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    Por favor, use este identificador para citar o enlazar este ítem: http://hdl.handle.net/10259/4263

    Título
    A vrtual sensor for online fault detection of multitooth-tools
    Autor
    Bustillo Iglesias, AndrésAutoridad UBU Orcid
    Correa, Maritza
    Reñones, Anibal
    Publicado en
    Sensors, 2011, V. 11, n. 3, p. 2282-3400
    Editorial
    MDPI
    Fecha de publicación
    2011-03
    ISSN
    1424-8220
    DOI
    10.3390/s110302773
    Resumen
    The installation of suitable sensors close to the tool tip on milling centres is not possible in industrial environments. It is therefore necessary to design virtual sensors for these machines to perform online fault detection in many industrial tasks. This paper presents a virtual sensor for online fault detection of multitooth tools based on a Bayesian classifier. The device that performs this task applies mathematical models that function in conjunction with physical sensors. Only two experimental variables are collected from the milling centre that performs the machining operations: the electrical power consumption of the feed drive and the time required for machining each workpiece. The task of achieving reliable signals from a milling process is especially complex when multitooth tools are used, because each kind of cutting insert in the milling centre only works on each workpiece during a certain time window. Great effort has gone into designing a robust virtual sensor that can avoid re-calibration due to, e.g., maintenance operations. The virtual sensor developed as a result of this research is successfully validated under real conditions on a milling centre used for the mass production of automobile engine crankshafts. Recognition accuracy, calculated with a k-fold cross validation, had on average 0.957 of true positives and 0.986 of true negatives. Moreover, measured accuracy was 98%, which suggests that the virtual sensor correctly identifies new cases.
    Palabras clave
    virtual sensor
    Bayesian classifier
    industrial applications
    tool condition monitoring
    multitooth-tools
    Materia
    Informática
    Computer science
    URI
    http://hdl.handle.net/10259/4263
    Versión del editor
    http://dx.doi.org/10.3390/s110302773
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    • Artículos ADMIRABLE
    Attribution 3.0 Unported
    Documento(s) sujeto(s) a una licencia Creative Commons Attribution 3.0 Unported
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    Nombre:
    Bustillo-Sensors_2011.pdf
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    487.0Kb
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