吉林大学学报(工学版) ›› 2023, Vol. 53 ›› Issue (8): 2332-2338.doi: 10.13229/j.cnki.jdxbgxb.20220334

• 交通运输工程·土木工程 • 上一篇    

桥梁时变可靠性的多过程贝叶斯动态混合预测

樊学平1,2(),周衡2,刘月飞1,2()   

  1. 1.兰州大学 西部灾害与环境力学教育部重点实验室，兰州 730013
    2.兰州大学 土木工程与力学学院，兰州 730013
  • 收稿日期:2022-03-29 出版日期:2023-08-01 发布日期:2023-08-21
  • 通讯作者: 刘月飞 E-mail:fxp_2004@163.com;yfliu@lzu.edu.cn
  • 作者简介:樊学平（1983-），男，副教授，博士.研究方向：桥梁结构与可靠性预测.E-mail：fxp_2004@163.com
  • 基金资助:
    国家自然科学基金项目(51608243);中央高校基金面上项目(lzujbky-2022-43);甘肃省自然科学基金面上项目(20JR10RA625)

Multi⁃process Bayesian dynamic combinatorial prediction of time⁃variant reliability for bridges

Xue-ping FAN1,2(),Heng ZHOU2,Yue-fei LIU1,2()   

  1. 1.Key Laboratory of Mechanics on Disaster and Environment in Western China of Ministry of Education，Lanzhou University，Lanzhou 730013
    2.School of Civil Engineering and Mechanics，Lanzhou University，Lanzhou 730013，China
  • Received:2022-03-29 Online:2023-08-01 Published:2023-08-21
  • Contact: Yue-fei LIU E-mail:fxp_2004@163.com;yfliu@lzu.edu.cn

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摘要：

基于在役桥梁健康监测信息对结构可靠性进行预测分析。首先，采用时间序列分析方法、移动平均法以及五点三次平滑法将采集的健康监测信息（极值应力信号）进行降噪处理；其次考虑到时间序列用单一的动态线性模型预测不够完善，需要用多个动态线性模型的组合进行预测，引入多过程模型，建立多过程贝叶斯动态线性模型（BDLM），进行监测极值应力的预测和分析；最后，结合多过程贝叶斯动态线性模型（BDLM）和一次二阶矩（FOSM）可靠度方法进行桥梁构件的时变可靠性分析。研究成果为结构可靠性预测提供了理论基础。

关键词: 结构工程, 五点三次平滑法, 多过程动态线性模型, 贝叶斯预测, 可靠度分析

Abstract:

Based on the health monitoring information of the in-service bridge， it is very important to reasonably analyse the structural reliability for the safety and serviceability assessment. In this paper， the time series analysis method， the moving average method and the cubical smoothing algorithm with five-point approximation are used to reduce the noise of monitoring information （extreme stress signal）. Considering that some time series is not enough to predict with a single dynamic linear model， these time series need to be predicted by a combination of multiple dynamic linear models. This study introduces multi-process model and establishes a multi-process Bayesian dynamic linear model to predict and analyse the extreme stresses； Further， the time-dependent reliability of bridge members is predicted by combining multi-process Bayesian dynamic linear model （BDLM） and first-order second moment （FOSM） reliability method. The research results of this paper will provide the theoretical basis for structural reliability prediction.

Key words: structural engineering, cubical smoothing algorithm with five-point approximation, multi-process dynamic linear model, Bayesian prediction, reliability prediction

中图分类号: 

