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Neuro-Fuzzy Methods for Fault Diagnosis of Nonlinear Systems

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Author(s): L. Mehennaoui | N. Debbache | M.L. Benloucif

Journal: Journal of Applied Sciences
ISSN 1812-5654

Volume: 6;
Issue: 9;
Start page: 2020;
Date: 2006;
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Keywords: Fuzzy identification | neural identification | fault diagnosis | neuro-fuzzy scheme

ABSTRACT
The study presents a Fault Detection and Isolation (FDI) scheme with a particular emphasis placed on sensor fault diagnosis in nonlinear dynamic systems. The non-analytical FDI scheme is based on a two-step procedure. Two methods are proposed for the first step, called residual generation, one use fuzzy sets and the second neuronal network. A fuzzy neural network performs the second step, called residual evaluation. Some simulation results are given for efficiency assessment of this fault diagnosis approach.
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