Neuro-fuzzy sensor fault diagnosis of an induction motor

Abstract EN

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.