Seismic Signal Analysis Based on Adaptive Variational Mode Decomposition for High-speed Rail Seismic Waves
Lei Yang, Liu Lu, Bai Wen-lei, Feng Hai-xin, Wang Zhi-yang*
1. College of Information Science and Technology, Beijing University of Chemical Technology, Beijing, 100029, PRC
2. Aramco Beijing Research Center, Aramco Asia, Beijing, 100102, PRC
3. Key Laboratory of Petroleum Resources Research, Institute of Geology and Geophysics, Chinese Academy of Sciences, Beijing, 100029, PRC
4. Third Research Institute of China Electronics Technology Group Company, 100015, PRC
Abstract High-speed rails with determined length and load run for long periods at almost uniform speeds along fixed routes, constituting a new stable and repeatable artificial seismic source. Studies have demonstrated the wide bands and discrete spectra of high-speed rail seismic signals. Exploring the abundant information contained in massive high-speed rail seismic signals has great application value in the safety monitoring of high-speed rail operation and subgrade. However, given the complex environment around the rail network system, field data contain not only high-speed rail seismic waves but also ambient noise and the noise generated by various human activities. The foundation and key to effectively using high-speed rail seismic signals is to extract them from field data. In this paper, we propose an adaptive variational mode decomposition (VMD)-based separation algorithm for high-speed rail seismic signals. The optimization algorithm is introduced to VMD, and sample entropy and energy difference are used to construct the fitness function for the optimal adjustment of the mode number and penalty factor. Furthermore, time–frequency analysis is performed on the extracted high-speed rail signals and field data using the synchrosqueezed wavelet transform (SSWT). After verifying the processing of simulated signals, the proposed method is applied to field data. Results show that the algorithm can effectively extract high-speed rail seismic signals and eliminate other ambient noises, providing a basis for the imaging and inversion of high-speed rail seismic waves.
Fund: This work was supported by project A2309002, XJZ2023050044, and XJZ2023070052
Corresponding Authors: Wang Zhi-yang E-mail: zhzxwzy@126.com.
E-mail: zhzxwzy@126.com.
About author: Lei Yang received his B.S. degree from the Anhui University of Science and Technology, China, in 2021. He is currently pursuing a master’s degree at the College of Information Science and Technology, Beijing University of Chemical Technology, China. His primary research focus is numerical analysis of seismic waves.
Cite this article:
. Seismic Signal Analysis Based on Adaptive Variational Mode Decomposition for High-speed Rail Seismic Waves[J]. APPLIED GEOPHYSICS, 2024, 21(2): 358-371.
2024, Vol. 21 
