Research on Improved Wavelet Packet Threshold Denoising Algorithm Based on Sample Entropy

被引：0
|
作者：
Xiang B. [1 ]
Zhou J. [1 ]
Ni L. [1 ]
Ai P. [1 ]
机构：
[1] Manufacturing Process Testing Technology Key Laboratory of the Ministry of Education, Southwest University of Science and Technology, Mianyang
来源：
Zhendong Ceshi Yu Zhenduan/Journal of Vibration, Measurement and Diagnosis | 2019年 / 39卷 / 02期
关键词：
Fault diagnosis; Sample entropy; Threshold denoising; Vibration signal; Wavelet packet coefficients;
D O I：
10.16450/j.cnki.issn.1004-6801.2019.02.027
中图分类号：
学科分类号：
摘要：
In the light of eliminating the interference of noise, the limitation of traditional wavelet packet threshold denoising method is analyzed and an improved wavelet packet threshold denoising algorithm based on sample entropy is proposed. At the aspect of threshold function, the method takes sample entropy as a characteristic parameter to represent noise distribution of noisy signal wavelet packet coefficients, and improves the threshold function according to the parameter value, so that it can adjust adaptively based on the noise distribution of signal wavelet packet coefficients. In terms of threshold selection, define the difference between denoised signal and original signal as the estimation of the noise signal, and use sample entropy as the determination criterion to choose the optimal threshold which makes the noise estimation sample entropy maximum. Finally, the method is used to denoise rolling bearing vibration. Comparison with the traditional method shows that the method removed noise effectively and restored signal frequency characteristic better, it's a greater denoising algorithm. © 2019, Editorial Department of JVMD. All right reserved.
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页码：410 / 415
页数：5
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