Data-Driven Cooperative Control Model of Shearer-Scraper Conveyor Based on Rough Set Theory

The cooperative control of shearer and scraper conveyors is the prerequisite for the realization of intelligent comprehensive mining equipment and unmanned comprehensive mining workings. However, because of the harsh working face environment, the complex process of comprehensive mining, and the many uncertainties, it is difficult to establish a mathematical model for the cooperative control of shearer and scraper conveyors precisely through the operating mechanism. In the era of big data, the data-driven model has become a popular trend. Therefore, according to the actual production process data, this article proposed a data-driven cooperative control model of shearer–scraper conveyor based on rough set theory. First, the selection method of process monitoring parameters based on rough set theory was proposed to remove redundant parameters and redundant parameter values. Moreover, the decision rule base of cooperative speed regulation of shearer and scraper conveyor was established. Then a collaborative speed regulation decision algorithm based on attribute importance was designed. The algorithm matches the decision rules according to the real-time observation data and then determines the running speed of the shearer. The simulation results show that the proposed data-driven collaborative control model of shearer–scraper conveyor based on rough set theory overcomes the limitations of the mathematical model. It can predict the running speed of shearer well and realize the collaborative speed regulation of shearer–scraper conveyor.