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Deep Learning-Based Feature Extraction of Acoustic Emission Signals for Monitoring Wear of Grinding Wheels

Tool wear monitoring is a critical issue in advanced manufacturing systems. In the search for sensing devices that can provide information about the grinding process, Acoustic Emission (AE) appears to be a promising technology. The present paper presents a novel deep learning-based proposal for grin...

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Detalles Bibliográficos
Autores principales:	González, D., Alvarez, J., Sánchez, J. A., Godino, L., Pombo, I.
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	MDPI 2022
Materias:	Article
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9503273/ https://www.ncbi.nlm.nih.gov/pubmed/36146262 http://dx.doi.org/10.3390/s22186911

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