SU Buxin
School of Metallurgical and Ecological Engineering， University of Science and Technology， Beijing 100083， ChinaZHANG Jianliang
School of Metallurgical and Ecological Engineering， University of Science and Technology， Beijing 100083， ChinaGUO Hongwei
School of Metallurgical and Ecological Engineering， University of Science and Technology， Beijing 100083， ChinaCAO Weichao
School of Metallurgical and Ecological Engineering， University of Science and Technology， Beijing 100083， ChinaFU Yuandi
School of Metallurgical and Ecological Engineering， University of Science and Technology， Beijing 100083， ChinaBAI Yanan
School of Metallurgical and Ecological Engineering， University of Science and Technology， Beijing 100083， ChinaA mathematical model of coal blending optimization for blast furnace injection is proposed. Because Chinese current blast furnaces blend pulverized coal by simple mix and traditional lab blending optimization needs plenty of work for the larger number of characteristics of pulverized coal. The new model is based on the principal component analysis indexes P1, P2 and P3 combined with the proximate analysis and elementary analysis of pulverized coal. P1, P2 and P3 are obtained from principal component analysis of the injection characteristic of pulverized coal determined by lab experiment. This model is proved to be effective on both lab experiment coal blending and actual production of BF.
苏步新,张建良,国宏伟,曹维超,傅源荻,白亚楠.基于主成分分析的高炉喷吹煤优化配煤模型[J].重庆大学学报,2013,36(11):51~57
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