Abstract
The influence of the evolution rule of basicity (0.6∼2.4) on the mineral composition and microstructure of sinter is studied by using a polarizing microscope, and the comprehensive application analysis of the drum index, vertical sintering speed, and yield of sinter shows that, over the course of an increase in basicity (0.6∼1.0), the mineral structure changed from the original porphyritic-granular structure to a porphyritic structure. At the same time, there was no calcium ferrite phase in the bonding phase at a basicity of less than 1.0; therefore, the downward trend of the three indicators is obvious. When the basicity was further increased to approximately 1.6, the main structure of the mineral phase changed from a corrosion structure to an interweaving corrosion structure. Because of the existence of a porphyritic-granular structure, the structure of the mineral phase was extremely inhomogeneous and most complex near the basicity of 1.6; although a small amount of calcium ferrite displayed an acicular structure, the drum index appeared to show a very low value. With an increase in basicity to 2.0, the mineral phase structure was dominated by an interweaving corrosion structure with a uniform framework, and the content of calcium ferrite reached the highest value. Moreover, a clear acicular structure developed, and the drum index also increased to the highest value. At a basicity of more than 2.0, a mineral structure began to appear and the corrosion, porphyritic-granular structure, and the drum index also showed a slightly declining trend. Therefore, in the actual production process, basicity should be avoided as far as possible at around 1.0 and 1.6 and it should be controlled at around 2.0. At the same time, based on the mineral facies data set of this paper, the convolutional neural network is used to carry out a simple prediction model experiment on the basicity corresponding to the mineral facies photos, and the effect is quite good, which provides a new idea and method for the follow-up study of mineral facies.
Highlights
In the 21st century, with the development of the steel industry and the progress of science and technology, recent research on the composition of sinter minerals and the structure of minerals is increasing
Guo et al [8] used X-ray diffraction (XRD), an optical microscope (OM), a scanning electron microscope (SEM), and other types of equipment to study the differences in mineral composition and structure of high-basicity (1.84∼2.11) sinters produced by many large domestic steel plants. e results showed that most of the sinters are composed of magnetite, hematite, calcium ferrite, calcium silicate, and glass phases, and as the basicity increases, their morphology changes, displaying xenomorphic crystals
Webster et al [9] used in situ S-XRD to study the effect of basicity on the crystallization of the effective bonding phase of SFCA and Fe-rich SFCA in the sinter during cooling. e formation of Fe-rich SFCA is inhibited when the basicity is decreased from 4.0 to 2.5, but SFCA crystallizes from the melt during the cooling of material with basicity of 2.5
Summary
Effect of Basicity on the Microstructure of Sinter and Its Application Based on Deep Learning. When the basicity was further increased to approximately 1.6, the main structure of the mineral phase changed from a corrosion structure to an interweaving corrosion structure. Because of the existence of a porphyritic-granular structure, the structure of the mineral phase was extremely inhomogeneous and most complex near the basicity of 1.6; a small amount of calcium ferrite displayed an acicular structure, the drum index appeared to show a very low value. With an increase in basicity to 2.0, the mineral phase structure was dominated by an interweaving corrosion structure with a uniform framework, and the content of calcium ferrite reached the highest value. At a basicity of more than 2.0, a mineral structure began to appear and the corrosion, porphyritic-granular structure, and the drum index showed a slightly declining trend. At the same time, based on the mineral facies data set of this paper, the convolutional neural network is used to carry out a simple prediction model experiment on the basicity corresponding to the mineral facies photos, and the effect is quite good, which provides a new idea and method for the follow-up study of mineral facies
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