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铁前炉料制备过程先进控制与智能优化 被引量:7

Advanced Control and Intelligent Optimization of Raw-materials Preparation Process in Ironmaking
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摘要 铁前炉料制备过程主要包括炼焦过程和烧结过程,分别生产焦炭和烧结矿,为高炉炼铁提供燃料和原料.实现铁前炉料制备过程的先进控制与智能优化,有利于提高产品的质量和产量、降低生产能耗和成本.本文阐述了炼焦过程和烧结过程先进控制与智能优化的研究进展,包括炼焦配煤过程智能优化与控制、焦炉火道温度集成软测量、焦炉加热燃烧过程智能控制、炼焦生产全流程优化及烧结配料过程建模与优化、烧结热状态参数控制、烧结生产全流程优化与控制、烧结碳效建模与优化.最后总结分析了铁前炉料制备过程控制与优化的发展趋势. The preparation of raw materials in ironmaking involves coking and sintering processes,which produce coke and sinter,respectively. Coke and sinter serve as fuel and raw materials for blast-furnace ironmaking.Advanced control and intelligent optimization of the raw-materials preparation process will help to improve product quality and quantity,and reduce production energy consumption and costs. In this paper,we describe the research progress of the advanced control and intelligent optimization of the coking and sintering processes,including the intelligent optimization and control of the coal-blending process,the integrated softsensing of the coke-oven flue temperature, the intelligent control of the coke-oven heating combustion process,and the optimization of the entire coke production. In addition,we describe the modeling and optimization of the sinter production proportioning process,sintering thermal-state control,the optimization and control of the entire sintering process,and the modeling and optimization of the sintering carbon efficiency.Lastly,we summarize and analyze the development trends in the control and optimization of the raw-materials preparation process in ironmaking.
作者 胡杰 杜胜 吴敏 陈鑫 曹卫华 HU Jie;DU Sheng;WU Min;CHEN Xin;CAO Weihua(School of Automation,China University of Geosciences,Wuhan 430074,China;Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems,Wuhan 430074,China)
出处 《信息与控制》 CSCD 北大核心 2018年第4期411-420,共10页 Information and Control
基金 国家自然科学基金重点国际(地区)合作研究项目(61210011) 湖北省自然科学基金创新群体项目(2015CFA010) 高等学校学科创新引智计划资助项目(B17040)
关键词 钢铁冶金 炼焦过程 烧结过程 混合建模 智能优化 先进控制 iron and steel metallurgy coking process sintering process hybrid modeling intelligent optimization advanced control
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