The neural networks application in predicting the geometrical parameters of coatings formed on a steel substrate by laser alloying

摘要

A mathematical model for predicting the geometric parameters of boron and aluminum-based coatings formed on a steel substrate by laser alloying is presented in the work. The model combines the principles of the theory of experiment planning with an artificial neural network (ANN) apparatus. Coatings were formed by means of laser heating of the steel surface with a pre-applied treatment paste. The ANN was built, trained and tested for the prediction of the width and depth of the molten bath on a steel substrate. The prediction results of the obtained neural network were compared with the corresponding linear models. The efficiency of the considered approach and the possibility of its application for predicting the values of laser treatment of steel parts of machines subjected to surface hardening are shown. The presented approach allows to use one mathematical model for predicting several parameters, thereby reducing the number of experiments.