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Rolling Bearing Fault Diagnosis Based on FDM and Singular Value Difference Spectrum |
FU Xiu-wei,GAO Xing-quan |
College of Information & Control Engineering, Jilin Institute of Chemical Technology, Jilin, Jilin 132002, China |
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Abstract Based on the characteristic that is the feature extraction of rolling bearing’s impact features is very hard under strong noise, a method based on Fourier decomposition method (FDM) and singular value difference spectrum is proposed. First, the non-stationary original bearing fault vibration signal was decomposed into several Fourier intrinsic band functions (FIBFs) by FDM. Then, the original signal was reconstructed by using correlation cross-coefficient method. The reconstructed signal was de-noised by the singular value difference spectrum. Finally, the fault characteristic frequency is accurately identified by using Hilbert envelope spectrum to the combined de-noised signal. The simulation analysis and test are good to verify the proposed method.
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Received: 13 April 2017
Published: 05 September 2018
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