Expert system of diagnostics blast furnace process

The expert system of diagnostics blast furnace process is presented. It is based on a logical-mathematical model for assessing the progress of blast furnace smelting. The model provides an opportunity to evaluate the normal operation mode of blast furnace and further deviations from this mode such as overdeveloped gas flows (peripheral and central), violation of thermal melting conditions (hot and cold course of melt), violation of smooth descent of burned materials in the furnace (tight furnace operation, higher and lower suspension of burden). The functional capabilities of developed software are represented. © Published under licence by IOP Publishing Ltd

Analysis of slag mode of blast furnace melting using model decision support systems

The article presents a balance model of the blast furnace process improved by the researchers from UrFU and PJSC "Magnitogorsk Iron and Steel Works" (MMK). It generally represents a system of deterministic dependencies characterizing the thermal, reduction, gas dynamic, blast and slag modes of blast furnace melting. The basic principle underlying the model is full-scale mathematical modeling. Indicators characterizing the properties of the final slag for implementation of normal slag mode of blast furnace melting (slag viscosity in the temperature range of 1350 - 1550 °C, as well as values of the slag viscosity gradients) were proposed. The slag viscosity gradient, along with the acceptable ranges of slag viscosity at different slag temperatures, are used in modeling the slag mode as limiting factors for the diagnosis of slag mode. Selection of the limit values of each of the ranges and the viscosity gradient is carried out by the method of expert evaluation. Structure of the model for calculating the parameters of the final slag is considered. Using a mathematical model of the blast furnace process, analysis of the slag mode of blast furnace melting was performed according to the actual indicators of their operation. It was established that desulfurizing ability of the slag is insufficiently used, as a result of which cast iron of reduced quality is smelted both in terms of content of sulfur and silicon. Change in characteristics of the slag mode, other things being equal, has a positive effect on gas permeability in the slag formation zone, reducing capacity of the gas and productivity of the blast furnace increase, as well as the consumption of coke decreases. The authors describe the results of design calculations of the MMK furnace performance indicators when changing the composition of loaded materials. Recommendations on the slag optimal basicity are given. Calculations showed that the optimal basicity of the final slag, which ensures its maximum liquid mobility, for operating conditions of blast furnaces of the combine is 1.04 - 1.05 for the CaO/SiO2ratio and 1.30 - 1.32 for the (CaO + MgO)/SiO2ratio. © 2022 National University of Science and Technology MISIS. All rights reserved

Assessment of an expediency of binder material mechanical activation in cemented rockfill

This study is aimed to assess the expediency of applying the binder material mechanical activation in a cemented rockfill (CRF), consisting of ground smelter slag, waste of limestone and rock refuse at one of the largest mines, as well as at any other mines which use these components for CRF. The polynomial dependences have been obtained of strength variation of the CRF, which is used in the conditions of studied mine, on the time of consolidation and the ratio of backfill materials. In the CRF mixtures, the mechanical activation was carried out of the granulated blast-furnace slag, and the compliance has been assessed of CRF with the design strength of the backfill massif. In the studied conditions of the ore mine, with ratio of a binder material to filler of 0.5 and the existing cost of backfill materials, the use of mechanical activation of the binder material according to the two-stage grinding scheme turned out to be insufficiently expedient, since the production cost (materials + grinding) of the most economical backfill mixture is only 2.8% less compared with a basic composition. It is noted that the expediency of using the mechanical activation depends on the remoteness of the mineral raw material base, especially the main inert filler that significantly increases the cost of backfilling works. It is shown that in the operating conditions of other mines with a similar component proportion and a close rich mineral raw base, the mechanical activation of the binder material can be enough effective. It has been determined that with an increase in ratio of Cbin/Cin from 1.0 to 4.6, the difference in costs for the backfill mixture production in the considered compositions, where mechanical activation was performed, increases in a positive direction, but for the most economical backfill mixture, if compared to the basic one, it will be changed from 16.8 to 46.0%. An attention is focused on possible ways to increase the expediency of applying the mechanical activation of the binder material by means of forming the backfill massif with different strength along the height of the stope chamber

Logical-mathematical Evaluation Model of Blast-furnace Melting Operation

The logical-mathematical evaluation model of blast-furnace melting operation is represented. The model provides an opportunity to evaluate the normal operation mode of blast furnace and further deviations from this mode such as overdeveloped gas flows (peripheral and central), violation of thermal melting conditions (hot and cold course of melt), violation of smooth descent of burned materials in the furnace (tight furnace operation, higher and lower suspension of burden). The functional capabilities of developed software are represented. Keywords: blast-furnace production, information logical system, software development, blast-furnace melting operation diagnostic

The development of a process charge expert system for a Basic Oxygen Steelmaking plant.

