A converter final slag composition prediction method, system, terminal and storage medium

Abstract

The present application belongs to the technical field of converter steelmaking, and specifically provides a converter final slag composition prediction method, system, terminal and storage medium, comprising collecting information of historical heats of a converter, and establishing a historical database based on the collected historical heat information; preprocessing the historical heat information in the historical database, and constructing a secondary database of final slag composition under the same or similar conditions; performing optimization calculation on the preprocessed final slag composition data, respectively calculating the optimal final slag composition optimization value under various conditions, and forming an optimization value database; combining the information of the current heat, obtaining the corresponding final slag composition optimization value F 推优值 from the optimization value database; by collecting and establishing an information database of historical heats of the converter; the present application can fully utilize the process knowledge and experience in the historical data, and avoids waste of data resources. These data provide a solid foundation for optimizing the final slag composition, and help to improve the accuracy and reliability of the prediction.

Description

Technical Field

[0001] This invention belongs to the field of converter steelmaking technology, specifically relating to a method, system, terminal and storage medium for predicting the composition of converter final slag. Background Technology

[0002] At present, converter steelmaking is the most important part of the steel production process, occupying an important production position. Moreover, under the influence of continuous economic and social development, it is being widely applied and promoted. The specific objectives of endpoint control are: (1) the carbon content of molten steel should reach the target range required by the steel grade being produced; (2) the phosphorus and sulfur content in the steel should be lower than the lower limit required by the specification; (3) the tapping temperature should ensure the smooth progress of the next process; (4) the molten steel should have suitable oxidizing properties. Endpoint control is essentially the control of the converter blowing process. The quality of endpoint control is related to the steelmaking productivity, metal yield, production cost and steel quality, so it is a very important link in the converter steelmaking process. In the whole steelmaking process, converter slag plays a very important role. It participates in desulfurization and dephosphorization through slag-steel interface reaction, and plays a role in slowing down the oxygen flow scouring the furnace lining during the smelting process. The slag covering the surface of the molten steel can also effectively prevent the oxidation of the molten steel and the entry of harmful gases into the molten steel. Slag plays the following important physical and chemical roles in the smelting process: ① Forming molten slag to facilitate the separation of gangue components or oxidation products of impurities from molten metal or matte; ② Removing harmful impurities such as sulfur, phosphorus, and oxygen from molten steel, absorbing non-metallic inclusions in molten steel, and protecting molten steel from direct absorption of hydrogen, nitrogen, and oxygen; ③ Enriching useful metal oxides; ④ In electric arc furnace smelting (electric arc furnace, submerged arc furnace, electroslag remelting furnace, etc.), slag also acts as a resistance heating element.

[0003] Slag plays a decisive role in ensuring the quality of smelted products, metal recovery rate, smooth smelting operations, and various technical and economic indicators. The saying "Good slag makes good steel" vividly reflects the crucial role of slag in the smelting process. The physicochemical properties of slag, and the effectiveness of its metallurgical function, are primarily determined by the melting point, viscosity, interfacial tension, specific gravity, electrical conductivity, enthalpy, thermal conductivity, and the activity of certain components of the molten slag. These physicochemical properties are determined by the composition of the slag. The composition of the slag is adjusted by adding appropriate amounts of flux, with limestone and quartz being the most important fluxes. Fluorite (CaF2) is also an important flux in electric arc furnace steelmaking slag and synthetic slag. Therefore, studying the final slag composition of a combined blowing converter is highly significant, and the control of the final converter slag is particularly important.

[0004] Traditional methods often fail to fully utilize the vast amounts of data from historical heats. This data contains rich process knowledge and experience, which is invaluable for optimizing final slag composition. The lack of systematic data management and analysis tools leads to a waste of data resources. Because the converter steelmaking process is complex and variable, involving multiple variables and parameters, traditional prediction methods often struggle to accurately capture the intricate relationships between these variables, resulting in low prediction accuracy and failing to meet actual production needs. During steelmaking, slag composition dynamically changes with the blowing process, raw material input, temperature, and other conditions. Traditional methods often lack real-time detection and adjustment mechanisms, making it difficult to reflect these changes promptly, resulting in poor control of final slag composition. Summary of the Invention

[0005] In view of the above-mentioned shortcomings of the prior art, the present invention provides a method, system, terminal and storage medium for predicting the composition of converter final slag, so as to solve the above-mentioned technical problems.

