process parts. A diagnosis system using knowledge engineering techniques is described. Typical faults are classified and described by rules involving alarm patterns and variations of important parameters. By structuring the fault hypotheses in a hierarchy the search space is limited which is important for real time diagnosis. Introduction of certainty factors improve the flexibility and robustness of diagnosis by exploring parallel problems even when some data are missing. A new display proposal should facilitate the operator interface and the integration of fault detection and diagnosis tasks in disturbance handling. The techniques of early fault detection and diagnosis are presently being implemented and tested in the experimental control room of a full-scope PWR simulator in Halden

  5. 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.

  6. Effects of integrated designs of alarm and process information on diagnosis performance in digital nuclear power plants.

    Science.gov (United States)

    Wu, Xiaojun; She, Manrong; Li, Zhizhong; Song, Fei; Sang, Wei

    2017-12-01

    In the main control rooms of nuclear power plants (NPPs), operators frequently switch between alarm displays and system-information displays to incorporate information from different screens. In this study, we investigated two integrated designs of alarm and process information - integrating alarm information into process displays (denoted as Alarm2Process integration) and integrating process information into alarm displays (denoted as Process2Alarm integration). To analyse the effects of the two integration approaches and time pressure on the diagnosis performance, a laboratory experiment was conducted with ninety-six students. The results show that compared with the non-integrated case, Process2Alarm integration yields better diagnosis performance in terms of diagnosis accuracy, time required to generate correct hypothesis and completion time. In contrast, the Alarm2Process integration leads to higher levels of workload, with no improvement in diagnosis performance. The diagnosis performance of Process2Alarm integration was consistently better than that of Alarm2Process integration, regardless of the levels of time pressure. Practitioner Summary: To facilitate operator's synthesis of NPP information when performing diagnosis tasks, we proposed to integrate process information into alarm displays. The laboratory validation shows that the integration approach significantly improves the diagnosis performance for both low and high time-pressure levels.

  7. Development of module-based simulation system for nuclear power plant

    International Nuclear Information System (INIS)

    Yoshikawa, H.

    1990-01-01

    Module-based Simulation System (MSS) has been developed to realize a new software environment enabling versatile dynamic simulation of a complex nuclear power plant system flexibly. Described in the paper are (i) fundamental methods utilized in MMS and its software systemization, (ii) development of human interface system to help users in generating integrated simulation programs automatically, and (iii) development of an intelligent user support system for helping users in the two phases of automatical semantic diagnosis and consultation to automatic input data setup for the MSS-generated programs

  8. Cloud Monitoring for Solar Plants with Support Vector Machine Based Fault Detection System

    Directory of Open Access Journals (Sweden)

    Hong-Chan Chang

    2014-01-01

    Full Text Available This study endeavors to develop a cloud monitoring system for solar plants. This system incorporates numerous subsystems, such as a geographic information system, an instantaneous power-consumption information system, a reporting system, and a failure diagnosis system. Visual C# was integrated with ASP.NET and SQL technologies for the proposed monitoring system. A user interface for database management system was developed to enable users to access solar power information and management systems. In addition, by using peer-to-peer (P2P streaming technology and audio/video encoding/decoding technology, real-time video data can be transmitted to the client end, providing instantaneous and direct information. Regarding smart failure diagnosis, the proposed system employs the support vector machine (SVM theory to train failure mathematical models. The solar power data are provided to the SVM for analysis in order to determine the failure types and subsequently eliminate failures at an early stage. The cloud energy-management platform developed in this study not only enhances the management and maintenance efficiency of solar power plants but also increases the market competitiveness of solar power generation and renewable energy.

  9. Rapid immunohistochemical diagnosis of tobacco mosaic virus disease by microwave-assisted plant sample preparation

    Science.gov (United States)

    Zellnig, Günther; Möstl, Stefan; Zechmann, Bernd

    2013-01-01

    Immunoelectron microscopy is a powerful method to diagnose viral diseases and to study the distribution of the viral agent within plant cells and tissues. Nevertheless, current protocols for the immunological detection of viral diseases with transmission electron microscopy (TEM) in plants take between 3 and 6 days and are therefore not suited for rapid diagnosis of virus diseases in plants. In this study, we describe a method that allows rapid cytohistochemical detection of tobacco mosaic virus (TMV) in leaves of tobacco plants. With the help of microwave irradiation, sample preparation of the leaves was reduced to 90 min. After sample sectioning, virus particles were stained on the sections by immunogold labelling of the viral coat protein, which took 100 min. After investigation with the TEM, a clear visualization of TMV in tobacco cells was achieved altogether in about half a day. Comparison of gold particle density by image analysis revealed that samples prepared with the help of microwave irradiation yielded significantly higher gold particle density as samples prepared conventionally at room temperature. This study clearly demonstrates that microwave-assisted plant sample preparation in combination with cytohistochemical localization of viral coat protein is well suited for rapid diagnosis of plant virus diseases in altogether about half a day by TEM. PMID:23580761

  10. 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

  11. Fault diagnosis technology of nuclear power plant based on weighted degree of grey incidence of optimized entropy

    International Nuclear Information System (INIS)

    Kong Yan; Li Zhenjie; Ren Xin; Wang Chuan

    2012-01-01

    Nuclear power plants (NPPs) are very complex grey system, in which faults and signs have not certain corresponding connection, so it's hard to diagnose the faults. A model based on weighted degree of grey incidence of optimized entropy was proposed according to the problem. To validate the system, some simulation experiments about the typical faults of condenser of NPPs were conducted. The results show that the system's conclusion is right, and the system's velocity is fast which can satisfy diagnosis in real time, and with the distinctive features such as good stability, high resolution rate and so on. (authors)

  12. Two Thermoeconomic Diagnosis Methods Applied to Representative Operating Data of a Commercial Transcritical Refrigeration Plant

    DEFF Research Database (Denmark)

    Ommen, Torben Schmidt; Sigthorsson, Oskar; Elmegaard, Brian

    2017-01-01

    In order to investigate options for improving the maintenance protocol of commercial refrigeration plants, two thermoeconomic diagnosis methods were evaluated on a state-of-the-art refrigeration plant. A common relative indicator was proposed for the two methods in order to directly compare the q...

  13. Deep knowledge expert system for diagnosis of multiple-failure severe transients in nuclear power plant

    International Nuclear Information System (INIS)

    Martin, R.P.; Nassersharif, B.

    1987-01-01

    TAMUS (Transient Analysis of MUltiple-failure Simulations) is a prototype expert system which is the result of a project investigating and implementing event confidence-levels (used by reactor safety experts in reactor transient analysis) in the form of an expert system. Currently, TAMUS is designed to diagnose reactor transients by analyzing simulated sensor and plant thermal hydraulic information from a system simulation. TAMUS uses a knowledge base of existing emergency nuclear plant operating guidelines and detailed thermal-hydraulic calculating results correlated to confidence-levels. TAMUS can diagnose a number of reactor transients (for example, loss-of-coolant accidents, steam-generator-tube ruptures, loss-of-offsite power, etc.). Future work includes the expansion of the knowledge base and improvement of the deep-knowledge qualitative models

  14. Potential Applications and Limitations of Electronic Nose Devices for Plant Disease Diagnosis

    Directory of Open Access Journals (Sweden)

    Antonio Cellini

    2017-11-01

    Full Text Available Electronic nose technology has recently been applied to the detection of several plant diseases and pests, with promising results. However, in spite of its numerous advantages, including operational simplicity, non-destructivity, and bulk sampling, drawbacks include a low sensitivity and specificity in comparison with microbiological and molecular methods. A critical review of the use of an electronic nose for plant disease diagnosis and pest detection is presented, describing the instrumental and procedural advances of sensorial analysis, for the improvement of discrimination between healthy and infected or infested plants. In conclusion, the use of electronic nose technology is suggested to assist, direct, and optimise traditionally adopted diagnostic techniques.

  15. FUNCTIONAL MODELLING FOR FAULT DIAGNOSIS AND ITS APPLICATION FOR NPP

    Directory of Open Access Journals (Sweden)

    MORTEN LIND

    2014-12-01

    Full Text Available The paper presents functional modelling and its application for diagnosis in nuclear power plants. Functional modelling is defined and its relevance for coping with the complexity of diagnosis in large scale systems like nuclear plants is explained. The diagnosis task is analyzed and it is demonstrated that the levels of abstraction in models for diagnosis must reflect plant knowledge about goals and functions which is represented in functional modelling. Multilevel flow modelling (MFM, which is a method for functional modelling, is introduced briefly and illustrated with a cooling system example. The use of MFM for reasoning about causes and consequences is explained in detail and demonstrated using the reasoning tool, the MFMSuite. MFM applications in nuclear power systems are described by two examples: a PWR; and an FBR reactor. The PWR example show how MFM can be used to model and reason about operating modes. The FBR example illustrates how the modelling development effort can be managed by proper strategies including decomposition and reuse.

  16. Functional Modelling for fault diagnosis and its application for NPP

    Energy Technology Data Exchange (ETDEWEB)

    Lind, Morten; Zhang, Xin Xin [Dept. of Electrical Engineering, Technical University of Denmark, Kongens Lyngby (Denmark)

    2014-12-15

    The paper presents functional modelling and its application for diagnosis in nuclear power plants. Functional modelling is defined and its relevance for coping with the complexity of diagnosis in large scale systems like nuclear plants is explained. The diagnosis task is analyzed and it is demonstrated that the levels of abstraction in models for diagnosis must reflect plant knowledge about goals and functions which is represented in functional modelling. Multilevel flow modelling (MFM), which is a method for functional modelling, is introduced briefly and illustrated with a cooling system example. The use of MFM for reasoning about causes and consequences is explained in detail and demonstrated using the reasoning tool, the MFMSuite. MFM applications in nuclear power systems are described by two examples: a PWR; and an FBR reactor. The PWR example show how MFM can be used to model and reason about operating modes. The FBR example illustrates how the modelling development effort can be managed by proper strategies including decomposition and reuse.

  17. Functional Modelling for fault diagnosis and its application for NPP

    International Nuclear Information System (INIS)

    Lind, Morten; Zhang, Xin Xin

    2014-01-01

    The paper presents functional modelling and its application for diagnosis in nuclear power plants. Functional modelling is defined and its relevance for coping with the complexity of diagnosis in large scale systems like nuclear plants is explained. The diagnosis task is analyzed and it is demonstrated that the levels of abstraction in models for diagnosis must reflect plant knowledge about goals and functions which is represented in functional modelling. Multilevel flow modelling (MFM), which is a method for functional modelling, is introduced briefly and illustrated with a cooling system example. The use of MFM for reasoning about causes and consequences is explained in detail and demonstrated using the reasoning tool, the MFMSuite. MFM applications in nuclear power systems are described by two examples: a PWR; and an FBR reactor. The PWR example show how MFM can be used to model and reason about operating modes. The FBR example illustrates how the modelling development effort can be managed by proper strategies including decomposition and reuse.

  18. New Infrared spectroscopic methods for tumor diagnosis and medicinal plants analytics

    International Nuclear Information System (INIS)

    Pezzei, C.

    2012-01-01

    This work was done to verify the feasibility of infrared spectroscopy as a method for tumor diagnosis and medicinal plants analysis. The method of IR imaging has been successfully used for the diagnosis of prostate-, bladder- and oral squamous cell carcinoma as well as for localization of different ingredients of plant roots. All measurements have been done with a resolution down to 1,2 µm. As a non-invasive method, IR imaging can be used for qualitative analysis of 2-dimensional chemical structures and distribution of these substances in plant roots. It was found that IR imaging can be used for detecting cancer-affected areas in tissue-samples. For more profound results, IR-imaging has to be combined with chemometric evaluation methods like multi- and univariate data analysis. Measurements applying that combination of methods allow the identification of cancer-affected areas of tissue-samples of prostate-, bladder- and oral squamous cell carcinoma as well as an illustration of the local distribution of components like carbon-hydrates, proteins, lipids, amides and nucleic acids in samples from Urtica dioica, Phytolacca americana, Levisticum officinale, Primula veris, Cimicifuga racemosa and Gentiana lutea. All research was done by using state of the art technology for IR-imaging and image processing. It was found that IR-imaging can be used for localizing dissolved substances in roots of medical plants with a high resolution down to 1,2 µm. This work shows that different species of Polygala can be identified using FT-NIR and FT-IR spectroscopy. Future developments of more sophisticated and powerful detectors will help to establish IR-imaging as an objective technology for diagnostics of cancer as well as a method in the field of research on medical plants and botany in general. (author) [de

  19. Energy systems Diagnosis in developing countries

    International Nuclear Information System (INIS)

    Girod, J.

    1991-01-01

    Energy systems diagnosis is necessary to allow evaluation of energy balance by administration and political authorities of a country. First, the author describes the principle stages of energetic diagnosis. Then this work is divided into three parts: First part: Energy consumption diagnosis in several districts (families, utilities, agriculture, transport, industry) Second part: Energy supplies diagnosis (energy markets). Third part: Interactions between energy consumption and energy supply. 28 figs.; 52 tabs.; 107 refs

  20. Plant Phenotype Characterization System

    Energy Technology Data Exchange (ETDEWEB)

    Daniel W McDonald; Ronald B Michaels

    2005-09-09

    This report is the final scientific report for the DOE Inventions and Innovations Project: Plant Phenotype Characterization System, DE-FG36-04GO14334. The period of performance was September 30, 2004 through July 15, 2005. The project objective is to demonstrate the viability of a new scientific instrument concept for the study of plant root systems. The root systems of plants are thought to be important in plant yield and thus important to DOE goals in renewable energy sources. The scientific study and understanding of plant root systems is hampered by the difficulty in observing root activity and the inadequacy of existing root study instrumentation options. We have demonstrated a high throughput, non-invasive, high resolution technique for visualizing plant root systems in-situ. Our approach is based upon low-energy x-ray radiography and the use of containers and substrates (artificial soil) which are virtually transparent to x-rays. The system allows us to germinate and grow plant specimens in our containers and substrates and to generate x-ray images of the developing root system over time. The same plant can be imaged at different times in its development. The system can be used for root studies in plant physiology, plant morphology, plant breeding, plant functional genomics and plant genotype screening.

  1. The Plant-Window system: A flexible, expandable computing environment for the integration of power plant activities

    International Nuclear Information System (INIS)

    Wood, R.T.; Mullens, J.A.; Naser, J.A.

    1994-01-01

    Power plant data, and the information that can be derived from it, provide the link to the plant through which the operations, maintenance and engineering staff understand and manage plant performance. The increasing use of computer technology in the US nuclear power industry has greatly expanded the capability to obtain, analyze, and present data about the plant to station personnel. However, it is necessary to transform the vast quantity of available data into clear, concise, and coherent information that can be readily accessed and used throughout the plant. This need can be met by an integrated computer workstation environment that provides the necessary information and software applications, in a manner that can be easily understood and used, to the proper users throughout the plant. As part of a Cooperative Research and Development Agreement with the Electric Power Research Institute, the Oak Ridge National Laboratory has developed functional requirements for a Plant-Wide Integrated Environment Distributed on Workstations (Plant-Window) System. The Plant-Window System (PWS) can serve the needs of operations, engineering, and maintenance personnel at nuclear power stations by providing integrated data and software applications (e.g., monitoring, analysis, diagnosis, and control applications) within a common environment. The PWS requirements identify functional capabilities and provide guidelines for standardized hardware, software, and display interfaces to define a flexible computer environment that permits a tailored implementation of workstation capabilities and facilitates future upgrades

  2. Intelligent software system for the advanced control room of a nuclear power plant

    Energy Technology Data Exchange (ETDEWEB)

    Chang, Soon Heung; Choi, Seong Soo; Park, Jin Kyun; Heo, Gyung Young [Korea Advanced Institute of Science and Technology, Taejon (Korea, Republic of); Kim, Han Gon [Korea Electric Power Research Institute, Taejon (Korea, Republic of)

    1998-12-31

    The intelligent software system for nuclear power plants (NPPs) has been conceptually designed in this study. Its design goals are to operate NPPs in an improved manner and to support operators` cognitive takes. It consists of six major modules such as {sup I}nformation Processing,{sup {sup A}}larm Processing,{sup {sup P}}rocedure Tracking,{sup {sup P}}erformance Diagnosis,{sup a}nd {sup E}vent Diagnosis{sup m}odules for operators and {sup M}alfunction Diagnosis{sup m}odule for maintenance personnel. Most of the modules have been developed for several years and the others are under development. After the completion of development, they will be combined into one system that would be main parts of advanced control rooms in NPPs. 5 refs., 4 figs. (Author)

  3. Intelligent software system for the advanced control room of a nuclear power plant

    Energy Technology Data Exchange (ETDEWEB)

    Chang, Soon Heung; Choi, Seong Soo; Park, Jin Kyun; Heo, Gyung Young [Korea Advanced Institute of Science and Technology, Taejon (Korea, Republic of); Kim, Han Gon [Korea Electric Power Research Institute, Taejon (Korea, Republic of)

    1997-12-31

    The intelligent software system for nuclear power plants (NPPs) has been conceptually designed in this study. Its design goals are to operate NPPs in an improved manner and to support operators` cognitive takes. It consists of six major modules such as {sup I}nformation Processing,{sup {sup A}}larm Processing,{sup {sup P}}rocedure Tracking,{sup {sup P}}erformance Diagnosis,{sup a}nd {sup E}vent Diagnosis{sup m}odules for operators and {sup M}alfunction Diagnosis{sup m}odule for maintenance personnel. Most of the modules have been developed for several years and the others are under development. After the completion of development, they will be combined into one system that would be main parts of advanced control rooms in NPPs. 5 refs., 4 figs. (Author)

  4. Functional Modelling for Fault Diagnosis and its application for NPP

    DEFF Research Database (Denmark)

    Lind, Morten; Zhang, Xinxin

    2014-01-01

    The paper presents functional modelling and its application for diagnosis in nuclear power plants.Functional modelling is defined and it is relevance for coping with the complexity of diagnosis in large scale systems like nuclear plants is explained. The diagnosis task is analyzed and it is demon...... operating modes. The FBR example illustrates how the modeling development effort can be managed by proper strategies including decomposition and reuse....

  5. Development of a multi-functional platform to perform the I and C system test, diagnosis and training

    International Nuclear Information System (INIS)

    Ren Chunxiang; Guan Yunquan; Wang Xingye

    2014-01-01

    The Safety I and C system of Tianwan Nuclear Power Station (TNPS) is implemented with the Class lE digital I and C platform TELEPERM XS (TXS). To satisfy the requirements of TXS system fault diagnosis, spare parts performance test as well as the staff maintenance skill training, through the study of operating environment and configuration characteristics of the online TXS system, and adequately absorb the experiences of the digital control device test systems which are applied in both domestic and abroad, developed and established a set of TXS system multifunctional platform which performs the TXS software/hardware testing, fault diagnosis and staff maintenance skill training. Practice has proved that the platform running well to perform the test of the TXS system hardware and software, fault diagnosis and the training tasks to ensure the reliable operation of the online safety I and C system, and shorten the maintenance cycle of online TXS system, improved the technical level of the Operation and maintenance personnel, it provides a reference for similar I and C systems of other nuclear power plants. (authors)

  6. Corrective maintenance support system for nuclear power plants

    International Nuclear Information System (INIS)

    Kakiuchi, Tetsuo

    1996-01-01

    With increase of share of nuclear power generation in electric power supply in Japan, requirement for further safe operation and improvement of economics for the nuclear power plants is promoting. The pressed water type (PWR) nuclear power plant in operation in Japan reaches to 22 sets, application rate of the instruments is 74% as mean value for 7 years since 1989 and in high level, which is due to a result of preventive maintenance in ordinary and periodical inspections. The present state of maintenance at the nuclear power plant is mainly preventive maintenance, which is mainly conducted in a shape of time planning maintenance but partially in a shape of state monitoring maintenance for partial rotating appliances. Concretely speaking, the periodical inspection was planned on a base of daily inspection and a long term program on maintenance, and executed on a base of feedback function to think of the long term program again by evaluating the periodical inspection results. Here were introduced on the monitoring diagnosis and periodical inspection regionalization equipment, fatigue monitoring system, automatic supersonic wave damage inspection equipment for reactor, steam evaporator heat conductive tube inspection equipment, automatic testing equipment for measuring controller, air working valve property testing equipment, as maintaining support system in the PW generation plant. (G.K.)

  7. A study on quantification of the information flow and effectiveness of information aids for diagnosis tasks in nuclear power plants

    International Nuclear Information System (INIS)

    Kim, Jong Hyun

    2004-02-01

    Diagnosis is one of the most complex and mental resource-demanding tasks in nuclear power plants (NPPs), especially, to main control room (MCR) operators. Diagnosis is a crucial part of disturbance control in NPPs, since it is a prerequisite task for initiating operating procedures. In order to design a control room feature for NPPs, three elements need to be considered: 1) the operational tasks that must be performed, 2) a model of human performance for these tasks, and 3) a model of how control room features are intended to support performance. The operational tasks define the classes of performance that must be considered. A model of human performance makes more explicit the requirements for accurate and efficient performance and reveals potential sources of error. Finally, the model of support allows the generation of specific hypotheses about how performance is facilitated in the control room. The model of support needs to be developed based on the human performance model. This paper proposes three approaches for the system design of operator support systems to aid MCR operators' diagnosis tasks in NPPs, considering the above three elements. This paper presents 1) a quantitative approach to modeling the information flow of diagnosis tasks, 2) strategy-based evaluation of information aids for diagnosis tasks, and 3) quantitative evaluation of NPP decision support systems. As an analysis of diagnosis tasks, this paper presents a method to quantify the cognitive information flow of diagnosis tasks, integrating a stage model (a qualitative approach) with information theory (a quantitative approach). The method includes: 1) constructing the information flow model, which consists of four stages based on operating procedures of NPPs: and 2) quantifying the information flow using Conant's model, a kind of information theory. Then, three experiments were conducted to evaluate the effectiveness of the proposed approach to predicting human performances, especially in

  8. The use of mass and energy balances for observation in process plant diagnosis

    International Nuclear Information System (INIS)

    Lind, M.; Talmon, H.

    1981-12-01

    A method is described that uses the invariant mass and energy conservation laws in order to extract a detailed pattern of mass and energy flows from the instrumentation of a process plant. The basic feature of the method is that it is applicable to a large range of plant operational situations, such as those initiated by unforeseen failures during sequential operations. The authors' intensions with this interim progress report are to describe the basic ideas behind the method, as well as to discuss some of its implications for man-computer cooperation in process plant diagnosis. (author)

  9. 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.

  10. 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.

  11. Trouble diagnostic system for pumps used in thermal and nuclear power plant

    International Nuclear Information System (INIS)

    Amano, K.; Hayashi, M.; Takagi, M.; Katsura, H.

    1995-01-01

    Most power plants have been operated under severe conditions to meet the diversification in electricity supply and demand. Therefore, it has become an important objective to keep the pumps under maintenance and control which necessitates a more reliable diagnostic system. With this in mind, the authors set out to perform the simulation tests of abnormal operation using a model pump, and have developed the diagnostic system for pumps based on vibration and process data. The main features of the system are 1) parallel processing of data acquisition and the diagnosis and 2) guidance function for the abnormal operation. The system has been applied to an actual pump to detect a bearing damage and set up at the nuclear power plant. (author)

  12. Diagnosis and Fault-Tolerant Control for Thruster-Assisted Position Mooring System

    DEFF Research Database (Denmark)

    Nguyen, Trong Dong; Blanke, Mogens; Sørensen, Asgeir

    2007-01-01

    Development of fault-tolerant control systems is crucial to maintain safe operation of o®shore installations. The objective of this paper is to develop a fault- tolerant control for thruster-assisted position mooring (PM) system with faults occurring in the mooring lines. Faults in line......'s pretension or line breaks will degrade the performance of the positioning of the vessel. Faults will be detected and isolated through a fault diagnosis procedure. When faults are detected, they can be accommodated through the control action in which only parameter of the controlled plant has to be updated...... to cope with the faulty condition. Simulations will be carried out to verify the advantages of the fault-tolerant control strategy for the PM system....

  13. Monitoring and aid to diagnosis of French PWRs

    International Nuclear Information System (INIS)

    Jousellin, A.; Trenty, A.; Benas, J.C.; Renault, Y.; Busquet, J.L.; Mouhamed, B.

    1996-01-01

    In order to improvise safety and availability in its nuclear power plants, EDF has designed a new generation of monitoring systems integrated into a workstation for monitoring and aid to diagnosis (PSAD). These systems perform on-line monitoring of the main power plant components and PSAD stations provide homogeneous aid to diagnosis which enable plant personnel to pinpoint the mechanical behavior of plant equipments. The objective of PSAD is to provide them with high-efficiency and user-friendly tools which can considerably free them from routine tasks. The first version of the prototype is working on a French plant at Tricastin. This version includes the software host structure and two monitoring functions: the reactor coolant pumps and the turbo-generator monitoring functions. Internal Structures Monitoring (ISM) and Loose Parts Detection function (LPD) are under development and should be integrated into PSAD prototype in 1996. (authors)

  14. Technical requirements on knowledge base and instrumentation system for decision making in plant operation and maintenance

    International Nuclear Information System (INIS)

    Kitamura, Masaharu; Yoshikawa, Shinji; Hasegawa, Makoto

    1998-03-01

    A series of technical surveys and studies are described in this report to examine and identify technical requirements to be posed on knowledge base and instrumentation system as the fundamental in high reliability computational decision making in operation and maintenance of nuclear power plants. Monitoring and diagnosis are focused as the important tasks among the operation/maintenance-related tasks. A concrete monitoring and diagnosis system configuration has been proposed consisting of distributed symptom database and of on-demand measurement subsystem. An prototype of the proposed system configuration has been successfully verified. (author)

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

    Directory of Open Access Journals (Sweden)

    Jian-Hua Zhong

    2016-01-01

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

  16. Investigation of relation between operator's mental workload and information flow in accident diagnosis tasks of nuclear power plant

    International Nuclear Information System (INIS)

    Ha, Chang Hoon; Kim, Jong Hyun; Seong, Poong Hyun

    2004-01-01

    In the main control room (MCR) of a nuclear power plant (NPP), there are lots of dynamic information sources for MCR operator's situation awareness. As the human-machine interface in MCR is advanced, operator's information acquisition, information gathering and decision-making is becoming an important part to maintain the effective and safe operation of NPPs. Diagnostic task in complex and huge systems like NPP is the most difficult and mental effort-demanding for operators. This research investigates the relation between operator's mental workload and information flow in accident diagnosis tasks. The amount of information flow is quantified, using information flow model and Conant's model, a kind of information theory. For the mental workload measure, eye blink rate, blink duration, fixation time, number of fixation, and gaze direction are measured during accident diagnosis tasks. Subjective methods such as NASA-Task Load Index (NASA-TLX) and Modified Cooper-Harper (MCH) method are also used in the experiment. It is shown that the operator's mental workload has significant relation to information flow of diagnosis task. It makes possible to predict the mental workload through the quantity of the information flow of a system

  17. A computer program to reduce the time of diagnosis in complex systems

    International Nuclear Information System (INIS)

    Arellano-Gomez, Juan; Romero-Rubio, Omar U.

    2006-01-01

    In Nuclear Power Plants (NPPs), the time that some systems are allowed to be down is frequently very limited. Thus, when one of these systems fails, diagnosis and repair must be quickly performed in order to get the system back to an operative state. Unfortunately, in complex systems, a considerable amount of the total repair time could be spent in the duty of diagnosis. For this reason, it seems very useful to provide maintenance personnel with a systematic approach to system failure diagnosis, capable to minimize the time required to effectively identify the causes of system malfunction. In this context, the expert systems technology has been widely applied in several disciplines to successfully develop diagnostic systems. Obviously, an important input to develop these expert systems is, of course, knowledge; this knowledge includes both formal knowledge and experience on what faults could occur, how these faults occur, which are the effects of these faults, what could be inferred from symptoms, etc. Due to their logical nature, those fault trees developed by expert analysts during risk studies could also be used as the source of knowledge of diagnostic expert systems (DES); however, these fault trees must be expanded to include symptoms because, typically, diagnosis is performed by inferring the causes of system malfunction from symptoms. This paper presents SANA (Symptom Analyzer), a new software package specially designed to develop diagnostic expert systems. The main feature of this software is that it exploits the knowledge stored in fault trees (in particular, expanded fault trees) to generate very efficient diagnostic strategies. These strategies guide diagnostic activities seeking to minimize the time required to identify those components which are responsible of the system failure. Besides, the generated strategies 'emulate' the way experienced technicians proceed in order to diagnose the causes of system failure (i.e. by recognizing categories of

  18. Fault diagnosis method for nuclear power plants based on neural networks and voting fusion

    International Nuclear Information System (INIS)

    Zhou Gang; Ge Shengqi; Yang Li

    2010-01-01

    A new fault diagnosis method based on multiple neural networks (ANNs) and voting fusion for nuclear power plants (NPPs) was proposed in view of the shortcoming of single neural network fault diagnosis method. In this method, multiple neural networks that the types of neural networks were different were trained for the fault diagnosis of NPP. The operation parameters of NPP, which have important affect on the safety of NPP, were selected as the input variable of neural networks. The output of neural networks is fault patterns of NPP. The last results of diagnosis for NPP were obtained by fusing the diagnosing results of different neural networks by voting fusion. The typical operation patterns of NPP were diagnosed to demonstrate the effect of the proposed method. The results show that employing the proposed diagnosing method can improve the precision and reliability of fault diagnosis results of NPPs. (authors)

  19. SENSORS FAULT DIAGNOSIS ALGORITHM DESIGN OF A HYDRAULIC SYSTEM

    Directory of Open Access Journals (Sweden)

    Matej ORAVEC

    2017-06-01

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

  20. A multivariate statistical study on a diversified data gathering system for nuclear power plants

    International Nuclear Information System (INIS)

    Samanta, P.K.; Teichmann, T.; Levine, M.M.; Kato, W.Y.

    1989-02-01

    In this report, multivariate statistical methods are presented and applied to demonstrate their use in analyzing nuclear power plant operational data. For analyses of nuclear power plant events, approaches are presented for detecting malfunctions and degradations within the course of the event. At the system level, approaches are investigated as a means of diagnosis of system level performance. This involves the detection of deviations from normal performance of the system. The input data analyzed are the measurable physical parameters, such as steam generator level, pressurizer water level, auxiliary feedwater flow, etc. The study provides the methodology and illustrative examples based on data gathered from simulation of nuclear power plant transients and computer simulation of a plant system performance (due to lack of easily accessible operational data). Such an approach, once fully developed, can be used to explore statistically the detection of failure trends and patterns and prevention of conditions with serious safety implications. 33 refs., 18 figs., 9 tabs

  1. Application of forwardchaining method to diagnosis of onion plant diseases

    Science.gov (United States)

    Sitanggang, Delima; Siregar, Saut D.; Situmeang, Suryani M. F.; Indra, Evta; Sagala, Ayu R.; Sihombing, Oloan; Nababan, Marlince; Pasaribu, Hendra; Damanik, Rudolf R.; Turnip, Mardi; Saragih, Rijois I. E.

    2018-04-01

    Red Onion is a tuber plant that is widely used by the people of Indonesia, both as herbs and herbal medicines. Onion farmers have limitations in identifying diseases that attack their crops.This disease can cause crop failure against the onion.This design begins with the creation of a knowledge base up to input-output design with forward chaining method. The results of this design can assist farmers in identifying their plant diseases. Based on diagnostic results of several methods that have been done testing can diagnose diseases contained in onion plants. With symptoms data that has been determined by the expert with the value of each symptom is different. As for the symptoms that have been determined that the leaves contain patches with a value of 0.3, White leaf spots value 0.4, Leaf spots form a purple zone if it is severe 0.5, Leaf tip of 0.2, Tubers rot 0.4. Based on the above diagnostic results then get the value of diagnosis 67% forward chaining with trotol disease type, Purple spotting.

  2. A Multi-Model Approach for System Diagnosis

    DEFF Research Database (Denmark)

    Niemann, Hans Henrik; Poulsen, Niels Kjølstad; Bækgaard, Mikkel Ask Buur

    2007-01-01

    A multi-model approach for system diagnosis is presented in this paper. The relation with fault diagnosis as well as performance validation is considered. The approach is based on testing a number of pre-described models and find which one is the best. It is based on an active approach......,i.e. an auxiliary input to the system is applied. The multi-model approach is applied on a wind turbine system....

  3. Active fault diagnosis in closed-loop uncertain systems

    DEFF Research Database (Denmark)

    Niemann, Hans Henrik

    2006-01-01

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

  4. Fast diagnosis and treatment of cracklike defect injuriousness in PWR power plant equipment

    International Nuclear Information System (INIS)

    Boneh, B.; Gilles, P.; Benchimol, M.

    1983-01-01

    The potential risk of cracking phenomena (initial defects or propagating cracks) in auxiliary and secondary power plant systems makes it essential to evaluate the injuriousness of such defects. This paper presents a Defect Injuriousness Diagnosis and Treatment Package (DIDTP) which can be applied to auxiliary and secondary system analysis during manufacturing and installation work as well as during actual system operation. Following a presentation of the individual elements comprising a DIDTP, a description is given of the analytical and computational methods, which are based on brittle and ductile fracture mechanics concepts fundamental to any DIDTP. A brief description is then given of the TITAN and ANODE computer codes developed by FRAMATOME which are used for automatic compilation of DIDTP's. Finally, a practical example is given to demonstrate the different stages involved in the compilation of a DIDTP, and the way in which the DIDTP can be used to provide results which make it possible to determine short or longterm actions: rework of faulty component, operating modifications, monitoring of critical zones, additional computations, etc. (orig./GL)

  5. 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.

  6. An internet-based bioinformatics toolkit for plant biosecurity diagnosis and surveillance of viruses and viroids.

    Science.gov (United States)

    Barrero, Roberto A; Napier, Kathryn R; Cunnington, James; Liefting, Lia; Keenan, Sandi; Frampton, Rebekah A; Szabo, Tamas; Bulman, Simon; Hunter, Adam; Ward, Lisa; Whattam, Mark; Bellgard, Matthew I

    2017-01-11

    Detection and preventing entry of exotic viruses and viroids at the border is critical for protecting plant industries trade worldwide. Existing post entry quarantine screening protocols rely on time-consuming biological indicators and/or molecular assays that require knowledge of infecting viral pathogens. Plants have developed the ability to recognise and respond to viral infections through Dicer-like enzymes that cleave viral sequences into specific small RNA products. Many studies reported the use of a broad range of small RNAs encompassing the product sizes of several Dicer enzymes involved in distinct biological pathways. Here we optimise the assembly of viral sequences by using specific small RNA subsets. We sequenced the small RNA fractions of 21 plants held at quarantine glasshouse facilities in Australia and New Zealand. Benchmarking of several de novo assembler tools yielded SPAdes using a kmer of 19 to produce the best assembly outcomes. We also found that de novo assembly using 21-25 nt small RNAs can result in chimeric assemblies of viral sequences and plant host sequences. Such non-specific assemblies can be resolved by using 21-22 nt or 24 nt small RNAs subsets. Among the 21 selected samples, we identified contigs with sequence similarity to 18 viruses and 3 viroids in 13 samples. Most of the viruses were assembled using only 21-22 nt long virus-derived siRNAs (viRNAs), except for one Citrus endogenous pararetrovirus that was more efficiently assembled using 24 nt long viRNAs. All three viroids found in this study were fully assembled using either 21-22 nt or 24 nt viRNAs. Optimised analysis workflows were customised within the Yabi web-based analytical environment. We present a fully automated viral surveillance and diagnosis web-based bioinformatics toolkit that provides a flexible, user-friendly, robust and scalable interface for the discovery and diagnosis of viral pathogens. We have implemented an automated viral surveillance and

  7. Computerized operator support system with new man-machine interface for BWR power plants

    International Nuclear Information System (INIS)

    Monta, K.; Naito, N.; Sugawara, M.; Sato, N.; Mori, N.; Tai, I.; Fukumoto, A.; Tsuchida, M.

    1984-01-01

    Improvement of the man-machine interface of nuclear power plants is an important contribution to the further enhancement of operational safety. In addition, recent advances in computer technology seem to offer the greatest opportunity to date for achieving improvement in the man-machine interface. The development of a computerized operator support system for BWRs has been undertaken since 1980 with the support of the Japanese Government. The conceptual design of this system is based on the role of the operators. The main functions are standby system management, disturbance analysis and post-trip operational guidance. The objective of the standby system management is to monitor the standby status of the engineered safety feature during normal operation to assure its proper functioning at the onset of emergency situations. The disturbance analysis system detects disturbances in the plant in their early stages and informs the plant operators about, for example, the cause of the disturbances, the plant status and possible propagations. Consequently, operators can take corrective actions to prevent unnecessary plant shutdown. The objective of the post trip operational guide is to support operators in diagnosis and corrective action after a plant trip. Its functions are to monitor the performance of the engineered safety feature, to identify the plant status and to guide the appropriate corrective action to achieve safe plant shutdown. The information from the computerized operator support system is supplied to operators through a colour CRT operator console. The authors have evaluated the performance of various new man-machine interfacing tools and proposed a new operator console design. A prototype system has been developed and verification/validation is proceeding with a BWR plant simulator. (author)

  8. Multilevel flow modelling of process plant for diagnosis and control

    International Nuclear Information System (INIS)

    Lind, M.

