Fuzzy Pattern Recognition Based Fault Diagnosis
| Autor: | Bensaadi, Rafik, Mouss, Leïla-Hayet, Mouss, Mohamed Djamel, Benbouzid, Mohamed |
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| Přispěvatelé: | Laboratoire d'Automatique et de Productique de Batna (LAP), Université Hadj Lakhdar Batna 1, Laboratoire brestois de mécanique et des systèmes (LBMS), École Nationale d'Ingénieurs de Brest (ENIB)-Université de Brest (UBO)-École Nationale Supérieure de Techniques Avancées Bretagne (ENSTA Bretagne), Benbouzid, Mohamed |
| Jazyk: | angličtina |
| Rok vydání: | 2011 |
| Předmět: | |
| Zdroj: | International Review on Modelling and Simulations (I.RE.MO.S.) International Review on Modelling and Simulations (I.RE.MO.S.), 2011, 4 (6), pp.3361-3370 |
| Popis: | International audience; In order to avoid catastrophic situations when the dynamics of a physical system (entity in Multi Agent System architecture) are evolving toward an undesirable operating mode, particular and quick safety actions have to be programmed in the control design. Classic control (PID and even state model based methods) becomes powerless for complex plants (nonlinear, MIMO and ill-defined systems). A more efficient diagnosis requires an artificial intelligence approach. We propose in this paper the design of a Fuzzy Pattern Recognition System (FPRS) that solves, in real time, the main following problems: 1) Identification of an actual state; 2) Identification of an eventual evolution towards a failure state; 3) Diagnosis and decision-making. Simulations have been carried for a fictive complex process plant with the objective to evaluate the consistency and the performance of the proposed diagnosis philosophy. The obtained results seem to be encouraging and very promising for application to fault diagnosis of a real and complex plant process. |
| Databáze: | OpenAIRE |
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