Datta, A. and Dutta, S. and Pal, S.K. and Sen, R. (2013) Progressive cutting tool wear detection from machined surface images using Voronoi tessellation method. Journal of Materials Processing Technology, 213. pp. 2339-2349. ISSN 0924-0136

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Abstract

Tool condition monitoring by machine vision approach has been gaining popularity day by day sinceit is a low cost and flexible method. In this paper, a tool condition monitoring technique by analysingturned surface images has been presented. The aim of this work is to apply an image texture analysistechnique on turned surface images for quantitative assessment of cutting tool flank wear, progressively.A novel method by the concept of Voronoi tessellation has been applied in this study to analyse thesurface texture of machined surface after the creation of Voronoi diagram. Two texture features, namely,number of polygons with zero cross moment and total void area of Voronoi diagram of machined surfaceimages have been extracted. A correlation study between measured flank wear and extracted texturefeatures has been done for depicting the tool flank wear. It has been found that number of polygons withzero cross moment has better linear relationship with tool flank wear than that of total void area.

Item Type:	Article
Subjects:	Condition monitoring
Depositing User:	Dr. Sarita Ghosh
Date Deposited:	06 Apr 2016 10:48
Last Modified:	06 Apr 2016 10:48
URI:	http://cmeri.csircentral.net/id/eprint/100

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