    1982-08-01

    The paper describes the multilevel flow modelling methodology which can be used to construct functional models of energy and material processing systems. The models describe mass and energy flow topology on different levels of abstraction and represent the hierarchical functional structure of complex systems. A model of a nuclear power plant (PWR) is presented in the paper for illustration. Due to the consistency of the method, multilevel flow models provide specifications of plant goals and functions and may be used as a basis for design of computer-based support systems for the plant operator. Plant control requirements can be derived from the models and due to independence of the actual controller implementation the method may be used as basic for design of control strategies and for the allocation of control tasks to the computer and the plant operator. (author)

  9. Multilevel Flow Modelling of Process Plant for Diagnosis and Control

    DEFF Research Database (Denmark)

    Lind, Morten

    1982-01-01

    The paper describes the multilevel flow modelling methodology which can be used to construct functional models of energy and material processing systems. The models describe mass and energy flow topology on different levels of abstraction and represent the hierarchical functional structure...... of complex systems. A model of a nuclear power plant (PWR) is presented in the paper for illustration. Due to the consistency of the method, multilevel flow models provide specifications of plant goals and functions and may be used as a basis for design of computer-based support systems for the plant...... operator. Plant control requirements can be derived from the models and due to independence of the actual controller implementation the method may be used as a basis for design of control strategies and for the allocation of control tasks to the computer and the plant operator....

  10. NN-Es Fault Diagnosis Method in Nuclear Power Equipment Based on Concept Lattice

    International Nuclear Information System (INIS)

    Liu Yongkuo; Xie Chunli; Xia Hong

    2010-01-01

    In order to improve the fault diagnosis accuracy of nuclear power plant,neural network and expert systems were combined to give full play to their advantages. In this paper, the concept lattice was applied to get the object properties, extracting the core attributes, dispensable attributes and relative necessary attributes from a large number raw data of fault symptoms.Based on these attributes, neural networks with different levels of importance were designed to improve the learning speed and diagnosis accuracy, and the diagnosis results of the neural networks were verified by using rule-based reasoning expert system. To verify the accuracy of this method, some simulation experiments about the typical faults of nuclear power plant were conducted. And the simulation results show that it is feasible to diagnose nuclear power plant faults with the confederation diagnosis methods combined the neural networks based on the concept lattice theory and expert system, with the distinctive features such as the efficiency of neural network learning, less calculation and reliability of diagnosis results and so on. (authors)

  11. Development of new plant monitoring and control system with advanced man-machine interfaces NUCAMM-80

    International Nuclear Information System (INIS)

    Sato, Hideyuki; Joge, Toshio; Miyake, Masao; Kishi, Shoichi

    1981-01-01

    BWR type nuclear power stations are the typical plants adopting central monitoring system in view of the size of the scale of system and the prevention of radiation exposure. Central control boards became large as much informations and many operating tools are concentrated on them. Recently, the unit capacity has increased, and the safety has been strengthened, therefore more improvement of the man-machine interface is required concerning the monitoring of plant operation. Hitachi Ltd. developed the central monitoring and control system for nuclear power stations ''NUCAMM-80'', concentrating related fundamental techniques such as the collection of plant informations, the expansion of automatic operation, the ergonomic re-evaluation of the arrangement of panels and subsystems, and the effective use of functional hardwares such as controlling computers and cathode ray tubes, for the purposes of improving the reliability of plant operation and the rate of operation, the reduction of the burden of operators and drastic labor saving. The fundamental policy of the development, the construction of the system, panel layout and the collection of informations, the development of the system for plant automation, the development of plant diagnosis and prevention systems, computer system and the merits of this system are described. (Kako, I.)

  12. 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

  13. A method for diagnosis of plant environmental stresses by gene expression profiling using a cDNA macroarray

    International Nuclear Information System (INIS)

    Tamaoki, Masanori; Matsuyama, Takashi; Nakajima, Nobuyoshi; Aono, Mitsuko; Kubo, Akihiro; Saji, Hikaru

    2004-01-01

    Plants in the field are subjected to numerous environmental stresses. Lengthy continuation of such environmental stresses or a rapid increase in their intensity is harmful to vegetation. Assessments of the phytotoxicity of various stresses have been performed in many countries, although they have largely been based on estimates of leaf injury. We developed a novel method of detecting plant stresses that is more sensitive and specific than those previously available. This method is based on the detection of mRNA expression changes in 205 ozone-responsive Arabidopsis expressed sequence tags (ESTs) by cDNA macroarray analysis. By using this method, we illustrated shifts in gene expression in response to stressors such as drought, salinity, UV-B, low temperature, high temperature, and acid rain, as distinct from those in response to ozone. We also made a mini-scale macroarray with 12 ESTs for diagnosis of the above environmental stresses in plants. These results illustrate the potential of our cDNA macroarray for diagnosis of various stresses in plants

  14. 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

  15. 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

  16. Development of a knowledge-based system for loop diagnosis

    International Nuclear Information System (INIS)

    Liao, L.Y.; Tang, H.C.; Chen, S.S.

    1987-01-01

    An accident diagnostic system is developed as an attempt to provide a useful aid for the operators of an experimental loop or a nuclear power plant in the case of emergency condition. Because the current practices in the system diagnosis are not satisfactory, there is an increasing demand on the establishment of various operator decision support systems. The knowledge based system is a new and promising technique which can be used to fulfill this demand. With the capability of automatic reasoning and by incorporating the information about system status, the knowledge based system can simulate the process of human thinking and serve as a good decision support system. This knowledge based decision support system can be helpful for both a fast, violent accident and a slowly developed accident. Specifically, a fast diagnostic report can be provided for a fast and violent accident of which time is the main concern and a complete diagnostic report can be provided for a slowly developed accident of which complexity is the main concern. Such a knowledge based decision support system also provides many other equally important advantages, such as the elimination of human error, the automatic validation of signal readings, the establishment of human error, the automatic validation of signal readings, and the establishment of a simulation environment

  17. Design of the expert system to analyze disease in Plant Teak using Forward Chaining

    Directory of Open Access Journals (Sweden)

    Poningsih Poningsih

    2017-06-01

    Full Text Available Teak is one kind of plant that is already widely known and developed by the wider community in the form of plantations and community forests. This is because until now Teak wood is a commodity of luxury, high quality, the price is expensive, and high economic value. Expert systems are a part of the method sciences artificial intelligence to make an application program disease diagnosis teak computerized seek to replace and mimic the reasoning process of an expert or experts in solving the problem specification that can be said to be a duplicate from an expert because science knowledge is stored inside a database  Expert System for the diagnosis of disease teak using forward chaining method aims to explore the characteristics shown in the form of questions in order to diagnose the disease teak with web-based software. Device keel expert system can recognize the disease after consulting identity by answering some of the questions presented by the application of expert systems and can infer some kind of disease in plants teak. Data disease known customize rules (rules are made to match the characteristics of teak disease and provide treatment solutions.

  18. FPGA-Based Plant Protection System

    Energy Technology Data Exchange (ETDEWEB)

    Lee, Yoon Hee; Ha, Jae Hong; Kim, Hang Bae [KEPCO E and C, Daejeon (Korea, Republic of)

    2011-08-15

    This paper relates to a plant protection system which detects non-permissible conditions and determines initiation of protective actions for nuclear power plants (NPPs). Conventional plant protection systems were designed based on analog technologies. It is well known that existing protection systems for NPPs contain many components which are becoming obsolete at an increasing rate. Nowadays maintenance and repair for analog-based plant protection systems may be difficult as analog parts become obsolete or difficult to obtain. Accordingly, as an alternative to the analog technology, the digitalisation of the plant protection system was required. Recently digital plant protection systems which include programmable logic controllers (PLCs) and/or computers have been introduced. However PLC or computer-based plant protection systems use an operating system and application software, and so they may result in a common mode failure when a problem occurs in the operating system or application software. Field Programmable Gate Arrays (FPGAs) are highlighted as an alternative to conventional protection or control systems. The paper presents the design of a four-channel plant protection system whose protection functions are implemented in FPGAs without any central processing unit or operating system.

  19. FPGA-Based Plant Protection System

    International Nuclear Information System (INIS)

    Lee, Yoon Hee; Ha, Jae Hong; Kim, Hang Bae

    2011-01-01

    This paper relates to a plant protection system which detects non-permissible conditions and determines initiation of protective actions for nuclear power plants (NPPs). Conventional plant protection systems were designed based on analog technologies. It is well known that existing protection systems for NPPs contain many components which are becoming obsolete at an increasing rate. Nowadays maintenance and repair for analog-based plant protection systems may be difficult as analog parts become obsolete or difficult to obtain. Accordingly, as an alternative to the analog technology, the digitalisation of the plant protection system was required. Recently digital plant protection systems which include programmable logic controllers (PLCs) and/or computers have been introduced. However PLC or computer-based plant protection systems use an operating system and application software, and so they may result in a common mode failure when a problem occurs in the operating system or application software. Field Programmable Gate Arrays (FPGAs) are highlighted as an alternative to conventional protection or control systems. The paper presents the design of a four-channel plant protection system whose protection functions are implemented in FPGAs without any central processing unit or operating system

  20. Application of optical diagnosis to aged low-voltage cable insulation in nuclear plants

    International Nuclear Information System (INIS)

    Katagiri, Junichi; Takezawa, Yoshitaka; Shouji, Hiroshi

    2008-01-01

    We have developed a novel non-destructive optical diagnosis technique for low-voltage cable insulations used in nuclear power plants. The key features of this diagnosis are the use of two wavelengths to measure the change in reflective absorbance (ΔA R ), the use of polarized light to measure crystallinity and the use of element volatilizing to measure fluorescence. Chemical kinetics is used to predict the lifetimes of the cable insulations. When cable insulations darken and harden by time degradation, the ΔA R and depolarization parameters increase. This means that the cross-linking density in the cable insulations increases due to deterioration reactions. When the cross-linking density of insulation increases, its elasticity, corresponding to the material's life, increases. Similarly, as the crystallinity increases due to the change in the high-order structure of the insulating resin caused by irradiation, its elongation property decreases. The elongation property of insulation is one of the most important parameters that can be used to evaluate material lifetimes, because it relates to elasticity. The ΔA R correlated with the elongation property, and the correlation coefficient of an accelerated experiment using model pieces was over 0.9. Thus, we concluded that this optical diagnosis should be applied to evaluate the degradation of cable insulations used in nuclear power plants. (author)

  1. Advanced I and C systems for nuclear power plants

    International Nuclear Information System (INIS)

    Bock, H.W.; Graf, A.; Hofmann, H.

    1995-01-01

    Advanced I and C systems for nuclear power plants have to meet increasing demands for safety and availability. Additionally, specific requirements coming from the nuclear qualification have to be fulfilled. To meet both subjects adequately in the future, Siemens has developed advanced I and C technology consisting of the two complementary I and C systems TELEPERM XP and TELEPERM XS. The main features of these systems are the clear task related architecture with adaptable redundancy, the consequent application of standards for interfaces and communication, comprehensive tools for easy design and service and a highly ergonomic screen based man-machine-interface. The engineering tasks are supported by an integrated engineering system, which has the capacity for design, test and diagnosis of all I and C functions and the related equipment. TELEPERM XP is designed to optimally perform all automatic functions, which require no nuclear specific qualification. This includes all sequences and closed-loop controls as well as most man-machine-interface functions. TELEPERM XS is designed for all control tasks which require a nuclear specific qualification. This especially includes all functions to initiate automatic countermeasures to prevent or to cope with accidents. By use of the complementary I and C systems TELEPERM XP and TELEPERM XS, economical as well as advanced plant automation and man-machine-interfaces can be implemented into Nuclear Plants, assuring the compliance with the relevant international safety standards. (author). 10 figs

  2. Advanced I and C systems for nuclear power plants

    International Nuclear Information System (INIS)

    Bock, H.W.; Graf, A.; Hofmann, H.

    1997-01-01

    Advanced I and C systems for nuclear power plants have to meet increasing demands for safety and availability. Additionally specific requirements arising from nuclear qualification have to be fulfilled. To meet both subjects adequately in the future, Siemens has developed advanced I and C technology consisting of the two complementary I and C systems TELEPERM XP and TELEPERM XS. The main features of these systems are a clear task related architecture with adaptable redundancy, a consequent application of standards for interfaces and communication, comprehensive tools for easy design and service and a highly ergonomic screen based man-machine-interface. The engineering tasks are supported by an integrated engineering system, which has the capacity for design, test and diagnosis of all I and C functions and the related equipment. TELEPERM XP is designed to optimally perform all automatic functions, which require no nuclear specific qualification. This includes all sequences and closed-loop controls as well as most man-machine-interface functions. TELEPERM XS is designed for all control tasks which require a nuclear specific qualification. This especially includes all function to initiated automatic countermeasures to prevent or to cope with accidents. By use of the complementary I and C systems TELEPERM XP and TELEPERM XS, advanced and likewise economical plant automation and man-machine-interfaces can be implemented into Nuclear Power Plant, assuring compliance with the relevant international safety standards. (author). 10 figs

  3. Advanced I and C systems for nuclear power plants

    Energy Technology Data Exchange (ETDEWEB)

    Bock, H W; Graf, A; Hofmann, H [Siemens AG, Erlangen (Germany)

    1997-07-01

    Advanced I and C systems for nuclear power plants have to meet increasing demands for safety and availability. Additionally specific requirements arising from nuclear qualification have to be fulfilled. To meet both subjects adequately in the future, Siemens has developed advanced I and C technology consisting of the two complementary I and C systems TELEPERM XP and TELEPERM XS. The main features of these systems are a clear task related architecture with adaptable redundancy, a consequent application of standards for interfaces and communication, comprehensive tools for easy design and service and a highly ergonomic screen based man-machine-interface. The engineering tasks are supported by an integrated engineering system, which has the capacity for design, test and diagnosis of all I and C functions and the related equipment. TELEPERM XP is designed to optimally perform all automatic functions, which require no nuclear specific qualification. This includes all sequences and closed-loop controls as well as most man-machine-interface functions. TELEPERM XS is designed for all control tasks which require a nuclear specific qualification. This especially includes all function to initiated automatic countermeasures to prevent or to cope with accidents. By use of the complementary I and C systems TELEPERM XP and TELEPERM XS, advanced and likewise economical plant automation and man-machine-interfaces can be implemented into Nuclear Power Plant, assuring compliance with the relevant international safety standards. (author). 10 figs.

  4. Development of a framework to estimate human error for diagnosis tasks in advanced control room

    International Nuclear Information System (INIS)

    Kim, Ar Ryum; Jang, In Seok; Seong, Proong Hyun

    2014-01-01

    In the emergency situation of nuclear power plants (NPPs), a diagnosis of the occurring events is crucial for managing or controlling the plant to a safe and stable condition. If the operators fail to diagnose the occurring events or relevant situations, their responses can eventually inappropriate or inadequate Accordingly, huge researches have been performed to identify the cause of diagnosis error and estimate the probability of diagnosis error. D.I Gertman et al. asserted that 'the cognitive failures stem from erroneous decision-making, poor understanding of rules and procedures, and inadequate problem solving and this failures may be due to quality of data and people's capacity for processing information'. Also many researchers have asserted that human-system interface (HSI), procedure, training and available time are critical factors to cause diagnosis error. In nuclear power plants, a diagnosis of the event is critical for safe condition of the system. As advanced main control room is being adopted in nuclear power plants, the operators may obtain the plant data via computer-based HSI and procedure. Also many researchers have asserted that HSI, procedure, training and available time are critical factors to cause diagnosis error. In this regards, using simulation data, diagnosis errors and its causes were identified. From this study, some useful insights to reduce diagnosis errors of operators in advanced main control room were provided

  5. Plant air systems safety study: Portsmouth Gaseous Diffusion Plant

    International Nuclear Information System (INIS)

    1982-05-01

    The Portsmouth Gaseous Diffusion Plant Air System facilities and operations are reviewed for potential safety problems not covered by standard industrial safety procedures. Information is presented under the following section headings: facility and process description (general); air plant equipment; air distribution system; safety systems; accident analysis; plant air system safety overview; and conclusion

  6. Image diagnosis of plant function under environmental pollution. Shokubutsu de kankyo osen wo shindansuru

    Energy Technology Data Exchange (ETDEWEB)

    Omasa, K. (National Inst. for Environmental studies, Tsukuba (Japan))

    1993-12-20

    Various physiological reaction of plants would be obstructed and troubles of their growth would be met under environmental pollution. There are also cases that the polluted materials as nutritious components are absorbed by plants. Consequently, if plant's reaction on this environmental pollution would be used, indexes of environmental pollution and environment can be improved. For examples, Ipomoea Nil and Petunia having high reaction on photochemical oxidate are widely used as index plant of air pollution. Zelkova trees and poplars planted as street trees can also greatly absorbed the polluted gas and have a function to clear air. In this paper, a diagnosis method by visualizing plant's reaction on environmental pollution by using technique of image measurement was explained. As devices of usable image measurement, a thermal camera, a solid measuring cameras, an ultrasonic camera, a multi-spectral camera and an X-ray TV camera were given. 6 refs., 4 figs., 1 tab.

  7. Accident diagnosis, recovery, and prognosis aid

    International Nuclear Information System (INIS)

    Touchton, R.A.

    1987-01-01

    This paper describes an investigation that was conducted to assess and demonstrate the feasibility of using artificial intelligence (AI) techniques to develop an expert system serving as a nuclear plant accident diagnosis, recovery, and prognosis aid. This effort was sponsored under a contract with the Department of Energy as a part of their Small Business Innovation Research Program. The interest in such a system is based upon on-going industry and regulatory commitment to improved nuclear plant performance and safety

  8. 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.

  9. Diagnosis of dynamic systems based on explicit and implicit behavioural models: an application to gas turbines in Esprit Project Tiger

    Energy Technology Data Exchange (ETDEWEB)

    Trave-Massuyes, L. [Centre National de la Recherche Scientifique (CNRS), 31 - Toulouse (France); Milne, R.

    1995-12-31

    We are interested in the monitoring and diagnosis of dynamic systems. In our work, we are combining explicit temporal models of the behaviour of a dynamic system with implicit behavioural models supporting model based approaches. This work is drive by the needs of and applied to, two gas turbines of very different size and power. In this paper we describe the problems of building systems for these domains and illustrate how we have developed a system where these two approaches complement each other to provide a comprehensive fault detection and diagnosis system. We also explore the strengths and weaknesses of each approach. The work described here is currently working continuously, on line to a gas turbine in a major chemical plant. (author) 24 refs.

  10. Diagnosis of dynamic systems based on explicit and implicit behavioural models: an application to gas turbines in Esprit Project Tiger

    Energy Technology Data Exchange (ETDEWEB)

    Trave-Massuyes, L [Centre National de la Recherche Scientifique (CNRS), 31 - Toulouse (France); Milne, R

    1996-12-31

    We are interested in the monitoring and diagnosis of dynamic systems. In our work, we are combining explicit temporal models of the behaviour of a dynamic system with implicit behavioural models supporting model based approaches. This work is drive by the needs of and applied to, two gas turbines of very different size and power. In this paper we describe the problems of building systems for these domains and illustrate how we have developed a system where these two approaches complement each other to provide a comprehensive fault detection and diagnosis system. We also explore the strengths and weaknesses of each approach. The work described here is currently working continuously, on line to a gas turbine in a major chemical plant. (author) 24 refs.

  11. Plant-derived chimeric virus particles for the diagnosis of primary Sjögren syndrome

    Directory of Open Access Journals (Sweden)

    Elisa eTinazzi

    2015-12-01

    Full Text Available Plants are ideal for the production of protein-based nanomaterials because they synthesize and assemble complex multimeric proteins that cannot be expressed efficiently using other platforms. Plant viruses can be thought of as self-replicating proteinaceous nanomaterials generally stable and easily produced in high titers. We used Potato virus X (PVX chimeric virus particles (CVPs and Cowpea mosaic virus (CPMV empty virus-like particles (eVLPs to display a linear peptide (lipo derived from human lipocalin , which is immunodominant in Sjögren’s syndrome (SjS and is thus recognized by autoantibodies in SjS patient serum. These virus-derived nanoparticles (VNPs were thus used to develop a diagnostic assay for SjS based on a direct enzyme linked immunosorbent assay (ELISA format. We found that PVX-lipo formulations were more sensitive than the chemically synthesized immunodominant peptide and equally specific when used to distinguish between healthy individuals and SjS patients. Our novel assay therefore allows the diagnosis of SjS using a simple, low-invasive serum test, contrasting with the invasive labial biopsy required for current tests. Our results demonstrate that nanomaterials based on plant viruses can be used as diagnostic reagents for SjS, and could also be developed for the diagnosis of other diseases.

  12. Toxic plants affecting the nervous system of ruminants and horses in Brazil

    Directory of Open Access Journals (Sweden)

    Franklin Riet-Correa

    Full Text Available ABSTRACT: This review updates information about neurotoxic plants affecting ruminants and equidae in Brazil. Currently in the country, there are at least 131 toxic plants belonging to 79 genera. Thirty one of these poisonous plants affect the nervous system. Swainsonine-containing plants (Ipomoea spp., Turbina cordata and Sida carpinifolia cause numerous outbreaks of poisoning, mainly in goats, but cattle and horses are occasionally affected. The poisoning by Ipomoea asarifolia, a tremorgenic plant, is very common in sheep, goats and cattle in the Northeastern region and in the Marajo island. Poisoning by the pods of Prosopis juliflora are frequent in cattle in Northeastern Brazil; occasionally this poisoning affects goats and more rarely sheep. Some poisonings by plants, such as Hybanthus calceolaria, Ipomoea marcellia and Talisia esculenta in ruminants and Indigofera lespedezioides in horses were recently described and needs to be accurately investigated about its occurrence and importance. Other plants poisonings causing nervous signs in ruminants and equidae are less important, but should be considered for the differential diagnosis of neurologic diseases.

  13. Diagnosis of wind turbine rotor system

    DEFF Research Database (Denmark)

    Niemann, Hans Henrik; Mirzaei, Mahmood; Henriksen, Lars Christian

    2016-01-01

    is based on available standard sensors on wind turbines. The method can be used both on-line as well as off-line. Faults or changes in the rotor system will result in asymmetries, which can be monitored and diagnosed. This can be done by using the multi-blade coordinate transformation. Changes in the rotor......This paper describes a model free method for monitoring and fault diagnosis of the elements in a rotor system for a wind turbine. The diagnosis as well as the monitoring is done without using any model of the wind turbine and the applied controller or a description of the wind profile. The method...

  14. Diagnosis device for abnormality of power plant equipment

    International Nuclear Information System (INIS)

    Matono, Chiemi; Okamachi, Masao.

    1995-01-01

    In a power plant, if contained water leaks in a condensate system, water is automatically supplied from a feedwater system in accordance with the leakage. Since the diameter of the pipeline of the supplementary feedwater system is generally small, the influence of the leakage of the contained water appears remarkably as a change of the amount of the feed water in the supplementary feed water system. The change of the supplementary state of water to the condensate system by the supplementary feed water system is monitored, to estimate the presence or absence of the leakage of water contained in the condensate system depending on the result of the monitoring, and then the results are informed. In addition, when leakage of water contained in the condensate system is estimated, guidance information is prepared and outputted for coping with the result of the estimation, and the result of the estimation and the guidance information are displayed auditory and visually. As a result, a plant operator can recognize the abnormality of water leakage in the condensate system rapidly and accurately without observing various states of the condensate system and with no knowledge or experiences at high levels, thereby enabling to conduct appropriate processing rapidly. (N.H.)

  15. Malfunction diagnosis and applications of stable adaptive schemes for a nuclear reactor system

    International Nuclear Information System (INIS)

    Fukuda, Toshio; Shibata, Heki.

    1979-01-01

    Malfunction diagnosis concerns a method to detect the abnormal phenomena during nuclear reactor operations, while stable adaptive schemes does the application of Model Reference Adaptive System (MRAS) to the nonlinear dynamics of a reactor for parameter identification and control. The new method for the malfunction diagnosis consists of the following ideas; an index defined as the sum of ratios of the square of a factor score to the contribution weight of the factor, which is evaluated by applying the multi-factor analysis technique to the data of the state of nuclear reactor systems like neutron flux, temperature, flow rate and so on. The excess of the index over some given threshold shows the reactor system would be in an abnormal state. Then a theory of optimal filtering by Kalman with the aid of the stochastic approximation is applied to estimate the neutron flux distribution at its abnormal state and subsequently the squared sum of difference between desirable and estimated flux distributions shows the spot at which the abnormal phenomena would have occurred in terms of the peak of its distribution. Parameter identification and adaptive control schemes are presented for a point reactor and a loosely-coupled-core reactor with internal feedbacks which lead to the nonlinearity of the overall system. Both schemes are shown stable with new representations of the systems, which correspond to the nonminimal system representation, in the vein of the MRAS via the Lyapunov's method. For the sake of the parameter identification, model parameters can be adjusted adaptively as soon as measurements start, while plant parameters can also adaptively be compensated through control input to reduce the output error between the model and the plant for the case of the adaptive control. Some experiments of parameter identification for the thermal-hydraulic system are carried out successfully using a simplified channel in which flow rate is varied in a binary form. (J.P.N.)

  16. General knowledge structure for diagnosis

    International Nuclear Information System (INIS)

    Steinar Brendeford, T.

    1996-01-01

    At the OECD Halden Reactor Project work has been going on for several years in the field of automatic fault diagnosis for nuclear power plants. Continuing this work, studies are now carried out to combine different diagnostic systems within the same framework. The goal is to establish a general knowledge structure for diagnosis applied to a NPP process. Such a consistent and generic storage of knowledge will lighten the task of combining different diagnosis techniques. An integration like this is expected to increase the robustness and widen the scope of the diagnosis. Further, verification of system reliability and on-line explanations of hypotheses can be helped. Last but not least there is a potential in reuse of both specific and generic knowledge. The general knowledge framework is also a prerequisite for a successful integration of computerized operator support systems within the process supervision and control complex. Consistency, verification and reuse are keywords also in this respect. Systems that should be considered for integration are; automatic control, computerized operator procedures, alarm - and alarm filtering, signal validation, diagnosis and condition based maintenance. This paper presents three prototype diagnosis systems developed at the OECD Halden Reactor Project. A software arrangement for process simulation with these three systems attached in parallel is briefly described. The central part of this setup is a 'blackboard' system to be used for representing shared knowledge. Examples of such knowledge representations are included in the paper. The conclusions so far in this line of work are only tentative. The studies of existing methodologies for diagnosis, however, show a potential for several generalizations to be made in knowledge representation and use. (author). 14 refs, 6 figs

  17. General knowledge structure for diagnosis

    Energy Technology Data Exchange (ETDEWEB)

    Steinar Brendeford, T [Institutt for Energiteknikk, Halden (Norway). OECD Halden Reaktor Projekt

    1997-12-31

    At the OECD Halden Reactor Project work has been going on for several years in the field of automatic fault diagnosis for nuclear power plants. Continuing this work, studies are now carried out to combine different diagnostic systems within the same framework. The goal is to establish a general knowledge structure for diagnosis applied to a NPP process. Such a consistent and generic storage of knowledge will lighten the task of combining different diagnosis techniques. An integration like this is expected to increase the robustness and widen the scope of the diagnosis. Further, verification of system reliability and on-line explanations of hypotheses can be helped. Last but not least there is a potential in reuse of both specific and generic knowledge. The general knowledge framework is also a prerequisite for a successful integration of computerized operator support systems within the process supervision and control complex. Consistency, verification and reuse are keywords also in this respect. Systems that should be considered for integration are; automatic control, computerized operator procedures, alarm - and alarm filtering, signal validation, diagnosis and condition based maintenance. This paper presents three prototype diagnosis systems developed at the OECD Halden Reactor Project. A software arrangement for process simulation with these three systems attached in parallel is briefly described. The central part of this setup is a `blackboard` system to be used for representing shared knowledge. Examples of such knowledge representations are included in the paper. The conclusions so far in this line of work are only tentative. The studies of existing methodologies for diagnosis, however, show a potential for several generalizations to be made in knowledge representation and use. (author). 14 refs, 6 figs.

  18. Application of ENN-1 for Fault Diagnosis of Wind Power Systems

    Directory of Open Access Journals (Sweden)

    Meng-Hui Wang

    2012-01-01

    Full Text Available Maintaining a wind turbine and ensuring secure is not easy because of long-term exposure to the environment and high installation locations. Wind turbines need fully functional condition-monitoring and fault diagnosis systems that prevent accidents and reduce maintenance costs. This paper presents a simulator design for fault diagnosis of wind power systems and further proposes some fault diagnosis technologies such as signal analysis, feature selecting, and diagnosis methods. First, this paper uses a wind power simulator to produce fault conditions and features from the monitoring sensors. Then an extension neural network type-1- (ENN-1- based method is proposed to develop the core of the fault diagnosis system. The proposed system will benefit the development of real fault diagnosis systems with testing models that demonstrate satisfactory results.

  19. Metabolomics in plants and humans: applications in the prevention and diagnosis of diseases.

    Science.gov (United States)

    Gomez-Casati, Diego F; Zanor, Maria I; Busi, María V

    2013-01-01

    In the recent years, there has been an increase in the number of metabolomic approaches used, in parallel with proteomic and functional genomic studies. The wide variety of chemical types of metabolites available has also accelerated the use of different techniques in the investigation of the metabolome. At present, metabolomics is applied to investigate several human diseases, to improve their diagnosis and prevention, and to design better therapeutic strategies. In addition, metabolomic studies are also being carried out in areas such as toxicology and pharmacology, crop breeding, and plant biotechnology. In this review, we emphasize the use and application of metabolomics in human diseases and plant research to improve human health.

  20. An Automated and Continuous Plant Weight Measurement System for Plant Factory.

    Science.gov (United States)

    Chen, Wei-Tai; Yeh, Yu-Hui F; Liu, Ting-Yu; Lin, Ta-Te

    2016-01-01

    In plant factories, plants are usually cultivated in nutrient solution under a controllable environment. Plant quality and growth are closely monitored and precisely controlled. For plant growth evaluation, plant weight is an important and commonly used indicator. Traditional plant weight measurements are destructive and laborious. In order to measure and record the plant weight during plant growth, an automated measurement system was designed and developed herein. The weight measurement system comprises a weight measurement device and an imaging system. The weight measurement device consists of a top disk, a bottom disk, a plant holder and a load cell. The load cell with a resolution of 0.1 g converts the plant weight on the plant holder disk to an analog electrical signal for a precise measurement. The top disk and bottom disk are designed to be durable for different plant sizes, so plant weight can be measured continuously throughout the whole growth period, without hindering plant growth. The results show that plant weights measured by the weight measurement device are highly correlated with the weights estimated by the stereo-vision imaging system; hence, plant weight can be measured by either method. The weight growth of selected vegetables growing in the National Taiwan University plant factory were monitored and measured using our automated plant growth weight measurement system. The experimental results demonstrate the functionality, stability and durability of this system. The information gathered by this weight system can be valuable and beneficial for hydroponic plants monitoring research and agricultural research applications.

  1. An Automated and Continuous Plant Weight Measurement System for Plant Factory

    Directory of Open Access Journals (Sweden)

    Wei-Tai eChen

    2016-03-01

    Full Text Available In plant factories, plants are usually cultivated in nutrient solution under a controllable environment. Plant quality and growth are closely monitored and precisely controlled. For plant growth evaluation, plant weight is an important and commonly used indicator. Traditional plant weight measurements are destructive and laborious. In order to measure and record the plant weight during plant growth, an automated measurement system was designed and developed herein. The weight measurement system comprises a weight measurement device and an imaging system. The weight measurement device consists of a top disk, a bottom disk, a plant holder and a load cell. The load cell with a resolution of 0.1 g converts the plant weight on the plant holder disk to an analogue electrical signal for a precise measurement. The top disk and bottom disk are designed to be durable for different plant sizes, so plant weight can be measured continuously throughout the whole growth period, without hindering plant growth. The results show that plant weights measured by the weight measurement device are highly correlated with the weights estimated by the stereo-vision imaging system; hence, plant weight can be measured by either method. The weight growth of selected vegetables growing in the National Taiwan University plant factory were monitored and measured using our automated plant growth weight measurement system. The experimental results demonstrate the functionality, stability and durability of this system. The information gathered by this weight system can be valuable and beneficial for hydroponic plants monitoring research and agricultural research applications.

  2. A Structural Model Decomposition Framework for Hybrid Systems Diagnosis

    Science.gov (United States)

    Daigle, Matthew; Bregon, Anibal; Roychoudhury, Indranil

    2015-01-01

    Nowadays, a large number of practical systems in aerospace and industrial environments are best represented as hybrid systems that consist of discrete modes of behavior, each defined by a set of continuous dynamics. These hybrid dynamics make the on-line fault diagnosis task very challenging. In this work, we present a new modeling and diagnosis framework for hybrid systems. Models are composed from sets of user-defined components using a compositional modeling approach. Submodels for residual generation are then generated for a given mode, and reconfigured efficiently when the mode changes. Efficient reconfiguration is established by exploiting causality information within the hybrid system models. The submodels can then be used for fault diagnosis based on residual generation and analysis. We demonstrate the efficient causality reassignment, submodel reconfiguration, and residual generation for fault diagnosis using an electrical circuit case study.

  3. Experimental investigation between attentional-resource effectiveness and perception and diagnosis in nuclear power plants

    International Nuclear Information System (INIS)

    Ha, Jun Su; Seong, Poong Hyun

    2014-01-01

    Highlights: • Effectiveness in information searching is measured by two eye-tracking measures. • The relationship between the effectiveness and perception and diagnosis is addressed. • An experimental study is conducted to investigate the relationship. • The experimental results show close correlation. • The eye-tracking measures as inferential measures for perception and diagnosis. - Abstract: Eye-tracking-based measures of attentional-resource effectiveness in information searching such as FIR (fixation to importance ratio) and SAE (selective attention effectiveness) have been developed based on cost-benefit principles. The relationship between the eye-tracking-based measures and perception and diagnosis of operators during operating tasks in main control rooms (MCRs) of nuclear power plants (NPPs) is investigated with experimental studies. The FIR and the SAE, which represent how effectively an operator attends to important information sources, are used as measures of the effectiveness in information searching. Perception failure rate (PFR) and diagnosis score (DS) are used as measures of perception and diagnosis, respectively. Experimental results show that the FIR and the SAE correlate closely with the PFR and the DS, respectively. It is concluded that the FIR and the SAE can be used as inferential measures of perception and diagnosis for human factors in NPP MCRs

  4. Experimental investigation between attentional-resource effectiveness and perception and diagnosis in nuclear power plants

    Energy Technology Data Exchange (ETDEWEB)

    Ha, Jun Su, E-mail: junsu.ha@kustar.ac.ae [Nuclear Engineering Department, Khalifa University of Science, Technology and Research, P.O. Box 127788, Abu Dhabi (United Arab Emirates); Seong, Poong Hyun, E-mail: phseong@kaist.ac.kr [Department of Nuclear and Quantum Engineering, Korea Advanced Institute of Science and Technology, 373-1 Guseong-dong, Yuseong-gu, Daejeon 305-701 (Korea, Republic of)

    2014-10-15

    Highlights: • Effectiveness in information searching is measured by two eye-tracking measures. • The relationship between the effectiveness and perception and diagnosis is addressed. • An experimental study is conducted to investigate the relationship. • The experimental results show close correlation. • The eye-tracking measures as inferential measures for perception and diagnosis. - Abstract: Eye-tracking-based measures of attentional-resource effectiveness in information searching such as FIR (fixation to importance ratio) and SAE (selective attention effectiveness) have been developed based on cost-benefit principles. The relationship between the eye-tracking-based measures and perception and diagnosis of operators during operating tasks in main control rooms (MCRs) of nuclear power plants (NPPs) is investigated with experimental studies. The FIR and the SAE, which represent how effectively an operator attends to important information sources, are used as measures of the effectiveness in information searching. Perception failure rate (PFR) and diagnosis score (DS) are used as measures of perception and diagnosis, respectively. Experimental results show that the FIR and the SAE correlate closely with the PFR and the DS, respectively. It is concluded that the FIR and the SAE can be used as inferential measures of perception and diagnosis for human factors in NPP MCRs.

  5. Nuclear power plant diagnostic system

    International Nuclear Information System (INIS)

    Prokop, K.; Volavy, J.

    1982-01-01

    Basic information is presented on diagnostic systems used at nuclear power plants with PWR reactors. They include systems used at the Novovoronezh nuclear power plant in the USSR, at the Nord power plant in the GDR, the system developed at the Hungarian VEIKI institute, the system used at the V-1 nuclear power plant at Jaslovske Bohunice in Czechoslovakia and systems of the Rockwell International company used in US nuclear power plants. These diagnostic systems are basically founded on monitoring vibrations and noise, loose parts, pressure pulsations, neutron noise, coolant leaks and acoustic emissions. The Rockwell International system represents a complex unit whose advantage is the on-line evaluation of signals which gives certain instructions for the given situation directly to the operator. The other described systems process signals using similar methods. Digitized signals only serve off-line computer analyses. (Z.M.)

