钢水“脱氧合金化”配料方案的优化

脱氧合金化是钢铁冶炼中的重要工艺环节,如何优化脱氧合金化配料方案,最大限度地降低合金钢的生产成本,已成为各大钢铁企业提升竞争力的关键。首先,本文通过采集的低合金钢种前期冶炼历史真实数据,选择恰当的方法,计算出C,Mn两种元素的历史合金收得率,接着建立BP神经网络预测模型,实现对C、Mn两种元素收得率的预测。接着根据不同合金的投入量和价格建立非线性方程模型。以总成本、收得率、投入合金质量的上限和下限作为非线性方程的限制条件。然后,选取不同的合金进行实验和比较,计算得出最优的合金配料方案。优化后,每一包钢水生产成本比平均成本节约239.18万元。

Deoxidizing alloying is an important process in iron and steel smelting.How to optimize the mixing scheme of deoxidizing alloying and reduce the production cost of alloy steel to the maximum extent has become the key to improve the competitiveness of major iron and steel enterprises.First of all,this paper calculated the historical alloy yield of C and Mn through the collected real historical data of early smelting of low alloy steel,and selected appropriate methods.Then BP neural network prediction model was established to realize the prediction of the yield of C and Mn.Then the nonlinear equation model is established according to the input quantity and price of different alloys.The total cost,yield,upper and lower limits of input alloy mass are used as the limiting conditions of nonlinear equation.Then,different alloys are selected for experiment and comparison,and the optimal alloy batching scheme is calculated.After optimization,the production cost of each pack of molten steel is 2,391,800 yuan less than the average cost.