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    Por favor, use este identificador para citar o enlazar este ítem:https://uvadoc.uva.es/handle/10324/57658

    Título
    State of the art and trends in the monitoring, detection and diagnosis of failures in electric induction motors
    Autor
    Merizalde Zamora, Yury Humberto
    Hernández Callejo, LuisAutoridad UVA Orcid
    Duque Pérez, ÓscarAutoridad UVA Orcid
    Año del Documento
    2017
    Editorial
    MDPI
    Descripción
    Producción Científica
    Documento Fuente
    Energies, 2017, vol. 10, n. 7, p. 1056
    Résumé
    Despite the complex mathematical models and physical phenomena on which it is based, the simplicity of its construction, its affordability, the versatility of its applications and the relative ease of its control have made the electric induction motor an essential element in a considerable number of processes at the industrial and domestic levels, in which it converts electrical energy into mechanical energy. The importance of this type of machine for the continuity of operation, mainly in industry, is such that, in addition to being an important part of the study programs of careers related to this branch of electrical engineering, a large number of investigations into monitoring, detecting and quickly diagnosing its incipient faults due to a variety of factors have been conducted. This bibliographic research aims to analyze the conceptual aspects of the first discoveries that served as the basis for the invention of the induction motor, ranging from the development of the Fourier series, the Fourier transform mathematical formula in its different forms and the measurement, treatment and analysis of signals to techniques based on artificial intelligence and soft computing. This research also includes topics of interest such as fault types and their classification according to the engine, software and hardware parts used and modern approaches or maintenance strategies.
    Materias Unesco
    33 Ciencias Tecnológicas
    Palabras Clave
    Induction electric motors
    Maintenance strategies
    Types of faults
    Detection and diagnosis
    Monitoring
    Artificial intelligence
    Revisión por pares
    SI
    DOI
    10.3390/en10071056
    Version del Editor
    https://www.mdpi.com/1996-1073/10/7/1056
    Propietario de los Derechos
    © 2017 The Author(s)
    Idioma
    eng
    URI
    https://uvadoc.uva.es/handle/10324/57658
    Tipo de versión
    info:eu-repo/semantics/publishedVersion
    Derechos
    openAccess
    Aparece en las colecciones
    • DEP45 - Artículos de revista [47]
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    Nombre:
    State-art-trends.pdf
    Tamaño:
    1.426Mo
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    Atribución 4.0 InternacionalExcepté là où spécifié autrement, la license de ce document est décrite en tant que Atribución 4.0 Internacional

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