基于贝叶斯网络的结构易损性智能推理

Intelligent inference of structural vulnerability using Bayesian networks

为实现结构易损性的智能化推理,提出以贝叶斯网络(Bayesian networks,BNs)重构桁架结构的易损性分析体系。首先,分别定义外荷载、体系和杆件为网络顶层父节点、中间节点和底层子节点,节点间通过有向弧表示因果关系,形成BN拓扑;接着,提出以杆件“大损伤”替代传统的“概念移除”方式,考虑杆件参数及外荷载的不确定性,结合抽样实现对节点间条件概率表的学习,完成BN的构建;然后将特定杆件的观测状态作为证据输入BN,同步推理其他杆件的节点状态概率,进而计算杆件的重要性系数,并定义所有杆件的重要性系数之和为体系的易损性系数;最后,提出杆件易损指标,作为预测桁架体系最可能失效路径的依据。研究结果表明:所提方法能更合理地评价各杆件在体系中的重要性,推理得到的杆件破坏路径与试验观测一致,所计算的试验桁架体系易损性系数远小于杆件数目,表明当前荷载组合下特定杆件的损伤引起体系发生连续性倒塌的可能性较小。

In order to realize the intelligent inference of structural vulnerability,Bayesian networks(BNs)have been adopted for reconstructing the analysis system of a truss structure.Firstly,the external load combination,the truss system and its members are defined as the top parent nodes,the middle nodes and the bottom child nodes of the network,respectively.These nodes are connected by some directed edges representing the causality between them.Therefore,the BN topology of the truss structure is defined.Secondly,serious damage is suggested to replace the commonly-used assumption of conceptual removal in vulnerability analysis.Based on the uncertainty distributions of the parameters of members and external loads,the samples are randomly drawn from the probability distributions for learning the conditional probability tables between the different nodes,thereby realizing the BN establishment.Thirdly,the observed state of a specific member is used as the evidence into the established BN for synchronously inferring the state probabilities of the other members,based on which the member importance coefficient is calculated.The sum of all the importance coefficients is further defined as the system vulnerability index.Finally,a member vulnerability index is proposed to predict the most probable failure path of the truss system.The numerical and experimental examples have demonstrated that the proposed method can effectively evaluate the importance of each member within a truss system.The inferred failure path accords well with the experimental observation.The estimated value of the system vulnerability index of the experimental truss is far less than the number of members,and thus,it indicates the low possibility of progressive collapse of the system due to the damaged member.