平—摆复合振动筛分层机理研究

发布时间：2018-09-02 08:33

【摘要】：振动筛是工程中应用最广泛的筛分设备,主要是通过电机施加振动使物料经过筛网选别按物料粒度大小分成若干个等级。实践证明,筛分机理的突破是促进筛分设备创新与发展的决定因素。筛分过程主要分为被筛颗粒物的松散、分层、触筛和透筛四个细节过程。本文运用离散单元法对平动与摆动复合的新型振动筛分形式下颗粒群的筛分过程进行数值模拟的研究,分析了不同筛分参数对分层以及筛分效率的影响,主要内容有:1.建立了平-摆复合筛的三维模型,以EDEM软件为试验模拟平台模拟筛分过程,设计试验,研究分层机理。2.提出了全新的概念——分层沉降系数,定义了平动与摆动复合的新型振动筛分形式下颗粒群分层的特征量(沉降差);寻找颗粒群分层与筛分参数(振动参数、结构参数以及生产工艺参数)之间的关系,建立了以分层沉降系数为基础的沉降差与筛分参数之间的模型。3.筛分参数的优化:设置振动参数与结构参数的正交试验,考虑振动频率与摆动频率的交互作用,分析筛分参数影响分层的显著性,并且获得最佳分层的最优筛分参数组合。4.沉降差的预测:从筛分参数与沉降差的关系的角度,应用基于结构最小化准则的支持向量回归(Support Vector Regression,SVR)方法,建立SVR预测模型来研究预测沉降差问题。在选择适当的核函数和参数的基础上,对沉降差进行预测,能获得较小的误差,说明了支持向量回归能够较好地表示沉降差与筛分参数之间的非线性映射关系,用支持向量回归预测沉降差是合理的,它为预测沉降差提供了一种崭新的方法。5.在不同的筛分参数下,通过对比沉降差与筛分效率的关系,分析分层对筛分效率的影响,丰富分层理论。
[Abstract]:Vibrating screen is the most widely used screening equipment in engineering. The main reason is that the material can be divided into several grades according to the size of the material through the sieve screen selection by the vibration of the motor. Practice shows that the breakthrough of screening mechanism is the decisive factor to promote the innovation and development of screening equipment. The screening process is mainly divided into four detail processes: loose, stratified, contact and permeable particles. In this paper, the discrete element method is used to simulate the sieving process of the particle group in the new type of vibrating screen. The effects of different screening parameters on the stratification and screening efficiency are analyzed. The main contents are: 1: 1. The three-dimensional model of flat-pendulum composite sieve was established. The screening process was simulated with EDEM software, the experiment was designed and the delamination mechanism was studied. In this paper, a new concept, stratified settlement coefficient, is proposed, the characteristic quantity (settlement difference) of particle group stratification is defined under the new type of vibrating screen, and the parameters of particle group stratification and screening (vibration parameter, vibration parameter) are found. The relationship between structural parameters and production process parameters, the model of settlement difference and sieving parameters based on stratified settlement coefficient is established. Optimization of screening parameters: setting the orthogonal test of vibration parameters and structural parameters, considering the interaction between vibration frequency and oscillating frequency, analyzing the significance of sieving parameters affecting stratification, and obtaining the optimal sieving parameter combination. 4. Settlement difference prediction: from the point of view of the relationship between sieving parameters and settlement difference, using the support vector regression (Support Vector Regression,SVR) method based on structural minimization criterion, a SVR prediction model is established to study the problem of predicting settlement difference. On the basis of selecting proper kernel function and parameters, the settlement difference can be predicted and the smaller error can be obtained. It is shown that support vector regression can better represent the nonlinear mapping relationship between settlement difference and sieve parameters. It is reasonable to use support vector regression to predict settlement difference, which provides a new method for predicting settlement difference. Under different screening parameters, the influence of stratification on screening efficiency is analyzed by comparing the relationship between settlement difference and screening efficiency, and the theory of stratification is enriched.
【学位授予单位】：华侨大学
【学位级别】：硕士
【学位授予年份】：2016
【分类号】：TH237.6
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本文编号：2218824