Study On Water Supply Network Model Calibration And Leakage Location

The hydraulic model is the basis for the optimal dispatching and management control of the urban water supply network,and the model check of the network is a necessary link in the establishment of the water supply network model.Optimal check of the hydraulic model parameters of the pipe network based on the measured operating data of the pipe network is the key to ensuring the accuracy of the pipe network operation and hydraulic calculation.This paper uses a combination of laboratory simulation and theoretical analysis,and proposes an optimization model for checking the parameters of a water supply network model based on pressure analysis.The main research results obtained are as follows:(1)A laboratory-scale water supply system has been established.The system simulates urban water supply by setting up pump stations(water sources),looped pipe networks,water use nodes,water leakage nodes,pressure monitoring points,flow monitoring points,etc.,which can be used for subsequent water supply pipes.Network hydraulic model parameter optimization and analysis provide test site and test data.(2)The objective function and constraint conditions of parameter optimization for the hydraulic model of the water supply network are proposed,and a new immune genetic algorithm(IGA)is be used.Through the verification of the model,the simulation accuracy reaches the domestic hydraulic model pressure calibration nuclear standards.(3)Using the verified hydraulic model,a study on the optimal layout of newly added pressure monitoring points was carried out.The results show that compared with the traditional empirical method,this method can make the monitoring results more accurate on the basis of fewer new pressure monitoring points.(4)Combined with actual engineering cases,based on the water supply network of a town in the north,the previous model verification,monitoring point layout and other studies were verified,and then the leakage damage location analysis model of the water supply network was established in conjunction with BP neural network.