  6. Development of a New Safety Culture Assessment Method for Nuclear Power Plants (NPPs) (Decision support system for an OPR-1000 type power plant)

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Yo Chan; Jung, Won Dea [Korea Atomic Energy Institute, Daejeon (Korea, Republic of)

    2014-08-15

    To support operators in the diagnosis of abnormal operating procedures (AOPs), we developed a decision support system for an OPR-1000 type power plant. This system aids operators who identify abnormal situations from annunciated alarms using three functions: an AOP flowchart, AOP search, and alarm simulation. This paper introduces the developed system, compares the characteristics of the functions in the system, and discusses the strength of this approach compared with other previous research. It is expected that the advanced functions may elevate the performance and reliability of operators who manage abnormal situations.

  7. Development of a New Safety Culture Assessment Method for Nuclear Power Plants (NPPs) (Decision support system for an OPR-1000 type power plant)

    International Nuclear Information System (INIS)

    Kim, Yo Chan; Jung, Won Dea

    2014-01-01

    To support operators in the diagnosis of abnormal operating procedures (AOPs), we developed a decision support system for an OPR-1000 type power plant. This system aids operators who identify abnormal situations from annunciated alarms using three functions: an AOP flowchart, AOP search, and alarm simulation. This paper introduces the developed system, compares the characteristics of the functions in the system, and discusses the strength of this approach compared with other previous research. It is expected that the advanced functions may elevate the performance and reliability of operators who manage abnormal situations

  8. PSAD, a prototype for monitoring and aid to diagnosis of French PWRs; PSAD, un systeme prototype pour la surveillance et l`aide au diagnostic des centrales REP Francaises

    Energy Technology Data Exchange (ETDEWEB)

    Jousselin, A.; Bourgeois, P. [Electricite de France (EDF), 78 - Chatou (France); Busquet, J.L.; Monnier, B. [Electricite de France (EDF), 75 - Paris (France); Mouhamed, B. [SEMA Group France, 37 - Meylan (France)

    1996-03-01

    In order to improve safety and availability in its nuclear power plants, EDF has designed a new generation of monitoring systems integrated into a workstation for monitoring and aid to diagnosis (PSAD). These systems perform on-line monitoring of the main power plant components and PSAD stations provide homogenous aids ro diagnosis which enable plant personnel to diagnose the mechanical behavior of plant equipments. The objective of PSAD is to provide them with high-efficiency and user-friendly tools which can considerably free them from routine tasks. PSAD has a flexible architecture, guaranteeing optimum distribution of computing power to make it available where it is needed, thus enhancing the quality of the information. Its architecture includes diagnosis support software based on artificial intelligence technology which can dialogue with real-time or deferred-time processing software and a relational database. The first version of the prototype is working on a french plant at Tricastin. This version includes the software for the host structure and two monitoring functions: the reactor coolant pumps and the turbo-generator monitoring functions. Internal Structures Monitoring function (ISM) and Loose Parts Detection function (LPD) are under development and should be integrated into PSAD prototype in 1996. (author). 5 refs., 6 figs.

  9. A decision support system based on hybrid knowledge approach for nuclear power plant operation

    International Nuclear Information System (INIS)

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

    1991-01-01

    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. Frames and rules are adopted to represent the various knowledge types. Rule-based deduction and abduction are used for shallow and deep knowledge based reasoning respectively. The event-based operational guidelines are provided to the operator according to the diagnosed results

  10. Multilevel Flow Modeling for Nuclear Power Plant Diagnosis

    DEFF Research Database (Denmark)

    Gola, G; Lind, Morten; Thunem, Harald P-J

    2012-01-01

    , especially if extended to the whole plant. Monitoring plant performances by means of data reconciliation techniques has proved successful to detect anomalies during operation, provide early warnings and eventually schedule maintenance. At the same time, the large amount of information provided by large...... detected anomalies. The combination of a data reconciliation system and the Multilevel Flow Modeling approach is illustrated with regard to the secondary loop of the Loviisa-2 Pressurized Water Reactor located in Finland....

  11. Integrated Knowledge Based Expert System for Disease Diagnosis System

    Science.gov (United States)

    Arbaiy, Nureize; Sulaiman, Shafiza Eliza; Hassan, Norlida; Afizah Afip, Zehan

    2017-08-01

    The role and importance of healthcare systems to improve quality of life and social welfare in a society have been well recognized. Attention should be given to raise awareness and implementing appropriate measures to improve health care. Therefore, a computer based system is developed to serve as an alternative for people to self-diagnose their health status based on given symptoms. This strategy should be emphasized so that people can utilize the information correctly as a reference to enjoy healthier life. Hence, a Web-based Community Center for Healthcare Diagnosis system is developed based on expert system technique. Expert system reasoning technique is employed in the system to enable information about treatment and prevention of the diseases based on given symptoms. At present, three diseases are included which are arthritis, thalassemia and pneumococcal. Sets of rule and fact are managed in the knowledge based system. Web based technology is used as a platform to disseminate the information to users in order for them to optimize the information appropriately. This system will benefit people who wish to increase health awareness and seek expert knowledge on the diseases by performing self-diagnosis for early disease detection.

  12. Model-based sensor diagnosis

    International Nuclear Information System (INIS)

    Milgram, J.; Dormoy, J.L.

    1994-09-01

    Running a nuclear power plant involves monitoring data provided by the installation's sensors. Operators and computerized systems then use these data to establish a diagnostic of the plant. However, the instrumentation system is complex, and is not immune to faults and failures. This paper presents a system for detecting sensor failures using a topological description of the installation and a set of component models. This model of the plant implicitly contains relations between sensor data. These relations must always be checked if all the components are functioning correctly. The failure detection task thus consists of checking these constraints. The constraints are extracted in two stages. Firstly, a qualitative model of their existence is built using structural analysis. Secondly, the models are formally handled according to the results of the structural analysis, in order to establish the constraints on the sensor data. This work constitutes an initial step in extending model-based diagnosis, as the information on which it is based is suspect. This work will be followed by surveillance of the detection system. When the instrumentation is assumed to be sound, the unverified constraints indicate errors on the plant model. (authors). 8 refs., 4 figs

  13. 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.

  14. 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.

  15. 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)

  16. Detector design for active fault diagnosis in closed-loop systems

    DEFF Research Database (Denmark)

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

    2018-01-01

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

  17. Development of on-line operator aid system (OASYSTM) for nuclear power plants

    International Nuclear Information System (INIS)

    Kang, Ki Sig; Choi, Seong Soo; Kim, Han Gon; Chang, Soon Heung; Jeong, Hee Kyo; Yi, Chul Un

    1994-01-01

    In this paper, the development of On - line operator Aid SYStem (OASYS TM ) are discussed by focusing attention on the importance of the operator's role for nuclear power plants. The OASYS TM is under development to support the operator's decision making process and to enhance the safety of a nuclear power plant by providing the plant operators with timely and proper guideline during abnormal and emergency conditions. The OASYS TM has capabilities for the signal validation/management, the alarm processing, the failure diagnosis using abnormal operating procedures, and the dynamic tracking of emergency operating procedures using function restoration guidelines and optimal recovery guidelines with a series of complex logic steps covering a broad spectrum of event sequences. The proposed system is being implemented on a SUN-4/75 Workstation using C and Quintus TM prolog language. For verification studies a full-scope real-time simulator is being used. Test results show that the OASYS TM is capable of diagnosing a plant failure quickly and providing an operator guideline with fast response time. After verification the OASYS TM will be installed in the simulator II of Kori nuclear training center

  18. Diagnosis of Thermal Efficiency of Nuclear Power Plants Using Optical Torque Sensors

    International Nuclear Information System (INIS)

    Shuichi Umezawa; Jun Adachi

    2006-01-01

    A new optical torque measuring method was applied to diagnosis of thermal efficiency of nuclear power plants. The sensor allows torque deformation of the rotor caused by power transmission to be measured without contact. Semiconductor laser beams and small pieces of stainless reflector that have bar-code patterns are employed. The intensity of the reflected laser beam is measured and then input into a computer through an APD and an A/D converter having high frequency sampling rates. The correlation analysis technique can translate these data into the torque deformation angle. This angle allows us to obtain the turbine output along with the torsional rigidity and the rotating speed of the rotor. The sensor was applied to a nuclear plant of Tokyo Electric Power Company, TEPCO, following its application success to the early combined cycle plants and the advanced combined cycle plants of TEPCO. As the turbine rotor of the nuclear power plant is less exposed than that of the combined cycle plants, the measurement position is confined to a narrow gap. In order to overcome the difficulty in installation, the shape of the sensor is modified to be long and thin. Sensor performance of the nuclear power plant was inspected over a year. The value of the torsional rigidity was analyzed by the finite element method at first. Accuracy was improved by correcting the torsional rigidity so that the value was consistent with the generator output. As a result, it is considered that the sensor performance has reached a practical use level. (authors)

  19. Aid system in the attention direction for accidents diagnosis at nuclear power plants based on artificial intelligence

    International Nuclear Information System (INIS)

    Costa, Rafael Gomes da

    2009-01-01

    Transient identification in Nuclear Power Plant (NPP) is often a very hard task and may involve a great amount of human cognition. The early identification of unexpected departures from steady state behavior is an essential step for the operation, control and accident management in NPPs. The bases for the transient identification relay on the evidence that different system faults and anomalies lead to different pattern evolution in the involved process variables. During an abnormal event, the operator must monitor a great amount of information from the instruments that represents a specific type of event Several systems based on specialist systems, neural-networks, and fuzzy logic have been developed for transient identification. In the work, we investigate the possibility of using a Neuro Fuzzy modeling tool for efficient transient identification, aiming to helping the operator crew to take decisions relative to the procedure to be followed in situations of accidents/transients at NPPs. The proposed system uses artificial neural networks (ANN) as first level transient diagnostic After the ANN has done the preliminary transient type identification, a fuzzy-logic system analyzes the results emitting reliability degree of it. A preliminary evaluation of the developed system was made at the Human-System Interface Laboratory (LABIHS). The obtained results show that the system can help the operators to take decisions during transients/accidents in the plant (author)

  20. Specification of an Expert system for the control of extraction units in reprocessing plants

    International Nuclear Information System (INIS)

    Jorda, A.; Charon, E.; Coppens, P.; Romet, J.L.

    1986-01-01

    Industrial operation of extraction units in reprocessing plants is very complex because the great number of chemical and hydraulic parameters to take into account. This complexity associated to the impossibility to see inside the active enclosures make difficult the operation processes, diagnosis and corrections. Management of parameters by an expert system will increase productivity and safety of solvent extraction in pulsed columns [fr

  1. Plant monitor system

    International Nuclear Information System (INIS)

    Scarola, K.; Jamison, D.; Manazir, R.; Rescori, R.; Harmon, D.

    1991-01-01

    An advanced control room complex for a nuclear power plant, including a discrete indicator and alarm system which is nuclear qualified for rapid response to changes in plant parameters and a component control system which together provide a discrete monitoring and control capability at a panel in the control room. A separate data processing system, which need not be nuclear qualified, provides integrated and overview information to the control room and to each panel, through CRTs and a large, overhead integrated process status overview board. The discrete indicator and alarm system and the data processing system receive inputs from common plant sensors and validate the sensor outputs to arrive at a representative value of the parameter for use by the operator during both normal and accident conditions, thereby avoiding the need for him to assimilate data from each sensor individually. The integrated process status board is at the apex of an information hierarchy that extends through four levels and provides access at each panel to the full display hierarchy. The control room panels are preferably of a modular construction, permitting the definition of inputs and outputs, the main machine interface, and the plant specific algorithms, to proceed in parallel with the fabrication of the panels, the installation of the equipment and the generic testing thereof. (author)

  2. Data monitoring system of technical diagnosis system for EAST

    International Nuclear Information System (INIS)

    Qian Jing; Weng Peide; Chen Zhuomin; Wu Yu; Xi Weibin; Luo Jiarong

    2010-01-01

    Technical diagnosis system (TDS) is an important subsystem to monitor status parameters of EAST (experimental advanced superconducting tokamak). The upgraded TDS data monitoring system is comprised of management floor, monitoring floor and field floor.. Security protection, malfunction record and analysis are designed to make the system stable, robust and friendly. During the past EAST campaigns, the data monitoring system has been operated reliably and stably. The signal conditioning system and software architecture are described. (authors)

  3. Investigation of relation between operator's mental workload and information flow in accident diagnosis tasks of nuclear power plant

    Energy Technology Data Exchange (ETDEWEB)

    Ha, Chang Hoon; Kim, Jong Hyun; Seong, Poong Hyun [KAIST, Taejon (Korea, Republic of)

    2004-07-01

    In the main control room (MCR) of a nuclear power plant (NPP), there are lots of dynamic information sources for MCR operator's situation awareness. As the human-machine interface in MCR is advanced, operator's information acquisition, information gathering and decision-making is becoming an important part to maintain the effective and safe operation of NPPs. Diagnostic task in complex and huge systems like NPP is the most difficult and mental effort-demanding for operators. This research investigates the relation between operator's mental workload and information flow in accident diagnosis tasks. The amount of information flow is quantified, using information flow model and Conant's model, a kind of information theory. For the mental workload measure, eye blink rate, blink duration, fixation time, number of fixation, and gaze direction are measured during accident diagnosis tasks. Subjective methods such as NASA-Task Load Index (NASA-TLX) and Modified Cooper-Harper (MCH) method are also used in the experiment. It is shown that the operator's mental workload has significant relation to information flow of diagnosis task. It makes possible to predict the mental workload through the quantity of the information flow of a system.

  4. failures diagnosis. Theory and practice for industrial systems

    International Nuclear Information System (INIS)

    Zwingelstein, G.

    1995-01-01

    Failure diagnosis methods represent appreciable tools for the maintenance and the improvement of availability and safety in complex industrial installations. The industrial diagnosis can be assimilated to a deterministic causality relation between the cause and the effect. This book describes the methodology associated to the resolution of the diagnosis problem applied to complex industrial system failures, and evaluates the principles of the main diagnosis methods. The introduction presents the terminology and norms used in the industry to situate the diagnosis context in the possession cost of a product. After a formulation of the diagnosis in the form of the resolution of inverse problems, the author gives details about the inductive and deductive methods and about internal and external diagnosis methods. Each method is illustrated with examples taken in the industry with recommendations about their operating limitations. Finally, a guideline summarizes the principal criteria for the selection of an industrial diagnosis method according to the available informations. (J.S.). 168 refs., 294 figs., 22 tabs., 1 annexe

  5. The application of plant information system on third Qinshan nuclear power plant

    International Nuclear Information System (INIS)

    Liu Wangtian

    2005-01-01

    Plant overall control has been applied in Qinshan Nuclear Power Plant, which enhances the security of plant operation, but it is not enough to improve the technical administration level. In order to integrate the overall information and to improve the technical administration level more. Third Qinshan Nuclear Power Plant applies the plant information system. This thesis introduces the application of plant information system in Third Qinshan Nuclear Power Plant and the effect to the plant after the system is carried into execution, in addition, it does more analysis and exceptions for application of plant information system in the future. (authors)

  6. [A computer-aided image diagnosis and study system].

    Science.gov (United States)

    Li, Zhangyong; Xie, Zhengxiang

    2004-08-01

    The revolution in information processing, particularly the digitizing of medicine, has changed the medical study, work and management. This paper reports a method to design a system for computer-aided image diagnosis and study. Combined with some good idea of graph-text system and picture archives communicate system (PACS), the system was realized and used for "prescription through computer", "managing images" and "reading images under computer and helping the diagnosis". Also typical examples were constructed in a database and used to teach the beginners. The system was developed by the visual developing tools based on object oriented programming (OOP) and was carried into operation on the Windows 9X platform. The system possesses friendly man-machine interface.

  7. Experiences with an expert system technology for real-time monitoring and diagnosis of industrial processes

    International Nuclear Information System (INIS)

    Chou, Q.B.; Mylopoulos, J.; Opala, J.

    1996-01-01

    The complexity of modern industrial processes and the large amount of data available to their operators make it difficult to monitor their status and diagnose potential failures. Although there have been many attempts to apply knowledge-based technologies to this problem, there have not been any convincing success. This paper describes recent experiences with a technology that combines artificial intelligence and simulation techniques for building real-time monitoring and diagnosis systems. A prototype system for monitoring and diagnosing the feedwater system of a nuclear power plant built using this technology is described. The paper then describes several interesting classes of failures that the prototype is capable of diagnosing. (author). 19 refs, 6 figs

  8. Experiences with an expert system technology for real-time monitoring and diagnosis of industrial processes

    Energy Technology Data Exchange (ETDEWEB)

    Chou, Q B [Ontario Hydro, Toronto, ON (Canada); Mylopoulos, J [Toronto Univ., ON (Canada); Opala, J [CAE Electronics, Montreal, Quebec (Canada)

    1997-12-31

    The complexity of modern industrial processes and the large amount of data available to their operators make it difficult to monitor their status and diagnose potential failures. Although there have been many attempts to apply knowledge-based technologies to this problem, there have not been any convincing success. This paper describes recent experiences with a technology that combines artificial intelligence and simulation techniques for building real-time monitoring and diagnosis systems. A prototype system for monitoring and diagnosing the feedwater system of a nuclear power plant built using this technology is described. The paper then describes several interesting classes of failures that the prototype is capable of diagnosing. (author). 19 refs, 6 figs.

  9. ITER plant systems

    International Nuclear Information System (INIS)

    Kolbasov, B.; Barnes, C.; Blevins, J.

    1991-01-01

    As part of a series of documents published by the IAEA that summarize the results of the Conceptual Design Activities for the ITER project, this publication describes the conceptual design of the ITER plant systems, in particular (i) the heat transport system, (ii) the electrical distribution system, (iii) the requirements for radioactive equipment handling, the hot cell, and waste management, (iv) the supply system for fluids and operational chemicals, (v) the qualitative analyses of failure scenarios and methods of burn stability control and emergency shutdown control, (vi) analyses of tokamak building functions and design requirements, (vii) a plant layout, and (viii) site requirements. Refs, figs and tabs

  10. Information system for diagnosis of respiratory system diseases

    Science.gov (United States)

    Abramov, G. V.; Korobova, L. A.; Ivashin, A. L.; Matytsina, I. A.

    2018-05-01

    An information system is for the diagnosis of patients with lung diseases. The main problem solved by this system is the definition of the parameters of cough fragments in the monitoring recordings using a voice recorder. The authors give the recognition criteria of recorded cough moments, audio records analysis. The results of the research are systematized. The cough recognition system can be used by the medical specialists to diagnose the condition of the patients and to monitor the process of their treatment.

  11. Monitoring and diagnosis systems to improve nuclear power plant reliability and safety. Proceedings of the specialists` meeting

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1997-12-31

    The 50 participants, representing 21 Member States (Argentina, Austria, Belgium, Canada, Czech Republic, France, Germany, Hungary, Japan, Netherlands, Norway, Russian Federation, Slovak Republic, Slovenia, Spain, Sweden, Switzerland, Turkey, Ukraine, UK and USA), reviewed the current approaches in Member States in the area of monitoring and diagnosis systems. The Meeting attempted to identify advanced techniques in the field of diagnostics of electrical and mechanical components for safety and operation improvements, reviewed actual practices and experiences related to the application of those systems with special emphasis on real occurrences, exchanged current experiences with diagnostics as a means for predictive maintenance. Refs, figs, tabs.

  12. Monitoring and diagnosis systems to improve nuclear power plant reliability and safety. Proceedings of the specialists' meeting

    International Nuclear Information System (INIS)

    1996-01-01

    The 50 participants, representing 21 Member States (Argentina, Austria, Belgium, Canada, Czech Republic, France, Germany, Hungary, Japan, Netherlands, Norway, Russian Federation, Slovak Republic, Slovenia, Spain, Sweden, Switzerland, Turkey, Ukraine, UK and USA), reviewed the current approaches in Member States in the area of monitoring and diagnosis systems. The Meeting attempted to identify advanced techniques in the field of diagnostics of electrical and mechanical components for safety and operation improvements, reviewed actual practices and experiences related to the application of those systems with special emphasis on real occurrences, exchanged current experiences with diagnostics as a means for predictive maintenance. Refs, figs, tabs

  13. Least-cost failure diagnosis in uncertain reliability systems

    International Nuclear Information System (INIS)

    Cox, Louis Anthony; Chiu, Steve Y.; Sun Xiaorong

    1996-01-01

    In many textbook solutions, for systems failure diagnosis problems studied using reliability theory and artificial intelligence, the prior probabilities of different failure states can be estimated and used to guide the sequential search for failed components after the whole system fails. In practice, however, both the component failure probabilities and the structure function of the system being examined--i.e., the mapping between the states of its components and the state of the system--may not be known with certainty. At best:, the probabilities of different hypothesized system descriptions, each specifying the component failure probabilities and the system's structure function, may be known to a useful approximation, perhaps based on sample data and previous experience. Cost-effective diagnosis of the system's failure state is then a challenging problem. Although the probabilities of component failures are aleatory, uncertainties about these probabilities and about the system structure function are epistemic. This paper examines how to make best use of both epistemic prior probabilities for system descriptions and the information gleaned from costly inspections of component states after the system fails, to minimize the average cost of identifying the failure state. Two approaches are introduced for systems dominated by aleatory uncertainties, one motivated by information theory and the other based on the idea of trying to prove a hypothesis about the identity of the failure state as efficiently as possible. While the general problem of cost-effective failure diagnosis is computationally intractable (NP-hard), both heuristics provide useful approximations on small to moderate sized problems and optimal results for certain common types of reliability systems, including series, parallel, parallel-series, and k-out-of-n systems. A hybrid heuristic that adaptively chooses which heuristic to apply next after any sequence of observations (component test results

  14. Bond graph model-based fault diagnosis of hybrid systems

    CERN Document Server

    Borutzky, Wolfgang

    2015-01-01

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

  15. A Learning Health Care System Using Computer-Aided Diagnosis.

    Science.gov (United States)

    Cahan, Amos; Cimino, James J

    2017-03-08

    Physicians intuitively apply pattern recognition when evaluating a patient. Rational diagnosis making requires that clinical patterns be put in the context of disease prior probability, yet physicians often exhibit flawed probabilistic reasoning. Difficulties in making a diagnosis are reflected in the high rates of deadly and costly diagnostic errors. Introduced 6 decades ago, computerized diagnosis support systems are still not widely used by internists. These systems cannot efficiently recognize patterns and are unable to consider the base rate of potential diagnoses. We review the limitations of current computer-aided diagnosis support systems. We then portray future diagnosis support systems and provide a conceptual framework for their development. We argue for capturing physician knowledge using a novel knowledge representation model of the clinical picture. This model (based on structured patient presentation patterns) holds not only symptoms and signs but also their temporal and semantic interrelations. We call for the collection of crowdsourced, automatically deidentified, structured patient patterns as means to support distributed knowledge accumulation and maintenance. In this approach, each structured patient pattern adds to a self-growing and -maintaining knowledge base, sharing the experience of physicians worldwide. Besides supporting diagnosis by relating the symptoms and signs with the final diagnosis recorded, the collective pattern map can also provide disease base-rate estimates and real-time surveillance for early detection of outbreaks. We explain how health care in resource-limited settings can benefit from using this approach and how it can be applied to provide feedback-rich medical education for both students and practitioners. ©Amos Cahan, James J Cimino. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 08.03.2017.

  16. Development of plant maintenance systems

    International Nuclear Information System (INIS)

    Tomita, Jinji; Ike, Masae; Nakayama, Kenji; Kato, Hisatomo

    1989-01-01

    Toshiba is making active efforts for the continuing improvement of reliability and maintainability of operating nuclear power plants. As a part of these efforts, the company has developed new maintenance administration systems, diagnostic monitoring facilities for plant equipments, computer-aided expert systems, and remote-controlled machines for maintenance work. The maintenance administration systems provide efficient work plans and data acquisition capabilities for the management of personnel and equipments involved in nuclear power plant maintenance. The plant diagnostic facilities monitor and diagnose plant conditions for preventive maintenance, as well as enabling rapid countermeasures to be carried out should they be required. Expert systems utilizing artificial intelligence (AI) technology are also employed. The newly developed remote-controlled machines are useful tools for the maintenance inspection of equipment which can not be easily accessed. (author)

  17. An intelligent system for monitoring and diagnosis of the CO{sub 2} capture process

    Energy Technology Data Exchange (ETDEWEB)

    Zhou, Q.; Chan, C.W.; Tontiwachwuthikul, P. [University of Regina, Regina, SK (Canada). Faculty of Engineering

    2011-07-15

    Amine-based carbon dioxide capture has been widely considered as a feasible ideal technology for reducing large-scale CO{sub 2} emissions and mitigating global warming. The operation of amine-based CO{sub 2} capture is a complicated task, which involves monitoring over 100 process parameters and careful manipulation of numerous valves and pumps. The current research in the field of CO{sub 2} capture has emphasized the need for improving CO{sub 2} capture efficiency and enhancing plant performance. In the present study, artificial intelligence techniques were applied for developing a knowledge-based expert system that aims at effectively monitoring and controlling the CO{sub 2} capture process and thereby enhancing CO{sub 2} capture efficiency. In developing the system, the inferential modeling technique (IMT) was applied to analyze the domain knowledge and problem-solving techniques, and a knowledge base was developed on DeltaV Simulate. The expert system helps to enhance CO{sub 2} capture system performance and efficiency by reducing the time required for diagnosis and problem solving if abnormal conditions occur. The expert system can be used as a decision-support tool that helps inexperienced operators control the plant: it can be used also for training novice operators.

  18. 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

  19. CT diagnosis of congenital anomalies of the central nervous system

    International Nuclear Information System (INIS)

    Mori, Koreaki

    1980-01-01

    In the diagnosis of central nervous system congenital anomalies, understanding of embryology of the central nervous system and pathophysiology of each anomaly are essential. It is important for clinical approach to central nervous system congenital anomalies to evaluate the size of the head and tention of the anterior fontanelle. Accurate diagnosis of congenital anomalies depends on a correlation of CT findings to clinical pictures. Clinical diagnosis of congenital anomalies should include prediction of treatability and prognosis, in addition to recognition of a disease. (author)

  20. The appropriateness of the systematic framework to develop diagnosis procedures of nuclear power plants-an experimental verification

    International Nuclear Information System (INIS)

    Park, Jinkyun; Jung, Wondea

    2006-01-01

    It has been well recognized that a diagnosis procedure that allows operators to successfully identify the nature of an on-going event is inevitable for an effective and appropriate recovery. Unfortunately, studies for a framework that can suggest a unified and consistent process in constructing a serviceable diagnosis procedure seem to be scant. Thus, Park et al. have suggested a systematic framework that can be used to construct a useful diagnosis procedure. In addition, the diagnosis procedure that is currently in use at the reference nuclear power plant (NPP) is reformed in order to demonstrate the appropriateness of the suggested framework. However, the necessity of a well-designed experiment is proposed to confirm the appropriateness of the suggested framework. In this regard, in this study, an experiment is conducted using a full-scope simulator of the reference NPP. From the experiment, two sets of operators' diagnosis performance data are collected, and then they are compared to investigate the change of an operator's diagnosis performance with respect to two types of diagnosis procedures. As a result, it is shown that an operator's diagnosis performance is improved when the revised diagnosis procedure is used. Therefore, it is reasonable to conclude that the suggested framework is useful in constructing an effective diagnosis procedure

  1. A statistical-based approach for fault detection and diagnosis in a photovoltaic system

    KAUST Repository

    Garoudja, Elyes

    2017-07-10

    This paper reports a development of a statistical approach for fault detection and diagnosis in a PV system. Specifically, the overarching goal of this work is to early detect and identify faults on the DC side of a PV system (e.g., short-circuit faults; open-circuit faults; and partial shading faults). Towards this end, we apply exponentially-weighted moving average (EWMA) control chart on the residuals obtained from the one-diode model. Such a choice is motivated by the greater sensitivity of EWMA chart to incipient faults and its low-computational cost making it easy to implement in real time. Practical data from a 3.2 KWp photovoltaic plant located within an Algerian research center is used to validate the proposed approach. Results show clearly the efficiency of the developed method in monitoring PV system status.

  2. Learning and case-based reasoning for faults diagnosis-aiding in nuclear power plants

    International Nuclear Information System (INIS)

    Nicolini, C.

    1998-01-01

    The aim of this thesis is the design of a faults diagnosis-aiding system in a nuclear facility of the Cea. Actually the existing system allows the optimization of the production processes in regular operating conditions. Meanwhile during accidental events, the alarms, managed by threshold, are bringing no relevant information. To increase the reliability and the safety, the human operator needs a faults diagnosis-aiding system. The developed system, SECAPI, combines problem solving techniques and automatic learning techniques, that allow the diagnosis and the the simulation of various faults happening on nuclear facilities. Its reasoning principle uses case-based and rules-based techniques. SECAPI owns a learning module which reads out knowledge connected with faults. It can then simulate various faults, using the inductive logical computing. SECAPI has been applied on a radioactive tritium treatment operating channel, at the Cea with good results. (A.L.B.)

  3. An expert system in medical diagnosis

    International Nuclear Information System (INIS)

    Raboanary, R.; Raoelina Andriambololona; Soffer, J.; Raboanary, J.

    2001-01-01

    Health problem is still a crucial one in some countries. It is so important that it becomes a major handicap in economic and social development. In order to solve this problem, we have conceived an expert system that we called MITSABO, which means TO HEAL, to help the physicians to diagnose tropical diseases. It is clear that by extending the data base and the knowledge base, we can extend the application of the software to more general areas. In our expert system, we used the concept of 'self organization' of neural network based on the determination of the eigenvalues and the eigenvectors associated to the correlation matrix XX t . The projection of the data on the two first eigenvectors gives a classification of the diseases which is used to get a first approach in the diagnosis of the patient. This diagnosis is improved by using an expert system which is built from the knowledge base.

  4. Decision Support System for Hepatitis Disease Diagnosis using Bayesian Network

    Directory of Open Access Journals (Sweden)

    Shamshad Lakho

    2017-12-01

    Full Text Available Medical judgments are tough and challenging as the decisions are often based on the deficient and ambiguous information. Moreover, the result of decision process has direct effects on human lives. The act of human decision declines in emergency situations due to the complication, time limit, and high risks. Therefore, provision of medical diagnosis plays a dynamic role, specifically in the preliminary stage when a physician has limited diagnosis experience and identifies the directions to be taken for the treatment process. Computerized Decision Support Systems have brought a revolution in the medical diagnosis. These automatic systems support the diagnosticians in the course of diagnosis. The major role of Decision Support Systems is to support the medical personnel in decision-making procedures regarding disease diagnosis and treatment recommendation. The proposed system provides easy support in Hepatitis disease recognition. The system is developed using the Bayesian network model. The physician provides the input to the system in the form of symptoms stated by the patient. These signs and symptoms match with the casual relationships present in the knowledge model. The Bayesian network infers conclusion from the knowledge model and calculates the probability of occurrence of Hepatitis B, C and D disorders.

  5. Wind power plant system services

    DEFF Research Database (Denmark)

    Basit, Abdul; Altin, Müfit

    Traditionally, conventional power plants have the task to support the power system, by supplying power balancing services. These services are required by the power system operators in order to secure a safe and reliable operation of the power system. However, as in the future the wind power...... is going more and more to replace conventional power plants, the sources of conventional reserve available to the system will be reduced and fewer conventional plants will be available on-line to share the regulation burden. The reliable operation of highly wind power integrated power system might...... then beat risk unless the wind power plants (WPPs) are able to support and participate in power balancing services. The objective of this PhD project is to develop and analyse control strategies which can increase the WPPs capability to provide system services, such as active power balancing control...

  6. The structure of an expert system to diagnose and supply a corrective procedure for nuclear power plant malfunctions

    International Nuclear Information System (INIS)

    Hajek, B.K.; Stasenko, J.E.; Hashemi, S.; Bhatnagar, R.; Punch, W.F. III; Yamada, N.

    1987-01-01

    During the past two years, two prototype knowledge based systems have been developed at the Ohio State University. These systems were the result of collaboration between the Nuclear Engineering Program and the Laboratory for Artificial Intelligence Research (LAIR). The first system uses hierarchical classification to diagnose malfunctions of the coolant system in a General Electric Boiling Water Reactor (BWR). The second system provides a plan of action, through a process of dynamic procedure management, to stabilize the plant once an abnormal transient has occurred. The objective of this paper is to discuss the structure that has been designed to integrate the two systems. The combined system will be capable of informing plant personnel about the nature of malfunctions, and of supplying to the operator the most direct corrective procedure available. Two important features of the integrated system are faulty sensor detection, based on malfunction context and unlike sensor data, and procedure management based on the initial state of the plant. Since the two knowledge based systems were developed separately, the integration has required a separate component currently under development, the Plant Status Monitoring System (PSMS). The task of PSMS is to monitor plant parameters in order to detect an abnormal condition developing within the plant. Based on the nature of the event, PSMS is capable of directing control to either the procedure management or diagnosis component. The integrated system plays only an advisory role, and any suggested action would be executed by the plant personnel

  7. The System 80+ Standard Plant Information Management System

    Energy Technology Data Exchange (ETDEWEB)

    Turk, R.S.; Bryan, R.E. [ABB Combuions Engineering Nuclear Systems (United States)

    1998-07-01

    Historically, electric nuclear power plant owners, following the completion of construction and startup, have been left with a mountain of hard-copy documents and drawings. Hundreds of thousands of hours are spent searching for relevant documents and, in most cases, the documents found require many other documents and drawings to fully understand the design basis. All too often the information is incomplete, and eventually becomes obsolete. In the U.S., utilities spend millions of dollars to discover design basis information and update as-built data for each plant. This information must then be stored in an easily accessed usable form to assist satisfy regulatory requirements and to improve plant operating efficiency. ABB Combustion Engineering Nuclear Systems (ABB-CE) has an active program to develop a state-of-the-art Plant Information Management System (IMS) for its advanced light water reactor, the System 80+TM Standard Plant Design. This program is supported by ABB's Product Data Management (PDM) and Computer Aided Engineering (CAE) efforts world wide. This paper describes the System 80+ plant IMS and how it will be used during the entire life cycle of the plant. (author)

  8. The System 80+ Standard Plant Information Management System

    International Nuclear Information System (INIS)

    Turk, R.S.; Bryan, R.E.

    1998-01-01

    Historically, electric nuclear power plant owners, following the completion of construction and startup, have been left with a mountain of hard-copy documents and drawings. Hundreds of thousands of hours are spent searching for relevant documents and, in most cases, the documents found require many other documents and drawings to fully understand the design basis. All too often the information is incomplete, and eventually becomes obsolete. In the U.S., utilities spend millions of dollars to discover design basis information and update as-built data for each plant. This information must then be stored in an easily accessed usable form to assist satisfy regulatory requirements and to improve plant operating efficiency. ABB Combustion Engineering Nuclear Systems (ABB-CE) has an active program to develop a state-of-the-art Plant Information Management System (IMS) for its advanced light water reactor, the System 80+TM Standard Plant Design. This program is supported by ABB's Product Data Management (PDM) and Computer Aided Engineering (CAE) efforts world wide. This paper describes the System 80+ plant IMS and how it will be used during the entire life cycle of the plant. (author)

  9. Development of an integrated condition monitoring and diagnostic system for motor-operated valves used in nuclear power plant

    International Nuclear Information System (INIS)

    Carneiro, Alvaro Luiz Guimaraes

    2003-01-01

    The reliability question of the components, specifically of motor operated valves, became one of the most important issues to be investigated in nuclear power plants, considering security and life plant extension. Therefore, the necessity of improvements in monitoring and diagnosis methods started to be of extreme relevance in the maintenance predictive field, establishing as main goal the reliability and readiness of the system components. Specially in nuclear power plants, the predictive maintenance contributes in the security factor in order to diagnosis in advance the occurrence of a possible failure, preventing severe situations. It also presents a contribution on the economic side by establishing a better maintenance programming, and reducing unexpected shutdown. The development of non intrusive monitoring and diagnostic method makes it possible to identify malfunctions in plant components during normal plant operation. This dissertation presents the development of an integrated condition monitoring system for motor-operated valves used in nuclear power plants. The methodology used in this project is based on the electric motor power signatures analysis, during the closing and opening stroke time of the valve. Once the measurements baseline diagnostic of the motor-operated valve is taken, it is possible to detect long-term deviations during valve lifetime, detecting in advance valve failures. The system implements two parallel techniques for detection and categorization of anomalies: expert system using fuzzy logic based on rules and knowledge base, providing a systematic approach for decision making, and the Wavelet Transform Technique, where the main goal is to obtain more detailed information contained in the measured data, identifying and characterizing the transients phenomena in the time and frequency domains, correlating them to failures situations in the incipient stage. The conditioning monitoring and diagnostic system was designed and implemented at

  10. Application of diagnostic system for diesel engines in nuclear power plant

    International Nuclear Information System (INIS)

    Yoshinaga, Takeshi

    2004-01-01

    The diagnostic system for diesel engines makes a diagnosis of secular change and abnormal indications of diesel engines (DG) by combination of characteristic analysis of engine, lubricating oil, fuel oil, and cooling water. The principles of diagnostic system for DG, results of confirmation of the efficiency and the maintenance plan for DG in the Japan Atomic Power Company are described. DG in the company is classified to a safety device in order to supply the power source to the Emergency Core Cooling System etc., when the power source in the plant is lost, for example, at lightning struck. Characteristics of DG, outline of the diagnostic system for DG, diagnostic technologies such as engine signature analysis, chemical analysis of samples, temperature measurement, degradation mode of DG, and training in the company are stated. (S.Y.)

