Analysis of the input material flow of the transport conveyor

Purpose. To develop a method for analyzing the material flow entering the input of a conveyor section, based on the decomposition of the input material flow into a deterministic material flow and a stochastic material flow. Methodology. The analysis of experimental data characterizing the input material flow was performed using the methods of the canonical Fourier representation of a random process. Findings. A method for representing a stochastic material flow as a combination of a deterministic process and a stationary random process with ergodic properties is proposed. Originality. The originality of the obtained results lies in the fact that, for the first time, a method of analysis based on the decomposition of the input material flow for a conveyor section has been proposed, which, unlike the existing methods of input flow typing for the mining industry, will allow us to independently perform deterministic flow typing and stochastic material flow typing in transport conveyors. The proposed approach makes it possible to highlight special characteristics separately for deterministic and stochastic material flows. This will make it possible to use the obtained regularities to increase the accuracy of the conveyor model and will accordingly increase the quality of the belt speed control systems and the flow of material coming from the input bunker. The obtained results are of particular importance due to the fact that the characteristics of the deterministic material flow are directly related to the technical or technological factors of material extraction. Practical value. The obtained results allow determining statistically stable regularities for the incoming flow, which makes it possible, based on these regularities from the set of available control algorithms, to choose the optimal control algorithm for the parameters of the operating conveyor section. This allows reducing the enterprise’s energy costs of the transportation of material. The proposed method can be successfully applied to build random number generators simulating the sequence of values of the input flow of material. The developed generators can be used both for validating existing belt speed control systems and creating new control systems based on neural networks. This opens perspectives for the design of effective systems for controlling the flow parameters of transport system, based on the transport conveyor model, which takes into account the stochastic nature of the incoming material flow.