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An Experimental Demonstration Of Tailored Excitations For Improved Damage Detection In The Presence Of Operational Variability

机译:在操作可变性的情况下,量身定制的激励可以改善损伤检测的实验演示

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We have shown in previous work that the parameters governing the dynamic evolution of a system of ordinary differential equations may be modified via an evolutionary algorithm to yield excitations that improve damage detection sensitivity in a computational model of a structural health monitoring application. In this work we use the same method to develop improved excitations for an experimental system. Improvement in change detection sensitivity is shown for several generated excitations. In addition, we present an excitation that increases the robustness of the damage detection feature to the types of parameter perturbations that arise not from damage, but from environmental sources such as temperature change.
机译:我们在先前的工作中已经表明,可以通过演化算法修改控制常微分方程组动态演化的参数,以产生激励,从而在结构健康监测应用的计算模型中提高损伤检测的灵敏度。在这项工作中,我们使用相同的方法来为实验系统开发改进的激励。对于几种产生的激励,变化检测灵敏度的提高已显示出来。此外,我们提出了一种激励,可以将损坏检测功能的鲁棒性提高到参数摄动的类型,这种摄动不是源于损坏,而是源于环境因素(例如温度变化)。

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