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Natsui, Shungo; Goto, Yuko; Takahashi, Jun-ichi; Nogami, Hiroshi
Chemical engineering science, 07/2023, Volume: 276Journal Article
Display omitted •Combustion studies of Cu concentrate tablets were performed.•A video-based classification system based on deep learning was used.•This system recognized the combustion patterns of the Cu concentrate tablets.•The contact area between the tablet and gas may be critical in this recognition. The combustion behavior of the complex, ever-changing Cu concentrate with SiO2 flux in a flash smelting shaft should be comprehensively understood to improve the efficiency and energy consumption of smelting. To characterize the combustion behavior of each sample, combustion studies involving high-speed digital microscopy and thermal measurements were performed using numerous small Cu concentrate tablets. Generally, two temperature ranges of heating retardation were observed during combustion, at approximately 800–1000 and 1150–1200 °C. A novel video-based Cu concentrate classification system was used to successfully recognize the different combustion patterns of tablets with Cu concentrate-SiO2 mixtures under oxidation gas. This classification system also enabled the calculation of the chemical composition of the concentrate by transforming the network output into a probability distribution. The algorithm based on deep learning employed in this study could learn the combustion behaviors of SiO2-containing Cu concentrates using time-series images extracted from video data.
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