Litcius/Paper detail

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

Andrés Sio-Sever, E. Muñoz, Juan Manuel López, Ricardo Alzugaray-Franz, Antonio Vizán Idoipe, Guillermo de Arcas

2020Sensors12 citationsDOIOpen Access PDF

Abstract

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.

Topics & Concepts

MachiningAcoustic emissionProcess (computing)Energy (signal processing)SIGNAL (programming language)DynamometerMechanical engineeringSignal processingEngineeringMachine toolSignal conditioningComputer scienceAcousticsElectronic engineeringPower (physics)Digital signal processingStatisticsPhysicsMathematicsProgramming languageQuantum mechanicsOperating systemAdvanced machining processes and optimizationAdvanced Machining and Optimization TechniquesAdvanced Sensor Technologies Research