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A Combined Modal Correlation Criterion for Structural Damage Identification with Noisy Modal Data

机译:含模态数据的组合模态相关判据用于结构损伤识别

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Structural damage identification is a scientific field that has attracted a lot of interest in the scientific community during the recent years. There have been many studies intending to find a reliable method to identify damage in structural elements both in location and extent. Most damage identification methods are based on the changes of dynamic characteristics and static responses, but the incompleteness of the test data is a great obstacle for both. In this paper, a structural damage identification method based on the finite element model updating is proposed, in order to provide the location and the extent of structural damage using incomplete modal data of a damaged structure. The structural damage identification problem is treated as an unconstrained optimization problem which is solved using the differential evolution search algorithm. The objective function used in the optimization process is based on a combination of two modal correlation criteria, providing a measure of consistency and correlation between estimations of mode shape vectors. The performance and robustness of the proposed approach are evaluated with two numerical examples a simply supported concrete beam and a concrete frame under several damage scenarios. The obtained results exhibit high efficiency of the proposed approach for accurately identifying the location and extent of structural damage.
机译:结构损伤识别是近年来在科学界引起广泛兴趣的一个科学领域。有许多研究打算寻找一种可靠的方法来识别结构元件在位置和范围上的损坏。大多数损伤识别方法都是基于动态特性和静态响应的变化,但是测试数据的不完整对于这两者都是一个很大的障碍。本文提出了一种基于有限元模型更新的结构损伤识别方法,以利用损伤结构的不完整模态数据提供结构损伤的位置和程度。结构损伤识别问题被视为无约束优化问题,可以使用差分进化搜索算法解决。在优化过程中使用的目标函数基于两个模态相关标准的组合,提供了模态形状矢量估计之间一致性和相关性的度量。该方法的性能和鲁棒性通过两个数值示例,分别是在几种破坏情况下的简单支撑混凝土梁和混凝土框架进行了评估。获得的结果显示了所提出的方法的高效率,该方法可以准确地识别结构损坏的位置和程度。

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