Xue Bai
ABSTRACT
Detection of blast furnace condition is an important basis for making control decisions for blast furnaces. The distribution characteristics of the gas flow is one of the decisive factors for production conditions. Because the interior of the blast furnace is dark and airtight state, the environment is extremely complex and the distribution characteristics of the gas flow cannot be detected directly, the identification of the distribution characteristics of the gas flow has become a current research hotspot. This article summarizes and analyzes the related literature on identification of the distribution characteristics of the gas flow. It mainly summarizes the research progress of this direction from four research methods, and makes a brief evaluation, comprehensively analyzes the related methods based on mathematical and mechanism model, soft melting zone model, neural network model based on cross temperature measurement and infrared camera technology, points out the existing problems, and summarize it.
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