1.兰州交通大学 研究院,兰州 730070
2.兰州交通大学 机电技术研究所,兰州 730070
3.湘西民族职业技术学院,湘西 416000
4.中车兰州机车有限公司,兰州 730070
5.中国铁路兰州局集团有限公司 机务部,兰州 730030
QI Jinping, E-mail: qijinping@lzjtu.cn
收稿:2024-03-05,
修回:2024-05-16,
纸质出版:2025-11-15
移动端阅览
齐金平,冯洪,刘晓宇,等. 考虑随机变阈值的车轮相依竞争失效可靠性建模[J]. 机械强度,2025,47(11):150-158.
QI Jinping,FENG Hong,LIU Xiaoyu,et al. Reliability modeling of the wheel dependent competing failures considering random variable thresholds[J]. Journal of Mechanical Strength,2025,47(11):150-158.
齐金平,冯洪,刘晓宇,等. 考虑随机变阈值的车轮相依竞争失效可靠性建模[J]. 机械强度,2025,47(11):150-158. DOI: 10.16579/j.issn.1001.9669.2025.11.018.
QI Jinping,FENG Hong,LIU Xiaoyu,et al. Reliability modeling of the wheel dependent competing failures considering random variable thresholds[J]. Journal of Mechanical Strength,2025,47(11):150-158. DOI: 10.16579/j.issn.1001.9669.2025.11.018.
由于车轮在正常运行中受磨损、冲击等多种因素的耦合作用会产生退化现象,而当前研究则是多考虑单一因素影响,并认为车轮失效的阈值为定值,因而无法准确反映车轮退化规律,为此提出一种考虑变阈值的相依竞争失效模型,分别采用非平稳Gamma过程和极端冲击描述车轮的自然退化和冲击过程,认为冲击导致的自然退化增量与冲击幅值具有相依性;令冲击失效阈值服从正态分布,表征自然退化对冲击失效阈值的随机性影响。基于某型动车组的车轮轮缘实测磨耗数据进行实例计算,并通过蒙特卡洛仿真方法进行对比研究,验证了所提建模方法的可行性和有效性,为车轮维修周期优化提供科学参考。
Wheels degraded during normal operation due to the coupling effect of multiple factors such as wear and impact. However
most existing studies only considered the influence of a single factor and regarded the failure threshold as a fixed value
thus failing to accurately reflect the wheel degradation law.For this reason
a dependent competing failure model considering variable thresholds was proposed. The non-stationary Gamma process and extreme shocks were used to describe the natural degradation and shock process of wheels
respectively. It was assumed that the natural degradation increment caused by shocks was dependent on the shock amplitude. The shock failure threshold was set to follow a normal distribution
so as to characterize the random influence of natural degradation on the shock failure threshold. Case calculations were conducted based on the measured wear data of the wheel flange of a certain EMU
and a comparative study is carried out using the Monte Carlo simulation method. The results verify the feasibility and effectiveness of the proposed modeling method
which can provide a reference for the optimization of wheel maintenance cycles.
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