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Dynamic reliability prediction of bridge member based on Bayesian dynamic nonlinear model and monitored data:

机译:基于贝叶斯动态非线性模型和监测数据的桥梁构件动态可靠性预测:

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Bridge monitoring systems provide a huge number of stress data used for reliability prediction. In this article, the dynamic measure of structural stress over time is considered as a time series, and considering the limitation of the existing Bayesian dynamic linear models only applied for short-term performance prediction, Bayesian dynamic nonlinear models are introduced. With the monitored stress data, the quadratic function is used to build the Bayesian dynamic nonlinear model. And two methods are proposed to handle with the built Bayesian dynamic nonlinear model and the corresponding probability recursion processes. One method is to transform the built Bayesian dynamic nonlinear model into Bayesian dynamic linear model with Taylor series expansion technique; then the corresponding probability recursion processes are completed based on the transformed Bayesian dynamic linear model. The other one is to directly handle with the built Bayesian dynamic nonlinear model and the corresponding probability recu...
机译:桥梁监控系统提供了大量用于可靠性预测的应力数据。本文将结构应力随时间的动态度量视为一个时间序列,并考虑到仅适用于短期性能预测的现有贝叶斯动态线性模型的局限性,介绍了贝叶斯动态非线性模型。利用监测到的应力数据,使用二次函数来构建贝叶斯动态非线性模型。提出了两种方法来处理建立的贝叶斯动态非线性模型和相应的概率递归过程。一种方法是采用泰勒级数展开技术将建立的贝叶斯动态非线性模型转换为贝叶斯动态线性模型。然后根据变换后的贝叶斯动态线性模型完成相应的概率递归过程。另一种是直接处理建立的贝叶斯动态非线性模型和相应的概率估计。

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