部分观测下基于子结构的大型结构损伤诊断法

该文提出一种适用于大型结构在激励与响应部分观测情况下进行结构损伤诊断的方法。基于有限元模型,大型结构被划分成若干个子结构。相邻子结构间的作用,视为对子结构的“附加未知激励”。依次采用扩展卡尔曼估计和最小二乘估计识别扩展状态向量和未知外部激励,在子结构界面响应未观测的情况下,对各子结构的单元动力参数分别进行识别,并以追踪子结构内单元结构参数的变化,例如单元刚度的退化,对大型结构的局部损伤进行诊断。通过一个较大型的平面桁架桥的损伤识别数值算例,证实了该方法的可行性。与其他方法相比,提出的方法减少了对结构响应观测的要求。

A DAMAGE DETECTION ALGORITHM BASED ON SUBSTRUCTURES FOR LARGE SIZE STRUCTURES UNDER LIMITED MEASUREMENTS

In this paper,a damage detection algorithm is proposed for large size structures under limited input and output measurements.A large size structure is decomposed into small size substructures based on its finite element formulation.The interconnections between adjacent substructures are treated as ’additional unknown inputs’ to substructures.By sequentially utilizing the extended Kalman estimator for the extended state vector and a least squares estimation for the unmeasured external inputs,the algorithm can identify element dynamic parameters in each substructure.Structural local damage in the large size structure can be detected by tracking the changes in the identified values of dynamic parameters at an element level,e.g.,the degrading of stiffness parameters.The numerical example of detecting structural damages in a relatively large size plane truss bridge validates the feasibility of the proposed algorithm.Compared with other approaches,the proposed algorithm requests fewer input and output measurements.