Research On Ore Crushing Control System And Its Algorithms

Mineral processing technology plays a very important role in metallurgical industry.The ore taste obtained from mineral processing has a direct impact on the quality of the products produced in smelting,so it is extremely necessary to control the mineral processing process.The crushing process is the primary process flow in the mineral processing technology,which plays an important role in the quality and output of mineral processing products.The primary task to realize the automatic control of the crushing process is to adjust the ore feeding automatically amount to ensure the stability of the material level of the crusher cavity,so as to improve the crushing ability and the overall operation efficiency of the crusher,so that the crusher can always work in the best state.Reducing the production cost of mineral processing has important economic and practical value for mineral processing technology and even the whole metallurgical industry.However,the automatic feeding control in crushing system has the characteristics of large inertia,pure delay,time-varying and nonlinear,which makes it difficult to meet the control requirements by using conventional PID control.In this paper,an optimization method of crushing feed control based on improved particle swarm optimization(PSO)is proposed to optimize the parameters of fuzzy controller.The fuzzy control has the characteristics of good control and adaptability to nonlinear system and variable parameters.The better optimal control of the crushing feed control system is carried out.at the same time,considering that the control effect of the fuzzy adaptive PID controller is greatly affected by its initial value and related parameters,these parameters must be optimized to solve this problem.In this paper,the improved particle swarm optimization algorithm is used to optimize the parameters of the controller,and the optimal parameters are selected and applied to the fuzzy controller,so as to achieve more stable control of the crushing and feeding control system.Through the simulation results,it can be seen that the fuzzy controller optimized by the improved particle swarm optimization algorithm has a good control effect on the crushing feed control,which makes the crusher work in the best operation state and ensures the stability of the mineral processing crushing process.It improves the crushing efficiency,reduces the production cost,has high engineering application value,and has important economic and practical value for mineral processing technology and even the whole metallurgical industry.