WO2023095647A1 - Dispositif d'inférence d'état intra-four, procédé d'inférence d'état intra-four et procédé de fabrication d'acier fondu - Google Patents

Dispositif d'inférence d'état intra-four, procédé d'inférence d'état intra-four et procédé de fabrication d'acier fondu Download PDF

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Publication number
WO2023095647A1
WO2023095647A1 PCT/JP2022/042138 JP2022042138W WO2023095647A1 WO 2023095647 A1 WO2023095647 A1 WO 2023095647A1 JP 2022042138 W JP2022042138 W JP 2022042138W WO 2023095647 A1 WO2023095647 A1 WO 2023095647A1
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Prior art keywords
refining process
refining
model
furnace
model parameters
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PCT/JP2022/042138
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English (en)
Japanese (ja)
Inventor
寛人 加▲瀬▼
智裕 杉野
涼 川畑
祐貴 木村
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Ｊｆｅスチール株式会社
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Application filed by Ｊｆｅスチール株式会社 filed Critical Ｊｆｅスチール株式会社
Priority to CN202280069651.9A priority Critical patent/CN118103530A/zh
Priority to KR1020247015910A priority patent/KR20240090437A/ko
Priority to EP22898431.6A priority patent/EP4400607A1/fr
Priority to JP2023505466A priority patent/JP7392897B2/ja
Publication of WO2023095647A1 publication Critical patent/WO2023095647A1/fr

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    • C—CHEMISTRY; METALLURGY
    • C21—METALLURGY OF IRON
    • C21C—PROCESSING OF PIG-IRON, e.g. REFINING, MANUFACTURE OF WROUGHT-IRON OR STEEL; TREATMENT IN MOLTEN STATE OF FERROUS ALLOYS
    • C21C7/00—Treating molten ferrous alloys, e.g. steel, not covered by groups C21C1/00 - C21C5/00
    • C—CHEMISTRY; METALLURGY
    • C21—METALLURGY OF IRON
    • C21C—PROCESSING OF PIG-IRON, e.g. REFINING, MANUFACTURE OF WROUGHT-IRON OR STEEL; TREATMENT IN MOLTEN STATE OF FERROUS ALLOYS
    • C21C5/00—Manufacture of carbon-steel, e.g. plain mild steel, medium carbon steel or cast steel or stainless steel
    • C21C5/28—Manufacture of steel in the converter
    • C—CHEMISTRY; METALLURGY
    • C21—METALLURGY OF IRON
    • C21C—PROCESSING OF PIG-IRON, e.g. REFINING, MANUFACTURE OF WROUGHT-IRON OR STEEL; TREATMENT IN MOLTEN STATE OF FERROUS ALLOYS
    • C21C5/00—Manufacture of carbon-steel, e.g. plain mild steel, medium carbon steel or cast steel or stainless steel
    • C21C5/28—Manufacture of steel in the converter
    • C21C5/42—Constructional features of converters
    • C21C5/46—Details or accessories
    • C21C5/4673—Measuring and sampling devices
    • C—CHEMISTRY; METALLURGY
    • C21—METALLURGY OF IRON
    • C21C—PROCESSING OF PIG-IRON, e.g. REFINING, MANUFACTURE OF WROUGHT-IRON OR STEEL; TREATMENT IN MOLTEN STATE OF FERROUS ALLOYS
    • C21C5/00—Manufacture of carbon-steel, e.g. plain mild steel, medium carbon steel or cast steel or stainless steel
    • C21C5/52—Manufacture of steel in electric furnaces
    • C21C2005/5288—Measuring or sampling devices
    • C—CHEMISTRY; METALLURGY
    • C21—METALLURGY OF IRON
    • C21C—PROCESSING OF PIG-IRON, e.g. REFINING, MANUFACTURE OF WROUGHT-IRON OR STEEL; TREATMENT IN MOLTEN STATE OF FERROUS ALLOYS
    • C21C2300/00—Process aspects
    • C21C2300/06—Modeling of the process, e.g. for control purposes; CII

Definitions

  • the present disclosure relates to an in-core state estimation device, an in-core state estimation method, and a molten steel production method.
  • the present disclosure particularly relates to an in-furnace state estimating device, an in-furnace state estimating method, and a molten steel manufacturing method for estimating component concentrations in molten metal and slag in refining facilities in the steel industry.
  • the composition and temperature of the hot metal tapped from the blast furnace are adjusted in refining equipment such as pretreatment equipment, converters and secondary refining equipment.
  • a converter is a process that removes impurities from molten metal and raises the temperature by blowing oxygen into the furnace, and plays a very important role in the quality control of steel and rationalization of refining costs.
  • flow rate and speed of top-blowing oxygen, height of top-blowing lance, flow rate of bottom-blowing gas, and the like are used as manipulated variables.
  • the input amount and input timing of auxiliary materials such as lime and iron ore, the timing of sampling molten metal, the timing of ending blowing, and the like are used as manipulated variables.
  • These manipulated variables should be optimized according to the conditions in the furnace such as the molten metal temperature, molten metal composition and slag composition.
  • the material balance and heat balance in the furnace are calculated using the measurement information about the refining equipment including the flue gas measurement value that can be measured continuously during the refining process. A method of doing the calculation is proposed. This method is generally considered to be capable of estimating the molten metal temperature, molten metal composition and slag composition in real time with high accuracy.
