Mostrar el registro sencillo del ítem
dc.contributor.author | Ocaña-Levario, Silvia Janeth | es_ES |
dc.contributor.author | Carreño-Alvarado, Elizabeth Pauline | es_ES |
dc.contributor.author | Ayala Cabrera, David | es_ES |
dc.contributor.author | Izquierdo Sebastián, Joaquín | es_ES |
dc.date.accessioned | 2019-07-25T20:00:53Z | |
dc.date.available | 2019-07-25T20:00:53Z | |
dc.date.issued | 2018 | es_ES |
dc.identifier.issn | 0926-9851 | es_ES |
dc.identifier.uri | http://hdl.handle.net/10251/124215 | |
dc.description.abstract | [EN] Nowadays, there is growing interest in controlling and reducing the amount of water lost through leakage in water supply systems (WSSs). Leakage is, in fact, one of the biggest problems faced by the managers of these utilities. This work addresses the problem of leakage in WSSs by using GPR (Ground Penetrating Radar) as a non-destructive method. The main objective is to identify and extract features from GPR images such as leaks and components in a controlled laboratory condition by a methodology based on second order statistical parameters and, using the obtained features, to create 3D models that allows quick visualization of components and leaks in WSSs from GPR image analysis and subsequent interpretation. This methodology has been used before in other fields and provided promising results. The results obtained with the proposed methodology are presented, analyzed, interpreted and compared with the results obtained by using a well-established multi-agent based methodology. These results show that the variance filter is capable of highlighting the characteristics of components and anomalies, in an intuitive manner, which can be identified by non-highly qualified personnel, using the 3D models we develop. This research intends to pave the way towards future intelligent detection systems that enable the automatic detection of leaks in WSSs. (C) 2017 Published by Elsevier B.V. | es_ES |
dc.description.sponsorship | Part of this work has been developed under the support of Fundacion Carolina PhD (2014) and short-term scholarship program for the first author (Doctorado y estancias cortas). | es_ES |
dc.language | Inglés | es_ES |
dc.publisher | Elsevier | es_ES |
dc.relation.ispartof | Journal of Applied Geophysics | es_ES |
dc.rights | Reconocimiento - No comercial - Sin obra derivada (by-nc-nd) | es_ES |
dc.subject | Variance filters | es_ES |
dc.subject | GPR images | es_ES |
dc.subject | Non-destructive methods | es_ES |
dc.subject | Water leaks | es_ES |
dc.subject | Water supply systems | es_ES |
dc.subject.classification | MATEMATICA APLICADA | es_ES |
dc.subject.classification | MECANICA DE FLUIDOS | es_ES |
dc.title | GPR image analysis to locate water leaks from buried pipes by applying variance filters | es_ES |
dc.type | Artículo | es_ES |
dc.identifier.doi | 10.1016/j.jappgeo.2018.03.025 | es_ES |
dc.rights.accessRights | Abierto | es_ES |
dc.contributor.affiliation | Universitat Politècnica de València. Instituto Universitario de Matemática Multidisciplinar - Institut Universitari de Matemàtica Multidisciplinària | es_ES |
dc.contributor.affiliation | Universitat Politècnica de València. Departamento de Matemática Aplicada - Departament de Matemàtica Aplicada | es_ES |
dc.description.bibliographicCitation | Ocaña-Levario, SJ.; Carreño-Alvarado, EP.; Ayala Cabrera, D.; Izquierdo Sebastián, J. (2018). GPR image analysis to locate water leaks from buried pipes by applying variance filters. Journal of Applied Geophysics. 152:236-247. https://doi.org/10.1016/j.jappgeo.2018.03.025 | es_ES |
dc.description.accrualMethod | S | es_ES |
dc.relation.publisherversion | http://doi.org/10.1016/j.jappgeo.2018.03.025 | es_ES |
dc.description.upvformatpinicio | 236 | es_ES |
dc.description.upvformatpfin | 247 | es_ES |
dc.type.version | info:eu-repo/semantics/publishedVersion | es_ES |
dc.description.volume | 152 | es_ES |
dc.relation.pasarela | S\356078 | es_ES |
dc.contributor.funder | Fundación Carolina |