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dc.contributor.author | Antonino-Daviu, J. | es_ES |
dc.contributor.author | Pons Llinares, Joan | es_ES |
dc.contributor.author | Lee, Sang Bin | es_ES |
dc.date.accessioned | 2018-03-01T12:37:27Z | |
dc.date.available | 2018-03-01T12:37:27Z | |
dc.date.issued | 2016 | es_ES |
dc.identifier.issn | 0093-9994 | es_ES |
dc.identifier.uri | http://hdl.handle.net/10251/98706 | |
dc.description.abstract | [EN] Anumber of field case studies for rotor fault diagnosis on medium-voltage induction motors operating in a petrochemical plant are presented in this paper. The methodology employed is based on analyzing the induction motor startup current with advanced signal processing tools (continuous transforms) that enable a capture of a complete picture of the rotor condition. Indeed, unlike the classical tools that often rely on the detection of few fault frequencies, these new tools allow extraction of the evolution of a wide range of fault components during the startup transient and steady-state evolutions, which enables improved reliability. This is crucial in medium-high-voltage motors, where a false diagnosis may result in significant expense due to inspection, repair, or forced outage. An additional contribution of the study is its immunity to external voltage supply disturbances, which introduce components that are not related to the failure and which are difficult to detect with classical tools. The results of this study prove how the advanced continuous tools enable an improved visualization of the fault components, distinguishing them from the other components that are not linked to the failure. | es_ES |
dc.description.sponsorship | This work was supported by the Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education, Science, and Technology under Grant NRF-2013R1A1A2010370, and in part by the Human Resources Development Program of the Korea Institute of Energy Technology Evaluation and Planning (KETEP) funded by the Korea Government Ministry of Trade, Industry, and Energy under Grant 20134030200340 | |
dc.language | Inglés | es_ES |
dc.publisher | Institute of Electrical and Electronics Engineers | es_ES |
dc.relation.ispartof | IEEE Transactions on Industry Applications | es_ES |
dc.rights | Reserva de todos los derechos | es_ES |
dc.subject | Fault diagnosis | es_ES |
dc.subject | Induction motors | es_ES |
dc.subject | Spectral analysis | es_ES |
dc.subject | Transient analysis | es_ES |
dc.subject | Wavelet transforms | es_ES |
dc.subject.classification | INGENIERIA ELECTRICA | es_ES |
dc.title | Advanced Rotor Fault Diagnosis for Medium-Voltage Induction Motors Via Continuous Transforms | es_ES |
dc.type | Artículo | es_ES |
dc.type | Comunicación en congreso | es_ES |
dc.identifier.doi | 10.1109/TIA.2016.2582720 | es_ES |
dc.relation.projectID | info:eu-repo/grantAgreement/NRF//2013R1A1A2010370/ | |
dc.relation.projectID | info:eu-repo/grantAgreement/NRF//20134030200340/ | |
dc.rights.accessRights | Abierto | es_ES |
dc.contributor.affiliation | Universitat Politècnica de València. Departamento de Ingeniería Eléctrica - Departament d'Enginyeria Elèctrica | es_ES |
dc.description.bibliographicCitation | Antonino-Daviu, J.; Pons Llinares, J.; Lee, SB. (2016). Advanced Rotor Fault Diagnosis for Medium-Voltage Induction Motors Via Continuous Transforms. IEEE Transactions on Industry Applications. 52(5):4503-4509. https://doi.org/10.1109/TIA.2016.2582720 | es_ES |
dc.description.accrualMethod | S | es_ES |
dc.relation.conferencename | 12th Petroleum and Chemical Industry Conference Europe (PCIC Europe 2015) Electrical and Instrumentation Applications | es_ES |
dc.relation.conferencedate | June 09-11,2015 | es_ES |
dc.relation.conferenceplace | London, UK | es_ES |
dc.relation.publisherversion | http://doi.org/10.1109/TIA.2016.2582720 | es_ES |
dc.description.upvformatpinicio | 4503 | es_ES |
dc.description.upvformatpfin | 4509 | es_ES |
dc.type.version | info:eu-repo/semantics/publishedVersion | es_ES |
dc.description.volume | 52 | es_ES |
dc.description.issue | 5 | es_ES |
dc.relation.pasarela | S\317474 | es_ES |
dc.contributor.funder | National Research Foundation of Korea |