Bearing Failures Detection in Induction Motors Using the Stator Current Analysis Based on Hilbert Huang Transform

Fault detection is a major challenge for the maintenance of asynchronous motors. The bearings defects are the most important defects that can occur in these. In this context, we propose a new approach for the detection of these defects based on the analysis of the stator current. The Ensemble Empirical Mode Decomposition is applied to the stator current experimental data of the asynchronous motor subjected to various loads in healthy and failing case. The results of the analysis of the envelope of selected Intrinsic Mode Functions, obtained by Ensemble Empirical Mode Decomposition algorithm allowed us to get a better discrimination of different bearing defects.