Leak localization in water distribution networks using model-based bayesian reasoning

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To access the full text documents, please follow this link: http://hdl.handle.net/2117/101117

dc.contributor	Universitat Politècnica de Catalunya. Departament d'Enginyeria de Sistemes, Automàtica i Informàtica Industrial
dc.contributor	Institut de Robòtica i Informàtica Industrial
dc.contributor	Universitat Politècnica de Catalunya. BIOART - BIOsignal Analysis for Rehabilitation and Therapy
dc.contributor	Universitat Politècnica de Catalunya. SIC - Sistemes Intel·ligents de Control
dc.contributor	Universitat Politècnica de Catalunya. SAC - Sistemes Avançats de Control
dc.contributor.author	Soldevila Coma, Adrià
dc.contributor.author	Fernández Canti, Rosa M.
dc.contributor.author	Blesa Izquierdo, Joaquim
dc.contributor.author	Tornil Sin, Sebastián
dc.contributor.author	Puig Cayuela, Vicenç
dc.date	2016
dc.identifier.citation	Soldevila, A., Rosa M. Fernandez-Canti, Blesa, J., Tornil-Sin, S., Puig, V. Leak localization in water distribution networks using model-based bayesian reasoning. A: European Control Conference. "ECC 2016 European Control Conference June 29 - July 1, 2016. Aalborg, Denmark". Aalborg: 2016, p. 1758-1763.
dc.identifier.uri	http://hdl.handle.net/2117/101117
dc.language.iso	eng
dc.rights	info:eu-repo/semantics/openAccess
dc.subject	Àrees temàtiques de la UPC::Informàtica::Automàtica i control
dc.subject	Water distribution network
dc.subject	Water distribution networks
dc.subject	leak localization
dc.subject	fault diagnosis
dc.subject	Bayesian reasoning
dc.subject	model-based.
dc.subject	Aigua -- Distribució -- Control automàtic
dc.title	Leak localization in water distribution networks using model-based bayesian reasoning
dc.type	info:eu-repo/semantics/submittedVersion
dc.type	info:eu-repo/semantics/conferenceObject
dc.description.abstract	This paper presents a new method for leak localization in Water Distribution Networks that uses a model-based approach combined with Bayesian reasoning. Probability density functions in model-based pressure residuals are calibrated off-line for all the possible leak scenarios by using a hydraulic simulator, being leak size uncertainty, demand uncertainty and sensor noise considered. A Bayesian reasoning is applied online to the available residuals to determine the location of leaks present in the Water Distribution Network. A time horizon method combined with the Bayesian reasoning is also proposed to improve the accuracy of the leak localization method. The Hanoi District Metered Area case study is used to illustrate the performance of the proposed approach.
dc.description.abstract	Peer Reviewed

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