Journal article
基于分量筛选奇异值分解的滚动轴承故障诊断方法研究
振动与冲击, Vol.34(20), pp.61-65
2015
Abstract
The fault diagnosis of bearings in rotary machines is of great significance. In order to extract information from complicated bearing vibration signal, a fault diagnosis method based on component screening singular value decomposition (CSSVD) is proposed. The theory of SVD is explained and a Hankel matrix is constructed for SVD of the bearing vibration signal. To choose the component signals after SVD, the criterion of correlation coefficient is employed. Then the component signals are reconstructed and fault feature frequencies are extracted. Compared with the traditional method, the effectiveness and advantage of the proposed method are demonstrated by analyzing simulated signals and actual bearing signals.
Details
- Title: Subtitle
- 基于分量筛选奇异值分解的滚动轴承故障诊断方法研究
- Creators
- 朱军闵祥敏孔凡让黄伟国王超胡智勇
- Resource Type
- Journal article
- Publication Details
- 振动与冲击, Vol.34(20), pp.61-65
- ISSN
- 1000-3835
- Alternative title
- Rolling bearing fault diagnosis based on component screening singular value decomposition
- Language
- Chinese
- Date published
- 2015
- Academic Unit
- Industrial and Systems Engineering
- Record Identifier
- 9984221731202771
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