Underground gangue filling technology in coal mines is one of the effective ways to realize green mining. In this paper, a process of underground raw coal primary selection is proposed, which is based on a mechanical sieve jig as the main washing equipment. It refers to the structure of the ground mechanical moving sieve jig. It optimizes and improves the main structure of the jig machine’s driving mechanism and gangue discharge mechanism. It meets the requirements of the technology and the narrow space environment in the underground mine and realizes the effective separation of coal and gangue. In the jigging process of a moving sieve, it is very important to keep the jig bed stable and precisely control the quantity of gangue discharge for improving the system separation accuracy and efficiency. In this paper, a control method based on a fuzzy logic combination is proposed to realize the fuzzy logic control of the motor speed of gangue discharging, which aims at the nonlinear, time-varying uncertainty and pure lag characteristics of the control system of the underground moving sieve jig. Further industrial experiments were carried out and we obtained the variation law of the gangue’s quality in the moving sieve and the output curve of the gangue motor frequency under three working conditions. The experimental results show that the fuzzy logic control algorithm can quickly stabilize the jig bed in the vibrating sieve when the quantity of gangue changes abruptly or fluctuates greatly. It improves the separation efficiency of coal and gangue and effectively solves the problems of nonlinearity, time-varying and hysteresis in the control process of the moving sieve jig.
Genetic-based reinforcement learning for fuzzy logic control systems
