华南理工大学学报(自然科学版) ›› 2013, Vol. 41 ›› Issue (3): 70-75.doi: 10.3969/j.issn.1000-565X.2013.03.010

• 土木建筑工程 • 上一篇    下一篇

基于多个BDLM 的桥梁结构可靠度实时预测

樊学平 吕大刚   

  1. 哈尔滨工业大学 土木工程学院,黑龙江 哈尔滨 150090
  • 收稿日期:2012-08-09 修回日期:2013-01-08 出版日期:2013-03-25 发布日期:2013-02-01
  • 通信作者: 吕大刚(1970-),男,教授,博士生导师,主要从事地震工程、结构可靠度以及风险评估的研究. E-mail:ludagang@hit.edu.cn
  • 作者简介:樊学平(1985-),男,博士生,主要从事桥梁安全评定研究.E-mail:fxp_2004@163.com
  • 基金资助:

    国家自然科学基金资助项目( 50978080, 50678057)

Real-Time Reliability Forecast of Bridge Structures Based on Multiple BDLMs

Fan Xue-ping Lü Da-gang   

  1. School of Civil Engineering,Harbin Institute of Technology,Harbin 150090,Heilongjiang,China
  • Received:2012-08-09 Revised:2013-01-08 Online:2013-03-25 Published:2013-02-01
  • Contact: 吕大刚(1970-),男,教授,博士生导师,主要从事地震工程、结构可靠度以及风险评估的研究. E-mail:ludagang@hit.edu.cn
  • About author:樊学平(1985-),男,博士生,主要从事桥梁安全评定研究.E-mail:fxp_2004@163.com
  • Supported by:

    国家自然科学基金资助项目( 50978080, 50678057)

摘要: 基于桥梁的极值应力监测信息,采用贝叶斯动态线性模型( BDLM) ,建立了监测应力的贝叶斯动态线性组合预测模型; 采用该模型对结构的可靠指标进行实时预测,并通过工程实例进行了极值应力的组合预测和单个预测的精度分析. 结果表明: 所建立的组合预测模型的一步预测值与单个预测模型、取平均值的点预测模型的都很接近,但组合预测模型具有较高的预测精度; 相对于确定性的监测极值应力的可靠指标而言,组合预测模型考虑了监测应力的随机性和不确定性,所得的可靠度较小,可以更好地对结构的安全状态进行评定.

关键词: 桥梁结构, 可靠度, 极值应力, 贝叶斯动态线性模型, 组合预测, 预测精度

Abstract:

Based on the monitored extreme stress of bridges,a combinational forecasting model of extreme stress isconstructed with the Bayesian dynamic linear model ( BDLM) .Then,the proposed model is used to forecast thestructural reliability indices in real time.Moreover,a project case is provided to analyze the forecasting precisionsof the combinational forecasting model and the existing single forecasting models.The results show that,though theproposed model is of an one-step forecasting value close to that of the single forecasting models and the mean pointforecasting model,it is of higher forecasting precision,and that,as compared with the deterministic reliability indicesfor extreme stress monitoring,the combinational forecasting model fully considers the uncertainty and randomnessof monitored stress and helps to obtain smaller reliability indices,so that it is more effective in forecasting thestructural safety.

Key words: bridge structure, reliability, extreme stress, Bayesian dynamic linear model, combinational forecast, forecasting precision