Quantitative Analysis of Grinding Wheel Loading Using Image Processing. (2016)

• Record Type: Journal Article
• Authors: Gopan, Vipin; Wins, K. Leo Dev
• Is Part Of: Procedia technology. Volume 25(2016)
• Page Start: 885
• Page End: 891
• Publication Date: 2016
• Subjects: Grinding wheel -- Machine vision -- Image segmentation -- Global thresholding -- Wheel loading; Technology -- Congresses; Technology -- Periodicals; Engineering -- Congresses; Engineering -- Periodicals; Engineering; Technology; Conference proceedings; Periodicals; 605
• DOI: 10.1016/j.protcy.2016.08.198
• Languages: English
• ISSNs: 2212-0173

Abstract

Abstract: Grinding is an abrasive machining process which can produce very fine surface finishes. The removed chips from the workpiece which get welded to the porosities between the abrasive grains can adversely affect the final surface finish of the machined component. Quantitative analysis of wheel loading can provide information about the cutting conditions of the wheel. With the development in the field of machine vision and image processing, this study focuses on developing a system for the quantitative assessment of wheel loading using image capturing and image processing. Images of the grinding wheel were acquired using microscope with a magnification of 20x. Image segmentation by global thresholding technique was utilized for segmenting the loaded portions from the rest of the wheel. Experimental results presented show the feasibility of the proposed system in the quantitative assessment of grinding wheel loading.