Modeling and parameter optimization for the design of vibrating screens |
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| Affiliation: | 1. University of California-Davis, Davis, CA, USA;2. University of California-San Diego, La Jolla, CA, USA;3. Rice University, Houston, TX, USA;1. School of Chemical Engineering and Technology, China University of Mining and Technology, Xuzhou 221116, China;2. School of Mechatronic Engineering, China University of Mining and Technology, Xuzhou 221116, China |
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| Abstract: | 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. |
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| Keywords: | Support Vector Machines PSO algorithm Discrete Element Method Modeling Screening efficiency |
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