【作者】 黄涌波；

【导师】 周孑民； 瞿向东；

【作者基本信息】 中南大学 ， 热能工程， 2008， 博士

【摘要】 铝冶金是有色金属工业的重要组成部分。铝及铝加工材作为有色金属基础材料,被广泛应用于建筑、电力、交通、机械、国防等众多领域。近年来,我国铝冶金工业得到了迅速的发展,目前已成为世界主要的铝生产国。然而,铝冶金工业一直以来都是能耗大户。在铝冶金工业的所有流程中,电解工序占整个铝生产用能的80%～89%。因此,采取各种措施降低铝电解的能耗是铝冶金工业节能的关键,也是制约我国铝冶金工业健康发展的主要因素。铝电解生产节能的有效途径是在维持电解槽热平衡稳定的条件下降低电解温度。降低电解温度的最佳方法之一是选择合适的添加剂,形成初晶温度较低的电解质体系。在所有的添加剂中,氟化铝所占比例最大,因此对电解质成分和电解温度的影响十分显著。本论文通过对铝电解槽热平衡特性与氟化铝添加量之间耦合关系的分析,寻求并应用适当的氟化铝添加量控制策略,在维持铝电解槽热平衡稳定的条件下,通过降低电解温度实现铝电解生产过程节能的目的。本论文完成的研究主要工作和创新点如下:(1)在大量查阅中外文献的基础上,综述了铝电解槽热平衡分析的各种方法,评述了用于铝电解槽内传热分析的物理模型和数值模型。从铝电解槽内物料和能量平衡的角度出发,首次研究了过剩氟化铝含量与电解温度之间的特征联系,运用传热学规律建立了铝电解槽内耦合物料和能量平衡的理论模型,并通过适当的简化显式地给出了实用表达式,最后通过现场试验验证了该模型的正确性。(2)采用多项式回归分析方法,以铝电解槽实测参数为依据,以氟化铝添加量为因变量,以电解温度为自变量,提出了基于回归分析的氟化铝添加量控制模型,利用该模型可根据前一天电解温度预测当天的氟化铝添加量。现场试验表明,该氟化铝添加量控制策略对于稳定电解温度有利,有助于提高电流效率和节约电能。(3)首次运用遗传算法对氟化铝添加量进行控制,以日均槽电压和氟化铝添加量作为遗传操作变量,以过热度最小作为氟化铝添加量控制目标,以过热度的倒数作为适应度函数,得到不同槽电压下对应的氟化铝添加量最佳值。建模过程中,引入了最优保存策略,使适应度最好的个体尽可能地保留到下一代种群中。试验结果表明,该氟化铝添加量控制方法较之目前工业常规使用的方法具有明显的优势,可以使过热度大大降低。(4)首次将支持向量机引入到氟化铝添加量控制问题的研究,建立了以电解温度、初晶温度、槽电压作为输入,以氟化铝添加量作为输出,分别以多项式函数和径向基函数为核函数的支持向量机模型。试验结果表明,经过训练后的支持向量机能够较好地预测氟化铝添加量,核函数的不同对支持向量机性能的影响不大。(5)以某大型铝业公司电解铝厂160kA系列铝电解槽为对象,采用Delphi语言开发了氟化铝添加量控制决策系统,将基于回归分析、遗传算法、支持向量机的氟化铝添加量控制策略嵌入到现场上位机中,以实现实时地根据槽况动态调节氟化铝添加量。现场试验结果表明,所提出的氟化铝添加量控制策略及开发的相应软件系统有效可行,实用性强,节能效果显著。更多还原