  • Patent Document 1 discloses that the value of the parameter in the independent model formula of the converter is based on the past performance information and the performance with similar processing conditions. We propose a method of extraction and calculation.
  • Patent Document 2 proposes a method of determining multiple parameters of a molten metal temperature estimation model in a secondary refining facility by obtaining approximate solutions of simultaneous equations set so that the heat balance is balanced.
  • Patent Document 1 targets an independent physical reaction model or a primary binding model as a model formula. Therefore, the technique of Patent Document 1 is difficult to apply to a model in which the amount of reaction in the furnace and the amount of temperature rise interact in a complicated manner, such as a state estimation model based on the calculation of the material balance and heat balance in the furnace.
  • Patent Document 2 proposes a method of obtaining an approximate solution of simultaneous equations set so that the heat balance is balanced for a temperature estimation model formula in which a plurality of model formulas and parameters interact with each other.
  • Patent Document 2 does not describe in-furnace material balance calculation using measurement information including exhaust gas measurement values in calculating the reaction amount in the furnace. Therefore, it is difficult to apply the technique of Patent Document 2 to a model in which the in-core material balance interacts with the heat balance.
  • An object of the present disclosure which has been made in view of such circumstances, is to provide an in-furnace state estimating device, an in-furnace state estimating method, and a molten steel manufacturing method that can accurately and continuously estimate the concentration of components in molten metal and slag. It is in.
  • An in-core state estimation device Measurement results of molten metal temperature and component concentration and slag component concentration before or during the refining process in the refining equipment, measurement results of the refining equipment including the flow rate and component concentration of the exhaust gas discharged from the refining equipment an input unit for inputting performance information and conditions for the refining process;
  • a model determination unit that determines the model parameters;
  • an in-furnace state calculation unit that calculates state quantities in the furnace including the temperature and component concentration of the molten metal and the component concentration of the slag using the determined model parameters;
  • Based on the performance information including the result of the refining process of the target charge based on an evaluation function including a term representing the mass balance error and the heat balance error in the furnace from the start point to the end point of
  • the model determination unit averages the model parameters of the past refining processes similar to the conditions of the refining process of the target charge among the past model parameters stored in the database, thereby determining the target charge. determine the model parameters in the refining process of
  • the model determination unit models the relationship between the past model parameters stored in the database and refining conditions including at least one of the number of times of processing in the refining process, the date and time of processing, and the number of times the refining equipment is used. , determining the parameters in the smelting process of the target charge from the model;
  • the model parameters are the integrated amount of carbon introduced into the furnace during a specific period, the integrated amount of carbon discharged outside the furnace during a specified period, the amount of oxygen introduced into the furnace, and the amount of carbon discharged outside the furnace.
  • a coefficient or a constant term for correcting at least one of the amount of oxygen discharged, the amount of oxygen used for oxidizing various metal impurities in the molten metal, and the integrated amount for a specific period of the amount of change in the temperature of the molten metal due to changes in the amount of heat in the furnace. include.
  • the evaluation function is composed of a weighted sum of a term indicating the carbon balance, a term indicating the oxygen balance, and a term indicating the heat balance.
  • a reactor state estimation method includes: An in-core state estimation method executed by an in-core state estimation device, comprising: Measurement results of molten metal temperature and component concentration and slag component concentration before or during the refining process in the refining equipment, measurement results of the refining equipment including the flow rate and component concentration of the exhaust gas discharged from the refining equipment an input step in which performance information and conditions for the refining process are input; In the refining process of the target charge using the past model parameters obtained from a database that stores the model parameters of the model related to the blowing reaction in the refining equipment, the performance information, and the conditions of the refining process a model determination step of determining the model parameters; an in-furnace state calculation step of calculating in-furnace state quantities including the temperature and component concentration of the molten metal and the component concentration of the slag using the determined model parameters; Based on the performance information including the result of the refining process of the target charge, based on an evaluation function including a
  • the model determining step averages the model parameters of the past refining processes similar to the conditions of the refining process of the target charge among the past model parameters stored in the database, thereby determining the target charge. determine the model parameters in the refining process of
  • the model determination step models the relationship between the past model parameters stored in the database and the conditions of the refining process including at least one of the number of times of refining process, the date and time of the process, and the number of times the refining equipment is used. , determining the parameters in the smelting process of the target charge from the model;
  • a molten steel production method includes: Based on the temperature and component concentration of the molten metal and the component concentration of the slag estimated by the furnace state estimation method of any one of (6) to (8), the flow rate and speed of the top-blown oxygen, the height of the top-blowing lance, Refining operation is performed by determining at least one of the flow rate of bottom-blown gas, the input amount and input timing of auxiliary materials such as lime and iron ore, the timing of sampling the molten metal, and the timing of ending blowing, and molten steel is manufactured. do.
  • an in-furnace state estimation device an in-furnace state estimation method, and a molten steel production method that are capable of accurately and continuously estimating component concentrations in molten metal and slag.
  • FIG. 1 is a schematic diagram showing the configuration of an in-core state estimation device that is an embodiment of the present disclosure.
  • FIG. 2 is a diagram showing a configuration example of a database.
  • FIG. 3 is a flow chart showing processing of an in-core state estimation method according to an embodiment of the present disclosure.
