Better Understanding of the Capacity of Pressure Sensor Systems to Detect Pipe Burst within Water Distribution Networks

• Published in: Journal of water resources planning and management 2018-07, Vol.144 (7)
• Main Authors: Qi, Zhexian, Zheng, Feifei, Guo, Danlu, Maier, Holger R, Zhang, Tuqiao, Yu, Tingchao, Shao, Yu
• Format: Article
• Language: English
• Subjects: Bursting; Bursts; Capacity; Decision making; Deployment; Detection; Distribution; Distribution management; Leakage; Localization; Methods; Networks; Nodes; Outflow; Pipes; Pressure; Pressure sensors; Sensors; Spatial distribution; Technical Papers; Water distribution; Water engineering; Water resources management
• ISSN: 0733-9496; 1943-5452
• DOI: 10.1061/(ASCE)WR.1943-5452.0000957

AbstractLeakage or pipe burst detection, often carried out by using the pressure sensor systems (PSSs) within a water distribution network (WDN), is critical to enable such networks to operate in a safe manner. The majority of previous studies have focused on either the advancement of detection equipment or the development of detection algorithms (leakage localization or sensor deployment). In contrast, this paper proposes a methodology to investigate the underlying capacity of existing PSSs for pipe burst detection using a set of quantitative metrics. These metrics focus on the identification of (1) nodes where bursts cannot be detected by the PSS (undetectable nodes); (2) undetectable demands, derived from the demands of undetectable nodes; (3) detection dimension, representing the number of sensors that can simultaneously detect a burst at a node; (4) the spatial region where bursts within each subregion can be detected by a particular sensor with a minimum outflow; and (5) the detectable threshold, which indicates the minimum burst outflow of each node triggering its associated pressure sensor. The proposed methodology has been applied to two real-world WDNs with varying sizes and configurations. Results show that the former two metrics can indicate the spatial distribution of the nodes at which bursts can be detected, and the latter three metrics can successfully reveal the PSS’s detection dimension and spatial regions, as well as the detectable threshold of each node. Such improved understanding offers guidance to develop effective burst-management strategies and to facilitate decision-making processes regarding sensor placement and burst localization.