基于Tγ/A-磨损率模型的U75V钢轨磨损预测研究

doi:10.3901/JME.2025.21.345

机械工程学报 ›› 2025, Vol. 61 ›› Issue (21): 345-354.doi: 10.3901/JME.2025.21.345

• 特邀专栏：纪念张启先院士诞辰 100 周年 • 上一篇

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基于Tγ/A-磨损率模型的U75V钢轨磨损预测研究

苏家宝¹, 郭立昌¹, 丁昊昊¹, 安博洋², 徐井芒², 刘启跃¹, 王文健¹

1. 西南交通大学轨道交通运载系统全国重点实验室成都 610031;
2. 西南交通大学高速铁路线路工程教育部重点实验室成都 610031

收稿日期:2024-11-19 修回日期:2025-05-19 发布日期:2025-12-27
作者简介:苏家宝，男，1998年出生，博士研究生。主要研究方向为轮轨关系与服役行为。E-mail：sjb6116@163.com
王文健(通信作者)，男，1980年出生，博士，研究员，博士研究生导师。主要研究方向为轨道交通轮轨摩擦学。E-mail：wwj527@swjtu.edu.cn
基金资助:
国家自然科学基金(52202510，52375205)、轨道交通运载系统全国重点实验室自主研究课题(2024RVL-T02)和中央高校基本科研业务费专项资金(2682024CG007)资助项目。

Prediction of U75V Rail Wear Based on the Model of Tγ/A-wear Rate

SU Jiabao¹, GUO Lichang¹, DING Haohao¹, AN Boyang², XU Jingmang², LIU Qiyue¹, WANG Wenjian¹

1. State Key Laboratory of Rail Transit Vehicle System, Southwest Jiaotong University, Chengdu 610031;
2. Key Laboratory of High-speed Railway Engineering of Ministry of Education, Southwest Jiaotong University, Chengdu 610031

Received:2024-11-19 Revised:2025-05-19 Published:2025-12-27

摘要/Abstract

摘要： 随着货运列车运量和运行速度的提升，钢轨磨损加剧，降低了服役寿命并增加运营成本。研究建立了U75V钢轨材料Tγ/A-磨损率模型，结合动力学仿真与数值计算方法建立了钢轨磨损预测模型。利用预测模型对现场服役钢轨的磨损规律进行预测，基于预测模型对影响钢轨磨损的关键因素(轴重、蠕滑)进行分析。结果表明：所建立的U75V钢轨Tγ/A-磨损率模型可划分为三个不同磨损区域，仿真得到的钢轨磨损规律与现场实测结果基本一致，验证了该预测模型的合理性。轴重和蠕滑均与U75V钢轨的磨损深度呈正相关；轴重增加导致蠕滑减小，在轨顶接触区域，蠕滑对钢轨磨损影响较大；在轨侧接触区域，轴重对钢轨磨损影响较大。上述结果表明基于Tγ/A-磨损率模型的钢轨预测方法能够为现场钢轨磨损演化规律与减磨措施优化提供技术指导。

关键词: 磨损预测模型, U75V钢轨, Tγ/A-磨损率, 重载铁路, 磨损关键因素

Abstract: With the increase of freight train volume and running speed, rail wear is aggravated, which reduces its service life and increases operating costs. In this paper, the U75V rail material Tγ/A-wear rate model is established, and the rail wear prediction model is established by combining dynamic simulation and numerical calculation methods. The prediction model is used to predict the wear law of rail in field service, and the key factors affecting rail wear (axle load, creep) are analyzed based on the prediction model. The results show that the U75V rail Tγ/A-wear rate model can be divided into three different wear areas, and the rail wear law obtained by simulation is basically consistent with the field measured results, which verifies the rationality of the prediction model. Axle load and creep are positively correlated with rail wear depth of U75V rail. The increase of axle load results in the decrease of creep, and the influence of creep on rail wear is great in the contact area of rail top. In the rail side contact area, axle load has great influence on rail wear. The above results show that the rail prediction method based on Tγ/A-wear rate model can provide technical guidance for the evolution of rail wear and the optimization of wear reduction measures.

Key words: wear prediction model, U75V rail, Tγ/A-wear rate, heavy haul railway, key factor of rail wear

中图分类号:

TH117

苏家宝, 郭立昌, 丁昊昊, 安博洋, 徐井芒, 刘启跃, 王文健. 基于Tγ/A-磨损率模型的U75V钢轨磨损预测研究[J]. 机械工程学报, 2025, 61(21): 345-354.

SU Jiabao, GUO Lichang, DING Haohao, AN Boyang, XU Jingmang, LIU Qiyue, WANG Wenjian. Prediction of U75V Rail Wear Based on the Model of Tγ/A-wear Rate[J]. Journal of Mechanical Engineering, 2025, 61(21): 345-354.

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基于Tγ/A-磨损率模型的U75V钢轨磨损预测研究

Prediction of U75V Rail Wear Based on the Model of Tγ/A-wear Rate

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