Abstract: Aiming at shortcomings of traditional denoising methods on the China Railway High-speed(CRH) data, to assure the accuracy, this paper researches on the wavelet method through analyzing the reasons causing that shortage. To improve the accuracy as much as possible, by analyzing the parameters selecting methods, simulations of different parameters are carried out for dealing with CRH data. According to the comparisons, it gets the better parameters to process CRH data. It can provide strong support for the further research on denoising method.

Key words: wavelet threshold, Wavelet Transform(WT), denoising, distortion, China Railway High-speed(CRH) data

摘要： 动车组传统信号去噪方法无法区分信号和噪声的高频部分，导致部分有用信息的流失。为此，分析失真的原因，研究小波阈值去噪方法。为提高小波去噪的精度，采用不同的参数选择方法，对动车组数据的处理进行实验对比，以得到更为合适的参数。实验结果验证了该方法的有效性。

关键词: 小波阈值, 小波变换, 去噪, 失真, 动车组数据

CLC Number: 

• TP399