[0006] In a first aspect, the present invention provides a method for predicting the composition of converter final slag, comprising:

[0007] Information on historical furnace runs is collected, including furnace charging conditions, slag-forming auxiliary material composition and amount, and endpoint conditions. A historical database is then established based on the collected historical furnace run information.

[0008] The historical furnace information in the historical database is preprocessed to construct a secondary database of final slag composition under the same or similar conditions;

[0009] The pretreated final slag composition data is used to perform optimization calculations, and the optimal final slag composition optimization values ​​under various conditions are calculated to form an optimization value database. Combined with the information of the current furnace, the corresponding final slag composition optimization value F is obtained from the optimization value database. 推优值 ;

[0010] Based on the current furnace feed information and target steel grade requirements, material balance calculations are performed to determine the amount of auxiliary materials added, the amount of ore added, the total slag amount, and the initial and final slag composition.

[0011] During the blowing process, the calculated value of the final slag composition is dynamically adjusted based on the actual feeding situation and changes in process control, resulting in the dynamically adjusted calculated value F of the final slag composition. 计算值 ;

[0012] During and after the blowing process, the temperature and carbon content are measured using a secondary lance, and the measurement results are used as real-time feedback information.

[0013] The composition of slag and molten steel in the converter was detected in real time using a LIBS spectrometer.

[0014] Based on the sub-gun measurement results and feedback information from the LIBS spectrometer, the final slag composition F was calculated. 计算值 Real-time corrections are performed to obtain the correction value F for the final slag composition. 修正值 ;

[0015] The optimal value of the final residue composition F 推优值 and correction value F 修正值 As input, the predicted value F of the final slag composition under the current furnace conditions is obtained through calculation using a symmetric connected neural network. 预测值 .

[0016] Further improvements to this technical solution include furnace charging conditions, such as the composition, temperature, and weight of the molten iron, as well as the type and weight of the scrap steel.

[0017] Further improvements to this technical solution include endpoint conditions such as endpoint composition and temperature, and final residue composition.

[0018] Further improvements to this technical solution include requiring the target steel grade to include the final slag composition.

[0019] Further improvements to this technical solution include process control variations such as splashing and re-drying.

[0020] Further improvements to this technical solution include the addition of a secondary weapon, either a TSC or a TSO.

[0021] Further improvements to this technical solution include the use of a LIBS spectrometer to perform real-time detection of the CaO, SiO2, MgO, and FeO contents in the slag and the C content in the molten steel.

[0022] Secondly, the present invention provides a converter final slag composition prediction system, comprising:

[0023] The data acquisition and database establishment module is used to collect information on historical furnace runs of the converter. The historical furnace run information includes furnace charging conditions, slag-forming auxiliary material composition and addition amount, and endpoint conditions, and establishes a historical database based on the collected historical furnace run information.

[0024] The secondary database creation module is used to preprocess historical furnace information in the historical database and construct a secondary database of final slag composition under the same or similar conditions.

[0025] The optimization calculation module is used to perform optimization calculations on the pre-treated final slag composition data, calculate the optimal final slag composition optimization values ​​under various conditions, and form an optimization value database; combined with the information of the current furnace, it retrieves the corresponding final slag composition optimization value F from the optimization value database. 推优值 ;

[0026] The material balance calculation module is used to perform material balance calculations based on the current furnace feed information and target steel grade requirements, and to determine the amount of auxiliary materials added, the amount of ore added, the total slag amount, and the initial and final slag composition.

[0027] The final slag composition dynamic adjustment module is used to dynamically adjust the calculated value of the final slag composition based on the actual feeding situation and process control changes during the blowing process, thus obtaining the dynamic adjustment calculation value F of the final slag composition. 计算值 ;

[0028] The secondary gun measurement module is used to measure temperature and carbon content using a secondary gun during and after the blowing process, and to provide the measurement results as real-time feedback information.

[0029] The slag and molten steel composition detection module is used to detect the composition of slag and molten steel in the converter in real time using a LIBS spectrometer;

[0030] The final slag composition correction module is used to combine the sub-gun measurement results and LIBS spectrometer feedback information to calculate the final slag composition value F. 计算值 Real-time corrections are performed to obtain the correction value F for the final slag composition. 修正值 ;

[0031] The final slag composition prediction module is used to predict the optimal value F of the final slag composition. 推优值 and correction value F 修正值 As input, the predicted value F of the final slag composition under the current furnace conditions is obtained through calculation using a symmetric connected neural network. 预测值 .

