由于中厚板轧制过程传统道次修正方法稳定性较差,提出了基于灰色关联度的道次修正算法.通过灰色关联度模型计算出最近生产的n块钢板所有道次以及当前正在轧制钢板前m道次与当前轧制道次轧制力自学习系数的关联度,根据关联度的高低来确定当前道次和后续道次的自学习系数,并通过道次修正对后续辊缝进行二次调整,以获取精确的目标出口厚度.实际应用结果表明,产品目标出口厚度的命中率提高了2.5%～3.0%,具有很高的现场应用价值.
As the stability of traditional pass correction method is relatively poor in plate rolling process, pass correction based on gray relational grade is put forward. Relational grade of rolling force self-learning coefficient which is obtained from all passes of recently produced n pieces and m passes before current pass of slab in stand is calculated by gray relational grade model, and force self-learning coefficient of current and succeeding passes is determined by all those relational grade, then succeeding gaps start to adjusting by pass correction so as to obtain accurate target thickness. Actual application shows that hit rate of target thickness of product increases by 2. 5% - 3. 0%, so it has high utility value.
参考文献
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