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A methodology for leak detection in water distribution networks using graph theory and artificial neural network

机译:采用图论和人工神经网络水分配网络泄漏检测方法

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摘要

Considering the scarcity of water resources, it is necessary to identify the leakage in Water Distribution Networks (WDNs). In this paper, a step-by-step method of WDN decomposition has been introduced for leak detection. First, the WDN is divided into two parts using the graph theory, then the part with leakage is identified using the results of pressure loggers and the artificial neural network. This process continues for the identified part to reach the limited leakage area. This method was applied to the Balerma WDN with five leakage scenarios including uncertainty of demand and pressure parameters. The results show that the proposed method can find the leakage area of WDNs with good accuracy.
机译:考虑到水资源的稀缺性,有必要识别水分配网络(WDN)的泄漏。在本文中,引入了用于泄漏检测的WDN分解的逐步方法。首先,使用图形理论将WDN分成两部分,然后使用压力记录器和人工神经网络的结果来识别具有泄漏的部分。该过程继续确定的部分达到有限的泄漏区域。该方法应用于Balerma WDN,具有五种泄漏场景,包括需求和压力参数的不确定度。结果表明,该方法可以以良好的准确度找到WDN的泄漏面积。

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