Author(s)

Wen-Fa Zhu¹, Hui-Zhen Ma², Xiao-Dong Chai¹, Shu-Bin Zhen¹

¹College of Urban Railway Transportation, Shanghai University of Engineering Science, Shanghai, China.
²Library, Shanghai University of Engineering Science, Shanghai, China.

In this paper, an EMD de-noising algorithm is proposed based on the statistical feature of random noise, which can eliminate the noise impaction digital integrator generated by the collected railway line state detection signals using strap-down inertial technology. Firstly, the first IMF component of the noise-dominant modes treated by the process “random sort-sum-average-reconstruc-tion”, the signal-to-noise ratio is improved while the noise power is weakened in this process. Then the signal-to-noise cut-off can be determined according to the characters of noise autocorrelation function. Finally, the global threshold could be selected by the noise-dominant mode component, so as to realize the function of filtering. The simulation and validation based on the collected railway line acceleration data using the EMD de-noising algorithm show that the noise in railway line state acceleration detection signals can be effectively eliminated using this method.

Track Status, EMD, Autocorrelation Function, Statistical Properties, Filtering

Zhu, W. , Ma, H. , Chai, X. and Zhen, S. (2015) The Research of Railway Line State Detection Signal Processing Method Based on EMD. Open Journal of Safety Science and Technology, 5, 63-68. doi: 10.4236/ojsst.2015.52008.