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    Por favor, use este identificador para citar o enlazar este ítem:https://uvadoc.uva.es/handle/10324/59253

    Título
    Sensorless speed estimation for the diagnosis of induction motors via MCSA. Review and commercial devices analysis
    Autor
    Bonet Jara, Jorge
    Quijano Lopez, Alfredo
    Moríñigo Sotelo, DanielAutoridad UVA Orcid
    Pons Llinares, Joan
    Año del Documento
    2021
    Editorial
    MDPI
    Descripción
    Producción Científica
    Documento Fuente
    Sensors, 2021, Vol. 21, Nº. 15, 5037
    Resumen
    Sensorless speed estimation has been extensively studied for its use in control schemes. Nevertheless, it is also a key step when applying Motor Current Signature Analysis to induction motor diagnosis: accurate speed estimation is vital to locate fault harmonics, and prevent false positives and false negatives, as shown at the beginning of the paper through a real industrial case. Unfortunately, existing sensorless speed estimation techniques either do not provide enough precision for this purpose or have limited applicability. Currently, this is preventing Industry 4.0 from having a precise and automatic system to monitor the motor condition. Despite its importance, there is no research published reviewing this topic. To fill this gap, this paper investigates, from both theoretical background and an industrial application perspective, the reasons behind these problems. Therefore, the families of sensorless speed estimation techniques, mainly conceived for sensorless control, are here reviewed and thoroughly analyzed from the perspective of their use for diagnosis. Moreover, the algorithms implemented in the two leading commercial diagnostic devices are analyzed using real examples from a database of industrial measurements belonging to 79 induction motors. The analysis and discussion through the paper are synthesized to summarize the lacks and weaknesses of the industry application of these methods, which helps to highlight the open problems, challenges and research prospects, showing the direction in which research efforts have to be made to solve this important problem.
    Materias (normalizadas)
    Electric motors, Induction
    Motores de inducción
    Motores
    Industry 4.0
    Industria - Tecnología
    Materias Unesco
    3306.03 Motores Eléctricos
    Palabras Clave
    Fault diagnosis
    MCSA
    Sensorless speed estimation
    ISSN
    1424-8220
    Revisión por pares
    SI
    DOI
    10.3390/s21155037
    Patrocinador
    Universidad Politécnica de Valencia y Ministerio de Ciencia, Innovación y Universidades (Proyecto FPU19/02698)
    Version del Editor
    https://www.mdpi.com/1424-8220/21/15/5037
    Propietario de los Derechos
    © 2021 The authors
    Idioma
    eng
    URI
    https://uvadoc.uva.es/handle/10324/59253
    Tipo de versión
    info:eu-repo/semantics/publishedVersion
    Derechos
    openAccess
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    • DEP45 - Artículos de revista [44]
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