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A field implementation of linear prediction for leak-monitoring in water distribution networks

机译:水分配网络泄漏监测线性预测的现场实现

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Water distribution networks (WDNs) are complex systems that are subjected to stresses due to a number of hydraulic and environmental loads. As a result, system leaks remain an unavoidable reality. Leaks which are not large enough to become visible at the street level can often go undetected for prolonged periods of time; the presence of smaller leaks can be concealed in system variability. The current paper addresses the problem of leak-detection and localization in WDNs, using a data-driven methodology which utilizes linear prediction (LP) theory. LP has a relatively simple mathematical formulation and has been shown in laboratory studies to effectively capture leak-induced signatures in fluid-filled pipes. In this paper, the performance of LP for leak-detection is verified, using field data in an operational WDN. In addition, a two-part localization approach is proposed which utilizes LP pre-processed data, in tandem with the traditional cross-correlation approach. Results of the field study show that the proposed method is able to perform both leak-detection and localization in full-scale systems using relatively short time signal lengths. This is advantageous in continuous monitoring situations as this minimizes data transmission requirements, which are one of the main impediments to full-scale implementation and deployment of leak-detection technology. In addition to the analysis results, a novel hydrant-mounted data-acquisition system is proposed, along with its unique hardware and software capabilities.
机译:水分配网络(WDN)是由于许多液压和环境载荷而受到应力的复杂系统。结果,系统泄漏仍然是一个不可避免的现实。在街道水平上不足以可见的泄漏通常可以在长时间的时间内未被发现;可以在系统变异性中隐藏较小泄漏的存在。目前纸张使用利用线性预测(LP)理论的数据驱动方法来解决WDN中的泄漏检测和定位问题。 LP具有相对简单的数学制剂,并且已经在实验室研究中显示,以有效地捕获流体填充管道中的泄漏诱导的签名。在本文中,使用操作WDN中的现场数据来验证LP对泄漏检测的性能。此外,提出了一种双零件定位方法,其利用LP预处理数据,与传统的互相关方法进行串联。实地研究结果表明,该方法能够使用相对短的时间信号长度在满量程系统中执行泄漏检测和定位。这在连续的监视情况下是有利的,因为这最小化了数据传输要求,这是满量程实现和泄漏检测技术部署的主要障碍之一。除了分析结果之外,提出了一种新型消防栓数据采集系统,以及其独特的硬件和软件功能。

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