  • TU391
1 樊学平, 吕大刚. 基于BDNM的桥梁结构可靠度预测[J]. 哈尔滨工业大学学报, 2014, 46(2): 1-5.
Fan Xue-ping, Da-gang Lyu. Reliability prediction of bridge structures based on BDNM[J]. Journal of Harbin Institute of Technology, 2014, 46(2): 1-5.
2 樊学平, 吕大刚. 基于贝叶斯DLM的桥梁结构可靠度预测[J]. 铁道学报, 2014, 36(6): 93-98.
Fan Xue-ping, Lu Da-gang. Reliability prediction of aging bridges based on Bayesian dynamic linear model[J]. Journal of the China Railway Society, 2014, 36(6): 93-98.
3 钟才根, 丁文其, 王茂和.神经网络模型在高速公路软基沉降预测中的应用[J].中国公路学报, 2003, 16(2): 31-34.
Zhong Cai-gen, Ding Wen-qi, Wang Mao-he. Application of neural network model to the settlement projection of sofr-soil foundation for expressway[J]. China Journal of Highway and Transport, 2003, 16(2): 31-34.
4 兰孝奇, 杨永平, 黄庆, 等.建筑物沉降的时间序列分析与预报[J].河海大学学报: 自然科学版, 2006, 34(4): 426-429.
Lan Xiao-qi, Yang Yong-ping, Huang Qing, et al. Analysis and prediction of time series for building settlement[J]. Journal of Hohai University(Natural Sciences), 2006, 34(4): 426-429.
5 张仪萍, 俞亚南, 张土乔, 等. 沉降预测中的灰色模型理论与 Asaoka 法[J].系统工程理论与实践, 2002(9): 141-144.
Zhang Yi-ping, Yu Yan-nan, Zhang Tu-qiao, et al. Grey theory and asaoka method in settlement prediction[J]. System Engineering-Theory&Practice, 2002(9): 141-144.
6 杨叔子, 吴雅, 轩建平. 时间序列分析的工程应用[M]. 第二版, 华中科技大学出版社, 2007.
Yang Shu-zi, Wu Ya, Xuan Jian-ping. Engineering Application of Time-Series Analysis [M]. Second Edition, Press of Huazhong University of Science and Technology, 2007.
7 孙永福, 王良曦, 庞磊. GM(1,1)模型与指数回归模型的比较与研究[J]. 装甲兵工程学院学报, 2000, 14(1): 76-79.
Sun Yong-fu, Wang Liang-xi, Pang Lei. Comparison between and research of gray model GM(1,1) and exponential regressing model[J]. Journal of Armored Force Engineering Institute, 2000, 14(1): 76-79.
8 Catbas F N, Susoy M, Frangopol D M. Structure health monitoring and reliability estimation: long span truss bridge application with environmental monitoring data[J]. Engineering Structure, 2008, 30:2347-2359.
9 Petris G, Petrone S, Campagnoli P. Dynamic Linear Models with R[M]. New York: Springer-Verlag, 2009.
10 West M, Harrison J. Bayesian Forecasting and Dynamic Models[M]. Second Edition. New York: Springer Series in Statistics, 1997.
11 West M, Harrison J. Bayesian Forecasting and Dynamic Models[M]. New York: Springer Verlag, 1989.
12 王剑.基于信息更新的混凝土结构性能预测和可靠性管理[D]. 北京: 清华大学土木水利学院, 2006.
Wang Jian. Performance prediction and reliability management of concrete structures based on information updating[D]. Beijing: School of Civil Engineering, Tsinghua University. 2006.
13 张孝令, 刘福升, 张承进, 等. 贝叶斯动态模型及其预测[M]. 济南: 山东科技技出版社, 1992.
Zhang Xiao-ling, Liu Fu-sheng, Zhang Cheng-jin, et al. Bayesian Dynamic Model and Forecasting[M], Jinan: Shan Dong Science&Technolyge Press, 1922.
14 Melchers R E. Structural Reliability, Analysis and Prediction[M]. Ellis Horwood: Chichester, 1987.
15 Frangopol D M, Strauss A, Kim S Y. Use of monitoring extreme data for the performance prediction of structures: general approach[J]. Engineering Structures, 2008, 30: 3644-3653.
16 Strauss A, Frangopol D M, Kim S Y. Use of monitoring extreme data for the performance prediction of structures: Bayesian updating[J]. Engineering Structures, 2008, 30: 3654-3666.
17 Mahmoud H N, Connor R J, Bowman C A. Results of the fatigue evaluation and field monitoring of the I-39 northbound bridge over the wisconsin river[R]. Bethlehem: Lehigh University, 2005.
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