关键词: 盲均衡理论；特征向量算法;时间序列分解；源冲击；滚动轴承

Abstract:

After analyzing the shortcomings of current bearing fault diagnosis technologies,a novel enhanced blind equalization(BE) technology based on time-series decomposition(TD) analysis was proposed to extract directly impacting features and diagnose bearings’ faults herein.First，the blind equalization model and algorithm of impacting signal processing of rolling bearings were established based on the BE theory and
eigenvector algorithm(EVA) algorithm.Then,the TD theory and method were applied to the model and algorithm. After these, the enhanced signal processing and fault diagnosis algorithm based on TD and BE was proposed,and the improving method of the inherent shortcomings of the algorithm was presented.Finally, the built model and algorithm were applied to two impact experiments and two real engineering data for verification.The results show that the method is very effective in extracting the impacting features and fault diagnosis for rolling bearings. 

Key words: blind equalization;eigenvector algorithm;time-series decomposition;source impact;rolling bearing