[0032] Thirdly, a terminal is provided, including:

[0033] Processor, memory, among which,

[0034] This memory is used to store computer programs.

[0035] The processor is used to retrieve and run the computer program from memory, causing the terminal to perform the terminal method described above.

[0036] Fourthly, a computer storage medium is provided, wherein instructions are stored therein, which, when executed on a computer, cause the computer to perform the methods described in the above aspects.

[0037] The beneficial effects of this invention are as follows:

[0038] Efficient utilization of data resources: By collecting and establishing an information database of historical converter heats, this invention can fully utilize the process knowledge and experience in historical data, avoiding waste of data resources. This data provides a solid foundation for optimizing the final slag composition, helping to improve the accuracy and reliability of predictions.

[0039] Significantly improved prediction accuracy: This invention employs advanced algorithms such as optimization calculations and symmetric connection neural networks to deeply mine and analyze historical data, accurately capturing the complex relationships between multiple variables and parameters in the converter steelmaking process. This results in more accurate predictions, better meeting actual production needs and improving steelmaking productivity and product quality.

[0040] Real-time monitoring and dynamic adjustment: During the blowing process, this invention utilizes advanced monitoring equipment such as a secondary lance and a LIBS spectrometer to monitor the temperature, carbon content, slag, and molten steel composition within the converter in real time. Based on this real-time feedback, this invention can dynamically adjust the calculated values ​​of the final slag composition, ensuring that the final slag composition remains within the optimal range. This real-time monitoring and dynamic adjustment mechanism significantly improves the flexibility and accuracy of final slag composition control.

[0041] Optimization of material balance calculations: Based on the furnace feed information and target steel grade requirements for the current heat, this invention performs precise material balance calculations to determine the amount of auxiliary materials added, the amount of ore added, the total slag volume, and the initial and final slag compositions. This helps reduce material waste, improve metal recovery rate, and lower production costs.

[0042] Improving production efficiency and product quality: By accurately predicting and controlling the composition of the final slag, this invention ensures that key indicators such as carbon content, phosphorus and sulfur content, tapping temperature, and oxidizability of molten steel all meet target requirements. This helps to improve steelmaking efficiency, reduce defect rates, and enhance the overall quality of steel products.

[0043] Enhancing Technical and Economic Indicators: Slag plays a crucial role in the smelting process, and its physicochemical properties directly affect the quality of smelted products, metal recovery rate, and various technical and economic indicators. By optimizing the final slag composition, this invention can significantly improve these technical and economic indicators, bringing greater economic benefits to enterprises.

[0044] Furthermore, the design principle of this invention is reliable, the structure is simple, and it has a very wide range of application prospects. Attached Figure Description

[0045] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, for those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0046] Figure 1 This is a schematic flowchart of a method according to an embodiment of the present invention.

[0047] Figure 2 This is a schematic block diagram of a system according to an embodiment of the present invention.

[0048] Figure 3 This is a schematic diagram of the structure of a terminal provided in an embodiment of the present invention.

[0049] 210 is the data acquisition and database establishment module, 220 is the secondary database establishment module, 230 is the optimization calculation module, 240 is the material balance calculation module, 250 is the final slag composition dynamic adjustment module, 260 is the secondary lance measurement module, 270 is the slag and molten steel composition detection module, 280 is the final slag composition correction module, and 290 is the final slag composition prediction module. Detailed Implementation

[0050] To enable those skilled in the art to better understand the technical solutions of this invention, the technical solutions of the embodiments of this invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this invention, and not all embodiments. Based on the embodiments of this invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of this invention.

[0051] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains. The terminology used herein in the description of the invention is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention.

[0052] The key terms used in this invention will be explained below.

[0053] TSC, while not having a direct full name, in the steelmaking field, generally refers to the sublance probe technology related to temperature measurement and carbon content determination. Function: The TSC sublance probe is primarily used to measure the temperature of molten steel and determine its carbon content via liquidus temperature. Additionally, it can obtain steel samples for further analysis. Timing of Use: The TSC probe is typically used during the middle stage of oxygen blowing, i.e., a few minutes before the end of oxygen blowing, to ensure that the temperature and carbon content of the molten steel reach the predetermined requirements. Technical Features: Through high-precision measurement technology, the TSC probe can accurately determine the temperature and carbon content of molten steel, providing crucial data support for end-point control in the steelmaking process.

