1 School of Metallurgical Engineering, Anhui University of Technology, Ma’anshan 243032, Anhui, China 2 Key Laboratory of Metallurgical Emission Reduction and Resource Comprehensive Utilization, Anhui University of Technology, Ma’anshan 243032, Anhui, China
Drop strength measurement of green pellet based on drop-rebound mechanism
1 School of Metallurgical Engineering, Anhui University of Technology, Ma’anshan 243032, Anhui, China 2 Key Laboratory of Metallurgical Emission Reduction and Resource Comprehensive Utilization, Anhui University of Technology, Ma’anshan 243032, Anhui, China
摘要 The construction of blast furnace charge structure based on pellet and the development of short process from non-blast furnace to electric furnace will be an efficient way to accomplish ‘‘carbon peak, carbon neutral’’. Since drop strength is one of the most crucial quality indexes for green pellet, the crack detection in the collision process is an indispensable segment; however, the present crack determination is basically completed manually. Due to a series of problems including high labor intensity and poor detection conditions, it is urgent to develop an accurate, convenient and fast standardized method for drop strength detection. In view of the above issues, combined with plenty of experimental studies, it is found that whether rebound occurs after the collision of green ball can be used as the basis for judging if there are cracks on the surface, and the mechanism of this segment is explained by the energy conversion of collision process that the plastic deformation of the collision is a cumulative process. Each collision will cause a slight displacement of the iron ore particles; until the cumulative displacement exceeds the binding force between the particles, they will slip in a large range, that is, cracks will occur. The drop strength can be detected based on the drop-rebound mechanism determining crack generation during collision process by high-speed cameras, and the method is fully applicable to oxidized pellets with particle size of 8–16 mm though various pellet plasticities and masses increase the difficulty of bounce height monitoring. Based on the drop-rebound mechanism of green pellet, three methods for automatically detecting the drop strength are proposed, which are high-speed camera, photoelectric sensor and pressure sensor methods.
Abstract：The construction of blast furnace charge structure based on pellet and the development of short process from non-blast furnace to electric furnace will be an efficient way to accomplish ‘‘carbon peak, carbon neutral’’. Since drop strength is one of the most crucial quality indexes for green pellet, the crack detection in the collision process is an indispensable segment; however, the present crack determination is basically completed manually. Due to a series of problems including high labor intensity and poor detection conditions, it is urgent to develop an accurate, convenient and fast standardized method for drop strength detection. In view of the above issues, combined with plenty of experimental studies, it is found that whether rebound occurs after the collision of green ball can be used as the basis for judging if there are cracks on the surface, and the mechanism of this segment is explained by the energy conversion of collision process that the plastic deformation of the collision is a cumulative process. Each collision will cause a slight displacement of the iron ore particles; until the cumulative displacement exceeds the binding force between the particles, they will slip in a large range, that is, cracks will occur. The drop strength can be detected based on the drop-rebound mechanism determining crack generation during collision process by high-speed cameras, and the method is fully applicable to oxidized pellets with particle size of 8–16 mm though various pellet plasticities and masses increase the difficulty of bounce height monitoring. Based on the drop-rebound mechanism of green pellet, three methods for automatically detecting the drop strength are proposed, which are high-speed camera, photoelectric sensor and pressure sensor methods.
Jie Lei,Xu Gao,Jing-shu An, et al. Drop strength measurement of green pellet based on drop-rebound mechanism[J]. Journal of Iron and Steel Research International, 2023, 30(11): 2143-2152.
2023, Vol. 30 
