Abstract：As for the dynamic strain signal of the track vehicle, the number of acquisition channels is smaller than that of source channels and it is difficult to apply Independent Component Analysis (ICA) algorithm for noise reduction. To solve this problem, a method for the removal of power frequency interference is proposed, which is based on Empirical Mode Decomposition (EMD) and Independent Subspace Algorithm (ISA). First, the signal is decomposed into a series of Intrinsic Mode Functions (IMF) through EMD. The results are analyzed through ICA algorithm to get the independent components. Then, the original signal is decomposed into different sub spaces by clustering ICs using hierarchical clustering algorithm so that the purpose of separating noise can be achieved. Experimental results show that the proposed method is superior to the traditional filtering algorithm in noise reduction, and the processed value of the signal damage is higher than that of the band stop filter, which makes the life assessment results appear safer. Applying this method to removing the power frequency interference in the dynamic strain signals of track vehicles is thus proved feasible.
李广全，刘志明，张子璠,于洪传. 基于EMD和ISA方法的轨道车辆动态应变信号去工频干扰研究[J]. 北京交通大学学报, 2018, 42(1): 106-.
LI Guangquan, LIU Zhiming, ZHANG Zifan, YU Hongchuan. Research on removing power frequency interference on dynamic strain signal of rolling stock based on EMD and ISA algorithm. Beijing Jiaotong University, 2018, 42(1): 106-.