  • a reactor state estimation device, a reactor state estimation method, and a molten steel production method according to an embodiment of the present disclosure will be described below with reference to the drawings.
  • FIG. 1 is a schematic diagram showing the configuration of an in-core state estimation device 1 according to an embodiment of the present disclosure.
  • the in-core state estimation device 1 is used as a part of equipment for manufacturing molten steel in the steel industry.
  • a facility for manufacturing molten steel includes a refining facility 2 and a blowing control system including an in-furnace state estimation device 1 .
  • the refining facility 2 includes a converter 100, a lance 102 and a duct 104.
  • a lance 102 is placed above the molten metal 101 in the converter 100 .
  • High-pressure oxygen is jetted from the tip of the lance 102 toward the molten metal 101 below.
  • Impurities in the molten metal 101 are oxidized by this high-pressure oxygen and incorporated into the slag 103 (refining process).
  • the duct 104 is flue equipment for flue gas, and is installed in the upper part of the converter 100 .
  • An exhaust gas detector 105 is arranged inside the duct 104 .
  • the flue gas detection unit 105 detects the flow rate and component concentrations (for example, concentrations of CO, CO 2 , O 2 , N 2 , Ar, etc.) of the flue gas discharged along with the refining process.
  • the exhaust gas detector 105 measures the flow rate of the exhaust gas in the duct 104 based on the differential pressure across the venturi tube provided in the duct 104, for example. Further, the exhaust gas detection unit 105 measures the concentration [%] of each component in the exhaust gas as the exhaust gas measurement.
  • the flow rate and component concentration of the exhaust gas are measured, for example, at intervals of several seconds.
  • a signal indicating the detection result of the exhaust gas detection unit 105 is sent to the control terminal 10 .
  • a stirring gas is blown into the molten metal 101 in the converter 100 through the ventilation holes 106 formed in the bottom of the converter 100 .
  • the stirring gas is an inert gas such as Ar.
  • the blown stirring gas stirs the molten metal 101 and accelerates the reaction between the high-pressure oxygen and the molten metal 101 .
  • a flow meter 107 measures the flow rate of the stirring gas blown into the converter 100 .
  • the temperature and component concentration of the molten metal 101 are analyzed immediately before the start of blowing and after blowing.
  • the temperature and component concentration of the molten metal 101 are measured once or multiple times during blowing, and based on the measured temperature and component concentration, the supply amount (oxygen supply amount) and speed (oxygen transfer speed) of high pressure oxygen and The flow rate of the stirring gas (stirring gas flow rate) and the like are determined.
  • the blowing control system includes a control terminal 10, a display device 20, and an in-core state estimation device 1 as main components.
  • the control terminal 10 may be configured by an information processing device such as a personal computer or workstation.
  • the control terminal 10 controls the oxygen supply amount, acid supply rate and stirring gas flow rate so that the temperature and component concentration of the molten metal 101 are within the desired range, Collect value data.
  • the display device 20 may be configured by, for example, a liquid crystal display (Liquid Crystal Display) or a CRT (Cathode Ray Tube) display.
  • the display device 20 may display the calculation results and the like output from the in-core state estimation device 1 .
  • the in-furnace state estimation device 1 is a device that estimates the temperature and component concentration of the molten metal 101 being processed in the refining equipment 2 and the component concentration of the slag 103 .
  • the in-core state estimation device 1 is configured by an information processing device such as a personal computer or a work station.
  • the in-core state estimation device 1 includes an input unit 11 , a database 12 , a model parameter calculation unit 13 , a model determination unit 14 , an in-core state calculation unit 15 and an output unit 16 .
  • the input unit 11 is an input interface for inputting performance information (performance data), etc., which are various measurement results related to the refining equipment 2 .
  • the input unit 11 may be, for example, at least one of a keyboard, mouse, pointing device, data receiving device, graphical user interface (GUI), and the like.
  • GUI graphical user interface
  • the input unit 11 receives performance information, parameter setting values, etc. from the outside, writes the information into the database 12 and transmits the information to the in-core state calculation unit 15 .
  • Performance information is input to the input unit 11 from the control terminal 10 .
  • the performance information includes information on the flow rate and component concentration of the exhaust gas measured by the exhaust gas detection unit 105, information on the oxygen supply amount and oxygen supply rate, information on the stirring gas flow rate, and information on the amount of raw material (main raw material, auxiliary raw material) input. , the temperature and component concentration of the molten metal 101, the component concentration of the slag 103, and the like. These pieces of information correspond to items 1 to M in the performance information shown in FIG. 2, which will be described later.
  • the input unit 11 may be capable of manual data input (manual input) by an operator of the refining equipment 2, for example. Parameter settings of a model formula (hereinafter also simply referred to as "model”) can be entered manually. In this embodiment, the input unit 11 also receives refining processing conditions and manipulated variable information, which will be described later. Further, the input unit 11 may acquire performance information and the like before the start of the refining process, during the process, or after the end of the process.
  • the database 12 stores model information on the blowing reaction in the refining equipment 2, performance information on the refining process, and calculation results of the in-furnace state estimation device 1.
  • the database 12 is composed of a storage device such as a memory and a hard disk drive. The storage device may also store computer programs.
  • the database 12 stores model formulas and parameters of the model formulas (hereinafter referred to as "model parameters") as model information relating to the blowing reaction.
