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Modeling and parameter optimization for the design of vibrating screens

机译:振动筛设计的建模和参数优化

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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. (C) 2015 Elsevier Ltd. All rights reserved.
机译:在本文中,我们使用离散元方法(DEM)在线性振动筛上模拟了复杂的颗粒流动特性和筛分效率。使用可调实验原型屏幕中的数据验证了仿真。然后,基于支持向量机(SVM)的非线性回归建模的新应用被用于绘制操作参数和振动筛配置的样本空间。最后,使用粒子群优化(PSO)算法实现参数优化。主要研究结果证明,基于SVM的非参数模型不仅可行,而且具有可行性。而且还高度适应需要大规模迭代计算的参数优化。利用DEM和SVM的集成建立的非参数模型,结合PSO算法在随后的参数优化中,为振动筛的设计和制造提供了见识。 (C)2015 Elsevier Ltd.保留所有权利。

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