Separating induction Motor Current Signature for stator winding faults from that due to supply voltage unbalances

Abstract

Statistical spreads of the surveys suggest that stator winding faults are one of the most prevailing faults in induction motor. Most of the methods for stator winding inter-turn fault diagnosis are based on Motor Current Signature Analysis (MCSA) combined with signal-and-data processing tools. Fault diagnosis using MCSA becomes more challenging when stator current signatures due to winding short circuit fault and supply voltage unbalance appear identical. The present paper proposes a method through analysis of Park's Vector Modulus (PVM) to discriminate stator winding inter-turn fault cases, from supply voltage unbalance conditions where both cases exhibit apparently similar kind of current signatures. A series of experiments have been performed on a motor with different degrees of stator winding inter-turn faults. The same motor under healthy condition was also tested while operating under unbalanced supply voltages that caused similar current unbalances as in the case of inter-turn short circuit faults. This work aims at identification of the motor voltage unbalance conditions separately from inter-turn fault cases through detection of high frequency signals present in different PVM profiles. Signal processing tools such as Fast Fourier Transform (FFT), Discrete Wavelet Transform (DWT) and Power Spectral Density (PSD) calculation have been employed to discriminate inter-turn short circuit faults from supply voltage unbalance conditions of the motor at different load levels. Entire analysis presented in this paper is based on experimentally obtained motor current signatures.