Robust Data-Driven Leak Localization in Water Distribution Networks Using Pressure Measurements and Topological Information.

data-driven leak localization water distribution networks

Journal

Sensors (Basel, Switzerland)
ISSN: 1424-8220
Titre abrégé: Sensors (Basel)
Pays: Switzerland
ID NLM: 101204366

Informations de publication

Date de publication:
13 Nov 2021
Historique:
received: 08 09 2021
revised: 01 11 2021
accepted: 06 11 2021
entrez: 27 11 2021
pubmed: 28 11 2021
medline: 28 11 2021
Statut: epublish

Résumé

This article presents a new data-driven method for locating leaks in water distribution networks (WDNs). It is triggered after a leak has been detected in the WDN. The proposed approach is based on the use of inlet pressure and flow measurements, other pressure measurements available at some selected inner nodes of the WDN, and the topological information of the network. A reduced-order model structure is used to calculate non-leak pressure estimations at sensed inner nodes. Residuals are generated using the comparison between these estimations and leak pressure measurements. In a leak scenario, it is possible to determine the relative incidence of a leak in a node by using the network topology and what it means to correlate the probable leaking nodes with the available residual information. Topological information and residual information can be integrated into a likelihood index used to determine the most probable leak node in the WDN at a given instant

Identifiants

pubmed: 34833627
pii: s21227551
doi: 10.3390/s21227551
pmc: PMC8625422
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Subventions

Organisme : Agency for Administration of University and Research
ID : COMRDI-16-1-0054-0
Organisme : Spanish Ministry of Science and Innovatio
ID : PID2020-115905RB-C
Organisme : Interreg Cooperation Program POCTEFA 2014-2020
ID : EFA153/16

Auteurs

Débora Alves (D)

Supervision, Safety and Automatic Control Research Center (CS2AC), Universitat Politècnica de Catalunya, Gaia Building, Rambla Sant Nebridi, 22, 08222 Terrassa, Spain.
IMT Nord Europe, Université de Lille, CERI Digital Systems, F-59000 Lille, France.

Joaquim Blesa (J)

Supervision, Safety and Automatic Control Research Center (CS2AC), Universitat Politècnica de Catalunya, Gaia Building, Rambla Sant Nebridi, 22, 08222 Terrassa, Spain.
Institut de Robòtica i Informàtica Industrial (CSIC-UPC), Carrer Llorens Artigas, 4-6, 08028 Barcelona, Spain.
Serra Húnter Fellow Automatic Control Department (ESAII), Universitat Politècnica de Catalunya (UPC), Pau Gargallo, 5, 08028 Barcelona, Spain.

Eric Duviella (E)

IMT Nord Europe, Université de Lille, CERI Digital Systems, F-59000 Lille, France.

Lala Rajaoarisoa (L)

IMT Nord Europe, Université de Lille, CERI Digital Systems, F-59000 Lille, France.

Classifications MeSH