ZHAOWen-xuan,DUKun,MENGFan-yi,et al.Multi-objective Optimization of Water Pressure Monitoring Points for Pipe Burst Detection in Water Supply Networks[J].China Water & Wastewater,2023,39(7):57-62.
Click Copy

Multi-objective Optimization of Water Pressure Monitoring Points for Pipe Burst Detection in Water Supply Networks

China Water & Wastewater[ISSN:1000-4062/CN:12-1073/TU] volume: 第39卷 Number: 第7期 Page: 57-62 Column: Date of publication: 2023-04-01
Author(s):
ZHAO　Wen-xuan1;  DU　Kun1;  MENG　Fan-yi2;  LUO　Xiong-wu3;  ZHOU　Ming1;  SONG　Zhi-gang1
（1. Faculty of Civil Engineering and Mechanics， Kunming University of Science and Technology， Kunming 650500， China； 2. Yunnan Design Institute Group Co. Ltd.， Kunming 650100， China； 3. Kunming Guanfang Architecture & Design Inc.， Kunming 650051， China）
Keywords:
water supply network;  pipe burst;  water pressure monitoring point;  multi-objective optimization;  non-dominated sorting differential evolution algorithm
Abstract:
The single objective optimization algorithm has low computational efficiency and poor solution set quality in the process of solving the optimal arrangement model of water pressure monitoring points. A multi-objective non-dominated sorting differential evolution (NSDE) algorithm was proposed to solve these problems. Firstly, the nodes added in the middle of each pipe segment were distributed a pipe burst flow and the pipe burst simulation was carried out successively, and the pipe burst event judgment matrix was generated according to the pressure change value of each node. Then, a mathematical model for optimizing the arrangement of monitoring points was constructed with the objective function of minimizing the number of monitoring points and maximizing the leakage volume of pipe burst detection, and the solution was obtained by using NSDE algorithm. Finally, the arrangement characteristics of monitoring points in Pareto solution were analyzed and discussed. The model was solved by single objective genetic algorithm, multi-objective non-dominated sorting genetic algorithm (NSGA-Ⅱ) and NSDE algorithm respectively exemplified by the net3 water supply network. The multi-objective NSDE algorithm has higher computational efficiency and better optimal solution set quality, and the multiple layout schemes corresponding to its Pareto solution sets provide flexibility for monitoring site arrangement in actual projects.
Last Update: 2023-04-01