State Analysis And Quantification Of Leakage In Water Supply Network

China’s vast territory,the water supply pipeline has amounted to hundreds of thousands of kilometers,and in recent years,urban expansion speed,although with the development of the city,a large number of network obtained the reconstruction and expansion,but many old living area is located in the central area of a city,there are still a number of buried in the old pipe network running,because of its backward facilities and network disrepair,The leakage phenomenon is quite serious.Leakage is different from pipe burst,most of which will gradually evolve from small leakage into big accidents,so a comprehensive diagnosis of pipe network before its evolution has become an important topic.At present,the quantitative research on pipeline leakage is relatively scarce.This paper mainly studies the amount of leakage in the process of water supply pipeline leakage.In the process of pipe network operation,leakage will be affected by various aspects,such as water pressure,water supply flow,pipeline properties,etc.These influencing factors are interrelated,and their combined effect will have a huge impact on the quantitative study of leakage.The traditional exponential model is difficult to accurately calculate the size of the loss,mainly because the loss coefficient is difficult to determine in the application of the exponential model,and the loss area is constantly changing in the process of loss,which directly affects the determination of the loss index.In view of the dynamic change of the loss area affecting the loss coefficient,this study applied the fluid-structure coupling technology to find out the relationship between the loss area and water pressure under different types of leakage orifice,and then obtained the loss amount under different water pressure through the experimental method.The curve fitting method is applied to the curve fitting of the loss area ratio and the loss coefficient in the process of leakage,and the calculation formula of the loss coefficient and the ratio of water leakage area is obtained,which provides reference for the calculation of leakage.In order to deeply study the influence of leakage on water supply pipe network,a hydraulic analysis method is proposed to establish a water supply pipe network simulation experiment platform to conduct hydraulic analysis on the pipe network operating under leakage condition.The operating state of the pipe network under leakage condition is reflected by the pressure and flow change of each node.In order to simplify the leakage research of water supply pipe network,the hydraulic modeling of the pipe network is done through the corresponding mathematical model,and the hydraulic model is established by using EPA on the experimental platform constructed,and the real value is compared with the simulated value,and the reliability of the established model is illustrated by comparison.By using the hydraulic model,the variation law of the joint pressure of the pipe network under the leakage condition is obtained,which provides a theoretical basis for the leakage research of the pipe network.In recent years,the construction of smart cities has been developing continuously,but the diagnosis technology of municipal pipe network is relatively lagging behind.In this paper,the artificial neural network is used to predict the amount of water lost in the leakage process of pipe network.Leakage of pipeline leakage occurs near the point of water flow will produce pressure fluctuation,the fluctuation will affect the network running status,and pipe network system of different funnelled reaction conditions vary,it can be different funnelled data corresponding to different leakage of pipe net model,artificial neural network can learn through sample data to get the best mapping rules,Then identify the various operating conditions of pipe network leakage.The water supply pipe network simulation platform is used to carry out leakage experiment to obtain the pressure data of each node of the pipe network when leakage occurs.To improve the efficiency of artificial neural network prediction,using genetic algorithm and particle swarm algorithm to optimize neural network,and then set up the GA-BP neural network and PSO-BP neural network to forecast the state of pipeline leakage loss,and using the sample data after the training,the construction of artificial neural network can be judged pipeline leakage of different patterns,It provides a method to study the leakage of pipeline network.