Water leakage detection and localization using hydraulic modeling and classification

A significant percentage of treated water is lost due to leakage in water distribution systems. The state-of-the-art leak detection and localization schemes use a hybrid approach to hydraulic modeling and data-driven techniques. Most of these works, however, focus on single leakage detection and loc...

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Autores principales:	Eliyas Girma Mohammed, Ethiopia Bisrat Zeleke, Surafel Lemma Abebe
Formato:	article
Lenguaje:	EN
Publicado:	IWA Publishing 2021
Materias:	classification combined residuals hydraulic modeling leakage detection localization Information technology T58.5-58.64 Environmental technology. Sanitary engineering TD1-1066
Acceso en línea:	https://doaj.org/article/35ece0bc00f54e52b20e4bcca965fa18
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spelling	oai:doaj.org-article:35ece0bc00f54e52b20e4bcca965fa182021-11-05T17:48:55ZWater leakage detection and localization using hydraulic modeling and classification1464-71411465-173410.2166/hydro.2021.164https://doaj.org/article/35ece0bc00f54e52b20e4bcca965fa182021-07-01T00:00:00Zhttp://jh.iwaponline.com/content/23/4/782https://doaj.org/toc/1464-7141https://doaj.org/toc/1465-1734A significant percentage of treated water is lost due to leakage in water distribution systems. The state-of-the-art leak detection and localization schemes use a hybrid approach to hydraulic modeling and data-driven techniques. Most of these works, however, focus on single leakage detection and localization. In this research, we propose to use combined pressure and flow residual data to detect and localize multiple leaks. The proposed approach has two phases: detection and localization. The detection phase uses the combination of pressure and flow residuals to build a hydraulic model and classification algorithm to identify leaks. The localization phase analyzes the pattern of isolated leak residuals to localize multiple leaks. To evaluate the performance of the proposed approach, we conducted experiments using Hanoi Water Network benchmark and a dataset produced based on LeakDB benchmark's dataset preparation procedure. The result for a well-calibrated hydraulic model shows that leak detection is 100% accurate while localization is 90% accurate, thereby outperforming minimum night flow and raw- and residual-based methods in localizing leaks. The proposed approach performed relatively well with the introduction of demand and noise uncertainty. The proposed localization approach is also able to locate two to four leaks that existed simultaneously. HIGHLIGHTS Water leak detection and localization (LDL) approaches based on a hybrid of hydraulic modeling and classification, and statistical approaches are proposed.; Combined residual data of pressure and flow are used to enhance LDL.; By separating the detection and classification phase, multiple leaks are localized.;Eliyas Girma MohammedEthiopia Bisrat ZelekeSurafel Lemma AbebeIWA Publishingarticleclassificationcombined residualshydraulic modelingleakage detectionlocalizationInformation technologyT58.5-58.64Environmental technology. Sanitary engineeringTD1-1066ENJournal of Hydroinformatics, Vol 23, Iss 4, Pp 782-794 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	classification combined residuals hydraulic modeling leakage detection localization Information technology T58.5-58.64 Environmental technology. Sanitary engineering TD1-1066
spellingShingle	classification combined residuals hydraulic modeling leakage detection localization Information technology T58.5-58.64 Environmental technology. Sanitary engineering TD1-1066 Eliyas Girma Mohammed Ethiopia Bisrat Zeleke Surafel Lemma Abebe Water leakage detection and localization using hydraulic modeling and classification
description	A significant percentage of treated water is lost due to leakage in water distribution systems. The state-of-the-art leak detection and localization schemes use a hybrid approach to hydraulic modeling and data-driven techniques. Most of these works, however, focus on single leakage detection and localization. In this research, we propose to use combined pressure and flow residual data to detect and localize multiple leaks. The proposed approach has two phases: detection and localization. The detection phase uses the combination of pressure and flow residuals to build a hydraulic model and classification algorithm to identify leaks. The localization phase analyzes the pattern of isolated leak residuals to localize multiple leaks. To evaluate the performance of the proposed approach, we conducted experiments using Hanoi Water Network benchmark and a dataset produced based on LeakDB benchmark's dataset preparation procedure. The result for a well-calibrated hydraulic model shows that leak detection is 100% accurate while localization is 90% accurate, thereby outperforming minimum night flow and raw- and residual-based methods in localizing leaks. The proposed approach performed relatively well with the introduction of demand and noise uncertainty. The proposed localization approach is also able to locate two to four leaks that existed simultaneously. HIGHLIGHTS Water leak detection and localization (LDL) approaches based on a hybrid of hydraulic modeling and classification, and statistical approaches are proposed.; Combined residual data of pressure and flow are used to enhance LDL.; By separating the detection and classification phase, multiple leaks are localized.;
format	article
author	Eliyas Girma Mohammed Ethiopia Bisrat Zeleke Surafel Lemma Abebe
author_facet	Eliyas Girma Mohammed Ethiopia Bisrat Zeleke Surafel Lemma Abebe
author_sort	Eliyas Girma Mohammed
title	Water leakage detection and localization using hydraulic modeling and classification
title_short	Water leakage detection and localization using hydraulic modeling and classification
title_full	Water leakage detection and localization using hydraulic modeling and classification
title_fullStr	Water leakage detection and localization using hydraulic modeling and classification
title_full_unstemmed	Water leakage detection and localization using hydraulic modeling and classification
title_sort	water leakage detection and localization using hydraulic modeling and classification
publisher	IWA Publishing
publishDate	2021
url	https://doaj.org/article/35ece0bc00f54e52b20e4bcca965fa18
work_keys_str_mv	AT eliyasgirmamohammed waterleakagedetectionandlocalizationusinghydraulicmodelingandclassification AT ethiopiabisratzeleke waterleakagedetectionandlocalizationusinghydraulicmodelingandclassification AT surafellemmaabebe waterleakagedetectionandlocalizationusinghydraulicmodelingandclassification
_version_	1718444094375591936

Water leakage detection and localization using hydraulic modeling and classification

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