A molten steel carbon content prediction method for converter blowing decarburization critical point based on online dynamic detection model

Abstract

A kind of steel liquid carbon content prediction method of converter blowing decarburization critical point based on online dynamic detection model, for each current heat, at decarburization critical point, based on current oxygen lance flow, and according to the linear fitting equation of oxygen lance flow and steel liquid carbon content established by linear fitting analysis, the prediction of steel liquid carbon content of decarburization critical point of the heat is completed.The steel liquid carbon content prediction method of converter blowing decarburization critical point based on online dynamic detection model of the present application uses the calculation information, measurement information and model of adjacent historical heats to carry out statistical regression analysis, obtains the relationship between the carbon content of decarburization critical point and the detection value, and is applied to the prediction and determination of the critical point carbon content of the current heat, wherein the model is subjected to deviation correction treatment;Through the technical implementation of the present application, investment and maintenance cost are saved;Provide important information for end point control.

Description

Technical Field

[0001] This invention belongs to the field of converter steelmaking process control, specifically relating to a method for predicting the carbon content of molten steel at the critical point of decarburization in converter blowing based on an online dynamic detection model. Background Technology

[0002] Existing methods for determining converter carbon content do not focus on predicting the carbon content at the decarburization critical point. Current techniques typically employ an integral method, integrating data from flue gas composition and flow rate measurements to obtain the cumulative decarburization amount. Subtracting this cumulative decarburization amount from the initial carbon content yields the current remaining carbon content. This method suffers from several drawbacks: initial hot metal carbon content analysis errors and flue gas flow rate measurement errors can negatively impact the calculated steel carbon content. Furthermore, these errors increase with decreasing carbon content, rendering the method less applicable. Existing research and literature only describe the characteristic changes in flue gas composition during the later stages of converter blowing, failing to establish a direct correlation with the specific characteristics of flue gas composition changes at the decarburization critical point. Predicting the carbon content at the decarburization critical point is crucial for predicting the final carbon content at the blowing endpoint. The neglect of this prediction in existing techniques hinders the stability and accuracy of flue gas-based endpoint prediction.

[0003] The utility model application with application number CN201220612261.5 discloses "an online sampling device for analyzing the composition of furnace gas in front of a steelmaking converter", which includes a corundum sampling tube and a stainless steel sampling tube. The corundum sampling tube has a 45° bevel at the end facing the flow, and a portion of the tube with the end is inserted into the flue gas duct before the first-stage Venturi tube of the converter, while the other portion has a short section on its outer side. The stainless steel sampling tube is equipped with a water-cooled outer sleeve and a water-cooled inner sleeve. The water-cooled inner sleeve has an inlet pipe, and the lower part of the water-cooled outer sleeve has a drain pipe. The end of the stainless steel sampling tube is connected to a cyclone separator dust collector, the outlet of which is connected to two switchable metal sintering filters. The outlet of the metal sintering filters is connected to a membrane suction pump, and the outlet of the membrane suction pump is equipped with a T-connector. One end of the T-connector is equipped with a vent valve V12, and the other end is connected to two parallel low-temperature water washing tanks. The outlet pipe of the low-temperature water washing tank is connected to a paper filter, which is connected to an online gas analyzer.

[0004] The invention application with application number CN201310399078.0 discloses "a method for online prediction of carbon content in high-carbon steel during converter smelting". The method first determines the amount of carbon charged into the converter; secondly, it determines the amount of decarburization online; and finally, it continuously determines the carbon content in the molten pool. A dynamic control model based on furnace gas analysis technology is established, which can obtain real-time information on the carbon content during the rapid decarburization period in a high-carbon environment in the molten pool. This method can achieve a carbon removal success rate of over 90% in a single pass of high-carbon steel blowing, significantly reducing the need for reblowing, resulting in purer molten steel and reduced iron loss. Compared with auxiliary lances, the furnace gas analysis technology is less expensive and shortens the smelting cycle by 3-5 minutes.

