高炉冶炼过程中炉温是影响技术经济指标的关键参数,保持合理的炉温是高炉稳定顺行的关键因素。采用某炼铁厂在线采集的数据,通过核主元分析对建模数据进行预处理,根据相关系数选定模型参数,确定参数对炉温的滞后时间,基于支持向量机建立了高炉向凉、向热预测诊断模型。通过实例验证,该模型具有很高的精度。 Blast furnace smelting furnace temperature is the key technical and economic indicators of the key parameters to maintain a reasonable furnace temperature is the key to stable and smooth blast furnace. Using the data collected online by a ironworks, the modeling data were preprocessed by KPCA, the model parameters were selected according to the correlation coefficient to determine the lag time of the parameters on the furnace temperature. Based on the support vector machine, Predict the thermal model. Through the example verification, the model has high precision.