基于最优R-Vine Gaussian Copula模型的服役大跨桥梁主梁失效概率分析

Failure Probability Analysis of Service Long-Span Bridge Girder Based on Optimal R-Vine Gaussian Copula Model

摘要:

考虑到服役大跨桥梁主梁多个控制监测点失效模式的相关性，提出失效概率分析的最优regular?vine （R?vine） Gaussian copula信息融合新方法。利用极值应变信息，引入双变量pair?Gaussian?copula模型和最优R?vine模型，结合多个控制监测点的功能函数，进行失效模式相关性的最优R?vine Gaussian copula建模分析；融合一次二阶矩方法，进行失效模式相关的服役大跨桥梁主梁失效概率分析；通过在役桥梁监测数据对所提方法的合理性进行验证，并与其他分析方法进行比较。结果表明，考虑控制监测点失效模式相关性的大跨桥梁主梁失效概率分析的最优R?Vine Gaussian copula信息融合方法更为合理。

Abstract:

Considering the correlation among the failure modes of the multiple control monitoring points from the existing long-span bridge girder， a novel optimal R-vine Gaussian copula data fusion method for failure probability analysis is presented. Based on the extreme strain information， an optimal R-vine Gaussian copula model considering the correlation among the failure modes of the multiple control monitoring points is built by combining the corresponding performance functions， the bivariate pair-Gaussian-copula model and the optimal R-vine model. Further， with the first order second moment method， the failure probability analysis of the existing long-span bridge girder is conducted considering the correlation among the failure modes. The feasibility and application of the method proposed is compared with the other analysis methods based on the monitoring data of the existing bridge. The results show that the optimal R-Vine Gaussian copula information fusion method for the failure probability analysis of long-span bridge girder considering the correlation among failure modes is more reasonable.