Strong noise signal filtering algorithm based on wavelet transform module and modified Perona-Malik model

被引：0
|
作者：
Wu W. [1 ]
Chen X. [2 ]
机构：
[1] Department of Management Science and Engineering, Officers College of PAP, Chengdu
[2] Department of Equipment Management Engineering, Rocket Force University of Engineering, Xi'an
来源：
Chen, Xiaohu | 2018年 / Chinese Vibration Engineering Society卷 / 37期
关键词：
Diffusion coefficient; Partial differential equation; Perona-Malik model; Signal de-noising; Strong noise; Wavelet transform;
D O I：
10.13465/j.cnki.jvs.2018.17.039
中图分类号：
学科分类号：
摘要：
Aiming at traditional mechanical vibration signals de-noising method's limitation, considering partial differential equations' principle and application in image de-noising, a strong noise signal filtering algorithm based on wavelet transform module and modified Perona-Malik model was proposed. Firstly, the correlation between the wavelet threshold de-noising and Perona-Malik nonlinear anisotropic diffusion filtering model was studied. Secondly, wavelet transform module was used to substitute gradient module and construct an improved diffusion coefficient. The modified Perona-Malik model was derived based on wavelet transform module. The test results showed that compared with the traditional de-noising method and the basic Perona-Malik model, the modified Perona-Malik model can not only realize mechanical vibration signals' effective de-noising under strong noise background, but also keep signals' detail features with little signal distortion; it has a strong anti-noise capacity, the new algorithm makes the average SNR increase by about 3 dB. © 2018, Editorial Office of Journal of Vibration and Shock. All right reserved.
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页码：277 / 282
页数：5
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