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Stfuctural damage identification using static test data and changes in frequencies

机译:使用静态测试数据和频率变化识别结构损伤

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摘要

A structural damage identification algorithm using static test data and changes in natural frequencies is presented in this paper.: To locate damage in the structure, the Damage Signature Matching (DSM) technique is improved through a proper definition of' Measured Damage Signatures (MDS) and Predicted Damage Signatures (PDS). The effect of damage severity can be eliminated effectively as the result that the first-order approximation of changes in static deformation and natural frequencies are employed jointly in the damage signatures. The damage location, then, can be detected successfully by matching MDS with PDS. After obtaining the possible damage location, an iterative estimation scheme for solving non-linear optimization programming problems, which is based on the quadratic programming technique, is proposed to predict the damage extent. A remarkable characteristic of the present approach is that it can be directly applied in the cases of incomplete measured data. The correctness and the effectiveness of the algorithm are Proved by two examples: A planar truss model with the numerically simulated data and a beam with two- fixed ends, of which the static response and the natural frequencies are obtained experimentally. The results show that the proposed algorithm is efficient for the damage identification.
机译:本文提出了一种使用静态测试数据和固有频率变化的结构损伤识别算法。:为了确定结构中的损伤,通过正确定义“实测损伤特征”(MDS)改进了损伤特征匹配(DSM)技术。和预测的损坏签名(PDS)。由于在破坏特征中联合采用了静态变形和固有频率变化的一阶近似,因此可以有效消除破坏严重程度的影响。然后,通过将MDS与PDS匹配,可以成功检测到损坏位置。在获得可能的损伤位置后,提出了一种基于二次规划技术的求解非线性优化规划问题的迭代估计方案,以预测损伤程度。本方法的显着特征是它可以直接用于不完整的测量数据的情况。通过两个例子证明了该算法的正确性和有效性。一个具有数值模拟数据的平面桁架模型和一个两端固定的梁,通过实验获得了它们的静态响应和固有频率。结果表明,该算法对损伤的识别是有效的。

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