  11. Application of monitoring, diagnosis, and prognosis in thermal performance analysis for nuclear power plants

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Hyeong Min; Heo, Gyun Young [Kyung Hee University, Yongin (Korea, Republic of); Na, Man Gyun [Chosun University, Gwangju (Korea, Republic of)

    2014-12-15

    As condition-based maintenance (CBM) has risen as a new trend, there has been an active movement to apply information technology for effective implementation of CBM in power plants. This motivation is widespread in operations and maintenance, including monitoring, diagnosis, prognosis, and decision-making on asset management. Thermal efficiency analysis in nuclear power plants (NPPs) is a longstanding concern being updated with new methodologies in an advanced IT environment. It is also a prominent way to differentiate competitiveness in terms of operations and maintenance costs. Although thermal performance tests implemented using industrial codes and standards can provide officially trustworthy results, they are essentially resource-consuming and maybe even a hind-sighted technique rather than a foresighted one, considering their periodicity. Therefore, if more accurate performance monitoring can be achieved using advanced data analysis techniques, we can expect more optimized operations and maintenance. This paper proposes a framework and describes associated methodologies for in-situ thermal performance analysis, which differs from conventional performance monitoring. The methodologies are effective for monitoring, diagnosis, and prognosis in pursuit of CBM. Our enabling techniques cover the intelligent removal of random and systematic errors, deviation detection between a best condition and a currently measured condition, degradation diagnosis using a structured knowledge base, and prognosis for decision-making about maintenance tasks. We also discuss how our new methods can be incorporated with existing performance tests. We provide guidance and directions for developers and end-users interested in in-situ thermal performance management, particularly in NPPs with large steam turbines.

  12. Application of monitoring, diagnosis, and prognosis in thermal performance analysis for nuclear power plants

    International Nuclear Information System (INIS)

    Kim, Hyeong Min; Heo, Gyun Young; Na, Man Gyun

    2014-01-01

    As condition-based maintenance (CBM) has risen as a new trend, there has been an active movement to apply information technology for effective implementation of CBM in power plants. This motivation is widespread in operations and maintenance, including monitoring, diagnosis, prognosis, and decision-making on asset management. Thermal efficiency analysis in nuclear power plants (NPPs) is a longstanding concern being updated with new methodologies in an advanced IT environment. It is also a prominent way to differentiate competitiveness in terms of operations and maintenance costs. Although thermal performance tests implemented using industrial codes and standards can provide officially trustworthy results, they are essentially resource-consuming and maybe even a hind-sighted technique rather than a foresighted one, considering their periodicity. Therefore, if more accurate performance monitoring can be achieved using advanced data analysis techniques, we can expect more optimized operations and maintenance. This paper proposes a framework and describes associated methodologies for in-situ thermal performance analysis, which differs from conventional performance monitoring. The methodologies are effective for monitoring, diagnosis, and prognosis in pursuit of CBM. Our enabling techniques cover the intelligent removal of random and systematic errors, deviation detection between a best condition and a currently measured condition, degradation diagnosis using a structured knowledge base, and prognosis for decision-making about maintenance tasks. We also discuss how our new methods can be incorporated with existing performance tests. We provide guidance and directions for developers and end-users interested in in-situ thermal performance management, particularly in NPPs with large steam turbines.

  13. PSAD, a prototype for monitoring and aid to diagnosis of French PWRs

    International Nuclear Information System (INIS)

    Jousselin, A.; Bourgeois, P.; Busquet, J.L.; Monnier, B.; Mouhamed, B.

    1996-01-01

    In order to improve safety and availability in its nuclear power plants, EDF has designed a new generation of monitoring systems integrated into a workstation for monitoring and aid to diagnosis (PSAD). These systems perform on-line monitoring of the main power plant components and PSAD stations provide homogenous aids ro diagnosis which enable plant personnel to diagnose the mechanical behavior of plant equipments. The objective of PSAD is to provide them with high-efficiency and user-friendly tools which can considerably free them from routine tasks. PSAD has a flexible architecture, guaranteeing optimum distribution of computing power to make it available where it is needed, thus enhancing the quality of the information. Its architecture includes diagnosis support software based on artificial intelligence technology which can dialogue with real-time or deferred-time processing software and a relational database. The first version of the prototype is working on a french plant at Tricastin. This version includes the software for the host structure and two monitoring functions: the reactor coolant pumps and the turbo-generator monitoring functions. Internal Structures Monitoring function (ISM) and Loose Parts Detection function (LPD) are under development and should be integrated into PSAD prototype in 1996. (author). 5 refs., 6 figs

  14. A landscape simulation system for power plants

    International Nuclear Information System (INIS)

    Yoshinaga, Toshiaki; Yoshida, Miki; Usami, Yoshiaki.

    1997-01-01

    As scenes of power plants give many influences to environments, the plants that harmonized with the environments are demanded. We developed a landscape simulation system for the plants by using computer graphics technologies. This system has functions to generate realistic images about plant buildings and environments. Since the system contains information of ridge lines in addition to usual terrain data, the terrain shapes are expressed more precisely. Because the system enables users to visualize plant construction plans, the advance evaluations of plant scenes become possible. We regard this system as useful for environmental assessment of power plants. (author)

  15. Consultation system for image diagnosis: Report formation support system

    International Nuclear Information System (INIS)

    Ikeda, M.; Sakuma, S.; Ishigaki, T.; Suzuki, K.; Oikawa, K.

    1987-01-01

    The authors developed a consultation system for image diagnosis, involving artificial intelligence ideas. In this system, the authors proposed a new report formation support system and implemented it in lymphangiography. This support system starts with the input of image interpretation. The input process is made mainly by selecting items. This system encodes the input findings into the semantic network, which is represented as a directed graph, and it reserves them into the knowledge database in the above structure. Finally, the output (report) is made in the near natural language, which corresponds to the input findings

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

    Directory of Open Access Journals (Sweden)

    Chin-Tsung Hsieh

    2014-01-01

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

  17. Transmission and distribution of information in power plants

    International Nuclear Information System (INIS)

    Pinkernell, H.

    1978-01-01

    Operation of modern large-site power plants is no longer imaginable without facilities for automatic control. Brown-Boveri Company has developed a promising control system for power plants called Procontrol k. An essential piece of the system is DATRAS k, a digital bus-oriented data transport system for transmitting and distributing signals in power plants. DATRAS will save a large amount of cables and reduce the constructional effect. It offers opportunities for diagnosis and service and by means of continuous monitoring of all system components it will essentially improve plant availability. (orig.) [de

  18. Heartbeat-based error diagnosis framework for distributed embedded systems

    Science.gov (United States)

    Mishra, Swagat; Khilar, Pabitra Mohan

    2012-01-01

    Distributed Embedded Systems have significant applications in automobile industry as steer-by-wire, fly-by-wire and brake-by-wire systems. In this paper, we provide a general framework for fault detection in a distributed embedded real time system. We use heartbeat monitoring, check pointing and model based redundancy to design a scalable framework that takes care of task scheduling, temperature control and diagnosis of faulty nodes in a distributed embedded system. This helps in diagnosis and shutting down of faulty actuators before the system becomes unsafe. The framework is designed and tested using a new simulation model consisting of virtual nodes working on a message passing system.

  19. Plant growth and gas balance in a plant and mushroom cultivation system

    Science.gov (United States)

    Kitaya, Y.; Tani, A.; Kiyota, M.; Aiga, I.

    1994-11-01

    In order to obtain basic data for construction of a plant cultivation system incorporating a mushroom cultivation subsystem in the CELSS, plant growth and atmospheric CO2 balance in the system were investigated. The plant growth was promoted by a high level of CO2 which resulted from the respiration of the mushroom mycelium in the system. The atmospheric CO2 concentration inside the system changed significantly due to the slight change in the net photosynthetic rate of plants and/or the respiration rate of the mushroom when the plant cultivation system combined directly with the mushroom cultivation subsystem.

  20. Plant Systems Biology (editorial)

    Science.gov (United States)

    In June 2003, Plant Physiology published an Arabidopsis special issue devoted to plant systems biology. The intention of Natasha Raikhel and Gloria Coruzzi, the two editors of this first-of-its-kind issue, was ‘‘to help nucleate this new effort within the plant community’’ as they considered that ‘‘...

  1. Fault Diagnosis in Deaerator Using Fuzzy Logic

    Directory of Open Access Journals (Sweden)

    S Srinivasan

    2007-01-01

    Full Text Available In this paper a fuzzy logic based fault diagnosis system for a deaerator in a power plant unit is presented. The system parameters are obtained using the linearised state space deaerator model. The fuzzy inference system is created and rule base are evaluated relating the parameters to the type and severity of the faults. These rules are fired for specific changes in system parameters and the faults are diagnosed.

  2. TOSHIBA CAE system for nuclear power plant

    International Nuclear Information System (INIS)

    Machiba, Hiroshi; Sasaki, Norio

    1990-01-01

    TOSHIBA aims to secure safety, increase reliability and improve efficiency through the engineering for nuclear power plant using Computer Aided Engineering (CAE). TOSHIBA CAE system for nuclear power plant consists of numbers of sub-systems which had been integrated centering around the Nuclear Power Plant Engineering Data Base (PDBMS) and covers all stage of engineering for nuclear power plant from project management, design, manufacturing, construction to operating plant service and preventive maintenance as it were 'Plant Life-Cycle CAE System'. In recent years, TOSHIBA has been devoting to extend the system for integrated intelligent CAE system with state-of-the-art computer technologies such as computer graphics and artificial intelligence. This paper shows the outline of CAE system for nuclear power plant in TOSHIBA. (author)

  3. Fault diagnosis for discrete event systems: Modelling and verification

    International Nuclear Information System (INIS)

    Simeu-Abazi, Zineb; Di Mascolo, Maria; Knotek, Michal

    2010-01-01

    This paper proposes an effective way for diagnosis of discrete-event systems using a timed-automaton. It is based on the model-checking technique, thanks to time analysis of the timed model. The paper proposes a method to construct all the timed models and details the different steps used to obtain the diagnosis path. A dynamic model with temporal transitions is proposed in order to model the system. By 'dynamical model', we mean an extension of timed automata for which the faulty states are identified. The model of the studied system contains the faultless functioning states and all the faulty states. Our method is based on the backward exploitation of the dynamic model, where all possible reverse paths are searched. The reverse path is the connection of the faulty state to the initial state. The diagnosis method is based on the coherence between the faulty occurrence time and the reverse path length. A real-world batch process is used to demonstrate the modelling steps and the proposed backward time analysis method to reach the diagnosis results.

  4. Remote diagnosis as used for mechanized parking systems

    Science.gov (United States)

    Humberg, Heinz; Maeder, Hans Friedrich; Will, Frank

    1992-10-01

    The new possibilities offered by worldwide data transmission networks, which are being used for the remote diagnosis of mechanized parking systems are discussed. This has led to a reduction in service costs for systems installed in Asia and elsewhere. The principles of the mechanized multistorey car park and their control concept are described. The parking facilities are fully geared up for remote diagnosis, the key functions of which are: data collection, data storage, data transmission, and data evaluation. The reports transmitted from the parking facility are analyzed using an evaluation system. The objectives are to detect impending component failures and to quickly identify the causes of irregularities which have occurred. The evaluation system can be easily adapted for other applications.

  5. Stroke Diagnosis using Microstrip Patch Antennas Based on Microwave Tomography Systems

    Directory of Open Access Journals (Sweden)

    Sakthisudhan K

    2017-03-01

    Full Text Available Microwave tomography (MT based on stroke diagnosis is one of the alternative methods for determinations of the haemorrhagic, ischemic and stroke in brain nervous systems. It is focusing on the brain imaging, continuous monitoring, and preclinical applications. It provides cost effective system and able to use the rural and urban medical clinics that lack the necessary resources in effective stroke diagnosis during emerging applications in road accident and pre-ambulance clinical treatment. In the early works, the design of microstrip patch antennas (MPAs involved the implementation of MT system. Consequently, the MT system presented a few limitations since it required an efficient MPA design with appropriate parameters. Moreover, there were no specific diagnosis modules and body centric features in it. The present research proposes the MPA designs in the forms of diagnosis modules and implements it on the MT system.

  6. 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...

  7. Monodetector system for diagnosis (DETEC)

    International Nuclear Information System (INIS)

    Alonso Abad, D.; Fernandez Paz, J.L.; Lopez Torres, O.M. and others

    1997-01-01

    Several clinical searches can be done using The Single Probe Diagnosis System: Thyroid uptake, Eritroferrocinetic studies, Studies of survival of hematite's, Studies of peripheral vascular diseases , Studies of gastric emptying time. The system can be set spectrometric parameters for several radionuclides ( 131I , 125I , 99mT c, 59F e, 51C r, 57G a, 57C o) used in Nuclear Medicine by itself. It is a unit made of a mechanical structure and a detection-measured system based in a Z80 microprocessor. Data obtained are processed and can be printed or sent to a P C by RS-232 protocol

  8. Proceedings: Power Plant Electric Auxiliary Systems Workshop

    International Nuclear Information System (INIS)

    1992-06-01

    The EPRI Power Plant Electric Auxiliary Systems Workshop, held April 24--25, 1991, in Princeton, New Jersey, brought together utilities, architect/engineers, and equipment suppliers to discuss common problems with power plant auxiliary systems. Workshop participants presented papers on monitoring, identifying, and solving problems with auxiliary systems. Panel discussions focused on improving systems and existing and future plants. The solutions presented to common auxiliary system problems focused on practical ideas that can enhance plant availability, reduce maintenance costs, and simplify the engineering process. The 13 papers in these proceedings include: Tutorials on auxiliary electrical systems and motors; descriptions of evaluations, software development, and new technologies used recently by electric utilities; an analysis of historical performance losses caused by power plant auxiliary systems; innovative design concepts for improving auxiliary system performance in future power plants

  9. Active fault diagnosis in closed-loop systems

    DEFF Research Database (Denmark)

    Niemann, Hans Henrik; Poulsen, Niels Kjølstad

    2005-01-01

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

  10. Water quality diagnosis system

    International Nuclear Information System (INIS)

    Nagase, Makoto; Asakura, Yamato; Sakagami, Masaharu

    1989-01-01

    By using a model representing a relationship between the water quality parameter and the dose rate in primary coolant circuits of a water cooled reactor, forecasting for the feature dose rate and abnormality diagnosis for the water quality are conducted. The analysis model for forecasting the reactor water activity or the dose rate receives, as the input, estimated curves for the forecast Fe, Ni, Co concentration in feedwater or reactor water pH, etc. from the water quality data in the post and forecasts the future radioactivity or dose rate in the reactor water. By comparing the result of the forecast and the setting value such as an aimed value, it can be seen whether the water quality at present or estimated to be changed is satisfactory or not. If the quality is not satisfactory, it is possible to take an early countermeasure. Accordingly, the reactor water activity and the dose rate can be kept low. Further, the basic system constitution, diagnosis algorithm, indication, etc. are identical between BWR and PWR reactors, except for only the difference in the mass balance. (K.M.)

  11. Portable multispectral imaging system for oral cancer diagnosis

    Science.gov (United States)

    Hsieh, Yao-Fang; Ou-Yang, Mang; Lee, Cheng-Chung

    2013-09-01

    This study presents the portable multispectral imaging system that can acquire the image of specific spectrum in vivo for oral cancer diagnosis. According to the research literature, the autofluorescence of cells and tissue have been widely applied to diagnose oral cancer. The spectral distribution is difference for lesions of epithelial cells and normal cells after excited fluorescence. We have been developed the hyperspectral and multispectral techniques for oral cancer diagnosis in three generations. This research is the third generation. The excited and emission spectrum for the diagnosis are acquired from the research of first generation. The portable system for detection of oral cancer is modified for existing handheld microscope. The UV LED is used to illuminate the surface of oral cavity and excite the cells to produce fluorescent. The image passes through the central channel and filters out unwanted spectrum by the selection of filter, and focused by the focus lens on the image sensor. Therefore, we can achieve the specific wavelength image via fluorescence reaction. The specificity and sensitivity of the system are 85% and 90%, respectively.

  12. Diagnostic technology of PWR plant equipment failures

    International Nuclear Information System (INIS)

    Nakamura, Tetsuo; Tanaka, Mamoru; Okamachi, Masao; Taguchi, Shozo; Nagashima, Kazuhiro; Ishikawa, Satoshi

    1985-01-01

    To confirm the soundness of the important facilities in a nuclear power plant contributes to the reliability of the plant operations and improvement of its operation rate. For this purpose, the following diagnostic techniques have been developed. (1). Vibration and loose parts monitoring: Detection of abnormal structural vibrations in the reactor, estimation of its mode, detection of loose parts in the primary system, and estimation of the position and energy of their collisions against the reactor vessel or the like. (2). Valve leak monitoring: Detection of leaks from primary valves in the primary cooling boundary, such as the pressurizer relief valve and safety valve, and estimation of the form of the leaks. (3). Detector noise response diagnosis: Diagnosis of degradation of principal process detectors during plant operation. Furthermore, a diagnostic system incorporating the above diagnostic technology applicable to actual plants has been experimentally manufactured and successfully verified. (author)

  13. Promises in intelligent plant control systems

    International Nuclear Information System (INIS)

    Otaduy, P.J.

    1987-01-01

    The control system is the brain of a power plant. The traditional goal of control systems has been productivity. However, in nuclear power plants the potential for disaster requires safety to be the dominant concern, and the worldwide political climate demands trustworthiness for nuclear power plants. To keep nuclear generation as a viable option for power in the future, trust is the essential critical goal which encompasses all others. In most of today's nuclear plants the control system is a hybrid of analog, digital, and human components that focuses on productivity and operates under the protective umbrella of an independent engineered safety system. Operation of the plant is complex, and frequent challenges to the safety system occur which impact on their trustworthiness. Advances in nuclear reactor design, computer sciences, and control theory, and in related technological areas such as electronics and communications as well as in data storage, retrieval, display, and analysis have opened a promise for control systems with more acceptable human brain-like capabilities to pursue the required goals. This paper elaborates on the promise of futuristic nuclear power plants with intelligent control systems and addresses design requirements and implementation approaches

  14. Automatic vibration monitoring system for the diagnostic inspection of the WWER-440 type nuclear power plants

    International Nuclear Information System (INIS)

    Hollo, E.; Siklossy, P.; Toth, Zs.

    1982-01-01

    In the Hungarian Research Institute for Electric Power Industry (VEIKI) an automatic vibration monitoring system for diagnostics and inspection of nuclear power plants of type WWER-440 was developed. The paper summarizes the results of this work and investigates the use of mechanical vibrations and oscillations induced by flow for fault diagnosis. The design of the hardware system, the present software possibilities, the laboratory experiments and the guidelines for future software developments are also described in detail. (A.L.)

  15. Plant operator performance evaluation system

    International Nuclear Information System (INIS)

    Ujita, Hiroshi; Fukuda, Mitsuko; Kubota, Ryuji.

    1989-01-01

    A plant operator performance evaluation system to analyze plant operation records during accident training and to identify and classify operator errors has been developed for the purpose of supporting realization of a training and education system for plant operators. A knowledge engineering technique was applied to evaluation of operator behavior by both even-based and symptom-based procedures, in various situations including event transition due to multiple failures or operational errors. The system classifies the identified errors as to their single and double types based on Swain's error classification and the error levels reflecting Rasmussen's cognitive level, and it also evaluates the effect of errors on plant state and then classifies error influence, using 'knowledge for phenomena and operations', as represented by frames. It has additional functions for analysis of error statistics and knowledge acquisition support of 'knowledge for operations'. The system was applied to a training analysis for a scram event in a BWR plant, and its error analysis function was confirmed to be effective by operational experts. (author)

  16. Diagnosis of multiple system atrophy.

    Science.gov (United States)

    Palma, Jose-Alberto; Norcliffe-Kaufmann, Lucy; Kaufmann, Horacio

    2018-05-01

    Multiple system atrophy (MSA) may be difficult to distinguish clinically from other disorders, particularly in the early stages of the disease. An autonomic-only presentation can be indistinguishable from pure autonomic failure. Patients presenting with parkinsonism may be misdiagnosed as having Parkinson disease. Patients presenting with the cerebellar phenotype of MSA can mimic other adult-onset ataxias due to alcohol, chemotherapeutic agents, lead, lithium, and toluene, or vitamin E deficiency, as well as paraneoplastic, autoimmune, or genetic ataxias. A careful medical history and meticulous neurological examination remain the cornerstone for the accurate diagnosis of MSA. Ancillary investigations are helpful to support the diagnosis, rule out potential mimics, and define therapeutic strategies. This review summarizes diagnostic investigations useful in the differential diagnosis of patients with suspected MSA. Currently used techniques include structural and functional brain imaging, cardiac sympathetic imaging, cardiovascular autonomic testing, olfactory testing, sleep study, urological evaluation, and dysphagia and cognitive assessments. Despite advances in the diagnostic tools for MSA in recent years and the availability of consensus criteria for clinical diagnosis, the diagnostic accuracy of MSA remains sub-optimal. As other diagnostic tools emerge, including skin biopsy, retinal biomarkers, blood and cerebrospinal fluid biomarkers, and advanced genetic testing, a more accurate and earlier recognition of MSA should be possible, even in the prodromal stages. This has important implications as misdiagnosis can result in inappropriate treatment, patient and family distress, and erroneous eligibility for clinical trials of disease-modifying drugs. Copyright © 2017 Elsevier B.V. All rights reserved.

  17. [Central nervous system involvement in systemic lupus erythematosus - diagnosis and therapy].

    Science.gov (United States)

    Szmyrka, Magdalena

    Nervous system involvement in lupus belongs to its severe complications and significantly impacts its prognosis. Neuropsychiatric lupus includes 19 disease manifestations concerning both central and peripheral nervous system. This paper presents clinical aspects of central nervous system involvement in lupus. It reviews its epidemiology, risk factors and principles of diagnosis and therapy.

  18. Application of expert system to nuclear power plant operation and guidance system

    International Nuclear Information System (INIS)

    Goto, M.; Takada, Y.

    1990-01-01

    For a nuclear power plant, it is important that an expert system supplies useful information to the operator to meet the increasing demand for high-level plant operation. It is difficult to build a user-friendly expert system that supplies useful information in real time using existing general-purpose expert system shells. Therefore a domain-specific expert system shell with a useful knowledge representation for problem-solving in nuclear power plant operation was selected. The Plant Table (P/T) representation format was developed for description of a production system for nuclear power plant operation knowledge. The P/T consists of plant condition representation designed to process multiple inputs and single output. A large number of operation inputs for several plant conditions are divided into 'timing conditions', 'preconditions' and 'completion conditions' to facilitate knowledge-base build-up. An expert system for a Nuclear Power Plant Operation and Guidance System utilizing the P/T was developed to assist automatic plant operation and surveillance test operation. In these systems, automatic plant operation signals to the plant equipment and operation guidance messages to the operators are both output based on the processing and assessment of plant operation conditions by the P/T. A surveillance test procedure guide for major safety-related systems, such as those for emergency core cooling systems, is displayed on a CRT (Cathode Ray Tube) and test results are printed out. The expert system for a Nuclear Power Plant Operation and Guidance System has already been successfully applied to Japanese BWR plants

  19. Comparison of capability between two versions of reactor transient diagnosis expert system 'DISKET' programmed in different languages

    International Nuclear Information System (INIS)

    Yokobayashi, Masao; Yoshida, Kazuo

    1991-01-01

    An expert system DISKET has been developed at JAERI to apply knowledge engineering techniques to the transient diagnosis of nuclear power plant. The first version of DISKET programmed in UTILISP has been developed with the main-frame computer FACOM M-780 at JAERI. The LISP language is not suitable for on-line diagnostic systems because it is highly dependent on computer to be used and requires a large computer memory. The large mainframe computer is also not suitable because there are various restrictions as a multi-user computer system. The second version of DISKET for a practical use has been developed in FORTRAN to realize on-line real time diagnoses with limited computer resources. These two versions of DISKET with the same knowledge base have been compared in running capability, and it has been found that the LISP version of DISKET needs more than two times of memory and CPU time of FORTRAN version. From this result, it is shown that this approach is a practical one to develop expert systems for on-line real time diagnosis of transients with limited computer resources. (author)

  20. An intelligent medical system for diagnosis of bone diseases

    International Nuclear Information System (INIS)

    Hatzilygeroudis, I.; Vassilakos, P.J.; Tsakalidis, A.

    1994-01-01

    In this paper, aspects of the design of an intelligent medical system for diagnosis of bone diseases that can be detected by scintigraphic images are presented. The system comprises three major parts: a user interface (UI), a database management system (DBMS), and an expert system (ES). The DBMS is used for manipulation of various patient data. A number of patient cases are selected as prototype and stored in separate database. Diagnosis is performed via the ES, called XBONE, based on patient data. Knowledge is represented via an integrated formalism that combines production rules and a neural network. This results in better representation, and facilitates knowledge acquisition and maintenance. (authors)

  1. Chapter 15. Plant pathology and managing wildland plant disease systems

    Science.gov (United States)

    David L. Nelson

    2004-01-01

    Obtaining specific, reliable knowledge on plant diseases is essential in wildland shrub resource management. However, plant disease is one of the most neglected areas of wildland resources experimental research. This section is a discussion of plant pathology and how to use it in managing plant disease systems.

  2. Precision Diagnosis, Monitoring and Control of Structural Component Degradation in Nuclear Power Plants

    International Nuclear Information System (INIS)

    Han, J. H.; Choi, M. S.; Lee, D. H.; Hur, D. H.; Na, J. W.; Kim, K. M.; Hong, J. H.; Kim, H. S.

    2007-06-01

    The occurrence of structural material degradations in NPPs and their progress during operation are directly related to the safety and the integrity of NPPs. The various kinds of material degradation are usually examined by methods of material integrity evaluation and non-destructive evaluation(NDE). Material integrity evaluation is well known as classical method to interpret cause and mechanism of degradation and failure, however, this method has a limitation of detection and diagnosis for actual condition of flaws and defects occurring during plant operation, particularly for their formation in the early stage. NDE used widely for detection of defects formed on structural materials provides many information for safety regulation, plant management, repairing, however, this technique has a generic problem in its reliability due to low detectability and ability of signal analysis, etc. The objective of this research project is to develop the advanced technologies ensuring a precision diagnosis on the various kind of defects in structural materials of NPP and a high performance in material degradation evaluation. Many of the advanced technologies were developed in the 1st phase of this project. They contributed to interpret more precisely the root causes of degradation, failure and to establish the proper measures for the safety and integrity of NPPs. The accomplishment of comprehensive technology developed as planned will be practically applied to the nuclear industries and contributed to improve the safety and integrity of NPPs

  3. Development of EDG Engine Condition Diagnosis Logic in Korean Nuclear Power Plants

    International Nuclear Information System (INIS)

    Lee, Byoung Oh; Choi, Kwang Hee; Lee, Sang Guk

    2012-01-01

    Through benchmarking using the excellent record of the nuclear power plants under operation in the United States and Europe and with the continuous development of nuclear-related technology, the Korea Hydro and Nuclear Power Co., LTD (KHNP) reached an average planned preventive maintenance period of 29.6 days in 2009. In addition, KHNP plans to reduce the planned preventive maintenance period at Korea standard nuclear plants (KSNPs) from 29.6 days to less than 21 days by 2014 through a combination of domestic research and development (R and D) and the introduction of the technical know-how applied in the very best overseas nuclear power plants (NPPs). Accordingly, it is necessary to reduce the inspection and maintenance periods of an emergency diesel generator (EDG), which are currently set in the planned preventive maintenance period. If the condition-based predictive maintenance (CBM) technology is applied to EDG engines, the maintenance period of an EDG will be shortened because engine maintenance is accomplished according to the engine condition under this plan. In this study, in the series of CBM program developments which will be applied to EDG engines, the development results of condition diagnosis logic to be applied to EDG engines for exiting domestic NPPs are introduced

  4. Combined Deep And Shallow Knowledge In A Unified Model For Diagnosis By Abduction

    Directory of Open Access Journals (Sweden)

    Viorel Ariton

    2006-10-01

    Full Text Available Abstract: Fault Diagnosis in real systems usually involves human expert’s shallow knowledge (as pattern causes-effects but also deep knowledge(as structural / functional modularization and models on behavior. The paper proposes a unified approach on diagnosis by abduction based onplausibility and relevance criteria multiple applied, in a connectionist implementation. Then, it focuses elicitation of deep knowledge on targetconductive flow systems – most encountered in industry and not only, in the aim of fault diagnosis. Finally, the paper gives hints on design andbuilding of diagnosis system by abduction, embedding deep and shallow knowledge (according to case and performing hierarchical fault isolation,along with a case study on a hydraulic installation in a rolling mill plant.

  5. COMBINED DEEP AND SHALLOW KNOWLEDGE IN A UNIFIED MODEL FOR DIAGNOSIS BY ABDUCTION

    Directory of Open Access Journals (Sweden)

    Viorel Ariton

    2007-05-01

    Full Text Available Fault Diagnosis in real systems usually involves human expert’s shallow knowledge (as pattern causeseffectsbut also deep knowledge (as structural / functional modularization and models on behavior. The paperproposes a unified approach on diagnosis by abduction based on plausibility and relevance criteria multipleapplied, in a connectionist implementation. Then, it focuses elicitation of deep knowledge on target conductiveflow systems – most encountered in industry and not only, in the aim of fault diagnosis. Finally, the paper giveshints on design and building of diagnosis system by abduction, embedding deep and shallow knowledge(according to case and performing hierarchical fault isolation, along with a case study on a hydraulicinstallation in a rolling mill plant.

  6. System identification of the Arabidopsis plant circadian system

    Science.gov (United States)

    Foo, Mathias; Somers, David E.; Kim, Pan-Jun

    2015-02-01

    The circadian system generates an endogenous oscillatory rhythm that governs the daily activities of organisms in nature. It offers adaptive advantages to organisms through a coordination of their biological functions with the optimal time of day. In this paper, a model of the circadian system in the plant Arabidopsis (species thaliana) is built by using system identification techniques. Prior knowledge about the physical interactions of the genes and the proteins in the plant circadian system is incorporated in the model building exercise. The model is built by using primarily experimentally-verified direct interactions between the genes and the proteins with the available data on mRNA and protein abundances from the circadian system. Our analysis reveals a great performance of the model in predicting the dynamics of the plant circadian system through the effect of diverse internal and external perturbations (gene knockouts and day-length changes). Furthermore, we found that the circadian oscillatory rhythm is robust and does not vary much with the biochemical parameters except those of a light-sensitive protein P and a transcription factor TOC1. In other words, the circadian rhythmic profile is largely a consequence of the network's architecture rather than its particular parameters. Our work suggests that the current experimental knowledge of the gene-to-protein interactions in the plant Arabidopsis, without considering any additional hypothetical interactions, seems to suffice for system-level modeling of the circadian system of this plant and to present an exemplary platform for the control of network dynamics in complex living organisms.

  7. Fault diagnosis for dynamic power system

    International Nuclear Information System (INIS)

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

    2011-01-01

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

  8. A methodology for fault diagnosis in large chemical processes and an application to a multistage flash desalination process: Part I

    International Nuclear Information System (INIS)

    Tarifa, Enrique E.; Scenna, Nicolas J.

    1998-01-01

    This work presents a new strategy for fault diagnosis in large chemical processes (E.E. Tarifa, Fault diagnosis in complex chemistries plants: plants of large dimensions and batch processes. Ph.D. thesis, Universidad Nacional del Litoral, Santa Fe, 1995). A special decomposition of the plant is made in sectors. Afterwards each sector is studied independently. These steps are carried out in the off-line mode. They produced vital information for the diagnosis system. This system works in the on-line mode and is based on a two-tier strategy. When a fault is produced, the upper level identifies the faulty sector. Then, the lower level carries out an in-depth study that focuses only on the critical sectors to identify the fault. The loss of information produced by the process partition may cause spurious diagnosis. This problem is overcome at the second level using qualitative simulation and fuzzy logic. In the second part of this work, the new methodology is tested to evaluate its performance in practical cases. A multiple stage flash desalination system (MSF) is chosen because it is a complex system, with many recycles and variables to be supervised. The steps for the knowledge base generation and all the blocks included in the diagnosis system are analyzed. Evaluation of the diagnosis performance is carried out using a rigorous dynamic simulator

  9. Plant automation

    International Nuclear Information System (INIS)

    Christensen, L.J.; Sackett, J.I.; Dayal, Y.; Wagner, W.K.

    1989-01-01

    This paper describes work at EBR-II in the development and demonstration of new control equipment and methods and associated schemes for plant prognosis, diagnosis, and automation. The development work has attracted the interest of other national laboratories, universities, and commercial companies. New initiatives include use of new control strategies, expert systems, advanced diagnostics, and operator displays. The unique opportunity offered by EBR-II is as a test bed where a total integrated approach to automatic reactor control can be directly tested under real power plant conditions

  10. Research on Fault Diagnosis of HTR-PM Based on Multilevel Flow Model

    International Nuclear Information System (INIS)

    Zhang Yong; Zhou Yangping

    2014-01-01

    In this paper, we focus on the application of Multilevel Flow Model (MFM) in the automatic real-time fault diagnosis of High Temperature Gas-cooled Reactor Pebble-bed Module (HTR-PM) accidents. In the MFM, the plant process is described abstractly in function level by mass, energy and information flows, which reveal the interaction between different components and capacitate the causal reasoning between functions according to the flow properties. Thus, in the abnormal status, a goal-function-component oriented fault diagnosis can be performed with the model at a very quick speed and abnormal alarms can be also precisely explained by the reasoning relationship of the model. By using MFM, a fault diagnosis model of HTR-PM plant is built, and the detailed process of fault diagnosis is also shown by the flowcharts. Due to lack of simulation data about HTR-PM, experiments are not conducted to evaluate the fault diagnosis performance, but analysis of algorithm feasibility and complexity shows that the diagnosis system will have a good ability to detect and diagnosis accidents timely. (author)

  11. 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.

  12. PSG-EXPERT. An expert system for the diagnosis of sleep disorders.

    Science.gov (United States)

    Fred, A; Filipe, J; Partinen, M; Paiva, T

    2000-01-01

    This paper describes PSG-EXPERT, an expert system in the domain of sleep disorders exploring polysomnographic data. The developed software tool is addressed from two points of view: (1)--as an integrated environment for the development of diagnosis-oriented expert systems; (2)--as an auxiliary diagnosis tool in the particular domain of sleep disorders. Developed over a Windows platform, this software tool extends one of the most popular shells--CLIPS (C Language Integrated Production System) with the following features: backward chaining engine; graph-based explanation facilities; knowledge editor including a fuzzy fact editor and a rules editor, with facts-rules integrity checking; belief revision mechanism; built-in case generator and validation module. It therefore provides graphical support for knowledge acquisition, edition, explanation and validation. From an application domain point of view, PSG-Expert is an auxiliary diagnosis system for sleep disorders based on polysomnographic data, that aims at assisting the medical expert in his diagnosis task by providing automatic analysis of polysomnographic data, summarising the results of this analysis in terms of a report of major findings and possible diagnosis consistent with the polysomnographic data. Sleep disorders classification follows the International Classification of Sleep Disorders. Major features of the system include: browsing on patients data records; structured navigation on Sleep Disorders descriptions according to ASDA definitions; internet links to related pages; diagnosis consistent with polysomnographic data; graphical user-interface including graph-based explanatory facilities; uncertainty modelling and belief revision; production of reports; connection to remote databases.

  13. Developments in power plant cooling systems

    International Nuclear Information System (INIS)

    Agarwal, N.K.

    1993-01-01

    A number of cooling systems are used in the power plants. The condenser cooling water system is one of the most important cooling systems in the plant. The system comprises a number of equipment. Plants using sea water for cooling are designed for the very high corrosion effects due to sea water. Developments are taking place in the design, materials of construction as well as protection philosophies for the various equipment. Power optimisation of the cycle needs to be done in order to design an economical system. Environmental (Protection) Act places certain limitations on the effluents from the plant. An attempt has been made in this paper to outline the developing trends in the various equipment in the condenser cooling water systems used at the inland as well as coastal locations. (author). 5 refs., 6 refs

  14. Intelligent Case Based Decision Support System for Online Diagnosis of Automated Production System

    International Nuclear Information System (INIS)

    Ben Rabah, N; Saddem, R; Carre-Menetrier, V; Ben Hmida, F; Tagina, M

    2017-01-01

    Diagnosis of Automated Production System (APS) is a decision-making process designed to detect, locate and identify a particular failure caused by the control law. In the literature, there are three major types of reasoning for industrial diagnosis: the first is model-based, the second is rule-based and the third is case-based. The common and major limitation of the first and the second reasonings is that they do not have automated learning ability. This paper presents an interactive and effective Case Based Decision Support System for online Diagnosis (CB-DSSD) of an APS. It offers a synergy between the Case Based Reasoning (CBR) and the Decision Support System (DSS) in order to support and assist Human Operator of Supervision (HOS) in his/her decision process. Indeed, the experimental evaluation performed on an Interactive Training System for PLC (ITS PLC) that allows the control of a Programmable Logic Controller (PLC), simulating sensors or/and actuators failures and validating the control algorithm through a real time interactive experience, showed the efficiency of our approach. (paper)

  15. An intelligent medical system for diagnosis of bone diseases

    Energy Technology Data Exchange (ETDEWEB)

    Hatzilygeroudis, I [University of Patras, School of Engineering, Department of Computer Engineering and Informatics, 26500 Patras, Greece (Greece); Vassilakos, P J [Regional University Hospital of Patras, Department of Nuclear Medicine, Patras Greece (Greece); Tsakalidis, A [Computer Technology Institute, P.O. Box 1122, 26110 Patras, Greece (Greece)

    1994-12-31

    In this paper, aspects of the design of an intelligent medical system for diagnosis of bone diseases that can be detected by scintigraphic images are presented. The system comprises three major parts: a user interface (UI), a database management system (DBMS), and an expert system (ES). The DBMS is used for manipulation of various patient data. A number of patient cases are selected as prototype and stored in separate database. Diagnosis is performed via the ES, called XBONE, based on patient data. Knowledge is represented via an integrated formalism that combines production rules and a neural network. This results in better representation, and facilitates knowledge acquisition and maintenance. (authors). 10 refs., 2 figs.

