Screening Research Of Flip-flow Screen And Design Optimization Of Rebound Baffle

Flip-flow screen,as a new equipment developed in recent years of deep dry screening,has good performances in the classification of moist fine coal.However,in the current screening research of flip-flow screen,the research on the movement behavior of granular material over the flexible screen surface and the complicated screening process is not thorough and detailed.The influence of design parameters(e.g.rotating speed,inclined angle,expansion amount)on the screening effect remains unclear.Part of material have a long bounce distance along the horizontal direction of the screen surface,whose penetration are insufficient.Aiming to solve above problems,the screen surface-granular material coupling model was established by using the coupling method of MBD and DEM to numerically simulate the movement behavior of the granular material over the screen surface.The screening mechanism was explained by using the velocity vector distribution diagram method.The relationship between design parameters and the screening effect was studied.Combining BP neural network model and GA genetic algorithm globally optimized the design parameter,furthermore,rebound baffles were designed and installed on the flip-flow screen to improve the screening performance,the main contents are as follows:(1)The rigid-flexible coupling model of the screen surface-screen machine was built,and the kinematics characteristics of the flexible surface were analyzed,which was compared with the model of elastic compression bar.On the basis of that,the flexible screen surface was approximated to establish,screen surfacegranular material coupling model screening was built with consideration of the actual working conditions.(2)Based on the screen surface-granular material coupling model,the stress analysis of the granular material materials on the flexible screen is carried out;the complete screening performance on the flip-flow screen is explained by combining the velocity vector distribution diagram method;orthogonal experiments were carried out on the design parameters.The influence rule of design parameters on the screening performance was discussed,and the primary and secondary sequence of factors affecting the screening effect were determined.(3)The BP neural network is used to map the relationship between design parameters and screening effect.This non-linear mapping model was used as the fitness function,and the genetic algorithm without expression was used to perform global optimization of parameters,and the optimal design parameter combination was obtained.(4)After the experiment verified the beating distribution of the material,the rebound baffle was designed according to the distribution of the granular material on the flip-flow screen,and the relationship between the installation height of the rebound baffle and the screening effect of the granular material was discussed.The results show that the screening efficiency was greatly increased,while,the screening ability is almost unaffected.