Induction Motor Faults Classification using Parks-Hilbert Transforms Approach and ANN Networks

Abstract

Due to the cardinal features like robustness, efficient load handling, reliability etc the Induction Motor is foremost used for number of applications. While working environmental conditions, mechanical stresses etc cause fault like bearing fault, inter-turn short circuit fault, rotor bar crack. These faults should be eliminated and categorized as early as possible to avoid harm. There are list of techniques are accessible for the fault catalogue of I.M. The Artificial Neural Network is the best solution over other existing techniques. The motor line currents recorded under varied faults conditions were analyzed using ANN.