Improved Estimation of End-Milling Parameters from Acoustic Emission Signals Using a Microphone Array Assisted by AI Modelling

This paper presents the implementation of a measurement system that uses a four microphone array and a data-driven algorithm to estimate depth of cut during end milling operations. The audible range acoustic emission signals captured with the microphones are combined using a spectral subtraction and...

Descripción completa

Detalles Bibliográficos
Autores principales: Sio-Sever, Andrés, Lopez, Juan Manuel, Asensio-Rivera, César, Vizan-Idoipe, Antonio, de Arcas, Guillermo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9146282/
https://www.ncbi.nlm.nih.gov/pubmed/35632214
http://dx.doi.org/10.3390/s22103807

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9146282/
https://www.ncbi.nlm.nih.gov/pubmed/35632214
http://dx.doi.org/10.3390/s22103807

Ejemplares similares