  16. Optimal estimation and control in nuclear power plants

    International Nuclear Information System (INIS)

    Purviance, J.E.; Tylee, J.L.

    1982-08-01

    Optimal estimation and control theories offer the potential for more precise control and diagnosis of nuclear power plants. The important element of these theories is that a mathematical plant model is used in conjunction with the actual plant data to optimize some performance criteria. These criteria involve important plant variables and incorporate a sense of the desired plant performance. Several applications of optimal estimation and control to nuclear systems are discussed

  17. Testing and diagnosis of the cause of increased vibration of the fan plant's support structure

    Directory of Open Access Journals (Sweden)

    Varju Đerđ

    2015-01-01

    Full Text Available This paper presents a procedure of determining the causes of increased vibration of a fan plant and its support structure in the PUC 'Subotička toplana'. Excessive vibrations were observed following the installation of the frequency converter, thus a methodological approach of testing-analysis-diagnosis has been applied. Based on the definition of the causes of this problem, the paper also suggests possible repair procedures.

  18. Integrated ADIOS-IGENPRO operator advisory support system

    International Nuclear Information System (INIS)

    Lee, Dong Young; Park, J. H.; Kim, J. T.; Kim, C. H.; Park, W. M.; Hwang, I. K.; Cheon, S. W.; Song, S. J.

    2001-05-01

    The I and C systems and control rooms of nuclear power plants have been constructed by using the automatic control concept and changed to computer-based systems in nowadays. For Increase of an automation and CRT, the role of operators is changed to monitor the condition of the nuclear power plants. Therefore, the information that is offered to operators has to integrate in order for operator to understand the hole condition of plants. In commercial nuclear plants, raw data of sensors and components are shown in a control room. So, operators can not diagnose the condition of plants correctly. For a development of an integrated operator aid system which contain an alarm processing system and a fault diagnosis system, we integrated IGENPRO of ANL(Argonne National Lab.) and ADIOS of KAERI (Korea Atomic Energy Institute). IGENPRO is a fault diagnosis system contains three module such as PROTREN, PRODIAG and PROTREN. ADIOS is an alarm processing system that informs operators of important alarms. The integrated operator advisory support system developed in the research is composed of an alarm processing module and a fault diagnosis module. The alarm processing module shows important alarms to operator by using dynamic alarm filtering methods. The fault diagnosis module shows the cause of faults of sensors and hardwares

  19. Integrated ADIOS-IGENPRO operator advisory support system

    Energy Technology Data Exchange (ETDEWEB)

    Lee, Dong Young; Park, J. H.; Kim, J. T.; Kim, C. H.; Park, W. M.; Hwang, I. K.; Cheon, S. W.; Song, S. J

    2001-05-01

    The I and C systems and control rooms of nuclear power plants have been constructed by using the automatic control concept and changed to computer-based systems in nowadays. For Increase of an automation and CRT, the role of operators is changed to monitor the condition of the nuclear power plants. Therefore, the information that is offered to operators has to integrate in order for operator to understand the hole condition of plants. In commercial nuclear plants, raw data of sensors and components are shown in a control room. So, operators can not diagnose the condition of plants correctly. For a development of an integrated operator aid system which contain an alarm processing system and a fault diagnosis system, we integrated IGENPRO of ANL(Argonne National Lab.) and ADIOS of KAERI (Korea Atomic Energy Institute). IGENPRO is a fault diagnosis system contains three module such as PROTREN, PRODIAG and PROTREN. ADIOS is an alarm processing system that informs operators of important alarms. The integrated operator advisory support system developed in the research is composed of an alarm processing module and a fault diagnosis module. The alarm processing module shows important alarms to operator by using dynamic alarm filtering methods. The fault diagnosis module shows the cause of faults of sensors and hardwares.

  20. A study on the efficiency improvement of the plant secondary System in NPP

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Chun Ho; Song Jong Sun [Chosun Univ., Kwangju (Korea, Republic of)

    2012-10-15

    The ultimate objective of the diagnostic test for thermal performance of generation facilities is to assist in making an economic decision on operation optimization of power plants by understanding the degree of heat aging due to operation of relevant facilities and planning on this basis the maintenance and repair. In this thesis, the trend in performance change was analyzed against the acceptance performance test conducted after the replacement of the high pressure turbine in 2007, through thermal performance diagnosis conducted at 100 % reactor thermal output after the 19th planned preventive maintenance of Yonggwang Nuclear Units 1 and 2, and the power plant operation was optimized by acquiring base line data for management of performance record for each major facility of the secondary system and by improving efficiency of unit instruments and peripheral instruments of the secondary system. As a result derived from the thermal performance analysis, the increase in electric output of the power plants was achieved through such operation optimizations of efficiency affecting instruments as optimization of the continuous exhaust flow rate for water supply heaters, vacuum improvement of condensers due to opening the upper/lower screens of heat transfer pipe washing system for condensers during summer, and flow rate optimization of the water vapor supplied to MSR (Moisture Separator Re heater) high pressure re heaters. This improves operation of the existing power plants without additional expense and so requires expert review by responsible personnel for practical application.

  1. Diagnosis of multi-agent systems and its application to public administration

    NARCIS (Netherlands)

    Boer, A.; van Engers, T.; Abramowicz, W.; Maciaszek, L.; Węcel, K.

    2011-01-01

    In this paper we present a model-based diagnosis view on the complex social systems in which large public administration organizations operate. The purpose of diagnosis as presented in this paper is to identify agent role instances that are not conforming to expectations in a multi-agent system

  2. Deductive Error Diagnosis and Inductive Error Generalization for Intelligent Tutoring Systems.

    Science.gov (United States)

    Hoppe, H. Ulrich

    1994-01-01

    Examines the deductive approach to error diagnosis for intelligent tutoring systems. Topics covered include the principles of the deductive approach to diagnosis; domain-specific heuristics to solve the problem of generalizing error patterns; and deductive diagnosis and the hypertext-based learning environment. (Contains 26 references.) (JLB)

  3. Thermo-power in Brazil: diagnosis of control and monitoring of gas emissions

    International Nuclear Information System (INIS)

    Xavier, E.E.; Magrini, Alessandra; Rosa, L.P.; Santos, M.A. dos

    2004-01-01

    In parallel to Brazil's recent supply crisis, the privatization process of its power sector has drastically reshaped the nation's energy matrix. From a profile based mainly on hydro-power generation, this sector is being reshaped through a thermo-power plant construction program whose environmental repercussions will certainly be felt over the next few years. This paper offers a description of the thermo-power segment currently in operation, under construction and on the drawing board in Brazil, followed by the results of a diagnosis of the control and monitoring of the gas emissions by this segment. The methodology used for the exploratory analysis and to prepare the diagnosis consists of surveys through questionnaires completed by companies owning the thermo-power plants. After consolidating, processing and analyzing the findings reached through the replies sent in by the companies, it is concluded that thermo-power plants currently in operation lack control systems that would help reduce atmospheric pollution, and are not equipped with monitoring systems for these emissions. The thermo-power plants currently under construction and on the drawing board indicate a trend towards including these systems in their project designs, due to more stringent licensing processes

  4. 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

  5. An Event-Based Approach to Distributed Diagnosis of Continuous Systems

    Science.gov (United States)

    Daigle, Matthew; Roychoudhurry, Indranil; Biswas, Gautam; Koutsoukos, Xenofon

    2010-01-01

    Distributed fault diagnosis solutions are becoming necessary due to the complexity of modern engineering systems, and the advent of smart sensors and computing elements. This paper presents a novel event-based approach for distributed diagnosis of abrupt parametric faults in continuous systems, based on a qualitative abstraction of measurement deviations from the nominal behavior. We systematically derive dynamic fault signatures expressed as event-based fault models. We develop a distributed diagnoser design algorithm that uses these models for designing local event-based diagnosers based on global diagnosability analysis. The local diagnosers each generate globally correct diagnosis results locally, without a centralized coordinator, and by communicating a minimal number of measurements between themselves. The proposed approach is applied to a multi-tank system, and results demonstrate a marked improvement in scalability compared to a centralized approach.

  6. The intelligent plant

    Energy Technology Data Exchange (ETDEWEB)

    Bruce Firth [CSIRO Energy Technology (Australia)

    2009-06-15

    The current advances in electronics and smart sensors, coupled with the large amount of information that modern distributed control systems can create, provide opportunities but posses some significant problems. The potential suite of data measurements could provide plant operators, maintenance staff and supervisors with a comprehensive understanding of the current health of a coal preparation plant. Analysis of this issue would also provide a tool for the recognition of where important data is not or poorly (timeframe and/or quality) currently available. A suitable system for categorisation of the information associated with the description of the 'Health of a Plant' has been developed. A relational data base model for these categories was derived. The process and performance information relationships were established via the use of models derived from the wide body of literature available. Given the availability of the above model relationships and measurements, the best way to utilise this information in a simple intelligent manner was addressed. It involved the construction of a high level fuzzy set diagnosis chart and an underlying set of unit operation diagnostic charts. These charts provided the basis for the implementation of a generic diagnosis system. This was deliberately developed in EXCEL so that it can be used and/or modified to suit a particular plant. A sensing system which combines a limited set of measurements with an algorithm or logic system for optimisation of a process can be termed a smart sensor. These are vey useful in the optimisation of difficult process situations, and can be used to supplement expert systems. It is believed that the models developed in this project can also provide the basis for appropriate smart sensors when access to appropriate measurements is available.

  7. Fault trees for diagnosis of system fault conditions

    International Nuclear Information System (INIS)

    Lambert, H.E.; Yadigaroglu, G.

    1977-01-01

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

  8. Development of A Plant Navigation System

    International Nuclear Information System (INIS)

    Furuta, Tomihiko; Nakagawa, Tsuneo; Kubota, Ryuji; Ikeda, Kouji

    1998-01-01

    A 'Plant Navigation System (PNS)' is under development to assist nuclear power plant (NPP) operators by automatically displaying the plant situation and plant operational procedures on a CRT screen when abnormalities occur. The operation procedures given in a symptom-oriented manual are expressed in a tree - type flowchart (modified PAD). The optimum operation procedure for an NPP is selected automatically using built-in diagnostic logics based on the current status of the NPP. Concerning the plant situation, the PNS displays important information only on the current status of the NPP. A prototype PNS system is being constructed. (authors)

  9. Design and simulation of a plant control system for a GCFR demonstration plant

    International Nuclear Information System (INIS)

    Estrine, E.A.; Greiner, H.G.

    1980-02-01

    A plant control system is being designed for a 300 MW(e) Gas Cooled Fast Breeder Reactor (GCFR) demonstration plant. Control analysis is being performed as an integral part of the plant design process to ensure that control requirements are satisfied as the plant design evolves. Plant models and simulations are being developed to generate information necessary to further define control system requirements for subsequent plant design iterations

  10. Monitoring support system for nuclear power plant

    International Nuclear Information System (INIS)

    Higashikawa, Yuichi; Kubota, Rhuji; Tanaka, Keiji; Takano, Yoshiyuki

    1996-01-01

    The nuclear power plants in Japan reach to 49 plants and supply 41.19 million kW in their installed capacities, which is equal to about 31% of total electric power generation and has occupied an important situation as a stable energy supplying source. As an aim to keeping safe operation and working rate of the power plants, various monitoring support systems using computer technology, optical information technology and robot technology each advanced rapidly in recent year have been developed to apply to the actual plants for a plant state monitoring system of operators in normal operation. Furthermore, introduction of the emergent support system supposed on accidental formation of abnormal state of the power plants is also investigated. In this paper, as a monitoring system in the recent nuclear power plants, design of control panel of recent central control room, introduction to its actual plant and monitoring support system in development were described in viewpoints of improvement of human interface, upgrade of sensor and signal processing techniques, and promotion of information service technique. And, trend of research and development of portable miniature detector and emergent monitoring support system are also introduced in a viewpoint of labor saving and upgrade of the operating field. (G.K.)

  11. Using a plant health system framework to assess plant clinic performance in Uganda

    DEFF Research Database (Denmark)

    Danielsen, Solveig; Matsiko, Frank B.

    2016-01-01

    and expand, new analytical frameworks and tools are needed to identify factors influencing performance of services and systems in specific contexts, and to guide interventions. In this paper we apply a plant health system framework to assess plant clinic performance, using Uganda as a case study...... factors, influenced by basic operational and financial concerns, inter-institutional relations and public sector policies. Overall, there was a fairly close match between the plant health system attributes and plant clinic performance, suggesting that the framework can help explain system functioning....... A comparative study of plant clinics was carried out between July 2010 and September 2011 in the 12 districts where plant clinics were operating at that time. The framework enabled us to organise multiple issues and identify key features that affected the plant clinics. Clinic performance was, among other...

  12. Plant introduction system applying virtual reality

    International Nuclear Information System (INIS)

    Kasai, Yasusuke; Tanaka, Kazuo; Kimura, Katsumi; Nakakosi, Tetsuhiro

    1995-01-01

    We developed the prototype of the introduction system for nuclear power plant applying 3D-CAD data and the virtual reality (V.R) technologies. For the purpose of the public acceptance (PA), the use of the V.R technologies, such as CG stereographic, will be interesting for the public. Also, it is very important to introduce the components of the plant in detail, which will become easy by using the 3D-CAD data of the nuclear plant. We made a prototype system for introducing the main portion of the nuclear power plant, such as main control room, containment vessel or turbine building, applying CG stereographic by plant 3D data and artificial voice guidance for the explanations. We have exhibited this system in two local festivals at the plant sites. It has been efficient for creating plant scene by using 3D-CAD from the viewpoint of cost, and stereographic has been much attractive to the resident. The detail scenario must be investigated from the viewpoint of PA effect. Also the performance of the graphics workstation should be increased to promote the quality of the CG movie. But we think that this system will have much effective by its novelty and flexibility. (author)

  13. Information management systems improve advanced plant design

    International Nuclear Information System (INIS)

    Turk, R.S.; Serafin, S.A.; Leckley, J.B.

    1994-01-01

    Computer-aided engineering tools are proving invaluable in both the design and operation of nuclear power plants. ABB Combustion Engineering's Advanced Light Water Reactor (ALWR) features a computerized Information Management System (IMS) as an integral part of the design. The System 80+IMS represents the most powerful information management tool for Nuclear Power Plants commercially available today. Developed by Duke Power Company specifically for use by nuclear power plant owner operators, the IMS consists of appropriate hardware and software to manage and control information flow for all plant related work or tasks in a systematic, consistent, coordinated and informative manner. A significant feature of this IMS is that it is primarily based on plant data. The principal design tool, PASCE (Plant Application and Systems from Combustion Engineering), is comprised of intelligent databases that describe the design and from which accurate plant drawings are created. Additionally the IMS includes, at its hub, a relational database management system and an associated document management system. The data-based approach and applications associated with the IMS were developed, and have proven highly effective, for plant modifications, configuration management, and operations and maintenance applications at Duke Power Company's operating nuclear plants. This paper presents its major features and benefits. 4 refs

  14. Surveillance system for nuclear power plants

    International Nuclear Information System (INIS)

    Mizeracki, M.T.

    1981-01-01

    This paper describes an integrated surveillance system for nuclear power plant application. The author explores an expanded role for closed circuit television, with remotely located cameras and infrared scanners as the basic elements. The video system, integrated with voice communication, can enhance the safe and efficient operation of the plant, by improving the operator's knowledge of plant conditions. 7 refs

  15. Research on fault diagnosis of nuclear power plants based on genetic algorithms and fuzzy logic

    International Nuclear Information System (INIS)

    Zhou Yangping; Zhao Bingquan

    2001-01-01

    Based on genetic algorithms and fuzzy logic and using expert knowledge, mini-knowledge tree model and standard signals from simulator, a new fuzzy-genetic method is developed to fault diagnosis in nuclear power plants. A new replacement method of genetic algorithms is adopted. Fuzzy logic is used to calculate the fitness of the strings in genetic algorithms. Experiments on the simulator show it can deal with the uncertainty and the fuzzy factor

  16. EXTRACSION: a system for automatic Eddy Current diagnosis of steam generator tubes in nuclear power plants

    International Nuclear Information System (INIS)

    Georgel, B.; Zorgati, R.

    1992-01-01

    Improving speed and quality of Eddy Current non-destructive testing of steam generator tubes leads to automation of all process that contribute to diagnosis. This paper describes how signal processing, pattern recognition and artificial and artificial intelligence are used to build a software package that is able to automatically provide an efficient diagnosis. (author)

  17. Extraction: a system for automatic eddy current diagnosis of steam generator tubes in nuclear power plants

    International Nuclear Information System (INIS)

    Georgel, B.; Zorgati, R.

    1994-01-01

    Improving speed and quality of Eddy Current non-destructive testing of steam generator tubes leads to automatize all processes that contribute to diagnosis. This paper describes how we use signal processing, pattern recognition and artificial intelligence to build a software package that is able to automatically provide an efficient diagnosis. (authors). 2 figs., 5 refs

  18. Development of the Inspection and Diagnosis Technology for the NSSS Components Integrity

    International Nuclear Information System (INIS)

    Kim, Jae Hee; Eom, Heung Soup; Lee, Jae Cheol

    2007-02-01

    This project is to develop and demonstrate new technologies for a monitoring, inspection, diagnosis and evaluation of the safety related components in nuclear power plants. These technologies are required to detect the defects in the components of nuclear power plants and to prepare thoroughly against accidents. We studied on the four issues recently focused. Thus we developed an impact analysis model of the reactor and steam generator, and diagnosis software of the reactor internals. As an on-line monitoring technology using an ultrasonic guided wave, we developed a new method enhancing the S/N ratio of the weak signal based on time reversal technique. A network based remote inspection system and an inspection robot for reactor vessel head penetration was developed. We also performed a lifetime estimation and degradation analysis of the NPP cables through accelerated degradation tests. The technologies developed in this project are applied to the components of nuclear power plants. The applications include a localization of the NSSS integrity monitoring system, replacement of an in-service inspection by on-line monitoring, remote inspection of the major components of the plants, lifetime estimation of the degraded plant cables, and so on

  19. Development of the Inspection and Diagnosis Technology for the NSSS Components Integrity

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Jae Hee; Eom, Heung Soup; Lee, Jae Cheol (and others)

    2007-02-15

    This project is to develop and demonstrate new technologies for a monitoring, inspection, diagnosis and evaluation of the safety related components in nuclear power plants. These technologies are required to detect the defects in the components of nuclear power plants and to prepare thoroughly against accidents. We studied on the four issues recently focused. Thus we developed an impact analysis model of the reactor and steam generator, and diagnosis software of the reactor internals. As an on-line monitoring technology using an ultrasonic guided wave, we developed a new method enhancing the S/N ratio of the weak signal based on time reversal technique. A network based remote inspection system and an inspection robot for reactor vessel head penetration was developed. We also performed a lifetime estimation and degradation analysis of the NPP cables through accelerated degradation tests. The technologies developed in this project are applied to the components of nuclear power plants. The applications include a localization of the NSSS integrity monitoring system, replacement of an in-service inspection by on-line monitoring, remote inspection of the major components of the plants, lifetime estimation of the degraded plant cables, and so on.

  20. Design for testability and diagnosis at the system-level

    Science.gov (United States)

    Simpson, William R.; Sheppard, John W.

    1993-01-01

    The growing complexity of full-scale systems has surpassed the capabilities of most simulation software to provide detailed models or gate-level failure analyses. The process of system-level diagnosis approaches the fault-isolation problem in a manner that differs significantly from the traditional and exhaustive failure mode search. System-level diagnosis is based on a functional representation of the system. For example, one can exercise one portion of a radar algorithm (the Fast Fourier Transform (FFT) function) by injecting several standard input patterns and comparing the results to standardized output results. An anomalous output would point to one of several items (including the FFT circuit) without specifying the gate or failure mode. For system-level repair, identifying an anomalous chip is sufficient. We describe here an information theoretic and dependency modeling approach that discards much of the detailed physical knowledge about the system and analyzes its information flow and functional interrelationships. The approach relies on group and flow associations and, as such, is hierarchical. Its hierarchical nature allows the approach to be applicable to any level of complexity and to any repair level. This approach has been incorporated in a product called STAMP (System Testability and Maintenance Program) which was developed and refined through more than 10 years of field-level applications to complex system diagnosis. The results have been outstanding, even spectacular in some cases. In this paper we describe system-level testability, system-level diagnoses, and the STAMP analysis approach, as well as a few STAMP applications.

  1. Diagnosis and on-line displacement monitoring for critical pipe of fossil power plant

    Energy Technology Data Exchange (ETDEWEB)

    Heo, J. S.; Hyun, J. S. [Korea Electric Power Corporation, Seoul (Korea, Republic of); Heo, J. R.; Lee, S. K.; Cho, S. Y. [Korea South-East Power Co., Ltd., Seoul (Korea, Republic of)

    2009-07-01

    High temperature steam pipes of fossil power plant are subject to a severe thermal range and usually operates well into the creep range. Cyclic operation of the plant subjects the piping system to mechanical and thermal fatigue mechanisms and poor or malfunctional support assemblies can impose massive loads or stress onto the piping system. In order to prevent the serious damage and failure of the critical pipe system, various inspection methods such as visual inspection, computational analysis and on-line piping displacement monitoring were developed. 3-Dimensional piping displacement monitoring system was developed with using he aluminum alloy rod and rotary encoder type sensors, this system was installed and operated on the 'Y' fossil power plant successfully. It is expected that this study will contribute to the safety of piping system, which could minimize stress and extend the actual life of critical piping.

  2. Research on export system of marine nuclear power device

    International Nuclear Information System (INIS)

    Fu Mingyu; Bian Xinqian; Shi Ji; Xin Chengdong; Wei Dong

    2002-01-01

    A marine nuclear power plant simulation system is founded, and a management expert system, which can administer and diagnose the typical faults, is constituted by the intelligent expert theory. This real-time expert system can analyze the reason of the typical fault caused by the nuclear power plant practically running and give the best solvent by the expert knowledge reasoning in the repository; a neural network fault inspection and diagnosis expert system which can inspect every equipment continually and give the faults diagnosis result based on the inspective dates is established. Based on the three hierarchical architecture, the operation performance is improved very much by using of the neural network fault inspection and diagnosis expert system to inspect and diagnose the nuclear power plant faults and the management expert system to supervise the nuclear power plant running. The expert system research can give guidance for the marine nuclear power plant safety operation

  3. Computerized systems for on-line management of failures: a state-of-the-art discussion of alarm systems and diagnostic systems applied in the nuclear industry

    International Nuclear Information System (INIS)

    Kim, I.S.

    1994-01-01

    It is now well perceived in the nuclear industry that improving plant information systems is vital for enhancing the operational safety of nuclear power plants. Considerable work is underway worldwide to support operators' decision-making, particularly in their difficult tasks of managing process anomalies on-line. The work includes development of (1) advanced alarm systems, such as various kinds of computer-based alarm processing systems, Critical Function Monitoring System, Success Path Monitoring System and Safety Assessment System II, and (2) real-timer diagnostic systems, such as Disturbance Analysis System, Maryland Operator Advisory System II, Model-Integrated Diagnostic Analysis System, Diagnosis System using Knowledge Engineering Technique, Detailed Diagnosis, and Operator Advisor System. This paper presents a state-of-the-art review of plant information systems for on-line management of failures in nuclear power plants, focusing on the methodological features of computerized alarm systems and diagnostic systems. (author)

  4. A study on diagnosis of Dysmenorrhea patients by Diagnosis System of Oriental Medicine

    Directory of Open Access Journals (Sweden)

    In Sun,Lee

    2007-02-01

    Full Text Available Purpose : This study was undertaken to make a diagnosis weakness and firmness (虛實 of Dysmenorrhea patients by diagnosis questionnaires system(Diagnosis System of Oriental Medicine-DSOM Methods : The subjects were 58 volunteers who was suffering for dysmenorrhea, employed using Measure of Menstrual Pain (MMP questionnaire. The had agreed to take part in this experiment, with didn't take any anodyne drugs. The MMP score by using 7 questions and the Menstrual Symptom Severity List(MSSL-D was measured before and after menstruation cycle. Results and Conclusions : The findings of this study were as follows; 1. We examined Pathogenic Factor's frequency of DSOM, Coldness(寒 was 45 persons 80.36%, Damp(濕 was 40 persons 71.43%, Heart(心 was 37 persons 66.07%, Heat syndrom(熱 was 9 persons 16.07%, insufficiency of Yang(陽虛 was 6 persons 10.71%. 2. We divided Dysmenorrhea patients into two groups(weakness and firmness by Results of DSOM, Firmness was 25 Persons 43.1%, Weakness was 23 persons 39.7%, Unknown was 10 persons 17.2%. 3. In estimation based on Measure of Menstrual Pain (MMP questionnaire Severe menstrual pain is weakness, Mild menstrual pain is Firmness. 4. In estimation of coldness and heat syndrom, Coldness was 40 persons 69.0%, Heat syndrom, was 2 persons 3.5%, Possess both coldness and heat syndrom was 9 persons 15.5%.

  5. Multi-variable systems in nuclear power plant

    International Nuclear Information System (INIS)

    Collins, G.B.; Howell, J.

    1982-01-01

    Nuclear power plant are complex multi-variable dynamically interactive systems which employ many facets of systems and control theory in their analysis and design. Whole plant mathematical models must be developed and validated and in addition to their obvious role in control system synthesis and design, they are also widely used for operational constraint and plant malfunction analysis. The need for and scope of an integrated power plant control system is discussed and, as a specific example, the design of an integrated feedwater regulator is reviewed. The multi-variable frequency response analysis employed in the design is described in detail. (author)

  6. Development of a Multi-Channel Ultrasonic Testing System for Automated Ultrasonic Pipe Inspection of Nuclear Power Plant

    International Nuclear Information System (INIS)

    Lee, Hee Jong; Cho, Chan Hee; Cho, Hyun Joon

    2009-01-01

    Currently almost all in-service-inspection techniques, applied in domestic nuclear power plants, are partial to field inspection technique. These kinds of techniques are related to managing nuclear power plants by the operation of foreign-produced inspection devices. There have been so many needs for development of native in-service-inspection device because there is no native diagnosis device for nuclear power plant inspection yet in Korea. In this research, we developed several core techniques to make an automated ultrasonic pipe inspection system for nuclear power plants. A high performance multi-channel ultrasonic pulser/receiver module, an A/D converter module and a digital main CPU module were developed and the performance of the developed modules was verified. The S/N ratio, noise level and signal acquisition performance of the developed modules showed proper level as we designed in the beginning.

  7. Plant control system upgrades in the context of industry trends towards plant life-extension

    International Nuclear Information System (INIS)

    De Grosbois, J.; Basso, R.; Hepburn, A.; Kumar, V.

    2002-01-01

    Domestic CANDU nuclear plants were brought online between 1972 and 1986. Over the next decade, most of these stations will be nearing the end of their designed operating life. Effort has traditionally been placed on ensuring that the existing installed plant control system equipment could operate reliably until the end of this design life. Until recently, little attention has been given to plant control system upgrades or replacements to meet the expected requirement for 30+ years of additional plant operation following potential plant refurbishments. Industry developments are changing this thinking. The combination of expected increases in electricity demand (and prices), and the many recent successful turnaround stories of U.S. nuclear power plants has resulted in new interest in plant life improvement and plant life extension programs. Plant control system upgrade decisions are now being driven by the need to replace or upgrade these systems to support plant life extension. This article is the first of several that investigate aspects of plant control system upgrades or replacement, specifically in the context of the CANDU station digital control computers (DCCs). It sets the context for the discussion in the subsequent articles by providing a brief review of industry trends favouring plant refurbishment, by outlining the basic issues of aging and obsolescence of control system equipment, by establishing the need for upgrades and replacements, and by introducing some of the basic challenges to be addressed by the industry as it moves forward. (author)

  8. Plant-wide integrated equipment monitoring and analysis system

    International Nuclear Information System (INIS)

    Morimoto, C.N.; Hunter, T.A.; Chiang, S.C.

    2004-01-01

    A nuclear power plant equipment monitoring system monitors plant equipment and reports deteriorating equipment conditions. The more advanced equipment monitoring systems can also provide information for understanding the symptoms and diagnosing the root cause of a problem. Maximizing the equipment availability and minimizing or eliminating consequential damages are the ultimate goals of equipment monitoring systems. GE Integrated Equipment Monitoring System (GEIEMS) is designed as an integrated intelligent monitoring and analysis system for plant-wide application for BWR plants. This approach reduces system maintenance efforts and equipment monitoring costs and provides information for integrated planning. This paper describes GEIEMS and how the current system is being upgraded to meet General Electric's vision for plant-wide decision support. (author)

  9. Fault Diagnosis in Dynamic Systems Using Fuzzy Interacting Observers

    Directory of Open Access Journals (Sweden)

    N. V. Kolesov

    2013-01-01

    Full Text Available A method of fault diagnosis in dynamic systems based on a fuzzy approach is proposed. The new method possesses two basic specific features which distinguish it from the other known fuzzy methods based on the application of fuzzy logic and a bank of state observers. First, this method uses a bank of interacting observers instead of traditional independent observers. The second specific feature of the proposed method is the assumption that there is no strict boundary between the serviceable and disabled technical states of the system, which makes it possible to specify a decision making rule for fault diagnosis.

  10. Abnormality diagnostic technology for nuclear power plants

    International Nuclear Information System (INIS)

    Ishikawa, Satoshi

    1986-01-01

    In nuclear power plants, it is feared that the failure of the installations containing radioactive substances may inflict serious damage on public and workers. Therefore in nuclear power plants, the ensuring of safety is planned by supposing hypothetical accidents which are not likely to occur from engineering viewpoint, and multiple protection measures are taken in the plant constitution. In addition to the safety measures from such hardware aspect, recently in order to prevent the occurrence of accidents by using various safety-confirming means, and to detect early when any accident occurred, the development and putting in practical use of many monitoring equipments have been promoted. In such background, the development of nuclear power generation supporting system was carried out for five years since fiscal year 1980, subsidized by the Ministry of International Trade and Industry, and in this report, the technology of equipment abnormality diagnosis developed as a part of that project and the diagnostic techniques for actual plants are described. The technology of diagnosing nuclear reactor abnormality includes the diagnosis of loose metal pieces and the abnormal vibration of in-core structures. The detection and diagnosis of valve leak and the diagnosis of the deterioration of detectors are also explained. (Kako, I.)

  11. 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

  12. Transient pattern analysis for fault detection and diagnosis of HVAC systems

    International Nuclear Information System (INIS)

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

    2005-01-01

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

  13. Study on large scale knowledge base with real time operation for autonomous nuclear power plant. 1. Basic concept and expecting performance

    International Nuclear Information System (INIS)

    Ozaki, Yoshihiko; Suda, Kazunori; Yoshikawa, Shinji; Ozawa, Kenji

    1996-04-01

    Since it is desired to enhance availability and safety of nuclear power plants operation and maintenance by removing human factor, there are many researches and developments for intelligent operation or diagnosis using artificial intelligence (AI) technique. We have been developing an autonomous operation and maintenance system for nuclear power plants by substituting AI's and intelligent robots. It is indispensable to use various and large scale knowledge relative to plant design, operation, and maintenance, that is, whole life cycle data of the plant for the autonomous nuclear power plant. These knowledge must be given to AI system or intelligent robots adequately and opportunely. Moreover, it is necessary to insure real time operation using the large scale knowledge base for plant control and diagnosis performance. We have been studying on the large scale and real time knowledge base system for autonomous plant. In the report, we would like to present the basic concept and expecting performance of the knowledge base for autonomous plant, especially, autonomous control and diagnosis system. (author)

  14. Development of simulator for the uranium enrichment plant using a real-time expert system

    International Nuclear Information System (INIS)

    Kodama, Shinichi; Kondo, Kazuhiro.

    1996-01-01

    The uranium enrichment plant simulator of the new material centrifuge cascade for intelligent process monitoring and alarm generation has been developed by applying an artificial intelligence technology. The real time expert shell, G2 has been used for the system development. The UF6 supply system and cascade equipment was modeled using G2. For a detailed calculation of the cascade, the cascade static characteristic FORTRAN program has been used. These calculation results have been used for the diagnosis of a suspicious behavior in measurement data. Especially, when the deviation of the product uranium concentration was detected, the cause of the deviation was inferred from the knowledge base. (author)

  15. Building and application of the plant condition monitoring system for nuclear power plants

    International Nuclear Information System (INIS)

    Ono, S.

    2013-01-01

    To achieve the stable operation of nuclear power plants, we developed the plant condition monitoring system based on the heat and mass balance calculation. This system has adopted the heat balance model based on the actual plant data to find the symptoms of the disorder of the equipment by heat balance changes in the turbine system. (author)

  16. Nuclear plant data systems - some emerging directions

    International Nuclear Information System (INIS)

    Johnson, R.D.; Humphress, G.B.; McCullough, L.D.; Tashjian, B.M.

    1983-01-01

    Significant changes have occurred in recent years in the nuclear power industry to accentuate the need for data systems to support information flow and decision making. Economic conditions resulting in rapid inflation and larger investments in new and existing plants and the need to plan further ahead are primary factors. Government policies concerning environmental control, as well as minimizing risk to the public through increased nuclear safety regulations on operating plants are additional factors. The impact of computer technology on plant data systems, evolution of corporate and plant infrastructures, future plant data, system designs and benefits, and decision making capabilities and data usage support are discussed. (U.K.)

  17. Application of an expert system for real time diagnosis of the limiting conditions for operation in nuclear power plants

    International Nuclear Information System (INIS)

    Paiva, Gustavo Varanda; Schirru, Roberto

    2015-01-01

    In the history of nuclear power plants operation safety is an important factor to be considered and for this, the use of resistant materials and the application of redundant systems are used to make a plant with high reliability. Through the acquisition of experience with time and accidents that happened in the area, it was observed that the importance of creating methods that simplify the operator work in making decisions in accidents scenarios is an important factor in ensuring the safety of nuclear power plants. This work aims to create a program made with the Python language, which with the use of an expert systems be able to apply, in real time, the rules contained in the Limiting Conditions for Operation (LCO) and tell to the operator the occurrence of any limiting conditions and the occurrence of failure to perform the require actions in the time to completion. The generic structure used to represent the knowledge of the expert system was a fault tree where the events of this tree are objects in program. To test the accuracy of the program a simplified model of a fault tree was used that represents the LCO of the nuclear power station named Central Nuclear Almirante Alvaro Alberto 1. With the results obtained in the analysis of the simplified model it was observed a significant reduction in the time to identify the LCO, showing that the implementation of this program to more complex models of fault tree would be viable.(author)

  18. Application of an expert system for real time diagnosis of the limiting conditions for operation in nuclear power plants

    Energy Technology Data Exchange (ETDEWEB)

    Paiva, Gustavo Varanda; Schirru, Roberto, E-mail: gustavopaiva@poli.ufrj.br [Coordenacao dos Programas de Pos-Graduacao em Engenharia (COPPE/UFRJ), Rio de Janeiro, RJ (brazil). Programa de Engenharia Nuclear

    2015-07-01

    In the history of nuclear power plants operation safety is an important factor to be considered and for this, the use of resistant materials and the application of redundant systems are used to make a plant with high reliability. Through the acquisition of experience with time and accidents that happened in the area, it was observed that the importance of creating methods that simplify the operator work in making decisions in accidents scenarios is an important factor in ensuring the safety of nuclear power plants. This work aims to create a program made with the Python language, which with the use of an expert systems be able to apply, in real time, the rules contained in the Limiting Conditions for Operation (LCO) and tell to the operator the occurrence of any limiting conditions and the occurrence of failure to perform the require actions in the time to completion. The generic structure used to represent the knowledge of the expert system was a fault tree where the events of this tree are objects in program. To test the accuracy of the program a simplified model of a fault tree was used that represents the LCO of the nuclear power station named Central Nuclear Almirante Alvaro Alberto 1. With the results obtained in the analysis of the simplified model it was observed a significant reduction in the time to identify the LCO, showing that the implementation of this program to more complex models of fault tree would be viable.(author)

  19. Artificial intelligence tools decision support systems in condition monitoring and diagnosis

    CERN Document Server

    Galar Pascual, Diego

    2015-01-01

    Artificial Intelligence Tools: Decision Support Systems in Condition Monitoring and Diagnosis discusses various white- and black-box approaches to fault diagnosis in condition monitoring (CM). This indispensable resource: Addresses nearest-neighbor-based, clustering-based, statistical, and information theory-based techniques Considers the merits of each technique as well as the issues associated with real-life application Covers classification methods, from neural networks to Bayesian and support vector machines Proposes fuzzy logic to explain the uncertainties associated with diagnostic processes Provides data sets, sample signals, and MATLAB® code for algorithm testing Artificial Intelligence Tools: Decision Support Systems in Condition Monitoring and Diagnosis delivers a thorough evaluation of the latest AI tools for CM, describing the most common fault diagnosis techniques used and the data acquired when these techniques are applied.

