The use of intelligent approaches to improve the quality of plasma coatings

Author

Lasnikov, Vladimir N. ; Speransky, Sergey K.

Author_Institution

State Tech. Univ. of Saratov, Saratov, Russia

fYear

2014

fDate

June 30 2014-July 4 2014

Firstpage

124

Lastpage

125

Abstract

The main source of information was data collected in the study of the morphology of the surface after different modes of plasma spraying [1]. Microstructure analysis of data shows that coatings have strongly developed structure consisting of deformed melted particles with spherical shapes. Developing the algorithms and software for automatic detection of microparticles in digital images is of practical importance. With these tools available, we are able to create the automatic evaluation system for specific parameters of sprayed-on materials in the digital photos depicting their surfaces. We will be able to know the relative number of spheroidal particles and thereby forcast technological and operational properties of a coating.

Keywords

genetic algorithms; image classification; neural nets; object detection; plasma arc spraying; principal component analysis; production engineering computing; PCA; automatic evaluation system; digital images; genetic algorithm optimization; intelligent approach; microparticles automatic detection; microstructure analysis; neural network; plasma coatings quality; plasma spraying; principal component method; surface morphology; Coatings; Neural networks; Plasmas; Principal component analysis; Spraying; Vectors;

fLanguage

English

Publisher

ieee

Conference_Titel

Computer Technologies in Physical and Engineering Applications (ICCTPEA), 2014 International Conference on

Conference_Location

St. Petersburg

Print_ISBN

978-1-4799-5315-8

Type

conf

DOI

10.1109/ICCTPEA.2014.6893315

Filename

6893315