Induction Motor Bearing Fault Detection under Transient Conditions
Pages : 1287-1292
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.
Keywords: Induction motor, bearing fault, MCSA, DWT, ANN
Article published in International Journal of Current Engineering and Technology, Vol.3,No.4(Oct- 2013)