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桥梁监测数据的动态线性建模与可靠性预测
引用本文:樊学平,刘月飞,吕大刚.桥梁监测数据的动态线性建模与可靠性预测[J].同济大学学报(自然科学版),2016,44(7):1002-1009.
作者姓名:樊学平  刘月飞  吕大刚
作者单位:兰州大学 西部灾害与环境力学教育部重点实验室,甘肃 兰州 730000;兰州大学 土木工程与力学学院, 甘肃 兰州 730000,兰州大学 西部灾害与环境力学教育部重点实验室,甘肃 兰州 730000;兰州大学 土木工程与力学学院, 甘肃 兰州 730000,哈尔滨工业大学 土木工程学院,黑龙江 哈尔滨 150090
基金项目:国家自然科学基金(51378162),“中央高校基本科研业务费专项资金”项目(lzujbky-2015-28,lzujbky-2015-31)
摘    要:引入贝叶斯动态线性模型(BDLM),建立桥梁监测应力的状态方程和观测方程,并利用贝叶斯因子监控监测应力.通过监测应力和应力状态的先验信息,对监测应力的状态参数进行贝叶斯后验概率推断,并不断进行"概率预测-修正"递推运算,获得最优监测应力的状态概率估计来预测桥梁的应力.基于贝叶斯动态修正的应力概率模型,建立桥梁结构可靠性的预测公式.最后,通过实例验证了本文所建模型的合理性和适用性.

关 键 词:桥梁监测应力  贝叶斯方法  动态线性模型  折扣因子
收稿时间:2015/8/31 0:00:00
修稿时间:2016/5/20 0:00:00

Dynamic Linear Modeling of Bridge Monitored Data and Reliability Prediction
FAN Xueping,LIU Yuefei and Lyu Dagang.Dynamic Linear Modeling of Bridge Monitored Data and Reliability Prediction[J].Journal of Tongji University(Natural Science),2016,44(7):1002-1009.
Authors:FAN Xueping  LIU Yuefei and Lyu Dagang
Institution:Key Laboratory of Mechanics on Disaster and Environment in Western China of the Ministry of Education, Lanzhou University, Lanzhou 730000, China; School of Civil Engineering and Mechanics, Lanzhou University, Lanzhou 730000, China,Key Laboratory of Mechanics on Disaster and Environment in Western China of the Ministry of Education, Lanzhou University, Lanzhou 730000, China; School of Civil Engineering and Mechanics, Lanzhou University, Lanzhou 730000, China and School of Civil Engineering, Harbin Institute of Technology, Harbin 150090, China
Abstract:A Bayesian dynamic linear model (BDLM) is introduced, which includes state equation and observation equation of bridge monitoring stress, and the stress is monitored with Bayesian factors. Combining parameters prior information with the early stress monitored data containing noise, the monitored stress state parameters are deduced with Bayesian posterior probability. Optimal stress state estimation uses continuous probability forecast fixed recursion operator to predict the bridge stress. The prediction formula of bridge reliability is given based on BDLM of bridge stress. Finally, an actual example is provided to demonstrate the applicability and feasibility of the proposed model.
Keywords:bridge monitored stress  Bayesian method  dynamic linear model  discount factor
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