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基于ARMAX代理模型的车-桥耦合系统可靠性研究
引用本文:向活跃,陈绪黎,李永乐.基于ARMAX代理模型的车-桥耦合系统可靠性研究[J].西南交通大学学报,2022,57(6):1217-1223, 1232.
作者姓名:向活跃  陈绪黎  李永乐
作者单位:西南交通大学土木工程学院, 四川 成都 610031
基金项目:国家自然科学基金(51978589, 51778544, 51525804)
摘    要:为探究车-桥耦合系统可靠性的效率和精度,建立列车-桥梁的耦合振动模型,并采用自回归方法模拟轨道不平顺. 回顾ARMAX (auto-regressive moving average exogenous)模型的基本原理,提出了基于ARMAX代理模型的车-桥耦合系统可靠性分析框架;利用代理模型获得列车响应预测值,并与直接蒙特卡罗模拟(monte carlo simulation,MCS)法结果进行对比,探讨了代理模型在分析行车安全时的计算精度和可靠性分析效率. 结果表明:代理模型预测列车竖向和横向加速度响应的效率显著高于MCS法,约为3个数量级;预测竖向、横向车体加速度的精度分别为98.66%、86.55%,求解精度较好,可显著提高车-桥耦合系统可靠性分析的效率. 

关 键 词:ARMAX模型    车-桥系统    代理模型    可靠性    动态系统
收稿时间:2020-03-20

Reliability Analysis of Coupled Train-Bridge Systems Based on ARMAX Surrogate Model
XIANG Huoyue,CHEN Xuli,LI Yongle.Reliability Analysis of Coupled Train-Bridge Systems Based on ARMAX Surrogate Model[J].Journal of Southwest Jiaotong University,2022,57(6):1217-1223, 1232.
Authors:XIANG Huoyue  CHEN Xuli  LI Yongle
Institution:School of Civil Engineering, Southwest Jiaotong University, Chengdu 610031, China
Abstract:In order to improve the efficiency of the coupled train-bridge system reliability analysis, a train-bridge coupling vibration model is established, and the track irregularity is simulated by auto-regressive (AR) method. After basic principles of the (auto-regressive moving average exogenous (ARMAX) model are reviewed, the reliability analysis framework of the train-bridge coupling system based on the ARMAX surrogate model is proposed. The acceleration responses predicted by the surrogate model are then compared with those by the direct Monte Carlo method to examine the calculation accuracy and reliability analysis efficiency of the surrogate model in analyzing driving safety. The results show that the efficiency of the surrogate model in predicting the vertical and lateral acceleration responses of trains is significantly higher than that of the MCS method, by about 3 orders of magnitude; besides, acceptable solution accuracy of 98.66% and 86.55% can be achieved for vertical and horizontal car body acceleration prediction, respectively. Therefore, the surrogate model can significantly improve the reliability analysis efficiency of coupled train-bridge systems. 
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