Signal Denoising Method Based on EWT-FE-NLM

A combined adaptive noise reduction method introducing fuzzy entropy FE optimized empirical wavelet transform (EWT) combined with non-local mean (NLM) filtering is proposed. The method uses FE to determine the boundaries of low-frequency valid signals in all empirical modal components, superimposes the remaining medium- and high-frequency components and then performs NLM filtering, and then reconstructs the filtered signals and the valid signals as the final noise reduction signals, so as to achieve the purpose of filtering out high-frequency noise. The experimental results of telemetry data show that the method of this paper is better than the wavelet thresholding method as a whole, the RMSE is reduced by 10.75%, and the signal-to-noise ratio is reduced by 7.38%.