Tool Wear Condition Monitoring using Emitted Sound Signals by Acoustic - Electro Conversion

Abstract

The fully automated manufacturing system suffers from breakage and deterioration of tools. This paper proposes a novel setup and methodology to monitor the tool flank wear from emitted sound signals while turning operation is on. The proposed method is efficient then the other similar methods were a rough estimation of the tool condition into slight, medium and severe wear categories only can identified. But the proposed technique is free from using complex mathematical techniques and delivers the state of the tool wear in terms of voltage using the attached hardware circuits. By the conversion of the emitted sound pressure into corresponding voltage the correlation between the voltage and tool flank wear helped us to perfectly do the classification of carbide inserts which are created with Aluminium Titanium Nitride. The classification is done with the help of standard deviations from the class average of different categories. The classification accuracy is confirmed with correlation result and regression analysis 90% is reached with the proposed technique. Hence, the proposed technique would be utilized to monitor the tool condition while the turning process by converting the emitted sound into voltage by the proposed technique. An ANOVA test is made to ensure this significant difference between the voltages derived from the different categories of tool wear.