城市轨道交通剪切型减振扣件区段钢轨波磨测试与预测  

Testing and Prediction of Rail Corrugation in Sections with Egg Fastener in Urban Rail Transit

作　　者：高斯 廖英英 张厚贵 任州 GAO Si;LIAO Yingying;ZHANG Hougui;REN Zhou(School of Civil Engineering,Shijiazhuang Tiedao University,Shijiazhuang 050043,China;Institute of Urban Safety and Environmental Science,Beijing Academy of Science and Technology,Beijing 100054,China;Beijing OWP Rail Transit Technology Co.Ltd.,Beijing 100071,China)

机构地区：[1]石家庄铁道大学土木工程学院,河北石家庄050043 [2]北京市科学技术研究院城市安全与环境科学研究所,北京100054 [3]北京东方维平轨道交通科技有限公司,北京100071

出　　处：《石家庄铁道大学学报（自然科学版）》2024年第2期80-85,共6页Journal of Shijiazhuang Tiedao University(Natural Science Edition)

基　　金：国家自然科学基金(12172235,12072208,52072249)。

摘　　要：城市轨道交通运营过程中会出现钢轨波磨,在剪切型减振扣件区段较为严重。为了预测剪切型减振扣件区段钢轨波磨的发展,对某地铁线进行了为期16个月的跟踪测试,并分析了钢轨波磨的1/3倍频程谱、移动波深幅值峰-峰平均值(PPR)及发展规律。测试结果表明,PPR在波磨的发展上具有良好的可重复性,可用于预测钢轨波磨的发展趋势。然而由于波磨形成的机理复杂,基于传统力学机理特征很难得到普适性的预测方法。基于机器学习的理论,提出了一种改进多项式扩展线性回归模型的钢轨磨耗预测方法。结果表明,所提出的预测方法在移动峰-峰值平均值(PPR)预测方面的均方根误差为4.246μm,超限率误差为5.42%。改进的多项式扩展线性回归模型在钢轨波磨预测中具有较高的准确性和预测能力。In the operation of urban rail transit,rail corrugation occurs,which is particularly severe in sections with egg fastener.To predict the development of rail corrugation in shear-type fastener sections,a 16-month tracking test was conducted on a certain subway line,and the third-octave frequency spectrum of rail corrugation,the peak-to-peak moving average value of wave depth(PPR),and its development pattern were analyzed.The test results indicate that PPR has good repeatability in the development pattern of corrugation and can be used to predict the trend of rail corrugation development.However,due to the complex mechanisms behind corrugation formation,it is difficult to obtain a universal prediction method based on traditional mechanical mechanism characteristics.Based on the theory of machine learning,a rail wear prediction method using an improved polynomial expansion linear regression model is proposed.The results of the study show that the proposed prediction method has a root mean square error of 4.246μm in predicting the moving peak-to-peak value average(PPR)and an over-limit rate error of 5.42%,indicating that the improved polynomial expansion linear regression model has high accuracy and predictive capability in rail corrugation forecasting.

关 键 词：城市轨道交通 钢轨波磨 剪切型扣件 预测 

分 类 号：U231[交通运输工程—道路与铁道工程]