[0005] The invention application with application number CN201710235590.X discloses "a one-button automatic steelmaking method for converters without auxiliary lances or furnace gas detection". It calculates the equilibrium state of molten steel, slag and furnace gas by establishing a thermodynamic kinetic energy curve model system related to molten steel, slag and furnace gas; by collecting real-time information on lance position, oxygen pressure, oxygen flow rate and changes in auxiliary materials fed into the furnace, it calculates and displays the chemical composition of molten steel and slag in the converter and the predicted temperature of molten steel every 3-5 seconds, automatically controls the lance position and feeding, controls splashing and slag overflow, and can monitor and control the endpoints S and P to realize converter steelmaking. Summary of the Invention

[0006] To address the above problems, this invention provides a method for predicting the carbon content of molten steel at the critical point of decarburization in converter blowing based on an online dynamic detection model. The specific technical solution is as follows:

[0007] A method for predicting the carbon content of molten steel at the critical point of decarburization in converter blowing based on an online dynamic detection model, characterized in that:

[0008] For each current heat, the carbon content of the molten steel at the decarburization critical point is predicted based on the current oxygen lance flow rate and the linear fitting equation between the oxygen lance flow rate and the carbon content of the molten steel, established according to linear fitting analysis.

[0009] According to the present invention, a method for predicting the carbon content of molten steel at the critical point of decarburization in converter blowing is based on an online dynamic detection model, characterized in that:

[0010] The sample values ​​used to provide the sample space for linear fitting analysis are determined based on the statistics of the corresponding values ​​of a set number of furnaces prior to the current furnace.

[0011] The set number of furnaces preceding the current furnace cycle is updated iteratively with each furnace cycle iteration.

[0012] According to the present invention, a method for predicting the carbon content of molten steel at the critical point of decarburization in converter blowing is based on an online dynamic detection model, characterized in that:

[0013] The sample values ​​provided for the sample space in the linear fitting analysis include: the oxygen lance flow rate and the carbon content of the molten steel at the decarburization critical point for each heat.

[0014] The oxygen lance flow rate is determined by detection.

[0015] The carbon content of the molten steel at the decarburization critical point is derived from the carbon content of the molten steel at the end of converter blowing, combined with the carbon element mass balance equation.

[0016] According to the present invention, a method for predicting the carbon content of molten steel at the critical point of decarburization in converter blowing is based on an online dynamic detection model, characterized in that:

[0017] The aforementioned "the carbon content of the molten steel at the decarburization critical point is derived from the carbon content of the molten steel at the end of converter blowing, combined with the carbon element mass balance equation" specifically means:

[0018]

[0019] in,

[0020] C C,tp Carbon content at the estimated decarbonization critical point based on flue gas;

[0021] △m c Decarburization amount from the decarburization critical point to the blowing end point, unit: kg;

[0022] m stl : Weight of molten steel tapped, unit: kg;

[0023] △m Fe : Iron oxygen consumption from the decarburization critical point to the end of the blowing process, unit: kg;

[0024] C C,end : Carbon content of molten steel at the end of the blowing process.

[0025] According to the present invention, a method for predicting the carbon content of molten steel at the critical point of decarburization in converter blowing is based on an online dynamic detection model, characterized in that:

[0026] Where △m c The calculation is based on the established flue gas flow calculation model.

[0027] According to the present invention, a method for predicting the carbon content of molten steel at the critical point of decarburization in converter blowing is based on an online dynamic detection model, characterized in that:

[0028] The flue gas flow calculation model is based on flue gas detection and the deviation correction for flue gas detection is established based on the mass balance of carbon elements during the blowing process.

[0029] According to the present invention, a method for predicting the carbon content of molten steel at the critical point of decarburization in converter blowing is based on an online dynamic detection model, characterized in that:

[0030] The specific model for calculating flue gas flow rate is as follows:

[0031] △m c =f q w c ,

[0032] in,

[0033] △m c Decarbonization amount from the decarbonization critical point to the decarbonization endpoint, unit: kg;

[0034] f q Correction factor;

[0035] w c Cumulative decarbonization from the decarbonization critical point to the decarbonization endpoint, calculated based on flue gas flow rate, in kg.

