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冶炼烟气制酸技术及控制研究进展 被引量:5

Research Progress on Technology and Control of Acid Production With Smelting Flue Gas
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摘要 有色金属冶炼产生的烟气对生态环境污染严重,冶炼烟气中二氧化硫浓度高、变化范围广,对其进行回收制酸是目前使用最为广泛的脱硫方法.因此,以冶炼烟气制酸为主要研究对象,对其工艺技术和控制过程进行分析.首先,简要回顾了国内外冶炼烟气制酸的发展历程;其次,对现有的烟气脱硫方法进行综述,重点分析了烟气制酸的工艺流程及其发展现状;最后,结合近年来烟气制酸系统建模、优化和控制研究现状,分析讨论了优化控制算法应用过程中的发展前景与难点. The flue gas produced by non-ferrous metal smelting seriously pollutes the ecological environment.Sulfur dioxide in the smelting flue gas has a high concentration and a wide range of variation.The recovery of sulfur dioxide to produce acid is currently the most widely used desulfurization method.Acid production with smelting fue gas was taken as the main research object,and its technology and control process were analyzed.First,the development history of acid production with smelting flue gas at home and abroad was briefly reviewed.Second,the existing flue gas desulfurization methods were reviewed,and the process of acid production with flue gas and its development status were mainly analyzed.Finally,combined with the research status of modeling,optimization,and control of the system of acid production with flue gas in recent years,the development prospects and diffculties in the process of optimal control algorithm application were analyzed and discussed.
作者 李晓理 刘明华 王康 刘志强 李桂海 LI Xiaoli;LIU Minghua;WANG Kang;LIU Zhiqiang;LI Guihai(Faculy of Information Technology,Bejjing University of Technology,Beijing 100124,China;Beijing Key Laboratory of Computational Ielligence and Inelligent System,Beijing 100124,China;Engineering Research Center of Digital Community,Ministry of Education,Beijing 100124,China;Guixi Smelter,Jiangxi Copper Co.,Ld.,Guixi 335499,Jiangxi,China;Bejjing RTlink Technology Co.,Ltd.,Beijing 100012,China)
出处 《北京工业大学学报》 CAS CSCD 北大核心 2023年第4期475-484,共10页 Journal of Beijing University of Technology
基金 国家自然科学基金资助项目(61873006) 北京市自然科学基金资助项目(4212040,4204087)。
关键词 烟气制酸 脱硫技术 有色金属冶炼 优化控制 控制算法 多模型自适应控制 acid production with flue gas desulfurization technology non-ferrous metal smelting .optimal control control algorithm multi-model adaptive control
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