铁矿粉烧结过程建模与仿真研究现状

刘代飞,曹海鹏,史先菊,李军

钢铁研究学报 ›› 2018, Vol. 30 ›› Issue (8) : 585-597.

钢铁研究学报 ›› 2018, Vol. 30 ›› Issue (8) : 585-597. DOI: 10. 13228/j.boyuan.issn1001- 0963. 20180145
综合论述

铁矿粉烧结过程建模与仿真研究现状

  • 刘代飞1,曹海鹏1,史先菊2,李军2
作者信息 +

Research status on modeling and simulation of iron ore sintering process

  • LIU Dai- fei1,CAO Hai- peng1,SHI Xian- ju2,LI Jun2
Author information +
文章历史 +

摘要

铁矿烧结是高炉炼铁生产的重要环节,开展烧结过程建模、仿真与优化对提升烧结自动化水平,实现智能制造具有重要意义。阐述了铁矿粉烧结生产自动化建模与仿真的发展状况,从信息建模和智慧优化层面归纳总结了过程机理与特征信息的表征、数据驱动的融合和数值模拟的场态分析3类模型。结合烧结流程自动化,分析比较了系列方法的优势与局限,并指出了建模和仿真模型的应用发展趋势。面向国家2025智能制造战略需求,开展烧结过程建模与仿真的生产实践,积极推进烧结领域的智能制造。

Abstract

Iron ore sintering is a part of blast furnace ironmaking production. In order to upgrade the sintering automation and intelligent manufacturing, it is necessary to carry out sintering process modeling and simulation optimization. The research status of sintering process modeling and simulation was discussed. And three kinds of model, namely process mechanism and feature information characterization model, data- driven fusion model and field state analysis numerical simulation model, were summarized from the aspects of information modeling and intelligent optimization. The advantages and disadvantages of a series of model construction methods were analyzed by combining with automation requirement of sintering process, and the simulation models application trends were proposed. According to the requirement of sintering intelligent manufacturing that included in the “Made in China 2025” plan, the production practices of sintering process modeling and simulation optimization are crucial.

关键词

铁矿烧结 / 过程建模 / 流程仿真 / 信息优化

Key words

iron ore sintering / process modeling / process simulation / information optimization

引用本文

导出引用
刘代飞,曹海鹏,史先菊,李军. 铁矿粉烧结过程建模与仿真研究现状[J]. 钢铁研究学报, 2018, 30(8): 585-597 https://doi.org/10. 13228/j.boyuan.issn1001- 0963. 20180145
LIU Dai- fei,CAO Hai- peng,SHI Xian- ju,LI Jun. Research status on modeling and simulation of iron ore sintering process[J]. Journal of Iron and Steel Research, 2018, 30(8): 585-597 https://doi.org/10. 13228/j.boyuan.issn1001- 0963. 20180145

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