Denoising Method of Train Vibration Signal Based on Improved Wavelet Threshold

Abstract

In view of the wheel state monitoring, the wheel vibration signal is often used to reflect the wheel state information, but the original vibration signal contains a lot of noise. In order to extract the effective wheel information, it is necessary to reduce the noise of the original vibration signal. The problems existing in the traditional wavelet threshold denoising method include unreasonable threshold setting, lack of continuity of hard threshold function and fixed deviation of wavelet coefficients processed by soft threshold function. In this paper, the traditional wavelet threshold denoising method is improved from threshold selection and threshold function, and an improved wavelet threshold denoising method is proposed. This method is used to reduce the noise of the measured wheelset vibration signal and compared with the traditional wavelet denoising method from evaluation indexes and graphical results. The results show that the improved wavelet threshold denoising method has better noise reduction effect.