应用熵权-TOPSIS法的加热炉炉温在线设定模型

发布时间：2018-03-22 22:04

  本文选题：钢坯加热炉　切入点：板坯　出处：《哈尔滨工业大学学报》2017年07期 　论文类型：期刊论文

【摘要】：为解决加热炉中同时存在多块状态不同的板坯而导致加热策略不同的问题,针对每个板坯的实时情况,以单个炉区为研究对象,结合熵权法和TOPSIS法的中间过程,提出一种熵权-TOPSIS法.引入特殊钢种等级概念,对不同的钢种进行量化处理,并将其与板坯温差、当前位置和板坯厚度共同作为评价指标;结合熵权法对评价指标差异性的要求和TOPSIS法对样本方案的加权方法,把客观熵权作为TOPSIS法计算贴近度的权值,归一化后得到最终的板坯综合权重,利用此权重对控制段炉温进行最终设定.分别数值模拟了固定数值模型与熵权-TOPSIS模型,对比结果表明:与固定权值模型相比,使用本模型后,板坯平均温差下降了5.05℃,最大温差下降了7.77℃.炉温平均波动值减小了8.98℃.
[Abstract]:In order to solve the problem of different heating strategies caused by the existence of many different slabs in reheating furnace at the same time, aiming at the real-time situation of each slab, taking a single furnace area as an object of study, the intermediate process of entropy weight method and TOPSIS method is combined. An entropy weight TOPSIS method is proposed. The concept of special steel grade is introduced, and different steel grades are treated quantitatively, and the difference of slab temperature, current position and slab thickness are taken as evaluation indexes. Combined with the requirements of entropy weight method for evaluation index difference and the weight method of TOPSIS method for sample scheme, the objective entropy weight is taken as the weight value of TOPSIS method to calculate the closeness degree, and the final slab comprehensive weight is obtained after normalization. The fixed numerical model and entropy weight TOPSIS model are numerically simulated respectively. The results show that compared with the fixed weight model, the average temperature difference of slab decreases by 5.05 鈩，

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