无先验信息情况下基于解耦极值荷载效应的桥梁时变可靠性分析  

Time-Dependent Reliability Analysis of Bridges Based on Decoupled Extreme Load Effects and No-Prior Distribution Information

作　　者：刘月飞[1,2] 肖青凯 屈广 樊学平[1,2] LIU Yuefei;XIAO Qingkai;QU Guang;FAN Xueping(Key Laboratory of Mechanics on Disaster and Environment in Western China of the Ministry of Education, Lanzhou University,Lanzhou 730000,Gansu,P.R.China;School of Civil Engineering and Mechanics, Lanzhou University,Lanzhou 730000,Gansu,P.R.China)

机构地区：[1]兰州大学西部灾害与环境力学教育部重点实验室,甘肃兰州730000 [2]兰州大学土木工程与力学学院,甘肃兰州730000

出　　处：《重庆交通大学学报（自然科学版）》2018年第9期1-6,65,共7页Journal of Chongqing Jiaotong University(Natural Science)

基　　金：国家自然科学基金项目(51608243);甘肃省自然科学基金项目(1606RJYA246);中央高校基本科研业务费专项资金项目(lzujbky-2015-300;lzujbky-2015-301)

摘　　要：在役桥梁健康监测系统在长期运营中积累了大量数据,如何有效处理这些数据来预测结构的可靠性是结构健康监测(SHM)领域的一个关键问题。鉴于SHM极值应力信号的耦合性和随机性,首先采用一次移动平均法解耦极值应力耦合信号;然后,针对解耦数据的分布特性,建立观测误差方差未知的贝叶斯动态线性模型(BDLM),预测解耦极值应力;最后,结合一次二阶矩(FOSM)可靠度方法进行桥梁构件的时变可靠性分析。研究成果将为结构的可靠性预测提供理论基础。Bridge health monitoring system has produced a huge amount of data in long-term service periods,and how to reasonably deal with these data to predict the structural reliability is a key issue in the field of structural health monitoring(SHM).Considering the coupling and randomness of SHM extreme stress data,firstly,the coupled extreme stress signal was decoupled with single moving average method.Then,considering the distribution characteristics of decoupled data,Bayesian dynamic linear models(BDLM)with unknown variance of observation error were established to predict the decoupled extreme stress.Finally,the time-dependent reliability of bridge members was analyzed with first-order second moment(FOSM)reliability method.The research results will provide the theoretical basis for structural reliability prediction.

关 键 词：桥梁工程 健康监测 耦合性 无信息先验分布 贝叶斯动态模型 可靠度分析 

分 类 号：TU391[建筑科学—结构工程] TU392.5