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Optimal tuning for an abrupt change detection algorithm: Application to an underground gallery structure health monitoring

机译:突变检测算法的最佳调整:在地下画廊结构健康监控中的应用

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The aim of this paper is to detect faults such as cracks in an underground structure to ensure its health monitoring. The proposed approach is based on an ARMAX modeling of a deformation sensor (a vibrating wire gauge), to generate a residual. This residual is then used by a statistical test, the dynamic cumulative sum, to generate a detection function which is compared to a threshold for decision. The main contribution of this paper is the use of the receiver operating characteristic curve to optimally tune the parameters of the statistical test and to have the best fault detection/false alarm rate. The originality of this work is that the receiver operating characteristic curve is used for two aims: First, to optimally tune the sliding windows width of the statistical test and second, to precisely tune the decision threshold. The effectiveness of the proposed method is highlighted on the application of an underground gallery structure health monitoring.
机译:本文的目的是检测诸如地下结构中的裂缝之类的故障,以确保对其进行健康监测。提出的方法基于变形传感器(振弦规)的ARMAX建模,以生成残差。然后,此残差将由统计测试(动态累积总和)使用,以生成检测功能,将其与决策阈值进行比较。本文的主要贡献是利用接收机的工作特性曲线来优化统计测试的参数,并具有最佳的故障检测/误报率。这项工作的独创性是将接收机的工作特性曲线用于两个目的:首先,优化调整统计测试的滑动窗口宽度;其次,精确调整决策阈值。地下画廊结构健康监测的应用突出了所提方法的有效性。

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