转炉优化配料与冶炼静态控制模型

在分析转炉炉料结构优化及 BP 预报模型特点的基础上，针对某厂50 t 转炉生产条件，构建了由优化配料、静态预测、过程控制、脱氧合金化和成本计算等模块构成转炉冶炼静态控制系统。以机理模型为基础、采用增量模型校正的优化配料模块，用以精确计算入炉料结构；以 BP 神经网络为基础构建了静态预测模块，对转炉冶炼终点碳和温度进行预测；以操作经验为基础构建了过程控制模块，动态给出冶炼过程控制的枪位曲线、加料时机和加入量；基于终点预测和全氧计算模型构建了脱氧及合金化模块，进而对转炉冶炼成本进行计算，构建了成本计算模块。通过本系统的开发，建立了全过程指导的炉料结构优化与冶炼静态控制，为现场生产提供了指导。

Proportioning Optimization and Static Control Model for 50t Converter

Based on the analysis about the proportioning optimization and prodiction model applied with BP neural network,a static control system for converter has been established for 50t converter used in a plant,which comprised with some modules as the proportioning optimization,the static pridiction,process control,deoxidation and alloying, and cost calculation. The porportioning optimization module has been established on mechanical modle,and used to calculate the burden sturcture for converter. The static pridiction model has been set up on BP neural network to pridicting the endpoint carbon content in liquid steel and its temperature. The process control model has been con-structed with operating experiences to provide lance level curve,the charging time and the feeding quantities. The deoxidation and alloying model has been set up on endpoint pridiction and total oxygen content module to provide the quantities of deoxidant and alloys. The cost calculation model has been established on process control and static pridcition. The static control system could provide real-time and direct guidance for operater through the proportion optimization and static control model.