  • the model parameters are calculated by the model parameter calculator 13 .
  • the database 12 may store various kinds of information input to the input unit 11 and calculation/analysis results of actual blowing calculated by the in-furnace state calculation unit 15 .
  • FIG. 2 is a diagram showing a configuration example of the database 12.
  • the database 12 stores the model parameters, which are the conditions, performance information, and calculation results in N times (N charges) of refining processes, in association with charge identification numbers.
  • N is an integer of 2 or more, for example.
  • the leftmost column indicates the identification number of the charge.
  • the database 12 stores performance information and model parameters in the past N-1 refining processes.
  • the model determining unit 14 determines model parameters as described later, the information on the past N-1 refining processes stored in the database 12 is used as a candidate.
  • the performance information and the calculation results in the N-th refining process are added to the database 12 (see the thick-framed portion in FIG. 2). Thereafter, in the N+1th refining process, when the model determination unit 14 determines the model parameters, the information on the past N refining processes stored in the database 12 is used as a candidate.
  • the model parameter calculation unit 13, the model determination unit 14, and the in-core state calculation unit 15 are composed of an arithmetic processing unit such as a CPU, for example.
  • the model parameter calculation unit 13, the model determination unit 14, and the in-core state calculation unit 15 may be realized, for example, by reading and executing a computer program by an arithmetic processing unit.
  • the model parameter calculation unit 13, the model determination unit 14, and the in-core state calculation unit 15 may have dedicated arithmetic units or arithmetic circuits.
  • the model parameter calculation unit 13 calculates the model parameters of the model related to the blowing reaction so that the balance error is minimized based on the material balance and heat balance in the furnace, and stores them in the database 12 . After one refining process is completed, the model parameter calculation unit 13 calculates the mass balance and heat balance using performance information that is the result of the refining process.
  • the material balance calculation is to calculate the input amount of each component into the converter 100 and the discharge amount of each component from the converter 100.
  • the input amount of each component is calculated from the main raw material and auxiliary raw material input amounts to the converter 100, the oxygen supplied from the lance 102, and the amount of air entrained from outside the converter 100.
  • the emission amount of each component is calculated from the exhaust gas flow rate and the exhaust gas component concentration.
  • the heat balance calculation is to calculate the amount of heat input and the amount of heat exhausted in the furnace of the converter 100.
  • the amount of heat input is calculated from the sensible heat of the main raw material inserted into the converter 100, the heat of reaction due to the reaction occurring in the furnace, the heat of dissolution of the auxiliary raw material fed into the converter 100, and the like.
  • the amount of exhaust heat is calculated from heat radiation from the surface of the furnace body, radiant heat from the furnace throat, heat removal by stirring gas, slag 103 discharged outside the furnace, sensible heat of the exhaust gas, and the like.
  • the model determination unit 14 acquires past model parameters stored in the database 12.
  • the model determination unit 14 determines model parameters to be used by the in-core state calculation unit 15 using past model parameters, and transmits the model parameters to the in-core state calculation unit 15 .
  • the in-furnace state calculation unit 15 calculates the temperature and component concentration of the molten metal 101 and the component concentration of the slag 103 based on the model parameters determined by the model determination unit 14, the performance information and parameter setting values collected by the input unit 11. Calculate (estimate) the state quantity in the converter 100 including The estimated state quantity in the converter 100 is transmitted to the output unit 16 .
  • the output unit 16 transmits the state quantity inside the converter 100 calculated by the in-core state estimation device 1 to the control terminal 10 . In the refining process, various manipulated variables are determined and operating conditions are changed based on the calculation results output from the in-core state estimation device 1 .
  • the output unit 16 also has a function of transmitting information calculated by the in-core state estimation device 1 to the display device 20, and can display the calculation results output from the in-core state estimation device 1. is.
  • the in-furnace state estimating apparatus 1 having such a configuration performs the process of the in-furnace state estimating method described below to obtain the temperature and component concentration in the molten metal 101 and the conversion including the component concentration in the slag 103 and the like.
  • the state quantity in the furnace 100 is estimated with high accuracy.
  • the operation of the in-core state estimating device 1 when executing the in-core state estimating method will be described below with reference to the flowchart shown in FIG.
  • FIG. 3 is a flow chart showing processing of an in-core state estimation method according to an embodiment of the present disclosure.
  • the flowchart shown in FIG. 3 starts at an arbitrary timing before the refining process starts. That is, at an arbitrary timing before the refining process is started, the in-furnace state estimation process proceeds to the process of step S1.
  • the input unit 11 acquires the conditions for the refining process.
  • the conditions of the refining process include the refining mode, the planned amount of auxiliary material to be added, the target values of the component concentrations and temperatures of the molten metal 101 and the slag 103, the number of times of processing, the date and time of processing, and the equipment including the furnace, lance, and measuring equipment. Including the number of times of use.
  • the input unit 11 transmits the acquired refining conditions to the database 12 and the in-core state calculation unit 15 . Thereby, the process of step S1 is completed, and the in-core state estimation process proceeds to the process of step S2.
  • Step S1 corresponds to part of the "input step".
  • the data input in step S1 is used in the processing of the model determination unit 14.
  • step S2 the model determining unit 14 uses the past model parameters stored in the database 12 to determine the model parameters to be used by the in-core state calculating unit 15 based on the conditions of the refining process.
