针铁矿法沉铁过程铁离子浓度预测模型研究及系统开发
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摘要
沉铁是湿法炼锌的关键工序,通过向含杂质铁的硫酸锌溶液中加入中和剂(锌焙砂)和氧气,使溶液中的铁离子以针铁矿的形式沉淀到渣中,从而达到除铁的目的。实际生产中,沉铁过程出口铁离子浓度采用人工化验方式获得,存在很大的滞后,给沉铁过程的实时控制带来了极大的困难。为此,研究针铁矿法沉铁过程出口铁离子浓度与各工艺参数之间的关系,实时预测出口铁离子浓度,对实现针铁矿法沉铁过程的优化控制,保证出口铁离子浓度满足后续生产工序要求具有十分重要的意义。
本文在分析湿法炼锌沉铁过程工艺机理的基础上,确定了影响出口铁离子浓度的主要因素；深入分析了沉铁过程亚铁氧化和铁水解反应原理,建立了基于反应动力学、气液相平衡和物料平衡的沉铁过程出口铁离子浓度预测模型。为确定预测模型中的未知参数,提出了一种引入粒子群平均位置信息和位置更新约束因子的非线性动态惯性权重粒子群优化算法(NIWPSO),实现了对机理模型未知参数的优化估计。最后,利用实际生产数据验证了铁离子浓度预测模型的精度和可靠性,仿真结果表明模型可用于工业实际生产,为沉铁过程的优化控制提供了可用信息。
在此基础上,采用基于Visual C++的模块化程序设计方法,开发了针铁矿法沉铁过程铁离子浓度预测系统,详细介绍了系统软件的设计。本系统实现了沉铁过程工艺参数的实时监测、出口铁离子浓度的在线预报及报表打印等功能,为下一步优化控制针铁矿法沉铁过程中锌焙砂和氧气的添加量奠定了基础。
The iron removal is a key process of hydrometallurgy, in which zinc calcine and oxygen are added to zinc sulfate solution to remove the impurities of iron, and to turn the iron ion in solution into goethite precipitation,so the purpose of iron removal can be achieved. In actual production, the iron ion concentration of iron removal process is obtained by manual testing, bringing large time delay and making the real-time control of iron removal process extremely difficult. Therefore, it is necessary and significant to study the relations between iron ion concentration output in the goethite iron removal process and the various process parameters, to achieve the real-time forecast of iron ion concentration output and the optimal control of the goethite iron removal process, so that the iron ion concentration meets the requirements of the follow-up production.
Based on the analysis of hydrometallurgy iron removal mechanism, the factors affecting the iron ion concentration are determined.The reaction principle of ferrous iron oxidation and iron hydrolysis are deeply analyzed. Therefore, the iron ion concentration prediction model based on the kinetic equation, gas-liquid phase equilibrium and material balance is established. Aiming at the unknown parameters existing in the prediction model. A nonlinear dynamic inertia weight strategy particle swarm optimization algorithm (NIWPSO) with particle swarm average location and location update constraint factor is proposed to estimate the unknown parameters of the mechanism model. Finally, the accuracy and reliability of the prediction model of iron ion concentration are evaluated by using the actual production data. The simulation results show that the model can be used for industrial production, which provides valuable information for the optimal control of the iron removal process.
With the use of modular programming method based on Visual C++,the prediction system of iron ion concentration in goethite iron removal process is developed, and a detailed description of the system software design is presented. The system can achieve the following functions:the real-time monitor of process parameters in iron removal process, the prediction of iron ion concentration, and report printing and so on. What's more, the system also lays the foundation for optimal contron of the addictional amount of zinc calcine and oxygen in iron removal process in the next step.
