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Reducción de la dependencia de etiquetas en el monitoreo de la condición de brocas basado en vibraciones con
M N Chandan1,2, Avinash Badadhe2, Alemu Workie Kebede3
1Department of Mechanical Engineering, G H Raisoni College of Engineering and Management, Pune, Maharashtra, 412207, India.
Este estudio presenta un marco de preentrenamiento de características enmascaradas (SSL-MFP) autosupervisado para el monitoreo de la condición de herramientas (TCM). El método reduce significativamente la necesidad de datos etiquetados en el aprendizaje automático, lo que permite una clasificación precisa del desgaste con menos anotaciones.
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