[0054] TSO, while not having a direct full name, refers to another sub-lance probe technology in steelmaking, primarily used for oxygen activity measurement. Functions: The TSO sub-lance probe can not only measure molten steel temperature but also perform sampling and oxygen activity measurement. This helps to understand the oxygen content in the molten steel, thereby adjusting steelmaking process parameters. Timing of Use: The TSO probe is typically used at the end of oxygen blowing, i.e., within a short period (e.g., 30-50 seconds) after oxygen blowing ends, to obtain information on the oxygen content of the molten steel after blowing. Technical Features: By integrating multiple measurement functions, the TSO probe can comprehensively assess the quality of molten steel, providing strong support for optimizing the steelmaking process.

[0055] The converter final slag composition prediction method provided in this embodiment of the invention is executed by computer equipment, and correspondingly, the converter final slag composition prediction system runs in the computer equipment.

[0056] Figure 1 This is a schematic flowchart illustrating a method according to an embodiment of the present invention. Wherein, Figure 1 The implementing entity can be a converter final slag composition prediction system. Depending on different requirements, the order of steps in this flowchart can be changed, and some steps can be omitted.

[0057] like Figure 1 As shown, the method includes:

[0058] Step 110: Collect information on historical furnace runs of the converter. The historical furnace run information includes furnace charging conditions, slag-forming auxiliary material composition and addition amount, and endpoint conditions. A historical database is established based on the collected historical furnace run information.

[0059] Step 120: Preprocess the historical furnace information in the historical database to construct a secondary database of final slag composition under the same or similar conditions;

[0060] Step 130: Perform optimization calculations on the pretreated final slag composition data, calculate the optimal final slag composition optimization values ​​under various conditions, and form an optimization value database; combine the information of the current furnace, and obtain the corresponding final slag composition optimization value F from the optimization value database. 推优值 ;

[0061] Step 140: Perform material balance calculations based on the current furnace feed information and target steel grade requirements to determine the amount of auxiliary materials added, the amount of ore added, the total slag amount, and the initial and final slag composition.

[0062] Step 150: During the blowing process, the calculated value of the final slag composition is dynamically adjusted based on the actual feeding situation and changes in process control, resulting in the dynamically adjusted calculated value F of the final slag composition. 计算值 ;

[0063] Step 160: During and after the blowing process, the temperature and carbon content are measured using a secondary lance, and the measurement results are used as real-time feedback information.

[0064] Step 170: Use a LIBS spectrometer to detect the composition of slag and molten steel in the converter in real time;

[0065] Step 180: Combining the sub-gun measurement results and feedback information from the LIBS spectrometer, calculate the final slag composition value F. 计算值 Real-time corrections are performed to obtain the correction value F for the final slag composition. 修正值 ;

[0066] Step 190, the optimal value F of the final residue composition is calculated. 推优值 and correction value F 修正值 As input, the predicted value F of the final slag composition under the current furnace conditions is obtained through calculation using a symmetric connected neural network. 预测值 . Specific Implementation Example 1:

[0068] Heater 1: Inlet temperature of molten iron 1386℃; molten iron composition: C: 4.40%; Si: 0.65%; Mn: 0.35%; P: 0.082%; S: 0.028%; Scrap steel + molten iron addition: (180+51)t; Main slag-forming materials and alloy additions: lime 30kg / t, dolomite 9kg / t, ore 10kg / t; Oxygen consumption: 49m³ / t. The blowing process was stable, with no splashing or back-drying phenomena, and the endpoint was hit on the first attempt. Converter endpoint target values: [C]: 0.081%; T: 1636℃; Sub-lance TSC results: [C]: 0.035%; T: 1521℃; Sub-lance TSO results: [C]: 0.080%; T: 1635℃; Calculated value of final slag composition dynamic adjustment F. 计算值 LIBs detection value, final residue composition correction value F 修正值 Recommendation value F 推优值 Predicted value F 预测值 Target value F 目标值 Laboratory value F 化验值 The content of each component is shown in the table below:

[0069] .

