Fuzzy Pattern Recognition Based Fault Diagnosis

Abstract ±In order to avoid catastrophic situations when the dynamics of a physical system (entity in Multi Agent System architectu re) 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 actua l 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 propo sed diagnosis philosophy. The obtained results seem to be encouraging and very promising for application to fault diagnosis of a real and complex plant process. Copyright © 2011 Praise Worthy Prize S.r.l. - All rights reserved.

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