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Enhanced Sensitivity for Structural Damage Detection Using Incomplete Modal Data

机译:使用不完整的模态数据提高结构损伤检测的灵敏度

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摘要

The necessity of detecting structural damages in an early stage has led to the development of various procedures for structural model updating. In this regard, sensitivity-based model updating methods utilizing mode shape data are known as effective tools. For this purpose, accurate estimation of the mode shape changes is desired to achieve successful model updating. In this paper, Wangs method is improved by including measured natural frequencies of the damaged structure in derivation of the sensitivity equation. The sensitivity equation is then solved using an incomplete subset of mode shape data in evaluation of the changes of the structural parameters. A comparative study of the results obtained by the proposed method with those by the modal method for a truss and a frame model indicated that the former is significantly more effective for damage detection than the latter. Furthermore, the capability of the proposed method for model updating in the presence of measurement and mass modeling errors is investigated.
机译:在早期阶段检测结构损伤的必要性导致了各种程序的结构模型更新。在这方面,利用模式形状数据的基于灵敏度的模型更新方法被称为有效的工具。为此目的,需要精确估计模式形状的变化来实现成功的模型更新。在本文中,通过包括升温结构的损坏结构的测量自然频率来改善王氏方法。然后使用在评估结构参数的变化的评估时使用不完整的模式形状数据来解决灵敏度方程。通过桁架模型方法的提出方法获得的结果的比较研究表明,前者对损坏检测比后者更有效。此外,研究了所提出的模型方法在存在测量和质量建模误差的情况下更新的能力。

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