高炉炉况判断神经网络专家系统  

Neural Network Expert System of Forecasting Blast Furnace Operational Conditions

作　　者：卢虎生[1] 高斌[2] 赵利国[3] 国宏伟[3] 杨天钧[3] 

机构地区：[1]北京科技大学信息工程学院,北京100083 [2]包头钢铁学院,包头014010 [3]北京科技大学冶金学院,北京100083

出　　处：《北京科技大学学报》2002年第3期276-279,共4页Journal of University of Science and Technology Beijing

基　　金：国家重点科技项目(No.97-562-02-02)

摘　　要：在深入分析高炉冶炼特点的基础上，提出泛化特性和自适应特性是高炉炉况判断系 统稳定有效运行的２个重要特性．设计了增进系统泛化特性和自适应特性的方案，并相应开发 出一套炉况判断专家系统．开发的系统在高炉上运行获得了满意效果．Based on deeply-analyzing the characteristics of iron-making process, it is presented that gen-eralization and self-adaptation of the BF judgement systems are two important factors for maintaining the sta-bility and efficiency of neural network expert system. The strategy for improving these two features has been proposed and a new developed system has been proved to be satisfactory in the on-site blast furnace operation.

关 键 词：高炉 炉况判断 神经网络 专家系统 泛化性 自适应性 系统构成 

分 类 号：TF57[冶金工程—钢铁冶金] TP182[自动化与计算机技术—控制理论与控制工程]