腐蚀作用下城市轨道车辆齿轮磨损可靠性研究  

Reliability Analysis of Urban Rail Vehicle Gear Wear Considering Corrosion

作　　者：徐向阳[1] 陈庆科 王晗 任梓源 XU Xiangyang;CHEN Qingke;WANG Han;REN Ziyuan(School of Mechatronics and Vehicle Engineering,Chongqing Jiaotong University,Chongqing 400074,China)

机构地区：[1]重庆交通大学机电与车辆工程学院,重庆400074

出　　处：《重庆交通大学学报（自然科学版）》2024年第2期107-114,共8页Journal of Chongqing Jiaotong University(Natural Science)

基　　金：重庆市自然科学基金杰出青年基金项目(cstc2021jcyj-jqX0010);重庆市教委科学技术研究项目重点项目(KJZD-K202000703)。

摘　　要：为解决城市轨道车辆齿轮在腐蚀性环境下的磨损可靠性预测问题,采用非齐次泊松过程和对数高斯分布表征齿面腐蚀坑的萌生和生长,并考虑磨损对腐蚀坑深度的改变,通过分析腐蚀坑对赫兹接触应力、齿面粗糙度的影响,基于Archard磨损理论,以齿面最大累积磨损深度为关键参数建立性能裕量退化模型,构建出一种腐蚀作用下的城市轨道车辆齿轮磨损可靠性分析模型,并对腐蚀过程涉及的参数进行可靠性灵敏度分析。结果表明:随着工作时间的增长,齿轮累积磨损量的不确定性增加,腐蚀对齿轮磨损可靠性的影响程度降低;腐蚀坑生长过程的比例参数、形状参数和最大腐蚀深度对可靠性的灵敏度依次增加,且均与齿轮磨损可靠寿命呈负相关关系。In order to solve the problem of wear reliability prediction of gears in urban rail vehicles in corrosive environment,the nonhomogeneous Poisson process and the logarithmic Gaussian distribution were adopted to characterize the initiation and growth of corrosion pits on the tooth face.And then,considering the change of the wear and tear on the depth of corrosion pit,the maximum cumulative wear depth was taken as key parameter to establish the performance margin degradation model based on Archard wear theory,by analyzing the influence of corrosion pit on the Hertz contact stress and the tooth surface roughness.A reliability analysis model of gear wear of urban rail vehicles considering corrosion was constructed,and the reliability sensitivity analysis of parameters involved in corrosion process was also carried out.The results show that with the increase of working time,the uncertainty of cumulative gear wear increases,and the influence of corrosion on gear wear reliability decreases.The sensitivity of the proportion parameter,shape parameter and maximum corrosion depth in the corrosion pit growth process to the reliability increases in turn,and all of them are negatively correlated with the reliable life of gear wear.

关 键 词：车辆工程 可靠性 齿面磨损 腐蚀 性能裕量 

分 类 号：TB114.3[理学—概率论与数理统计]