关键词: 最小熵反褶积, 数学形态, 故障诊断, 滚动轴承

Abstract: Aiming at the extractions of fault features of rolling bearings under the strong noise background, a novel method, called mathematical morphology based on minimum entropy deconvolution (MMBMED) was proposed herein. In this method, MED was first introduced to enhance the impact behaviors of the signals. And the fault characteristics of defective bearings were extracted by MM method, where the DIF filter with catching the bidirectional pulses was adopted as morphological operator, and kurtosis was employed as the criterion to the length selection of structural elements. The effectiveness of the new method was validated by both of simulation signals and vibration signals of rolling bearings with the outer and inner race faults. Finally, the results disclose that MED is effective to increase signal kurtosis and to strengthen the impulsive characteristics.

Key words: minimum entropy deconvolution(MED), mathematical morphology(MM), fault diagnosis, rolling bearing