Rolling bearing fault diagnosis based on improved EMD and morphological filter
WEN Cheng， ZHOU Chuande
（College of Mechanical and Power Engineering，Chongqing University of Science and Technology，
Abstract: A new technology is proposed to solve the non-stationarity in vibration signals of antifriction bearing faults in accordance with the improved empirical mode decomposition （EMD） and morphological filters. First， a high-frequency harmonic was added into the original signal and then decomposed by means of EMD to reduce the mode mixing phenomenon in traditional EMD. Next， the high-frequency harmonic was removed from the high-frequency intrinsic mode component （IMF） to obtain fault impact compositions. The fault characteristic information was extracted by spectrum analysis after morphological filter de-noising. At the same time， the above steps were simulated by signals. This method was applied to diagnose the faults in inner and outer races of antifriction bearings. The experimental results show that the method can extract the fault characteristics and diagnose the faults of antifriction bearings.
Keywords: improved empirical mode decomposition； morphological filter； rolling bearing； fault diagnosis