基于K-means聚类算法的电弧炉强化用氧的优化研究  

Study of optimizing oxygen injection in EAF process based on K-means clustering

作　　者：王振宙[1] 朱荣[1] 蒋金燕[2] 牛重生 胡俊邦[3] 

机构地区：[1]北京科技大学冶金与生态工程学院,北京100083 [2]国家知识产权局专利审查协作中心,北京100083 [3]安阳钢铁股份有限公司

出　　处：《北京科技大学学报》2007年第S1期146-149,共4页Journal of University of Science and Technology Beijing

摘　　要：主要采用数据挖掘技术中的聚类分析算法对电弧炉炼钢的历史数据进行分析、加工处理,得出不同热装铁水比、炼钢成本、氧耗情况下的炉次分类,再利用K-means聚类法得到聚类结果,并对结果进行分析.通过分析比对,在结果的不同分类中选出最优的用氧和用电曲线.The history data produced by steel-making were analyzed and then were processed to classify them according to the differences of hot metal, cost, oxygen consumption and yield. It provides practical infor-mation for the operator. For different sorts, several groups of oxygen injection and active power curves were found representing the corresponding sort and its optimization oxygen injection and active power curve were obtained after processing the curves together.

关 键 词：电弧炉 集束氧枪 聚类 

分 类 号：TF341.2[冶金工程—冶金机械及自动化]