Strong noise signal filtering algorithm based on wavelet transform module and modified Perona-Malik model
WU Wenfeng1, CHEN Xiaohu2
1. Department of Management Science and Engineering,Officers College of PAP,Chengdu 610213,China;
2. Department of Equipment Management Engineering,Rocket Force University of Engineering,Xi’an 710025,China
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.
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