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Vision Based Surface Roughness Characterization of Flat Surfaces Machined with EDM BSA Crescent Institute of Science and Technology

SAE Technical Papers (1906-current) Available online

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Format:
Book
Conference/Event
Author/Creator:
Ali, Mahashar, author.
Contributor:
Anandan, Mangalnath
Jailani, Siddhi
Mariappan, Murugan
Pavithran, Vignesh
Conference Name:
International Conference on Advances in Design, Materials, Manufacturing and Surface Engineering for Mobility (2019-10-11 : Chennai, India)
Language:
English
Physical Description:
1 online resource cm
Place of Publication:
Warrendale, PA SAE International 2019
Summary:
Surface roughness measurement is an important one in any manufacturing next to dimensions. In this investigation, a vision system and image processing tools were used to develop reliable surface roughness characterization technique for Electrical Discharge Machined surfaces. A CMOS camera with red LED light source were used for capturing images of EDMed surfaces. A separate signal vector generated for all the images from its image pixel intensity matrices. The mean, skewness and kurtosis were obtained from the signal vector. The mean, skewness and kurtosis of the images signal vector correlates very well with the stylus measured hybrid roughness parameters Rda and Rdq. Hence the technique may be preferred for online surface roughness characterization of Electrical Discharge Machined (EDMed) surfaces
Notes:
Vendor supplied data
Publisher Number:
2019-28-0148
Access Restriction:
Restricted for use by site license

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