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Detection of damage in cyclic structures using an eigenpair sensitivity matrix

机译:使用特征对灵敏度矩阵检测循环结构中的损伤

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摘要

In cyclic structures, the eigenvectors associated with repeated eigenvalues do not change smoothly in case of damages, thus, the existing sensitivity-based damage detection techniques are rendered ineffective. To overcome this problem, a transformation from such eigenvectors to a set of well-behaved pseudo-eigenvectors is introduced. The proposed pseudo-eigenvectors can be linearly approximated, and hence, they admit sensitivity-based analysis. Subsequently, sensitivity matrices of eigenvalues and pseudo-eigenvectors are established, and four damage detection algorithms are developed accordingly. Simulation results under different number of sensors and various noise levels confirm the efficiency of the proposed approach.
机译:在循环结构中,与重复特征值关联的特征向量在发生损坏的情况下不会平滑变化,因此,现有的基于灵敏度的损坏检测技术将变得无效。为了克服这个问题,引入了从这种特征向量到一组行为良好的伪特征向量的变换。拟议的伪特征向量可以线性近似,因此,它们可以进行基于灵敏度的分析。随后,建立了特征值和伪特征向量的灵敏度矩阵,并据此开发了四种损伤检测算法。在不同数量的传感器和各种噪声水平下的仿真结果证实了该方法的有效性。

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