基于贝叶斯更新和逆高斯过程的在役钢筋混凝土桥梁构件可靠度动态预测方法

陈龙; 黄天立

doi:10.6052/j.issn.1000-4750.2019.05.0273

基于贝叶斯更新和逆高斯过程的在役钢筋混凝土桥梁构件可靠度动态预测方法

doi: 10.6052/j.issn.1000-4750.2019.05.0273

陈龙,
黄天立

中南大学土木工程学院, 湖南, 长沙 410075

基金项目: 国家自然科学基金项目（U1734208，51478472）；国家重点研究计划项目（2017YFB1201204）

详细信息

作者简介:
陈龙(1994-),男,安徽人,硕士生,主要从事桥梁结构可靠度研究(E-mail:1349508326@qq.com).

通讯作者:
黄天立(1977-),男,湖南人,教授,博士,主要从事桥梁结构健康监测、评估与维护管理研究(E-mail:htianli@csu.edu.cn).

中图分类号: U445.7;U446
计量
- 文章访问数: 754
- HTML全文浏览量: 57
- PDF下载量: 168
- 被引次数: 0
出版历程
- 收稿日期: 2019-05-18
- 修回日期: 2019-10-25
- 刊出日期: 2020-04-14

DYNAMIC PREDICTION OF RELIABILITY OF IN-SERVICE RC BRIDGES USING THE BAYESIAN UPDATING AND INVERSE GAUSSIAN PROCESS

School of Civil Engineering, Central South University, Changsha, Hu'nan 410075, China

摘要

摘要: 在役钢筋混凝土桥梁在服役环境和车辆荷载的耦合作用下，其服役性能随时间不断退化，采用确定性的性能退化模型无法准确描述退化过程中的不确定性和时间变异性。该文采用逆高斯随机过程描述其抗力退化过程，同时采用复合泊松过程描述车辆荷载效应，建立了基于抗力-车辆荷载效应双随机过程的在役钢筋混凝土桥梁构件时变可靠度分析方法。结合检测数据，采用贝叶斯分析和期望最大化算法，对逆高斯过程抗力退化模型参数进行更新，提出了在役钢筋混凝土桥梁构件可靠度的动态预测方法。以一座钢筋混凝土T梁桥为例，采用其40年服役期的抗力退化数据，分别在四个服役时刻对逆高斯过程抗力退化模型参数进行了更新，演示了提出的可靠度动态预测方法。研究表明：逆高斯随机过程可更合理地描述钢筋混凝土桥梁构件抗力退化过程中的不确定性和时间变异性；融入桥梁服役期间检测的抗力退化信息，采用贝叶斯更新逆高斯过程抗力退化模型参数后，可更准确地预测桥梁未来的可靠度服役状况和估计桥梁的剩余使用寿命。
- 桥梁工程 /
- 在役钢筋混凝土桥梁 /
- 可靠度预测 /
- 逆高斯过程 /
- 贝叶斯更新
Abstract: The performance of reinforced concrete (RC) bridges deteriorates with time under the combined action of environmental effects and loadings. The deterministic degradation models cannot accurately describe the uncertainty and time variability of the degradation process. In this study, the inverse Gaussian process (IGP) and the composite Poisson process were respectively adopted to describe the resistance degradation process and the load effect. The time-dependent reliability analysis method for RC bridge members was established based on the double dual random process model of resistance and load. Furthermore, combined with the monitored data, the Bayesian analysis and the expectation maximization (EM) algorithm were adopted to update the IGP-based resistance deterioration model parameters. Subsequently, a dynamic prediction procedure for the reliability of RC bridge members was proposed. Finally, using the resistance degradation data of a RC T-girder bridge during its 40-year service period, the IGP-based resistance deterioration model parameters were updated at four different service times. The reliability of the proposed dynamic prediction procedure was validated. The research results show that IGP can be used to describe the uncertainty and time variability of the resistance degradation process of RC bridge members. The future reliability level and the remaining service life of RC bridges can be accurately predicted by using the detected resistance degradation data during its service period and the updated IGP-based resistance deterioration model parameters.
- bridge engineering /
- existing RC bridges /
- reliability prediction /
- inverse Gaussian process /
- Bayesian updating

HTML全文

参考文献(23)

