摘要
铁水脱硫预处理是炼钢中的关键技术之一。在分析炼钢铁水预处理工艺流程基础上,研究了影响脱硫效果的各种因素,消化、剖析了目前比较通用的铁水脱硫预处理各类控制模型。对于铁水预处理粉剂模型,设计了BP人工神经元网络数学模型,并给出了在系统中的应用方案,使脱硫效果提高8%,符合现场实际生产需求,避免了过吹引起粉剂的浪费。
The pretreatment of hot metal desulphurization technology is the key process of steelmaking.Based on analysis of the technology,all factors that influence the efficiency of hot metal desulphurization are studied and most popular models for hot metal desulphurization are reviewed in this paper.A mathematic model of powder consumption optimization for hot metal pretreatment has been developed with BP artificel neuro-network technique.The applicatiom of this model can meet the requirements of steelmaking production with good results.As a result,the efficiency of desulphurization increased by 8 % and no powder superfluous has happened.
出处
《钢铁研究》
CAS
2011年第3期16-18,共3页
Research on Iron and Steel
关键词
炼钢
铁水预处理
神经网络
数学模型
steelmaking
hot metal pretreatment
neural network
mathematic model