  • Step S2 corresponds to the "model determination step". Specifically, the model parameters determined in the process of step S2 are obtained by calculation or selection based on model parameters corresponding to past refining processes already stored in the database 12 . As described above, in the N-th refining process, for example, the model determining unit 14 determines the model parameters using the information on the past N-1 refining processes stored in the database 12 .
  • model parameters or refining process condition data for the past N-1 times are not complete, such as when it takes time to acquire the refining process results, the necessary model parameter or refining process condition data is complete.
  • the model parameters may be determined by extracting the actual performance information.
  • the N-th refining process that is, the refining process currently being executed may be referred to as the refining process of the target charge.
  • the model determination unit 14 extracts, for example, model parameters stored in the database 12 whose refining process conditions are similar to those of the target charge, and determines by averaging the extracted model parameters.
  • the model determining unit 14 may extract only the model parameters in the latest predetermined number of charges, that is, exclude old model parameters from the extraction target, and perform averaging.
  • the degree of similarity (Ds) between the conditions in the refining process of the target charge and the past performance can be evaluated, for example, by calculating the Euclidean distance as shown in the following formula (1).
  • k is the number of conditions for refining treatment.
  • CA k indicates conditions in past performance.
  • CP k indicates the conditions in the refining process of the target charge.
  • Gk is a parameter for weighting the conditions of each refining process.
  • Refining conditions include, for example, the date and time of refining, the weight of charged hot metal, the weight of charged scrap, the temperature of hot metal, the concentration of components such as C, Si, Mn, and P in the hot metal, and the size of the refining furnace and top-blowing lance. The number of times of use and the like can be mentioned.
  • the molten metal temperature after treatment in the refining treatment performed immediately before and the elapsed time after treatment correspond to items 1 to L in the scouring treatment conditions in FIG.
  • the degree of similarity only results that match the shape of the refining furnace used, the shape of the top-blowing lance, the shape of the bottom-blowing nozzle, etc. may be targeted.
  • the similarity is not limited to the Euclidean distance shown in Equation (1), but can also be evaluated by a method for evaluating the distance between k-dimensional vectors such as the city block distance, Minkowski distance, Mahalanobis distance, and cosine similarity. .
  • a high degree of similarity is synonymous with a short distance between the calculated k-dimensional vectors.
  • the results having a calculated similarity higher than a set threshold value may be extracted, or an arbitrary number of past results having a high similarity may be extracted.
  • the difference between the conditions of the calculation target process and the conditions of the past results is calculated for each item of the condition k of the refining process, and the results with k differences smaller than the set threshold are extracted. method is good.
  • the model determination unit 14 determines the model parameters stored in the database 12 and the conditions of the refining process including the number of times of refining process, the processing date and time, the number of times of use of the refining equipment including the furnace, the lance, and the measuring equipment. You can model the relationship. Then, the model determination unit 14 may calculate the optimum parameters by model calculation from the refining process condition input values of the target charge. The model determination unit 14 transmits the determined model parameters to the in-core state calculation unit 15 . Thereby, the process of step S2 is completed, and the in-core state estimation process proceeds to the process of step S3.
  • steps S3 and S4 is started at the timing when one refining process starts, and is repeatedly performed at an arbitrary cycle during the refining process.
  • the input unit 11 acquires the operation amount information of the refining process and the measurement information in the converter 100 .
  • the manipulated variable information is, for example, information on the manipulated variable such as the height of the lance 102, the oxygen feed rate, the stirring gas flow rate, the input amount of the auxiliary material, and the like.
  • the measurement information is, for example, measurement values such as the flow rate and component concentration of the exhaust gas.
  • the measured value is not limited to the measured value itself, and may also include the result after analysis (analysis value).
  • Step S3 corresponds to part of the "input step".
  • the data input in step S ⁇ b>3 is used in the processing of the in-core state calculator 15 .
  • step S4 the in-furnace state calculation unit 15 calculates the state quantity in the converter 100 using the model having the information acquired by the input unit 11 and the model parameters determined by the model determination unit 14 .
  • State quantities include, for example, the carbon concentration in the molten metal 101 and the Fe t O concentration in the slag 103 .
  • Step S4 corresponds to the "in-core state calculation step".
  • the carbon concentration in the molten metal 101 can be obtained, for example, by calculating the amount of carbon remaining in the converter 100.
  • the amount of carbon introduced into the converter 100 and the amount of carbon discharged out of the converter 100 can be expressed by the following equations (2) and (3), respectively.
  • the carbon concentration in the molten metal 101 can be calculated by assuming that the amount of carbon remaining in the converter 100 obtained by subtracting the carbon emission amount from the input carbon amount corresponds to the carbon amount in the molten metal 101 .
  • "%" and various flow rates represent "mass%" and flow rate unit.
  • C in [%] which is the amount of carbon introduced, is the concentration-converted value in the molten metal 101 of the sum of the amount of carbon in the main raw material and the amount of carbon in the introduced auxiliary raw material.
  • ⁇ pig [%] is the carbon concentration in charged hot metal.
  • ⁇ i Cscr [%] is the carbon concentration in the charged scrap (brand i).
  • ⁇ j Caux [%] is the carbon concentration in the input auxiliary material (brand j).
  • W pig [t] is charged hot metal weight.
