Application of neural network technologies to solving the problem of materials classification of two-layer structure by hardness parameter

Don state technical University, Gagarin square 1, 344003 Rostov-on-Don, Russia

^* Corresponding author: copybird@yandex.ru

Abstract

The focus of the article is on utilizing neural networks, a form of artificial intelligence, to address the task of categorizing mechanical characteristics of diverse materials. Brinell hardness was chosen as the considered characteristics of materials for the study, the choice of this property was justified. The study simulates a finite element model of the impact of an indenter on a two-layer structure in an Ansys environment. The difference in the properties of the construction materials is determined by the application of a strengthening coating or the accumulation of multiple defects in the surface layer. Using the model, a set of data for training a neural network was obtained. As part of the experimental part, the structure of the neural network was developed, its hyperparameters were adjusted. A comparative analysis is presented that examines two different methods for neural network calculations based on the nature of the input impact.