1.Department of Precision Machinery and Precision Instrumentation, University of Science and Technology of China, Hefei 230027,China；
2. School of Urban Rail Transportation, Soochow University, Suzhou 215021,China
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.
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