Application of CBSR and LMD in reciprocating compressor fault diagnosis

被引：1
|
作者：
Li, Yongbo [1 ]
Xu, Minqiang [1 ]
Wei, Yu [1 ]
Huang, Wenhu [1 ]
机构：
[1] Harbin Inst Technol, Dept Astronaut Sci & Mech, Harbin 150001, Peoples R China
来源：
JOURNAL OF VIBROENGINEERING | 2015年 / 17卷 / 01期
基金：
中国国家自然科学基金;
关键词：
cascaded bistable stochastic resonance (CBSR); local mean decomposition (LMD); fault diagnosis; reciprocating compressor; LOCAL MEAN DECOMPOSITION; HILBERT SPECTRUM;
D O I：
暂无
中图分类号：
R318 [生物医学工程];
学科分类号：
0831 ;
摘要：
Local mean decomposition (LMD) is a novel adaptive time-frequency analysis method, which is widely used in reciprocating compressor fault diagnosis. However, LMD decomposition results method is sensitive to noise. In order to eliminate influence of noise, cascaded bistable stochastic resonance (CBSR) is introduced and a new fault diagnosis method based on CBSR denoising and LMD is proposed in this paper. Firstly, CBSR is employed as the pretreatment to remove noise in vibration signals, and then the denoised signal is decomposed by LMD method. Finally, the fault frequency of reciprocating compressor is found through the envelope spectrum analysis of the first PF component. The effectiveness of the proposed method is verified by the simulation data and the practical reciprocating compressor fault diagnosis.
引用
收藏
页码：203 / 215
页数：13
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