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钢包精炼炉元素收得率的影响因素分析及预报
引用本文:徐喆,毛志忠. 钢包精炼炉元素收得率的影响因素分析及预报[J]. 钢铁, 2012, 47(3): 34-37
作者姓名:徐喆  毛志忠
作者单位:1. 东北大学信息科学与工程学院, 辽宁 沈阳 110819 2. 流程工业综合自动化国家重点实验室东北大学, 辽宁 沈阳 110819
基金项目:国家高新技术研究发展计划资助项目
摘    要: 不能及时获得收得率影响因素的检测数据是钢包精炼炉元素收得率预报的难点之一。为了解决该问题,首先通过机制分析,在可测变量中选取并创建可以间接表达收得率影响因素的变量,然后将这些变量作为模型的输入,使用支持向量机方法建立元素收得率预报模型。在试验中,将本方法与已有方法进行了比较,比较结果表明本方法所建模型有较高的预报精确度与命中率,更适合于在生产中使用。

关 键 词:钢包精炼炉  元素收得率  支持向量回归  影响因素  预报  
收稿时间:2011-06-13

Analysis and Prediction of Influencing Factor on Element Recovery in Ladle Furnace
XU Zhe,MAO Zhi-zhong. Analysis and Prediction of Influencing Factor on Element Recovery in Ladle Furnace[J]. Iron & Steel, 2012, 47(3): 34-37
Authors:XU Zhe  MAO Zhi-zhong
Affiliation:1. School of Information Science and Engineering, Northeastern University, Shenyang 110819, Liaoning, China 2. State Key Laboratory of Integrated Automation for Process Industries Northeastern University, Shenyang 110819, Liaoning, China
Abstract:The influencing factors of element recovery could not be obtained instantly,which was one of the difficulties of recovery prediction in ladle furnace(LF).In order to solve this problem,through mechanism analysis,some measurable variables were selected and some new variables that can express the factors of element recovery indirectly were created by using measurable variables.Then,the selected and created variables were used as inputs of element recovery prediction model that was established using support vector regression(SVR).In the experiment,the proposed method was compared with existing recovery prediction methods.The results show that the proposed method has higher accuracy and hit rate,and is more suitable in production.
Keywords:ladle furnace  element recovery  support vector regression  influencing factor  prediction
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