基于数据挖掘的热轧带钢质量分析方法
Quality analysis method for hot strip based on data mining
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摘要: 带钢热连轧是一个多阶段的生产过程,在工序繁多的加工过程中与产品质量直接相关的控制参数和目标参数近百个.如何找到控制参数和目标参数之间存在的信息加以利用,提高热轧带钢产品质量一直是科研人员和工程技术人员努力的目标.研究表明,利用数据挖掘方法结合热连轧生产的工业特点,提取潜在的、有用的、最终可理解的工艺知识,得到质量缺陷与控制状态的对应关联关系,通过控制变量权值向量和数据挖掘高危关联状态集合综合分析,可以迅速对带钢质量问题的产生原因进行定位,找出关键控制变量做出调整,减少经济损失,提高生产效率,为热轧带钢产品质量问题分析提供科学、准确的思路.Abstract: The hot rolling of strip is a multi-stage production process. There are about a hundred of control parameters and target parameters which are related to the quality of products directly in the multi-channel processes. It is the main development orientation for both the literal research and engineering practice to improve the quality of hot rolling products,by finding the information between the control parameters and target parameters,and making use of the information. It is investigated that combining data mining with the industrial features of hot rolling productions,the potentially,useful,ultimately understandable process knowledge can be extracted.The correspondence relationship between quality defects and control state can be got. Through a comprehensive analysis of control parameters weight vector and the set of high-risk relationships,the key control parameters can be find to improve. This method can reduce the economic losses,improve the production efficiency,and provide the scientific and accurate idea for the quality analysis of hot rolling strip production.