[0036] According to the present invention, a method for predicting the carbon content of molten steel at the critical point of decarburization in converter blowing is based on an online dynamic detection model, characterized in that:

[0037] The w mentioned c Specifically, it is determined based on the following:

[0038]

[0039] in,

[0040] P 0 Standard atmosphere (Pa)

[0041] M C Molar mass of carbon, unit: kg / mol;

[0042] R: gas constant, unit: J / mol / K;

[0043] T 0 Standard temperature, unit: K;

[0044] t p : Critical point of decarburization in converter blowing, unit: seconds;

[0045] te : End time of converter blowing, unit: s;

[0046] q off Flue gas flow rate, unit: m 3 / s;

[0047] C co CO content, mole fraction;

[0048] CO2 content, mole fraction.

[0049] According to the present invention, a method for predicting the carbon content of molten steel at the critical point of decarburization in converter blowing is based on an online dynamic detection model, characterized in that:

[0050] The f q Specifically, it is determined based on the following:

[0051]

[0052] in,

[0053] l: Furnace number;

[0054] N: The set number of furnace cycles;

[0055] m' C Change in total carbon content during the blowing process, unit: kg;

[0056] The cumulative amount of decarburization from the start of converter blowing to the end of decarburization, calculated based on flue gas flow rate, in kg.

[0057] According to the present invention, a method for predicting the carbon content of molten steel at the critical point of decarburization in converter blowing is based on an online dynamic detection model, characterized in that:

[0058] The m' mentioned C It is determined as follows:

[0059] m' C =m hot C C,hot +m scr C C,scr -m stl C stl ,

[0060] in,

[0061] m hot : Weight of molten iron, unit: kg;

[0062] C C,hot The mass content of carbon in molten iron;

[0063] m scr Weight of scrap steel added to the converter, unit: kg;

[0064] C C,scr The mass content of carbon in the scrap steel added to the converter;

[0065] m stl : Weight of molten steel tapped from the converter, unit: kg;

[0066] C C,stl The mass content of carbon in the molten steel tapped from the converter.

[0067] According to the present invention, a method for predicting the carbon content of molten steel at the critical point of decarburization in converter blowing is based on an online dynamic detection model, characterized in that:

[0068] The aforementioned △m Fe It is determined as follows:

[0069]

[0070] in,

[0071] M Fe Molar mass of iron, unit: kg / mol;

[0072] α: The molar ratio of iron oxidation to oxygen;

[0073] △V O2 Oxygen content from the decarburization critical point to the end of the blowing process, unit: m 3 ;

[0074] △m c Decarburization amount from the decarburization critical point to the blowing end point, unit: kg;

[0075] P 0 Standard atmosphere (Pa)

[0076] R: gas constant, unit: J / mol / K;

[0077] T 0 Standard temperature, unit: K;

[0078] M c Molar mass of carbon atom, unit: kg / mol.

[0079] According to the present invention, a method for predicting the carbon content of molten steel at the critical point of decarburization in converter blowing is based on an online dynamic detection model, characterized in that:

[0080] The start time of the flue gas flow calculation model is determined by subtracting the lag time of flue gas detection and analysis from the actual time.

[0081] The end time of flue gas detection is determined by adding the lag time of flue gas detection and analysis to the actual stop time.

[0082] This invention discloses a method for predicting the carbon content of molten steel at the decarburization critical point in converter blowing based on an online dynamic detection model. Utilizing calculation, measurement, and model-determined information from nearby historical heats, statistical regression analysis is performed to derive the relationship between the carbon content at the decarburization critical point and the detected value. This relationship is then applied to predict the carbon content at the critical point in the current heat. The model incorporates bias correction processing. This technology typically does not impose limitations on the lag time of flue gas analysis; therefore, existing infrared flue gas analysis from dust removal systems can be used, eliminating the need for additional gas detection equipment and saving investment and maintenance costs. The information obtained using this technology provides crucial information for endpoint control. For traditional secondary lance control methods, the critical point determined by this technology provides an important reference for improving the determination of the secondary lance's exit time. Furthermore, the determined carbon content can be compared with the secondary lance's detected value, which is of significant importance and value in improving the accuracy of secondary lance detection and endpoint control. Attached Figure Description

[0083] Figure 1 This is a schematic diagram showing the relationship between the carbon content of molten steel and the oxygen lance flow rate at the decarburization critical point of the present invention. Detailed Implementation

[0084] The following is a detailed description of a method for predicting the carbon content of molten steel at the critical point of decarburization in converter blowing, based on an online dynamic detection model, according to the accompanying drawings and specific embodiments of the present invention.

