Optimal Sensor Placement for Leak Location in Water Distribution Networks using Evolutionary Algorithms

In this paper, a sensor placement approach to improve the leak location in waterdistribution networks is proposed when the leak signature space (LSS) method is used.The sensor placement problem is formulated as an integer optimization problem where thecriterion to be minimized is the number of overl...

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Main Authors: Myrna V. Casillas, Luis E. Garza-Castañón, Vicenç Puig
Format: Article
Language:English
Published: MDPI AG 2015-11-01
Series:Water
Subjects:
Online Access:http://www.mdpi.com/2073-4441/7/11/6496
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spelling doaj-fa723e0178254953bdfd4305f91536182020-11-25T00:12:16ZengMDPI AGWater2073-44412015-11-017116496651510.3390/w7116496w7116496Optimal Sensor Placement for Leak Location in Water Distribution Networks using Evolutionary AlgorithmsMyrna V. Casillas0Luis E. Garza-Castañón1Vicenç Puig2Supervision and Advanced Control Chair, Tecnológico de Monterrey, Campus Monterrey, Av. Eugenio Garza Sada 2501, 64849 Monterrey, MexicoSupervision and Advanced Control Chair, Tecnológico de Monterrey, Campus Monterrey, Av. Eugenio Garza Sada 2501, 64849 Monterrey, MexicoAdvanced Control Systems Research Group, Technical University of Catalonia, Rambla Sant Nebridi 10, 08222 Terrassa, SpainIn this paper, a sensor placement approach to improve the leak location in waterdistribution networks is proposed when the leak signature space (LSS) method is used.The sensor placement problem is formulated as an integer optimization problem where thecriterion to be minimized is the number of overlapping signature domains computed fromthe original LSS representation. First, a semi-exhaustive search approach based on a lazyevaluation mechanism ensures optimal placement in the case of low complexity scenarios.For more complex cases, a stochastic optimization process is proposed, based on eitherthe genetic algorithms (GAs) or particle swarm optimization (PSO). Experiments on twodifferent networks are used to evaluate the performance of the resolution methods, as well asthe efficiency achieved in the leak location when using the sensor placement results.http://www.mdpi.com/2073-4441/7/11/6496water distribution networksleak isolationsensor placementleak signature space
collection DOAJ
language English
format Article
sources DOAJ
author Myrna V. Casillas
Luis E. Garza-Castañón
Vicenç Puig
spellingShingle Myrna V. Casillas
Luis E. Garza-Castañón
Vicenç Puig
Optimal Sensor Placement for Leak Location in Water Distribution Networks using Evolutionary Algorithms
Water
water distribution networks
leak isolation
sensor placement
leak signature space
author_facet Myrna V. Casillas
Luis E. Garza-Castañón
Vicenç Puig
author_sort Myrna V. Casillas
title Optimal Sensor Placement for Leak Location in Water Distribution Networks using Evolutionary Algorithms
title_short Optimal Sensor Placement for Leak Location in Water Distribution Networks using Evolutionary Algorithms
title_full Optimal Sensor Placement for Leak Location in Water Distribution Networks using Evolutionary Algorithms
title_fullStr Optimal Sensor Placement for Leak Location in Water Distribution Networks using Evolutionary Algorithms
title_full_unstemmed Optimal Sensor Placement for Leak Location in Water Distribution Networks using Evolutionary Algorithms
title_sort optimal sensor placement for leak location in water distribution networks using evolutionary algorithms
publisher MDPI AG
series Water
issn 2073-4441
publishDate 2015-11-01
description In this paper, a sensor placement approach to improve the leak location in waterdistribution networks is proposed when the leak signature space (LSS) method is used.The sensor placement problem is formulated as an integer optimization problem where thecriterion to be minimized is the number of overlapping signature domains computed fromthe original LSS representation. First, a semi-exhaustive search approach based on a lazyevaluation mechanism ensures optimal placement in the case of low complexity scenarios.For more complex cases, a stochastic optimization process is proposed, based on eitherthe genetic algorithms (GAs) or particle swarm optimization (PSO). Experiments on twodifferent networks are used to evaluate the performance of the resolution methods, as well asthe efficiency achieved in the leak location when using the sensor placement results.
topic water distribution networks
leak isolation
sensor placement
leak signature space
url http://www.mdpi.com/2073-4441/7/11/6496
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AT luisegarzacastanon optimalsensorplacementforleaklocationinwaterdistributionnetworksusingevolutionaryalgorithms
AT vicencpuig optimalsensorplacementforleaklocationinwaterdistributionnetworksusingevolutionaryalgorithms
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