• CN:11-2187/TH
  • ISSN:0577-6686

机械工程学报 ›› 2016, Vol. 52 ›› Issue (2): 144-149.doi: 10.3901/JME.2016.02.144

• 运载工程 • 上一篇    下一篇

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高速列车轮对磨耗统计规律及预测模型

韩鹏,  张卫华   

  1. 西南交通大学牵引动力国家重点实验室  成都  610031
  • 收稿日期:2015-08-06 修回日期:2015-12-14 出版日期:2016-01-15 发布日期:2016-01-15
  • 通讯作者: 张卫华,男,1961年出生,博士,教授,博士研究生导师。主要研究方向为高速列车耦合大系统动力学,其中包括高速列车车辆设计、动力学、强度可靠性以及试验研究等。 E-mail:tpl@swjtu.edu.cn
  • 作者简介:韩鹏,男,1991年出生,博士研究生。主要研究方向为车辆系统动力学。 E-mail:tpl_hp@163.com
  • 基金资助:
    国家自然科学基金委员会-铁道部高速铁路基础研究联合基金(U1234208)和中国铁路总公司科技研究开发计划重大课题(2013J008-A)资助项目

Prediction Model and Verification of Wheel Wear in High-speed Trains

HAN Peng,  ZHANG Weihua   

  1. State Key Laboratory of Traction Power, Southwest Jiaotong University, Chengdu 610031
  • Received:2015-08-06 Revised:2015-12-14 Online:2016-01-15 Published:2016-01-15

摘要: 为研究我国高速列车轮对踏面磨耗规律,对某线路服役高速动车组进行跟踪测试,记录其镟轮周期内的踏面磨耗量,并基于对磨耗统计特征的两次拟合提出轮对型面磨耗预测函数模型。对某高速线路实测型面磨耗量进行拟合,分别得到各走行里程下磨耗量关于型面位置的拟合函数;并进一步对各走行里程下的拟合函数系数进行二次拟合,得到磨耗量关于型面位置及走行里程的二元预测函数。在模型的预测精度与适用性验证时,对比相同走行里程下预测型面和实测型面在轮轨接触几何关系与车辆各关键部件加速度响应两方面结果。对比结果显示,提出的磨耗预测模型在轮轨接触点、等效锥度、轮轨作用力及车辆安全性等各方面均与线路实测结果具有很好的一致性。

关键词: 车辆动力学, 高速列车, 轮对磨耗, 轮对型面测量, 磨耗特征统计, 磨耗预测

Abstract: Wheel-tracking measurement is carried on to survey the wear law of wheel profiles of the high-speed trains in China. Numerical prediction function of wheel wear model is proposed according to a large number of these measured data in this article. Abrasion losses are fitting to get the polynomial fitting function on different locations of wheel profiles at fixed operation mileage. And further, the second fitting is conducted to predict the coefficients of the above polynomial function. The binary numerical prediction model is raised to predict the abrasion losses as a function of wear location and operation mileage. The applicable and the accuracy of the prediction model are proved by the comparison of the tested wear profile curves and the predicted ones. Vehicle system dynamics models are also established to compare wheel/rail contact points, equivalent conicity, wheel/rail contact forces and the safety of vehicle which are calculated with the tested and the predicted wear profiles respectively. The results show that the predicted profiles calculated by the proposed numerical prediction function have a great agreement with tested profiles both in the curve shapes and vehicle system dynamic performances.

Key words: high-speed trains, statistic characteristics of wheel wear, vehicle system dynamics, wear prediction, wheel profile measurement, wheel wear

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