[0085] A method for predicting the carbon content of molten steel at the critical point of decarburization in converter blowing based on an online dynamic detection model.

[0086] For each current heat, the carbon content of the molten steel at the decarburization critical point is predicted based on the current oxygen lance flow rate and the linear fitting equation between the oxygen lance flow rate and the carbon content of the molten steel, established according to linear fitting analysis.

[0087] in,

[0088] The sample values ​​used to provide the sample space for linear fitting analysis are determined based on the statistics of the corresponding values ​​of a set number of furnaces prior to the current furnace.

[0089] The set number of furnaces preceding the current furnace cycle is updated iteratively with each furnace cycle iteration.

[0090] in,

[0091] The sample values ​​provided for the sample space in the linear fitting analysis include: the oxygen lance flow rate and the carbon content of the molten steel at the decarburization critical point for each heat.

[0092] The oxygen lance flow rate is determined by detection.

[0093] The carbon content of the molten steel at the decarburization critical point is derived from the carbon content of the molten steel at the end of converter blowing, combined with the carbon element mass balance equation.

[0094] in,

[0095] The aforementioned "the carbon content of the molten steel at the decarburization critical point is derived from the carbon content of the molten steel at the end of converter blowing, combined with the carbon element mass balance equation" specifically means:

[0096]

[0097] in,

[0098] C C,tp Carbon content at the estimated decarbonization critical point based on flue gas;

[0099] △m c Decarburization amount from the decarburization critical point to the blowing end point, unit: kg;

[0100] m stl : Weight of molten steel tapped, unit: kg;

[0101] △m Fe : Iron oxygen consumption from the decarburization critical point to the end of the blowing process, unit: kg;

[0102] C C,end : Carbon content of molten steel at the end of the blowing process.

[0103] in,

[0104] Where △m c The calculation is based on the established flue gas flow calculation model.

[0105] in,

[0106] The flue gas flow calculation model is based on flue gas detection and the deviation correction for flue gas detection is established based on the mass balance of carbon elements during the blowing process.

[0107] in,

[0108] The specific model for calculating flue gas flow rate is as follows:

[0109] △m c =f q w c ,

[0110] in,

[0111] △m c Decarbonization amount from the decarbonization critical point to the decarbonization endpoint, unit: kg;

[0112] f q Correction factor;

[0113] w c Cumulative decarbonization from the decarbonization critical point to the decarbonization endpoint, calculated based on flue gas flow rate, in kg.

[0114] in,

[0115] The w mentioned c Specifically, it is determined based on the following:

[0116]

[0117] in,

[0118] P 0 Standard atmosphere (Pa)

[0119] M C Molar mass of carbon, unit: kg / mol;

[0120] R: gas constant, unit: J / mol / K;

[0121] T 0 Standard temperature, unit: K;

[0122] t p : Critical point of decarburization in converter blowing, unit: seconds;

[0123] te : End time of converter blowing, unit: s;

[0124] q off Flue gas flow rate, unit: m 3 / s;

[0125] C co CO content, mole fraction;

[0126] CO2 content, mole fraction.

[0127] in,

[0128] The f q Specifically, it is determined based on the following:

[0129]

[0130] in,

[0131] l: Furnace number;

[0132] N: The set number of furnace cycles;

[0133] m' C Change in total carbon content during the blowing process, unit: kg;

[0134] The cumulative amount of decarburization from the start of converter blowing to the end of decarburization, calculated based on flue gas flow rate, in kg.

[0135] in,

[0136] The m' mentioned C It is determined as follows:

[0137] m' C =m hot C C,hot +m scr C C,scr -m stl C stl ,

[0138] in,

[0139] m hot : Weight of molten iron, unit: kg;

[0140] C C,hot The mass content of carbon in molten iron;

[0141] m scr Weight of scrap steel added to the converter, unit: kg;

[0142] C C,scr The mass content of carbon in the scrap steel added to the converter;

[0143] m stl : Weight of molten steel tapped from the converter, unit: kg;

[0144] C C,stl The mass content of carbon in the molten steel tapped from the converter.

