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基于全局传递比函数与主成分分析的结构损伤识别

Structural damage detection based on global transmissibility functions and principal component analysis

  • 摘要: 基于全局传递比函数和主成分分析,提取特征值构建损伤指标,并结合损伤指标的统计信息设计阈值,从而提出一种对结构损伤有效识别的新方法。该方法无需事先筛选全局传递比函数,而是将全局传递比函数频带的筛选转化为主成分的选取,避免了经验判断和频带选择对损伤识别结果的影响。数值模拟与模型试验的结果表明,该方法在连续梁、空间钢桁架及钢制信号塔等多种工程结构形式中均表现出良好的适用性,在不同荷载激励条件下均可有效地识别单损伤与多损伤工况,即使在较高噪声水平和较低局部损伤程度的情况下,虽然损伤识别结果可能扩散至邻近区域,但该方法整体上仍展现出较强的抗噪声能力。

     

    Abstract: Based on global transmissibility functions and principal component analysis, eigenvalues are extracted to construct damage indices. These indices are then combined with the statistical properties to establish detection thresholds, proposing a novel method for effective structural damage identification. Unlike conventional approaches, this method eliminates the need for pre-selecting global transmissibility and replaces frequency band selection with principal components’ selection, reducing reliance on subjective judgment and improving damage detection accuracy. Numerical simulations and experimental tests demonstrated effectiveness of the proposed method on both single and multiple damage scenarios across diverse structural forms, including continuous beams, spatial steel trusses, and steel signal towers under varying loads. Even under high noise levels or minor localized damage, while the damage localizations may extend to adjacent regions, the method still provide reasonable and reliable results.

     

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