2026-04-17T01:34:53Zhttps://recercat.cat/oai/request
oai:recercat.cat:2117/4116622026-02-04T07:48:57Zcom_2072_1033col_2072_452950
RECERCAT author Irofti, Paul author Romero Ben, Luis author Stoican, Florin author Puig Cayuela, Vicenç 2024-05 © 2024 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting /republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other worksThis article presents a leak localization methodology based on state estimation and learning. The first is handled by an interpolation scheme, whereas dictionary learning (DL) is considered for the second stage. The novel proposed interpolation technique exploits the physics of the interconnections between hydraulic heads of neighboring nodes in water distribution networks (WDNs). In addition, residuals are directly interpolated instead of hydraulic head values. The results of applying the proposed method to a well-known case study (Modena) demonstrated the improvements of the new interpolation method with respect to a state-of-the-art approach, both in terms of interpolation error (considering state and residual estimation) and posterior localization.Peer ReviewedPostprint (author's final draft) Open Access Àrees temàtiques de la UPC::Informàtica::Automàtica i control Leak detectors Water -- Distribution Dictionary learning Interpolation Leak localization State estimation Water distribution network Detectors de fuites Aigua -- Distribució Learning dictionaries from physical-based interpolation for water network leak localization Article