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Motivated by the superior performances of neural networks and neuro-fuzzy approaches to fault detection of a single phase induction motor, this paper studies the applicability these two approaches for detection of stator inter-turn faults in a three phase induction motor. Firstly, the paper develops an adaptive neural fuzzy inference system (ANFIS) detection strategy and then compares its performance with that of using a multi layer perceptron neural network (MLP NN) applied to stator inter-turn fault detection of a three phase induction motor. The fault location process is based on the monitoring the three phase shifts between the line current and the phase voltage of the induction machine.

Stator inter-turn fault detection of an induction motor using neuro-fuzzy techniques