Rotating machine fault feature extraction based on reduced time frequency representation

被引：0

作者：

Zhang, Yan ^{[1
]}

Tang, Bao-Ping ^{[1
,2
]}

Liu, Zi-Ran ^{[2
]}

Chen, Ren-Xiang ^{[1
]}

机构：

[1] The State Key Laboratory of Mechanical Transmission, Chongqing University, Chongqing

[2] School of Mechanical & Electrical Engineering, Henan University of Technology, Zhengzhou

来源：

Zhendong Gongcheng Xuebao/Journal of Vibration Engineering | 2015年 / 28卷 / 01期

关键词：

Basis pursuit; Fault diagnosis; Feature extraction; Time frequency representation; Two dimensional non-negative matrix factorization;

D O I：

10.16385/j.cnki.issn.1004-4523.2015.01.020

中图分类号：

学科分类号：

摘要：

Aiming at extracting fault features from the two-dimensional time frequency representation, a novel time frequency feature extraction method based on reduced time frequency representation is proposed after investigating the principles of basis pursuit and Two Dimensional Non-negative Matrix Factorization (2DNMF). Combined with Wigner-Ville distribution, the basis pursuit method which represents the original signal as a set of atoms is introduced to compute the basis pursuit time frequency representation, and then 2DNMF is employed to reduce the dimension of the amplitude matrix of basis pursuit time frequency representation and extract its corresponding low dimensional features. The proposed method is applied to extract the fault features from eight different state rolling bearings, and the results verify its effectiveness. ©, 2015, Nanjing University of Aeronautics an Astronautics. All right reserved.

引用

页码：156 / 163

页数：7

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