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A flexibility-based method via the iterated improved reduction system and the cuckoo optimization algorithm for damage quantification with limited sensors

机译:通过迭代改进的减少系统和布谷鸟优化算法的基于灵活性的方法,用于有限传感器的损伤定量

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摘要

In this paper, a novel and effective damage diagnosis algorithm is proposed to localize and quantify structural damage using incomplete modal data, considering the existence of some limitations in the number of attached sensors on structures. The damage detection problem is formulated as an optimization problem by computing static displacements in the reduced model of a structure subjected to a unique static load. The static responses are computed through the flexibility matrix of the damaged structure obtained based on the incomplete modal data of the structure. In the algorithm, an iterated improved reduction system method is applied to prepare an accurate reduced model of a structure. The optimization problem is solved via a new evolutionary optimization algorithm called the cuckoo optimization algorithm. The efficiency and robustness of the presented method are demonstrated through three numerical examples. Moreover, the efficiency of the method is verified by an experimental study of a five-story shear building structure on a shaking table considering only two sensors. The obtained damage identification results for the numerical and experimental studies show the suitable and stable performance of the proposed damage identification method for structures with limited sensors.
机译:本文提出了一种新颖有效的损伤诊断算法,该方法可以使用不完整的模态数据对结构损伤进行定位和量化,同时考虑到结构上附着的传感器数量存在一些限制。通过计算结构的简化模型中承受独特静载荷的静态位移,将损坏检测问题公式化为优化问题。通过基于结构的不完整模态数据获得的受损结构的柔韧性矩阵来计算静态响应。在该算法中,采用迭代改进的简化系统方法来准备结构的精确简化模型。优化问题是通过一种称为“布谷鸟优化”算法的新进化优化算法解决的。通过三个数值例子证明了该方法的效率和鲁棒性。此外,通过仅考虑两个传感器的振动台上五层剪切建筑结构的实验研究,验证了该方法的有效性。通过数值和实验研究获得的损伤识别结果表明,所提出的有限传感器结构损伤识别方法具有适当和稳定的性能。

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