  • W i scr [t] is the weight of the charged scrap (brand i).
  • W j aux [t] is the accumulated input weight of the input auxiliary material (brand j).
  • W charge [t] is the weight of molten metal charged into the converter 100 .
  • the carbon concentrations ( ⁇ i Cscr , ⁇ j Caux ) in the charged scrap brand i and the charged auxiliary raw material brand j are stored in the database 12, and the in-furnace state calculation unit 15 calculates the brand used in the target charge.
  • Get information about C out [%], which is the amount of carbon emitted, is the concentration conversion value in the molten metal 101 of the amount of carbon contained in the exhaust gas.
  • V CO OG [Nm 3 /t] and V CO2 OG [Nm 3 /t] are the integrated flow rates of CO and CO 2 in the exhaust gas up to the calculation time, respectively.
  • the Fe t O concentration in the slag 103 can be calculated by assuming that the amount obtained by subtracting the amount of oxygen discharged from the amount of input oxygen corresponds to the amount of oxygen remaining in the converter 100 .
  • the amount of oxygen introduced into the converter 100 and the amount of oxygen discharged out of the converter 100 can be expressed by the following equations (4) and (5), respectively.
  • the input oxygen amount O 2 in [Nm 3 /t] is the top-blown oxygen integrated amount VO2 blow [Nm 3 /t] from the lance 102, the oxygen integrated amount in the input auxiliary raw material, and the It is the sum of the accumulated amount of oxygen in the air drawn into the furnace from the outside.
  • ⁇ i Oscr [%] is the converted value of the oxygen content in the charged scrap (brand i).
  • ⁇ j Oaux [(Nm 3 /t)/t] is the converted value of the oxygen content in the input auxiliary material (brand j).
  • the oxygen content ( ⁇ i Oaux , ⁇ j Oaux ) in the charged scrap brand i and the charged auxiliary raw material brand j are stored in the database 12, and the in-furnace state calculation unit 15 calculates the brand name used in the target charge.
  • Get information about For ⁇ i Oscr [%] and W j aux [t] may include analytical or calculated values for the composition and weight of slag 103 carried over from the previous charge.
  • the amount of oxygen in the entrained air is can be calculated as
  • V bot It is assumed that the amount obtained by subtracting [Nm 3 /t] corresponds to N 2 and Ar in the entrained air.
  • O 2 out [Nm 3 /t], which is the amount of exhausted oxygen, is calculated from the amount of oxygen contained in the exhaust gas.
  • V O2 OG [Nm 3 /t] is the integrated flow rate of O 2 in the exhaust gas up to the calculation time.
  • V CO OG [Nm 3 /t] and V CO2 OG [Nm 3 /t] are the same as in formula (3).
  • the amount of oxygen remaining in the converter 100 is the amount obtained by subtracting the amount of discharged oxygen from the amount of input oxygen. Oxygen remaining in the converter 100 is used to oxidize metal impurities such as Si, Mn, and P in the molten metal 101 and to oxidize iron.
  • V 02 Si [Nm 3 /t] which is the amount of oxygen used for oxidizing Si in the molten metal 101, is represented by the following formula (6).
  • ⁇ pig Si [%] is the Si concentration in charged hot metal.
  • ⁇ i Siscr [%] is the Si concentration in the charged scrap (brand i).
  • ⁇ j Siaux [%] is the Si concentration in the input auxiliary material (brand j).
  • K Si is the oxidation reaction rate constant of Si.
  • the amount of oxygen used for oxidizing various metal impurities such as Mn and P in the molten metal 101 can be calculated in the same manner as in Equation (6).
  • the total amount of oxygen used for oxidizing various metal impurities such as Si, Mn, and P in the molten metal 101 is V O2 met [Nm 3 /t].
  • the amount of Fe t O in the slag 103 can be calculated by assuming that it corresponds to the amount obtained by subtracting V O2 met from the amount obtained by subtracting the amount of discharged oxygen from the amount of input oxygen.
  • step S5 the processes of steps S3 and S4 are completed (Yes in step S5), and the in-furnace state estimation process proceeds to the process of step S6. If one refining process has not been completed (No in step S5), the in-furnace state estimation process returns to steps S3 and S4.
  • step S6 the input unit 11 acquires the result of the refining process as performance information.
  • the results of the refining process include the temperature and component concentration of the molten metal 101, the component concentration of the slag 103, and the flow rate and component concentration of the exhaust gas.
  • the input unit 11 stores the acquired result of the refining process in the database 12 .
  • Step S6 corresponds to part of the "input step”.
  • the data input in step S6 is used in the processing of the model parameter calculator 13. FIG.
  • step S7 the model parameter calculation unit 13 calculates the model parameters of the model related to the blowing reaction so that the balance error is minimized based on the material balance and heat balance in the furnace, and stores them in the database 12.
  • Step S7 corresponds to a "model parameter calculation step".
  • the in-furnace state calculation unit 15 uses the model parameters determined by the model determination unit 14 to estimate the state quantities in the converter 100 in the refining process of the target charge.
  • the model parameter calculation unit 13 corrects the model parameters used by the in-core state calculation unit 15 using the result of the refining process (performance information) of the target charge. Then, the model parameter calculator 13 stores the more accurate model parameters after correction in the database 12 .
