In-Situ Surface Roughness Evaluation of Surfaces Machined with EDM by Image Processing

• Published in: Journal of nondestructive evaluation Vol. 41; no. 2
• Main Authors: Ali, J. Mahashar, Jailani, H. Siddhi, Murugan, M.
• Format: Journal Article
• Language: English
• Published: New York Springer US 01.06.2022; Springer Nature B.V
• Subjects: Characterization and Evaluation of Materials; Classical Mechanics; Control; Dynamical Systems; Electric discharge machining; Engineering; Evaluation; Histograms; Image processing; Image quality; Mathematical analysis; Parameters; Reliability analysis; Solid Mechanics; Standard deviation; Styli; Surface roughness; Vibration; Vision systems; Wavelet transforms; White light; Measurement; Surface roughness; Vision system; Image processing; EDM; 2-D biorthogonal wavelets
• ISSN: 0195-9298; 1573-4862
• DOI: 10.1007/s10921-022-00864-3

In quality manufacturing, measurement of surface roughness addressed as important next to dimensional metrology. In this study, the in-situ surface roughness of Electrical Discharge Machined (EDM) surfaces was evaluated using vision system, image processing tools and mathematical transformations of biorthogonal two dimensional wavelet transform. The white light images were obtained by high magnification camera and they were 2-D wavelet transformed and processed using MATLAB software. From the 2-D wavelet transformed images, the histogram image parameters such as mean and the standard deviations for the 4th and 5th level detail coefficient were obtained. The correlation between the image parameter standard deviation and stylus parameters R a , R da and R dq clearly indicated a good linear relationship. Especially the hybrid surface slope parameters R da and R dq shows a good effectiveness in correlation as 0.813 and 0.806 respectively. Hence the proposed methodology can be used for in-situ roughness evaluation of surfaces machined with EDM with reliability.