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Pressure Sensor Placement for Leak Location in Zones of a Water Distribution Network

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Computational Intelligence Methodologies Applied to Sustainable Development Goals

Part of the book series: Studies in Computational Intelligence ((SCI,volume 1036))

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Abstract

A novel sensor placement approach for leak location in large-scale water distribution networks (WDNs) is presented. Estimating the exact location of leaks in large-scale WDNs requires a set of sensors with high sensitivity to be distributed. The partition of the WDN into leak zones allows to facilitate the location task. Thus, a topological clustering method aiming to divide the WDN into zones is combined with a novel sensor placement approach for solving the leak zone location problem. The goal of this approach is to determine the leak zone such that the water company can confine the exact location later by using specialized equipment. The Modena network is used as a real-life case study with synthetically generated field data assuming that a single leak occurs. The satisfactory performance of the proposal is demonstrated under uncertain conditions and measurement noise even when the sensitivity of the sensors is limited.

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Author information

Authors and Affiliations

  1. Departamento de Automática y Computación, Universidad Tecnológica de la Habana José Antonio Echeverríıa, CUJAE, La Habana, Cuba

    Marlon J. Ares-Milián & Orestes Llanes-Santiago

  2. Institute for Software Integrated Systems, Vanderbilt University, Nashville, TN, USA

    Marcos Quiñones-Grueiro

  3. Instituto de Ingeniería, Universidad Nacional Autónoma de México, Mexico City, Mexico

    Cristina Verde

Authors
  1. Marlon J. Ares-Milián
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  2. Marcos Quiñones-Grueiro
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  3. Cristina Verde
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  4. Orestes Llanes-Santiago
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Corresponding author

Correspondence to Orestes Llanes-Santiago .

Editor information

Editors and Affiliations

  1. Department of Computer Science and Artificial Intelligence, University of Granada, Granada, Spain

    José Luis Verdegay

  2. Department of Engineering of Systems, University of La Laguna, San Cristóbal de La Laguna, Spain

    Julio Brito

  3. Department of Computer Science and Artificial Intelligence, University of Granada, Granada, Spain

    Carlos Cruz

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Ares-Milián, M.J., Quiñones-Grueiro, M., Verde, C., Llanes-Santiago, O. (2022). Pressure Sensor Placement for Leak Location in Zones of a Water Distribution Network. In: Verdegay, J.L., Brito, J., Cruz, C. (eds) Computational Intelligence Methodologies Applied to Sustainable Development Goals. Studies in Computational Intelligence, vol 1036. Springer, Cham. https://doi.org/10.1007/978-3-030-97344-5_10

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