摘要
钢铁企业生产过程的信息流蕴藏着丰富的生产工艺规律。BP人工神经网络广泛用于信息流分析中,将其概括为四个方面:过程状态参数预测、产品性能参数预测、能耗信息预测和原材料参数优化。分别介绍相关研究和应用工作,指出应用流程中存在的不足,并给出规范流程。最后给出某大型钢铁企业新区焦炉单元的日能耗预测实例,验证了BP人工神经网络在钢铁生产过程信息流分析中的作用和应用流程的有效性。
The information flow in the steel production process has many rich laws in production process laws.BP artificial neural network has greatly applied in the information flow analysis including four aspects:the prediction of process status parameters;the prediction of product performance parameters;the prediction of energy consuming;the prediction of material parameters.This thesis introduces related research and application work,points out the disadvantages in application process and proposes regulated process.Finally the paper gives an example of daily energy consumption of new coke oven unit in a large steel company,the result has test the effectiveness in the information flow analysis of BP ANN in the steel production process.
出处
《节能》
2012年第1期50-55,3,共6页
Energy Conservation
基金
安徽省钢铁产业技术创新规划研究项目(项目编号:09020203014)
关键词
钢铁生产过程
信息流分析
BP人工神经网络
应用流程
steel production process
information flow analysis
BP artificial neural network
application process
