基于EEMD-ICA算法的地铁混合波长钢轨波磨识别

Identification of rail corrugation with mixed wavelength in Metro based on EEMD-ICA algorithm

地铁线路上常存在多种波长的钢轨波磨混合的情况,而目前的钢轨波磨识别方法主要适用于单一波长的钢轨波磨。针对混合波长的钢轨波磨识别问题,提出了一种基于集合经验模态分解-独立分量分析的地铁多波长钢轨波磨识别算法。首先建立了车辆-轨道耦合动力学模型和钢轨波磨激励模型,通过动力学计算得到混合波长的钢轨波磨作用下轴箱的振动加速度信号。对计算得到的轴箱振动加速度信号进行集合经验模态分解。引入相关系数筛选符合条件的本征模态分量,计算选择好的本征模态分量的能量平均值,通过设定能量阈值判断是否存在钢轨波磨,最后将选择的本征模态分量与源信号重构成多维信号,将重构的多维信号作为独立分量分析的输入矩阵以解决独立分量分析的欠定问题,定位分离结果的中心频率确定钢轨波磨波长。为了更好的验证本文算法,在广州某地铁线路上采集了波磨激扰下轴箱垂向振动加速度信号和线路不平顺水平,使用本文算法分析了实验数据。结果证明,在16和31.5 mm两种不同的波磨波长混合激扰下,该方法依然可以识别出两种不同的波磨波长,而传统的小波包能量熵法和EEMD能量熵-WVD法仅能识别振动特征较为明显的16 mm波长的波磨,即这两种方法不能应用于混合波长波磨识别的问题。本文的研究成果为地铁混合波长钢轨波磨的识别提供了理论支撑。

Rail corrugation with multiple wavelengths is often mixed on subway lines,and the current rail corrugation identification method is mainly suitable for rail corrugation with a single wavelength.Aiming at the problem of rail corrugation identification of mixed wavelengths,this paper proposes a multi-wavelength rail corrugation identification algorithm based on ensemble empirical mode decomposition-independent component analysis.Firstly,the vehicle-track coupling dynamics model and the rail corrugation excitation model are established,and the vibration acceleration signal of the axle box under the action of the mixed wavelength rail corrugation is obtained through dynamic calculation.The ensemble empirical mode decomposition is performed on the calculated vibration acceleration signal of the axle box.Introduce the correlation coefficient to screen the qualified eigenmode components,calculate the energy average value of the selected eigenmode components,determine whether there is rail corrugation by setting the energy threshold,and finally selected eigenmode components and the source signal are reconstructed into a multi-dimensional signal,and the reconstructed multi-dimensional signal is used as the input matrix of the independent component analysis to solve the underdetermined problem of the independent component analysis,The center frequency of the positioning separation results determines the rail corrugation wavelength.In order to better verify the algorithm in this paper,the vertical vibration acceleration signal of axle box and the line irregularity level under the wave and wear excitation were collected on a subway line in Guangzhou,and the experimental data were analyzed using the algorithm of this paper.The results prove that under the mixed excitation of two different corrugation wavelengths of 16 and 31.5 mm,the method can still identify two different corrugation wavelengths,while the traditional wavelet packet energy entropy method and EEMD energy entropy-WVD method can only identify corrugation with a wavelength of 16 mm with obvious vibration characteristics,in other words,these two methods cannot be applied to the problem of mixed wavelength corrugation identification.The research results of this paper provide theoretical support for the identification of rail corrugation with mixed wavelengths in subways.