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Sensor signal selection tool wear curve estimation and subsequent tool breakage prediction in a drilling operation.pdf (1.610Mb)
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Título
Sensor signal selection for tool wear curve estimation and subsequent tool breakage prediction in a drilling operation
Autor-a
Duo, AitorMondragon Unibertsitatea
Basagoiti, RosaMondragon Unibertsitatea
ARRAZOLA, PEDRO JOSE ccMondragon Unibertsitatea
CUESTA ZABALAJAUREGUI, MIKELMondragon Unibertsitatea
Grupo de investigación
Análisis de datos y ciberseguridad
Mecanizado de alto rendimiento
Fecha de publicación
2021
Editor
Taylor & Francis
Palabras clave
Tool condition monitoring
Inconel 718
Drilling
Data mining ... [+]
Tool condition monitoring
Inconel 718
Drilling
Data mining
Machine learning [-]
Resumen
Tool condition monitoring have an important role in machining processes to reduce defective component and ensure quality requirements. Stopping the process before the tool breaks or an excessive tool ... [+]
Tool condition monitoring have an important role in machining processes to reduce defective component and ensure quality requirements. Stopping the process before the tool breaks or an excessive tool wear is reached can avoid costs resulting from that undesirable situation. This research work presents the results obtained in drilling process monitoring carried out on Inconel 718. Monitoring systems should be light and scalable. Following this idea, multiple sensors for external signal acquisition are used in this work (cutting forces, vibrations, and acoustic emissions) and several machine internal signals are collected. The main objective is to evaluate the capacity of each acquisition source for the reconstruction of the tool wear curve and subsequently detection of tool breakage. Given the difficulty of using all of these signals in a real system, the methodology used to analyse the data makes it possible to have a comparative analysis of the potential of each of these sources for tool wear monitoring during the drilling process. The results indicate cutting forces whether they come from internal signals or external signals can carry out this task accurately. At the same time of data acquisition, detailed tool wear measurements were added. [-]
URI
https://hdl.handle.net/20.500.11984/5621
Versión del editor
https://doi.org/10.1080/0951192X.2021.1992661
ISSN
1362-3052
Publicado en
International Journal of Computer Integrated Manufacturing  Volume 35, Issue 2, 2022
Tipo de documento
Artículo
Versión
Postprint – Accepted Manuscript
Derechos
© 2021 Taylor & Francis
Acceso
Acceso embargado
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Recolectado por:

OpenAIREBASE

Validado por:

OpenAIRERebiun
MONDRAGON UNIBERTSITATEA | Biblioteca
Contacto | Sugerencias
DSpace