Optimal control of the drive drum of a belt conveyor with thermographic classification of operating modes using artificial neural networks

Optimum control of the drive drum of the belt conveyor in the transport flow by changing the belt tension is proposed in order to reduce the cost of transporting goods, increase the life of the belt, and reduce energy consumption due to the control of temperature and its distribution in the zone of frictional interaction between the belt and the drum. It is suggested to use belt tension control to eliminate the accidental slipping of the belt on the drum and its excessive abrasion during the transportation of the ore mass. To implement the control method being developed, it is necessary to use a mathematical model with distributed parameters, on the basis of which the optimal control system will be formed. Control of this kind of objects is determined by the technological need to compensate for the slippage of the belt on the drive drum of the conveyor, which is based on the process of transmission of motion using friction, and is implemented by changing the thermal field on the arc of the girth by changing the tension of the conveyor belt or the speed of rotation of the drum. Thus, from the point of view of the theory of control of systems with distributed parameters in the process of controlling the thermal field of the drive drum and the conveyor belt, the controlled coordinate is the temperature and its distribution on the girth arc. As a result of physical processes, both the size of the source of the heat flux and the size of the surface of its radiation change during the control of the tape tension. Thus, the problem of optimal control acquires a new character and turns into a problem of moving optimal control, where the source of the heat flow, just like its distribution, is considered as a moving element that changes its position during the control process. The use of an artificial neural network allows you to determine the modes of operation of the friction pair by analyzing thermograms from the obtained calculation models and obtained by thermal imaging control, to combine problems with distributed parameters, which are partial solutions to the problem of moving optimal control, where the source of heat flow and its distribution is considered as a moving element, which changes its position during the control.