Parameter Optimization And Mechanism Research Of Double-layer Variable Screen Surface Vibrating Screen

In the vibrating screening operation,each area of the screen surface has a different screening environment,and the material layer thickness,target particle proportion and other parameters of each area are different,which limits the screening efficiency of the traditional uniform screen vibrating screen.In order to give full play to the performance of the vibrating screen,this paper proposes a double-layer variable screen surface screening method,which uses different screen surface parameters of each screen area to deal with different screening environments,so as to give full play to the screening performance of the vibrating screen.In this paper,the screening efficiency is used as the evaluation index to study and optimize the screening parameters of the double-layer variable screen surface vibrating screen.Taking the elements of the screening process as the medium linking the screening parameters and the screening efficiency,the screening mechanism of the double-layer variable screen surface vibrating screen was explored.Its main research contents are as follows:(1)Based on the probability theory,the probability of the material passing through the screen surface of the double-layer vibrating screen was analyzed,and the difference in the probability of particles passing through the screen surface of the single-layer and double-layer vibrating screen was compared.The principle of the discrete element method is briefly described,and the discrete element model of the double-layer variable screen surface vibrating screen is established accordingly.The feeding method of granules and the evaluation index of screening performance were determined.(2)Aiming at the limitations of the traditional vibrating screen design,the necessity of zonal optimization of screen surface parameters is explained;the overall parameters of the screen surface are designed,and the aspect ratio of the screen surface and the form of the screen surface partition are obtained;The parameters are optimized,and the preliminary optimization results of the screen surface parameters of the new double-layer variable screen surface vibrating screen and the distribution law of screen surface parameters are obtained;the screening performance is compared with other commonly used vibrating screens to verify its superiority.(3)The discrete element simulation is used to establish the relationship between the screening efficiency,the elements of the screening process and the screening parameters of the double-layer variable screen surface vibrating screen.The particle velocity and material layer thickness are selected as the factors of the screening process,and the screening mechanism of the double-layer variable screen surface vibrating screen is explored with the elements of the screening rules as the link.(4)Using particle swarm optimization(PSO)to optimize the external parameters and kernel parameters of the support vector regression machine(SVR),a PSO-SVR model with better fitting effect was established.Mapping relationship of sieving efficiency.The PSO-SVR model is optimized by particle swarm algorithm again,and the optimal sieving efficiency and the corresponding sieving parameter combination are obtained.The discrete element method is used to simulate the sieving situation under the condition of optimal sieving parameter combination for many times,and the result of particle swarm optimization is verified.(5)Design and manufacture a double-layer variable screen surface vibrating screen experimental prototype with adjustable parameters,and use binocular measurement technology to make the physical test environment and simulation setting parameters closer.Comparative experiments were carried out on the experimental platform to verify the regularity of the vibrating screening efficiency with the amplitude and vibration frequency and the superiority of the optimal screening parameters,and to prove the reliability of the discrete element simulation and parameter optimization methods.