Abstract
The use of the optical device for the measurement of surface roughness reduces complexity and time for measurement. In the current study, surface roughness parameters were measured after machining on a shaper machine using the machine vision system which was compared with that obtained through the stylus method. Machining operation involves complexity and produces different surface finish with different cutting conditions, therefore in the present study correlation between surface roughness parameters (viz. arithmetic average height (Ra); maximum height of peaks (Rp); root mean square roughness (Rq); maximum height of the profile (Rt), and ten-point height (Rz)) and optical surface finish parameters (i.e., mean, standard deviation, skewness and kurtosis) has been developed for varied values of cutting parameters (i.e., depth of cut and RPM of pulley drive). The linear relation model with optical parameters and surface roughness parameters has been developed. It was observed that all the roughness parameters can be estimated with a fair degree of accuracy (R2 > 0.92) using optical statistical parameter kurtosis, while means, skewness, and standard deviation obtained through the same image processing data fail to estimate roughness parameters.
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Patel, D., Mysore, K., Thakkar, K. (2020). Noncontact Surface Roughness Assessment Using Machine Vision System. In: Narasimham, G., Babu, A., Reddy, S., Dhanasekaran, R. (eds) Recent Trends in Mechanical Engineering. Lecture Notes in Mechanical Engineering. Springer, Singapore. https://doi.org/10.1007/978-981-15-1124-0_49
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DOI: https://doi.org/10.1007/978-981-15-1124-0_49
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