ISSN 0021-3454 (print version)
ISSN 2500-0381 (online version)
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8
Issue
vol 60 / AUGUST, 2017
Article

DOI 10.17586/0021-3454-2015-58-6-485-491

UDC 629.7.036:621.373

CONTROL OVER RASTER IMAGE CONTRAST IN LASER MARKING: TECHNOLOGICAL PROCESS MODELLING

O. S. Yulmetova
Concern “CSRI Elektropribor”; JSC, Postgraduate


A. G. Scherbak
Concern CSRI “Elektropribor”, JSC, St. Petersbur; Leading Scientist


V. P. Veiko
ITMO University, Saint Petersburg, 197101, Russian Federation; Department Head


R. . Yulmetova
Saint Petersburg State University of Refrigeration and Food Technologies; lecturer


S. A. Shcherbak
St Petersburg Academic University — Nanotechnology Research and Education Centre of the RAS, Department of Physics and Technology of Nanoheterostructures; Student


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Abstract. A method is proposed for evaluation of conditions and variation interval for laser surface treatment parameters in laser marking of raster images on spherical electrostatic gyroscope rotors. The method makes it possible to manage the raster image contrast at retained accuracy of hundredths of a micrometer. The contrast simulation code is developed on the base of a model of contrast management process in the form of successive stages associated with the procedure of choosing the optimal approximating function. Nonparametric approximation is used at the first stage, when only the most general information on the dependence under investigation is available. At the second stage the model of the dependence is supposed to be known, a parametric approximation is performed and a quantitative indication of the model parameters is carried out. Application of the proposed model for laser marking for the general case and for a particular labeling of thin-film coating of titanium nitride is justified. A family of curves defining the contrast dependence on the laser power for various stoichiometric composition of titanium nitride TiNx (x = 0,80—1,00) is presented. Results of the practical use of the technology are presented.
Keywords: laser marking, raster image, contrast, modeling, approximation, titanium nitride, stoichiometry