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Multiobjective Contaminant Sensor Network Design for Water Distribution Systems

机译:供水系统的多目标污染物传感器网络设计

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A contaminant intentional intrusion into a water distribution system is one of the most difficult threats to address. This is because of the uncertainty of the type of the injected contaminant and its consequences, and the uncertainty of the location and intrusion time. An online contaminant sensor network is the main constituent to enhance the security of a water distribution system against such a threat. In this study a multiobjective model for water distribution system optimal sensor placement using the nondominated sorted genetic algorithm II is developed and demonstrated using two water distribution systems of increasing complexity. Tradeoffs between three objectives are explored: (1) sensor detection likelihood; (2) sensor detection redundancy; and (3) sensor expected detection time. Pareto fronts are plotted for pairs of conflicting objectives, and simultaneously for all three. A contamination event heuristic sampling methodology is developed for overcoming the problem of contamination event sampling.
机译:有意侵入水分配系统的污染物是要解决的最困难的威胁之一。这是因为所注入污染物的类型及其后果的不确定性,以及位置和侵入时间的不确定性。在线污染物传感器网络是增强供水系统抵御此类威胁的安全性的主要组成部分。在这项研究中,开发了一种使用非控制分类遗传算法II的水分配系统最优传感器放置的多目标模型,并使用两个复杂性不断提高的水分配系统进行了演示。探讨了三个目标之间的权衡:(1)传感器检测的可能性; (2)传感器检测冗余; (3)传感器的预期检测时间。对成对的冲突目标绘制了帕累托前沿,同时对所有这三个目标绘制了帕累托前沿。开发了一种污染事件启发式采样方法,以解决污染事件采样的问题。

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