A Dynamic Bayesian Network Model for Structural Time-Dependent Reliability Analysis of Resistance Deterioration
-
摘要: 针对存在抗力退化结构的时变可靠性问题,提出一种动态贝叶斯网络(dynamic Bayesian network, DBN)模型,以gamma过程作为抗力退化模型,并离散为Bayes网络,同时建立观测模型、可靠性模型,组合为动态Bayes网络,通过连续节点消除与离散得到仅含离散变量的动态Bayes网络;给出精确推理的3种情况,评估现在(滤波)、未来(预测)以及过去时刻(平滑)结构的状态.当测量信息出现时,对退化模型参数重新估计,利用精确推理来更新结构时变可靠性.以存在抗力退化的一跨刚架作为研究对象,验证了模型的合理性Abstract: A dynamic Bayesian network (DBN) model was proposed for timedependent reliability analysis of structures in deterioration. The structural resistance deterioration was modeled as a gamma process while the loads as random variables. The stochastic deterioration process was discretized in time domain as deterioration models. A DBN was established and comprised of the reliability model, deterioration model and observation model. Node elimination algorithm and discretization were applied to modify the DBN into a network with only discrete variables. Exact inferences with the DBN were presented to estimate the 3 structural states at present (filtering), in the future (prediction) and in the past (smoothing), respectively. The structural timedependent reliability was updated with the reestimated deterioration model when measurements were available. The proposed model was validated through the timedependent reliability analysis of a onebay example frame in resistance deterioration.
-
[1] 吕大刚, 樊学平, 蒋伟. 结构时变可靠度方法的对比分析研究[C]//全国工程结构设计安全与可持续发展研讨会. 宁波, 2010. (Lü Da-gang, FAN Xue-ping, JIANG Wei. Structural time-dependent reliability method research[C]// Seminar of National Engineering Structure Design Safety and Sustainable Development.Ningbo, 2010.(in Chinese)) [2] 王正, 谢里阳. 不确定性载荷作用下的零件时变可靠性模型[J]. 航空学报, 2009,30(7): 1243-1247.(WANG Zheng, XIE Li-yang. Time-variant reliability model of components under uncertain loads[J]. Acta Aeronautica et Astronautica Sinica,2009,30(7): 1243-1247.(in Chinese)) [3] Stewart M G, Mullard J A. Spatial time-dependent reliability analysis of corrosion damage and the timing of first repair for RC structures[J]. Engineering Structure,2007,29(7): 1457-1464. [4] Kuniewski S P, Van der Weide J A M, Van Noortwijk J M. Sampling inspection for the evaluation of time-dependent reliability of deteriorating systems under imperfect defect detection[J]. Reliability Engineering & System Safety,2009,94(9): 1480-1490. [5] Liu M, Frangopol D M. Time-dependent bridge network reliability: novel approach[J]. Journal of Structural Engineering,2005,131(2): 329-337. [6] Van Noortwijk J M, Van der Weide J A M, Kallen M J, Pandey M D. Gamma processes and peaks-over-threshold distributions for time-dependent reliability[J]. Reliability Engineering & System Safety,2007,92(12): 1651-1658. [7] 张连文, 郭海鹏. 贝叶斯网引论[M]. 北京: 科学出版社, 2006.(ZHANG Lian-wen, GUO Hai-peng. Introduction to Bayesian Networks [M]. Beijing: Science Press, 2006.(in Chinese)) [8] Jensen F V, Nielsen T D. Bayesian Networks and Decision Graphs [M]. 2nd ed. Berlin: Springer, 2007. [9] Abdel-Hameed M. A gamma wear process[J]. IEEE Transactions on Reliability,1975,24(2): 152-153. [10] Ellingwood B R, Mori Y. Probabilistic methods for condition assessment and life prediction of concrete structures in nuclear power plants[J]. Nuclear Engineering and Design,1993,142(2/3): 155-166. [11] Shachter R D. Evaluating influence diagrams[J]. Operations Research,1986,34(6): 871-882. [12] Straub D. Stochastic modeling of deterioration processes through dynamic Bayesian networks[J]. Journal of Engineering Mechanics,2009,135(10): 1089-1099. [13] Der Kiureghian A. First- and second-order reliability methods[C]//Nikolaidis E, Ghiocel D M, Singhal S, eds. Chap14. Engineering Design Reliability Handbook.Boca Raton, Florida: CRC Press, 2005.
点击查看大图
计量
- 文章访问数: 1219
- HTML全文浏览量: 85
- PDF下载量: 1094
- 被引次数: 0