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

• Main Authors: Andrés Sio-Sever, Erardo Leal-Muñoz, Juan Manuel Lopez-Navarro, Ricardo Alzugaray-Franz, Antonio Vizan-Idoipe, Guillermo de Arcas-Castro
• Format: Article
• Language: English
• Published: MDPI AG 2020-09-01
• Series: Sensors
• Subjects: microphone; MEMS; machining; milling; acoustic emission; process monitoring
• Online Access: https://www.mdpi.com/1424-8220/20/18/5326

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.