基于BP神经网络和遗传算法的智能配煤系统开发与应用
Development and application of intelligent coal blending system based on BP neural network and genetic algorithm
徐凌霄 1张保忠 1何有林 1朱春梅 1郑超 2田永胜2
作者信息
- 1. 宁波钢铁有限公司,浙江 宁波 315807
- 2. 湖北省煤转化与新型炭材料重点实验室,武汉科技大学化学与化工学院,湖北 武汉 430081
- 折叠
摘要
针对炼焦煤品种繁多,同一矿点来煤的煤质波动较大,混煤现象严重的问题,宁波钢铁有限公司通过搭建煤焦数据库,开发智能配煤系统,实现全流程监测煤焦数据变化.智能配煤系统结合历史生产数据分析提取影响焦炭质量的关键指标,采用多元线性回归和BP神经网络的建模方法,建立焦炭质量关键指标预测模型.同时,智能配煤系统结合焦炭质量预测模型、配煤专家系统和炼焦单种煤库存信息,采用优化后的遗传算法进行配煤模型的构建,从而实现快速实时调整配比、合理利用炼焦煤资源、稳定焦炭质量并且有效降低炼焦成本的目的.智能配煤系统运行稳定,实现了对炼焦煤资源的合理利用和降本增效的目的.
Abstract
In view of the problems of many varieties of coking coal,high fluctuation of coal quality from the same mine,and phenomenon of serious coal mixing,Ningbo Iron and Steel Co.,Ltd.realized the whole-process monitoring of the change of coal coke data by building a coal coke database and developing an intelligent coal blending system.Combined with the historical production data,the intelligent coal blending system analyzed and extracted the key indicators affecting the quality of coke.And by adopting the modeling method of multiple linear regression and BP neural network,a prediction model of key indicators of coke quality was established.Meanwhile,this intelligent system combined with the coke quality prediction model,coal blending expert knowledge and single coking coal inventory information,and adopted optimized genetic algorithm to build the coal blending model,thus achieving the purpose of rapid real-time adjustment in coal proportions,rational use of coking coal resources,stable coke quality,and effective reduction of coking cost.The stable operation of this intelligent coal blending system enabled the rational and efficient utilization of coking coal resources and the purpose of reducing cost and increasing efficiency.
关键词
BP神经网络/遗传算法/焦炭质量预测模型/智能配煤系统/煤焦数据库Key words
BP neural network/genetic algorithm/coke quality prediction model/intelligent coal blending system/coal coke database引用本文复制引用
基金项目
湖北省高等学校实验室研究项目(HBSY2023-030)
出版年
2024
NETL
NSTL
万方数据