【作者】 袁平； 毛志忠； 王福利；

【Author】 YUAN Ping MAO Zhi-zhong WANG Fu-li 2.School of Information Science & Engineering,Northeast University Shenyang 110004,China

【机构】 东北大学信息科学与工程学院；

【摘要】 LF精炼炉冶炼过程是一个复杂的物理化学反应过程及传热过程。基于增量预报模型的思想,本文提出采用案例推理方法进行LF炉炼钢的温度预报,该方法由于建立在已有的炼钢案例基础上,具有方法简单、不需要复杂的数学推理的优点,并具有较强的鲁棒性。考虑到LF炉炼钢影响因素较多、具有较强的非线性,采用支持向量机对案例推理的结果进行增量补偿修整。实验结果表明,此混合模型具有较好的预测结果,温度预测误差不大于±5℃的炉次大于85%。预报结果接近实际值,该方法是切实可行并有效的,可以用于LF炉钢水温度的预报。更多还原

【Abstract】 In the smelting process of Ladle Furnace,the steel temperature affects the LF’s operation and rhythm of steel-making process.Based on the idea of increasing model,a case based reasoning(CBR) based temperature prediction model is proposed in this paper.In order to minimize the severe nonlinear correlation among the input parameters,to improve the accuracy and robustness of the model,the result of CBR is corrected by fuzzy least square support vector machines(FLS-SVM).The temperature prediction model’s accuracy is perfectly improved and the simulation results demonstrate the efficiency of the method.And the number of heats of with the predictive errors of end temperature of molten steel in LF are all not over 5 degrees centigrade is greater than 85%.更多还原