Application of Wavelet Threshold Denoising in High-speed Rail Data Processing in Alpine Region

Abstrac t-In alpine regions, a series of external factors may result in error in observing data of the high-speed rail. Based on traditional high-speed rail subsidence and deformation monitoring methods, this article aims at denoising processing of observing data of Harbin-to-Dalian high-speed rail(Siping section), in which the wavelet threshold denoising method was adopted. Comparing the denoising results of the hard and the soft threshold function, we put up a new method, which preprocessed the raw data with fuzzy control filter. As the results showed, the method could sensitively recognize the noise without prior knowledge, therefore, it is suitable for high-speed rail subsidence and deformation data processing in alpine regions.