[0070] As can be seen from the data in the table, the predicted value F 预测值 Target value F 目标值 Test value F 化验值 The content of each component in the sample is close, resulting in accurate predictions. Specific Implementation Example 2:

[0072] Heater 2: Inlet temperature of molten iron 1372℃; molten iron composition: C: 4.28%; Si: 0.58%; Mn: 0.42%; P: 0.072%; S: 0.032%; Scrap steel + molten iron addition: (180+51)t; Main slag-forming materials and alloy additions: lime 30kg / t, dolomite 8.2kg / t, ore 9.6kg / t; Oxygen consumption: 49.2m³ / t. The blowing process was stable, with no splashing or back-drying phenomena, and the endpoint was hit on the first attempt. Converter endpoint target values: [C]: 0.076%; T: 1645℃; Sub-lance TSC results: [C]: 0.043%, T: 1556℃; Sub-lance TSO results: [C]: 0.077%, T: 1646℃; Calculated value of dynamic adjustment of final slag composition F, LIBs detection value, and corrected value of final slag composition F. 修正值 Recommendation value F 推优值 Predicted value F 预测值 Target value F 目标值 Test value F 化验值 The content of each component is shown in the table below:

[0073]

[0074] As can be seen from the data in the table, the predicted value F 预测值 Target value F 目标值 Test value F 化验值 The content of each component in the sample is close, and the prediction results are also relatively accurate.

[0075] To facilitate understanding of the present invention, the following description further illustrates the method for predicting the composition of converter final slag provided by the present invention, based on the principle of the method and the process of predicting the composition of converter final slag in the embodiments.

[0076] Specifically, the furnace charging conditions include the composition, temperature, and weight of the molten iron, as well as the type and weight of the scrap steel; the endpoint conditions include the endpoint composition and temperature and the final slag composition; the target steel grade requirements include the final slag composition; process control variations include splashing and re-drying; the secondary lance includes TSC or TSO; and a LIBS spectrometer is used to monitor the CaO content, SiO2 content, MgO content, FeO content in the slag, and the C content in the molten steel in real time.

[0077] In some embodiments, the converter final slag composition prediction system 200 may include multiple functional modules composed of computer program segments. The computer programs for each program segment in the converter final slag composition prediction system 200 may be stored in the memory of a computer device and executed by at least one processor to perform (see details). Figure 1 (Description) Function for predicting the composition of converter final slag.

[0078] In this embodiment, the converter final slag composition prediction system 200 can be divided into multiple functional modules according to its functions, such as... Figure 2 As shown. The functional modules may include: a data acquisition and database establishment module 210, a secondary database establishment module 220, an optimization calculation module 230, a material balance calculation module 240, a final slag composition dynamic adjustment module 250, a secondary lance measurement module 260, a slag and molten steel composition detection module 270, a final slag composition correction module 280, and a final slag composition prediction module 290. The module referred to in this invention is a series of computer program segments that can be executed by at least one processor and perform a fixed function, stored in memory. In this embodiment, the functions of each module will be described in detail in subsequent embodiments.

[0079] Specifically, the data acquisition and database establishment module is used to collect information on historical converter heats, including charging conditions, slag-forming auxiliary material composition and dosage, and endpoint conditions, and to establish a historical database based on the collected historical heat information; the secondary database establishment module is used to preprocess the historical heat information in the historical database to construct a secondary database of final slag composition under the same or similar conditions; the optimization calculation module is used to perform optimization calculations on the preprocessed final slag composition data, calculate the optimal final slag composition optimization value under various conditions, and form an optimization value database; combined with the information of the current heat, the corresponding final slag composition optimization value F is obtained from the optimization value database. 推优值 The material balance calculation module is used to perform material balance calculations based on the current furnace feed information and target steel grade requirements, determining the amount of auxiliary materials added, the amount of ore added, the total slag volume, and the initial and final slag compositions. The final slag composition dynamic adjustment module is used to dynamically adjust the calculated final slag composition value F during the blowing process based on actual feeding conditions and process control changes, obtaining the dynamic adjustment calculation value F of the final slag composition. 计算值 The secondary lance measurement module is used to measure temperature and carbon content using a secondary lance during and after the blowing process, and provides the results as real-time feedback. The slag and molten steel composition detection module is used to perform real-time detection of the slag and molten steel composition in the converter using a LIBS spectrometer. The final slag composition correction module combines the secondary lance measurement results and LIBS spectrometer feedback information to calculate the final slag composition value F. 计算值 Real-time corrections are performed to obtain the correction value F for the final slag composition. 修正值 The final slag composition prediction module is used to predict the optimal value F of the final slag composition. 推优值 and correction value F 修正值 As input, the predicted value F of the final slag composition under the current furnace conditions is obtained through calculation using a symmetric connected neural network. 预测值 .