[0145] in,

[0146] The aforementioned △m Fe It is determined as follows:

[0147]

[0148] in,

[0149] M Fe Molar mass of iron, unit: kg / mol;

[0150] α: The molar ratio of iron oxidation to oxygen;

[0151] △V O2 Oxygen content from the decarburization critical point to the end of the blowing process, unit: m 3 ;

[0152] △mc Decarburization amount from the decarburization critical point to the blowing end point, unit: kg;

[0153] P 0 Standard atmosphere (Pa)

[0154] R: gas constant, unit: J / mol / K;

[0155] T 0 Standard temperature, unit: K;

[0156] M c Molar mass of carbon atom, unit: kg / mol.

[0157] in,

[0158] The start time of the flue gas flow calculation model is determined by subtracting the lag time of flue gas detection and analysis from the actual time.

[0159] The end time of flue gas detection is determined by adding the lag time of flue gas detection and analysis to the actual stop time.

[0160] Working principle, process and implementation examples

[0161] 1.1 Correction method for converter flue gas detection flow rate

[0162] The following relationship exists between flue gas flow rate, flue gas composition, and the decarburization rate during the converter blowing process:

[0163]

[0164] In the formula, Decarbonization rate (kg / s); P 0 Standard atmospheric pressure (Pa); M C R is the molar mass of carbon (kg / mol); R is the gas constant (8.314 J / mol / K); T 0 The standard state temperature is 273.15 K; q off Flue gas flow rate (m 3 / s); C CO C CO2 The CO and CO2 content (mole fraction) in the flue gas composition. Integrating yields the cumulative amount of carbon carried away by the flue gas:

[0165]

[0166] In the formula, Let be the cumulative amount of carbon carried away by the flue gas (kg); t0 be the start time of converter blowing (s); and t be the time of converter blowing (s). Using the difference scheme of the above formula, for the calculation of a single time step, we have the cumulative amount of carbon carried away by the flue gas:

[0167]

[0168] In the formula, the superscript i represents the time step (s) for the i-th Δt calculation. For the starting point of the calculation, It is 0.

[0169] Due to deviations in flue gas flow rate measurement, the decarburization rate and amount obtained using flow rate detection are difficult to utilize. Therefore, based on carbon element mass balance calculations from historical blowing processes, a correction coefficient for the flue gas flow rate measurement is statistically derived and used as a calculation parameter for the current blowing process. This improves the reliability of flue gas detection information and allows for further extrapolation of other process information. Considering the drift characteristics of flue gas flow rate detection values, only a sufficient number of adjacent heats (20-30 heats) are selected from historical heats to ensure consistency with the detection device's measurements. A sufficient number of samples also eliminates deviations in other measurement information used in the calculation, such as deviations in iron carbon content analysis and weight weighing.

[0170] The change in the total amount of carbon introduced into the raw materials for each heat of the converter is calculated as follows:

[0171] m' C =m hot C C,hot +m scr C C,scr -m stl C stl (4)

[0172] In the formula, m' C The change in total carbon content during the blowing process (kg); m hot The weight of molten iron (kg); C C,hot The mass content of carbon in molten iron; m scr Add scrap steel (kg) to the converter (pig iron is considered together with the scrap steel); C C,scr The mass content of carbon in the scrap steel added to the converter; m stl The weight (kg) of molten steel tapped from the converter; C C,stl The carbon content of the molten steel tapped from the converter.

[0173] m' calculated using the historical furnace number of the nearest N furnaces C and From the data, we can derive the correction coefficient for the flue gas flow rate detection value, which is:

[0174]

[0175] In the formula, t e The time (s) is the end time of converter blowing; the subscript l is the furnace number.

[0176] 1.2 Determination method for carbon content at the decarbonization critical point

[0177] The carbon content at the decarburization critical point is not a fixed value but changes with varying operating conditions. Studies have shown a strong linear correlation between the critical carbon content and the oxygen lance flow rate, which can be used to predict the critical carbon content. This statistical relationship can be obtained through linear regression of results from multiple nearby furnace runs. To ensure consistency with the gradually changing conditions of the converter, fixed furnace run results can be set for statistical regression. When the latest usable furnace run results are stored in the data file, the oldest furnace run results are simultaneously deleted. This achieves online dynamic storage of furnace run data and learning from the latest results, which are then used for predicting the critical carbon content. The method for determining the critical carbon content written into the statistical regression data file is as follows.

