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Resilient Sensor Placement for Fault Localization in Water Distribution Networks

机译:弹性传感器布置,用于供水管网中的故障定位

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In this paper, we study the sensor placement problem in urban water networks that maximizes the localization of pipe failures given that some sensors give incorrect outputs. False output of a sensor might be the result of degradation in sensor's hardware, software fault, or might be due to a cyber attack on the sensor. Incorrect outputs from such sensors can have any possible values which could lead to an inaccurate localization of a failure event. We formulate the optimal sensor placement problem with erroneous sensors as a set multicover problem, which is NP-hard, and then discuss a polynomial time heuristic to obtain efficient solutions. In this direction, we first examine the physical model of the disturbance propagating in the network as a result of a failure event, and outline the multi-level sensing model that captures several event features. Second, using a combinatorial approach, we solve the problem of sensor placement that maximizes the localization of pipe failures by selecting m sensors out of which at most e give incorrect outputs. We propose various localization performance metrics, and numerically evaluate our approach on a benchmark and a real water distribution network. Finally, using computational experiments, we study relationships between design parameters such as the total number of sensors, the number of sensors with errors, and extracted signal features.
机译:在本文中,我们研究了城市供水网络中的传感器布置问题,该问题在某些传感器输出不正确的情况下最大化了管道故障的定位。传感器的错误输出可能是由于传感器硬件降级,软件故障或由于对传感器的网络攻击而导致的。来自此类传感器的错误输出可能具有可能导致故障事件定位不准确的任何可能值。我们将具有错误传感器的最优传感器放置问题公式化为一个设置为NP-难的多重覆盖问题,然后讨论多项式时间启发式算法以获得有效的解决方案。在这个方向上,我们首先检查由于故障事件而在网络中传播的干扰的物理模型,并概述捕获了多个事件特征的多级传感模型。其次,使用组合方法,我们通过选择m个传感器(最多e个给出错误的输出)来解决传感器放置问题,从而最大程度地解决管道故障。我们提出了各种本地化绩效指标,并在基准和真实的供水网络上对我们的方法进行了数字评估。最后,通过计算实验,我们研究了设计参数之间的关系,例如传感器的总数,有错误的传感器的数量以及提取的信号特征。

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