基于车致振动响应的无缝线路温度力识别研究  

Research on Temperature Force Identification of CWR Track Based on Vehicle-Induced Vibration Response

作　　者：马超[1,2] 安子旭 张晓东 Ma Chao;An Zixu;Zhang Xiaodong(Key Laboratory of Roads and Railway Engineering Safety Control of Ministry of Education,Shijiazhuang Tiedao University,Shijiazhuang 050043,China;School of Civil Engineering,Shijiazhuang Tiedao University,Shijiazhuang 050043,China)

机构地区：[1]石家庄铁道大学道路与铁道工程安全保障省部共建教育部重点实验室,河北石家庄050043 [2]石家庄铁道大学土木工程学院,河北石家庄050043

出　　处：《石家庄铁道大学学报（自然科学版）》2023年第1期99-105,共7页Journal of Shijiazhuang Tiedao University(Natural Science Edition)

基　　金：国能新朔铁路有限责任公司科技创新项目(SHXS-2020-06)。

摘　　要：无缝线路温度力过大会导致胀轨或断轨,现场需实时监测钢轨温度力。以钢轨在温度力作用下受到的车致振动加速度为研究对象,提出一种利用多元回归算法拟合温度力特征指标反向识别钢轨温度力的新方法。通过对温度力作用下车致钢轨振动加速度进行希尔伯特黄变换,提取钢轨加速度的HHT灰度时频直方图方差和边际谱在1300~1500 Hz内的瞬时幅值变化率作为温度力特征指标,将2指标分别输入到回归算法和灰色算法中,对比钢轨温度力识别误差。结果表明,钢轨所受温度力越大,识别结果的相对误差越小;利用多元回归算法识别温度力的平均识别误差可达到3.24%,相比于灰色预测模型降低了3.54%,为现场实时监测钢轨温度力提供借鉴。Excessive temperature force of CWR(Continuously Welded Rail)will lead to rail expansion or broken rail.So real-time monitoring of rail temperature force is needed on site.The acceleration of rail vibration caused by moving vehicle under the action of temperature force was taken as the research object,and a new method for reverse identification of rail temperature force was proposed by fitting the characteristic indicators of temperature force with multiple regression algorithm.Through Hilbert-Huang Transform of the rail vibration acceleration signal caused by moving vehicle under the temperature force,the variance of HHT time-frequency gray histogram and the instantaneous amplitude rate of marginal spectrum in 1300~1500 Hz were obtained to serve as the characteristic indices of temperature force.Then,the two indicators were input to compare the rail temperature force identification error through the regression model and gray model.The results show that the greater the temperature force on the rail,the smaller the relative error of the identification results.The average identification error of temperature force identified by the multiple regression algorithm is 3.24%,which is 3.54%lower than that of the gray prediction model.The results might provide reference for real-time monitoring of rail temperature force on site.

关 键 词：无缝线路 温度力 车致振动 希尔伯特黄变换 回归分析 

分 类 号：U216[交通运输工程—道路与铁道工程] U213.9