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Structural damage identification by a cross modal energy sensitivity based mode subset selection strategy

机译：基于跨模型能量灵敏度的模式子集选择策略的结构损伤识别

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摘要

This paper presents a strategy specialized for modal energy (ME) based methods, including modal strain energy (MSE) and modal kinetic energy (MICE), to select the best mode subset prior to damage identification. The damages due to the changes in stiffness and mass of structural members are both considered. In order to apply the proposed scheme to a more general situation, the cross modal energy (CME) sensitivity instead of the usual ME sensitivity is derived and designated as a sensitivity index. According to this index, the mode combinations (MCs) that are more sensitive to stiffness and mass changes are retained, while the remaining MCs that complicate the process of damage detection are eliminated. One of the important applications of the proposed mode subset selection strategy (MSSS) is to optimize the Cross model cross-mode (CMCM) system by eliminating some redundant equations, thereby improving the performance of the CMCM method and reducing the computational burden. Numerical and experimental studies are carried out to prove the effectiveness of the proposed scheme. The results show that the performance of the CMCM method has been significantly improved after adopting the MSSS.
机译：本文呈现专门用于模态能量的策略（ME）为基础的方法，包括模态应变能（MSE）和模态动能（MICE），选择前损伤识别的最佳模式的子集。由于刚度和结构构件的质量变化的损害都考虑。为了所提出的方案应用于更一般的情况下，横模态能量（CME）灵敏度而不是通常的ME灵敏度被导出并指定为灵敏度指数。根据该索引，那些对刚度和质量的变化更敏感的模式组合（MCS）被保留，而损伤检测的过程复杂化的剩余的MC被消除。一个所提出的模式的子集的选择策略（MSSS）的重要应用是通过消除一些多余的方程，从而改善了CMCM方法的性能并降低了计算负担，以优化跨模型交叉模式（CMCM）系统。数值模拟和实验的研究来论证该方案的有效性。该结果表明，该方法CMCM的性能已经采用MSSS之后已经显著改善。

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