铁道标准设计2026，Vol.70Issue(8)：43-49,81,8.DOI:10.13238/j.issn.1004-2954.202410220001
重载铁路钢轨磨耗廓形的快速预测与分析
Rapid Prediction and Analysis of Rail Wear Profiles in Heavy-Haul Railways
摘要
Abstract
[Objective]Rail wear is influenced by multiple factors,and changes in rail profile caused by wear significantly affect the safety and smoothness of train operations.Conducting field tests is labor-and resource-intensive,and frequent adjustments to track parameters on operational lines are not feasible.Numerical simulation methods for calculating worn rail profiles are costly and make rapid prediction difficult.Additionally,existing research on wear prediction typically relies on qualitative indicators,lacking the ability to quantitatively analyze the precise distribution of wear.[Methods]To address these gaps in current research,a rapid prediction model for rail wear profiles was developed based on vehicle-track coupled dynamics.Using simulation datasets,the model applied a multi-layer stacking strategy in combination with K-fold cross-validation to predict rail wear profiles and quantitatively analyze wear distribution.This model provided an efficient and cost-effective solution for complex wear problems.[Results]The results of the rapid prediction model showed that,for predicting rail wear on a curve with a radius of 600 m,the mean absolute error was less than 0.03 mm,and the computation speed was approximately 31 times faster than numerical simulations.Under the maximum accumulated gross tonnage condition,the median prediction error ranged between 0.1 and 0.2 mm,achieving rapid prediction of rail wear profiles.Quantitative analysis of wear distribution revealed that the nonlinear characteristics of rail profile evolution were primarily concentrated at the gauge corner.As the running speed increased,the wear distribution range expanded,and the wear peak shifted inward toward the rail head.Increasing the transition curve length significantly reduced both the total wear volume and wear peak,while having minimal impact on the wear distribution range.An increase in the friction coefficient expanded the contact patch area,made the stress distribution more complex,and increased the number of peak positions.[Conclusion]The research methods and results can serve as a reference for similar research.关键词
重载铁路/钢轨磨耗/仿真分析/廓形演变/多层堆栈/快速预测/磨耗分布Key words
heavy-haul railway/rail wear/simulation analysis/profile evolution/multi-layer stacking/rapid prediction/wear distribution分类
交通工程引用本文复制引用
安文杰,王建西,杨雅迪..重载铁路钢轨磨耗廓形的快速预测与分析[J].铁道标准设计,2026,70(8):43-49,81,8.基金项目
国家自然科学基金项目(52378454,72271170) （52378454,72271170）
国家重点研发计划(2021YFB2601001-05) （2021YFB2601001-05）
河北省自然科学基金重点项目(E202510176) （E202510176）
中国国家铁路集团有限公司科技研究开发计划重大项目(K2024G007,K2024G016) （K2024G007,K2024G016）
