Discrete Wavelet Transform for Stator Fault Detection in an Induction Motor

The problem of diagnosing inter-turn short circuits (ITSC) in the stator winding of an induction motor (IM) under various load conditions is considered. The enhancement of the reliability of the operations of IMs may be achieved by the timely detection of faults. Improvement of the methodology for diagnosis of IMs is required for this. An online methodology for diagnosing an inter-turn short circuit (ITSC} in the IM winding is presented. The proposed approach is based on the formation of the envelope of the stator current with the aid of the Hilbert transform by means of multiplying this current by the Tukey window, in order to reduce the effect of transient distortions. Then the discrete wavelet transform (DWT) is performed, to facilitate ITSC fault diagnosis. Finally, based on statistical analysis using the Weibull distribution, the fault thresholds are determined. Hence, by monitoring the estimation of the mean value, it is possible to detect an incipient fault condition of the induction motor. © 2023, Springer Science+Business Media, LLC, part of Springer Nature.