Coupling efect and characterization modeling of iron ore fnes mixing and granulating at 0–1 mm
Dai?fei Liu1, Xian?ju Shi2, Chao?jun Tang1, Hai?peng Cao1, Jun Li2
1 School of Energy and Power Engineering, Changsha University of Science and Technology, Changsha 410114, Hunan, China 2 Ironmaking Section, Wuhan Branch of Baosteel Central Research Institute (R & D Center of Wuhan Iron & Steel Co., Ltd.), Wuhan 430000, Hubei, China
Coupling efect and characterization modeling of iron ore fnes mixing and granulating at 0–1 mm
Dai?fei Liu1, Xian?ju Shi2, Chao?jun Tang1, Hai?peng Cao1, Jun Li2
1 School of Energy and Power Engineering, Changsha University of Science and Technology, Changsha 410114, Hunan, China 2 Ironmaking Section, Wuhan Branch of Baosteel Central Research Institute (R & D Center of Wuhan Iron & Steel Co., Ltd.), Wuhan 430000, Hubei, China
摘要 Characteristic of iron ore is the essential factor of granulating. Three ores, namely specularite, magnetite concentrate and limonite, were selected as adhesion powder to investigate granulating behavior and evolution process of agglomeration. Experiments and modeling were performed to represent granulating behavior on the basis of selectivity, ballability and adhesion rate. The mass fraction of water and particles size of adhesion and nucleation were set at (11 ± 1)%, 0–1 mm and 3–5 mm, respectively. Experimental results show that selectivity and ballability promote the evolution of granulation. The water absorption rate of specularite and the ballability of limonite are better. The coupling efects exist in two ores mixing and present positive efect when the proportion of magnetite concentrate is greater than that of specularite or specularite and limonite blend. During three ores mixing, the coupling efect presents a complex superposition state. A characterization model of adhesion rate of mixing granulation was established by random forest algorithms. Its output is adhesion rate, and its inputs include water absorption rate, balling index and mixing proportion. The model parameters are 957 trees and four branches, and the training and prediction errors of the model are 2.3% and 3.7%, respectively. Modeling indicates that the random forest model can be used to represent coupling efects of mixing granulation.
Abstract：Characteristic of iron ore is the essential factor of granulating. Three ores, namely specularite, magnetite concentrate and limonite, were selected as adhesion powder to investigate granulating behavior and evolution process of agglomeration. Experiments and modeling were performed to represent granulating behavior on the basis of selectivity, ballability and adhesion rate. The mass fraction of water and particles size of adhesion and nucleation were set at (11 ± 1)%, 0–1 mm and 3–5 mm, respectively. Experimental results show that selectivity and ballability promote the evolution of granulation. The water absorption rate of specularite and the ballability of limonite are better. The coupling efects exist in two ores mixing and present positive efect when the proportion of magnetite concentrate is greater than that of specularite or specularite and limonite blend. During three ores mixing, the coupling efect presents a complex superposition state. A characterization model of adhesion rate of mixing granulation was established by random forest algorithms. Its output is adhesion rate, and its inputs include water absorption rate, balling index and mixing proportion. The model parameters are 957 trees and four branches, and the training and prediction errors of the model are 2.3% and 3.7%, respectively. Modeling indicates that the random forest model can be used to represent coupling efects of mixing granulation.
Dai?fei Liu,Xian?ju Shi,Chao?jun Tang, et al. Coupling efect and characterization modeling of iron ore fnes mixing and granulating at 0–1 mm[J]. Journal of Iron and Steel Research International, 2019, 26(11): 1154-1161.
2019, Vol. 26 
