A study on adaptive wavelet packet threshold function de-noising algorithm based on Shannon entropy
ZHOU Jian,XIANG Beiping,NI Lei,AI Panhua
Manufacturing Process Testing Technology Key Laboratory of the Ministry of Education, Southwest University of Science and Technology, Mianyang 621000, China
The key problem of the wavelet packet de-noising algorithm is effectively eliminating noise while retaining as many of the original signal wavelet packet coefficients as possible.Due to the lack of adjustable parameters and the fixed de-noising form, the traditional threshold function fails to adjust adaptively based on the noise contribution of wavelet packet decomposition coefficients, and the de-noising effects have yet to be improved.Therefore, Shannon entropy was introduced as the adjusting parameter in the wavelet packet threshold function.To shrink wavelet packet coefficients on a large scale under a strong noise background and a smooth transition for threshold shrinkage under weak noise background, an adjustable wavelet packet threshold de-noising algorithm based on Shannon entropy was proposed.The signal was decomposed by the wavelet packet method, and the Shannon entropy of wavelet packet coefficients in the largest decomposition dimension was calculated for the adjustment of threshold function.The de-noising analysis of the simulation signal, the bearing vibration experimental signal based on the method above, and other wavelet threshold de-noising algorithms show that the new method has a greater de-noising effect and effectively retains original features of the signal while removing noise.
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