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首页> 外文期刊>Journal of Sound and Vibration >ARX model-based damage sensitive features for structural damage localization using output-only measurements
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ARX model-based damage sensitive features for structural damage localization using output-only measurements

机译：基于ARX模型的损伤敏感特征，可通过仅输出的测量来进行结构损伤定位

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The study proposes a set of four ARX model (autoregressive model with exogenous input) based damage sensitive features (DSFs) for structural damage detection and localization using the dynamic responses of structures, where the information regarding the input excitation may not be available. In the proposed framework, one of the output responses of a multi-degree-of-freedom system is assumed as the input and the rest are considered as the output. The features are based on ARX model coefficients, Kolmogorov-Smirnov (KS) test statistical distance, and the model residual error. At first, a mathematical formulation is provided to establish the relation between the change in ARX model coefficients and the normalized stiffness of a structure. KS test parameters are then described to show the sensitivity of statistical distance of ARX model residual error with the damage location. The efficiency of the proposed set of DSFs is evaluated by conducting numerical studies involving a shear building and a steel moment-resisting frame. To simulate the damage scenarios in these structures, stiffness degradation of different elements is considered. It is observed from this study that the proposed set of DSFs is good indicator for damage location even in the presence of damping, multiple damages, noise, and parametric uncertainties. The performance of these DSFs is compared with mode shape curvature-based approach for damage localization. An experimental study has also been conducted on a three-dimensional six-storey steel moment frame to understand the performance of these DSFs under real measurement conditions. It has been observed that the proposed set of DSFs can satisfactorily localize damage in the structure. (C) 2015 Elsevier Ltd. All rights reserved.
机译：该研究提出了一组四个基于ARX模型（具有外源输入的自回归模型）的损伤敏感特征（DSF），用于使用结构的动态响应进行结构损伤检测和定位，其中可能无法获得有关输入激励的信息。在所提出的框架中，多自由度系统的输出响应之一被假定为输入，其余被认为是输出。这些功能基于ARX模型系数，Kolmogorov-Smirnov（KS）测试统计距离以及模型残差。首先，提供数学公式来建立ARX模型系数的变化与结构的规范化刚度之间的关系。然后描述KS测试参数，以显示ARX模型残余误差的统计距离与损伤位置的敏感性。通过进行涉及剪力建筑物和钢制抗弯框架的数值研究，评估了建议的DSF的效率。为了模拟这些结构中的损坏情况，考虑了不同元素的刚度退化。从这项研究中可以看出，即使在存在阻尼，多重损伤，噪声和参数不确定性的情况下，建议的DSF集也可以很好地指示损伤的位置。将这些DSF的性能与基于模式形状曲率的损伤定位方法进行了比较。还已经对三维六层钢矩框架进行了实验研究，以了解这些DSF在实际测量条件下的性能。已经观察到，所提出的一组DSF可以令人满意地定位结构中的损坏。 （C）2015 Elsevier Ltd.保留所有权利。

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