Pattern recognition for diagnosis of technological systems: a review

Mourot, Gilles; Bousghiri, S.; Ragot, José

doi:10.1109/icsmc.1993.390863

Cited by 10 publications

(4 citation statements)

References 38 publications

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“…Among the areas where adaptive pattern recognition approaches are well justified to be applied, are development of expert systems, fault identification and diagnosis of complex systems [4]. So, for evaluation purposes, the approach proposed here has been applied to identification of faults in a power distribution network [9].…”

Section: Pattern Recognition and Complex Systemsmentioning

confidence: 99%

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Identification of distinctive features for classification in complex systems

Shahrestani

2009

2009 International Conference on Innovations in Information Technology (IIT)

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This paper deals with the problem of classifying patterns encountered in complex systems. It describes an approach to pattern recognition that results in a complete and reliable classification technique. It is noted that the majority of existing pattern recognition methods initiate their classification acts on identification of similarities between the members of various classes. On contrast, the work reported here, starts with the recognition of distinctive features of encountered patterns. It is proposed that the patterns to be clustered in a particular fashion to facilitate the exploration of their distinctive features. The process does not depend on utilization of heuristic rules. The membership of different classes will then be based on different values for some or all of such features. This paper will also establish that by utilizing the distinctive features complete classification of all patterns, even for complex systems, can be achieved.

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Section: Pattern Recognition and Complex Systemsmentioning

confidence: 99%

“…Expert systems have enjoyed widespread acceptance in various applications been developed for resolving various kinds of problems, including those encountered in complex systems [3], [4], [16] and [17]. A shortcoming for some of these systems, relates to their dependency on heuristic rules.…”

Section: Introductionmentioning

confidence: 99%

Identification of distinctive features for classification in complex systems

Shahrestani

2009

2009 International Conference on Innovations in Information Technology (IIT)

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“…The steam enters the HPPH at the top of the cylinder (1) where it is cooled down. In the condenser area the steam condensates to water (2), which is further cooled down (3) and which leaves the HPPH at (9). Under normal operating conditions two of these HPPH are operated in the power plant in series .…”

Section: Description Of the Modelmentioning

confidence: 99%

Fuzzy residual evaluation concept (FREC)

Kiupel

Köppen-Seliger

Kellinghaus

et al.

1995 IEEE International Conference on Systems, Man and Cybernetics. Intelligent Systems for the 21st Century

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In this paper we suggest a novel philosophy of process supervision based on knowledge based redundancy. The key idea is to replace the conventional residual evaluator of the fault diagnosis system based on crisp logic, by both a decision maker with fuzzy logic for residual evaluation and the human operator to make the final decisions using his natural intelligence, experience and common sense. The purpose of the employment of fuzzy logic for residual evaluation is to release only weighted alarms instead of yes-no decisions, such that (by definition) no false alarms can be produced; besides this the manmachine interaction becomes much easier. In contrast to the conventional expert system approach, the proposed concept leaves the final yes-no decisions to the natural intelligence, capability and responsibility of the human operator. In addition this method can be seen as an extension to the quantitative model-based techniques.Nevertheless the huge amount of information, which is normally given by most of the fault diagnosis schemes, should be both, filtered and reduced in the sense of the detectability and reliability of an FDI scheme. As an application example this concept has been applied to a part of a power plant in order to prove this theory.

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“…adaptive threshold [13], statistical evaluation of the residual 1131, pattern recognition [12], fuzzy generation of an adaptive threshold [15] or the use of a neural network [ll].…”

Section: Introductionmentioning

confidence: 99%

A fault diagnosis concept for a high-pressure-preheater line

Köppen-Seliger

Kiupel

Kellinghaus

et al.

Proceedings of 1995 34th IEEE Conference on Decision and Control

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This contribution describes a combined analytical/fuzzy model-based fault diagnosis concept which has been applied to the high-pressure-preheater line of a power plant.The key idea is to divide the whole system under supervision into several subsystems and to employ all available analytical knowledge to generate residuals for each subsystem seperately. Thereby the necessary observers for fault detection are of a handable size. For fault isolation, the residual evaluation is done by applying qualitative knowledge about the fault effects on the residuals and about the interaction of the different subsystems. Here a rule base is evaluated using fuzzy logic. With this method a complex system can be supervised without the need for a complex analytical model of the whole system. Furthermore, the presentation of the fault isolation results leaves the final decision about a fault alarm to the human operator. Results from a power plant prove the successful application of the proposed supervision concept.

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Pattern recognition for diagnosis of technological systems: a review

Cited by 10 publications

References 38 publications

Identification of distinctive features for classification in complex systems

Identification of distinctive features for classification in complex systems

Fuzzy residual evaluation concept (FREC)

A fault diagnosis concept for a high-pressure-preheater line

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