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Vision Based Surface Roughness Characterization of Flat Surfaces Machined with EDM BSA Crescent Institute of Science and Technology
- Format:
- Book
- Conference/Event
- Author/Creator:
- Ali, Mahashar, author.
- 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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