| 铁水预处理粉剂用量优化的神经网络模型 |
| |
| 引用本文： | 杨志勇,任小佳.铁水预处理粉剂用量优化的神经网络模型[J].钢铁研究,2011,39(3):16-18. |
| |
| 作者姓名： | 杨志勇 任小佳 |
| |
| 作者单位： | 宝钢设备检修有限公司,机械技术服务事业部,上海,201900 |
| |
| 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.
|
| 关 键 词： | 炼钢 铁水预处理 神经网络 数学模型 |
Mathematic model of neural network with powder consumption optimization for hot metal pretreatment |
| |
| YANG Zhi-yong,REN Xiao-jia.Mathematic model of neural network with powder consumption optimization for hot metal pretreatment[J].Research on Iron and Steel,2011,39(3):16-18. |
| |
| Authors: | YANG Zhi-yong REN Xiao-jia |
| |
| Affiliation: | 1(Shanghai Baosteel Equipment Maintenance Co.Ltd.,Shanghai 201900,China) |
| |
| Abstract: | 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. |
| |
| Keywords: | steelmaking hot metal pretreatment neural network mathematic model |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
|
