智能配煤技术在炼焦配煤中的应用进展  

Application progress of intelligent coal blending technology in coking coal blending process

作　　者：何有林 张保忠[1] 徐凌霄[1] 朱春梅[1] 王世杰[2] 田永胜[2] He Youlin;Zhang Baozhong;Xu Lingxiao;Zhu Chunmei;Wang Shijie;Tian Yongsheng(Ningbo Iron and Steel Co.,Ltd.,Ningbo Zhejiang 315807,China;Wuhan University of Science and Technology,Wuhan Hubei 430081,China)

机构地区：[1]宁波钢铁有限公司,浙江宁波315807 [2]武汉科技大学,湖北武汉430081

出　　处：《煤化工》2024年第5期80-84,共5页Coal Chemical Industry

基　　金：湖北省高等学校实验室研究项目(HBSY2023-030)。

摘　　要：综述了传统经验配煤、煤岩学理论配煤以及人工智能配煤三种炼焦配煤技术,分析了计算机辅助配煤算法在炼焦配煤中的应用。在此基础上,提出了炼焦配煤技术后续的发展趋势。在通过大数据训练配煤模型的同时,还需要综合考虑炼焦煤性质、炼焦工艺等对焦炭质量的影响。基于以上内容,结合钢铁生产实际,可以建立焦炭质量与配合煤性质之间的关系,提出了关联数据分析、煤质指标、降本增效等指标的整体思路。Three coking coal blending technologies were reviewed:traditional experience-based blending,coal petrology theory-based blending and artificial intelligence-driven blending.The application of computer-aided blending algorithms in coking coal blending process was analyzed.Based on this analysis,the future development trends for coal blending technologies were proposed.While training the coal blending model through big data,it was essential to comprehensively consider the impacts of coal property and coking process on the coke quality.Based on this content and combined with the actual steel production,a relationship between coke quality and blended coal property could be established.And the overall approach of related data analysis,coal quality indicator,cost reduction and efficiency improvement indicator had been proposed.

关 键 词：传统经验配煤 煤岩学理论配煤 人工智能配煤 焦炭质量预测 智能炼焦 

分 类 号：TQ53[化学工程—煤化学工程]