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Indirect solution modeling of melting behavior of SiO2 based on the image processing technology
Asia-Pacific Journal of Chemical Engineering ( IF 1.8 ) Pub Date : 2024-01-11 , DOI: 10.1002/apj.3028
Cunhao Lu 1 , Yi Zhang 1 , Jiayi Zhang 1 , Weixiang Sun 1 , Anying Xia 2 , Mingli Zhang 3, 4 , Jian Chen 1
Affiliation  

The utilization of tempered blast-furnace slag through the direct fiber forming process to produce high-value thermal insulation materials offers a dual benefit: it efficiently utilizes the latent heat in the unused slag and significantly increases the value of blast-furnace slag utilization. However, measuring the melting properties of iron slag at high temperatures is challenging. In this study, the melting behavior of SiO2 in a high-temperature molten pool was investigated. We employ dynamic visual data (video stream) captured via a non-contact charge coupled device video recording system to extract SiO2 contours through image processing. The change in image centroid characteristics is used to establish a convolution function relationship, and MATLAB's traversal search algorithm determines the centroid position of SiO2. Given that SiO2 is proportionate to crucible pixels, the area of the SiO2 is calculated through pixel statistics within these contours. A new indirect method is then proposed to process image information to obtain SiO2 volume and mass at different time points. An exponential fitting yields the melting rate function of SiO2. Finally, this indirect method has been compared with shape from shading, quantitative characterization, and dimensional analysis techniques. Besides, the strengths and limitations of each method have been discussed. Our findings reveal that the indirect solution method presented here boasts straightforward calculation steps and imposes minimal image format requirements, which provides theoretical and technical support for the direct fiber forming process of blast-furnace slag.

中文翻译:

基于图像处理技术的SiO2熔融行为间接求解建模

通过直接纤维成型工艺利用回火高炉渣生产高价值保温材料具有双重好处:有效利用未利用的炉渣中的潜热,显着提高高炉渣的利用价值。然而,测量铁渣在高温下的熔化特性具有挑战性。在这项研究中,研究了SiO 2在高温熔池中的熔化行为。我们利用通过非接触式电荷耦合器件视频记录系统捕获的动态视觉数据(视频流)通过图像处理提取SiO 2轮廓。利用图像质心特性的变化建立卷积函数关系,通过MATLAB的遍历搜索算法确定SiO 2的质心位置。由于SiO 2与坩埚像素成比例,因此通过这些轮廓内的像素统计来计算SiO 2的面积。然后提出一种新的间接方法来处理图像信息以获得不同时间点的SiO 2体积和质量。指数拟合产生 SiO 2的熔化速率函数。最后,这种间接方法与阴影形状、定量表征和尺寸分析技术进行了比较。此外,还讨论了每种方法的优点和局限性。我们的研究结果表明,本文提出的间接求解方法具有计算步骤简单、图像格式要求极低的特点,为高炉矿渣直接纤维形成过程提供了理论和技术支持。
更新日期:2024-01-11
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