[0080] Figure 3This is a schematic diagram of a terminal 300 provided in an embodiment of the present invention. The terminal 300 can be used to execute the method for updating heat dissipation strategy parameters provided in the embodiment of the present invention.

[0081] The terminal 300 may include a processor 310, a memory 320, and a communication module 330. These components communicate via one or more buses. Those skilled in the art will understand that the server structure shown in the figure does not constitute a limitation of the present invention. It may be a bus topology or a star topology, and may include more or fewer components than shown, or combine certain components, or have different component arrangements.

[0082] The memory 320 can be used to store the execution instructions of the processor 310. The memory 320 can be implemented by any type of volatile or non-volatile memory terminal or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk. When the execution instructions in the memory 320 are executed by the processor 310, the terminal 300 is able to perform some or all of the steps in the above method embodiments.

[0083] The processor 310 serves as the control center of the storage terminal, connecting various parts of the electronic terminal via various interfaces and lines. It executes software programs and / or modules stored in the memory 320, and calls data stored in the memory to perform various functions of the electronic terminal and / or process data. The processor can be composed of integrated circuits (ICs), such as a single packaged IC or multiple packaged ICs with the same or different functions connected together. For example, the processor 310 may consist only of a central processing unit (CPU). In this embodiment of the invention, the CPU may have a single processing core or include multiple processing cores.

[0084] The communication module 330 is used to establish a communication channel, enabling the storage terminal to communicate with other terminals. It receives user data sent by other terminals or sends user data to other terminals.

[0085] The present invention also provides a computer storage medium, wherein the computer storage medium may store a program, which, when executed, may include some or all of the steps provided in the embodiments of the present invention. The storage medium may be a magnetic disk, an optical disk, read-only memory (ROM), or random access memory (RAM), etc.

[0086] Therefore, the technical effects that can be achieved by this invention and this embodiment can be found in the description above, and will not be repeated here.

[0087] Those skilled in the art will clearly understand that the techniques in the embodiments of the present invention can be implemented using software plus necessary general-purpose hardware platforms. Based on this understanding, the technical solutions in the embodiments of the present invention, or the parts that contribute to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium such as a USB flash drive, a portable hard drive, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk, or any other medium capable of storing program code. It includes several instructions to cause a computer terminal (which may be a personal computer, a server, or a second terminal, a network terminal, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention.

[0088] The same or similar parts between the various embodiments in this specification can be referred to mutually. In particular, the terminal embodiments are basically similar to the method embodiments, so the description is relatively simple, and the relevant parts can be referred to the description in the method embodiments.

[0089] In the embodiments provided by this invention, it should be understood that the disclosed systems and methods can be implemented in other ways. For example, the system embodiments described above are merely illustrative; for instance, the division of modules is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple modules or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between systems or modules may be electrical, mechanical, or other forms.

[0090] The modules described as separate components may or may not be physically separate. The components shown as modules may or may not be physical modules; that is, they may be located in one place or distributed across multiple network modules. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs.

[0091] In addition, the functional modules in the various embodiments of the present invention can be integrated into one processing module, or each module can exist physically separately, or two or more modules can be integrated into one module.

[0092] Although the present invention has been described in detail with reference to the accompanying drawings and preferred embodiments, the present invention is not limited thereto. Various equivalent modifications or substitutions can be made to the embodiments of the present invention by those skilled in the art without departing from the spirit and essence of the invention, and such modifications or substitutions should all be within the scope of the present invention. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should also be covered within the protection scope of the present invention.