[1]	肖盛燮. 桥梁承载力演变理论及其应用技术[M]. 北京:科学出版社, 2009. Xiao Shengxie. Evolution theory and application technology of resistance of bridges[M]. Beijing:Science Press, 2009. (in Chinese)
[2]	Strauss A, Frangopol D M, Kim S. Reliability assessment and prediction using monitoring information[J]. IABSE Symposium Report, 2009, 96(5):73-86.
[3]	彭建新,张建仁,张克波,等. 锈蚀RC桥梁弯曲抗力时变概率模型与试验研究[J]. 工程力学, 2012, 29(6):125-132. Peng Jianxin, Zhang Jianren, Zhang Kebo, et al. Probabllistic resistance model and experimental investigation for corrosion RC bridges[J]. Engineering Mechanics, 2012, 29(6):125-132. (in Chinese)
[4]	孙俊祖, 黄侨, 任远, 等. 锈蚀疲劳后混凝土中钢筋力学性能试验[J]. 哈尔滨工业大学学报, 2016, 48(3):89-94. Sun Junzu, Huang Qiao, Ren Yuan, et al. Test for mechanical behaviour of steel reinforcing bar after corrosion fatigue[J]. Journal of Harbin Institute of Technology, 2016, 48(3):89-94. (in Chinese)
[5]	王建秀, 秦权. 考虑氯离子侵蚀与混凝土碳化的公路桥梁时变可靠度分析[J]. 工程力学, 2007, 24(7):86-93. Wang Jianxiu, Qin Quan. Analysis of time-dependent reliability of rc highway bridges considering chloride attack and concrete carbonation[J]. Engineering Mechanics, 2007, 24(7):86-93. (in Chinese)
[6]	Ellingwood B R. Risk-informed condition assessment of civil infrastructure:state of practice and research issues[J]. Structure and Infrastructure Engineering, 2005, 1(1):7-18.
[7]	Mori Y, Ellingwood B R. Reliability-based service-life assessment of aging concrete structures[J]. Journal of Structural Engineering, 1993, 119(5):1600-1621.
[8]	van Noortwijk J M, van der Weide J A M, Kallen M J, et al. Gamma processes and peaks-over-threshold distributions for time-dependent reliability[J]. Reliability Engineering and System Safety, 2007, 92(12):1651-1658.
[9]	van Noortwijk J M. A Survey of the application of gamma processes in maintenance[J]. Reliability Engineering and System Safety, 2009, 94(1):2-21.
[10]	黄天立,周浩,王超,等. 基于伽马过程的锈蚀钢筋混凝土桥梁检测维护策略优化[J]. 中南大学学报(自然科学版), 2015, 46(5):1851-1861. Huang Tianli, Zhou Hao, Wang Chao, et al. Optimization inspection and maintenance strategy for corrosive reinforced concrete girder bridges based on gamma process[J]. Journal of Central South University (Science and Technology), 2015, 46(5):1851-1861. (in Chinese)
[11]	黄天立,周浩,任伟新,等. 基于伽马过程的钢桥构件疲劳裂纹检测维护策略优化[J]. 中国公路学报, 2016, 29(5):50-57. Huang Tianli, Zhou Hao, Ren Weixin, et al. Optimal inspection and maintenance strategy for fatigue cracks of steel bridge members using gamma process model[J]. China Journal of Highway and Transport, 2016, 29(5):50-57. (in Chinese)
[12]	Strauss A, Wanwendner R, Vidovic A, et al. Gamma prediction models for long-term creep deformations of prestressed concrete bridges[J]. Journal of Civil Engineering and Management, 2017, 23(6):681-698.
[13]	Li Q W, Wang C, Ellingwood B R. Time-dependent reliability of aging structures in the presence of non-stationary loads and degradation[J]. Structural Safety, 2015, 52:132-141.
[14]	Wang X, Xu D. An inverse gaussian process model for degradation data[J]. Technometrics, 2010, 52(2):188-197.
[15]	Peng W W, Li Y F, Yang Y J, et al. Inverse gaussian process models for degradation analysis:A bayesian perspective[J]. Reliability Engineering and System Safety, 2014, 130(1):175-189.
[16]	Zhang S W, Zhou W X, Qin H. Inverse gaussian process-based corrosion growth model for energy pipelines considering the sizing error in inspection data[J]. Corrosion Science, 2013, 73(13):309-320.
[17]	van Noortwijk J M, Klatter H E. Optimal inspection decisions for the block mats of the eastern-scheldt barrier[J]. Reliability Engineering and System Safety, 1999, 65(3):203-211.
[18]	李扬海. 公路桥梁结构可靠度与概率极限状态设计[M]. 北京:人民交通出版社, 1997. Li Yanghai. Structural reliability and probabilistic limit state design of highway bridges[M]. Beijing:the People's Communication Publishing Company, 1997. (in Chinese)
[19]	王草, 李全旺. 考虑非平稳车载过程的在役桥梁时变可靠度分析[J]. 工程力学, 2016, 33(3):18-23. Wang Cao, Li Quanwang. Time-dependent reliability of exsiting bridges considering non-stationary load process[J]. Engineering Mechanics, 2016, 33(3):18-23. (in Chinese)
[20]	Hao S H, Yang J, Ma X B, et al. Reliability modeling for mutually dependent competing failure processes due to degradation and random shocks[J]. Applied Mathematical Modelling, 2017, 51:232-249.
[21]	司小胜,胡昌华,李娟,等. Bayesian更新与EM算法协作下退化数据驱动的剩余寿命估计方法[J]. 模式识别与人工智能, 2013, 26(4):357-365. Si Xiaosheng, Hu Changhua, Li Juan, et al. Degradation data-driven remaining useful life estimation approach under collaboration between bayesian updating and EM algorithm[J]. Pattern Recognition and Artificial Intelligence, 2013, 26(4):357-365. (in Chinese)
[22]	Pan D H, Liu J B, Cao J D. Remaining useful life estimation using an inverse gaussian degradation model[J]. Neurocomputing, 2016, 185:64-72.
[23]	杨跃新. 混凝土连续梁桥的时变可靠度评定与寿命预测[D]. 哈尔滨:哈尔滨工业大学, 2007. Yang Yuexin. Time-dependent reliability assessment and life Prediction of continuous concrete girder bridges[D]. Harbin:Harbin Institute of Technology, 2007. (in Chinese)