[0178] When the decarburization critical point is determined, the integral calculation of the decarburization amount (kg) is started simultaneously until the blowing end:

[0179]

[0180] In the formula, t p Let be the time (s) at which the decarbonization critical point occurs. For the calculation of a single time step, using the difference scheme of the above equation, we have:

[0181]

[0182] In the formula, the superscript i represents the i-th calculation time step. For the starting point of the calculation, The value is 0. At the end of the blowing process, the carbon content at the estimated decarburization critical point based on the flue gas can be obtained:

[0183]

[0184] In the formula, m stl The weight of the molten steel tapped (kg); C C,end The carbon content analysis value of the molten steel at the end of the blowing process; △m Fe The oxygen consumption (kg) of iron from the decarburization critical point to the end of the blowing process is calculated as follows:

[0185]

[0186] In the formula, M Fe α is the molar mass of iron (kg / mol); α is the molar ratio of iron oxidation to oxygen, which can be given empirically and ranges from [0.67, 1]; ΔV O2 Oxygen content (m) from the decarburization critical point to the end of the blowing process 3 ).

[0187] After each converter heat cycle calculation is completed, the updated learning file data is saved. At the start of a new heat cycle, linear regression analysis is performed using the learning file to derive the linear relationship between the carbon content at the decarburization critical point and the oxygen lance flow rate at the corresponding time.

[0188]

[0189] In the formula, A and B are regression coefficients, which will have different ranges for different converters. The regression equation is used as the formula for predicting the carbon content at the decarburization critical point of the current furnace batch.

[0190] Example

[0191] The prediction process established based on the above principles is as follows:

[0192] (a) The new batch of converter blowing begins, time t = 0;

[0193] (b) Calculation of correction coefficient for flue gas flow rate detection value;

[0194] Read the reference furnace learning file saved and m' C The correction factor for the flue gas flow rate detection value is calculated using the following formula:

[0195]

[0196] In the formula, The cumulative amount of carbon in the flue gas during one converter blowing process (kg); m' C The change in total carbon content during the converter blowing process (kg); N represents the number of historical furnace cycles recorded in the document.

[0197] (c) Regression analysis of the linear relationship between carbon content at the decarbonization critical point and oxygen lance flow rate at the corresponding time.

[0198] Learning file data C calculated and saved using multiple converter cycles C,tp and Linear regression analysis yielded the following relationship:

[0199]

[0200] In the formula, A and B are the coefficients of the regression equation; C C,tp The carbon content at the decarbonization critical point; The oxygen lance flow rate (Nm³) at the corresponding time. 3 / s).

[0201] like Figure 1 The figure shows the relationship between carbon content and oxygen lance flow rate at the decarbonization critical point. The straight line in the figure represents the linear relationship of regression.

[0202] (d) The time is denoted as t + Δt. Perform process model calculations within the time interval Δt(s);

[0203] By calculating the process over a time interval of Δt, continuous tracking of the process can be achieved, including changes in molten steel temperature, scrap steel melting, and changes in the composition of molten steel and slag.

[0204] (e) Perform cumulative calculation of carbon carried away by flue gas;

[0205] Calculate the cumulative decarburization over a time step of Δt:

[0206]

[0207] In the formula, the superscript i represents the i-th calculation time step; This represents the cumulative amount of carbon in the flue gas (kg). For the starting point of the calculation, =0; P 0 =1 standard atmosphere (Pa); M C R is the molar mass of carbon (kg / mol); R is the gas constant (8.314 J / mol / K); T 0 The standard state temperature is 273.15 K; q off Flue gas detection flow rate (Nm 3 / s); C CO , This refers to the CO and CO2 content in the flue gas.

