Quality analysis method for hot strip based on data mining
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摘要: 帶鋼熱連軋是一個多階段的生產過程,在工序繁多的加工過程中與產品質量直接相關的控制參數和目標參數近百個.如何找到控制參數和目標參數之間存在的信息加以利用,提高熱軋帶鋼產品質量一直是科研人員和工程技術人員努力的目標.研究表明,利用數據挖掘方法結合熱連軋生產的工業特點,提取潛在的、有用的、最終可理解的工藝知識,得到質量缺陷與控制狀態的對應關聯關系,通過控制變量權值向量和數據挖掘高危關聯狀態集合綜合分析,可以迅速對帶鋼質量問題的產生原因進行定位,找出關鍵控制變量做出調整,減少經濟損失,提高生產效率,為熱軋帶鋼產品質量問題分析提供科學、準確的思路.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.
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Key words:
- data mining /
- factor analysis /
- fault logic analysis /
- association analysis /
- quality analysis
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