Modeling Analysis of Melting and Crystallization Process of Mold Flux Based on the Image Processing Technology

Abstract

The aim of this paper is to obtain the image information based on a given image of mold flux and to obtain the features that can describe the dynamical difference. The melting and crystallization dynamics of the slag were analyzed using the autoregressive moving average (ARIMA) time series model and data fitting method. Firstly, the binary image of the digital region of the original image was obtained by image information processing and segmentation methods, the original image number was determined by comparing the similarity of the information matrices of the given and standard images. The standard number with the highest similarity was considered as the number of the original image, and MATLAB was used to solve the problem, the digital information in all the images was successfully extracted. Secondly, ten eigenvalues were extracted from the given image after removing the background, and three principal components were obtained by principal component analysis. Then, a scoring model was constructed based on the percentage of variance, and the comprehensive scores of the three principal components to analyze the melting and crystallization process of the mold flux. Finally, based on the above work, the dynamic relationship between temperature, time and the melting and crystallization process of the mold flux was investigated. Since the temperature is approximately linearly correlated with time, the problem was transformed into finding the relationship between the melting and crystallization process of the mold flux and time. The least squares method, polynomial fitting and other methods were used to derive the relationship function, the relationship between the melting and crystallization process of mold flux and temperature and time was quantitatively analyzed.