Research on leakage area detection method in water distribution network based on gray wolf optimization
Leakage in a water distribution network (WDN) leads to a large amount of water loss and water pipe pollution and affects residents’ domestic water supply. Therefore, network leakage detection significantly saves water resources. The traditional model approach has ample search space in solving large...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
IWA Publishing
2023-02-01
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| Series: | Water Supply |
| Subjects: | |
| Online Access: | http://ws.iwaponline.com/content/23/2/645 |
| _version_ | 1797850665239707648 |
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| author | QianSheng Fang Jie Chen ChenLei Xie |
| author_facet | QianSheng Fang Jie Chen ChenLei Xie |
| author_sort | QianSheng Fang |
| collection | DOAJ |
| description | Leakage in a water distribution network (WDN) leads to a large amount of water loss and water pipe pollution and affects residents’ domestic water supply. Therefore, network leakage detection significantly saves water resources. The traditional model approach has ample search space in solving large distribution network applications, a challenging and complex leakage detection process and a low detection accuracy. For the above problems, this study proposes a new method of leakage area detection based on gray wolf optimization (GWO). First, the extensive WDN is divided into several virtual areas. Then, the leakage is simulated by the additional water demand of nodes, and the node demand of the distribution network is calibrated based on the GWO algorithm. Finally, the leakage area is identified, and the size of the leakage in that area is estimated. The method was experimented on in two cases, simulating single-point leakage and multi-point simultaneous leakage, respectively. The results show that the method estimates the size of leakage in the corresponding area based on accurate identification of leakage areas, and the detection error of leakage is within 17.14%. The method provides water workers with guidance on leak detection, significantly reducing staff time to repair pipes.
HIGHLIGHTS
Use a small number of monitoring sensors to detect the leakage status of pipeline networks, identify leakage areas and estimate the leakage amount.;
A multi-leakage point detection method based on gray wolf optimization is proposed, which can effectively simulate the actual pipe network leakage situation.;
A method of dividing multiple virtual areas for leak detection is proposed, which improves the accuracy of leak detection.; |
| first_indexed | 2024-04-09T19:04:00Z |
| format | Article |
| id | doaj.art-c30e14515eae45609bddc884b9e7f945 |
| institution | Directory Open Access Journal |
| issn | 1606-9749 1607-0798 |
| language | English |
| last_indexed | 2024-04-09T19:04:00Z |
| publishDate | 2023-02-01 |
| publisher | IWA Publishing |
| record_format | Article |
| series | Water Supply |
| spelling | doaj.art-c30e14515eae45609bddc884b9e7f9452023-04-07T15:14:46ZengIWA PublishingWater Supply1606-97491607-07982023-02-0123264565610.2166/ws.2023.014014Research on leakage area detection method in water distribution network based on gray wolf optimizationQianSheng Fang0Jie Chen1ChenLei Xie2 Anhui Province Key Laboratory of Intelligent Building and Building Energy Saving, Anhui Jianzhu University, Hefei, China Anhui Province Key Laboratory of Intelligent Building and Building Energy Saving, Anhui Jianzhu University, Hefei, China Anhui Province Key Laboratory of Intelligent Building and Building Energy Saving, Anhui Jianzhu University, Hefei, China Leakage in a water distribution network (WDN) leads to a large amount of water loss and water pipe pollution and affects residents’ domestic water supply. Therefore, network leakage detection significantly saves water resources. The traditional model approach has ample search space in solving large distribution network applications, a challenging and complex leakage detection process and a low detection accuracy. For the above problems, this study proposes a new method of leakage area detection based on gray wolf optimization (GWO). First, the extensive WDN is divided into several virtual areas. Then, the leakage is simulated by the additional water demand of nodes, and the node demand of the distribution network is calibrated based on the GWO algorithm. Finally, the leakage area is identified, and the size of the leakage in that area is estimated. The method was experimented on in two cases, simulating single-point leakage and multi-point simultaneous leakage, respectively. The results show that the method estimates the size of leakage in the corresponding area based on accurate identification of leakage areas, and the detection error of leakage is within 17.14%. The method provides water workers with guidance on leak detection, significantly reducing staff time to repair pipes. HIGHLIGHTS Use a small number of monitoring sensors to detect the leakage status of pipeline networks, identify leakage areas and estimate the leakage amount.; A multi-leakage point detection method based on gray wolf optimization is proposed, which can effectively simulate the actual pipe network leakage situation.; A method of dividing multiple virtual areas for leak detection is proposed, which improves the accuracy of leak detection.;http://ws.iwaponline.com/content/23/2/645gray wolf optimization algorithmleakage arealeakage detectionwater distribution network |
| spellingShingle | QianSheng Fang Jie Chen ChenLei Xie Research on leakage area detection method in water distribution network based on gray wolf optimization Water Supply gray wolf optimization algorithm leakage area leakage detection water distribution network |
| title | Research on leakage area detection method in water distribution network based on gray wolf optimization |
| title_full | Research on leakage area detection method in water distribution network based on gray wolf optimization |
| title_fullStr | Research on leakage area detection method in water distribution network based on gray wolf optimization |
| title_full_unstemmed | Research on leakage area detection method in water distribution network based on gray wolf optimization |
| title_short | Research on leakage area detection method in water distribution network based on gray wolf optimization |
| title_sort | research on leakage area detection method in water distribution network based on gray wolf optimization |
| topic | gray wolf optimization algorithm leakage area leakage detection water distribution network |
| url | http://ws.iwaponline.com/content/23/2/645 |
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