摘要
在分析现有轴承故障诊断技术的基础上,基于盲均衡理论提出了一种独特的直接提取轴承故障冲击特征的故障诊断方法。首先根据盲均衡理论建立了轴承冲击信号处理的盲均衡模型和算法;然后基于时间序列分解对盲均衡模型和算法进行改进和加强,提出了算法中固有的幅值和相位缺陷的修正方法;最后给出了两个冲击实验和两个实际数据应用实例。研究结果表明,该方法能够有效地诊断轴承冲击性故障。
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 hearings.
出处
《中国机械工程》
EI
CAS
CSCD
北大核心
2009年第14期1708-1712,共5页
China Mechanical Engineering
基金
中国博士后科学基金资助项目(20080431392)
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
blind equalization
eigenvector algorithm
time-- series decomposition
source impact
rolling bearing
