Denoising method for vibration signal of hob based on grey criterion and EEMD

被引：0
|
作者：
Jia Y. [1 ]
Li G. [1 ]
He K. [2 ]
Dong X. [1 ]
机构：
[1] State Key Laboratory of Mechanical Transmission, Chongqing University, Chongqing
[2] Chongqing Key Laboratory of Manufacturing Equipment Mechanism Design and Control, Chongqing Technology and Business University, Chongqing
来源：
Yi Qi Yi Biao Xue Bao/Chinese Journal of Scientific Instrument | 2019年 / 40卷 / 07期
关键词：
Denoising; Ensemble empirical mode decomposition; Grey criterion; Vibration signal of hob;
D O I：
10.19650/j.cnki.cjsi.J1905242
中图分类号：
学科分类号：
摘要：
The collected vibration signal of hob in engineering site is contaminated with noise. It is difficult to extract features contained in vibration signal. In this study, ensemble empirical mode decomposition (EEMD) is applied to denoise vibration signals. To solve the problem of selecting and processing of intrinsic mode function (IMF) after EEMD decomposition, a denoising method of hob vibration signal based on grey criterion and EEMD is proposed. Firstly, the original signal is decomposed into several IMF components by EEMD. Then, according to the proposed grey criterion, each IMF component is processed by polarity consistency and mean processing. The grey correlation between IMF1 and other IMF components is calculated. All IMF components are arranged in descending order according to the grey correlation degree. The first half of IMF components in the descending order are selected for soft threshold processing. Finally, processed IMF components, unprocessed IMF components and residual components are reconstructed to obtain the denoised signal. The feasibility and validity of the method are verified by the simulation signal with different initial signal-to-noise ratios and the vibration signals of the hob in actual machining. Meanwhile, the proposed method is compared with EEMD combined with correlation coefficient and wavelet soft threshold denoising. Experimental results show that this method has better denoising effectiveness. © 2019, Science Press. All right reserved.
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页码：187 / 194
页数：7
相关论文
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