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基于智能优化算法的供水管网漏水点定位
引用本文:刘书明,王欢欢,徐锦华,刘文君. 基于智能优化算法的供水管网漏水点定位[J]. 同济大学学报(自然科学版), 2014, 42(5): 0740-0744
作者姓名:刘书明  王欢欢  徐锦华  刘文君
作者单位:清华大学 环境学院, 北京 100084;清华大学 环境学院, 北京 100084;北京市自来水集团, 北京 100031;清华大学 环境学院, 北京 100084
基金项目:“十二五”国家科技支撑计划(2012ZX07408-002)
摘    要:针对城市供水管网的爆管事故,基于管网水力学模型和管网水压监测点的监测信息,利用3种智能优化算法——杜鹃算法、遗传算法和粒子群算法,建立了爆管定位模型,并在2个算例管网中进行了测试.2个算例管网的运行结果显示,杜鹃算法由于其调节参数少,快速搜寻能力强,在爆管定位的智能优化算法中显示了更优秀的定位能力,在小规模算例管网中可以实现对爆管点的定位,在较大规模的算例管网中也可以实现90%以上的定位寻优效果,显示了强大的算法应用可扩展性.

关 键 词:给水管网  漏水点定位  智能优化算法
收稿时间:2013-06-29
修稿时间:2014-01-15

Identification of Leakage Location Based on Modern Optimization Algorithms
LIU Shuming,WANG Huanhuan,XU Jinhua and LIU Wenjun. Identification of Leakage Location Based on Modern Optimization Algorithms[J]. Journal of Tongji University(Natural Science), 2014, 42(5): 0740-0744
Authors:LIU Shuming  WANG Huanhuan  XU Jinhua  LIU Wenjun
Affiliation:School of Environment, Tsinghua University, Beijing 100084, China;School of Environment, Tsinghua University, Beijing 100084, China;Beijing Waterworks Group, Beijing 100031, China;School of Environment, Tsinghua University, Beijing 100084, China
Abstract:The paper presents an algorithm for the location of sudden bursts in combination with both continuous monitoring of pressure and hydraulic model computation. The Cuckoo Search, genetic algorithm and particle swarm approaches were employed to identify the location of leakage. Their performances were compared. The results show that the Cuckoo Search has a better performance in terms of searching speed and parameter requirement among the three optimization algorithms. The case study results reveal the potential of the proposed burst location identification technique in a real life water distribution system.
Keywords:water distribution system   leakage location   modern optimization algorithm
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