[0208] Considering the lag time in flue gas analysis, the flue gas detection signal needs to be shifted forward during online real-time calculations to align with other detection signals. This means that the current calculation will only reflect a past moment in time. Since the computational load is not directly used for control but is stored as reference furnace data, it will not affect process control. However, to ensure data integrity, calculations need to continue for a period after the initial blowdown to allow for complete acquisition of the delayed flue gas analysis information, thus guaranteeing the accuracy of the calculations.

[0209] (f) Predict the carbon content at the decarbonization critical point;

[0210] Using the oxygen flow rate at the critical point, equation (10) is used to predict the carbon content at the decarburization critical point. The carbon content of the molten steel calculated by the process model is corrected using the predicted value, and this is used as the new starting point value for subsequent calculations.

[0211] (g) Calculation of the correction value for carbon accumulation in flue gas starting from the decarbonization critical point;

[0212] Calculation of the correction value for carbon accumulation in flue gas, starting from the decarbonization critical point with a time step of Δt:

[0213]

[0214] In the formula, i is the number of calculation steps starting from the decarbonization critical point; For the cumulative value calculated in step i, given the starting point of the calculation, f is 0; q This is the correction factor for the flue gas flow rate detection value.

[0215] (h) Calculate and save the change in the total amount of carbon fed into the furnace in this batch;

[0216] m' C =m hot C C,hot +m scr C C,scr -m stl C end (4)

[0217] In the formula, m' C The change in total carbon content during the blowing process (kg); m hot The weight of molten iron (kg); C C,hot The mass content of carbon in molten iron; m scr Add scrap steel (kg) to the converter (pig iron is considered together with the scrap steel); C C,scr The mass content of carbon in the scrap steel added to the converter; m stl The weight (kg) of molten steel tapped from the converter; C C,end The carbon content analysis value of the molten steel at the end of the blowing process.

[0218] (i) Calculate the estimated carbon content at the decarburization critical point for this furnace batch;

[0219]

[0220] In the formula, m stl The weight of the molten steel tapped (kg); △m Fe The oxygen consumption (kg) of iron from the decarburization critical point to the end of the blowing process is calculated as follows:

[0221]

[0222] In the formula, α is the molar ratio of iron oxidation to oxygen, which can be given empirically and takes a value in the range of [0.67, 1]. Oxygen content (m) from the decarburization critical point to the end of the blowing process 3 ).

[0223] Calculate C C,tp and the oxygen flow rate at the corresponding point Save and update the learning file data.

[0224] (j) End.

[0225] (k) This invention provides a method for predicting the carbon content of molten steel at the decarburization critical point in converter blowing based on an online dynamic detection model. Statistical regression analysis is performed using calculation, measurement, and model-determined information from nearby historical heats to derive the relationship between the carbon content at the decarburization critical point and the detected value. This relationship is then applied to predict the carbon content at the critical point in the current heat. The model undergoes bias correction. This technology typically does not impose limitations on the lag time of flue gas analysis; therefore, existing infrared flue gas analysis from dust removal systems can be utilized, eliminating the need for additional gas detection equipment and saving investment and maintenance costs. The information obtained using this technology provides crucial information for endpoint control. For traditional secondary lance control methods, the critical point determined using this technology provides an important reference for determining the timing of secondary lance disengagement. Furthermore, the determined carbon content can be compared with the secondary lance's detected value, which is of significant importance and value in improving the accuracy of secondary lance detection and endpoint control.

Claims

1. A method for predicting the carbon content of molten steel at the critical point of decarburization in converter blowing based on an online dynamic detection model, characterized in that: For each current heat, based on the current oxygen lance flow rate and the linear fitting equation between the oxygen lance flow rate and the carbon content of the molten steel established by linear fitting analysis at the decarburization critical point, the carbon content of the molten steel at the decarburization critical point for that heat is predicted. The sample values ​​used to provide the sample space for linear fitting analysis are determined based on the statistics of the corresponding values ​​of a set number of furnaces prior to the current furnace. The set number of furnaces preceding the current furnace cycle is updated iteratively with each furnace cycle iteration. The sample values ​​provided for the sample space in the linear fitting analysis include: the oxygen lance flow rate and the carbon content of the molten steel at the decarburization critical point for each heat. The oxygen lance flow rate is determined by detection. The carbon content of the molten steel at the decarburization critical point is derived from the carbon content of the molten steel at the end of converter blowing, combined with the carbon element mass balance equation.

