Expert system of diagnostics blast furnace process (original) (raw)
Related papers
Logical-mathematical Evaluation Model of Blast-furnace Melting Operation
KnE Engineering, 2018
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.
Decision-Making Support in Blast-Furnace Operation
Steel in Translation, 2019
A model system for decision-making support (a model of the blast-furnace process developed at Yeltsin Ural Federal University and PAO MMK) is considered. The basic model modules permit calculation of the material and thermal balances, simulation of the thermal, slag, and gas-dynamic conditions in the blast furnace, and selection of the batch composition. The model system, embodied as software, is integrated into the PAO MMK information system. The model for calculating the material and thermal balances permits determination of the Fe, S, Mn, and Ti balances. Introduction of the Slag Conditions software permits identification of the most important slag property to ensure normal slag conditions; determination of the ratio of the iron-ore materials so that the slag has the best viscosity and viscosity gradient; and the production of hot metal of the required quality. The introduction of Blast-Furnace Gas Dynamics software permits calculation and visual mapping of the gas-dynamic characteristics of the batch bed and assessment of the change in pressure difference and equilibration of the batch within individual zones of the furnace in the design period, with variation in the batch parameters and properties. The results obtained in practical use of this system are outlined. Recommendations are made regarding the solution of industrial problems.
Using Expert Systems in Blast Furnace Operation — a few preliminary impressions
Strategic Management of the Manufacturing Value Chain, 1998
In this paper the enigmatic development of a expert system for blast furnace control in the steel industry. It is used as an example of how a perceived "low tech" industry may develop a "high tech" tool and the paper point to some initial impressions on consequences both on an industry and individual level.
Metals
This article presents a description of three decision support systems (DSS) in the mode of an adviser to the technological personnel of blast furnaces (BF), which were implemented by the Iron and Steel Institute of Z.I. Nekrasov (Dnipro, Ukraine) or underwent pilot testing as part of the automated control system of the BF shop of PrJSC “Kamet-steel” (Kamianske, Ukraine). The first DSS for managing the thermal state was implemented in 2021; it includes the entire list of information necessary for personnel in a convenient and compact form, generates recommendations in case of technology deviations, and, in the case of incorrect actions by the personnel, signals the need for correct actions. The main recommendations from the DSS are to correct the raceway adiabatic flame temperature, coke consumption when its characteristics are specified in (indicators of strength and abrasion, fractional composition, humidity, ash and sulfur), and ore load change. Using the system allows both reduci...
Metallurgical Research & Technology
The estimation of thermal level in blast furnace is of utmost importance, because the processes occurring inside the blast furnace are complex in nature and any drift in thermal level could lead to abnormal furnace state. The present review is made to understand the methods for estimating thermal level in blast furnace, and the drift in estimation of the thermal level. The thermal level estimation is divided into 3 categories, viz. mathematical models, statistical models and decision support systems. The mathematical models are based on the first principle of thermodynamics and give an estimate of the thermal level in blast furnace. On the other hand, the statistical models are mainly the data-based approach that uses the historical data to predict the instability in blast furnace. Lastly, the decision support systems are the prescriptive models that give the recommendations for making the necessary corrections in the process parameters to avoid occurrence of abnormality in blast fu...
Study of transition processes of blast-furnace smelting by the mathematical model method
IOP Conference Series: Materials Science and Engineering, 2018
In work possibilities of the developed computer model system for forecasting of a thermal condition of a blast furnace (on change of the maintenance of silicon in pig-iron) in a mode of real time are considered. The basis of the model is the fundamental knowledge of the theory and practice of the modern blast-furnace process, the use of regularities in the processes of heat and mass transfer, gas dynamics, slag formation processes in modern blast furnace melting. When solving the dynamic problem, it is envisaged to use the analytical (obtained on the basis of fundamental knowledge), but the linearized model of the domain process, the principle of small deviations and the natural-mathematical approach. In the algorithm for solving problems in transient blast furnace processes, the calculation of the dynamics of the change in the heating of the bottom of a blast furnace (based on the silicon content in cast iron) was performed according to the additivity rule by summing the predicted silicon concentrations in cast iron when the loading parameters (ore load) and the control actions on the thermal load the state of the furnace from the bottom-the consumption of natural gas, the concentration of oxygen in the blast and the humidity of the blast. Examples of calculations of the transient processes of the gas-dynamic resistance of the batch layer, the thermal state, and the productivity of the blast furnace are shown in the context of the changes in the properties and composition of the iron-ore materials being loaded and the parameters of the combined blast are applied to the conditions of PJSC "Magnitogorsk Iron and Steel Works" (MMK).
