Detecting and Localizing Leakages in Water Distribution Systems Using a Two-Phase Model
Publication: Journal of Water Resources Planning and Management
Volume 148, Issue 10
Abstract
Rapid and accurate detection/localization of leakage is important to preventing severe consequences in water distribution systems, such as loss of water resources and sinkholes. This study presents a novel two-phased approach to leakage detection and localization as a part of the ‘Battle of Leakage Detection and Isolation Methods’ (BattLeDIM). During Phase 1, data classification, data feature scaling, and data verification were performed, where individual leakage events were detected using the K-mean clustering algorithm. In Phase 2, the location of the leakage was identified using a trial-and-error optimization procedure. During the process, an emitter coefficient is assigned to each node, and the node that has the minimum error between the supervisory control and data acquisition (SCADA) measurements and the simulation results is determined as the leakage location. The results show that there were 23 real leakage events, none of which were detected or localized. Finally, ideas for real leak detection are provided, and a direction to overcome the limitations of existing leak detection techniques is presented.
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Data Availability Statement
All models, and all code generated or used during the study, are proprietary or confidential in nature, and all data used during the study are available from the corresponding author upon reasonable request.
Acknowledgments
This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (No. 2021R1C1C2004896) and by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (No. 2021R1G1A1003295).
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Published In
Journal of Water Resources Planning and Management
Volume 148 • Issue 10 • October 2022
Copyright
© 2022 American Society of Civil Engineers.
History
Received: Apr 30, 2021
Accepted: Jun 7, 2022
Published online: Aug 12, 2022
Published in print: Oct 1, 2022
Discussion open until: Jan 12, 2023
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