基于自适应VMD算法的高速铁路地震信号分析

Seismic Signal Analysis Based on Adaptive Variational Mode Decomposition for High-speed Rail Seismic Waves

高速铁路以确定的长度和负载在固定线路上以几乎均匀的速度长时间运行,构成了一种新的稳定且可重复的人工地震源。研究表明高速铁路地震信号具有宽频带分立谱特征。挖掘大量高速铁路地震信号中所包含的丰富信息在高速铁路运行和路基的安全监测方面具有重要的应用价值。然而,由于铁路网络系统周围环境的复杂性,实际采集数据中除高铁地震信号外,还包含有地球背景噪声以及各种人类活动所产生的噪声。如何提取实际记录中的高铁地震信号是有效利用该类信号的基础和关键。在本文中,我们提出了一种基于自适应变分模态分解(Variational mode decomposition,VMD)的高速铁路地震信号分离算法,将优化算法引入到变分模态分解中,利用能量差参数和样本熵构建适应度函数,实现对模态数及惩罚因子优化调整。此外,利用同步挤压小波变换(Synchrosqueezed wavelet transform,SSWT)对提取的高速铁路信号和现场数据进行时频分析。通过对模拟信号的处理验证后,应用到实际采集到的高铁地震数据进行分析处理。结果表明,该方法可以有效提取高铁地震信号,剔除其它背景噪声,为后续开展高铁地震的成像和反演提供基础。

High-speed rails with determined length and load run for long periods at almost uniform speeds along fi xed routes,constituting a new stable and repeatable artifi cial 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,fi eld 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 diff erence are used to construct the fi tness 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 fi eld data.Results show that the algorithm can eff ectively 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.