基于改进PCR方法的加热炉钢温预报模型
A Model for Billet Temperature Prediction of Heating-furnace Based on Improved PCR Method
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摘要: 运用多元统计投影原理,结合改进PCR方法,建立了钢坯出口温度变量和过程变量之间的主元回归预测模型,最后基于某钢厂实际生产数据对模型的参数进行了求取.校验和误差分析表明,该模型能提前5~25分钟预测出钢坯的出口温度,且预测误差满足工业应用的精度要求.Abstract: This paper establishes a pivot element predictive regression model between billet temperature variable and process variables with multi-statistic projection principle and PCR method, and parameters of the model are reckoned based on the actual data from a steel works. Check and error analysis indicate that this model can predict billet exit temperature 10~25 minutes in advance, and the predicting error can satisfy the demands of industrial application accuracy.