An Advanced Sensor Placement Strategy for Small Leaks Quantification Using Lean Graphs
Small leaks in water distribution networks have been a major problem both economically and environmentally, as they go undetected for years. We model the signature of small leaks as a unique Directed Acyclic Graph, called the Lean Graph, to find the best places for <i>k</i> sensors for d...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2020-12-01
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| Series: | Water |
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| Online Access: | https://www.mdpi.com/2073-4441/12/12/3439 |
| _version_ | 1797545360214720512 |
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| author | Ary Mazharuddin Shiddiqi Rachel Cardell-Oliver Amitava Datta |
| author_facet | Ary Mazharuddin Shiddiqi Rachel Cardell-Oliver Amitava Datta |
| author_sort | Ary Mazharuddin Shiddiqi |
| collection | DOAJ |
| description | Small leaks in water distribution networks have been a major problem both economically and environmentally, as they go undetected for years. We model the signature of small leaks as a unique Directed Acyclic Graph, called the Lean Graph, to find the best places for <i>k</i> sensors for detecting and locating small leaks. We use the sensors to develop dictionaries that map each leak signature to its location. We quantify leaks by matching out-of-normal flows detected by sensors against records in the selected dictionaries. The most similar records of the dictionaries are used to quantify the leaks. Finally, we investigate how much our approach can tolerate corrupted data due to sensor failures by introducing a subspace voting based quantification method. We tested our method on water distribution networks of literature and simulate small leaks ranging from [0.1, 1.0] liter per second. Our experimental results prove that our sensor placement strategy can effectively place <i>k</i> sensors to quantify single and multiple small leaks and can tolerate corrupted data up to some range while maintaining the performance of leak quantification. These outcomes indicate that our approach could be applied in real water distribution networks to minimize the loss caused by small leaks. |
| first_indexed | 2024-03-10T14:14:20Z |
| format | Article |
| id | doaj.art-2211587a7b974b268ead15be75be03f9 |
| institution | Directory Open Access Journal |
| issn | 2073-4441 |
| language | English |
| last_indexed | 2024-03-10T14:14:20Z |
| publishDate | 2020-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Water |
| spelling | doaj.art-2211587a7b974b268ead15be75be03f92023-11-20T23:53:17ZengMDPI AGWater2073-44412020-12-011212343910.3390/w12123439An Advanced Sensor Placement Strategy for Small Leaks Quantification Using Lean GraphsAry Mazharuddin Shiddiqi0Rachel Cardell-Oliver1Amitava Datta2Department of Informatics, Institut Teknologi Sepuluh Nopember, Jl. Raya ITS, Keputih, Sukolilo, Surabaya 60111, Jawa Timur, IndonesiaFaculty of Engineering and Mathematical Sciences, Computer Science and Software Engineering, University of Western Australia, 35 Stirling Hwy, Crawley 6009, WA, AustraliaFaculty of Engineering and Mathematical Sciences, Computer Science and Software Engineering, University of Western Australia, 35 Stirling Hwy, Crawley 6009, WA, AustraliaSmall leaks in water distribution networks have been a major problem both economically and environmentally, as they go undetected for years. We model the signature of small leaks as a unique Directed Acyclic Graph, called the Lean Graph, to find the best places for <i>k</i> sensors for detecting and locating small leaks. We use the sensors to develop dictionaries that map each leak signature to its location. We quantify leaks by matching out-of-normal flows detected by sensors against records in the selected dictionaries. The most similar records of the dictionaries are used to quantify the leaks. Finally, we investigate how much our approach can tolerate corrupted data due to sensor failures by introducing a subspace voting based quantification method. We tested our method on water distribution networks of literature and simulate small leaks ranging from [0.1, 1.0] liter per second. Our experimental results prove that our sensor placement strategy can effectively place <i>k</i> sensors to quantify single and multiple small leaks and can tolerate corrupted data up to some range while maintaining the performance of leak quantification. These outcomes indicate that our approach could be applied in real water distribution networks to minimize the loss caused by small leaks.https://www.mdpi.com/2073-4441/12/12/3439leak quantificationsensor networksfault tolerancewater distribution networks |
| spellingShingle | Ary Mazharuddin Shiddiqi Rachel Cardell-Oliver Amitava Datta An Advanced Sensor Placement Strategy for Small Leaks Quantification Using Lean Graphs Water leak quantification sensor networks fault tolerance water distribution networks |
| title | An Advanced Sensor Placement Strategy for Small Leaks Quantification Using Lean Graphs |
| title_full | An Advanced Sensor Placement Strategy for Small Leaks Quantification Using Lean Graphs |
| title_fullStr | An Advanced Sensor Placement Strategy for Small Leaks Quantification Using Lean Graphs |
| title_full_unstemmed | An Advanced Sensor Placement Strategy for Small Leaks Quantification Using Lean Graphs |
| title_short | An Advanced Sensor Placement Strategy for Small Leaks Quantification Using Lean Graphs |
| title_sort | advanced sensor placement strategy for small leaks quantification using lean graphs |
| topic | leak quantification sensor networks fault tolerance water distribution networks |
| url | https://www.mdpi.com/2073-4441/12/12/3439 |
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