  20. A handheld computer-aided diagnosis system and simulated analysis

    Science.gov (United States)

    Su, Mingjian; Zhang, Xuejun; Liu, Brent; Su, Kening; Louie, Ryan

    2016-03-01

    This paper describes a Computer Aided Diagnosis (CAD) system based on cellphone and distributed cluster. One of the bottlenecks in building a CAD system for clinical practice is the storage and process of mass pathology samples freely among different devices, and normal pattern matching algorithm on large scale image set is very time consuming. Distributed computation on cluster has demonstrated the ability to relieve this bottleneck. We develop a system enabling the user to compare the mass image to a dataset with feature table by sending datasets to Generic Data Handler Module in Hadoop, where the pattern recognition is undertaken for the detection of skin diseases. A single and combination retrieval algorithm to data pipeline base on Map Reduce framework is used in our system in order to make optimal choice between recognition accuracy and system cost. The profile of lesion area is drawn by doctors manually on the screen, and then uploads this pattern to the server. In our evaluation experiment, an accuracy of 75% diagnosis hit rate is obtained by testing 100 patients with skin illness. Our system has the potential help in building a novel medical image dataset by collecting large amounts of gold standard during medical diagnosis. Once the project is online, the participants are free to join and eventually an abundant sample dataset will soon be gathered enough for learning. These results demonstrate our technology is very promising and expected to be used in clinical practice.

  1. Development and application of the plant condition monitoring system for nuclear power plants

    International Nuclear Information System (INIS)

    Ono, S.

    2014-01-01

    To achieve the stable operation of nuclear power plants, we developed the plant condition monitoring system based on the heat and mass balance calculation. In this system, it is a significant feature to adopt the sophisticated heat balance model based on the actual plant data to find the symptoms of anomalies in the turbine system from heat balance changes. (author)

  2. Building Up an On-Line Plant Information System for the Emergency Response Center of the Hungarian Nuclear Safety Directorate

    International Nuclear Information System (INIS)

    Vegh, Janos; Major, Csaba; Horvath, Csaba; Hozer, Zoltan; Adorjan, Ferenc; Lux, Ivan; Horvath, Kristof

    2002-01-01

    The main design features, services, and human-machine interface characteristics are described of the CERTA VITA on-line plant information system developed and installed by KFKI AEKI at the Nuclear Safety Directorate (NSD) of the Hungarian Atomic Energy Authority (HAEA) in cooperation with experts from the NSD. The Center for Emergency Response, Training, and Analysis (CERTA) located at the headquarters of NSD, Budapest, Hungary, was established in 1997. The center supports the NSD installation, radiological monitoring, and advisory team in case of nuclear emergencies, with appropriate hardware and software for communication, diagnosis, prognosis, and prediction. The vital information transfer and analysis (VITA) system represents an important part of the CERTA, as it provides for the continuous remote inspection of the four VVER-440/V213 units of the Hungarian Paks nuclear power plant (NPP). The on-line information system maintains a continuous data link with the NPP through a managed leased line that connects CERTA to a gateway computer located at the Paks NPP. The present scope of the system is a result of a 4-yr development project: In addition to the basic safety parameter display functions, the VITA system now includes an on-line break parameter estimation module, an extensive training package based on simulated transients, and on-line data transfer capabilities to feed accident diagnosis/analysis codes

  3. A practical approach to the diagnosis of systemic amyloidoses.

    Science.gov (United States)

    Fernández de Larrea, Carlos; Verga, Laura; Morbini, Patrizia; Klersy, Catherine; Lavatelli, Francesca; Foli, Andrea; Obici, Laura; Milani, Paolo; Capello, Gian Luca; Paulli, Marco; Palladini, Giovanni; Merlini, Giampaolo

    2015-04-02

    Accurate diagnosis of systemic amyloidosis is necessary both for assessing the prognosis and for delineating the appropriate treatment. It is based on histologic evidence of amyloid deposits and characterization of the amyloidogenic protein. We prospectively evaluated the diagnostic performance of immunoelectron microscopy (IEM) of abdominal fat aspirates from 745 consecutive patients with suspected systemic amyloidoses. All cases were extensively investigated with clinical and laboratory data, with a follow-up of at least 18 months. The 423 (56.8%) cases with confirmed systemic forms were used to estimate the diagnostic performance of IEM. Compared with Congo-red-based light microscopy, IEM was equally sensitive (75% to 80%) but significantly more specific (100% vs 80%; P 99% of the cases. IEM of abdominal fat aspirates is an effective tool in the routine diagnosis of systemic amyloidoses. © 2015 by The American Society of Hematology.

  4. Diagnosis and Management of Systemic Sclerosis: A Practical Approach.

    Science.gov (United States)

    Lee, Jason J; Pope, Janet E

    2016-02-01

    Systemic sclerosis is a devastating multisystem rheumatologic condition that is characterized by autoimmunity, tissue fibrosis, obliterative vasculopathy and inflammation. Clinical presentation and course of the condition vary greatly, which complicates both diagnosis and corresponding treatment. In this regard, recent advances in disease understanding, both clinically and biochemically, have led to newer classification criteria for systemic sclerosis that are more inclusive than ever before. Still, significant disease modifying therapies do not yet exist for most patients. Therefore, organ-based management strategies are employed and research has been directed within this paradigm focusing on either the most debilitating symptoms, such as Raynaud's phenomenon, digital ulcers and cutaneous sclerosis, or life-threatening organ involvement such as interstitial lung disease and pulmonary arterial hypertension. The current trends in systemic sclerosis diagnosis, evidence-based treatment recommendations and potential future directions in systemic sclerosis treatment are discussed.

  5. High-temperature gas-cooled reactor steam-cycle/cogeneration lead plant. Plant Protection and Instrumentation System design description

    International Nuclear Information System (INIS)

    1983-01-01

    The Plant Protection and Instrumentation System provides plant safety system sense and command features, actuation of plant safety system execute features, preventive features which maintain safety system integrity, and safety-related instrumentation which monitors the plant and its safety systems. The primary function of the Plant Protection and Instrumentation system is to sense plant process variables to detect abnormal plant conditions and to provide input to actuation devices directly controlling equipment required to mitigate the consequences of design basis events to protect the public health and safety. The secondary functions of the Plant Protection and Instrumentation System are to provide plant preventive features, sybsystems that monitor plant safety systems status, subsystems that monitor the plant under normal operating and accident conditions, safety-related controls which allow control of reactor shutdown and cooling from a remote shutdown area

  6. Organelle-localized potassium transport systems in plants.

    Science.gov (United States)

    Hamamoto, Shin; Uozumi, Nobuyuki

    2014-05-15

    Some intracellular organelles found in eukaryotes such as plants have arisen through the endocytotic engulfment of prokaryotic cells. This accounts for the presence of plant membrane intrinsic proteins that have homologs in prokaryotic cells. Other organelles, such as those of the endomembrane system, are thought to have evolved through infolding of the plasma membrane. Acquisition of intracellular components (organelles) in the cells supplied additional functions for survival in various natural environments. The organelles are surrounded by biological membranes, which contain membrane-embedded K(+) transport systems allowing K(+) to move across the membrane. K(+) transport systems in plant organelles act coordinately with the plasma membrane intrinsic K(+) transport systems to maintain cytosolic K(+) concentrations. Since it is sometimes difficult to perform direct studies of organellar membrane proteins in plant cells, heterologous expression in yeast and Escherichia coli has been used to elucidate the function of plant vacuole K(+) channels and other membrane transporters. The vacuole is the largest organelle in plant cells; it has an important task in the K(+) homeostasis of the cytoplasm. The initial electrophysiological measurements of K(+) transport have categorized three classes of plant vacuolar cation channels, and since then molecular cloning approaches have led to the isolation of genes for a number of K(+) transport systems. Plants contain chloroplasts, derived from photoautotrophic cyanobacteria. A novel K(+) transport system has been isolated from cyanobacteria, which may add to our understanding of K(+) flux across the thylakoid membrane and the inner membrane of the chloroplast. This chapter will provide an overview of recent findings regarding plant organellar K(+) transport proteins. Copyright © 2014 Elsevier GmbH. All rights reserved.

  7. The Northeast Utilities generic plant computer system

    International Nuclear Information System (INIS)

    Spitzner, K.J.

    1980-01-01

    A variety of computer manufacturers' equipment monitors plant systems in Northeast Utilities' (NU) nuclear and fossil power plants. The hardware configuration and the application software in each of these systems are essentially one of a kind. Over the next few years these computer systems will be replaced by the NU Generic System, whose prototype is under development now for Millstone III, an 1150 Mwe Pressurized Water Reactor plant being constructed in Waterford, Connecticut. This paper discusses the Millstone III computer system design, concentrating on the special problems inherent in a distributed system configuration such as this. (auth)

  8. Nuclear plants gain integrated information systems

    International Nuclear Information System (INIS)

    Villavicencio-Ramirez, A.; Rodriquez-Alvarez, J.M.

    1994-01-01

    With the objective of simplifying the complex mesh of computing devices employed within nuclear power plants, modern technology and integration techniques are being used to form centralized (but backed up) databases and distributed processing and display networks. Benefits are immediate as a result of the integration and the use of standards. The use of a unique data acquisition and database subsystem optimizes the high costs of engineering, as this task is done only once for the life span of the system. This also contributes towards a uniform user interface and allows for graceful expansion and maintenance. This article features an integrated information system, Sistema Integral de Informacion de Proceso (SIIP). The development of this system enabled the Laguna Verde Nuclear Power plant to fully use the already existing universe of signals and its related engineering during all plant conditions, namely, start up, normal operation, transient analysis, and emergency operation. Integrated systems offer many advantages over segregated systems, and this experience should benefit similar development efforts in other electric power utilities, not only for nuclear but also for other types of generating plants

  9. Application of Equipment Monitoring Technology in Nuclear Power Plants

    International Nuclear Information System (INIS)

    Kang, H. T.; Lee, J. K.; Lee, K. D.; Jo, S. H.

    2012-01-01

    The major goal of nuclear power industries during the past 10 years is to increase reliability and utility capacity factor. As the capacitor factor, however, crept upward. it became harder to attain next percentage of improvement. Therefore other innovative technologies are required. By the technologies applied to the fossil power plants, equipment health monitoring was performed on equipment to maintain it in operable condition and contributed on improving their reliability a lot. But the equipment monitoring may be limited to the observation of current system states in nuclear power plant. Monitoring of current system states is being augmented with prediction of future operating states and predictive diagnosis of future failure states. Such predictive diagnosis is motivated by the need for nuclear power plants to optimize equipment performance and reduce costs and unscheduled downtime. This paper reviews the application of techniques that focus on improving reliability in nuclear power plant by monitoring and predicting equipment health and suggests how possible to support on-line monitoring

  10. Intelligent operation system for nuclear power plants

    International Nuclear Information System (INIS)

    Morioka, Toshihiko; Fukumoto, Akira; Suto, Osamu; Naito, Norio.

    1987-01-01

    Nuclear power plants consist of many systems and are operated by skillful operators with plenty of knowledge and experience of nuclear plants. Recently, plant automation or computerized operator support systems have come to be utilized, but the synthetic judgment of plant operation and management remains as human roles. Toshiba is of the opinion that the activities (planning, operation and maintenance) should be integrated, and man-machine interface should be human-friendly. We have begun to develop the intelligent operation system aiming at reducing the operator's role within the fundamental judgment through the use of artificial intelligence. (author)

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

    International Nuclear Information System (INIS)

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

    2012-01-01

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

  12. Design of comprehensive plant information system considering maintenance indicators in nuclear power plant

    International Nuclear Information System (INIS)

    Takata, Takashi; Yamaguchi, Akira; Yamamoto, Akio

    2013-01-01

    A safety of a nuclear power plant must be ensured and maintained through its entire plant life. For this plant life cycle safety (PLCS), a comprehensive plant information system, in which an each maintenance record of the plant is taken into consideration, is of importance. In this paper, a development of a plant chart, which is a part of the information system, has been developed based on a defense-in-depth concept that is one of the most important concept to ensure the plant safety. In the chart, an updated probability of loss of a component or function is used as a maintenance indicator and a probabilistic risk assessment (PRA) method is applied to quantify the plant status in the chart. (author)

  13. Development of the Inspection and Diagnosis Technology for the NSSS Components Integrity

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Jae Hee; Eom, Heung Soup; Lee, Jae Cheol and others

    2005-02-15

    This project aims at the development of new technologies for a monitoring, inspection, diagnosis and evaluation of the safety related components in nuclear power plants. These technologies are required to detect the defects in the components of nuclear power plants and to prepare thoroughly against accidents. We performed the 1st stage of the study on the four issues recently focused. Thus we developed an analysis model of dynamic characteristics on the reactor internals, an on-line monitoring technology using an ultrasonic guided wave, a network based remote inspection system and an inspection robot for a control rod guide tube support pin. We also performed a lifetime estimation and degradation analysis of the NPP cables through accelerated degradation tests. The technologies developed in this project are applied to the components of nuclear power plants. The applications include a localization of the NSSS integrity monitoring system, replacement of an in-service inspection by on-line monitoring, remote inspection of the major components of the plants, lifetime estimation of the degraded plant cables, and so on. Elemental technologies obtained through the project can have great ripple effects in general industry, and can be applied to the inspection and diagnosis of the components in the other industries.

  14. Development of the Inspection and Diagnosis Technology for the NSSS Components Integrity

    International Nuclear Information System (INIS)

    Kim, Jae Hee; Eom, Heung Soup; Lee, Jae Cheol and others

    2005-02-01

    This project aims at the development of new technologies for a monitoring, inspection, diagnosis and evaluation of the safety related components in nuclear power plants. These technologies are required to detect the defects in the components of nuclear power plants and to prepare thoroughly against accidents. We performed the 1st stage of the study on the four issues recently focused. Thus we developed an analysis model of dynamic characteristics on the reactor internals, an on-line monitoring technology using an ultrasonic guided wave, a network based remote inspection system and an inspection robot for a control rod guide tube support pin. We also performed a lifetime estimation and degradation analysis of the NPP cables through accelerated degradation tests. The technologies developed in this project are applied to the components of nuclear power plants. The applications include a localization of the NSSS integrity monitoring system, replacement of an in-service inspection by on-line monitoring, remote inspection of the major components of the plants, lifetime estimation of the degraded plant cables, and so on. Elemental technologies obtained through the project can have great ripple effects in general industry, and can be applied to the inspection and diagnosis of the components in the other industries

  15. Diablo Canyon plant information management system and integrated communication system

    International Nuclear Information System (INIS)

    Stanley, J.W.; Groff, C.

    1990-01-01

    The implementation of a comprehensive maintenance system called the plant information management system (PIMS) at the Diablo Canyon plant, together with its associated integrated communication system (ICS), is widely regarded as the most comprehensive undertaking of its kind in the nuclear industry. This paper provides an overview of the program at Diablo Canyon, an evaluation of system benefits, and highlights the future course of PIMS

  16. Diablo Canyon plant information management system and integrated communication system

    Energy Technology Data Exchange (ETDEWEB)

    Stanley, J.W.; Groff, C.

    1990-06-01

    The implementation of a comprehensive maintenance system called the plant information management system (PIMS) at the Diablo Canyon plant, together with its associated integrated communication system (ICS), is widely regarded as the most comprehensive undertaking of its kind in the nuclear industry. This paper provides an overview of the program at Diablo Canyon, an evaluation of system benefits, and highlights the future course of PIMS.

  17. Prototype of an expert system based nuclear power plant information systems

    International Nuclear Information System (INIS)

    Vegh, J.; Bodnar, M.; Buerger, L.; Tanyi, M.; Sefesik, F.

    1994-01-01

    The components and functioning of the GPCS information system applicable for intelligent process monitoring and alarm generation in a WWER-440 type nuclear power plant are described. The prototype system has been developed by using the G2 expert system, plant measurements were simulated by a WWER-440 compact simulator and by archive replay sessions performed by the VERONA-u core monitoring system. The GPCS contains an object oriented description of the basic subsystems of the plant and concentrates on the fast evaluation/displaying of measurements and alarms. The high-level information reflecting actual plant safety status is synthesized from primary measured data, by forming global alarms and by evaluating logical diagrams. (author). 10 refs, 4 figs

  18. Plant dynamics studies towards design of plant protection system for PFBR

    Energy Technology Data Exchange (ETDEWEB)

    Natesan, K., E-mail: natesan@igcar.gov.in [Nuclear and Safety Engineering Group, Indira Gandhi Centre for Atomic Research, Kalpakkam 603 102 (India); Kasinathan, N.; Velusamy, K.; Selvaraj, P.; Chellapandi, P. [Nuclear and Safety Engineering Group, Indira Gandhi Centre for Atomic Research, Kalpakkam 603 102 (India)

    2012-09-15

    Highlights: Black-Right-Pointing-Pointer Analysis of various design basis events in a fast breeder reactor towards design of plant protection system. Black-Right-Pointing-Pointer Plant dynamic modeling of a sodium cooled fast breeder reactor. Black-Right-Pointing-Pointer Selection of optimum set of plant parameters for considering best plant availability. - Abstract: Prototype fast breeder reactor (PFBR) is a 500 MWe (1250 MWt) liquid sodium cooled pool type reactor currently under construction in India. For a safe and efficient operation of the plant, it is necessary that the reactor is protected from all the transients that may occur in the plant. In order to accomplish this, adequate number of SCRAM parameters is required in the plant protection system with reliable instrumentation. For identifying the SCRAM parameters, the neutronic and thermal hydraulic responses of the plant for various possible events need to be established. Towards this, a one dimensional plant dynamics code DYANA-P has been developed with thermal hydraulic models for reactor core, hot and cold pools, intermediate heat exchangers, pipelines, steam generator, primary sodium circuits and secondary sodium circuits. The code also incorporates neutron kinetics and reactivity feedback models. By a comprehensive plant dynamics study an optimum list of SCRAM parameters and the maximum permissible response time for various instruments used for deriving them have been arrived at.

  19. Diagnosis of mechanical pumping system using neural networks and system parameters analysis

    International Nuclear Information System (INIS)

    Tsai, Tai Ming; Wang, Wei Hui

    2009-01-01

    Normally, a mechanical pumping system is equipped to monitor some of the important input and output signals which are set to the prescribed values. This paper addressed dealing with these signals to establish the database of input- output relation by using a number of neural network models through learning algorithms. These signals encompass normal and abnormal running conditions. The abnormal running conditions were artificially generated. Meanwhile, for the purpose of setting up an on-line diagnosis network, the learning speed and accuracy of three kinds of networks, viz., the backpropagation (BPN), radial basis function (RBF) and adaptive linear (ADALINE) neural networks have been compared and assessed. The assessment criteria of the networks are compared with the correlation result matrix in terms of the neuron vectors. Both BPN and RBF are judged by the maximum vector based on the post-regression analysis, and the ADALINE is judged by the minimum vector based on the least mean square error analysis. By ignoring the neural network training time, it has been shown that if the mechanical diagnosis system is tackled off-line, the RBF method is suggested. However, for on-line diagnosis, the BPN method is recommended

  20. Diagnosis of mechanical pumping system using neural networks and system parameters analysis

    Energy Technology Data Exchange (ETDEWEB)

    Tsai, Tai Ming; Wang, Wei Hui [National Taiwan Ocean University, Keelung (China)

    2009-01-15

    Normally, a mechanical pumping system is equipped to monitor some of the important input and output signals which are set to the prescribed values. This paper addressed dealing with these signals to establish the database of input- output relation by using a number of neural network models through learning algorithms. These signals encompass normal and abnormal running conditions. The abnormal running conditions were artificially generated. Meanwhile, for the purpose of setting up an on-line diagnosis network, the learning speed and accuracy of three kinds of networks, viz., the backpropagation (BPN), radial basis function (RBF) and adaptive linear (ADALINE) neural networks have been compared and assessed. The assessment criteria of the networks are compared with the correlation result matrix in terms of the neuron vectors. Both BPN and RBF are judged by the maximum vector based on the post-regression analysis, and the ADALINE is judged by the minimum vector based on the least mean square error analysis. By ignoring the neural network training time, it has been shown that if the mechanical diagnosis system is tackled off-line, the RBF method is suggested. However, for on-line diagnosis, the BPN method is recommended

  1. An automated, high-throughput plant phenotyping system using machine learning-based plant segmentation and image analysis.

    Science.gov (United States)

    Lee, Unseok; Chang, Sungyul; Putra, Gian Anantrio; Kim, Hyoungseok; Kim, Dong Hwan

    2018-01-01

    A high-throughput plant phenotyping system automatically observes and grows many plant samples. Many plant sample images are acquired by the system to determine the characteristics of the plants (populations). Stable image acquisition and processing is very important to accurately determine the characteristics. However, hardware for acquiring plant images rapidly and stably, while minimizing plant stress, is lacking. Moreover, most software cannot adequately handle large-scale plant imaging. To address these problems, we developed a new, automated, high-throughput plant phenotyping system using simple and robust hardware, and an automated plant-imaging-analysis pipeline consisting of machine-learning-based plant segmentation. Our hardware acquires images reliably and quickly and minimizes plant stress. Furthermore, the images are processed automatically. In particular, large-scale plant-image datasets can be segmented precisely using a classifier developed using a superpixel-based machine-learning algorithm (Random Forest), and variations in plant parameters (such as area) over time can be assessed using the segmented images. We performed comparative evaluations to identify an appropriate learning algorithm for our proposed system, and tested three robust learning algorithms. We developed not only an automatic analysis pipeline but also a convenient means of plant-growth analysis that provides a learning data interface and visualization of plant growth trends. Thus, our system allows end-users such as plant biologists to analyze plant growth via large-scale plant image data easily.

  2. Development of 3D VR plant digital information system

    International Nuclear Information System (INIS)

    Suh, Kune Y.; Ryu, Joong W.; Kang, Myung G.; Kim, H. Y.; Cho, J. G.; Kim, D. H.; Park, J. W.

    2006-07-01

    Currently, there are many ongoing efforts to shorten the plant refueling and maintenance outage durations, and it is expected to become more active as the time goes on. Improved training and education system are required for the personnel to perform efficient inspection on time. This work is focused on establishing virtual Nuclear Power Plant system which will help train the personnel to understand the system characteristics of the plant by creating navigation enabled 3D plant mockups. Furthermore, this project is aimed at constructing information management system over the whole plant area, by integrating safety related data and combining it with web based GUI technology, to make search and management activities easy. This project spans three years. The forst year was spent in 3D mockup modeling of most part of the plant, and prototyping the web based VR plant digital information system. Plant environment, buildings, reactor structure, steam generator, pressurizer, fuel assemblies, pressurizer safety valve, main steamline safety valve, reactor coolant system, main steamline system, auxiliary and main coolant supply system were modeled into 3D mockups. Control functions such as magnification, rotation, movement, transparency, location detection, cross-cut view, full screen toggle and screen capture were implemented to facilitate manipulation of and navigation through the VR mockups. It is expected that the VR plant will serve as an effective support system for power plant regulation and inspection

  3. Plant computer system in nuclear power station

    International Nuclear Information System (INIS)

    Kato, Shinji; Fukuchi, Hiroshi

    1991-01-01

    In nuclear power stations, centrally concentrated monitoring system has been adopted, and in central control rooms, large quantity of information and operational equipments concentrate, therefore, those become the important place of communication between plants and operators. Further recently, due to the increase of the unit capacity, the strengthening of safety, the problems of man-machine interface and so on, it has become important to concentrate information, to automate machinery and equipment and to simplify them for improving the operational environment, reliability and so on. On the relation of nuclear power stations and computer system, to which attention has been paid recently as the man-machine interface, the example in Tsuruga Power Station, Japan Atomic Power Co. is shown. No.2 plant in the Tsuruga Power Station is a PWR plant with 1160 MWe output, which is a home built standardized plant, accordingly the computer system adopted here is explained. The fundamental concept of the central control board, the process computer system, the design policy, basic system configuration, reliability and maintenance, CRT display, and the computer system for No.1 BWR 357 MW plant are reported. (K.I.)

  4. Ventilation-air conditioner system in nuclear power plant

    International Nuclear Information System (INIS)

    Kubota, Ryuji; Sugisaki, Toshihiko.

    1989-01-01

    This invention concerns a ventilation-air conditioner system which enables, upon occurrence of accidents in a nuclear power plant, continuous operation for other adjacent nuclear power plants with no effect of accidents. Air supply system and exhaust system are operated during usual operaiton. If loss of coolants accidents should occur in an adjacent nuclear power plants, operation is switched from ventilation operaiton to the operation of re-cycling system based on an AND logic of three signals, that is, a pressure HIGH signal for the reactor container, a water level LOW signal for the reactor and a radioactivity signal of the ventilation-air conditioner sytem on the side of air supply in the nuclear power plant. Thus, nuclear reactor buildings of the nuclear power plant are from the external atmosphere. Therefore, the radioactivity HIGH signal for switching to the emergency air conditioner system of the nuclear power plant is not actuated due to the loss of coolant accidents in the adjacent nuclear power plant. In addition, since the atmospheric temperature in the nuclear reactor building can be maintained by a cooling device disposed to the recycling system, reactor shutdown can be prevented. (I.S.)

  5. Advanced liquid metal reactor plant control system

    International Nuclear Information System (INIS)

    Dayal, Y.; Wagner, W.; Zizzo, D.; Carroll, D.

    1993-01-01

    The modular Advanced Liquid Metal Reactor (ALMR) power plant is controlled by an advanced state-of-the-art control system designed to facilitate plant operation, optimize availability, and protect plant investment. The control system features a high degree of automatic control and extensive amount of on-line diagnostics and operator aids. It can be built with today's control technology, and has the flexibility of adding new features that benefit plant operation and reduce O ampersand M costs as the technology matures

  6. Diagnosis abnormalities of limb movement in disorders of the nervous system

    Science.gov (United States)

    Tymchik, Gregory S.; Skytsiouk, Volodymyr I.; Klotchko, Tatiana R.; Bezsmertna, Halyna; Wójcik, Waldemar; Luganskaya, Saule; Orazbekov, Zhassulan; Iskakova, Aigul

    2017-08-01

    The paper deals with important issues of diagnosis early signs of diseases of the nervous system, including Parkinson's disease and other specific diseases. Small quantities of violation trajectory of spatial movement of the extremities of human disease at the primary level as the most appropriate features are studied. In modern medical practice is very actual the control the emergence of diseases of the nervous system, including Parkinson's disease. In work a model limbs with six rotational kinematic pairs for diagnosis of early signs of diseases of the nervous system is considered. subject.

  7. A plant control system development approach for IRIS

    International Nuclear Information System (INIS)

    Wood, R.T.; Brittain, C.R.; March-Leuba, J.A.; Conway, L.E.; Oriani, L.

    2003-01-01

    The plant control system concept for the International Reactor Innovative and Secure (IRIS) will make use of integrated control, diagnostic, and decision modules to provide a highly automated intelligent control capability. The plant control system development approach established for IRIS involves determination and verification of control strategies based on whole-plant simulation; identification of measurement, control, and diagnostic needs; development of an architectural framework in which to integrate an intelligent plant control system; and design of the necessary control and diagnostic elements for implementation and validation. This paper describes key elements of the plant control system development approach established for IRIS and presents some of the strategies and methods investigated to support the desired control capabilities. (author)

  8. An Approach to Management of Health Care and Medical Diagnosis Using of a Hybrid Disease Diagnosis System

    Directory of Open Access Journals (Sweden)

    Hodjat Hamidi

    2017-02-01

    Full Text Available Introduction: In order to simplify the information exchange within the medical diagnosis process, a collaborative software agent’s framework is presented. The purpose of the framework is to allow the automated information exchange between different medicine specialists. Methods: This study presented architecture of a hybrid disease diagnosis system. The architecture employed a learning algorithm and used soft computing to build a medical knowledge base. These machine intelligences are combined in a complementary approach to overcome the weakness of each other. To evaluate the hybrid learning algorithm and compare it with other methods, 699 samples were used in each experiment, where 60% was for training, 20% was for cross validation, and 20% for testing. Results: The results were obtained from the experiments on the breast cancer dataset. Different methods of soft computing system were merged to create diagnostic software functionality. As it is shown in the structure, the system has the ability to learn and collect knowledge that can be used in the detection of new images. Currently, the system is at the design stage. The system is to evaluate the performance of hybrid learning algorithm. The preliminary results showed a better performance of this system than other methods. However, the results can be tested with hybrid system on larger data sets to improve hybrid learning algorithm. Conclusion: The purpose of this paper was to simplify the diagnosis process of a patient by splitting the medical domain concepts (e.g., causes, effects, symptoms, tests in human body systems (e.g., respiratory, cardiovascular, though maintaining the holistic perspective through the links between common concepts.

  9. Multilevel flow modeling of Monju Nuclear Power Plant

    DEFF Research Database (Denmark)

    Lind, Morten; Yoshikawa, Hidekazu; Jørgensen, Sten Bay

    2011-01-01

    Multilevel Flow Modeling is a method for modeling complex processes on multiple levels of means-end and part-whole abstraction. The modeling method has been applied on a wide range of processes including power plants, chemical engineering plants and power systems. The modeling method is supported...... with reasoning tools for fault diagnosis and control and is proposed to be used as a central knowledge base giving integrated support in diagnosis and maintenance tasks. Recent developments of MFM include the introduction of concepts for representation of control functions and the relations between plant...... functions and structure. The paper will describe how MFM can be used to represent the goals and functions of the Japanese Monju Nuclear Power Plant. A detailed explanation will be given of the model describing the relations between levels of goal, function and structural. Furthermore, it will be explained...

  10. Towards a systems understanding of plant-microbe interactions

    Directory of Open Access Journals (Sweden)

    Akira eMine

    2014-08-01

    Full Text Available Plants are closely associated with microorganisms including pathogens and mutualists that influence plant fitness. Molecular genetic approaches have uncovered a number of signaling components from both plants and microbes and their mode of actions. However, signaling pathways are highly interconnected and influenced by diverse sets of environmental factors. Therefore, it is important to have systems views in order to understand the true nature of plant-microbe interactions. Indeed, systems biology approaches have revealed previously overlooked or misinterpreted properties of the plant immune signaling network. Experimental reconstruction of biological networks using exhaustive combinatorial mutants is particularly powerful to elucidate network structure and properties and relationships among network components. Recent advances in metagenomics of microbial communities associated with plants further point to the importance of systems approaches and open a research area of microbial community reconstruction. In this review, we highlight the importance of a systems understanding of plant-microbe interactions, with a special emphasis on reconstruction strategies.

  11. Improvement on reliability of control system in power plant

    International Nuclear Information System (INIS)

    Taguchi, S.; Mizumoto, T.; Hirose, Y.; Kashiwai, J.; Takami, I.; Shono, M.; Roji, Y.; Kizaki, S.

    1985-01-01

    Studies made of Japanese PWR operating experiences have revealed that failures in the control system are the primary causes of unscheduled shutdowns. An attempt has, therefore, been made to improve the reliability of the control system in order to raise the plant reliability. The following are the procedures applied to solve the issue; study of operating experiences, fault tree analysis and failure mode and effects analysis. Improvement measures are developed for the control system whose failure threatens to cause the plant trip during the plant life. These systems are the main feedwater control system, rod control system, pressurizer control system and main steam control system in the primary control system. As a result, the plant unavailability is expected to be reduced significantly by applying the improvements. The improvements are applied to the plants under construction and the operating plants in co-operation with utilities and vendors. (author)

  12. Plant-uptake of uranium: Hydroponic and soil system studies

    Science.gov (United States)

    Ramaswami, A.; Carr, P.; Burkhardt, M.

    2001-01-01

    Limited information is available on screening and selection of terrestrial plants for uptake and translocation of uranium from soil. This article evaluates the removal of uranium from water and soil by selected plants, comparing plant performance in hydroponic systems with that in two soil systems (a sandy-loam soil and an organic-rich soil). Plants selected for this study were Sunflower (Helianthus giganteus), Spring Vetch (Vicia sativa), Hairy Vetch (Vicia villosa), Juniper (Juniperus monosperma), Indian Mustard (Brassica juncea), and Bush Bean (Phaseolus nanus). Plant performance was evaluated both in terms of the percent uranium extracted from the three systems, as well as the biological absorption coefficient (BAC) that normalized uranium uptake to plant biomass. Study results indicate that uranium extraction efficiency decreased sharply across hydroponic, sandy and organic soil systems, indicating that soil organic matter sequestered uranium, rendering it largely unavailable for plant uptake. These results indicate that site-specific soils must be used to screen plants for uranium extraction capability; plant behavior in hydroponic systems does not correlate well with that in soil systems. One plant species, Juniper, exhibited consistent uranium extraction efficiencies and BACs in both sandy and organic soils, suggesting unique uranium extraction capabilities.

  13. Transparency and efficiency through plant operations management systems

    International Nuclear Information System (INIS)

    Ladage, L.

    2001-01-01

    Plant operations management systems, being IT application systems, provide integral support of the business processes making up plant operations management. The use of plant operations management systems improves mutually interdependent factors, such as high economic performance, high availability, and maximum safety. Since its commissioning in 1988, the Emsland nuclear power station (KKE) has been run with the IBFS plant operations management system. The work flow management system (WfMS), a module of IBFS, is described as an example of job order processing. IBFS-WfMS is to optimize all processes, thus cutting costs and ensuring that processes are run and documented reliably. Assessing the savings effect achieved through the use of IBFS-WfMS clearly reveals the savings in work/time achieved by the system. These savings are quoted as approx. 4 minutes and DM 10, respectively, per working step, which corresponds to several dozens of manyears or several million DM per annum in the KKE plant under consideration. This result can be extrapolated to other plants. (orig.) [de

  14. Sistem Pakar Diagnosis Hama dan Penyakit Tanaman Hortikultura dengan Teknik Inferensi Forward dan Backward Chaining

    Directory of Open Access Journals (Sweden)

    Ginanjar Wiro Sasmito

    2017-05-01

    Full Text Available One of the obstacles to doing cultivation of horticulture plant is to overcome pest and disease. Pest and disease attack can decrease productivity and even causes harvest fail that influence toward one of income sources the country. Therefore the diagnose on pest and disease must be done fastly and accurately. One of horticulture plant is red onion and chili plant. An expert system is offered as the second choice after expert on consultation. Using Expert System Development Life Cycle (ESDLC method, combination inference engine of and backward chaining for diagnosing pest and horticulture plant disease created as giving the solution. The technique of reasoning used in this research is the rule-based. The result of the research is an application that can be used to diagnosis pest and disease horticulture plant, that are red onion and chili. By this application, the farmer can determine quick action should be taken if the farm pests and diseases, without waiting for a consultation with an expert to do the handling. The application result also could be a learning system to the farmer about pest and disease horticulture plant. Salah satu kendala melakukan budidaya tanaman hortikultura adalah dalam mengatasi hama dan penyakit. Serangan hama dan penyakit dapat menurunkan produktivitas dan bahkan menyebabkan gagal panen yang berpengaruh terhadap salah satu sumber devisa negara. Oleh karena itu, diagnosis terhadap hama dan penyakit harus dilakukan dengan cepat dan akurat. Tanaman hortikultura tersebut salah satunya adalah bawang merah dan cabai. Sistem pakar dihadirkan sebagai pilihan kedua setelah pakar dalam melakukan konsultasi. Dengan menggunakan metode Expert System Development Life Cycle (ESDLC, penggabungan teknik inferensi forward dan backward chaining untuk diagnosis hama dan penyakit tanaman hortikultura dibuat sebagai solusi atas permasalahan yang ada. Teknik penalaran yang digunakan dalam penelitian ini yakni rule-based reasoning. Hasil

  15. Development and realization of the open fault diagnosis system based on XPE

    Science.gov (United States)

    Deng, Hui; Wang, TaiYong; He, HuiLong; Xu, YongGang; Zeng, JuXiang

    2005-12-01

    To make the complex mechanical equipment work in good service, the technology for realizing an embedded open system is introduced systematically, including open hardware configuration, customized embedded operation system and open software structure. The ETX technology is adopted in this system, integrating the CPU main-board functions, and achieving the quick, real-time signal acquisition and intelligent data analysis with applying DSP and CPLD data acquisition card. Under the open configuration, the signal bus mode such as PCI, ISA and PC/104 can be selected and the styles of the signals can be chosen too. In addition, through customizing XPE system, adopting the EWF (Enhanced Write Filter), and realizing the open system authentically, the stability of the system is enhanced. Multi-thread and multi-task programming techniques are adopted in the software programming process. Interconnecting with the remote fault diagnosis center via the net interface, cooperative diagnosis is conducted and the intelligent degree of the fault diagnosis is improved.

