Enhanced detection through low-order stochastic modeling for guided-wave structural health monitoring
Enhanced detection through low-order stochastic modeling for guided-wave structural health monitoring
复制标题
DOI：
10.1177/1475921711414232
复制
发表时间：
2012-03
期刊：
影响因子：
--
通讯作者：
Eric B. Flynn;M. Todd;A. Croxford;B. Drinkwater;P. Wilcox
中科院分区：
文献类型：
--
作者：
Eric B. Flynn;M. Todd;A. Croxford;B. Drinkwater;P. Wilcox
导波结构健康监测提供了有效的缺陷检测和大型板状结构定位的潜力。本文的目的是证明导波结构健康监测的性能可以量化，预测，并通过基本的随机建模和应用程序的似然检测器增强复杂结构。这些都是必要的步骤，使这种结构健康监测技术，以更强大的安全关键结构上使用。在几个位置引入几种尺寸的损伤之前和之后，以及在存在大噪声过程的情况下，使用具有几何复杂性（加强件）的铝板上的稀疏换能器阵列进行了广泛的测量。这使得一个完整的统计处理的性能评价使用修改的标准接收器工作特性曲线。随机建模的结合产生了平均44%的损失模式之间的检测失误减少，在某些情况下减少高达95%。
Guided wave structural health monitoring offers the potential for efficient defect detection and localization on large plate-like structures. The aim of this article is to demonstrate that the performance of guided wave structural health monitoring on complex structures can be quantified, predicted, and enhanced through basic stochastic modeling and application of a likelihood-based detector. These are necessary steps in enabling such structural heath monitoring techniques to be used more robustly on safety-critical structures. Extensive ensembles of measurements were taken using a sparse array of transducers on an aluminum plate with geometric complexities (stiffeners), before and after introducing several sizes of damage at several locations, and in the presence of large noise processes. This enabled a full statistical treatment of performance evaluation using a modification of the standard receiver operating characteristic curve. The incorporation of stochastic modeling produced on average a 44% reduction in missed detections among the damage modes tested, with up to a 95% reduction in some cases.