Detection of an Existing Local Loss in a Water Distribution System

2013 ◽  
Vol 353-356 ◽  
pp. 2965-2968
Author(s):  
Di Xiao ◽  
Jian Wen Liang

Water distribution system is one of the most critical facilities in cities, and is more fragile compared with other structures. Losses in a water distribution system are often existed before health monitoring is implemented. This paper proposes to detect an existing local loss in a water distribution system on the basis of optimal monitoring of water pressure. The local loss is assumed at different positions with different extents, and pressures at monitoring stations is calculated, and the loss is then detected by minimizing the difference between the calculated and monitoring pressures at the monitoring stations. The efficiency is validated by example analysis. It is shown that an existing local loss is more reliably detected in a water distribution system with optimal monitoring.

2018 ◽  
Vol 20 (6) ◽  
pp. 1323-1342 ◽  
Author(s):  
Nathan Sankary ◽  
Avi Ostfeld

Abstract Placing fixed water quality monitoring stations in a water distribution system can greatly improve the security of the system via prompt detection of poor water quality. In the event that a harmful substance is injected into a water distribution system, large populations can be put at risk of exposure to the contaminant. Promptly detecting the presence of a contaminant will reduce the number of people put at risk of exposure. However, to protect against a wide variety of possible contaminants, a water quality monitoring station will need to identify contamination via recognition of anomalous changes in a suite of surrogate water quality indicators (chlorine, pH, etc.). This work attempts to place water quality monitoring stations within the water distribution at locations that best detect contamination events via surrogate water quality signals. Networks of water quality monitoring stations are designed to minimize the population affected prior to contamination event detection, and simultaneously minimize the expected number of false positive detections, under uncertain water quality conditions. Solutions generated in this study are compared to solutions designed via classical detection methods. Results show the sensor networks designed without consideration to detection via surrogate water quality parameters have higher false positive detection rates.


Sign in / Sign up

Export Citation Format

Share Document