摘要
为了解决高速铁路钢轨波磨的快速检测问题,提出通过运营动车组车下声信号进行声学诊断的方法。该方法针对钢轨波磨声信号的低信噪比且易被掩蔽的特点,首先通过集成经验模态分解(EEMD)从高频到低频把含有严重噪声的初始信号分解为具有不同模态的子信号即本征模态函数(IMF)分量。根据IMF分量的能量比畸变特征筛选得到钢轨波磨区段对应的IMF分量,然后进行Hilbert变换得到时频域特征,从而实现对钢轨波磨区段的识别。经在一高速铁路2个典型路基区段进行现场验证,采用该方法可将钢轨粗糙度等级22.8 dB(幅值13.8μm)的钢轨波磨初期区段识别出来,且声学诊断识别出的瞬时峰值频率与由现场实测结果推算出的理论声学特征频率仅相差3.3%,准确度较高。
In order to solve the rapid detection problem of rail corrugation in high speed railway,an acoustic diagnosis method based on the acoustic signal under the EMU operating was proposed.According to the rail corrugation sound signal characteristics of low signal-to-noise ratio and being easily masked,the initial signal with serious noise was decomposed into sub signals with different modes,namely intrinsic mode function(IMF)components,from high frequency to low frequency by ensembling empirical mode decomposition(EEMD).According to the energy ratio distortion characteristics of the IMF component,the IMF component corresponding to the rail corrugation section was screened,and then the time-frequency domain characteristics were obtained by Hilbert transform,so as to realize the identification of the rail corrugation section.After field verification in two typical subgrade sections of a high speed railway,rail corrugation initial section with the rail roughness grade of 22.8 dB(amplitude of 13.8μm)could be identified by using this method.The instantaneous peak frequency identified by acoustic diagnosis is only 3.3%different from the theoretical acoustic characteristic frequency calculated from the field measurement results,which indicates that the accuracy is high.
作者
韩立
伍向阳
刘兰华
陈迎庆
张毅超
宣晓梅
朴爱玲
HAN Li;WU Xiangyang;LIU Lanhua;CHEN Yingqing;ZHANG Yichao;XUAN Xiaomei;PIAO Ailing(Energy Saving&Environmental Protection&Occupational Safty and Health Research Institute,China Academy of Railway Sciences Corporation Limited,Beijing 100081,China)
出处
《铁道建筑》
北大核心
2021年第9期117-120,共4页
Railway Engineering
基金
中国铁路总公司科技研究开发计划(2017G011-E)
中国铁道科学研究院基金(2017YJ109)。
