Research on a Noise Reduction Method Based on Multi-Resolution Singular Value Decomposition

被引:15
|
作者
Zhang, Gang [1 ]
Xu, Benben [2 ]
Zhang, Kaoshe [2 ]
Hou, Jinwang [2 ]
Xie, Tuo [1 ]
Li, Xin [2 ]
Liu, Fuchao [3 ]
机构
[1] Xian Univ Technol, State Key Lab Ecohydraul Northwest Arid Reg, Xian 710048, Peoples R China
[2] Xian Univ Technol, Sch Elect Engn, Xian 710048, Peoples R China
[3] State Grid Gansu Elect Power Co, Gansu Elect Power Res Inst, Lanzhou 730050, Peoples R China
来源
APPLIED SCIENCES-BASEL | 2020年 / 10卷 / 04期
基金
国家重点研发计划; 中国国家自然科学基金;
关键词
signal noise reduction; multi-resolution singular value decomposition; signal to noise ratio; mean square error; EMPIRICAL MODE DECOMPOSITION; EXTRACTION;
D O I
10.3390/app10041409
中图分类号
O6 [化学];
学科分类号
0703 ;
摘要
Reducing noise pollution in signals is of great significance in the field of signal detection. In order to reduce the noise in the signal and improve the signal-to-noise ratio (SNR), this paper takes the singular value decomposition theory as the starting point, and constructs various singular value decomposition denoising models with multiple multi-division structures based on the two-division recursion singular value decomposition, and conducts a noise reduction analysis on two experimental signals containing noise of different power. Finally, the SNR and mean square error (MSE) are used as indicators to evaluate the noise reduction effect, it is verified that the two-division recursion singular value decomposition is the optimal noise reduction model. This noise reduction model is then applied to the diagnosis of faulty bearings. By this method, the fault signal is decomposed to reduce noise and the detail signal with maximum kurtosis is extracted for envelope spectrum analysis. Comparison of several traditional signal processing methods such as empirical modal decomposition (EMD), ensemble empirical mode decomposition (EEMD), variational mode decomposition (VMD), wavelet decomposition, etc. The results show that multi-resolution singular value decomposition (MRSVD) has better noise reduction effect and can effectively diagnose faulty bearings. This method is promising and has a good application prospect.
引用
收藏
页数:17
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