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Particle Filter-Based Estimation of Instantaneous Frequency for the Diagnosis of Electrical Asymmetries in Induction Machines

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Particle Filter-Based Estimation of Instantaneous Frequency for the Diagnosis of Electrical Asymmetries in Induction Machines

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Climente Alarcon, V.; Antonino Daviu, JA.; Haavisto, A.; Arkkio, A. (2014). Particle Filter-Based Estimation of Instantaneous Frequency for the Diagnosis of Electrical Asymmetries in Induction Machines. IEEE Transactions on Instrumentation and Measurement. 63(10):2454-2463. doi:10.1109/TIM.2014.2310113

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Título: Particle Filter-Based Estimation of Instantaneous Frequency for the Diagnosis of Electrical Asymmetries in Induction Machines
Autor: Climente Alarcón, Vicente Antonino Daviu, José Alfonso Haavisto, Ari Arkkio, Antero
Entidad UPV: Universitat Politècnica de València. Departamento de Ingeniería Eléctrica - Departament d'Enginyeria Elèctrica
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Resumen:
Fault diagnosis of induction machines operating under variable load conditions is still an unsolved matter. Under those regimes, the application of conventional diagnostic techniques is not suitable, since they are ...[+]
Palabras clave: Fault diagnosis , Induction motors , Particle filters , Prognosis , Time frequency analysis , Variable load , Wigner Ville distribution (WVD) , Wind energy
Derechos de uso: Cerrado
Fuente:
IEEE Transactions on Instrumentation and Measurement. (issn: 0018-9456 ) (eissn: 1557-9662 )
DOI: 10.1109/TIM.2014.2310113
Editorial:
Institute of Electrical and Electronics Engineers (IEEE)
Versión del editor: http://dx.doi.org/10.1109/TIM.2014.2310113
Descripción: "© 2014 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 works.” Upon publication, authors are asked to include either a link to the abstract of the published article in IEEE Xplore®, or the article’s Digital Object Identifier (DOI).
Tipo: Artículo

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