转炉智能炼钢系统的研发
Research and Development of Converter Intelligence Steelmaking System
彭霞林 1向往 1谢森林 1王仕华 1樊智勇 1彭其春2
作者信息
- 1. 湖南华菱涟源钢铁有限公司,湖南娄底 417009
- 2. 武汉科技大学省部共建耐火材料与冶金国家重点实验室,湖北武汉 430081;武汉科技大学钢铁冶金及资源利用省部共建教育部重点实验室,湖北武汉 430081
- 折叠
摘要
单纯采用机理模型的计算精度难以满足转炉智能炼钢的要求,为此,基于机理和深度(BP神经元网络)/集成(XGBoost)学习,建立了转炉智能炼钢的融合模型,研发了转炉智能炼钢二级机过程控制系统.系统上线运行稳定可靠,各项技术指标预测精度满足实际生产要求,取得了良好效果.
Abstract
The calculation accuracy of solely using mechanism models cannot meet the requirements of intelligent steelmaking in converters.Therefore,based on mechanism and deep(BP neural network)/ensemble(XGBoost)learning,a fusion model of intelligent steelmaking in converters was established,and a process control system for intelligent steelmaking in converters was developed.The system runs stably and reliably online,and the prediction accuracy of various technical indicators meets the actual production requirements,achieving good results.
关键词
转炉/智能炼钢/机理模型/BP神经元网络Key words
converter/intelligent steelmaking/mechanism model/BP neural network引用本文复制引用
出版年
2024
NETL
NSTL
万方数据