Research on the applicability of color vision-based roughness inspection method. (1st June 2022)

• Record Type: Journal Article
• Authors: Yi, Huaian; Fang, Runji; Wang, Shuai; Niu, Yilun; Jiao, Yanming
• Is Part Of: Surface topography. Volume 10:Number 2(2022)
• Publication Date: 2022-06-01
• Subjects: average color difference -- machining process -- surface roughness -- workpiece materials; Surfaces (Physics) -- Periodicals; Surfaces (Physics) -- Measurement -- Periodicals; 530.417
• DOI: 10.1088/2051-672X/ac6c1d
• Languages: English
• ISSNs: 2051-672X

Abstract

Abstract: This study was designed to address the issue that the machine vision-based measurement method of surface roughness based on color information cannot be universally applicable to different machining processes and materials. To this end, the performance of the average color difference ( CD ) and five typical spectrum indices in the characterization of the surface roughness of two representative texture processes, namely milling and grinding, were explored in the present study. The research results proved that the CD had a stronger correlation with surface roughness and a better robustness to the incident angle than spectrum indices, and the cause for the correlation of index with milling sample being weaker than that with grinding sample was studied from the mechanism. Besides, the correlation between the CD and the surface roughness of different materials was investigated. The results showed that the correlation between roughness and the CD of different materials was stable under different incident angles and ambient light noise. However, the differences in the mathematical relationship models between the indices and the roughness of different materials proved that the materials had a mathematical nature effect on color information detection roughness. In conclusion, this experiment validates the effectiveness of machine vision-based roughness inspection method based on color information and common light sources.