Research And Design Of Water Supply Network Monitoring System Based On The Internet Of Things

The water supply network is the basic guarantee for a city's water operation.However,the leakage problem of the water supply network and how to supply water energy-efficiently have always been hot issues waiting to be solved.Because the high leakage rate of the traditional water supply network,and the slow repair response,the hidden danger of the water supply network cannot be found in time.In terms of leakage control,it can only rely on human inspection.In the aspect of water supply scheduling,the existing method is to distribute water according to the water consumption reports of various regions,which has low efficiency and high work intensity.The problems in the water supply network cannot be discovered in time.Therefore,the use of new technologies for real-time monitoring in the water supply network has become a hot issue for researchers.In view of the above problems,this research conducted a real-time monitoring study on the flow and pressure in the water supply network,and firstly proposed a water supply network monitoring system based on the Internet of Things.The monitoring nodes composed of electromagnetic flow meters and pressure transmitters are used to monitor the flow and pressure data of the water supply network in real time.The wireless communication gateway is responsible for the control of data collection and the process of data reception of each monitoring node,and sends the received data via GPRS to the monitoring and warning platform.The safety warning of the water supply network can be realized through analyzing the monitoring data.Because there are many monitoring nodes in different locations in the water supply network monitoring system.And when the time of monitoring data is different among the nodes,a large error will be caused to the monitoring data,and it will also cause great difficulties to the decision-making of the management personnel of the dispatched center.Therefore,this research conducted a time synchronization study among monitoring nodes,and established a time synchronization system among monitoring nodes.As a result,each monitoring node can be kept at the same time,the real-time flow and pressure data can be obtained more accurately,and the errors of early safety warning and decision can be reduced.While analyzing the operation data of the water supply network,this re search also studies the impact of flow and pressure on the operation of the water supply network and the corresponding measures.By coupling the flow and pressure of the pipeline network with the BP neural network algorithm optimized by genetic algorithm,the future trends of flow and pressure will be obtained.It will also provide technical support for the dispatch of the water supply network,and improve the operation efficiency and energy saving of it.