Morinigo-Sotelo, D.; Romero-Troncoso, R.; Panagiotou, P.; Antonino-Daviu, J.; Gyftakis, KN. (2018). Reliable Detection of Rotor Bars Breakage in Induction Motors via MUSIC and ZSC Methods. IEEE Transactions on Industry Applications. 54(2):1224-1234. https://doi.org/10.1109/TIA.2017.2764846
Por favor, use este identificador para citar o enlazar este ítem: http://hdl.handle.net/10251/145975
Título:
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Reliable Detection of Rotor Bars Breakage in Induction Motors via MUSIC and ZSC Methods
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Autor:
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Morinigo-Sotelo, Daniel
Romero-Troncoso, R.D.
Panagiotou, P.A.
Antonino-Daviu, J.A.
Gyftakis, Konstantinos N.
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Entidad UPV:
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Universitat Politècnica de València. Departamento de Ingeniería Eléctrica - Departament d'Enginyeria Elèctrica
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Fecha difusión:
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Resumen:
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[EN] Induction motors are used in a variety of industrial applications where frequent startup cycles are required. In those cases, it is necessary to apply sophisticated signal processing analysis methods in order to ...[+]
[EN] Induction motors are used in a variety of industrial applications where frequent startup cycles are required. In those cases, it is necessary to apply sophisticated signal processing analysis methods in order to reliably follow the time evolution of fault-related harmonics in the signal. In this paper, the zero-sequence current (ZSC) is analyzed using the high-resolution spectral method of multiple signal classification. The analysis of the ZSC signal has proved to have several advantages over the analysis of a single-phase current waveform. The method is validated through simulation and experimental results. The simulations are carried out for a 1.1-MW and a 4-kW induction motors under finite element analysis. Experimentation is performed on a healthy motor, a motor with one broken rotor bar, and a motor with two broken rotor bars. The analysis results are satisfactory since the proposed methodology reliably detects the broken rotor bar fault and its severity, both during transient and steady-state operation of the induction motor.
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Palabras clave:
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Induction motors
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Rotors
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Bars
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Harmonic analysis
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Multiple signal classification
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Transient analysis
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Stator windings
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Derechos de uso:
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Reserva de todos los derechos
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Fuente:
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IEEE Transactions on Industry Applications. (issn:
0093-9994
)
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DOI:
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10.1109/TIA.2017.2764846
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Editorial:
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Institute of Electrical and Electronics Engineers
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Versión del editor:
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https://doi.org/10.1109/TIA.2017.2764846
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Título del congreso:
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XXIIth International Conference on Electrical Machines (ICEM 2016)
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Lugar del congreso:
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Lausanne, Switzerland
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Fecha congreso:
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Septiembre 04-07,2016
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Código del Proyecto:
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info:eu-repo/grantAgreement/MINECO//DPI2014-52842-P/ES/COMBINACION DE TECNICAS NO INVASIVAS DE MONITORIZACION DEL ESTADO PARA EL DESARROLLO DE MOTORES ELECTRICOS INTELIGENTES/
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Descripción:
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"(c) 2018 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"
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Agradecimientos:
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This work was supported in part by the Spanish Ministerio de Economia y Competitividad (MINECO) and in part by the FEDER program in the framework of the Proyectos I+D del Subprograma de Generacion de Conocimiento, Programa ...[+]
This work was supported in part by the Spanish Ministerio de Economia y Competitividad (MINECO) and in part by the FEDER program in the framework of the Proyectos I+D del Subprograma de Generacion de Conocimiento, Programa Estatal de Fomento de la Investigacion Cientifica y Tecnica de Excelencia under Grant DPI2014-52842-P.
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Tipo:
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Artículo
Comunicación en congreso
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