Classification and diagnosis of broken rotor bar faults in induction motor using spectral analysis and SVM

In this paper, we propose to detect and localize the broken bar faults in multi-winding induction motor using Motor current signature (MCSA) combined to Support Vector Machine (SVM). The analysis of stator currents in the frequency domain is the most commonly used method, because induction machine faults often generates particular frequency components in the stator current spectrum. In order to obtain a more robust diagnosis, we propose to classify the feature vectors extracted from the magnitude of spectral analysis using multi-class SVM to discriminate the state of the motor. Finally, in order to validate our proposed approach, we simulated the multi-winding induction motor under Matlab software. Promising results were obtained, which confirms the validity of the proposed approach.