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

DOI

10.2991/iccasm.2012.390How to use a DOI?

Keywords

subsidence and deformation monitoring, denoising, wavelet analysis, threshold function

Abstract

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.

Copyright

© 2012, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Peng Zhou
AU  - Jianmin Wang
AU  - Jianchao Yang
AU  - Gang Wang
AU  - Zhenbin Tang
PY  - 2012/08
DA  - 2012/08
TI  - Application of Wavelet Threshold Denoising in High-speed Rail Data Processing in Alpine Region
BT  - Proceedings of the 2012 International Conference on Computer Application and System Modeling (ICCASM 2012)
PB  - Atlantis Press
SP  - 1523
EP  - 1526
SN  - 1951-6851
UR  - https://doi.org/10.2991/iccasm.2012.390
DO  - 10.2991/iccasm.2012.390
ID  - Zhou2012/08
ER  -