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Malfunction Detection and Localization Algorithm for Wireless Sensor Network

机译:无线传感器网络故障检测与定位算法

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摘要

Recently, the graph signal processing paves a new way to analyze the data residing in the networks. In this letter, the graph signal processing theory is applied to detect and localize the malfunctioning sensors caused by the sheer quality and complicated deploying environment of wireless sensor networks. Based on the high-pass graph filter and the history data information, a two-channel graph filtering structure is constructed to not only detect the malfunctioning phenomenon but also determine the positions of the malfunctioning sensors. The proposed scheme is operated on vertex domain, in which the graph Fourier transform is not required. Numerical examples conducted on the real-world data on sensor networks and artificial attack on IEEE bus grids demonstrate the effectiveness of the proposed algorithm.
机译:最近,图形信号处理铺平了一种新方法来分析驻留在网络中的数据。在这封信中,应用图形信号处理理论来检测和定位由无线传感器网络的纯粹质量和复杂的部署环境引起的故障传感器。基于高通图滤波器和历史数据信息,构造了双通道图滤波结构,不仅可以检测故障现象,还可以确定故障传感器的位置。所提出的方案在顶点域中运行,其中不需要图形傅里叶变换。在IEEE总线网格上的现实世界数据上进行的数值示例和IEEE总线网格上的人工攻击展示了所提出的算法的有效性。

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