Research on Dynamic Analysis and Optimization of Belt Conveyor Based on Intelligent Algorithm and Big Data Algorithm

At present, there are some problems in the control of belt conveyor, such as the equipment works at a constant speed, and the conveying speed cannot be adjusted according to the actual traffic volume, which leads to a serious waste of electricity under small traffic volume. In this paper, the dynamic performance of belt conveyor is optimized. This paper uses a two-layer structure dynamic optimization control method based on the combination of genetic algorithm and big data algorithm. Part of it is applied to the acceleration prediction of belt conveyor system, and the other part is to control the speed of belt conveyor in real time to ensure that the actual speed of belt is consistent with the expected speed. In the comparison of energy-saving rates under different traffic volumes, relatively speaking, when the traffic volume is 3000t/h, the maximum energy-saving rate is 0.533, which is helpful for the stable operation of belt conveyor.