Mostrar el registro sencillo del ítem
dc.contributor.author | Pons Llinares, Joan | es_ES |
dc.contributor.author | Riera-Guasp, Martín | es_ES |
dc.contributor.author | Antonino-Daviu, José Alfonso | es_ES |
dc.contributor.author | Habetler, TG | es_ES |
dc.date.accessioned | 2018-07-26T07:07:23Z | |
dc.date.available | 2018-07-26T07:07:23Z | |
dc.date.issued | 2016 | es_ES |
dc.identifier.issn | 0888-3270 | es_ES |
dc.identifier.uri | http://hdl.handle.net/10251/106298 | |
dc.description.abstract | [EN] The aim of this paper is to introduce a new linear time-frequency transform to improve the detection of fault components in electric machines transient currents. Linear transforms are analysed from the perspective of the atoms used. A criterion to select the atoms at every point of the time-frequency plane is proposed, taking into account the characteristics of the searched component at each point. This criterion leads to the definition of the Adaptive Slope Transform, which enables a complete and optimal capture of the different components evolutions in a transient current. A comparison with conventional linear transforms (Short-Time Fourier Transform and Wavelet Transform) is carried out, showing their inherent limitations. The approach is tested with laboratory and field motors, and the Lower Sideband Harmonic is captured for the first time during an induction motor startup and subsequent load oscillations, accurately tracking its evolution. (C) 2016 Elsevier Ltd. All rights reserved. | es_ES |
dc.description.sponsorship | This work was supported by the Spanish "Ministerio de Economia y Competitividad" in the framework of the "Programa Estatal de Investigacion, Desarrollo e Innovacion Orientada a los Retos de la Sociedad" (Project reference DPI2014-60881-R). | es_ES |
dc.language | Inglés | es_ES |
dc.publisher | Elsevier | es_ES |
dc.relation.ispartof | Mechanical Systems and Signal Processing | es_ES |
dc.rights | Reserva de todos los derechos | es_ES |
dc.subject | Time-frequency analysis | es_ES |
dc.subject | Transient analysis | es_ES |
dc.subject | Wavelet transforms | es_ES |
dc.subject | Signal analysis | es_ES |
dc.subject | Fault diagnosis | es_ES |
dc.subject | Rotor broken bar | es_ES |
dc.subject | Induction motors | es_ES |
dc.subject | Monitoring | es_ES |
dc.subject.classification | INGENIERIA ELECTRICA | es_ES |
dc.title | Pursuing optimal electric machines transient diagnosis: The adaptive slope transform | es_ES |
dc.type | Artículo | es_ES |
dc.identifier.doi | 10.1016/j.ymssp.2016.05.003 | es_ES |
dc.relation.projectID | info:eu-repo/grantAgreement/MINECO//DPI2014-60881-R/ES/VALUACION DE LA VIABILIDAD DE UN NUEVO PLANTEAMIENTO PARA EL SISTEMA DE DIAGNOSTICO DE AVERIAS EN LOS AEROGENERADORES/ | es_ES |
dc.rights.accessRights | Cerrado | es_ES |
dc.contributor.affiliation | Universitat Politècnica de València. Departamento de Ingeniería Eléctrica - Departament d'Enginyeria Elèctrica | es_ES |
dc.description.bibliographicCitation | Pons Llinares, J.; Riera-Guasp, M.; Antonino-Daviu, JA.; Habetler, T. (2016). Pursuing optimal electric machines transient diagnosis: The adaptive slope transform. Mechanical Systems and Signal Processing. 80:553-569. doi:10.1016/j.ymssp.2016.05.003 | es_ES |
dc.description.accrualMethod | S | es_ES |
dc.relation.publisherversion | http://doi.org/10.1016/j.ymssp.2016.05.003 | es_ES |
dc.description.upvformatpinicio | 553 | es_ES |
dc.description.upvformatpfin | 569 | es_ES |
dc.type.version | info:eu-repo/semantics/publishedVersion | es_ES |
dc.description.volume | 80 | es_ES |
dc.relation.pasarela | S\326131 | es_ES |
dc.contributor.funder | Ministerio de Economía y Competitividad | es_ES |