Abstract

Surface roughness evaluation is very important for many fundamental problems such as friction, contact deformation, tightness of contact joints positional accuracy etc. Many techniques have been developed for measuring surface finish ranging from the simple touch comparator to sophisticated optical techniques. In recent years, the advent of high-speed general-purpose digital computers and vision systems has made image analysis easier and more flexible. Unlike the stylus instruments, computer vision systems have the advantages of being non-contact and are capable of measuring an area from the surface rather than a single line. A vision system is considered relatively cheap, fast and suitable for automation.Work pieces are prepared with varied roughness using manufacturing process of EDM and subjected to different machining parameters such as variable current and voltage. The proposed method used vision system. Vision system consists of a CCD camera, frame grabber, advanced image processing card and a high end computer. The surface images are grabbed using CCD camera and then transferred to the computer memory through frame grabber. An image processing algorithm is prepared using MATLAB. The surface roughness parameter values (3D) obtained by Vision system are then compared with those obtained by Optical method. Strong correlation is obtained between the vision roughness and optical roughness parameters. Hence the proposed method can be used in the assessment of 3D surface finish. The complete analysis of results is presented in this work.

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