2009
In the last few years, the use of computers has made it possible to achieve a better image of blast furnace performance, allowing the establishment of models, the comparison of variables and the construction of powerful databases to store the variables and their evolution during the process. Nevertheless, part of the investment made in blast furnace equipment is not properly utilized and a considerable part of the information collected could be put to much better use. The application of modern data mining techniques has overcome these problems. This work shows ways to apply these techniques to data from probes located in the throat or shaft of the blast furnace, as well as how to extract useful information by defining and classifying a set of patterns in classes from temperature profiles that have been linked to the stability of the process in steelworks with blast furnaces.
Analysis of the Slag Mode of Blast Furnace Melting Using Model Decision Support Systems
2022
The paper presents a balance model of the blast-furnace process improved by the researchers from the Ural Federal University and Magnitogorsk Iron and Steel Works. It generally represents a system of deterministic dependencies characterizing the thermal, reduction, gas dynamics, blast, and slag modes of blastfurnace melting. The basic principle underlying the model is full-scale mathematical modeling. Indicators characterizing the process of the final slag for implementation of the normal slag mode of blast-furnace melting (the slag viscosity at temperatures ranging from 1350 to 1550°C, as well as the values of 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 the 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 expert evaluation method. The structure of the model for calculating the parameters of the final slag is considered. Using a mathematical model of the blast-furnace process, the 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, the smelted cast iron has a down-graded quality in terms of both the sulfur and silicon content. Due to the changes in the slag mode characteristics, other conditions being equal, it is possible to get a positive effect on the gas permeability in the slag formation zone; the gas reducing ability and productivity of the blast furnace increase; the coke consumption decreases. The authors present the results of design calculations of the performance indicators of the furnaces of the Magnitogorsk Iron and Steel Works when changing the composition of loaded materials. Recommendations on the slag optimal basicity are given. Calculations showed that the optimal values of basicity of the final slag, which ensure its maximum liquid mobility, for the operating conditions of blast furnaces of the Magnitogorsk Iron and Steel Works are 1.04-1.05 for the CaO/SiO 2 ratio and 1.30-1.32 for the (CaO + MgO)/SiO 2 ratio.
STUDY OF THE IMPACT OF OPERATIONAL PARAMETERS ON PRODUCTION OF HOT METAL IN A BLAST FURNACE
iaeme, 2019
The study made in this paper, is to analyze the Blast Furnace parameters based on Hybrid multi-criteria decision making approach. The analysis is important as the parameters cause the influence on the production process. The productivity as well as quality can be improved by knowing these parameters in advance. The present work examined is identification of various critical parameters of blast furnace in an integrated Steel Plant by utilizing Response Surface Method based on GRA integrated with PCA approach. GRA works like a discovery idea where known and obscure components are aggregated to get optimum level of the multiple responses. Breeze coke consumption, nut coke consumption, pulverized coal consumption, consumption of sinter, composite quality index of sinter plant, sized iron ore consumption, pellets consumption, Lime stone consumption, LD slag consumption, blast temperature, blast pressure, blast volume and oxygen enrichment are considered as Blast furnace operating parameters. Hot metal yield, % Si, %S, %P, %Mn, %CO 2 , %CO, %SO x , %NO x and PM are considered as the output variables.. The grey relation coefficients are subjected to principal component analysis to derive the principle component scores which represent the aggregated response of multiple output variables. Finally, response surface methodology is implemented by considering the input parameters of Blast Furnace as factors and PCA score as response to analyze the impact of input parameters on the Blast Furnace performance.