针对传统轧制力模型在现场应用中预报精度不高的现状,利用轧制过程中的仪表反馈数据开发出一种新的轧制力自学习模型.对计算所得轧制力自学习系数按照钢种、道次出口厚度、开轧温度、目标厚度、目标宽度等要素进行了层别的划分,并对其依据和效果分别做了系统的分析.现场在线应用结果表明,给出的轧制力模型具有良好的预测精度,末道次轧制力预测误差可以控制在3%以内,其它道次可以控制在5%以内.
The forecasting precision of conventional rolling force model in practice is not high,so a new rolling force learning model based on feedback data from the instrument in rolling process is developed.It is very necessary to study the method for division of learning coefficient layers according to the steel type,exit thickness,starting temperature,target thickness and width.Also,the gist and the effectiveness for the method are analysed.The resultof on-line application indicates that rolling force model has good precision of prediction with an error less than 3% in last pass and 5% in other passes.
参考文献
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