Study on Monitoring and Control of Machining Process by Acoustic Emission Technique

Abstract

In this study, the relationships between the frequency component of acoustic emission signals and the cutting state were examined in various machining processes such as turning, drilling and milling. As a result, it was found that adhesion of the workpiece material to the rake face of the cutting tool could be identified by high frequency AE signals of more than 1 MHz. Also, it was found that the occurrence frequency of high frequency AE signals increases as cutting distance increases. If AE sensing technique would be applied in developing IoT systems or smart systems for machine tools, it cannot only improve the quality and efficiency of machine tools but it could also greatly contribute in saving energy and resources.