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

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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.
出处 《Structural Durability & Health Monitoring》 EI 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).
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