冶金能源2024,Vol.43Issue(2) :30-35.

球团回转窑煤粉供入量预测

Prediction of coal demand of pellet rotary kilns

刘新民 路明 刘旭 刘书含 孙文强
冶金能源2024,Vol.43Issue(2) :30-35.

球团回转窑煤粉供入量预测

Prediction of coal demand of pellet rotary kilns

刘新民 1路明 2刘旭 2刘书含 1孙文强3
扫码查看

作者信息

  • 1. 东北大学冶金学院
  • 2. 鞍钢集团矿业有限公司大孤山球团厂
  • 3. 国家环境保护生态工业重点实验室;辽宁省流程工业节能与绿色低碳技术工程研究中心
  • 折叠

摘要

球团回转窑煤粉供入量的预测对回转窑精准控制和建设智能工厂都至关重要.然而,煤粉供入量与众多因素有关,只依据煤粉的历史数据建立模型进行预测,效果难以满足实际生产需求.因此,建立了基于XGBoost的煤粉消耗量预测模型,对影响煤粉消耗量的众多因素进行筛选,确定影响煤粉消耗量的关键影响因素.以某球团厂为应用案例,开展了煤粉供入量预测研究.煤粉消耗量预测结果的平均相对误差为7.22%,生产状态平稳时的预测平均相对误差为6.1%,生产波动较大时的预测平均相对误差为8.9%,预测结果精度较高.

Abstract

The prediction of pulverized coal supply in pelletizing rotary kilns is crucial for the precise control of rotary kilns and the construction of smart factories.However,it is difficult to achieve an ac-curate prediction of coal,which are influenced by various factors,just based on the historical data of coal consumption.Therefore,an XGBoost prediction model is established in this study.Many factors influencing the pulverized coal consumption are screened,and the key factors are determined.A pellet plant located in Liaoning Province,China,is used as a case study of the prediction of the supply of pulverized coal.The results show that the predicted values are in good agreement with the actual data.The mean absolute percentage error(MAPE)of the prediction of pulverized coal consumption is 7.22% for the whole investigated period,while the values of MAPE for smooth and unsmooth periods are 6.1% and 8.9% ,respectively.

关键词

回转窑/球团矿/XGBoost算法/煤粉

Key words

rotary kilns/pellets/XGBoost algorithm/pulverized coal

引用本文复制引用

基金项目

国家自然科学基金(52334008)

出版年

2024
冶金能源
中钢集团鞍山热能研究院有限公司

冶金能源

CSTPCD北大核心
影响因子:0.319
ISSN:1001-1617
参考文献量14
段落导航相关论文