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...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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IWA Publishing
2021-07-01
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| Series: | Journal of Hydroinformatics |
| Subjects: | |
| Online Access: | http://jh.iwaponline.com/content/23/4/782 |
| _version_ | 1818431912981561344 |
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| 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 |
| collection | DOAJ |
| 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.; |
| first_indexed | 2024-12-14T15:56:51Z |
| format | Article |
| id | doaj.art-35ece0bc00f54e52b20e4bcca965fa18 |
| institution | Directory Open Access Journal |
| issn | 1464-7141 1465-1734 |
| language | English |
| last_indexed | 2024-12-14T15:56:51Z |
| publishDate | 2021-07-01 |
| publisher | IWA Publishing |
| record_format | Article |
| series | Journal of Hydroinformatics |
| spelling | doaj.art-35ece0bc00f54e52b20e4bcca965fa182022-12-21T22:55:15ZengIWA PublishingJournal of Hydroinformatics1464-71411465-17342021-07-0123478279410.2166/hydro.2021.164164Water leakage detection and localization using hydraulic modeling and classificationEliyas Girma Mohammed0Ethiopia Bisrat Zeleke1Surafel Lemma Abebe2 School of Electrical and Computer Engineering, Addis Ababa Institute of Technology, Addis Ababa University, Addis Ababa, Ethiopia School of Civil and Environmental Engineering, Addis Ababa Institute of Technology, Addis Ababa University, Addis Ababa, Ethiopia School of Electrical and Computer Engineering, Addis Ababa Institute of Technology, Addis Ababa University, Addis Ababa, Ethiopia 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.;http://jh.iwaponline.com/content/23/4/782classificationcombined residualshydraulic modelingleakage detectionlocalization |
| spellingShingle | Eliyas Girma Mohammed Ethiopia Bisrat Zeleke Surafel Lemma Abebe Water leakage detection and localization using hydraulic modeling and classification Journal of Hydroinformatics classification combined residuals hydraulic modeling leakage detection localization |
| title | 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_short | Water leakage detection and localization using hydraulic modeling and classification |
| title_sort | water leakage detection and localization using hydraulic modeling and classification |
| topic | classification combined residuals hydraulic modeling leakage detection localization |
| url | http://jh.iwaponline.com/content/23/4/782 |
| work_keys_str_mv | AT eliyasgirmamohammed waterleakagedetectionandlocalizationusinghydraulicmodelingandclassification AT ethiopiabisratzeleke waterleakagedetectionandlocalizationusinghydraulicmodelingandclassification AT surafellemmaabebe waterleakagedetectionandlocalizationusinghydraulicmodelingandclassification |