  • model parameters associated with the target charge and stored in the database 12 are not the model parameters of the model used for calculation (estimation) by the in-core state calculator 15 .
  • the model parameters stored in the database 12 in association with the target charge are model parameters calculated (corrected) by the model parameter calculator 13 based on the performance information of the refining process of the target charge.
  • the model parameter calculation unit 13 may calculate coefficients for correction as model parameters.
  • the coefficients for correction may include, for example, a correction coefficient A for the measured value of the flow rate of the exhaust gas and a correction coefficient B for the measured value of the component concentration of the exhaust gas.
  • the coefficients for correction are, for example, the correction coefficient ⁇ C for the measured value of the component concentration of the molten metal 101, the correction coefficient D for the measured value of the temperature of the molten metal 101, the constant E regarding the yield of the reaction in the furnace of the charged scrap, and the charged secondary It may include a constant F related to the yield of the in-furnace reaction of raw materials.
  • the coefficients for correction include the coefficient H for heat rise and heat absorption due to various reactions in the furnace, such as the oxidation reaction of the components in the molten metal 101, the reduction reaction of the components in the slag 103, and the melting of auxiliary raw materials. good. Further, the coefficient for correction may include a coefficient I for heat loss such as the sensible heat of the gas and slag 103 and the amount of heat radiation from the furnace throat and furnace body.
  • the model parameter calculator 13 may, for example, incorporate the above coefficients as variables of the evaluation function such as Equation (7), and obtain model parameters that minimize the evaluation function.
  • the model parameter calculator 13 minimizes the evaluation function, but an evaluation function that maximizes the appropriate model parameters may be used. That is, the model parameter calculator 13 may obtain model parameters that minimize or maximize the evaluation function.
  • C in is the integrated amount of carbon charged into the converter 100 for a specific period.
  • C out is the integrated amount of the amount of carbon emitted outside the converter 100 by the exhaust gas or the like in a specific period.
  • O 2 in is the amount of oxygen introduced into the converter 100 .
  • O 2 out is the amount of oxygen discharged outside the converter 100 due to discharge of exhaust gas and slag 103 .
  • V O2 met is the amount of oxygen used for oxidizing various metal impurities in the molten metal 101 such as Si, Mn and P.
  • ⁇ T is the change in the amount of heat in the converter 100, including the reaction heat generated by the reaction in the converter 100, heat removal by the exhaust gas and slag 103 etc.
  • T ini is the measured temperature of the melt 101 at the beginning of a particular time period in the refining process.
  • [C] V O2 FetO , and T fin are Fe t O calculated from the measured carbon amount in the molten metal 101 and the measured Fe t O amount in the slag 103 at the end of a specific period in the refining process, respectively.
  • ⁇ C 2 , ⁇ O 2 , and ⁇ T 2 are constants that can be set arbitrarily.
  • a to I and ⁇ C correspond to the first to K-th parameters in FIG.
  • the model parameters include coefficients or constant terms that correct at least one of the integrated amount and oxygen amount used in equation (7).
  • ⁇ R m is the reaction amount for various reactions m in the furnace, such as the oxidation reaction of the components in the molten metal 101, the reduction reaction of the components in the slag 103, and the melting of auxiliary raw materials.
  • ⁇ L n is the amount of heat loss for the heat loss path n in the molten metal 101, such as the sensible heat of gas and slag 103, and the amount of heat radiation from the furnace throat and furnace body.
  • the evaluation function J shown in Equation (7) is a weighted sum of the following three terms.
  • the first and second terms represent the mass balance error
  • the third term represents the heat balance error.
  • the first term is the square value of the difference between the amount of carbon remaining in the converter 100 obtained by subtracting the amount of carbon discharged from the amount of carbon input and the measured value of the amount of carbon in the molten metal 101 . When this term becomes 0, it indicates that the carbon balance is maintained within the converter 100 .
  • the second term is the amount of oxygen used for iron oxidation in the molten metal 101 calculated from the amount obtained by subtracting the amount of oxygen discharged and the amount of oxygen used for impurity metal oxidation from the amount of input oxygen and the amount of oxygen used for iron oxidation in the molten metal 101 calculated from the Fe t O measurement value in the slag 103 is the squared value of the difference between When this term becomes 0, it indicates that the oxygen balance in the converter 100 is maintained.
  • the third term is the difference between the measured value of the temperature change of the molten metal 101 from the start point to the end point of the specific period in the refining process and the calculated value of the temperature change of the molten metal 101 calculated from the reaction heat and heat removal in the converter 100. is the squared value of The fact that this term approaches 0 indicates that the heat balance in the converter 100 is maintained.
  • different periods may be set for each of the three terms.
  • a weighting factor ( ⁇ C 2 , ⁇ O 2 , ⁇ T 2 ) in the denominator of each term of the evaluation function J is set by the user, for example.
  • Various algorithms have been proposed for the nonlinear programming problem for minimizing the evaluation function J under constraints, and calculations for obtaining model parameters may be performed by known methods.
  • the model parameters calculated by the model parameter calculation unit 13 are stored in the database 12 and used for in-core state estimation processing in subsequent refining processes. As a result, the process of step S7 is completed, and the in-furnace state estimation process completes the process in the refining process.
  • the operation amount is determined, the refining operation is performed, and good molten steel is produced. .
