De-Noising of High-speed Turnout Vibration Signal based on Wavelet Threshold
ZHOU Xiang-xin1, WANG Xiao-min1, YANG Yang1 , GUO Jin1, WANG Ping2
1. Key Lab of Traffic Information Engineering and Control, Southwest Jiaotong University, Chengdu 610031;2. School of Civil Engineering, Southwest Jiaotong University, Chengdu 610031
Abstract：Turnout vibration signals are important information in the high-speed turnout damage monitoring. As the signals are interfered with strong noise during the process of field acquisition and transmission, the accuracy of damage identification based on noisy vibration signals is declined seriously. To overcome this problem, a denoising method is generally employed before the damage identification. The complex and noisy vibration samples from the field, however, raise the hurdle for denoising. An effective denoising method based on wavelet threshold for turnout vibration signals is proposed in this paper. The wavelet basis, decomposition scale, threshold criteria and threshold function are empirically discussed for wavelet threshold denoising. Then damage identification analysis is conducted by the principal component analysis (PCA) of frequency response function (FRF) and average Mahalanobis distance (MD). The experimental results show that the method can reduce the noise interference effectively for damage identification, and create favorable conditions for further damage analysis.
2014, Vol. 33 
