Abstract
The state of a cutting tool is a critical factor in any metal cutting process because dull or damaged cutting tool reduces surface quality and dimensional accuracy of workpiece and damages the machine tool. This paper proposes a novel vision-based approach for determining tool wear in metal cutting. The surface irregularity changes caused by tool wear are used as a criterion for estimating the cutting tool wear. Undecimated Wavelet Transform is used to decompose the surface image of the workpiece into sub-images in which the cutting tool wear can be indicated. The texture of sub-images is analyzed using GLCM texture features. The experimental results showed that the combination of undecimated wavelet decomposition and GLCM texture features can be used as a robust method for determining tool wear in the turning process.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
