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A model-based approach for statistical assessment of detection and localization performance of guided wave-based imaging techniques

机译:基于模型的导波成像技术检测和定位性能的统计评估方法

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This article aims at providing a framework for assessing the detection and localization performance of guided wave–based structural health monitoring imaging systems. The assessment exploits a damage identification metric providing a diagnostic of the structure from an image of the scatterers generated by the system, allowing detection, localization, and size estimation of the damage. Statistical probability of detection and probability of localization curves are produced based on values of the damage identification metric for several damage sizes and positions. Instead of relying on arduous measurements on a significant number of structures instrumented in the same way, a model-based approach is considered in this article for estimating probability of detection and probability of localization curves numerically. This approach is first illustrated in a simplistic model, which allows characterizing the robustness of the structural health monitoring system for various levels of noise in test signals. An experimental test case using a more realistic case with an artificial damage is then considered for validating the approach. A good agreement between experimental and numerical values of the damage identification metric and derived probability of detection and probability of localization curves is observed.
机译:本文旨在为评估基于导波的结构健康监测成像系统的检测和定位性能提供一个框架。该评估利用了一种损坏识别度量标准,该度量可以根据系统生成的散射体图像对结构进行诊断,从而可以对损坏进行检测,定位和大小估算。基于几种损坏大小和位置的损坏识别指标的值,可以生成统计的检测概率和定位曲线的概率。本文不再考虑对以相同方式检测的大量结构进行艰苦的测量,而是考虑采用基于模型的方法来以数字方式估计检测概率和定位曲线的概率。首先以简化模型说明该方法,该模型可针对测试信号中各种噪声水平来表征结构健康监测系统的鲁棒性。然后考虑使用更实际的案例并进行人为破坏的实验测试案例来验证该方法。观察到损伤识别度量的实验值和数值与导出的检测概率和定位曲线的概率之间有很好的一致性。

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