Wavelet aided SVM classifier for stator inter-turn fault monitoring in induction motors

Early detection of faults in stator winding is crucial for reliable and economical operation of induction motors in industries. Whereas major winding faults can be easily identified from supply current magnitude, minor faults involving less than 5% of turns are not readily discernible. The present work documents experimental results for monitoring of minor short circuit faults in stator windings of induction motor. Motor line current has been analyzed using modern signal processing and data reduction tools combining Park´s transformation and Continuous Wavelet Transform (CWT). Support Vector Machine (SVM) based data classification tool has been used for fault characterization based on fault features extracted using CWT.