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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.

 

Keywords

Fuzzy logic Induction motor Neural networks Sensor fault detection and isolation

Article Details

How to Cite
Benloucif, M. L. (2011). Neuro-Fuzzy Sensor Fault Diagnosis of an Induction Motor. The Journal of Engineering Research [TJER], 8(1), 53–60. https://doi.org/10.24200/tjer.vol8iss1pp53-60
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