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

Autor: Andrés Sio-Sever, Erardo Leal-Muñoz, Juan Manuel Lopez-Navarro, Ricardo Alzugaray-Franz, Antonio Vizan-Idoipe, Guillermo de Arcas-Castro
Jazyk: angličtina
Rok vydání: 2020
Předmět:
Zdroj: Sensors, Vol 20, Iss 18, p 5326 (2020)
Druh dokumentu: article
ISSN: 1424-8220
DOI: 10.3390/s20185326
Popis: 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.
Databáze: Directory of Open Access Journals
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