ISSN:
1013-9826
Source:
Scientific.Net: Materials Science & Technology / Trans Tech Publications Archiv 1984-2008
Topics:
Mechanical Engineering, Materials Science, Production Engineering, Mining and Metallurgy, Traffic Engineering, Precision Mechanics
Notes:
Surface roughness is an important quality characteristic in grinding. Measurement ofsurface roughness by means of mechanical stylus is widely done in metrology. In this paper, a newmachine vision system has been utilized to quantify the surface roughness of machined surfaces(ground and milled). Compared with other measurement methods, it is accurate, quick and credible.This system is mounted on the grinding machine and automates the measurement process by usingcomputer control to automatically position the CCD and capture digital images of machinedsurfaces between grinding cycles. It was proposed that the proportional formula was used incalibrating this system, and calibration precision meets application requirement. Not only thestatistic character of gray image but also which of edge image were calculated out. These charactersinclude the mean value of pixels (Mean), standard deviation (σ), maximal value (Max) and minimalvalue (Min), the number of pixels on the examine line(Count), etc. It was found out that thestandard deviation value σ of the gray image could express the surface roughness most. Thecorrelation between σ and Ra is established by interpolating σ value used Lagrange interpolationlaw, and the σ value is converted into Ra value through the calculation procedure finally
Type of Medium:
Electronic Resource
URL:
http://www.tib-hannover.de/fulltexts/2011/0528/01/53/transtech_doi~10.4028%252Fwww.scientific.net%252FKEM.339.147.pdf
