烧结矿低温还原粉化率的影响因素及预测模型  

Influencing factors and prediction model of low temperature reduction disintegration index of sinter

作　　者：郑兆颖 邢相栋[1] 王荪璇 周小辉 ZHENG Zhaoying;XING Xiangdong;WANG Sunxuan;ZHOU Xiaohui(School of Metallurgical Engineering,Xi'an University of Architecture and Technology,Xi'an 710055,Shaanxi,China;Shaanxi Institute for Food and Drug Control,Xi'an 710016,Shaanxi,China;Laiwu Branch of Shandong Iron and Steel Co.,Ltd.,Jinan 250000,Shandong,China)

机构地区：[1]西安建筑科技大学冶金工程学院,陕西西安710055 [2]陕西省食品药品监督检验研究院,陕西西安710016 [3]山东钢铁股份有限公司莱芜分公司,山东济南250000

出　　处：《烧结球团》2023年第2期25-32,共8页Sintering and Pelletizing

基　　金：国家自然科学基金资助项目(52174325);陕西省重点研发计划资助项目(2019TSLGY05-09)。

摘　　要：针对烧结矿低温还原粉化率传统检测方法时间滞后、过程繁杂、耗时较长等问题,本文以某钢铁厂400 m^(2)烧结机烧结矿的性能指标为研究对象,选用60组训练集进行因子分析,建立以Al_(2)O_(3)、SiO_(2)、MgO、TiO_(2)、FeO质量分数以及R、w(MgO)/w(Al_(2)O_(3))和w(CaO)/w(TFe)为自变量,低温还原粉化率为因变量的烧结矿低温还原粉化率预测模型。结果表明:影响烧结矿低温还原粉化率的主要因素是w(Al_(2)O_(3))、w(SiO_(2))、w(FeO)、R和w(MgO)/w(Al_(2)O_(3));优化后预测模型为YRDI=1.137w(FeO)+5.56w(SiO_(2))+26.44R-20.19w(MgO)/w(Al_(2)O_(3))-6.07w(Al_(2)O_(3));模型的R^(2)为99.90%,具有较高的精确度,能够快速预测烧结矿的低温还原粉化率,并能在生产中改善烧结矿质量。本文建立的预测模型可为现场烧结生产提供理论指导和技术支持。Aiming at such problems as time lag,complicated process and high time consumption of traditional detection methods for low-temperature reduction disintegration index of sinter,the performance index of sinter of 400 m^(2)sintering machine of a steel plant is taken as the research object,the 60 training sets are selected for factor analysis,and a prediction model of low-temperature reduction disintegration index of sinter is established with Al_(2)O_(3),SiO_(2),MgO,TiO_(2),FeO mass fractions,R,w(MgO)/w(Al_(2)O_(3))and w(CaO)/w(TFe)as independent variables and low-temperature reduction disintegration index as dependent variables.The results show that the main factors affecting the low-temperature reduction disintegration index of sinter are w(Al_(2)O_(3)),w(SiO_(2)),w(FeO),R and w(MgO)/w(Al_(2)O_(3)).The optimized prediction model is YRDi=1.137w(Fe0)+5.56w(Si0,)+26.44R-20.19w(Mg0)/w(Al_(2)O_(3))-6.07w(Al_(2)O_(3)).The R^(2)of the model is 99.90%,and the model has high accuracy,which can quickly predict the low-temperature reduction disintegration index of sinter,and improve the quality of sinter in production.The prediction model can provide theoretical guidance and technical support for on-site sintering production.

关 键 词：烧结矿 低温还原粉化率 影响因数 主成分分析法 回归模型 预测模型 

分 类 号：TF046.4[冶金工程—冶金物理化学] TP202.2[自动化与计算机技术—检测技术与自动化装置]