本文在分析湿法炼锌沉铁过程工艺机理的基础上,确定了影响出口铁离子浓度的主要因素；深入分析了沉铁过程亚铁氧化和铁水解反应原理,建立了基于反应动力学、气液相平衡和物料平衡的沉铁过程出口铁离子浓度预测模型。为确定预测模型中的未知参数,提出了一种引入粒子群平均位置信息和位置更新约束因子的非线性动态惯性权重粒子群优化算法(NIWPSO),实现了对机理模型未知参数的优化估计。最后,利用实际生产数据验证了铁离子浓度预测模型的精度和可靠性,仿真结果表明模型可用于工业实际生产,为沉铁过程的优化控制提供了可用信息。
在此基础上,采用基于Visual C++的模块化程序设计方法,开发了针铁矿法沉铁过程铁离子浓度预测系统,详细介绍了系统软件的设计。本系统实现了沉铁过程工艺参数的实时监测、出口铁离子浓度的在线预报及报表打印等功能,为下一步优化控制针铁矿法沉铁过程中锌焙砂和氧气的添加量奠定了基础。
The iron removal is a key process of hydrometallurgy, in which zinc calcine and oxygen are added to zinc sulfate solution to remove the impurities of iron, and to turn the iron ion in solution into goethite precipitation,so the purpose of iron removal can be achieved. In actual production, the iron ion concentration of iron removal process is obtained by manual testing, bringing large time delay and making the real-time control of iron removal process extremely difficult. Therefore, it is necessary and significant to study the relations between iron ion concentration output in the goethite iron removal process and the various process parameters, to achieve the real-time forecast of iron ion concentration output and the optimal control of the goethite iron removal process, so that the iron ion concentration meets the requirements of the follow-up production.
Based on the analysis of hydrometallurgy iron removal mechanism, the factors affecting the iron ion concentration are determined.The reaction principle of ferrous iron oxidation and iron hydrolysis are deeply analyzed. Therefore, the iron ion concentration prediction model based on the kinetic equation, gas-liquid phase equilibrium and material balance is established. Aiming at the unknown parameters existing in the prediction model. A nonlinear dynamic inertia weight strategy particle swarm optimization algorithm (NIWPSO) with particle swarm average location and location update constraint factor is proposed to estimate the unknown parameters of the mechanism model. Finally, the accuracy and reliability of the prediction model of iron ion concentration are evaluated by using the actual production data. The simulation results show that the model can be used for industrial production, which provides valuable information for the optimal control of the iron removal process.
With the use of modular programming method based on Visual C++,the prediction system of iron ion concentration in goethite iron removal process is developed, and a detailed description of the system software design is presented. The system can achieve the following functions:the real-time monitor of process parameters in iron removal process, the prediction of iron ion concentration, and report printing and so on. What's more, the system also lays the foundation for optimal contron of the addictional amount of zinc calcine and oxygen in iron removal process in the next step.
引文
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[5]何蔼平,魏昶,刘中华,等.针铁矿法从镍电解混合阳极液中除铁研究.昆明理工大学学报,1996,21(6)：140-147
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[7]Claassen J O, Sandenbergh R F. Influence of temperature and pH on the quality of metastable iron phases produced in zinc-rich solutions. Hydrometallurgy, 2007(86):178-190
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[9]李仕雄.硫酸锌溶液中针铁矿法沉铁的氧化过程.中国有色冶金,1982(2)：40-43
[10]陈耐生,赵经贵,张滨秋.对针铁矿法除铁过程中亚铁离子氧化速度的研究.黑龙江大学自然科学学报,1984(3)：76-80
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[15]马莹,何静,马荣骏.三价铁离子在酸性水溶液中的行为.湖南有色金属,2005,21(1)：36-39
[16]于秀芳.Fe(Ⅲ)的水解聚合作用的热动力学研究.青岛化工学院学报,1999,20(2)：151-154
[17]王景杨,苑明哲,曹景兴,等.基于最小二乘参数辨识的非线性机理模型研究.沈阳理工大学学报,2008,27(3)：48-51
[18]吕志军,杨建国,项前,等.基于支持向量机的纺纱质量预测模型研究.控制与决策,2007,22(6)：693-696
[19]王凌云,桂卫华,刘梅花,等.基于改进在线支持向量回归的离子浓度预测模型.控制与决策,2009,24(4)：537-541
[20]朱红求,阳春华,桂卫华.一种净化过程钴离子浓度的混合智能预测方法.计算机科学,2009,36(7)：234-236
[21]孔玲爽,阳春华,王雅琳.一种基于灰色模型和机理模型集成的质量预测模型及其应用.湖南文理学院学报(自然科学版),2007,19(2)：68-70
[22]Elhaq S L, Giri F, Unbehauen H. Modeling identification and control of sugar evaporation theoretical design and experimental evaluation. Control Engineering Practice,1999,7:931-942
[23]Patan K, Parisini T. Identification of neural dynamic models for fault detection and isolation:the case of a real sugar evaporation proeess. Journal of Proeess Control,2005,15(1):67-79
[24]祝和云,王仁发,龙虹波.乳剂制备中银离子浓度过程建模及控制.化工自动化及仪表,1993(6)：21-26
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