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.
付秀伟,高兴泉. 基于傅里叶分解与奇异值差分谱的滚动轴承故障诊断方法[J]. 计量学报, 2018, 39(5): 688-692.
FU Xiu-wei,GAO Xing-quan. Rolling Bearing Fault Diagnosis Based on FDM and Singular Value Difference Spectrum. Acta Metrologica Sinica, 2018, 39(5): 688-692.
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