A New Robust Rolling Bearing Vibration Signal Analysis Method

被引:2
|
作者
Li, Jingchao [1 ,2 ]
Ying, Yulong [3 ]
Zhang, Guoyin [1 ]
Chen, Zhimin [2 ]
机构
[1] Harbin Engn Univ, Sch Comp Sci & Technol, Harbin, Heilongjiang, Peoples R China
[2] Shanghai Dianji Univ, Sch Elect & Informat, Shanghai, Peoples R China
[3] Shanghai Univ Elect Power, Sch Energy & Mech Engn, Shanghai, Peoples R China
来源
基金
中国国家自然科学基金;
关键词
Vibration signal processing; Holder theory; Gray relation theory; Fault diagnosis; SUPPORT VECTOR MACHINE; FAULT-DIAGNOSIS; ENTROPY; OPTIMIZATION;
D O I
10.1007/978-3-319-73317-3_17
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
As bearing vibration signal is of nonlinear and nonstationary characteristics, and the condition-indicating information distributed in the rolling bearing vibration signal is complicated, a new rolling bearing health status estimation approach using holder coefficient and gray relation algorithm was proposed based on bearing vibration signal in the paper. Firstly, the holder coefficient algorithm was proposed for extracting health status feature vectors based on the bearing vibration signals, and secondly the gray relation algorithm was developed for achieving bearing fault pattern recognition intelligently using the extracted feature vectors. At last, the experimental study has illustrated the proposed approach can efficiently and effectively recognize different fault types and in addition different severities with good real-time performance.
引用
收藏
页码:137 / 145
页数:9
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