Claims

1. A method for predicting the composition of converter final slag, characterized in that, include: Information on historical furnace runs is collected, including furnace charging conditions, slag-forming auxiliary material composition and amount added, and endpoint conditions. A historical database is then established based on the collected historical furnace run information. The historical furnace information in the historical database is preprocessed to construct a secondary database of final slag composition under the same or similar conditions; The pretreated final slag composition data is used to perform optimization calculations, and the optimal final slag composition optimization values ​​under various conditions are calculated to form an optimization value database. Combined with the information of the current furnace, the corresponding final slag composition optimization value F is obtained from the optimization value database. 推优值 ; Based on the current furnace feed information and target steel grade requirements, material balance calculations are performed to determine the amount of auxiliary materials added, the amount of ore added, the total slag amount, and the initial and final slag compositions. During the blowing process, the calculated value of the final slag composition is dynamically adjusted based on the actual feeding situation and changes in process control, resulting in the dynamically adjusted calculated value F of the final slag composition. 计算值 ; During and after the blowing process, the temperature and carbon content are measured using a secondary lance, and the measurement results are used as real-time feedback information. The composition of slag and molten steel in the converter was detected in real time using a LIBS spectrometer. Based on the sub-gun measurement results and feedback information from the LIBS spectrometer, the final slag composition F was calculated. 计算值 Real-time corrections are performed to obtain the correction value F for the final slag composition. 修正值 ; The optimal value of the final residue composition F 推优值 and correction value F 修正值 As input, the predicted value F of the final slag composition under the current furnace conditions is obtained through calculation using a symmetric connected neural network. 预测值 .

2. The method for predicting the composition of converter final slag according to claim 1, characterized in that, The conditions for charging the furnace include the composition, temperature, and weight of the molten iron, as well as the type and weight of the scrap steel.

3. The method for predicting the composition of converter final slag according to claim 1, characterized in that, The endpoint conditions include the endpoint composition and temperature, and the final residue composition.

4. The method for predicting the composition of converter final slag according to claim 1, characterized in that, The target steel grade requirements include the composition of the final slag.

5. The method for predicting the composition of converter final slag according to claim 1, characterized in that, Process control variations include splashing and re-drying.

6. The method for predicting the composition of converter final slag according to claim 1, characterized in that, Secondary weapons include TSC or TSO.

7. The method for predicting the composition of converter final slag according to claim 1, characterized in that, The CaO, SiO2, MgO, and FeO contents in the slag and the C content in the molten steel were detected in real time using a LIBS spectrometer.

8. A converter final slag composition prediction system, characterized in that, include: The data acquisition and database establishment module is used to collect information on historical furnace runs of the converter. The historical furnace run information includes furnace charging conditions, slag-forming auxiliary material composition and addition amount, and endpoint conditions, and establishes a historical database based on the collected historical furnace run information. The secondary database creation module is used to preprocess historical furnace information in the historical database and construct a secondary database of final slag composition under the same or similar conditions. The optimization calculation module is used to perform optimization calculations on the pre-treated final slag composition data, calculate the optimal final slag composition optimization values ​​under various conditions, and form an optimization value database; combined with the information of the current furnace, it retrieves the corresponding final slag composition optimization value F from the optimization value database. 推优值 ; The material balance calculation module is used to perform material balance calculations based on the current furnace feed information and target steel grade requirements, and to determine the amount of auxiliary materials added, the amount of ore added, the total slag amount, and the initial and final slag composition. The final slag composition dynamic adjustment module is used to dynamically adjust the calculated value of the final slag composition based on the actual feeding situation and process control changes during the blowing process, thus obtaining the dynamic adjustment calculation value F of the final slag composition. 计算值 ; The secondary gun measurement module is used to measure temperature and carbon content using a secondary gun during and after the blowing process, and to provide the measurement results as real-time feedback information. The slag and molten steel composition detection module is used to detect the composition of slag and molten steel in the converter in real time using a LIBS spectrometer; The final slag composition correction module is used to combine the sub-gun measurement results and LIBS spectrometer feedback information to calculate the final slag composition value F. 计算值 Real-time corrections are performed to obtain the correction value F for the final slag composition. 修正值 ; The final slag composition prediction module is used to estimate the final slag composition value F. 推优值 and correction value F 修正值 As input, the predicted value F of the final slag composition under the current furnace conditions is obtained through calculation using a symmetric connected neural network. 预测值 .

9. A terminal, characterized in that, include: processor; Memory used to store the processor's execution instructions; The processor is configured to perform the method according to any one of claims 1-7.

10. A computer-readable storage medium storing a computer program, characterized in that, When the program is executed by the processor, it implements the method as described in any one of claims 1-7.

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