Detection, diagnoses and discrimination of stator turn to turn fault and unbalanced supply voltage fault for three phase induction motors

Abstract

A method for fault detection and diagnosis of stator inter-turn short circuits and unbalanced supply voltages for three phase induction machines is presented. The method is based on the analysis of the ratio of third harmonic to fundamental FFT magnitude component of the three-phase stator line current and supply voltage to detect different insulation failure percentages at different load conditions using neural network, tested on motors with different ratings. The presented method yields a high degree of accuracy in fault detection and diagnosis between the effects of inter-turn short circuits and those due to unbalanced supply voltages, also, a more significant and reliable indicator for detection and diagnosis of stator inter-turn short-circuits faults under unbalanced supply voltage conditions using artificial neural network.