• CN:11-2187/TH
  • ISSN:0577-6686

机械工程学报 ›› 2019, Vol. 55 ›› Issue (4): 42-53.doi: 10.3901/JME.2019.04.042

• 材料科学与技术 • 上一篇    下一篇

样本信息聚集原理改进及其在铁路车辆结构疲劳评定中的应用

李存海, 吴圣川, 刘宇轩   

  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:2018-05-16 修回日期:2018-10-12 出版日期:2019-02-20 发布日期:2019-02-20
  • 通讯作者: 吴圣川(通信作者),男,1979年出生,博士后,研究员,博士研究生导师。主要研究方向大型工程结构抗疲劳断裂设计、疲劳断裂仿真软件研发及基于同步辐射三维X射线的材料疲劳损伤表征。E-mail:wusc@swjtu.edu.cn
  • 作者简介:李存海,男,1993年出生,博士研究生。主要研究方向为车辆结构抗疲劳断裂设计及寿命评价。E-mail:lch9308@163.com
  • 基金资助:
    国家自然科学基金(11572267)、四川省科技计划(2017JY0216)和西南交通大学牵引动力国家重点实验室开放课题(2018TPL_T03)资助项目

Improved Sample Polymerization Principle and the Applications onto Fatigue Assessment of Railway Vehicle Structures

LI Cunhai, WU Shengchuan, LIU Yuxuan   

  1. State Key Laboratory of Traction Power, Southwest Jiaotong University, Chengdu 610031
  • Received:2018-05-16 Revised:2018-10-12 Online:2019-02-20 Published:2019-02-20

摘要: 疲劳S-N曲线是高速动车组结构设计中最重要的基础数据。降低样本数据的离散性和提高寿命预测的准确性一直是铁路车辆结构长寿命安全可靠服役的热点研究课题,经典的样本信息聚集原理(Sample polymerization principle,SPP)能够确保小样本疲劳数据统计处理的准确性,但在寿命估算的可靠性上还有改进空间。通过参数搜索的优化建立应力与标准差之间的关系,实现不同应力水平下标准差的最优取值,从而提出一种新的基于SPP的概率疲劳S-N曲线拟合方法。研究结果表明,与成组法相比,基于(X-x-x-x)型数据的疲劳P-S-N曲线的斜率和截距的相对误差小于3%,估算寿命仅为成组法5%;在处理(x-x-x-x)型数据时,估算寿命约为传统方法的0.1%。在应用于高速列车焊接结构时,改进方法充分考虑了因焊接缺陷引入的离散性,预测的疲劳寿命更加可靠与合理。由此可见,改进的SPP以及标准差参数寻优技术不仅可以确保小样本数据的拟合精度,而且能够获得更加可靠的疲劳P-S-N曲线,工程应用中得到更保守的预测结果。

关键词: P-S-N曲线, 疲劳寿命, 铁路车辆, 小样本, 样本集聚

Abstract: Fatigue S-N curves are the most fundamental material input to design the lightweight structures and assess the service safety of high-speed railway vehicles. How to reduce the dispersion of fatigue life data and to improve the prediction precision of fatigue performance are frequently the principal attention on long life service of railway vehicle structures. Classical sample polymerization principle (SPP) can effectively solve the small size sample, while the accuracy of fatigue life is still of primary concern. An improved SPP (iSPP) to build the fatigue probabilistic S-N (P-S-N) curve is therefore proposed to pursue an optimized search parameter related with the standard deviation (SD), thus obtaining the optimal life SD under different stress levels. Results show the slope and intercept of newly-built P-S-N curves from (X-x-x-x) type life data have the relative error less than 3%, and predicted fatigue life is approximately 5% of the group method (TGM) estimation in contrast with the TGM. Moreover, the predicted fatigue life is only 0.1% of traditional fitted method for (x-x-x-x) type life data. For the welded joints with defect induced dispersion, iSPP can achieve more conservative and reliable life predictions.It shows the iSPP and optimal parameter search method can not only ensure the accuracy of small sample but also acquire a more conservative P-S-N curve into engineering applications.

Key words: P-S-N curve, fatigue life, railway vehicles, sample congregation, small size sample

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