  16. The assisting system for uranium enrichment plant operation

    International Nuclear Information System (INIS)

    Nakazawa, Hiroaki; Yamamoto, Fumio

    1990-01-01

    We have been developing an operation assisting system, partially supported by AI system, for uranium enrichment plant. The AI system is a proto-type system aiming a final one which can be applied to any future large uranium enrichment plant and also not only to specific operational area but also to complex and multi-phenomenon operational area. An existing AI system, for example facility diagnostic system that utilizes the result of CCT analysis as knowledge base, has weakness in flexibility and potentiality. To build AI system, we have developed the most suitable knowledge representations using deep knowledge for each facility or operation of uranium enrichment plant. This paper describes our AI proto-type system adopting several knowledge representations that can represent an uranium enrichment plant's operation with deep knowledge. (author)

  17. 75 FR 35457 - Draft of the 2010 Causal Analysis/Diagnosis Decision Information System (CADDIS)

    Science.gov (United States)

    2010-06-22

    ... Causal Analysis/Diagnosis Decision Information System (CADDIS) AGENCY: Environmental Protection Agency... site, ``2010 release of the Causal Analysis/Diagnosis Decision Information System (CADDIS).'' The..., organize, and share information useful for causal evaluations in aquatic systems. CADDIS is based on EPA's...

  18. Carrier system for a plant extract or bioactive compound from a plant

    DEFF Research Database (Denmark)

    2018-01-01

    This invention relates to a carrier system for use in producing a beverage with a metered amount of plant extract or bioactive compound.......This invention relates to a carrier system for use in producing a beverage with a metered amount of plant extract or bioactive compound....

  19. Potential utilities of optimal estimation and control in nuclear power plants

    International Nuclear Information System (INIS)

    Tylee, J.L.; Purviance, J.E.

    1983-01-01

    Optimal estimation and control theories offer the potential for more precise control and diagnosis of nuclear power plants. The important element of these theories is that a mathematical plant model is used in conjunction with the actual plant data to optimize some performance criteria. These criteria involve important plant variables and incorporate a sense of the desired plant performance. Several applications of optimal estimation and control to nuclear systems are discussed

  20. Power plant cooling systems: trends and challenges

    International Nuclear Information System (INIS)

    Rittenhouse, R.C.

    1979-01-01

    A novel design for an intake and discharge system at the Belle River plant is described followed by a general discussion of water intake screens and porous dikes for screening fish and zooplankton. The intake system for the San Onofre PWR plant is described and the state regulations controlling the use of water for power plants is discussed. The use of sewage effluent as a source of cooling water is mentioned with reference to the Palo Verde plant. Progress in dry cooling and a new wet/dry tower due to be installed at the San Juan plant towards the end of this year, complete the survey

  1. Decision support system for the diagnosis of schizophrenia disorders

    Directory of Open Access Journals (Sweden)

    D. Razzouk

    2006-01-01

    Full Text Available Clinical decision support systems are useful tools for assisting physicians to diagnose complex illnesses. Schizophrenia is a complex, heterogeneous and incapacitating mental disorder that should be detected as early as possible to avoid a most serious outcome. These artificial intelligence systems might be useful in the early detection of schizophrenia disorder. The objective of the present study was to describe the development of such a clinical decision support system for the diagnosis of schizophrenia spectrum disorders (SADDESQ. The development of this system is described in four stages: knowledge acquisition, knowledge organization, the development of a computer-assisted model, and the evaluation of the system's performance. The knowledge was extracted from an expert through open interviews. These interviews aimed to explore the expert's diagnostic decision-making process for the diagnosis of schizophrenia. A graph methodology was employed to identify the elements involved in the reasoning process. Knowledge was first organized and modeled by means of algorithms and then transferred to a computational model created by the covering approach. The performance assessment involved the comparison of the diagnoses of 38 clinical vignettes between an expert and the SADDESQ. The results showed a relatively low rate of misclassification (18-34% and a good performance by SADDESQ in the diagnosis of schizophrenia, with an accuracy of 66-82%. The accuracy was higher when schizophreniform disorder was considered as the presence of schizophrenia disorder. Although these results are preliminary, the SADDESQ has exhibited a satisfactory performance, which needs to be further evaluated within a clinical setting.

  2. The Relationship of Learning and Performance Diagnosis at Different System Levels.

    Science.gov (United States)

    Lubega, Khalid

    2003-01-01

    Examines learning and performance diagnosis, separately and in relation to each other, as they function in organization systems; explains the relationship between learning and performance diagnosis at the individual, process, and organizational levels using a three-level performance model; and discusses types of learning, including nonlearning,…

  3. Advanced chemistry management system for nuclear power plants

    International Nuclear Information System (INIS)

    Maeda, Katsuji; Kobayashi, Yasuhiro; Nagasawa, Katsumi

    2000-01-01

    Chemistry control in a boiling water reactor (BWR) plant has a close relationship with radiation field buildup, fuel reliability, integrity of plant components and materials, performance of the water treatment systems and radioactive waste generation. Chemistry management in BWR plants has become more important in order to maintain and enhance plant reliability. Adequate chemistry control and management are also essential to establish, maintain, and enhance plant availability. For these reasons, we have developed the advanced chemistry management system for nuclear power plants in order to effectively collect and evaluate a large number of plant operating and chemistry data. (author)

  4. Development of a GIS-Based Decision Support System for Diagnosis of River System Health and Restoration

    Directory of Open Access Journals (Sweden)

    Jihong Xia

    2014-10-01

    Full Text Available The development of a decision support system (DSS to inform policy making has been progressing rapidly. This paper presents a generic framework and the development steps of a decision tool prototype of geographic information systems (GIS-based decision support system of river health diagnosis (RHD-DSS. This system integrates data, calculation models, and human knowledge of river health status assessment, causal factors diagnosis, and restoration decision making to assist decision makers during river restoration and management in Zhejiang Province, China. Our RHD-DSS is composed of four main elements: the graphical user interface (GUI, the database, the model base, and the knowledge base. It has five functional components: the input module, the database management, the diagnostic indicators management, the assessment and diagnosis, and the visual result module. The system design is illustrated with particular emphasis on the development of the database, model schemas, diagnosis and analytical processing techniques, and map management design. Finally, the application of the prototype RHD-DSS is presented and implemented for Xinjiangtang River of Haining County in Zhejiang Province, China. This case study is used to demonstrate the advantages gained by the application of this system. We conclude that there is great potential for using the RHD-DSS to systematically manage river basins in order to effectively mitigate environmental issues. The proposed approach will provide river managers and designers with improved insight into river degradation conditions, thereby strengthening the assessment process and the administration of human activities in river management.

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

    CERN Document Server

    Ding, Steven X

    2014-01-01

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

  6. Remote Diagnosis of the International Space Station Utilizing Telemetry Data

    Science.gov (United States)

    Deb, Somnath; Ghoshal, Sudipto; Malepati, Venkat; Domagala, Chuck; Patterson-Hine, Ann; Alena, Richard; Norvig, Peter (Technical Monitor)

    2000-01-01

    Modern systems such as fly-by-wire aircraft, nuclear power plants, manufacturing facilities, battlefields, etc., are all examples of highly connected network enabled systems. Many of these systems are also mission critical and need to be monitored round the clock. Such systems typically consist of embedded sensors in networked subsystems that can transmit data to central (or remote) monitoring stations. Moreover, many legacy are safety systems were originally not designed for real-time onboard diagnosis, but a critical and would benefit from such a solution. Embedding additional software or hardware in such systems is often considered too intrusive and introduces flight safety and validation concerns. Such systems can be equipped to transmit the sensor data to a remote-processing center for continuous health monitoring. At Qualtech Systems, we are developing a Remote Diagnosis Server (RDS) that can support multiple simultaneous diagnostic sessions from a variety of remote subsystems.

  7. Preinspection of nuclear power plant systems

    International Nuclear Information System (INIS)

    1975-01-01

    The general plans of the systems affecting the safety of the nuclear power plants are accepted by the Institute of Radiation Protection (IRP) on the basis of the preinspection of the systems. This is the prerequisite of the preinspection of the structures and components belonging to these systems. Exceptionally, when separately agreed, the IRP may perform the preinspection of a separate structure or component, although the preinspection documentation of the whole system, e.g. the nuclear heat generating system, has not been accepted. This guide applies to the nuclear power plant systems that have been defined to be preinspected in the classification document accepted by the IRP

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

    OpenAIRE

    Xiangyu He; Shanghong He

    2014-01-01

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

  9. Expert systems for design, operation and management of industrial plant elctrical systems

    Energy Technology Data Exchange (ETDEWEB)

    Delfino, B.; Forzano, P.; Invernizzi, M.; Massucco, S. (Genoa Univ. (Italy) Pavia Univ. (Italy) Ansaldo Industria, Genoa (Italy))

    1991-02-01

    A discussion is made of modern industrial plant requirements with regard to man-machine interfacing. Indications are then given as to the optimum hardware and software for electrical plant and process control systems. Illustrative examples are provided on the use of expert systems to aid in the design of industrial plant electrical systems and to allow safe and reliable on-line control and monitoring.

  10. Fuel management of mixed reactor type power plant systems

    International Nuclear Information System (INIS)

    Csom, Gyula

    1988-01-01

    Breeding gain in symbiotic nuclear power plant system consisting of both thermal and fast breeder reactors depends on the characteristics and the ratio of thermal and fast reactors. The composition of the symbiotic power plant systems was determined for equilibrium and plutonium deficient systems. According to natural uranium utilization, symbiotic power plant systems are not less efficient than the systems containing only fast breeders. Depleted uranium can be applied in both types of systems. Reprocessing demands of the symbiotic power plant sytems were determined. (V.N.) 23 figs.; 1 tab

  11. Flu Diagnosis System Using Jaccard Index and Rough Set Approaches

    Science.gov (United States)

    Efendi, Riswan; Azah Samsudin, Noor; Mat Deris, Mustafa; Guan Ting, Yip

    2018-04-01

    Jaccard index and rough set approaches have been frequently implemented in decision support systems with various domain applications. Both approaches are appropriate to be considered for categorical data analysis. This paper presents the applications of sets operations for flu diagnosis systems based on two different approaches, such as, Jaccard index and rough set. These two different approaches are established using set operations concept, namely intersection and subset. The step-by-step procedure is demonstrated from each approach in diagnosing flu system. The similarity and dissimilarity indexes between conditional symptoms and decision are measured using Jaccard approach. Additionally, the rough set is used to build decision support rules. Moreover, the decision support rules are established using redundant data analysis and elimination of unclassified elements. A number data sets is considered to attempt the step-by-step procedure from each approach. The result has shown that rough set can be used to support Jaccard approaches in establishing decision support rules. Additionally, Jaccard index is better approach for investigating the worst condition of patients. While, the definitely and possibly patients with or without flu can be determined using rough set approach. The rules may improve the performance of medical diagnosis systems. Therefore, inexperienced doctors and patients are easier in preliminary flu diagnosis.

  12. System and Software Design for the Plant Protection System for Shin-Hanul Nuclear Power Plant Units 1 and 2

    International Nuclear Information System (INIS)

    Hwang, In Seok; Kim, Young Geul; Choi, Woong Seock; Sohn, Se Do

    2015-01-01

    The Reactor Protection System(RPS) protects the core fuel design limits and reactor coolant system pressure boundary for Anticipated Operational Occurrences (AOOs), and provides assistance in mitigating the consequences of Postulated Accidents (PAs). The ESFAS sends the initiation signals to Engineered Safety Feature - Component Control System (ESF-CCS) to mitigate consequences of design basis events. The Common Q platform Programmable Logic Controller (PLC) was used for Shin-Wolsung Nuclear Power Plant Units 1 and 2 and Shin-Kori Nuclear Power Plant Units 1, 2, 3 and 4 since Digital Plant Protection System (DPPS) based on Common Q PLC was applied for Ulchin Nuclear Power Plant Units 5 and 6. The PPS for Shin-Hanul Nuclear Power Plant Units 1 and 2 (SHN 1 and 2) was developed using POSAFE-Q PLC for the first time for the PPS. The SHN1 and 2 PPS was delivered to the sites after completion of Man Machine Interface System Integrated System Test (MMIS-IST). The SHN1 and 2 PPS was developed to have the redundancy in each channel and to use the benefits of POSAFE-Q PLC, such as diagnostic and data communication. The PPS application software was developed using ISODE to minimize development time and human errors, and to improve software quality, productivity, and reusability

  13. System and Software Design for the Plant Protection System for Shin-Hanul Nuclear Power Plant Units 1 and 2

    Energy Technology Data Exchange (ETDEWEB)

    Hwang, In Seok; Kim, Young Geul; Choi, Woong Seock; Sohn, Se Do [KEPCO EnC, Daejeon (Korea, Republic of)

    2015-10-15

    The Reactor Protection System(RPS) protects the core fuel design limits and reactor coolant system pressure boundary for Anticipated Operational Occurrences (AOOs), and provides assistance in mitigating the consequences of Postulated Accidents (PAs). The ESFAS sends the initiation signals to Engineered Safety Feature - Component Control System (ESF-CCS) to mitigate consequences of design basis events. The Common Q platform Programmable Logic Controller (PLC) was used for Shin-Wolsung Nuclear Power Plant Units 1 and 2 and Shin-Kori Nuclear Power Plant Units 1, 2, 3 and 4 since Digital Plant Protection System (DPPS) based on Common Q PLC was applied for Ulchin Nuclear Power Plant Units 5 and 6. The PPS for Shin-Hanul Nuclear Power Plant Units 1 and 2 (SHN 1 and 2) was developed using POSAFE-Q PLC for the first time for the PPS. The SHN1 and 2 PPS was delivered to the sites after completion of Man Machine Interface System Integrated System Test (MMIS-IST). The SHN1 and 2 PPS was developed to have the redundancy in each channel and to use the benefits of POSAFE-Q PLC, such as diagnostic and data communication. The PPS application software was developed using ISODE to minimize development time and human errors, and to improve software quality, productivity, and reusability.

  14. Plant Growth Modeling Using L-System Approach and Its Visualization

    Directory of Open Access Journals (Sweden)

    Atris Suyantohadi

    2011-05-01

    Full Text Available The visualizationof plant growth modeling using computer simulation has rarely been conducted with Lindenmayer System (L-System approach. L-System generally has been used as framework for improving and designing realistic modeling on plant growth. It is one kind of tools for representing plant growth based on grammar sintax and mathematic formulation. This research aimed to design modeling and visualizing plant growth structure generated using L-System. The environment on modeling design used three dimension graphic on standart OpenGL format. The visualization on system design has been developed by some of L-System grammar, and the output graphic on three dimension reflected on plant growth as a virtual plant growth system. Using some of samples on grammar L-System rules for describing of the charaterictics of plant growth, the visualization of structure on plant growth has been resulted and demonstrated.

  15. Intelligent Data Visualization for Cross-Checking Spacecraft System Diagnosis

    Science.gov (United States)

    Ong, James C.; Remolina, Emilio; Breeden, David; Stroozas, Brett A.; Mohammed, John L.

    2012-01-01

    Any reasoning system is fallible, so crew members and flight controllers must be able to cross-check automated diagnoses of spacecraft or habitat problems by considering alternate diagnoses and analyzing related evidence. Cross-checking improves diagnostic accuracy because people can apply information processing heuristics, pattern recognition techniques, and reasoning methods that the automated diagnostic system may not possess. Over time, cross-checking also enables crew members to become comfortable with how the diagnostic reasoning system performs, so the system can earn the crew s trust. We developed intelligent data visualization software that helps users cross-check automated diagnoses of system faults more effectively. The user interface displays scrollable arrays of timelines and time-series graphs, which are tightly integrated with an interactive, color-coded system schematic to show important spatial-temporal data patterns. Signal processing and rule-based diagnostic reasoning automatically identify alternate hypotheses and data patterns that support or rebut the original and alternate diagnoses. A color-coded matrix display summarizes the supporting or rebutting evidence for each diagnosis, and a drill-down capability enables crew members to quickly view graphs and timelines of the underlying data. This system demonstrates that modest amounts of diagnostic reasoning, combined with interactive, information-dense data visualizations, can accelerate system diagnosis and cross-checking.

  16. Sophistication and integration of plant engineering CAD-CAE systems

    International Nuclear Information System (INIS)

    Yoshinaga, Toshiaki; Hanyu, Masaharu; Ota, Yoshimi; Kobayashi, Yasuhiro.

    1995-01-01

    In respective departments in charge of basic planning, design, manufacture, inspection and construction of nuclear power plants, by the positive utilization of CAD/CAE system, efficient workings have been advanced. This time, the plant integrated CAE system wich heightens the function of these individual systems, and can make workings efficient and advanced by unifying and integrating them was developed. This system is composed of the newly developed application system and the data base system which enables the unified management of engineering data and high speed data conversion in addition to the CAD system for three-dimensional plant layout planning. On the basis of the rich experience and the proposal of improvement of designers by the application of the CAD system for three-dimensional plant layout planning to actual machines, the automation, speed increase and the visualization of input and output by graphical user interface (GUI) in the processing of respective applications were made feasible. As the advancement of plant CAE system, scenic engineering system, integrated layout CAE system, electric instrumentation design CAE system and construction planning CAE system are described. As for the integration of plant CAE systems, the integrated engineering data base, the combination of plant CAE systems, and the operation management in the dispersed environment of networks are reported. At present, Hitachi Ltd. exerts efforts for the construction of atomic energy product in formation integrated management system as the second stage of integration. (K.I.)

  17. A Textual Case-Based Mobile Phone Diagnosis Support System ...

    African Journals Online (AJOL)

    In this paper, a Mobile Phone Diagnosis Support System is presented as an extension to jCOLIBRI which accepts a problem and reasons with cases to provide a solution related to a new given problem. Experimental evaluation using some set of problems shows that the developed system predicts the solution that is ...

  18. A Diagnosis Support System for Abnormal Situations of Hanbit Units 3 and 4

    International Nuclear Information System (INIS)

    Kim, Yochan; Jung, Wondea

    2013-01-01

    In contrast with previous research, we separated the flowchart into a search phase of an AOP category and the phase of an AOP in order for the operators to informatively and efficiently find an AOP. Meanwhile, Kang et al. developed a technique to associate alarm response procedures from annunciated alarms and data related with their causes. The search engine in this system, however, associates complex abnormal situations with multiple alarms and considers multiple abnormal situations to be diagnosed. The developed system shows how some advanced digital functions can collaboratively enhance a human operator's cognition. We expect that improvements and integration of these kinds of functions into the instrument and control of an MCR will continue. When an abnormal situation occurs in a nuclear power plant, the operators in the main control room (MCR) diagnose the cause of the abnormal situation based on the occurring alarms. However, because there are many different alarms and abnormal operating procedures (AOPs) in an MCR, it is necessary to develop education techniques or diagnosis supporting tools for aiding operators to efficiently cope with abnormal situations. Owing to the recent development of new power plants and new human resources, the necessity of these techniques and tools has been magnified. There have been some efforts to support operators in diagnosing abnormal situations from annunciated alarms. This paper introduces an integrated system that not only educates operators but also aids operators in searching AOPs under actual situations. For the purpose of education, this system provides flowcharts to find an AOP from annunciated alarms and a mimic alarm window that displays annunciated alarms during a selected abnormal situation. For the purpose of aiding a real-time search, this system has a function that shows AOPs related to the inputted alarm data and calculates the similarity of the AOPs and the alarm data. The system was implemented by Livecode 6

  19. A Diagnosis Support System for Abnormal Situations of Hanbit Units 3 and 4

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Yochan; Jung, Wondea [Korea Atomic Energy Research Institute, Daejeon (Korea, Republic of)

    2013-10-15

    In contrast with previous research, we separated the flowchart into a search phase of an AOP category and the phase of an AOP in order for the operators to informatively and efficiently find an AOP. Meanwhile, Kang et al. developed a technique to associate alarm response procedures from annunciated alarms and data related with their causes. The search engine in this system, however, associates complex abnormal situations with multiple alarms and considers multiple abnormal situations to be diagnosed. The developed system shows how some advanced digital functions can collaboratively enhance a human operator's cognition. We expect that improvements and integration of these kinds of functions into the instrument and control of an MCR will continue. When an abnormal situation occurs in a nuclear power plant, the operators in the main control room (MCR) diagnose the cause of the abnormal situation based on the occurring alarms. However, because there are many different alarms and abnormal operating procedures (AOPs) in an MCR, it is necessary to develop education techniques or diagnosis supporting tools for aiding operators to efficiently cope with abnormal situations. Owing to the recent development of new power plants and new human resources, the necessity of these techniques and tools has been magnified. There have been some efforts to support operators in diagnosing abnormal situations from annunciated alarms. This paper introduces an integrated system that not only educates operators but also aids operators in searching AOPs under actual situations. For the purpose of education, this system provides flowcharts to find an AOP from annunciated alarms and a mimic alarm window that displays annunciated alarms during a selected abnormal situation. For the purpose of aiding a real-time search, this system has a function that shows AOPs related to the inputted alarm data and calculates the similarity of the AOPs and the alarm data. The system was implemented by

  20. Design and development of remote diagnosis center of electric power plant based on multi-source heterogeneous data%基于多源异构数据的电厂远程诊断中心的设计与开发

    Institute of Scientific and Technical Information of China (English)

    黄宏伟; 赵永强; 李永耀

    2017-01-01

    针对目前电厂系统不兼容,进行监测及诊断时需要打开不同系统的问题,提出了基于多源异构数据的电厂远程诊断中心系统.该系统所用到的TDM,SIS,EAM等系统中的振动动态数据及相关的工艺量集成到中心数据库中,将各个数据库有机地整合在一起,实现不同数据库之间的数据共同显示在同一系统中,降低了故障诊断时查看数据的工作量,提高了故障诊断的效率,在电力行业具有广阔的应用前景.%In view of the present system of power plant is not compatible,we need to open different monitoring and diagnosis system problems,puts forward the remote diagnosis of power plant based on multi-source heterogeneous data center system.Used in the system of TDM,SIS,EAM system vibration dynamic data and related technology are integrated into the center database,organic integration of various database together,realize data between different database show together in the same system,reduce the workload of fault diagnosis when the check data,improve the efficiency of fault diagnosis,and will have broad prospect of application in the electric power industry.

  1. Development experience and strategy for the combined algorithm on the alarm processing and diagnosis

    International Nuclear Information System (INIS)

    Chung, Hak-Yeong

    1997-01-01

    In this paper, I presented the development experience on the alarm processing and fault diagnosis which has been achieved from early 1988 to late 1995. The scope covered is the prototype stage, the development stage of on-line operator-aid system, and an intelligent human-machine interface system. In the second part, I proposed a new method (APEXS) of multi-alarm processing to select the causal alarm(s) among occurred alarms by using the time information of each occurred alarm and alarm tree knowledge and the corresponding diagnosis method based on the selected causal alarm(s) by using the prescribed qualitative model. With more knowledge base about the plant and some modification suitable for real environment, APEXS will be able to adapt to a real steam power plant. (author). 18 refs, 3 figs, 1 tab

  2. Plant Systems Biology at the Single-Cell Level.

    Science.gov (United States)

    Libault, Marc; Pingault, Lise; Zogli, Prince; Schiefelbein, John

    2017-11-01

    Our understanding of plant biology is increasingly being built upon studies using 'omics and system biology approaches performed at the level of the entire plant, organ, or tissue. Although these approaches open new avenues to better understand plant biology, they suffer from the cellular complexity of the analyzed sample. Recent methodological advances now allow plant scientists to overcome this limitation and enable biological analyses of single-cells or single-cell-types. Coupled with the development of bioinformatics and functional genomics resources, these studies provide opportunities for high-resolution systems analyses of plant phenomena. In this review, we describe the recent advances, current challenges, and future directions in exploring the biology of single-cells and single-cell-types to enhance our understanding of plant biology as a system. Copyright © 2017 Elsevier Ltd. All rights reserved.

  3. New developments in online plant monitoring

    International Nuclear Information System (INIS)

    Laipple, Bernd; Langenstein, Magnus

    2007-01-01

    The large quantities of information produced within plant processes nearly make the plausibility of data impossible without the help of additional tools. For this reason, a variety of plant monitoring tools has been developed in the past which promise a sensible compression of data. The main problem with the offered tools lies with the omission of procedural plausibility. The newly developed plant monitoring system BTB ProcessPlus is based on the VDI 2048 methodology of process data reconciliation. Plausibility and quality control therefore serve as a basis for the system. With this procedural process image, significant diagnosis and monitoring tools have been developed and now offer a fast and economically optimal support in process optimization. This paper describes the methodology according to VDI 2048. The benefits of the online plant monitoring system are demonstrated by means of examples from day-to-day operations. (author)

  4. Photovoltaic pilot plant of Vulcano (Italy)

    Energy Technology Data Exchange (ETDEWEB)

    Menga, P.; Previ, A.

    1988-12-31

    The rated peak power of the Vulcano plant is about 80 kW. The main feature of the plant lies in its dual operating mode: either stand-alone or grid-connected. The plant, commissioned half-way through 1984, has always worked uninterruptedly and satisfactorily and, for this reason, it is expected to keep on operating in the coming years. Beginning from 1987, it has been considered worth carrying out research on a number of specific points not so far dealt with in sufficient detail in literature, as follows: experimental research on the deterioration, over a period of time, of the characteristics of the modules of the plant; theoretical and experimental research on the plant`s electrochemical storage system. The research on the second of the above subjects has a number of aims: to improve methods of checking the state of charge of batteries in newly-designed photovoltaic plants; to improve the ways in which the Vulcano battery storage system is operated; and to monitor and make a careful diagnosis of the condition of the plant`s battery.

  5. 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

  6. Verification test for on-line diagnosis algorithm based on noise analysis

    International Nuclear Information System (INIS)

    Tamaoki, T.; Naito, N.; Tsunoda, T.; Sato, M.; Kameda, A.

    1980-01-01

    An on-line diagnosis algorithm was developed and its verification test was performed using a minicomputer. This algorithm identifies the plant state by analyzing various system noise patterns, such as power spectral densities, coherence functions etc., in three procedure steps. Each obtained noise pattern is examined by using the distances from its reference patterns prepared for various plant states. Then, the plant state is identified by synthesizing each result with an evaluation weight. This weight is determined automatically from the reference noise patterns prior to on-line diagnosis. The test was performed with 50 MW (th) Steam Generator noise data recorded under various controller parameter values. The algorithm performance was evaluated based on a newly devised index. The results obtained with one kind of weight showed the algorithm efficiency under the proper selection of noise patterns. Results for another kind of weight showed the robustness of the algorithm to this selection. (orig.)

  7. Ontology based decision system for breast cancer diagnosis

    Science.gov (United States)

    Trabelsi Ben Ameur, Soumaya; Cloppet, Florence; Wendling, Laurent; Sellami, Dorra

    2018-04-01

    In this paper, we focus on analysis and diagnosis of breast masses inspired by expert concepts and rules. Accordingly, a Bag of Words is built based on the ontology of breast cancer diagnosis, accurately described in the Breast Imaging Reporting and Data System. To fill the gap between low level knowledge and expert concepts, a semantic annotation is developed using a machine learning tool. Then, breast masses are classified into benign or malignant according to expert rules implicitly modeled with a set of classifiers (KNN, ANN, SVM and Decision Tree). This semantic context of analysis offers a frame where we can include external factors and other meta-knowledge such as patient risk factors as well as exploiting more than one modality. Based on MRI and DECEDM modalities, our developed system leads a recognition rate of 99.7% with Decision Tree where an improvement of 24.7 % is obtained owing to semantic analysis.

  8. Optimal planting systems for cut gladiolus and stock production

    Directory of Open Access Journals (Sweden)

    Iftikhar Ahmad

    2017-10-01

    Full Text Available A study was conducted to elucidate the effect of different planting systems, videlicet (viz. flat, ridge, and raised bed system on growth, yield and quality of gladiolus and stock. Corms of ‘Rose Supreme’ and ‘White Prosperity’ gladiolus and seedlings of ‘Cheerful White’, ‘Lucinda Dark Rose Double’ and ‘Lucinda Dark Rose Single’ stock were planted on different planting systems in individual experiments for each species. Gladiolus had similar good quality production irrespective of planting systems with numerical superiority of ridge planting, which produced longer stems with higher stem fresh weight, but delayed corm sprouting by ca. 1 d compared to raised bed or flat planting system. Among cultivars, ‘Rose Supreme’ produced higher number of florets per spike, taller stems with longer spikes, higher fresh weight of stems and higher number of cormels than ‘White Prosperity’. Stock plants grown on flat beds produced stems with greater stem length, leaf area and fresh weight of stems compared to ridge or raised bed planting systems. Plants grown on ridges produced the highest stem diameter, number of leaves per plant, total leaf chlorophyll contents, and number of flowers per spike. ‘Cheerful White’ and ‘Lucinda Dark Rose Double’ performed best by producing good quality stems in shorter period compared to ‘Lucinda Dark Rose Single’. In summary, gladiolus should be grown on ridges, while stock may be planted on flat beds for higher yields of better quality flowers.

  9. The Intelligent System of Cardiovascular Disease Diagnosis Based on Extension Data Mining

    Science.gov (United States)

    Sun, Baiqing; Li, Yange; Zhang, Lin

    This thesis gives the general definition of the concepts of extension knowledge, extension data mining and extension data mining theorem in high dimension space, and also builds the IDSS integrated system by the rough set, expert system and neural network, develops the relevant computer software. From the diagnosis tests, according to the common diseases of myocardial infarctions, angina pectoris and hypertension, and made the test result with physicians, the results shows that the sensitivity, specific and accuracy diagnosis by the IDSS are all higher than the physicians. It can improve the rate of the accuracy diagnosis of physician with the auxiliary help of this system, which have the obvious meaning in low the mortality, disability rate and high the survival rate, and has strong practical values and further social benefits.

  10. Multipurpose expert-robot system model for control, diagnosis, maintenance, and repairs at the steam generators of the NPP

    International Nuclear Information System (INIS)

    Popa, I.

    1994-01-01

    The paper presents the model concept for a multipurpose expert-robot system for control, diagnosis, forecast, maintenance, and repairs at the steam generators of CANDU type nuclear power plants. The system has two separate parts: the expert system and the robot (manipulator) system. These parts compose a hierarchic structure with the expert system on the upper level. The expert system has a blackboard architecture, to which tree interfaces with the robot system, with the control system of the NPP and with the methods and techniques of control, maintenance and repairs system of the steam generator are added. Due to complex nature of its activities the expert-robot system model combines the deterministic type reasons with probabilistic, fuzzy, and neural-networks type ones. The information that enter the expert system comes from the robot system, from process, from user, and human expert. The information that enter robot system comes from the expert system, from the human operator (when connected) and from process. Control maintenance and repair operations take place by means of the robot system that can be monitored either directly by the expert system or by the human operator who follows its activity. All these activities are performed in parallel with the adequate information of the expert system directly, by the human operator, about the status parameters and, possibly, operating parameters of the steam generator components. The expert-robot system can work independently, but it can be connected and integrated in the control system of NPP, to take over and develop some of its functions. The activities concerning diagnosis and characterization of the state of steam generator components subsequent to control, as well as the forecast of their future behavior, are performed by means of the expert system. Due to these characteristics the expert-robot system can be used successfully in personnel training activities. (Author)

  11. Diagnostic and prognostic system for identification of accident scenarios and prediction of 'source term' in nuclear power plants under accident conditions

    International Nuclear Information System (INIS)

    Santhosh; Gera, B.; Kumar, Mithilesh

    2014-01-01

    Nuclear power plant experiences a number of transients during its operations. These transients may be due to equipment failure, malfunctioning of process support systems etc. In such a situation, the plant may result in an abnormal state which is undesired. In case of such an undesired plant condition, the operator has to carry out diagnostic and corrective actions. When an event occurs starting from the steady state operation, instruments' readings develop a time dependent pattern and these patterns are unique with respect to the type of the particular event. Therefore, by properly selecting the plant process parameters, the transients can be distinguished. In this connection, a computer based tool known as Diagnostic and Prognostic System has been developed for identification of large pipe break scenarios in 220 MWe Pressurised Heavy Water Reactors (PHWRs) and for prediction of expected 'Source Term' and consequence for a situation where Emergency Core Cooling System (ECCS) is not available or partially available. Diagnostic and Prognostic System is essentially a transient identification and expected source term forecasting system. The system is based on Artificial Neural Networks (ANNs) that continuously monitors the plant conditions and identifies a Loss Of Coolant Accident (LOCA) scenario quickly based on the reactor process parameter values. The system further identifies the availability of injection of ECCS and in case non-availability of ECCS, it can forecast expected 'Source Term'. The system is a support to plant operators as well as for emergency preparedness. The ANN is trained with a process parameter database pertaining to accident conditions and tested against blind exercises. In order to see the feasibility of implementing in the plant for real-time diagnosis, this system has been set up on a high speed computing facility and has been demonstrated successfully for LOCA scenarios. (author)

  12. Method of modelization assistance with bond graphs and application to qualitative diagnosis of physical systems

    International Nuclear Information System (INIS)

    Lucas, B.

    1994-05-01

    After having recalled the usual diagnosis techniques (failure index, decision tree) and those based on an artificial intelligence approach, the author reports a research aimed at exploring the knowledge and model generation technique. He focuses on the design of an aid to model generation tool and aid-to-diagnosis tool. The bond graph technique is shown to be adapted to the aid to model generation, and is then adapted to the aid to diagnosis. The developed tool is applied to three projects: DIADEME (a diagnosis system based on physical model), the improvement of the SEXTANT diagnosis system (an expert system for transient analysis), and the investigation on an Ariane 5 launcher component. Notably, the author uses the Reiter and Greiner algorithm

  13. The condition monitoring system of turbine system components for nuclear power plants

    International Nuclear Information System (INIS)

    Ono, Shigetoshi

    2013-01-01

    The thermal and nuclear power plants have been imposed a stable supply of electricity. To certainly achieve this, we built the plant condition monitoring system based on the heat and mass balance calculation. If there are some performance changes on the turbine system components of their power plants, the heat and mass balance of the turbine system will change. This system has ability to detect the abnormal signs of their components by finding the changes of the heat and mass balance. Moreover we note that this system is built for steam turbine cycle operating with saturated steam conditions. (author)

  14. Guidelines for multipurpose data systems for nuclear power plants

    International Nuclear Information System (INIS)

    1994-07-01

    This TECDOC is intended to provide guidance on implementing a system to provide the staff and management of a nuclear power plant with data and information specific to the plant, to assist in making decisions concerning plant operation and maintenance. The guidelines do not deal with issues relating to software and hardware for database management owing to the rapid evolution in these technologies. It will be up to individual utilities to select a suitable technology to meet their data system needs. The guidelines are intended to help a utility with operating plants and/or plants under construction to implement a system which best suits its needs for the compilation of plant specific data. The plant specific data will in turn help in generating quantitative and qualitative results and insights to support decision making for optimized plant operation and maintenance. The guidelines are supplemented by examples of the data systems in use at the utilities that contributed to the preparation of the document Figs and tabs

  15. A nuclear power plant system engineering workstation

    International Nuclear Information System (INIS)

    Mason, J.H.; Crosby, J.W.

    1989-01-01

    System engineers offer an approach for effective technical support for operation and maintenance of nuclear power plants. System engineer groups are being set up by most utilities in the United States. Institute of Nuclear Power operations (INPO) and U.S. Nuclear Regulatory Commission (NRC) have endorsed the concept. The INPO Good Practice and a survey of system engineer programs in the southeastern United States provide descriptions of system engineering programs. The purpose of this paper is to describe a process for developing a design for a department-level information network of workstations for system engineering groups. The process includes the following: (1) application of a formal information engineering methodology, (2) analysis of system engineer functions and activities; (3) use of Electric Power Research Institute (EPRI) Plant Information Network (PIN) data; (4) application of the Information Engineering Workbench. The resulting design for this system engineer workstation can provide a reference for design of plant-specific systems

  16. Initial diagnosis and treatment in first-episode psychosis: can an operationalized diagnostic classification system enhance treating clinicians' diagnosis and the treatment chosen?

    LENUS (Irish Health Repository)

    Coentre, Ricardo

    2011-05-01

    Diagnosis during the initial stages of first-episode psychosis is particularly challenging but crucial in deciding on treatment. This is compounded by important differences in the two major classification systems, International Classification of Diseases, 10th revision (ICD-10) and Diagnostic and Statistical Manual of Mental Disorders, fourth edition (DSM-IV). We aimed to compare the concordance between an operationalized diagnosis using Operational Criteria Checklist (OPCRIT) and treating clinician-generated diagnosis in first episode psychosis diagnosis and its correlation with treatment prescribed.

  17. Plant risk status information management system

    International Nuclear Information System (INIS)

    Campbell, D.J.; Ellison, B.C.; Glynn, J.C.; Flanagan, G.F.

    1985-01-01

    The Plant Risk Status Information Management System (PRISIMS) is a PC program that presents information about a nuclear power plant's design, its operation, its technical specifications, and the results of the plant's probabilistic risk assessment (PRA) in a logically and easily accessible format. PRISIMS provides its user with unique information for integrating safety concerns into day-to-day operational decisions and/or long-range management planning

  18. Active Fault Diagnosis in Sampled-data Systems

    DEFF Research Database (Denmark)

    Niemann, Hans Henrik; Poulsen, Niels Kjølstad

    2015-01-01

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

  19. 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

  20. Development of plant status display system for on-site educational training system

    International Nuclear Information System (INIS)

    Yoshimura, Seiichi; Fujimoto, Junzo; Okamoto, Hisatake; Tsunoda, Ryohei; Watanabe, Takao; Masuko, Jiro.