In an integrated steelworks the Basic Oxygen Steelmaking (BOS) process is required for the refining of molten iron from a blast furnace to produce steel. The development of an expert diagnostic system is considered in the context of the initial phase of BOS operation, the loading and operation of the BOS vessel. In this part of the steelmaking process the BOS vessel is charged with the molten iron, scrap metal and fluxes which are there to facilitate the capture of impurities by forming slag. The nature of the elements added requires knowledge of the steelmaking process, the actual state of the contents of the vessel and the available process management options. The expert system produced to oversee this process exhibits the capability of dealing with both continuous and batch data, combining the two together to aid effective decision making and management. Fuzzy inference is used in the main diagnostic system due to the large rule base required to diagnose faults and infer a process state. The operation of the system and its use by the process operators and the application of this approach into other areas of the steelworks is considered in this paper

Auction-based approach to resolve the scheduling problem in the steel making process

Steel production is an extremely complex process and determining coherent schedules for the wide variety of production steps in a dynamic environment, where disturbances frequently occur, is a challenging task. In the steel production process, the blast furnace continuously produces liquid iron, which is transformed into liquid steel in the melt shop. The majority of the molten steel passes through a continuous caster to form large steel slabs, which are rolled into coils in the hot strip mill. The scheduling system of these processes has very different objectives and constraints, and operates in an environment where there is a substantial quantity of real-time information concerning production failures and customer requests. The steel making process, which includes steel making followed by continuous casting, is generally the main bottleneck in steel production. Therefore, comprehensive scheduling of this process is critical to improve the quality and productivity of the entire production system. This paper addresses the scheduling problem in the steel making process. The methodology of winner determination using the combinatorial auction process is employed to solve the aforementioned problem. In the combinatorial auction, allowing bidding on a combination of assets offers a way of enhancing the efficiency of allocating the assets. In this paper, the scheduling problem in steel making has been formulated as a linear integer program to determine the scheduling sequence for different charges. Bids are then obtained for sequencing the charges. Next, a heuristic approach is used to evaluate the bids. The computational results show that our algorithm can obtain optimal or near-optimal solutions for combinatorial problems in a reasonable computation time. The proposed algorithm has been verified by a case study

МНОГОУРОВНЕВОЕ РЕСУРСОСБЕРЕГАЮЩЕЕ УПРАВЛЕНИЕ ДОМЕННЫМ ПРОЦЕССОМ

A multilevel resource-saving blast furnace process control is considered. The resource-saving control is provided for operating, adaptation, technical and economic control in the automated systems of blast-furnace processes.It is proposed to form optimal operation modes of blast furnace heating, metal charge structures, natural gas and oxygen consumption. Decisions are made using Kohonen neural networks taking into account current and planned parameters of coke quality, iron ore, raw materials and blast.At the level of operating control, the work suggests a model predictive control to improve the resource conservation indicators. The method is based on decomposition of the general problem of the process dynamics identification on particular problems: dynamic synchronization and identification of process transfer functions.At the level of adaptive control, optimal operating modes of blast furnaces are expedient to be developed with respect to blast furnace heating, structure of metal charge, natural gas and oxygen rate considering the current and planned parameters of coke, blasting. The blast furnace operating modes are suggested to be determined based on Kohonen neural networks.In evaluating the efficiency of introducing the model predictive control, the existing actual statistics of scatter of BF mode parameters should be based upon. The fact is that the introduction of model predictive control assumes no radical change of the BF melt technology. Like in all the control systems, the BF process is considered as the set control object with all its characteristics. Changing process settings, raw material content does not introduce any cardinal variation in the scatter of process characteristics. However, in this case a transient process occurs which is necessary for the control system to identify the changing conditions. The transient process is inherent to all the control systems and the blast furnace process is not an exclusion. As a result of transient process, the control system is set to the optimal mode.Рассмотрены вопросы построения многоуровневого ресурсосберегающего управления доменным процессом. Ресурсосберегающее управление целесообразно выполнять на основе внедрения автоматизированной системы для оперативного, адаптивного и технико-экономического управления доменным процессом.На уровне адаптивного управления целесообразно осуществлять формирование оптимальных режимов работы доменных печей по нагреву печей, структуре металлошихты, расходу природного газа, кислорода с учетом текущих и планируемых параметров качества кокса, железорудного сырья, дутья. Определение режимов работы доменной печи предлагается осуществлять на основе нейронных сетей Кохонена.На уровне оперативного управления в работе предложен метод модельно-упреждающего управления, повышающий показатели эффективности использования ресурсов. Метод основан на декомпозиции общей задачи определения динамических характеристик сложных технологических процессов на частные задачи динамической синхронизации и идентификации передаточных свойств. Для решения сложных задач идентификации предложено использовать искусственные нейронные сети.При оценке эффективности введения модельно-упреждающего управления необходимо исходить из существующей реальной статистики разброса режимных параметров доменного процесса. Дело в том, что введение модельно-упреждающего управления не предполагает коренной смены технологии доменной плавки. Как и во всех системах управления, здесь доменный процесс рассматривается как заданный объект управления со всеми своими характеристиками. Изменение уставок процесса, состава сырья не вносит кардинального изменения в разброс характеристик процесса. Однако при этом возникает переходный процесс, необходимый системе управления для идентификации изменившихся условий. Переходный процесс присущ всем системам управления, и доменный процесс не является исключением. В результате переходного процесса система управления настраивается на оптимальный режим