摘要
运用基于数据挖掘的决策树分类算法,分析加热炉的大量生产数据,从中获取有价值的规则,形成规则知识库。最后从规则知识库中获取加热炉最优炉温设定值的方法。该方法可实现加热炉最优炉温设定值曲线的寻优及设定,可对应于不同的钢坯种类,提供控制系统优化控制指导,改善钢坯在加热炉内的燃烧过程,提高加热质量,降低加热炉能耗。
Based on data mining decision tree classification algorithm,this paper analyzes a large number of furnace production data to derive valuable rules from the rule knowledge database,from which the optimal temperature setting of reheating furnace is obtained.This method can be used to achieve optimization and setting of the curve of optimal heating temperature corresponding to different types of steel billet,provide optimal control of the guidance for the control system,improve the combustion process of billet and heating quality in the furnace,and reduce heating energy consumption.
出处
《武汉工程职业技术学院学报》
2014年第4期71-74,共4页
Journal of Wuhan Engineering Institute
关键词
加热炉
炉温设定值
数据挖掘
决策树
规则存储模型
节能减排
reheating furnace
temperature setting
data tapping
decision tree
rule storage model
energy saving
