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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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作者 Xueping Fan Guanghong Yang +2 位作者 Zhipeng Shang Xiaoxiong Zhao Yuefei Liu 《Structural Durability & Health Monitoring》 EI 2021年第1期69-83,共15页
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 dynami... 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. 展开更多
关键词 dynamic extreme deflection data serviceability reliability prediction structural health monitoring multivariate Bayesian dynamic linear models Gaussian copula technique
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