Broken-rotor-bar diagnosis for induction motors

Broken rotor bar is one of the commonly encountered induction motor faults that may cause serious motor damage to the motor if not detected timely. Past efforts on broken rotor bar diagnosis have been focused on current signature analysis using spectral analysis and wavelet transform. These methods require accurate slip estimation to localize fault-related frequency. This paper presents a new approach to broken rotor bar diagnosis without slip estimation, based on the ensemble empirical mode decomposition (EEMD) and the Hilbert transform. Specifically, the Hilbert transform first extracts the envelope of the motor current signal, which contains broken rotor fault-related frequency information. Subsequently, the envelope signal is adaptively decomposed into a number of intrinsic mode functions (IMFs) by the EEMD algorithm. Two criteria based on the energy and correlation analyses have been investigated to automate the IMF selection. Numerical and experimental studies have confirmed that the proposed approach is effective in diagnosing broken rotor bar faults for improved induction motor condition monitoring and damage assessment.