|
|
Innovation practice and future prospects of blast furnace ironmaking technology |
XIAO Peng |
CISDI Group Co.,Ltd., Chongqing 401122, China |
|
|
Abstract The steel industry has entered the road of green and intelligent development. Based on years of metallurgical technology and engineering practice,CISDI has achieved a series of achievement in the field of high-efficiency and long-life blast furnaces,and has developed a number of low-consumption and low-carbon smelting technologies to help the green development of the ironmaking industry. At the same time,CISDI regards intelligence as an important commanding height for future ironmaking technology development. Based on the metallurgical engineering process theory,CISDI builds the world′s first integrated intelligent management and control platform for ironmaking areas. In the future,CISDI will further use big data,artificial intelligence,digital twin and mathematical model to build a new generation of intelligent blast furnace,and vigorously develop hydrogen metallurgy and other low-carbon iron making technologies,and move towards the new goal of green ironmaking.
|
Received: 27 October 2020
|
|
|
|
[1] 项钟庸,姜曦. 用评价高炉生产效率的新方法研讨大型高炉生产状况[J]. 钢铁,2018,53(8):38.(XIANG Zhong-yong,JIANG Xi. Analysis of production indexes of large BF by new evaluation method for production efficiency[J].Iron and Steel,2018,53(8):38.) [2] 项钟庸,王筱留,邹忠平,等. 炉缸面积利用系数和燃料比的研究[J]. 世界金属导报,2016-11-22(B02).(XIANG Zhong-yong,WANG Xiao-liu,ZOU Zhong-ping,et al. Research on hearth area utilization coefficient and fuel ratio[J]. World Metals,2016-11-22(B02).) [3] 项钟庸,王筱留,银汉. 再论高炉生产效率的评价方法[J]. 钢铁,2013,48(3):86.(XIANG Zhong-yong,WANG Xiao-liu,YIN Han. More discussion on evaluation method for productive efficiency of ironmaking blast furnace[J]. Iron and Steel,2013,48(3):86.) [4] 项钟庸,王筱留,刘云彩,等. 落实高炉低碳炼铁生产方针的探讨[C]//第十届中国钢铁年会暨第六届宝钢学术年会论文集. 上海:中国金属学会,2015:507.(XIANG Zhong-yong,WANG Xiao-liu,LIU Yun-cai,et al. Study on implementation of blast furnace low-carbon production principle[C]//The 10th China Steel Annual Conference and The 6th Baosteel Annual Conference Conference. Shanghai:The Chinese Society for Metals,2015:507.) [5] 项钟庸. 全面研讨高炉低碳炼铁[C]//第九届中国钢铁年会. 北京:中国金属学会,2013:5.(XIANG Zhong-yong. Comprehensive study of low carbon on blast furnace ironmaking[C]//The 9th China Steel Annual Conference. Beijing:The Chinese Society for Metals,2013:5.) [6] 焦克新,张建良,刘征建,等. 关于高炉炉缸长寿的关键问题解析[J]. 钢铁,2020,55(8):193.(JIAO Ke-xin,ZHANG Jian-liang,LIU Zheng-jian,et al. Analysis of key issues concerning the longevity of blast furnace hearth[J]. Iron and Steel,2020,55(8):193.) [7] 金永龙,何志军,王川. 不同炉料结构高炉实现低碳排放的解析[J]. 钢铁,2019,54(7):8.(JIN Yong-long,HE Zhi-jun,WANG Chuan. Analysis of low carbon emission of blast furnace with different charge structure[J]. Iron and Steel,2019,54(7):8.) [8] 王劲松. 高炉智能化生产管理系统的开发与应用[J]. 钢铁技术,2014(2):2.(WANG Jin-song. Development and application of intelligent production management system for blast furnace[J]. Iron and Steel Technology,2014(2):2.) [9] 王刚,李爱锋,刘风军,等. 高炉炉缸长寿智能管理系统的开发与应用[J]. 中国冶金,2016,26(4):43.(WANG Gang,LI Ai-feng,LIU Feng-jun,et al. Development and application of intelligent management system for longevity of furnace and hearth[J]. China Metallurgy,2016,26(4):43.) [10] 孙小东. 高炉生产数据分析平台的开发[J]. 工业加热,2017,46(5):60.(SUN Xiao-dong. Development of data analysis platform for blast furnace production[J]. Industrial Heating,2017,46(5):60.) [11] 夏绪鹏. 智慧铁水运输系统研究与应用[J]. 冶金自动化,2019,43(5):6.(XIA Xu-peng. Research and application of smart hot metal transportation system[J]. Metallurgical Industry Automation,2019,43(5):6.) [12] 朱仁良. 未来炼铁技术发展方向探讨以及宝钢探索实践[J]. 钢铁,2020,55(8):2.(ZHU Ren-liang. Discussion on future development direction of ironmaking technology and exploratory practice of baosteel[J]. Iron and Steel,2020,55(8):2.) [13] XIE X,WANG G,SUN J,et al. Application of big data in optimization of blast furnace operation[C]//AISTech 2019. Pittsburgh:AIST-Association for Iron and Steel Technology,2019:587. [14] WANG Gao-peng. A hybrid algorithm based on PBIL algorithm and zooming algorithm and its convergence proof[C]//2013 China Intelligent Automation Conference. Yangzhou:Chinese Association of Automation,2013:11. |
[1] |
YANG Jian, WU Si-wei. Property prediction of steel rolling process based on machine learning[J]. Iron and Steel, 2021, 56(9): 1-9. |
[2] |
LI Hong-yang, LIU Xiao-jie, LI Xin, BU Xiang-ping, LI Hong-wei, LÜ Qing. Application of industrial Internet platform for blast furnace iron making[J]. Iron and Steel, 2021, 56(9): 10-18. |
[3] |
LI Jiang-yun, YANG Zhi-fang, ZHENG Jun-feng, ZHAO Yi-kai. Applications of iron and steel industry with deep learning technologies[J]. Iron and Steel, 2021, 56(9): 43-49. |
[4] |
WANG Jian-quan, LI Wei, MA Zhang-chao, SUN Lei, ZHANG Chao-yi. 5G industrial Internet empowers smart steel[J]. Iron and Steel, 2021, 56(9): 56-61. |
[5] |
YIN Rui-yu. Topic of times of metallurgy—Get through process,communicate different levels and open up a new theory[J]. Iron and Steel, 2021, 56(8): 4-9. |
[6] |
SHANGGUAN Fang-qin, YIN Rui-yu, LI Yu, ZHOU Ji-cheng, LI Xiu-ping. Dissussion on strategic significance of developing full scrap EAF process in China[J]. Iron and Steel, 2021, 56(8): 86-92. |
|
|
|
|