Induction Motor Bearing Fault Detection under Transient Conditions

Abstract

This paper introduces a method for diagnosis of bearing fault of induction motor under transient conditions. The q-axis component of the stator current signal is decomposed by using the discrete wavelet transform (DWT). The fault detection method is developed by using the artificial neural network (ANN) to identify the motor state. A dynamic model of the squirrel-cage induction motor taking account the bearing faults is developed using simulink/matlab. Simulation results show that the better performance of the proposed method.