考虑参数更新的大跨桥梁温差极值分布估计方法研究

张欢; 周广东; 吴二军

doi:10.6052/j.issn.1000-4750.2015.08.0717

考虑参数更新的大跨桥梁温差极值分布估计方法研究

河海大学土木与交通学院, 江苏, 南京 210098

基金项目: 国家自然科学基金项目（51678218）；中国博士后科学基金项目（2014M560387）

详细信息

作者简介:
张欢(1992-),女,江苏人,硕士生,主要从事结构健康监测研究(E-mail:zhhuan1214@163.com);吴二军(1972-),男,河北人,副教授,博士,主要从事工程结构平移、加固改造与监测研究(E-mail:wej@hhu.edu.cn).

通讯作者:
周广东(1982-),男,四川人,副教授,博士,主要从事结构健康监测研究(E-mail:zhougd@hhu.edu.cn).

中图分类号: U442
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出版历程
- 收稿日期: 2015-08-30
- 修回日期: 2016-01-13
- 刊出日期: 2017-03-24

STATISTICAL MODEL ESTIMATION OF EXTREME THERMAL GRADIENTS IN LONG-SPAN BRIDGES COMBINING PARAMETER UPDATING

College of Civil and Transportation Engineering, Hohai University, Nanjing, Jiangsu 210098, China

摘要

摘要: 为了建立可靠的大跨桥梁全寿命温差极值分布模型，提出采用广义帕累托分布（Generalized Pareto Distribution，GPD）对超阈值温差的统计特征进行描述，并给出了超阈值温差样本相关性的去除方法和最优阈值的确定方法。为了融合温差分布的先期经验信息和不断递增的温差监测样本，建立了考虑参数更新的贝叶斯估计方法，利用Gibbs抽样对贝叶斯后验分布进行计算，进而得到准确的基于广义帕累托分布的温差极值分布模型。最后利用九堡大桥长期监测温差数据进行了验证。研究结果表明，广义帕累托分布能够对超阈值温差样本的尾部统计特征进行准确描述，提出的考虑参数更新的温差极值分布贝叶斯估计方法能够对广义帕累托分布的参数进行可靠估计，估计的统计模型比极大似然估计计算的结果更接近真实情况。研究结果可为大跨桥梁温差特性分析提供参考。
- 桥梁工程 /
- 结构健康监测 /
- 温差极值 /
- 广义帕累托分布 /
- 贝叶斯估计
Abstract: In order to establish the reliable statistical models for extreme thermal gradients in long-span bridges during their life-cycles, a generalized Pareto distribution (GPD) is proposed to describe the statistical features of thermal gradient samples that excess a threshold. And the procedure of excluding correlation in thermal gradient samples and the approach of selecting the best threshold are suggested. A Bayesian estimation method combining parameter updating for finding a GPD-based extreme thermal gradient model is developed to fuse prior information and incoming monitoring data. In this method, the Gibbs sampling is employed for computing the Bayesian posterior distribution. The developed method is verified by the thermal gradient data monitored on the Jiubao Bridge. The results indicate that the GDP has strong ability in describing the statistical characteristics of thermal gradients, especially in the tail region, and the Bayesian estimation method combining parameter updating provides more reasonable parameters for the GDP than the maximum likelihood estimation method. The outcomes of this paper are expected to offer a reference for the study of thermal gradients in long-span bridges.
- bridge engineering /
- structural health monitoring /
- extreme thermal gradient /
- generalized Pareto distribution /
- Bayesian estimation

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