Open AccessCurrent aspects in automation of scientific researches of machinery surface quality using machine learning methods
Author(s) -
Vyacheslav Bezyazychnyy,
I. N. Palamar
Publication year - 2021
Publication title -
naukoëmkie tehnologii v mašinostroenii
Language(s) - English
Resource type - Journals
ISSN - 2223-4608
DOI - 10.30987/2223-4608-2021-7-12-19
Subject(s) - statistic , automation , surface roughness , surface (topology) , trace (psycholinguistics) , probabilistic logic , computer science , quality (philosophy) , sputtering , basis (linear algebra) , artificial intelligence , layer (electronics) , engineering drawing , mechanical engineering , materials science , machine learning , engineering , nanotechnology , mathematics , statistics , composite material , physics , thin film , geometry , linguistics , quantum mechanics , philosophy
A procedure is shown for the analysis of material structure in the parts surface layer manufactured through ion-plasma sputtering allowing the allocation and estimate automatically layers according to dislocation uniformity. A procedure is offered for the assessment of surface roughness on the basis of probabilistic-statistic classification of Talyrond trace allowing the definition and estimate automatically the peculiarities of a surface profile.