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42号高速道岔转辙器区钢轨磨耗规律的预测分析

王璞

王璞. 42号高速道岔转辙器区钢轨磨耗规律的预测分析[J]. 西南交通大学学报, 2021, 56(2): 289-299. doi: 10.3969/j.issn.0258-2724.20200060
引用本文: 王璞. 42号高速道岔转辙器区钢轨磨耗规律的预测分析[J]. 西南交通大学学报, 2021, 56(2): 289-299. doi: 10.3969/j.issn.0258-2724.20200060
WANG Pu. Prediction Analysis of Rail Wear in Switch Panel for No.42 High-Speed Turnout[J]. Journal of Southwest Jiaotong University, 2021, 56(2): 289-299. doi: 10.3969/j.issn.0258-2724.20200060
Citation: WANG Pu. Prediction Analysis of Rail Wear in Switch Panel for No.42 High-Speed Turnout[J]. Journal of Southwest Jiaotong University, 2021, 56(2): 289-299. doi: 10.3969/j.issn.0258-2724.20200060

42号高速道岔转辙器区钢轨磨耗规律的预测分析

doi: 10.3969/j.issn.0258-2724.20200060
基金项目: 国家自然科学基金(51878661,51808557);中国铁路总公司科技研究开发计划重点课题(N2018G042)
详细信息
    作者简介:

    王璞(1988—),男,副研究员,博士,研究方向为道路与铁道工程,E-mail:wpwp2012@yeah.net

  • 中图分类号: U213.2

Prediction Analysis of Rail Wear in Switch Panel for No.42 High-Speed Turnout

  • 摘要: 为了弥补42号高速道岔钢轨磨耗规律理论研究的不足,建立了高速道岔钢轨磨耗发展的理论预测模型. 基于Archard材料磨损理论和车辆-道岔耦合动力学仿真分析进行钢轨磨耗深度分布计算;采用了一种自适应步长算法对岔区各特征位置钢轨型面进行更新,可有效减少误差累积、改善数值模型稳定性;基于理论预测模型研究了42号高速道岔尖轨和基本轨的磨耗分布和发展规律. 研究的主要结论如下:1) 直向过岔时,轮载过渡发生于35.0~50.0 mm断面之间;在轮载过渡前磨耗发展缓慢加快,轮载过渡区段磨耗发展迅速加剧,轮载过渡完成后磨耗发展有所减缓. 2) 侧向过岔时,列车进岔后很快就开始贴靠曲尖轨运行,9.1 mm断面即出现侧磨;随着曲尖轨逐渐加宽,尖轨轨肩始终存在较严重磨耗,直基本轨虽主要承担轮载,但磨耗相对曲尖轨要小得多;轮载过渡开始后曲尖轨磨耗分布变宽,轨肩磨耗显著减小,至全断面后曲尖轨磨耗再次显著减小;曲基本轨磨耗均主要分布于轨头中部,轮载过渡前磨耗发展逐渐加快,过渡开始后磨耗发展减缓.

     

  • 图 1  高速道岔动力学模型

    Figure 1.  Dynamic model of high-speed turnouts

    图 2  轮轨接触斑磨耗深度分布计算模型

    Figure 2.  Calculation model of wear distribution in wheel-rail contact patch

    图 3  道岔区钢轨型面磨耗叠加示意

    Figure 3.  Diagram of superposition of rail profile wear in turnout

    图 4  钢轨磨耗速率示意

    Figure 4.  Diagram of rail wear rate

    直向过岔钢轨磨耗发展过程

    Rail wear development of train passing through turnout in main direction

    侧向过岔钢轨磨耗发展过程

    Rail wear development of train passing through turnout in branch direction

  • 王树国, 王平, 肖俊恒, 等. 高速铁路道岔区段轮轨关系深化研究报告[R]. 北京: 中国铁道科学研究院, 2016.
    王平,陈嵘,徐井芒,等. 高速铁路道岔系统理论与工程实践研究综述[J]. 西南交通大学学报,2016,51(2): 357-372. doi: 10.3969/j.issn.0258-2724.2016.02.015