  • the optimum flow rate and speed of top-blown oxygen, the height of the top-blown lance, the flow rate of bottom-blown gas, the amount and timing of feeding sub-materials such as lime and iron ore, the timing and blowing for sampling the molten metal is determined at least one of the timings for terminating the In this way, it is possible to realize a good molten steel production method based on the in-furnace state calculated by the above-described in-furnace state estimation method.
  • the in-furnace state estimating device 1, the in-furnace state estimating method, and the molten steel manufacturing method according to the present embodiment include terms representing the mass balance error and the heat balance error in the furnace due to the above-described configuration and processes.
  • After optimizing the model parameters based on the evaluation function they are stored in the database 12 .
  • the estimation accuracy of the temperature and component concentration of the molten metal 101 and the component concentration of the slag 103 can be improved. can be improved.
  • the types of model parameters to be determined, the number of model parameters, and the form of the evaluation function to be minimized are not limited to those mentioned in the above embodiment, and the form capable of minimizing the mass balance error and heat balance error in the furnace. If so, it will have the same effect.
  • the model is not limited to those exemplified by formulas (2) to (6) in the above embodiment, and the molten metal temperature estimation model, scrap melting model, auxiliary material melting/yield model, decarburization efficiency model, A dephosphorization model, a production reduction model of Fe t O, and the like may be used.
  • the material balance and heat balance in the furnace can also be calculated in the secondary refining equipment or the preliminary treatment equipment. It is effective for model parameter calculation calculated based on

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Abstract

L'invention concerne un dispositif d'inférence d'état intra-four (1) comprenant : une unité d'entrée (11) vers laquelle des informations d'enregistrement passé et une condition de traitement de raffinage sont entrées ; une unité de détermination de modèle (14) pour, en utilisant un paramètre de modèle passé acquis à partir d'une base de données dans laquelle un paramètre de modèle d'un modèle concernant une réaction de soufflage, des informations d'enregistrement passé et une condition de traitement de raffinage sont stockées, déterminer un paramètre de modèle dans un processus de raffinage pour une charge cible ; et une unité de calcul d'état intra-four (15) pour, en utilisant le paramètre de modèle déterminé, calculer une quantité d'état intra-four qui comprend la température et la concentration en composants du métal fondu et la concentration en composants d'une billette ; et une unité de calcul de paramètre de modèle (13) pour, en utilisant les informations d'enregistrement passé comprenant un résultat du processus de raffinage de la charge cible, calculer un paramètre de modèle dans le processus de raffinage pour la charge cible sur la base d'une fonction d'évaluation qui comprend des termes indiquant une erreur de bilan matière et une erreur de bilan thermique dans un four depuis un point de départ jusqu'à un point final d'une période spécifique du processus de raffinage.
PCT/JP2022/042138 2021-11-29 2022-11-11 Dispositif d'inférence d'état intra-four, procédé d'inférence d'état intra-four et procédé de fabrication d'acier fondu WO2023095647A1 (fr)

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KR1020247015910A KR20240090437A (ko) 2021-11-29 2022-11-11 노내 상태 추정 장치, 노내 상태 추정 방법 및 용강 제조 방법
EP22898431.6A EP4400607A1 (fr) 2021-11-29 2022-11-11 Dispositif d'inférence d'état intra-four, procédé d'inférence d'état intra-four et procédé de fabrication d'acier fondu
JP2023505466A JP7392897B2 (ja) 2021-11-29 2022-11-11 炉内状態推定装置、炉内状態推定方法及び溶鋼製造方法

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JP2014201770A (ja) * 2013-04-02 2014-10-27 株式会社神戸製鋼所 転炉の予測モデルの推定装置および推定方法
JP2017089001A (ja) * 2015-11-02 2017-05-25 Ｊｆｅスチール株式会社 溶湯状況推定装置、溶湯状況推定方法、及び溶湯の製造方法
WO2019181562A1 (fr) * 2018-03-19 2019-09-26 Ｊｆｅスチール株式会社 Dispositif d'estimation de composants de métal en fusion, procédé d'estimation de composants de métal en fusion et procédé de production de métal en fusion

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JP2004360044A (ja) 2003-06-06 2004-12-24 Nippon Steel Corp 溶鋼温度推定計算装置及び溶鋼温度推定計算方法
JP4093934B2 (ja) 2003-07-16 2008-06-04 株式会社神戸製鋼所 モデルパラメータ決定方法及びそのプログラム，モデル予測方法及びそのプログラム
KR102214879B1 (ko) * 2016-04-13 2021-02-09 제이에프이 스틸 가부시키가이샤 슬래그의 분석 방법 및 용융 철의 정련 방법
CN112347530B (zh) * 2020-09-27 2024-05-03 安徽工业大学 一种炼钢转炉出钢时间的计算方法

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JP2014201770A (ja) * 2013-04-02 2014-10-27 株式会社神戸製鋼所 転炉の予測モデルの推定装置および推定方法
JP2017089001A (ja) * 2015-11-02 2017-05-25 Ｊｆｅスチール株式会社 溶湯状況推定装置、溶湯状況推定方法、及び溶湯の製造方法
WO2019181562A1 (fr) * 2018-03-19 2019-09-26 Ｊｆｅスチール株式会社 Dispositif d'estimation de composants de métal en fusion, procédé d'estimation de composants de métal en fusion et procédé de production de métal en fusion

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