Induction motor asymmetrical faults detection using advanced signal processing techniques

Preventive maintenance of electric drive systems with induction motors involves monitoring of their operation for detection of abnormal electrical and mechanical conditions that indicate, or may lead to, a failure of the system. Intensive research effort has been for sometime focused on the motor current signature analysis. This technique utilizes the results of spectral analysis of the staler current. Reliable interpretation of the spectra is difficult, since distortions of the current waveform caused by the abnormalities in the drive system are usually minute. In the present investigation, the frequency signature of some asymmetrical motor faults are well identified using the Fast Fourier Transform (FFT), leading to a better interpretation of the motor current spectra. Laboratory experiments indicate that the motor current signature FFT-based analysis, with the proposed approach, is still a reliable tool for induction motor asymmetrical faults detection.