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作 者:赵钰铎 吴思炜 曹光明[1] 王国栋[1] ZHAO Yuduo;WU Siwei;CAO Guangming;WANG Guodong(State Key Laboratory of Rolling and Automation,Northeastern University,Shenyang 110819,China)
机构地区:[1]东北大学轧制技术及连轧自动化国家重点实验室,辽宁沈阳110819
出 处:《冶金自动化》2023年第6期2-14,36,共14页Metallurgical Industry Automation
基 金:国家自然科学基金青年科学基金项目(52104370);东北大学博士后基金项目(20210203);轧制技术及连轧自动化国家重点实验室自主课题(ZZ2021005)。
摘 要:现代转炉炼钢流程中的铁水预处理脱硫工序可以提高去除杂质效率、减轻转炉吹炼负担、缩短冶炼时间,是冶炼品种钢和洁净钢的必要工序。铁水预处理过程发生复杂的高温物理化学反应,是一个黑箱过程,这导致冶炼过程的精准控制十分困难。建立精确的过程控制模型是实现铁水预处理过程精准控制的核心,对企业降低钢材生产成本,促进企业数字化、绿色化转型具有重要意义。本文综述了国内外研究者针对铁水预处理脱硫工序建立的机理模型、统计回归模型、专家系统和机器学习模型等各类模型的建模原理、特点与研究进展。基于模型的不同用途,分别围绕终点硫含量与脱硫率预测、工艺参数预测及优化和脱硫剂耗量与利用率预测,总结了铁水预处理脱硫模型的发展历程,并就其未来发展提出展望。The hot metal pretreatment desulfurization process in modern converter steelmaking process can improve the efficiency of impurity removal,reduce the burden of converter blowing,and shorten smelting time.It is a necessary process for smelting variety steel and clean steel.The pretreatment process of molten iron undergoes complex high-temperature physical and chemical reactions,which is a black box process,making precise control of the smelting process very difficult.Establishing an accurate process control model is the core of achieving precise control of the hot metal pretreatment process,which is of great significance for enterprises to reduce steel production costs,promote digital and green transformation.This paper summarizes the modeling principles,characteristic and research progress of various models,such as mechanism model,statistical regression model,expert system and machine learning model,established by domestic and foreign researchers for hot metal pretreatment desulfurization process.Based on the different uses of the model,the development process of application in practice and prospects of the hot metal pretreatment desulfurization model were proposed,focusing on the prediction of endpoint sulfur content and desulfurization rate,prediction and optimization of smelting process parameters,and prediction of desulfurization agent consumption and utilization rate.
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