    WANG Ping, CHEN Rong, XU Jingmang, et al. Theories and engineering practices of high-speed railway turnout system:survey and review[J]. Journal of Southwest Jiaotong University, 2016, 51(2): 357-372. doi: 10.3969/j.issn.0258-2724.2016.02.015
    王树国, 张玉林, 方杭玮, 等. 高速铁路道岔设计技术[R]. 北京: 中国铁道科学研究院, 2009.
    张东风. 时速350 km客运专线铁路60 kg/m钢轨42号单开道岔结构设计[J]. 铁道标准设计,2009(5): 6-9. doi: 10.3969/j.issn.1004-2954.2009.05.003

    ZHANG Dongfeng. Design on No.42 single slit turnout structure on 60 kg/m steel rail of passenger dedicated lines with a speed of 350 km/h[J]. Railway Standard Design, 2009(5): 6-9. doi: 10.3969/j.issn.1004-2954.2009.05.003
    JENDEL T. Prediction of wheel profile wear-comparisons with field measurements[J]. Wear, 2002, 253(1/2): 89-99.
    IGNESTI M, INNOCENTI A, MARINI L, et al. Development of a model for the simultaneous analysis of wheel and rail wear in railway systems[J]. Multibody System Dynamics, 2014, 31(2): 191-240. doi: 10.1007/s11044-013-9360-0
    许玉德,魏恺,孙小辉,等. 钢轨磨耗预测模型及其算法的优化[J]. 中国铁道科学,2016,37(4): 48-53. doi: 10.3969/j.issn.1001-4632.2016.04.08

    XU Yude, WEI Kai, SUN Xiaohui, et al. Prediction model and algorithm optimization for rail wear[J]. China Railway Science, 2016, 37(4): 48-53. doi: 10.3969/j.issn.1001-4632.2016.04.08
    APEZETXEA I S, PEREZ X, CASANUEVA C, et al. New methodology for fast prediction of wheel wear evolution[J]. Vehicle System Dynamics, 2017, 55(7): 1071-1097. doi: 10.1080/00423114.2017.1299870
    孙宇,翟婉明. 钢轨磨耗演变预测模型研究[J]. 铁道学报,2017,39(8): 1-9. doi: 10.3969/j.issn.1001-8360.2017.08.001

    SUN Yu, ZHAI Wanming. A prediction model for rail wear evolution[J]. Journal of the China Railway Society, 2017, 39(8): 1-9. doi: 10.3969/j.issn.1001-8360.2017.08.001
    LUO R, SHI H, TENG W, et al. Prediction of wheel profile wear and vehicle dynamics evolution considering stochastic parameters for high-speed train[J]. Wear, 2017, 392/393: 126-138.
    XU J M, WANG P, WANG J, et al. Numerical analysis of the effect of track parameters on turnout rails wear for high-speed railways[J]. Proceedings of the Institution of Mechanical Engineers,Part F:Journal of Rail and Rapid Transit, 2018, 232(3): 709-721. doi: 10.1177/0954409716685188
    HAN P, ZHANG W H. A new binary wheel wear prediction model based on statistical method and the demonstration. Wear, 2015, 324/325: 90-99.
    徐凯,李芾,安琪,等. 高速动车组车轮踏面磨耗特征分析[J]. 西南交通大学学报,2021,56(1): 92-100. doi: 10.3969/j.issn.0258-2724.20190266

    XU Kai, LI Fu, AN Qi, et al. Wheel tread wear characteristics of high-speed electric multi-units[J]. Journal of Southwest Jiaotong University, 2021, 56(1): 92-100. doi: 10.3969/j.issn.0258-2724.20190266
    HERTZ H. Über die berührung fester elastische Körper[J]. Journal für die Reine und Angewandte Mathematik, 1882, 92: 156-171.
    KALKER J J. A fast algorithm for the simplified theory of rolling contact[J]. Vehicle System Dynamics, 1982, 11(1): 1-13. doi: 10.1080/00423118208968684
    ARCHARD J F. Contact and rubbing of flat surfaces[J]. Journal of Applied Physics, 1953(24): 981-988.
    中铁宝桥集团有限公司. 铁路道岔参数手册[M]. 北京: 中国铁道出版社, 2009.
    胡晓依, 侯茂锐, 孙加林, 等. 车辆-轨道耦合动力学仿真模型验证方案[R]. 北京: 中国铁道科学研究院, 2016.
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出版历程
  • 收稿日期:  2020-02-29
  • 修回日期:  2020-04-19
  • 网络出版日期:  2020-05-18
  • 刊出日期:  2021-04-15

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