Modeling and parameter optimization for the design of vibrating screens

• We simulate complex particles screening processes using Discrete Element Method.
• We test the validity of the simulations through an experimental prototype.
• Establish nonlinear regression model with Support Vector Machine (SVM).
• Optimize screening modeling parameters using Particle Swarm Optimization (PSO).

In this paper, we simulated the complex particle flow-behavior and screening efficiency on a linear vibrating screen using the Discrete Element Method (DEM). The simulations were validated with data from an adjustable experimental prototype screen. Then the novel application of non-linear regression modeling based on Support Vector Machines (SVMs) is used for mapping the sample space of operating parameters and vibrating screen configuration. Lastly, parameter optimization is implemented using Particle Swarm Optimization (PSO) algorithm. The primary findings proved that the SVM-based nonparametric model is not only feasible, but also highly adaptive to the parameter optimization that requires large-scale iterative computation. The non-parametric model established using the integration of DEM and SVM, combined with PSO algorithm in subsequent parameter optimization offered insights to the design and manufacture of vibrating screens.

Simplified three-dimensional model was used to simulate the screening process by the discrete element modeling software tool, EDEM.Figure optionsDownload as PowerPoint slide