Motor bearing faults diagnosis using modified empirical mode decomposition and bi-spectrum

The bearing is a very important part of motor equipment. Fault diagnosis of motor bearings is requisite to both safety and reliability, which can avoid accident. In this paper, the fault diagnosis method combined with modified empirical mode decomposition(EMD) and bi-spectrum analysis is used to diagnose the early fault of the motor bearing. Firstly, due to the mode confusion in traditional EMD, wavelet package is applied to reduce the complexity of the signal. Then decompose the signal by EMD, and use the variance contribution rate test to remove the illusive IMF. At last, bi-spectrum is applied to analysis the interactions and detect the fault characteristic frequency. Through processing and analyzing the rolling bearing experimental data of West Reserve University, it shows this method is effective.