2. The method for predicting the carbon content of molten steel at the critical point of decarburization in converter blowing according to claim 1, characterized in that: The statement that "the carbon content of the molten steel at the decarburization critical point is derived from the carbon content of the molten steel at the end of converter blowing, combined with the carbon element mass balance equation" specifically means: in, C C,tp : Carbon content based on flue gas estimation of decarburization critical point; Δm c : Decarburization amount from decarburization critical point to end of blowing, unit: kg; m stl : t tap weight of the steel, in kg; Δm Fe : iron element oxygen blowing consumption from decarburization critical point to blowing end point, unit: kg; C C,end : detected value of carbon content in the steel liquid at the end of the blowing 3. The method for predicting the carbon content of molten steel at the critical point of decarburization in converter blowing according to claim 2, characterized in that: wherein Δm c Calculated according to the set flue gas flow calculation model.

4. The method for predicting the carbon content of molten steel at the critical point of decarburization in converter blowing according to claim 3, characterized in that: The flue gas flow calculation model is based on flue gas detection and the deviation correction for flue gas detection is established based on the mass balance of carbon elements during the blowing process.

5. The method for predicting the carbon content of molten steel at the critical point of decarburization in converter blowing based on an online dynamic detection model, as described in claim 4, is characterized in that: The specific model for calculating flue gas flow rate is as follows: Δm c = f q w c , in, Δm c : Decarburization amount from decarburization critical point to decarburization end point, unit: kg; f q : correction factor; w c : The accumulated amount of decarburization from the decarburization critical point to the decarburization end point calculated based on the flue gas flow, unit: kg.

6. The method for predicting the carbon content of molten steel at the critical point of decarburization in converter blowing according to claim 5, characterized in that: The w c , in particular determined according to: in, P 0 : standard atmospheric pressure, unit: pa; M C : molar mass of the carbon element, in kg / mol; R: gas constant, unit: J / mol / K; T 0 : Standard state temperature, units: K; t p : Converter blowing decarburization critical point moment, unit: S; t e : Converter blowing end time, unit: S; q off : flue gas flow, unit: m 3 / s; C co : CO content, mole fraction; CO2content, mole fraction.

7. The method for predicting the carbon content of molten steel at the critical point of decarburization in converter blowing according to claim 5, characterized in that: The f q , in particular determined according to: in, l: Furnace number; N: The set number of furnace cycles; m' C : variation of total carbon in the blowing process, in kg; Decarburization cumulative amount from the start of the converter blowing to the end of decarburization calculated based on the flue gas flow, unit: kg.

8. The method for predicting the carbon content of molten steel at the critical point of decarburization in converter blowing according to claim 7, characterized in that: The m' is determined according to: C , is determined according to: m' C = m hot C C,hot + m scr C C,scr - m stl C stl , in, m hot : weight of molten iron, unit: kg; C C,hot : mass content of carbon element in molten iron; m scr : weight of scrap steel added to the converter, in kg; C C,scr : mass content of carbon element in scrap steel added into the converter m stl : weight of the molten steel tapped from the converter, unit: kg; C C,stl : mass content of carbon element in the converter tapping molten steel 9. The method for predicting the carbon content of molten steel at the critical point of decarburization in converter blowing according to claim 2, characterized in that: The Δm Fe is determined according to: in, M Fe : molar mass of the element iron, unit: kg / mol; α: The molar ratio of iron oxidation to oxygen; Oxygen quantity from decarburization critical point to blowing end point, unit: m 3 ; Δm c : Decarburization amount from decarburization critical point to end of blowing, unit: kg; P 0 : standard atmospheric pressure, unit: pa; R: gas constant, unit: J / mol / K; T 0 : Standard state temperature, units: K; M c : molar mass of carbon atoms, in kg / mol.

10. The method for predicting the carbon content of molten steel at the critical point of decarburization in converter blowing according to claim 4, characterized in that: The calculation start time of the flue gas flow calculation model is determined according to the actual time minus the lag time of flue gas detection analysis, The flue gas detection end time is determined according to the actual blowing-off time plus the lag time of flue gas detection analysis.

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