AUTHOR=Zhao Shuanfeng , Zhao Jiaojiao , Lu Zhengxiong , He Haitao , Zhang Chuanwei , Miao Yao , Xing Zhizhong 

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

JOURNAL=Frontiers in Energy Research

VOLUME=Volume 10 - 2022

YEAR=2022

URL=https://www.frontiersin.org/journals/energy-research/articles/10.3389/fenrg.2022.811648

DOI=10.3389/fenrg.2022.811648

ISSN=2296-598X

ABSTRACT=The cooperative control of shearer and scraper conveyor is a prerequisite for the realisation of intelligent comprehensive mining equipment and unmanned comprehensive mining workings. However, the harsh working face environment, the complex process of comprehensive mining and the many uncertainties make it difficult to establish a mathematical model for the cooperative control of coal 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 paper proposes a data-driven shearer-scraper conveyor cooperative control model based on rough set theory. This model first proposes the selection method of process monitoring parameters based on rough set theory, which removes redundant parameters and redundant parameter values, and establishes the decision rule base of cooperative speed regulation of shearer and scraper conveyor. Then, a shearer-scraper conveyor collaborative speed regulation decision algorithm based on attribute importance is 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 collaborative control model of data-driven shearer-scraper conveyor based on rough set theory overcomes the limitations of mathematical model, and can predict the running speed of shearer well, and realize the collaborative speed regulation of shearer-scraper conveyor.