HE Rui,YU Ting-chao,SHAO Yu.Optimal Placement Method of Pressure Monitoring Points for Monitoring Water Supply Pipe Burst[J].China Water & Wastewater,2020,36(17 17):36-40.
Optimal Placement Method of Pressure Monitoring Points for Monitoring Water Supply Pipe Burst
China Water & Wastewater[ISSN:1000-4062/CN:12-1073/TU]
volume:
第36卷
Number:
17 17
Page:
36-40
Column:
Date of publication:
2020-09-01
- Keywords:
- pipe burst; pressure monitoring point; heuristic algorithm; pressure variation matrix; burst threshold
- Abstract:
- In order to explore an optimal placement method of pressure monitoring points suitable for monitoring pressure change of each node when pipe burst, a heuristic algorithm was proposed through processing and analyzing the water supply network model and historical statistics of JX city in East China. Node pressure burst threshold at each node was first acquired by statistically analyzing historical data of the water supply network. Pressure of each node was obtained by compensating computation under standard condition. A virtual node was then added in the middle of the pipe to simulate pipe burst. A given efflux coefficient was set to obtain the corresponding pipe burst pressure of each node through iterative calculations, and pressure difference was calculated to obtain the pressure variation matrix. The judgment matrix ranging between 0-1 of pipe burst was obtained by comparing the variable value in the matrix with the threshold value. An appropriate monitoring point layout order was obtained through the matrix processing analysis and programming calculation. When five monitoring points were arranged in a total of 640 pipe sections, 467 pipe sections could be detected, accounting for 73.0% of the total pipes. When 10 monitoring points were set up, 545 pipe sections (accounting for 85.2% of the total pipes) could be detected. Therefore, it could be seen that the monitoring range of pressure monitoring points arranged by this method was wide. Under the most economical condition, the monitoring points could be evenly distributed in the pipe network, and the pipe burst could be effectively monitored.
Last Update:
2020-09-01