回转筒颗粒系统DEM参数的模糊自整定方法研究

发布时间：2018-03-30 17:42

本文选题：回转筒　切入点：颗粒混合　出处：《湖南大学》2015年硕士论文

【摘要】：回转窑、糖衣机等回转筒类过程装备广泛应用于冶金、化工、制药、食品等重要领域,在我国国民经济建设中发挥着重要的作用。回转筒内颗粒的混合过程关系到产品的最终质量以及生产效率。近年来随着高性能计算技术的不断发展,离散单元法(DEM)成为研究回转筒式过程设备中颗粒系统的一种强有力的新手段。但是,DEM计算结果对输入参数的取值较为敏感。颗粒-颗粒摩擦系数、颗粒-转筒摩擦参数等重要模型参数,在实际中难以进行测量。目前,DEM模型中的摩擦系数一般是根据经验并通过手工不断调整,直到仿真结果与实验结果一致。参数调整过程费时费力,且具有较强主观性。本文针对上述问题,以回转筒颗粒系统为对象,提出了一种DEM摩擦系数模糊自整定方法,基于Lab VIEW平台研发了相应软件,实现DEM仿真中摩擦系数的自动选取,选题具有较高的理论和实用价值。论文完成的主要工作和取得的成果有:(1)搭建回转筒颗粒系统平台进行多组颗粒物料混合实验,并建立了回转筒颗粒混合过程的DEM模型。并基于PFC3D软件对回转筒内颗粒混合过程进行DEM模拟,分析了摩擦系数对仿真结果的影响。(2)分析了回转筒内颗粒休止角的变化规律,定义了颗粒上偏角和下偏角两个特征休止角,研究了特征休止角与摩擦系数的关系。(3)在以上基础上,提出了基于模糊推理的DEM摩擦系数自整定方法。设计了DEM摩擦系数模糊推理机,将颗粒系统实际与仿真的特征休止角偏差作为输入,通过模糊推理计算出颗粒-颗粒摩擦系数与颗粒-筒壁摩擦系数。采用Lab VIEW和MATALAB混合编程方法开发了一套DEM摩擦系数模糊自整定的软件,可实现仿真与实验的交互、摩擦系数自动整定过程可视化等功能。(4)利用本文所研发的DEM摩擦系数模糊自整定软件进行9组测试实验,结果发现整定5-10次即可收敛,验证了本系统的正确性和快速性。利用自动整定获取得的摩擦系数进行回转筒颗粒系统DEM仿真,仿真结果与实验结果吻合良好,表明本文所提出的DEM摩擦系数模糊自整定方法的有效性和正确性。
[Abstract]:Rotary kilns, sugar-coated machines and other rotary drum process equipment are widely used in metallurgical, chemical, pharmaceutical, food and other important fields, It plays an important role in the national economic construction of our country. The mixing process of particles in the rotary drum is related to the final quality of the product and the production efficiency. In recent years, with the development of high performance computing technology, Discrete element method (DEM) has become a powerful new method to study particle system in rotary cylinder process equipment, but Dem results are more sensitive to the input parameters, the particle-particle friction coefficient, the particle-particle friction coefficient, the particle-particle friction coefficient, the particle-particle friction coefficient, the particle-particle friction coefficient, the particle-particle friction coefficient, It is difficult to measure some important model parameters such as particle-cylinder friction parameters in practice. At present, the friction coefficient of Dem model is generally adjusted according to experience and by manual adjustment. Until the simulation results are consistent with the experimental results, the parameter adjustment process is time-consuming and laborious, and has a strong subjectivity. In this paper, a fuzzy self-tuning method of DEM friction coefficient is proposed to solve the above problems. Based on Lab VIEW platform, the corresponding software is developed to realize the automatic selection of friction coefficient in DEM simulation. It has high theoretical and practical value. The main work and achievements of this paper are as follows: build a rotary particle system platform to carry out multi-group particle material mixing experiments. The DEM model of the particle mixing process in the rotary cylinder is established, and the DEM simulation of the particle mixing process in the rotary cylinder is carried out based on PFC3D software. The influence of friction coefficient on the simulation results is analyzed. (2) the variation law of the angle of repose of the particles in the rotary cylinder is analyzed. The two characteristic angles of repose are defined, and the relationship between the characteristic angle of repose and the friction coefficient is studied. A self-tuning method of DEM friction coefficient based on fuzzy reasoning is proposed. The fuzzy inference machine of DEM friction coefficient is designed. The deviation of characteristic angle of repose between the actual particle system and the simulation is taken as input. The friction coefficient of particle to particle and particle to cylinder wall are calculated by fuzzy inference. A set of fuzzy self-tuning software of DEM friction coefficient is developed by using Lab VIEW and MATALAB mixed programming method, which can realize the interaction between simulation and experiment. The DEM fuzzy self-tuning software developed in this paper is used to test nine groups of tests. The results show that the tuning can converge 5-10 times. The correctness and rapidity of the system are verified. The DEM simulation of rotary drum particle system is carried out by using the friction coefficient obtained by automatic tuning. The simulation results are in good agreement with the experimental results. The validity and correctness of the fuzzy self-tuning method of DEM friction coefficient presented in this paper are shown.
【学位授予单位】：湖南大学
【学位级别】：硕士
【学位授予年份】：2015
【分类号】：TQ051.7

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