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Non-Invasive Estimation of Machining Parameters during End-Milling Operations Based on Acoustic Emission

This work presents a non-invasive and low-cost alternative to traditional methods for measuring the performance of machining processes directly on existing machine tools. A prototype measuring system has been developed based on non-contact microphones, a custom designed signal conditioning board and...

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Autores principales: Sio-Sever, Andrés, Leal-Muñoz, Erardo, Lopez-Navarro, Juan Manuel, Alzugaray-Franz, Ricardo, Vizan-Idoipe, Antonio, de Arcas-Castro, Guillermo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7571012/
https://www.ncbi.nlm.nih.gov/pubmed/32957656
http://dx.doi.org/10.3390/s20185326
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author Sio-Sever, Andrés
Leal-Muñoz, Erardo
Lopez-Navarro, Juan Manuel
Alzugaray-Franz, Ricardo
Vizan-Idoipe, Antonio
de Arcas-Castro, Guillermo
author_facet Sio-Sever, Andrés
Leal-Muñoz, Erardo
Lopez-Navarro, Juan Manuel
Alzugaray-Franz, Ricardo
Vizan-Idoipe, Antonio
de Arcas-Castro, Guillermo
author_sort Sio-Sever, Andrés
collection PubMed
description This work presents a non-invasive and low-cost alternative to traditional methods for measuring the performance of machining processes directly on existing machine tools. A prototype measuring system has been developed based on non-contact microphones, a custom designed signal conditioning board and signal processing techniques that take advantage of the underlying physics of the machining process. Experiments have been conducted to estimate the depth of cut during end-milling process by means of the measurement of the acoustic emission energy generated during operation. Moreover, the predicted values have been compared with well established methods based on cutting forces measured by dynamometers.
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spelling pubmed-75710122020-10-28 Non-Invasive Estimation of Machining Parameters during End-Milling Operations Based on Acoustic Emission Sio-Sever, Andrés Leal-Muñoz, Erardo Lopez-Navarro, Juan Manuel Alzugaray-Franz, Ricardo Vizan-Idoipe, Antonio de Arcas-Castro, Guillermo Sensors (Basel) Article This work presents a non-invasive and low-cost alternative to traditional methods for measuring the performance of machining processes directly on existing machine tools. A prototype measuring system has been developed based on non-contact microphones, a custom designed signal conditioning board and signal processing techniques that take advantage of the underlying physics of the machining process. Experiments have been conducted to estimate the depth of cut during end-milling process by means of the measurement of the acoustic emission energy generated during operation. Moreover, the predicted values have been compared with well established methods based on cutting forces measured by dynamometers. MDPI 2020-09-17 /pmc/articles/PMC7571012/ /pubmed/32957656 http://dx.doi.org/10.3390/s20185326 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Sio-Sever, Andrés
Leal-Muñoz, Erardo
Lopez-Navarro, Juan Manuel
Alzugaray-Franz, Ricardo
Vizan-Idoipe, Antonio
de Arcas-Castro, Guillermo
Non-Invasive Estimation of Machining Parameters during End-Milling Operations Based on Acoustic Emission
title Non-Invasive Estimation of Machining Parameters during End-Milling Operations Based on Acoustic Emission
title_full Non-Invasive Estimation of Machining Parameters during End-Milling Operations Based on Acoustic Emission
title_fullStr Non-Invasive Estimation of Machining Parameters during End-Milling Operations Based on Acoustic Emission
title_full_unstemmed Non-Invasive Estimation of Machining Parameters during End-Milling Operations Based on Acoustic Emission
title_short Non-Invasive Estimation of Machining Parameters during End-Milling Operations Based on Acoustic Emission
title_sort non-invasive estimation of machining parameters during end-milling operations based on acoustic emission
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7571012/
https://www.ncbi.nlm.nih.gov/pubmed/32957656
http://dx.doi.org/10.3390/s20185326
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