Data Fusion about Serviceability Reliability Prediction for the Long-Span Bridge Girder Based on MBDLM and Gaussian Copula Technique  

作　　者：Xueping Fan Guanghong Yang Zhipeng Shang Xiaoxiong Zhao Yuefei Liu 

机构地区：[1]School of Civil Engineering and Mechanics,Lanzhou University,Lanzhou,730000,China

出　　处：《Structural Durability & Health Monitoring》2021年第1期69-83,共15页结构耐久性与健康监测（英文）

基　　金：This work was supported by Natural Science Foundation of Gansu Province of China(20JR10RA625,20JR10RA623);National Key Research and Development Project of China(Project No.2019YFC1511005);Fundamental Research Funds for the Central Universities(Grant No.lzujbky-2020-55);National Natural Science Foundation of China(Grant No.51608243).

摘　　要：This article presented a new data fusion approach for reasonably predicting dynamic serviceability reliability of the long-span bridge girder.Firstly,multivariate Bayesian dynamic linear model(MBDLM)considering dynamic correlation among the multiple variables is provided to predict dynamic extreme deflections;secondly,with the proposed MBDLM,the dynamic correlation coefficients between any two performance functions can be predicted;finally,based on MBDLM and Gaussian copula technique,a new data fusion method is given to predict the serviceability reliability of the long-span bridge girder,and the monitoring extreme deflection data from an actual bridge is provided to illustrated the feasibility and application of the proposed method.

关 键 词：Dynamic extreme deflection data serviceability reliability prediction structural health monitoring multivariate Bayesian dynamic linear models Gaussian copula technique 

分 类 号：U21[交通运输工程—道路与铁道工程]