Abstract:Аннотация. В настоящее время с развитием вычислительных средств и систем контроля возросла роль цифровизации и цифровой трансформации металлургического производства. Важнейшим элементом перехода на цифровую металлургию является концепция "Индустрия 4.0". Основными составляющими цифровой металлургии являются математические модели физико-химических процессов, протекающих в металлургических агрегатах, и базы данных этих процессов. В Институте металлургии УрО РАН предложен ряд технических решений по совершенствова… Show more
“…The Metallurgical Institute of the Urals Division of the Russian Academy of Sciences has developed and implemented a series of mathematical models within the framework of Industry 4.0; these models include 2D and 3D analyses of gas dynamic phenomena, temperature fields in the gas and charge, and iron oxide reduction degree; use of these models made it possible to determine the location and shape of the cohesion zone [7].…”
A comprehensive mathematical model is developed and tested to assess how the ore/coke ratio as a function of radius in the blast furnace affects the shape of the softening and melting (cohesion) zone. The height of the cohesion zone is determined by the temperature difference between the onset and end of melting for the iron ore materials. The cohesion zone is located between the isotherms formed by lines connecting the points corresponding to the onset and end of melting for materials in six vertical ring zones defined within the blast furnace. The location of the isotherms in the furnace space describes the configuration of the cohesion zone, which has a significant effect on the distribution of gas flow and the economic performance of the blast furnace process. A Λ-shaped cohesion zone was found to be better than a W-shaped cohesion zone from the standpoint of ensuring even operation of the furnace and improving the economic performance of the blast furnace process; however, the hearth temperature in each of the vertical ring zones must exceed the temperature for complete fluidization of the pig iron and slag by at least 50 °C.
“…The Metallurgical Institute of the Urals Division of the Russian Academy of Sciences has developed and implemented a series of mathematical models within the framework of Industry 4.0; these models include 2D and 3D analyses of gas dynamic phenomena, temperature fields in the gas and charge, and iron oxide reduction degree; use of these models made it possible to determine the location and shape of the cohesion zone [7].…”
A comprehensive mathematical model is developed and tested to assess how the ore/coke ratio as a function of radius in the blast furnace affects the shape of the softening and melting (cohesion) zone. The height of the cohesion zone is determined by the temperature difference between the onset and end of melting for the iron ore materials. The cohesion zone is located between the isotherms formed by lines connecting the points corresponding to the onset and end of melting for materials in six vertical ring zones defined within the blast furnace. The location of the isotherms in the furnace space describes the configuration of the cohesion zone, which has a significant effect on the distribution of gas flow and the economic performance of the blast furnace process. A Λ-shaped cohesion zone was found to be better than a W-shaped cohesion zone from the standpoint of ensuring even operation of the furnace and improving the economic performance of the blast furnace process; however, the hearth temperature in each of the vertical ring zones must exceed the temperature for complete fluidization of the pig iron and slag by at least 50 °C.
The article considers an overview and critical analysis of the digitalization of the leading Russian ferrous metallurgy enterprises in accordance with the Industry 4.0 development concept. It provides for the creation of digital twins of pyrometallurgical technologies, the widespread use of machine vision and artifcial intelligence. The examples of domestic industrial systems using the technologies of machine (technical) vision in production cycle, digital assistants (twins) of metallurgical units and their sets are presented. With regard to blastfurnace production, technical vision systems used to control processes in the upper and lower zones of blast furnace are considered. A promising area is the integration of technical vision and decision support systems, including algorithms and software modules for implementation of deterministic mathematical models of individual phenomena of blast furnace smelting. They are based on fundamental physical concepts of blastfurnace smelting processes. One of the main directions of digital transformation of pyrometallurgical technologies is creation of intelligent control systems for technological process in metallurgy in real time. When formulating and solving problems, it is required not only to study the characteristics describing the effect of change in melting conditions on technical and economic indicators of the operation of individual furnaces, but also a detailed analysis for mathematical description of external and internal constraints. The authors present the examples of subsystems for control of heat losses in a blast furnace, predicting the parameters of tuyere hearths and controlling distribution of blast parameters around the perimeter of a blast furnace, an automated system for analyzing and predicting production situations in a blast furnace. Creation of such systems was carried out on the basis of modern principles and technologies for the development of appropriate mathematical, algorithmic and software support.
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