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Leakage fault detection in district metered areas of water distribution systems

机译:配水系统集中计量区的泄漏故障检测

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摘要

Fault tolerance and security in drinking water distribution operations are important issues that have received increased attention in the last few years. In this work the problem of leakage detection is formulated within a systems engineering framework, and a solution methodology to detect leakages in a class of distribution systems is proposed. Specifically, the case where water utilities use standard flow sensors to monitor the water inflow in a District Metered Area (DMA) is considered. The goal is to design algorithms which analyze the discrete inflow signal and determine as early as possible whether a leakage has occurred in the system. The inflow signal is normalized to remove yearly seasonal effects, and a leakage fault detection algorithm is presented, which is based on learning the unknown, time-varying, weekly periodic DMA inflow dynamics using an adaptive approximation methodology for updating the coefficients of a Fourier series; for detection logic the Cumulative Sum (CUSUM) algorithm is utilized. For reference and comparison, a second solution methodology based on night-flow analysis using the normalized inflow signal is presented. To illustrate the solution methodology, results are presented based on randomized simulated leakages and real hydraulic data measured at a DMA in Limassol, Cyprus.
机译:饮用水分配操作中的容错性和安全性是重要的问题,最近几年已受到越来越多的关注。在这项工作中,在系统工程框架内提出了泄漏检测问题,并提出了一种用于检测一类配电系统中泄漏的解决方法。具体而言,考虑了自来水公司使用标准流量传感器来监视区域计量区域(DMA)中的水流入的情况。目的是设计分析离散流入信号并尽早确定系统中是否发生泄漏的算法。对流入信号进行归一化以消除年度季节性影响,并提出了一种泄漏故障检测算法,该算法基于使用自适应近似方法学习未知,时变,每周定期DMA流入动态以更新傅立叶级数的系数;对于检测逻辑,使用累积和(CUSUM)算法。作为参考和比较,提出了使用归一化流入信号基于夜流分析的第二种解决方法。为了说明解决方案方法,基于塞浦路斯利马索尔DMA的随机模拟泄漏和实际水力数据给出了结果。

著录项

  • 来源
    《Journal of Hydroinformatics》 |2012年第4期|p.992-1005|共14页
  • 作者单位

    KIOS Research Center for Intelligent Systems and Networks, ECE Department, University of Cyprus, 75 Kallipoleos Av., CY-1678, Nicosia, Cyprus;

    KIOS Research Center for Intelligent Systems and Networks, ECE Department, University of Cyprus, 75 Kallipoleos Av., CY-1678, Nicosia, Cyprus;

  • 收录信息 美国《科学引文索引》(SCI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    adaptive learning; leakage detection; water distribution networks;

    机译:适应性学习;泄漏检测;供水网络;

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