Neuro-Fuzzy Sensor Fault Diagnosis of an Induction Motor

Authors

M. L. Benloucif, Automatic Control Laboratory, LAS, Department of Electrical Engineering, Faculty of Engineering, University of Skikda, Algeria

Abstract

In this paper, a neuro-fuzzy fault diagnosis scheme is presented and its ability to detect and isolate sensor faults in an induction motor is assessed. This fault detection and isolation (FDI) approach relies on a combination of neural modelling and fuzzy logic techniques which can deal effectively with nonlinear dynamics and uncertainties. It is based on a two step neural network procedure: a first neural network is used for residual generation and a second fuzzy neural network performs residual evaluation. Simulation results are given to demonstrate the efficiency of this FDI approach.

Recommended Citation

Benloucif, M. L. (2011) "Neuro-Fuzzy Sensor Fault Diagnosis of an Induction Motor," The Journal of Engineering Research: Vol. 8: Iss. 1, Article 4.
DOI: https://doi.org/10.24200/tjer.vol8iss1pp53-60

First Page

53

Last Page

60

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This work is licensed under a Creative Commons Attribution 4.0 International License.