Application of multi-feature based on LMD in fault Feature extraction of bearing Type

被引：0
|
作者：
Qi Xiaoxuan [1 ]
Xu Changyuan [2 ]
机构：
[1] Tianjin Univ, Sch Elect Engn & Automat, Tianjin, Peoples R China
[2] Shenyang Univ, Sch Informat Engn, Shenyang, Peoples R China
来源：
PROCEEDINGS OF THE 4TH INTERNATIONAL CONFERENCE ON INFORMATION TECHNOLOGY AND MANAGEMENT INNOVATION | 2015年 / 28卷
关键词：
kurtosis; approximate entropy; LMD; APEN; WAVELET TRANSFORM;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
This paper presents a application of kurtosis and approximate entropy in rolling bearing fault diagnosis. First use the method of LMD adaptive decomposed he rolling bearing vibration signal into different time scales of PF component, then filtered to get PF component, and rebuilt a new weighted optimization reconstruction fusion PF component, finally have the rolling bearing vibration signal feature extraction and realize fault diagnosis.
引用
收藏
页码：1130 / 1133
页数：4
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