【Abstract】 The reduction of aluminium is an important part of the nonferrous metallurgy industry. As the basis material of nonferrous metals, the aluminium and its processed materials have been widely used in building, electricity, transportation, machinery, national defence and other fields. In recent years, the Al-metallurgical industry of China has obtained rapid development and China is being the world’s leading aluminium producer. However, the Al-metallurgical industry is always a kind of industry which consumes a large amount of energy. In all processes of Al-metallurgical industry, the electrolysis occupies 80% - 89% of the total energy consumption. As a result, taking various measures to reduce the energy consumption in aluminium electrolysis is the key to energy saving in the Al-metallurgical industry and is also the main factor which constrains the healthy development of China’s Al-metallurgical industry.An effective way to reduce the energy consumption in the aluminium electrolysis process is to lower the electrolysis temperature under the premise of maintaining the heat balance in the aluminium reduction cell. One of the best methods for reducing the electrolysis temperature is to choose suitable additives to form an electrolyte system whose liquidus temperature is low. In all additives adopted now, the aluminium fluoride occupies the largest proportion. Therefore, the aluminium fluoride can influence the electrolyte composition and electrolysis temperature significantly. In this paper, through the analysis on the coupling relationship between the heat balance characteristics of the aluminum reduction cell and the amount of aluminium fluoride addition, the author tries to seek and apply the control strategy which is concerned the appropriate amount of aluminium fluoride addition, and also tries to lower the electrolysis temperature under the condition of maintaining the heat balance in the aluminium reduction cell to achieve the goal of reducing the energy consumption in the aluminium electrolysis process. The main contributions of this dissertation are summarized as follows:(1) On the basis of extensive searching and reading domestic and foreign literatures, various methods about how to analyse the heat balance in the aluminium reduction cell was summarized, and the physical models and numerical models which were used in the aluminium reduction cell’s heat transfer analysis were reviewed. Based on the balance of the mass and energy in the aluminium reduction cell, the characteristics relationship between the amount of the excess aluminum fluoride and the electrolysis temperature was explored. The coupled mass and energy balance model in the aluminium reduction cell was established through the law of heat transfer, and a practical expression was given explicitly by appropriate simplifications. Finally, the validity of the model was verified by the on-site tests.(2) A control model for aluminum fluoride addition was put forward based on the regression analysis, which adopts the aluminum fluoride addition as the dependent variable and adopts the electrolysis temperature as the independent variable. Through this model, the amount of the present-day aluminum fluoride addition can be forecasted according to the yesterday’s electrolysis temperature. The field tests show that this control strategy for the aluminum fluoride addition is beneficial to stabilize the electrolysis temperature, and it is helpful to enhance the current efficiency and to reduce the electrical energy consumption.(3) The genetic algorithm was applied to control the amount of the aluminum fluoride addition with the daily average cell voltage and the amount of aluminum fluoride added as genetic operation variables. The control target is to minimize the superheat degree of the aluminum electrolyte with the reciprocal of the superheat degree as the sufficiency function. The best value of aluminum fluoride added was gained under different cell voltages. In the modeling process, the elitist strategy was introduced to retain the best individuals to the next generation of the population as much as possible. The field test results show that this control method about the amount of the aluminium fluoride added is better than the conventional method which was used in the industry and it can reduce the degree of overheat markedly.(4) The support vector machine was introduced into the investigation on the control problem of the aluminum fluoride addition. A support vector machine model was established using the electrolysis temperature, the liquidus temperature, the cell voltage as inputs and the aluminium fluoride addition as output. The polynomial function and the radial basis function were adopted as the kernel function respectively. The results showed that the trained support vector machine can predict the optimal amount of the amount of aluminum fluoride added, and the difference in the kernel function has little impact on the performance of the support vector machine.(5) Based on 160kA aluminium reduction cells in a large aluminum company, a decision-making program for the aluminium fluoride addition was developed using the Delphi language. The aluminium fluoride addition control strategies based on regression analysis, genetic algorithm, support vector machine were embedded in the program to adjust the aluminium fluoride addition according to the real-time cell state. Field test results show that the three proposed aluminum fluoride addition control strategies and the corresponding software system are feasible, practical and effective in energy saving.更多还原