Mostrar el registro sencillo del ítem
dc.contributor.author | Antonino-Daviu, J. | es_ES |
dc.contributor.author | Lee, Sang Bin | es_ES |
dc.contributor.author | Strangas, Elias | es_ES |
dc.date.accessioned | 2018-06-07T04:32:33Z | |
dc.date.available | 2018-06-07T04:32:33Z | |
dc.date.issued | 2017 | es_ES |
dc.identifier.issn | 1551-3203 | es_ES |
dc.identifier.uri | http://hdl.handle.net/10251/103513 | |
dc.description | © 2017 IEEE. Personal use of this material is permitted. Permissíon from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertisíng 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 works | |
dc.description.abstract | [EN] With the expansion of the use of electrical drive sys- tems to more critical applications, the issue of reliability and fault mitigation and condition-based maintenance have consequently taken an increasing importance: it has become a crucial one that cannot be neglected or dealt with in an ad-hoc way. As a result research activity has increased in this area, and new methods are used, some based on a continuation and improvement of previous accomplishments, while others are applying theory and techniques in related areas. This Special Section of the IEEE Transactions on Industrial Informatics attracted a number of papers dealing with Advanced Signal and Image Processing Techniques for Electric Machine and Drives Fault Diagnosis and Prognosis. This editorial aims to put these contributions in context, and highlight the new ideas and directions therein. | es_ES |
dc.language | Inglés | es_ES |
dc.publisher | Institute of Electrical and Electronics Engineers | es_ES |
dc.relation.ispartof | IEEE Transactions on Industrial Informatics | es_ES |
dc.rights | Reserva de todos los derechos | es_ES |
dc.subject | Feature extraction | es_ES |
dc.subject | Fault diagnosis | es_ES |
dc.subject | Prognostics and health management | es_ES |
dc.subject | Electric machines | es_ES |
dc.subject | Estimation | es_ES |
dc.subject | Sensors | es_ES |
dc.subject | Mathematical model | es_ES |
dc.subject.classification | INGENIERIA ELECTRICA | es_ES |
dc.title | Guest Editorial Special Section on Advanced Signal and Image Processing Techniques for Electric Machines and Drives Fault Diagnosis and Prognosis | es_ES |
dc.type | Artículo | es_ES |
dc.identifier.doi | 10.1109/TII.2017.2690464 | es_ES |
dc.rights.accessRights | Abierto | es_ES |
dc.date.embargoEndDate | 2018-06-01 | 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.; Lee, SB.; Strangas, E. (2017). Guest Editorial Special Section on Advanced Signal and Image Processing Techniques for Electric Machines and Drives Fault Diagnosis and Prognosis. IEEE Transactions on Industrial Informatics. 13(3):1257-1260. doi:10.1109/TII.2017.2690464 | es_ES |
dc.description.accrualMethod | S | es_ES |
dc.relation.publisherversion | http://doi.org/10.1109/TII.2017.2690464 | es_ES |
dc.description.upvformatpinicio | 1257 | es_ES |
dc.description.upvformatpfin | 1260 | es_ES |
dc.type.version | info:eu-repo/semantics/publishedVersion | es_ES |
dc.description.volume | 13 | es_ES |
dc.description.issue | 3 | es_ES |
dc.relation.pasarela | S\332158 | es_ES |