Open AccessEvaluation of the mechanism of the destruction of metals based on approaches of artificial intelligence and fractal analysis
Author(s) -
Yu. G. Kabaldin,
М. С. Аносов,
Д. А. Шатагин
Publication year - 2020
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/709/3/033076
Subject(s) - fractal dimension , fractal , brittleness , mechanism (biology) , artificial neural network , convolutional neural network , artificial intelligence , wavelet transform , fractal analysis , materials science , biological system , wavelet , pattern recognition (psychology) , computer science , mathematics , physics , metallurgy , mathematical analysis , biology , quantum mechanics
The article examines modern informational approaches to assess the degree of damageability of materials based on their fractographic images. The possibility of using the fractal dimension, wavelet transform and convolutional artificial neural networks for tiling and classifying the share of viscous and brittle destructions on fractures is shown. The results of experimental studies of the impact viscosity of materials with different types of crystal lattices in a wide range of temperatures are presented.