Image analysis of high temperature melting process of iron tailings based on clustering model
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DOI: 10.25236/iwmecs.2020.009
Author(s)
Ma Xiaocui, Lv Huanzhu, Zhang Kefei
Corresponding Author
Zhang Kefei
Abstract
In this paper, the melting process of iron tailings was studied. The region of silicon dioxide was obtained from 140 sequence images of silicon dioxide in high temperature molten pool during the melting process. According to the clustering results, the number of pixels in the whole image and the intercepted iron tailings image is counted. The specific physical process is analyzed by combining the pixel number of the whole image and the crucible outer diameter data. In this paper, the piecewise function and the exponential function of the angle between the center of mass and the center of the crucible are established. The position of the mass center and its motion track are studied, and the track diagram of the two-dimensional space is drawn by MATLAB. The morphology and area of SiO2 in the melting process can be effectively described by using the generalized diameter method. The phase between the generalized diameter and the velocity is calculated by using the micro element method. The melting rate at different time was quantitatively characterized by correlation function. The research realizes the transformation of data information from complex melting process to its change law, establishing reliable time sequence law for high temperature melting process, providing strong theoretical basis for production practice, and avoids various losses caused by repeated tests to a certain extent.
Keywords
Description of SiO2 Melting Process, Define diameter, Compound Time Series Solution, Data fitting, Image processing, Hierarchical cluster analysis