Determination of Tool Wear in Turning Process Using Undecimated Wavelet Transform and Textural Features. (2015)

• Record Type: Journal Article
• Authors: Danesh, Mahdi; Khalili, Khalil
• Is Part Of: Procedia technology. Volume 19(2015)
• Page Start: 98
• Page End: 105
• Publication Date: 2015
• Subjects: Tool Wear -- Turning -- Image Processing -- Undecimated Wavelet Transform -- Texture Features.; Technology -- Congresses; Technology -- Periodicals; Engineering -- Congresses; Engineering -- Periodicals; Engineering; Technology; Conference proceedings; Periodicals; 605
• DOI: 10.1016/j.protcy.2015.02.015
• Languages: English
• ISSNs: 2212-0173

Abstract

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.