一种基于虚拟压力分区的供水管网漏损区域识别方法

宋文轲; 王杉月; 陶涛

doi:10.13205/j.hjgc.202307025

一种基于虚拟压力分区的供水管网漏损区域识别方法

doi: 10.13205/j.hjgc.202307025

同济大学环境科学与工程学院, 上海 200092

基金项目:

国家水体污染与治理科技重大专项（2017ZX07201001）

详细信息

作者简介:
宋文轲(1998-),男,硕士研究生,主要研究方向为城市水资源与给排水管网设计运行最优化。2030504@tongji.edu.cn

通讯作者:
陶涛(1974-),女,教授,主要研究方向为城市水资源与给排水管网设计运行最优化。taotao@tongji.edu.cn

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出版历程
- 收稿日期: 2022-03-10

A LEAKAGE ZONE IDENTIFICATION METHOD FOR WATER DISTRIBUTION NETWORKS BASED ON VIRTUAL PRESSURE PARTITION

College of Environmental Science and Engineering, Tongji University, Shanghai 200092, China

摘要

摘要: 针对供水管网的漏损识别问题，提出了一种基于虚拟压力分区的漏损区域识别方法。通过虚拟压力分区降低漏损识别问题的维度，利用遗传算法优化真实漏损流量在管网空间中的分布，建立了各区域的漏损水量与漏损率的识别方法。该方法分为虚拟压力分区与漏损区域识别2个步骤：前者基于改进的K均值聚类算法，将管网节点划分为空间位置邻近、平均自由水头相似、拓扑结构连通的不同区域；后者以区域比例系数为决策变量，以最小化测压点处压力的模拟值与实测值差异为优化目标，实现各区域真实漏损情况识别。基于Z市L镇供水管网8号分区设计小型算例，验证了该方法对不同漏损工况识别的准确性。随后利用Z市L镇供水管网进行实际工程应用，结果表明，该方法对管网节点划分合理，管网中漏损严重区域的识别结果与实际情况相吻合，可以辅助大型供水管网的漏损检测工作。
- 漏损区域识别 /
- 虚拟压力分区 /
- 真实漏损 /
- 优化计算 /
- K均值聚类
Abstract: For the problem of leakage identification of water distribution networks, this paper proposed a leakage identification method based on virtual pressure partition. The dimension of the leakage identification problem was reduced by virtual pressure partition of water distribution networks, and the distribution of real leakage flow in the network was optimized by a genetic algorithm. The method was divided into virtual pressure partition and leakage zone identification. Firstly, based on the improved K-means clustering algorithm, the network nodes were divided into different regions with adjacent locations, similar average free water heads and connected topological structures. Secondly, the regional proportional coefficient was taken as the decision variable, and the objective function was to minimize the difference between the simulated value and the measured value at the pressure measuring point, and the real leakage situation of each region was identified. A small verification case was designed based on the No. 8 area of the water distribution network in L Town, Z City, to verify the accuracy of the method in identifying different leakage conditions. Subsequently, the water distribution network in L Town was also used for practical engineering application. The results show that the proposed method divides the nodes well, and the identification results of the serious leakage area in the network are consistent with the actual situation, which can assist in the leakage detection of large water distribution networks.
- leakage zone identification /
- virtual pressure partition /
- real leakage /
- optimization /
- K-means clustering

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