Structural damage detection with limited input and output measurement signals
Structural damage detection with limited input and output measurement signals
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DOI：
10.1016/j.ymssp.2011.07.026
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发表时间：
2012-04
影响因子：
8.4
通讯作者：
Y. Lei;Y. Jiang;Zhiqian Xu
中科院分区：
文献类型：
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作者：
Y. Lei;Y. Jiang;Zhiqian Xu
在有限的输入和输出测量信号下进行结构损伤检测是一项重要而又具有挑战性的工作。提出了一种基于有限输入输出测量信号的结构损伤检测算法。该算法基于结构扩展状态向量的扩展卡尔曼估值器和未知外部激励的最小二乘估计的顺序应用。给出了结构参数和未知激励辨识的递推解析解。这种直接的推导和解析解在以前的文献中是不可用的。从识别出的单元刚度退化可以检测到结构损伤。通过对一些小尺寸结构系统进行损伤检测的数值算例，验证了该算法的有效性。然后，将该算法扩展到基于子结构方法的大型结构系统损伤识别中。相邻子结构之间的互连效应通过子结构的“附加未知输入”来考虑。结果表明，该算法可以在不需要测量子结构界面自由度的情况下对“附加未知输入”进行估计，优于以往的识别方法。一个大型桁架结构损伤检测的数值算例说明了该算法的有效性。
It is important but still challenging to detect structural damage with limited input and output measurement signals. In this paper, an algorithm is proposed for detecting structural damage with limited input and output measurement signals. The algorithm is based on sequential application of an extended Kalman estimator for the extended state vector of a structure and least-squares estimation of its unknown external excitations. Analytical recursive solutions for the identification of structural parameters and unknown excitations are derived. Such straightforward derivation and analytical solutions are not available in the previous literature. Structural damage can be detected from the degradation of the identified element stiffness. Numerical examples of detecting damage of some small size structural systems are used to demonstrate the performances of the proposed algorithm. Then, the algorithm is extended to detect structural damage of large size structural systems based on substructure approach. Inter-connection effect between adjacent substructures is considered by ‘additional unknown inputs’ to substructures. It is shown that the ‘additional unknown inputs’ can be estimated by the algorithm without the measurements of the substructure interface DOFs, which is superior to previous identification approaches. A numerical example of detecting structural damage of a large size truss illustrates the efficiency of the proposed algorithm.