MANAGEMENT OF THE VAULTING SYSTEM BULK MATERIALS BASED ON A NEURAL NETWORK

Abstract

Background. This article presents the composition and algorithm of the automated control system for the parameters of a pneumatic arch-breaking system installed on bunkers with bulk materials. The relevance and practical significance of the issue considered in the article is determined by the fact that when unloading bulk material from the hopper, various violations of the technological process may occur, manifested in the formation of material freezes inside the container, a decrease in the amount of unloaded material, segregation, up to a complete stop of unloading due to the formation of arches. Materials and/or methods. Methods of mathematical modeling, system analysis, comparison, systems theory, as well as architecture and mathematical model of a recurrent neural network with feedback are used. Results. The composition of input and output parameters of the control system is substantiated. Methods for solving problems of classifying parameter sets are considered and an artificial recurrent neural network with feedback and with a sigmoidal activation function of neurons of the hidden layer and a linear activation function of the output layer is selected. Conclusion. The article analyzes the requirements for the system of automated control of the parameters of the pneumatic arch-breaking system. Based on the analysis of possible states of the system, the composition of the system elements and the sets of input, intermediate and output parameters of the system, as well as the objective function of the system operation, are substantiated. It is shown that the system can be built on the basis of an artificial neural network. The algorithm of the automated control system for the parameters of the pneumatic arch-breaking system has been developed.

Keywords

• bunker
• bulk materials
• pneumatic vault-breaking system
• vault formation
• automatic control system
• artificial neural network
• neural network training