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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

Por favor, use este identificador para citar o enlazar este ítem: http://hdl.handle.net/10251/70912

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Title: Particle Filter-Based Estimation of Instantaneous Frequency for the Diagnosis of Electrical Asymmetries in Induction Machines
Author:
UPV Unit: Universitat Politècnica de València. Departamento de Ingeniería Eléctrica - Departament d'Enginyeria Elèctrica
Issued date:
Abstract:
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 ...[+]
Subjects: Fault diagnosis , Induction motors , Particle filters , Prognosis , Time frequency analysis , Variable load , Wigner Ville distribution (WVD) , Wind energy
Copyrigths: Cerrado
Source:
IEEE Transactions on Instrumentation and Measurement. (issn: 0018-9456 ) (eissn: 1557-9662 )
DOI: 10.1109/TIM.2014.2310113
Publisher:
Institute of Electrical and Electronics Engineers (IEEE)
Publisher version: http://dx.doi.org/10.1109/TIM.2014.2310113
Description: "© 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).
Type: Artículo

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