Study on White Noise Suppression Using Complex Wavelet Threshold Algorithm

Shu Qi Zhang; Jin Zhong Li; Rui Guo; Hao Tang; Tao Zhao; Li Gao

doi:10.4028/www.scientific.net/AMM.521.347

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vol. 521Study on White Noise Suppression Using Complex...

Study on White Noise Suppression Using Complex Wavelet Threshold Algorithm

Abstract:

The complex wavelet transform modulus maximum of the PD signal increases with scale, while the complex wavelet transform modulus maximum of white noise decreases with scale. According to the characteristics, a study on white noise suppression using the effective complex wavelet coefficient (ECWC) threshold method is launched in this paper and a comparison is conducted with the wavelet threshold denoising method of threshold selection of Stein unbiased risk estimate theory and threshold selection of minimax theory. The PD signal denoising results show that ECWC threshold method is more effective and the distortion of the extract PD signal is lower compared with the other method.

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Periodical:

Applied Mechanics and Materials (Volume 521)

Pages:

347-351

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.521.347

Citation:

Cite this paper

Online since:

February 2014

Authors:

Shu Qi Zhang*, Jin Zhong Li, Rui Guo, Hao Tang, Tao Zhao, Li Gao

Keywords:

Complex Wavelet, Effective Complex Wavelet Coefficient Method, Partial Discharge (PD), White Noise Suppression

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