    1986-01-01

    The purpose of this system is to make easy the comprehension of the facility and dynamics of nuclear power plants. This report describes the tendency and future position of how the educational training system should be, and furthermore describes the experiment. Main results are as follows. 1. The present status and the future tendency of educational training system for nuclear power plant operators. CAI (Computer Assisted Instruction) system has following characteristics. (1) It is easy to introduce plant specific characteristics to the educational training. (2) It is easy to execute the detailed training for the compensation of the full-scale simulator. 2. Plant status display system for on-site educational training system. The fundamental function of the system is as follows. (1) It has 2 CRT displays and voice output devices. (2) It has easy manupulation type of man-machine interface. (3) It has the function for the evaluation of the training results. 3. The effectiveness of this system. The effectiveness evaluation test has been carried out by using this system actually. (1) This system has been proved to be essentially effective and some improvements for the future utilization has been pointed out. (2) It should be faster when the CRT displayes are changed, and it should have the explanation function when the plant transients are displayed. (author)

  1. Computerized information system of the Mochovce nuclear power plant

    International Nuclear Information System (INIS)

    Holik, V.

    1986-01-01

    The computer-based information system for the Mochovce nuclear power plant has a hierarchic structure which incorporates SM 1804 microcomputers and SM 1420 minicomputers. With regard to operation it is divided into two levels: the information system at the level of power plant units and the information system t the level of the whole power plant. The information system of a unit provides the collection of information on the technological equipment of each unit for the operative control of the unit and documentation on unit operation. Each unit has its own independent computer information system. The actual nucleus of each unit information system consists of two computer complexes based on SM 1420 twin computers, mutually substitutional. The power plant level information system provides the processing and output of information for personnel in the central control room of the power plant and for other managerial staff. It uses preprocessed information from the unit information systems and direct information from non-unit installations and from dosimetric control rooms of the power plant units. This information system is also based on a computer complex with two SM 1420 computers. (Z.M.)

  2. Individual plant care in cropping systems

    OpenAIRE

    Griepentrog, Hans W.; Nørremark, Michael; Nielsen, Henning; Blackmore, Simon

    2003-01-01

    Individual plant care cropping systems, embodied in precision farming, may lead to new opportunities in agricultural crop management. The objective of the project was to provide high accuracy seed position mapping of a field of sugar beet. An RTK GPS was retrofitted on to a precision seeder to map the seeds as they were planted. The average error between the seed map and the actual plant map was about 32 mm to 59 mm. The results showed that the overall accuracy of the estimated plant position...

  3. Study on fault diagnosis and load feedback control system of combine harvester

    Science.gov (United States)

    Li, Ying; Wang, Kun

    2017-01-01

    In order to timely gain working status parameters of operating parts in combine harvester and improve its operating efficiency, fault diagnosis and load feedback control system is designed. In the system, rotation speed sensors were used to gather these signals of forward speed and rotation speeds of intermediate shaft, conveying trough, tangential and longitudinal flow threshing rotors, grain conveying auger. Using C8051 single chip microcomputer (SCM) as processor for main control unit, faults diagnosis and forward speed control were carried through by rotation speed ratio analysis of each channel rotation speed and intermediate shaft rotation speed by use of multi-sensor fused fuzzy control algorithm, and these processing results would be sent to touch screen and display work status of combine harvester. Field trials manifest that fault monitoring and load feedback control system has good man-machine interaction and the fault diagnosis method based on rotation speed ratios has low false alarm rate, and the system can realize automation control of forward speed for combine harvester.

  4. Ways to integrate document management systems with industrial plant configuration management systems

    International Nuclear Information System (INIS)

    Munoz, M.

    1995-01-01

    Based on experience gained from tasks carried out for Almaraz Nuclear Power Plant, this paper describes computer platforms used both at the power plant and in the main offices of the engineering company. Subsequently, a description is given of the procedure followed for the continuous up-dating of plant documentation, in order to maintain consistency with other information stored in data bases in the Operation Management System, Maintenance System, Modification Management System, etc. The work method used for the unitary updating of all information (document images and attributes corresponding to the different data bases), following refuelling procedures is also described. Lastly, the paper describes the functions and the user interface of the system used in the power plant for document management. (Author)

  5. Suboptimal processor for anomaly detection for system surveillance and diagnosis

    Energy Technology Data Exchange (ETDEWEB)

    Ciftcioglu, Oe.; Hoogenboom, J.E.; Dam, H. van

    1989-06-01

    Anomaly detection for nuclear reactor surveillance and diagnosis is described. The residual noise obtained as a result of autoregressive (AR) modelling is essential to obtain high sensitivity for anomaly detection. By means of the method of hypothesis testing a suboptimal anomaly detection processor is devised for system surveillance and diagnosis. Experiments are carried out to investigate the performance of the processor, which is in particular of interest for on-line and real-time applications.

  6. 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.

  7. Diagnosis System for Diabetic Retinopathy and Glaucoma Screening to Prevent Vision Loss

    Directory of Open Access Journals (Sweden)

    Siva Sundhara Raja DHANUSHKODI

    2014-03-01

    Full Text Available Aim: Diabetic retinopathy (DR and glaucoma are two most common retinal disorders that are major causes of blindness in diabetic patients. DR caused in retinal images due to the damage in retinal blood vessels, which leads to the formation of hemorrhages spread over the entire region of retina. Glaucoma is caused due to hypertension in diabetic patients. Both DR and glaucoma affects the vision loss in diabetic patients. Hence, a computer aided development of diagnosis system for Diabetic retinopathy and Glaucoma screening is proposed in this paper to prevent vision loss. Method: The diagnosis system of DR consists of two stages namely detection and segmentation of fovea and hemorrhages. The diagnosis system of glaucoma screening consists of three stages namely blood vessel segmentation, Extraction of optic disc (OD and optic cup (OC region and determination of rim area between OD and OC. Results: The specificity and accuracy for hemorrhages detection is found to be 98.47% and 98.09% respectively. The accuracy for OD detection is found to be 99.3%. This outperforms state-of-the-art methods. Conclusion: In this paper, the diagnosis system is developed to classify the DR and glaucoma screening in to mild, moderate and severe respectively.

  8. [Public health impact of a remote diagnosis system implemented in regional and district hospitals in Paraguay].

    Science.gov (United States)

    Galván, Pedro; Velázquez, Miguel; Benítez, Gualberto; Ortellado, José; Rivas, Ronald; Barrios, Antonio; Hilario, Enrique

    2017-06-08

    Determine the viability of a remote diagnosis system implemented to provide health care to remote and scattered populations in Paraguay. The study was conducted in all regional and general hospitals in Paraguay, and in the main district hospitals in the country's 18 health regions. Clinical data, tomographic images, sonography, and electrocardiograms (ECGs) of patients who needed a diagnosis by a specialized physician were entered into the system. This information was sent to specialists in diagnostic imaging and in cardiology for remote diagnosis and the report was then forwarded to the hospitals connected to the system. The cost-benefit and impact of the remote diagnosis tool was analyzed from the perspective of the National Health System. Between January 2014 and May 2015, a total of 34 096 remote diagnoses were made in 25 hospitals in the Ministry of Health's telemedicine system. The average unit cost of remote diagnosis was US$2.6 per ECG, tomography, and sonography, while the unit cost of "face-to-face" diagnosis was US$11.8 per ECG, US$68.6 per tomography, and US$21.5 per sonography. As a result of remote diagnosis, unit costs were 4.5 times lower for ECGs; 26.4 times lower for tomography, and 8.3 times lower for sonography. In monetary terms, implementation of the remote diagnosis system during the 16 months of the study led to average savings of US$2 420 037. Paraguay has a remote diagnosis system for electrocardiography, tomography, and sonography, using low-cost information and communications technologies (ICTs) based on free software that is scalable to other types of remote diagnostic studies of interest for public health. Implementation of remote diagnosis helped to strengthen the integrated network of health services and programs, enabling professionals to optimize their time and productivity, while improving quality, increasing access and equity, and reducing costs.

  9. Fault detection and diagnosis for complex multivariable processes using neural networks

    International Nuclear Information System (INIS)

    Weerasinghe, M.

    1998-06-01

    Development of a reliable fault diagnosis method for large-scale industrial plants is laborious and often difficult to achieve due to the complexity of the targeted systems. The main objective of this thesis is to investigate the application of neural networks to the diagnosis of non-catastrophic faults in an industrial nuclear fuel processing plant. The proposed methods were initially developed by application to a simulated chemical process prior to further validation on real industrial data. The diagnosis of faults at a single operating point is first investigated. Statistical data conditioning methods of data scaling and principal component analysis are investigated to facilitate fault classification and reduce the complexity of neural networks. Successful fault diagnosis was achieved with significantly smaller networks than using all process variables as network inputs. Industrial processes often manufacture at various operating points, but demonstrated applications of neural networks for fault diagnosis usually only consider a single (primary) operating point. Developing a standard neural network scheme for fault diagnosis at all operating points would be usually impractical due to the unavailability of suitable training data for less frequently used (secondary) operating points. To overcome this problem, the application of a single neural network for the diagnosis of faults operating at different points is investigated. The data conditioning followed the same techniques as used for the fault diagnosis of a single operating point. The results showed that a single neural network could be successfully used to diagnose faults at operating points other than that it is trained for, and the data conditioning significantly improved the classification. Artificial neural networks have been shown to be an effective tool for process fault diagnosis. However, a main criticism is that details of the procedures taken to reach the fault diagnosis decisions are embedded in

  10. Operator support system for nuclear power plants

    International Nuclear Information System (INIS)

    Mori, Nobuyuki; Tai, Ichiro; Sudo, Osamu; Naito, Norio.

    1987-01-01

    The nuclear power generation in Japan maintains the high capacity factor, and its proportion taken in the total generated electric power exceeded 1/4, thus it has become the indispensable energy source. Recently moreover, the nuclear power plants which are harmonious with operators and easy to operate are demanded. For realizing this, the technical development such as the heightening of operation watching performance, the adoption of automation, and the improvement of various man-machine systems for reducing the burden of operators has been advanced by utilizing electronic techniques. In this paper, the trend of the man-machine systems in nuclear power plants, the positioning of operation support system, the support in the aspects of information, action and knowledge, the example of a new central control board, the operation support system using a computer, an operation support expert system and the problems hereafter are described. As the development of the man-machine system in nuclear power plants, the upgrading from a present new central control board system PODIA through A-PODIA, in which the operational function to deal with various phenomena arising in plants and safety control function are added, to 1-PODIA, in which knowledge engineering technology is adopted, is expected. (Kako, I.)

  11. Imaging corn plants with PhytoPET, a modular PET system for plant biology

    Energy Technology Data Exchange (ETDEWEB)

    Lee, S.; Kross, B.; McKisson, J.; McKisson, J. E.; Weisenberger, A. G.; Xi, W.; Zorn, C.; Bonito, G.; Howell, C. R.; Reid, C. D.; Crowell, A.; Cumberbatch, L. C.; Topp, C.; Smith, M. F.

    2013-11-01

    PhytoPET is a modular positron emission tomography (PET) system designed specifically for plant imaging. The PhytoPET design allows flexible arrangements of PET detectors based on individual standalone detector modules built from single Hamamatsu H8500 position sensitive photomultiplier tubes and pixelated LYSO arrays. We have used the PhytoPET system to perform preliminary corn plant imaging studies at the Duke University Biology Department Phytotron. Initial evaluation of the PhytoPET system to image the biodistribution of the positron emitting tracer {sup 11}C in corn plants is presented. {sup 11}CO{sub 2} is loaded into corn seedlings by a leaf-labeling cuvette and translocation of {sup 11}C-sugars is imaged by a flexible arrangement of PhytoPET modules on each side. The PhytoPET system successfully images {sup 11}C within corn plants and allows for the dynamic measurement of {sup 11}C-sugar translocation from the leaf to the roots.

  12. A REVIEW ON DIAGNOSIS OF NUTRIENT DEFICIENCY SYMPTOMS IN PLANT LEAF IMAGE USING DIGITAL IMAGE PROCESSING

    Directory of Open Access Journals (Sweden)

    S Jeyalakshmi

    2017-05-01

    Full Text Available Plants, for their growth and survival, need 13 mineral nutrients. Toxicity or deficiency in any one or more of these nutrients affects the growth of plant and may even cause the destruction of the plant. Hence, a constant monitoring system for tracking the nutrient status in plants becomes essential for increase in production as well as quality of yield. A diagnostic system using digital image processing would diagnose the deficiency symptoms much earlier than human eyes could recognize. This will enable the farmers to adopt appropriate remedial action in time. This paper focuses on the review of work using image processing techniques for diagnosing nutrient deficiency in plants.

  13. Hybrid intelligent monironing systems for thermal power plant trips

    Science.gov (United States)

    Barsoum, Nader; Ismail, Firas Basim

    2012-11-01

    Steam boiler is one of the main equipment in thermal power plants. If the steam boiler trips it may lead to entire shutdown of the plant, which is economically burdensome. Early boiler trips monitoring is crucial to maintain normal and safe operational conditions. In the present work two artificial intelligent monitoring systems specialized in boiler trips have been proposed and coded within the MATLAB environment. The training and validation of the two systems has been performed using real operational data captured from the plant control system of selected power plant. An integrated plant data preparation framework for seven boiler trips with related operational variables has been proposed for IMSs data analysis. The first IMS represents the use of pure Artificial Neural Network system for boiler trip detection. All seven boiler trips under consideration have been detected by IMSs before or at the same time of the plant control system. The second IMS represents the use of Genetic Algorithms and Artificial Neural Networks as a hybrid intelligent system. A slightly lower root mean square error was observed in the second system which reveals that the hybrid intelligent system performed better than the pure neural network system. Also, the optimal selection of the most influencing variables performed successfully by the hybrid intelligent system.

  14. Radiological diagnosis systems - problems and solutions

    International Nuclear Information System (INIS)

    Koeppe, P.

    1983-01-01

    An essential part of the work in a radiological diagnosis department is to produce the (written) physicians' reports. The majority is generally without any findings or ''normal pathologic'', only a minor part needs a special treatment. With respect to the quantity of this work, automation of the routine report writing was early attempted ley means of technical aids. Text processing systems and computers were used. The transition between these techniques is gradual. The article is limited to the use of computers in automation of report writing. (orig.) [de

  15. Preparation of plant and system design description documents

    International Nuclear Information System (INIS)

    1989-01-01

    This standard prescribes the purpose, scope, organization, and content of plant design requirements (PDR) documents and system design descriptions (SDDs), to provide a unified approach to their preparation and use by a project as the principal means to establish the plant design requirements and to establish, describe, and control the individual system designs from conception and throughout the lifetime of the plant. The Electric Power Research Institute's Advanced Light Water Reactor (LWR) Requirements Document should be considered for LWR plants

  16. Model-based fault diagnosis in PEM fuel cell systems

    Energy Technology Data Exchange (ETDEWEB)

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

    2009-07-01

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

  17. A User-Centered Cooperative Information System for Medical Imaging Diagnosis.

    Science.gov (United States)

    Gomez, Enrique J.; Quiles, Jose A.; Sanz, Marcos F.; del Pozo, Francisco

    1998-01-01

    Presents a cooperative information system for remote medical imaging diagnosis. General computer-supported cooperative work (CSCW) problems addressed are definition of a procedure for the design of user-centered cooperative systems (conceptual level); and improvement of user feedback and optimization of the communication bandwidth in highly…

  18. Problems of steam turbine diagnostics and the 'Simens' diagnosis system

    International Nuclear Information System (INIS)

    Tserner, V.; Andrea, K.

    1993-01-01

    Diagnostics system, allowing one to detect changes in the state on single turbine elements at an early stage is described. Besides this system allows one to utilize the turbine plant optimally and efficiency from the viewpoint of the equipment durability. Specially oriented monitoring of the turbine plant and equipment element state saves resources necessary to keep up the working order of the equipment

  19. An integrated reliability management system for nuclear power plants

    International Nuclear Information System (INIS)

    Kimura, T.; Shimokawa, H.; Matsushima, H.

    1998-01-01

    The responsibility in the nuclear field of the Government, utilities and manufactures has increased in the past years due to the need of stable operation and great reliability of nuclear power plants. The need to improve the reliability is not only for the new plants but also for those now running. So, several measures have been taken to improve reliability. In particular, the plant manufactures have developed a reliability management system for each phase (planning, construction, maintenance and operation) and these have been integrated as a unified system. This integrated reliability management system for nuclear power plants contains information about plant performance, failures and incidents which have occurred in the plants. (author)

  20. Use of bactec 460 TB system in the diagnosis of tuberculosis

    Directory of Open Access Journals (Sweden)

    Rodrigues C

    2007-01-01

    Full Text Available Purpose : To evaluate, the efficacy of BACTEC 460 TB system for the diagnosis of tuberculosis in a tertiary care hospital in Mumbai, India. Methods : We compared 12,726 clinical specimens using BACTEC 460 TB system and conventional method for detection of Mycobacterium tuberculosis over a period of six years. Result: The overall recovery rate was 39% by BACTEC technique and 29% using Lowenstein-Jensen (LJ medium. An average detection time for B actec0 460 TB system was found to be 13.3 days and 15.3 days as against 31.2 days and 35.3 days by LJ method for respiratory and nonrespiratory specimens respectively. The average reporting time for drug susceptibility results ranged from 6-10 days for the BACTEC 460 TB system. Conclusions: The BACTEC system is a good system for level II laboratories, especially in the diagnosis of extrapulmonary and smear negative tuberculosis.

  1. 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

  2. Diffuse-Illumination Systems for Growing Plants

    Science.gov (United States)

    May, George; Ryan, Robert

    2010-01-01

    Agriculture in both terrestrial and space-controlled environments relies heavily on artificial illumination for efficient photosynthesis. Plant-growth illumination systems require high photon flux in the spectral range corresponding with plant photosynthetic active radiation (PAR) (400 700 nm), high spatial uniformity to promote uniform growth, and high energy efficiency to minimize electricity usage. The proposed plant-growth system takes advantage of the highly diffuse reflective surfaces on the interior of a sphere, hemisphere, or other nearly enclosed structure that is coated with highly reflective materials. This type of surface and structure uniformly mixes discrete light sources to produce highly uniform illumination. Multiple reflections from within the domelike structures are exploited to obtain diffuse illumination, which promotes the efficient reuse of photons that have not yet been absorbed by plants. The highly reflective surfaces encourage only the plant tissue (placed inside the sphere or enclosure) to absorb the light. Discrete light sources, such as light emitting diodes (LEDs), are typically used because of their high efficiency, wavelength selection, and electronically dimmable properties. The light sources are arranged to minimize shadowing and to improve uniformity. Different wavelengths of LEDs (typically blue, green, and red) are used for photosynthesis. Wavelengths outside the PAR range can be added for plant diagnostics or for growth regulation

  3. Plant operation state monitoring system

    International Nuclear Information System (INIS)

    Sakai, Masanori; Babuchi, Katsumi; Arato, Toshiaki

    1994-01-01

    The system of the present invention accurately monitors a plant operation state of a plant, such as a nuclear power plant and a thermal power plant by using high temperature water, based on water quality informations. That is, water quality informations for the objective portion by using an electrochemical water quality sensor disposed in the objective portion to be monitored in the plant are continuously extracted for a predetermined period of time. Water quality is evaluated based on the extracted information. Obtained results for water quality evaluation and predetermined reference values of the plant operation handling are compared. Necessary part among the results of the measurement is displayed or recorded. The predetermined period of time described above is a period that the water quality information reaches at least a predetermined value or a period that the predetermined value is estimated by the water quality information, and it is defined as a period capable of measuring the information for three months continuously. The measurement is preferably conducted continuously in a period up to each periodical inspection on about every one year. (I.S.)

  4. Computer-aided diagnosis workstation and network system for chest diagnosis based on multislice CT images

    Science.gov (United States)

    Satoh, Hitoshi; Niki, Noboru; Eguchi, Kenji; Moriyama, Noriyuki; Ohmatsu, Hironobu; Masuda, Hideo; Machida, Suguru

    2008-03-01

    Mass screening based on multi-helical CT images requires a considerable number of images to be read. It is this time-consuming step that makes the use of helical CT for mass screening impractical at present. To overcome this problem, we have provided diagnostic assistance methods to medical screening specialists by developing a lung cancer screening algorithm that automatically detects suspected lung cancers in helical CT images, a coronary artery calcification screening algorithm that automatically detects suspected coronary artery calcification and a vertebra body analysis algorithm for quantitative evaluation of osteoporosis likelihood by using helical CT scanner for the lung cancer mass screening. The function to observe suspicious shadow in detail are provided in computer-aided diagnosis workstation with these screening algorithms. We also have developed the telemedicine network by using Web medical image conference system with the security improvement of images transmission, Biometric fingerprint authentication system and Biometric face authentication system. Biometric face authentication used on site of telemedicine makes "Encryption of file" and Success in login" effective. As a result, patients' private information is protected. Based on these diagnostic assistance methods, we have developed a new computer-aided workstation and a new telemedicine network that can display suspected lesions three-dimensionally in a short time. The results of this study indicate that our radiological information system without film by using computer-aided diagnosis workstation and our telemedicine network system can increase diagnostic speed, diagnostic accuracy and security improvement of medical information.

  5. Accident Diagnosis and Prognosis Aide (ADPA)

    International Nuclear Information System (INIS)

    Gunter, A.D.; Touchton, R.A.

    1987-01-01

    This presentation provides a demonstration of a prototypical expert system developed by Technology Applications, Inc. (TAI) under a contract with the Department of Energy as a part of their Small Business Innovation Research Program. The Accident Diagnosis and Prognosis Aide (ADPA) Demonstration Prototype is a working scale model of a real-time expert system which: Diagnoses an accident situation (as well as a number of underlying failures, events, and conditions deduced along the way). Calculates the change in the likelihood of core damage as a function of the events and failures diagnosed. Dynamically generates a recovery procedure tailored to the specific plant state at hand

  6. Autonomous Control of Nuclear Power Plants

    Energy Technology Data Exchange (ETDEWEB)

    Basher, H.

    2003-10-20

    A nuclear reactor is a complex system that requires highly sophisticated controllers to ensure that desired performance and safety can be achieved and maintained during its operations. Higher-demanding operational requirements such as reliability, lower environmental impacts, and improved performance under adverse conditions in nuclear power plants, coupled with the complexity and uncertainty of the models, necessitate the use of an increased level of autonomy in the control methods. In the opinion of many researchers, the tasks involved during nuclear reactor design and operation (e.g., design optimization, transient diagnosis, and core reload optimization) involve important human cognition and decisions that may be more easily achieved with intelligent methods such as expert systems, fuzzy logic, neural networks, and genetic algorithms. Many experts in the field of control systems share the idea that a higher degree of autonomy in control of complex systems such as nuclear plants is more easily achievable through the integration of conventional control systems and the intelligent components. Researchers have investigated the feasibility of the integration of fuzzy logic, neural networks, genetic algorithms, and expert systems with the conventional control methods to achieve higher degrees of autonomy in different aspects of reactor operations such as reactor startup, shutdown in emergency situations, fault detection and diagnosis, nuclear reactor alarm processing and diagnosis, and reactor load-following operations, to name a few. With the advancement of new technologies and computing power, it is feasible to automate most of the nuclear reactor control and operation, which will result in increased safety and economical benefits. This study surveys current status, practices, and recent advances made towards developing autonomous control systems for nuclear reactors.

  7. Autonomous Control of Nuclear Power Plants

    International Nuclear Information System (INIS)

    Basher, H.

    2003-01-01

    A nuclear reactor is a complex system that requires highly sophisticated controllers to ensure that desired performance and safety can be achieved and maintained during its operations. Higher-demanding operational requirements such as reliability, lower environmental impacts, and improved performance under adverse conditions in nuclear power plants, coupled with the complexity and uncertainty of the models, necessitate the use of an increased level of autonomy in the control methods. In the opinion of many researchers, the tasks involved during nuclear reactor design and operation (e.g., design optimization, transient diagnosis, and core reload optimization) involve important human cognition and decisions that may be more easily achieved with intelligent methods such as expert systems, fuzzy logic, neural networks, and genetic algorithms. Many experts in the field of control systems share the idea that a higher degree of autonomy in control of complex systems such as nuclear plants is more easily achievable through the integration of conventional control systems and the intelligent components. Researchers have investigated the feasibility of the integration of fuzzy logic, neural networks, genetic algorithms, and expert systems with the conventional control methods to achieve higher degrees of autonomy in different aspects of reactor operations such as reactor startup, shutdown in emergency situations, fault detection and diagnosis, nuclear reactor alarm processing and diagnosis, and reactor load-following operations, to name a few. With the advancement of new technologies and computing power, it is feasible to automate most of the nuclear reactor control and operation, which will result in increased safety and economical benefits. This study surveys current status, practices, and recent advances made towards developing autonomous control systems for nuclear reactors

  8. Nutrient supply of plants in aquaponic systems

    OpenAIRE

    Bittsánszky, András; Uzinger, Nikolett; Gyulai, Gábor; Mathis, Alex; Junge, Ranka; Villarroel, Morris; Kotzen, Benzion; Komives, Tamas

    2016-01-01

    In this preliminary article we present data on plant nutrient concentrations in aquaponic systems, and compare them to nutrient concentrations in “standard” hydroponic solutions. Our data shows that the nutrient concentrations supplied by the fish in aquaponic system are significantly lower for most nutrients, compared to hydroponic systems. Nevertheless, plants do thrive in solutions that have lower nutrient levels than “standard” hydroponic solutions. This is especially true for green leafy...

  9. Analysis of operators' diagnosis tasks based on cognitive process

    International Nuclear Information System (INIS)

    Zhou Yong; Zhang Li

    2012-01-01

    Diagnosis tasks in nuclear power plants characterized as high-dynamic uncertainties are complex reasoning tasks. Diagnosis errors are the main causes for the error of commission. Firstly, based on mental model theory and perception/action cycle theory, a cognitive model for analyzing operators' diagnosis tasks is proposed. Then, the model is used to investigate a trip event which occurred at crystal river nuclear power plant. The application demonstrates typical cognitive bias and mistakes which operators may make when performing diagnosis tasks. They mainly include the strong confirmation tendency, difficulty to produce complete hypothesis sets, group mindset, non-systematic errors in hypothesis testing, and etc. (authors)

  10. Evaluation of computer-aided detection and diagnosis systems.

    Science.gov (United States)

    Petrick, Nicholas; Sahiner, Berkman; Armato, Samuel G; Bert, Alberto; Correale, Loredana; Delsanto, Silvia; Freedman, Matthew T; Fryd, David; Gur, David; Hadjiiski, Lubomir; Huo, Zhimin; Jiang, Yulei; Morra, Lia; Paquerault, Sophie; Raykar, Vikas; Samuelson, Frank; Summers, Ronald M; Tourassi, Georgia; Yoshida, Hiroyuki; Zheng, Bin; Zhou, Chuan; Chan, Heang-Ping

    2013-08-01

    Computer-aided detection and diagnosis (CAD) systems are increasingly being used as an aid by clinicians for detection and interpretation of diseases. Computer-aided detection systems mark regions of an image that may reveal specific abnormalities and are used to alert clinicians to these regions during image interpretation. Computer-aided diagnosis systems provide an assessment of a disease using image-based information alone or in combination with other relevant diagnostic data and are used by clinicians as a decision support in developing their diagnoses. While CAD systems are commercially available, standardized approaches for evaluating and reporting their performance have not yet been fully formalized in the literature or in a standardization effort. This deficiency has led to difficulty in the comparison of CAD devices and in understanding how the reported performance might translate into clinical practice. To address these important issues, the American Association of Physicists in Medicine (AAPM) formed the Computer Aided Detection in Diagnostic Imaging Subcommittee (CADSC), in part, to develop recommendations on approaches for assessing CAD system performance. The purpose of this paper is to convey the opinions of the AAPM CADSC members and to stimulate the development of consensus approaches and "best practices" for evaluating CAD systems. Both the assessment of a standalone CAD system and the evaluation of the impact of CAD on end-users are discussed. It is hoped that awareness of these important evaluation elements and the CADSC recommendations will lead to further development of structured guidelines for CAD performance assessment. Proper assessment of CAD system performance is expected to increase the understanding of a CAD system's effectiveness and limitations, which is expected to stimulate further research and development efforts on CAD technologies, reduce problems due to improper use, and eventually improve the utility and efficacy of CAD in

  11. Influence of in-plant air pollution control measures on power plant and system operation

    International Nuclear Information System (INIS)

    Kurten, H.

    1990-01-01

    The burning of fossil fuels causes the emission of air pollutants which have harmful environmental impact. Consequently many nations have in the last few years established regulations for air pollution control and have initiated the development and deployment of air pollution control systems in power plants. The paper describes the methods used for reducing particulate, SO 2 and NO x emissions, their application as backfit systems and in new plants, the power plant capacity equipped with such systems in the Federal Republic of Germany and abroad and the additional investment and operating costs incurred. It is to be anticipated that advanced power plant designs will produce lower pollutant emissions and less waste at enhanced efficiency levels. A comparison with power generation in nuclear power plants completes the first part of the paper. This paper covers the impact of the above-mentioned air pollution control measures on unit commitment in daily operation

  12. Development of a system for monitoring and diagnosis of steam generator tubes using artificial intelligence techniques on Eddy Current Test signals

    International Nuclear Information System (INIS)

    Mesquita, Roberto Navarro de; Ting, Daniel Kao Sun; Lopez, Luis A. Negro M.; Upadhyaya, Belle R.

    2002-01-01

    New classification and feature extraction methods for steam generator tube defects are being developed by IPEN/CNEN-SP in cooperation with UTK to improve a monitoring and diagnosis system for classification and characterization of steam generator tube defects using Eddy Current Testing (ECT) signals. The first methodology being developed uses a set of feature extraction methods applied to different tube defect type ECT signals and each obtained feature vector is projected into a bi-dimensional map obtained by a Self-Organizing Map neural network. This methodology allows an optimal feature extraction method selection for the defect type classification. Other approach is being developed using tubes with different manufactured defect types which are tested using MIZ-17ET equipment with 4 sets of probes (two different diameter). A fuzzy inference system will be used to build a knowledge base for these defects. These methodology and algorithms will be integrated into an automated diagnosis system being developed with UTK, which is designed to read both on-line acquired data, as well as stored data files. These commercial software tools are the ones usually utilized in nuclear power plants. (author)

  13. Development of a system for monitoring and diagnosis of steam generator tubes using artificial intelligence techniques on Eddy Current Test signals

    Energy Technology Data Exchange (ETDEWEB)

    Mesquita, Roberto Navarro de [Instituto de Pesquisas Energeticas e Nucleares (IPEN), Sao Paulo, SP (Brazil). Centro de Monitoracao e Diagnostico]|[Sao Paulo Univ., SP (Brazil); Ting, Daniel Kao Sun [Instituto de Pesquisas Energeticas e Nucleares (IPEN), Sao Paulo, SP (Brazil). Centro de Monitoracao e Diagnostico; Cabral, Eduardo Lobo C. [Sao Paulo Univ., SP (Brazil); Lopez, Luis A. Negro M. [Faculdade de Engenharia Industrial, Sao Bernardo do Campo, SP (Brazil); Upadhyaya, Belle R. [Tennessee Univ., Knoxville, TN (United States)

    2002-07-01

    New classification and feature extraction methods for steam generator tube defects are being developed by IPEN/CNEN-SP in cooperation with UTK to improve a monitoring and diagnosis system for classification and characterization of steam generator tube defects using Eddy Current Testing (ECT) signals. The first methodology being developed uses a set of feature extraction methods applied to different tube defect type ECT signals and each obtained feature vector is projected into a bi-dimensional map obtained by a Self-Organizing Map neural network. This methodology allows an optimal feature extraction method selection for the defect type classification. Other approach is being developed using tubes with different manufactured defect types which are tested using MIZ-17ET equipment with 4 sets of probes (two different diameter). A fuzzy inference system will be used to build a knowledge base for these defects. These methodology and algorithms will be integrated into an automated diagnosis system being developed with UTK, which is designed to read both on-line acquired data, as well as stored data files. These commercial software tools are the ones usually utilized in nuclear power plants. (author)

  14. 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

  15. Fuel management of mixed reactor type power plant systems

    International Nuclear Information System (INIS)

    Csom, Gyula

    1988-01-01

    In equilibrium symbiotic power plant system containing both thermal reactors and fast breeders, excess plutonium produced by the fast breeders is used to enrich the fuel of the thermal reactors. In plutonium deficient symbiotic power plant system plutonium is supplied both by thermal plants and fast breeders. Mathematical models were constructed and different equations solved to characterize the fuel utilization of both systems if they contain only a single thermal type and a single fast type reactor. The more plutonium is produced in the system, the higher output ratio of thermal to fast reactors is achieved in equilibrium symbiotic power plant system. Mathematical equations were derived to calculate the doubling time and the breeding gain of the equilibrium symbiotic system. (V.N.) 2 figs.; 2 tabs

  16. Engineering Plant Immunity via CRISPR/Cas13a System

    KAUST Repository

    Aljedaani, Fatimah R.

    2018-05-01

    Viral diseases constitute a major threat to the agricultural production and food security throughout the world. Plants cope with the invading viruses by triggering immune responses and small RNA interference (RNAi) systems. In prokaryotes, CRISPR/Cas systems function as an adaptive immune system to provide bacteria with resistance against invading phages and conjugative plasmids. Interestingly, CRISPR/Cas9 system was shown to interfere with eukaryotic DNA viruses and confer resistance against plant DNA viruses. The majority of the plant viruses have RNA genomes. The aim of this study is to test the ability of the newly discovered CRISPR/Cas13a immune system, that targets and cleaves single stranded RNA (ssRNA) in prokaryotes, to provide resistance against RNA viruses in plants. Here, I employ the CRISPR/Cas13a system for molecular interference against Turnip Mosaic Virus (TuMV), a plant RNA virus. The results of this study established the CRISPR/Cas13a as a molecular interference machinery against RNA viruses in plants. Specifically, my data show that the CRISPR/Cas13a machinery is able to interfere with and degrade the TuMV (TuMV-GFP) RNA genome. In conclusion, these data indicate that the CRISPR/Cas13 systems can be employed for engineering interference and durable resistance against RNA viruses in diverse plant species.

  17. REACTOR: an expert system for diagnosis and treatment of nuclear reactor accidents

    International Nuclear Information System (INIS)

    Nelson, W.R.

    1982-01-01

    REACTOR is an expert system under development at EG and G Idaho, Inc., that will assist operators in the diagnosis and treatment of nuclear reactor accidents. This paper covers the background of the nuclear industry and why expert system technology may prove valuable in the reactor control room. Some of the basic features of the REACTOR system are discussed, and future plans for validation and evaluation of REACTOR are presented. The concept of using both event-oriented and function-oriented strategies for accident diagnosis is discussed. The response tree concept for representing expert knowledge is also introduced

  18. System Definition and Analysis: Power Plant Design and Layout

    International Nuclear Information System (INIS)

    1996-01-01

    This is the Topical report for Task 6.0, Phase 2 of the Advanced Turbine Systems (ATS) Program. The report describes work by Westinghouse and the subcontractor, Gilbert/Commonwealth, in the fulfillment of completing Task 6.0. A conceptual design for critical and noncritical components of the gas fired combustion turbine system was completed. The conceptual design included specifications for the flange to flange gas turbine, power plant components, and balance of plant equipment. The ATS engine used in the conceptual design is an advanced 300 MW class combustion turbine incorporating many design features and technologies required to achieve ATS Program goals. Design features of power plant equipment and balance of plant equipment are described. Performance parameters for these components are explained. A site arrangement and electrical single line diagrams were drafted for the conceptual plant. ATS advanced features include design refinements in the compressor, inlet casing and scroll, combustion system, airfoil cooling, secondary flow systems, rotor and exhaust diffuser. These improved features, integrated with prudent selection of power plant and balance of plant equipment, have provided the conceptual design of a system that meets or exceeds ATS program emissions, performance, reliability-availability-maintainability, and cost goals

  19. Role of fluorographic examinations in diagnosis of respiratory system diseases

    International Nuclear Information System (INIS)

    Vil'derman, A.M.; Tsurkan, E.P.; Moskovchuk, A.F.

    1984-01-01

    Materials are considered on the role of fluorography in diagnosis of posttuberculous changes and chromic respiratory system diseases during total epidemiologic examination of 7791 adults from urban and rural population. A scheme is developed that characterize diagnosed pathology of respiratory organs with references to medical establishments rendering medical supervision and forms of supervision. It is shown that fluorograhic examination of the population provide an early diagnosis of both tuberculosis, neoplastic diseases and nonspecific pulmonary diseases that have no visible clinical symptomatology

  20. Investigation of human system interface design in nuclear power plant

    International Nuclear Information System (INIS)

    Feng Yan; Zhang Yunbo; Wang Zhongqiu

    2012-01-01

    The paper introduces the importance of HFE in designing nuclear power plant, and introduces briefly the content and scope of HFE, discusses human system interface design of new built nuclear power plants. This paper also describes human system interface design of foreign nuclear power plant, and describes in detail human system interface design of domestic nuclear power plant. (authors)