Research On Pipeline Network Leakage Location And Early Warning Based On CS Algorithm Optimization

With the rapid development of society and economy,people’s demand for water resources increases,which makes the water supply pipe network system load larger,resulting in frequent occurrence of pipe network leakage incidents,bringing huge economic losses and security risks to the society.In order to effectively solve the leakage problem of the pipe network,this paper will build a hydraulic model for the purpose of studying the leakage location of the water supply pipe network,optimize the arrangement of pressure monitoring points,realize the location and early warning of the leakage location of the pipe network,effectively alleviatethe current situation of water shortage,reduce the leakage rate of the pipe network system and improve the safety and reliability of urban water supply.The specific research work and contributions are as follows:(1)Construct a hydraulic model of the water supply network.This research,which takes Fosspoly1 pipe network as an example,uses the basic data of the pipe network’s attributes and hydraulics to build its topology on the EPANET modeling platform,and simplifies and checks the pipe network based on the modeling process of the hydraulic model.And then perform hydraulic calculation and analysis on the constructed hydraulic model according to hydraulic principles.The results show that the Fosspoly1 hydraulic model constructed in this study based on modeling principles and methods effectively simulates the actual operating state of the pipeline network,and can lay a foundation for subsequent research on monitoring point optimization,leakage location and early warning.(2)Optimize the arrangement of pressure monitoring points based on the hydraulic model.In the actual pipe network,the layout density and location of pressure monitoring points have a great influence on the operating status of the monitoring pipe network.Based on the hydraulic model of Fosspoly1 pipe network,the pressure sensitivity matrix of the model is established and standardized.The K-means clustering algorithm is used for analysis and calculation,and the node nearest to the centroid is selected as the layout position of pressure monitoring points.The results show that the optimized pressure monitoring points are evenly distributed and representative in the pipeline network,which can effectively monitor the running state of the pipe network and provide data support for the subsequent leakage location research.(3)Leakage location of pipe network.This study uses the pressure-dependent leakage principle to construct a pipeline network leakage location model.Taking the Anytown pipeline network hydraulic model as an example,the Cuckoo Search(CS)and the traditional pipeline network leakage location algorithm are used to determine the number of monitoring points.,Leakage coefficient and other aspects of the leakage location results were analyzed.The results show that the CS algorithm has higher positioning accuracy than the traditional leakage location algorithm,and the more the number of monitoring points,the better the positioning effect.Then,according to the optimized layout results of the monitoring points of the above-mentioned Fosspoly1 hydraulic model,the CS algorithm based on parameter optimization was used to explore the leakage positioning effect of the pipeline network under different number of monitoring points and different leakage coefficients.The results show that the leakage location accuracy rate of the optimized CS algorithm exceeds 80%,which is higher than the accuracy rate before optimization.(4)Research on early warning of positioning results.The early warning analysis of the leakage location results of the water supply network help the water management personnel to discover and deal with the abnormal events in the pipeline network in time,reduce the economic cost of the traditional leak detection work,and provide decision guidance for the management of the water department.