Online monitoring system and method for temperature and splashing of high-temperature melt of top-blown furnace

Abstract

The invention relates to the technical field of high-temperature melt temperature monitoring, and discloses a top-blown furnace high-temperature melt temperature and splashing online monitoring system and method, and the system comprises a top-blown furnace data acquisition module, a furnace body splashing data calculation module and a smelting process control module. The method comprises the following steps: transmitting detected data to a data calculation module in real time; performing interface reconstruction on the real-time data to obtain the specific condition that the melt is splashed to the wall surface, and realizing visualization of impact of the melt on the furnace body according to the specific condition that the melt is splashed to the wall surface; the visual data is transmitted to the smelting process control module; and on the basis of the molten pool temperature distribution and the melt splashing condition, the flow of pulverized coal, dry powder and gas is adjusted, a melt temperature liquid level model is constructed, the molten pool temperature and the melt splashing condition are evaluated, and the smelting process is controlled according to the evaluation result. According to the method, the smelting quality problem caused by melt splashing and uneven temperature can be reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of high-temperature melt temperature monitoring, and particularly to an on-line monitoring system and method for the high-temperature melt temperature and splashing of a top-blown furnace. Background Art

[0002] Top-blown furnaces are widely used in the smelting of non-ferrous metals such as tin, copper, and lead. Taking tin smelting as an example, during the smelting process, a top-blown lance injects pulverized coal, dry material powder, and oxygen-enriched air into the molten bath, while stirring the melt, maintaining the temperature required for continuous smelting, and realizing the stable progress of the top-blown smelting process. Temperature is a key parameter reflecting the uniformity of melt stirring and the smelting rate. During the smelting process, the temperature of the molten bath is generally between 1300°C and 1500°C. The existing thermocouples for measuring high-temperature molten baths achieve temperature measurement by directly contacting the melt and are generally arranged on the inner wall of the furnace body. However, the central area of the molten bath at the bottom of the lance is the core area where the reaction takes place, and it is difficult for existing equipment to directly measure the melt temperature in this area. This makes the control of the injection amounts of pulverized coal, dry material powder, and oxygen-enriched air rely entirely on the experience of workers, greatly reducing the smelting efficiency and affecting the product quality to a certain extent. In addition, the top-blown process is accompanied by strong melt splashing. When the high-temperature melt splashes onto the furnace wall, it will cause its burnout, greatly affecting the furnace life and even endangering production safety in severe cases. Reasonable control of melt splashing during the top-blown process is crucial for the stable progress of the smelting process. Based on this, this study proposes an on-line monitoring system for the high-temperature melt temperature and splashing that can be applied to a top-blown furnace.

[0003] Prior Art One, a Chinese patent, application number: 202411210140.1, discloses an on-line detection system and method for the composition of top-blown slag in tin smelting, belonging to the technical field of intelligent smelting of non-ferrous metals. The system includes a LIBS detection system and a sampling rod dipping system; the sampling rod dipping system includes a top-blown furnace, a fume cleaning fan, a sampling rod, an anti-sway limit block, a steel wire rope, a winch, a fixed bracket, and a cover plate; the LIBS detection system includes an industrial probe and a spectrometer. The present invention uniquely creates a sampling rod dipping system, which can sample the tin-rich slag inside the furnace kiln at any smelting cycle, and coupling with the LIBS detection system can obtain the slag composition in real time. The application of the industrial probe can achieve remote monitoring and detection, greatly reducing the need for on-site manual observation and operation, improving work efficiency, increasing personnel safety, and improving the working environment. Although, according to the detection results, the batching and personnel operations can be adjusted in real time, which helps to accurately control the bath smelting, improve stability and smelting efficiency; however, the accuracy and real-time performance of temperature monitoring are poor, resulting in certain errors.

[0004] Prior Art 2, a Chinese patent with application number 202311263009.7, provides a method for sensor fault detection and data reconstruction based on spatio-temporal collaboration. It detects sensor faults by means of spatial correlation relationships and reconstructs the data of faulty sensors using temporal correlation relationships, enabling the system to ensure sufficient fault tolerance within a certain time range. By proposing a spatial correlation model based on MIC-GCN, graph theory is introduced into the scenario of top-blown converter sensor fault diagnosis. A knowledge graph of the sensor network is constructed according to the maximum mutual information, and multi-scale spatial features are captured by means of the graph convolution mechanism, thereby capturing the fault states of the sensors. Although a spatio-temporal collaborative STG-Transformer graph-level prediction model is designed by introducing graph-level temporal correlation relationships, on the basis of locating faulty sensors, the data of faulty sensors are reconstructed using the minimum residual, realizing the data reconstruction of faulty sensors; however, the monitoring coverage is small, resulting in difficulty in comprehensively perceiving.

[0005] Prior Art 3, a Chinese patent with application number 202411223157.0, discloses a method for detecting the dust concentration in a top-blown converter based on the combination of the light absorption method and the light reflection method, belonging to the field of dust concentration detection. Among them, the detection method includes: controlling a sensor to emit incident light to a preset position of the top-blown converter and receiving the reflected light that is reflected by the incident light and passes through the dust; determining the signal intensity corresponding to the reflected light; inputting the signal intensity into a dust concentration function expression to determine the dust concentration of the top-blown converter. Although by providing a new dust concentration function expression, it is only necessary to determine the signal intensity corresponding to the reflected light to calculate the dust concentration, without the need to arrange sensors inside the top-blown converter, which is applicable to the top-blown converter operating in a high-temperature environment and can improve the universality and applicability of dust concentration detection; however, the accuracy and real-time performance of temperature monitoring are poor, resulting in certain errors.

[0006] Currently, there are problems in Prior Art 1, Prior Art 2 and Prior Art 3 such as poor accuracy and real-time performance of temperature monitoring and small monitoring coverage. Therefore, the present invention provides a high-temperature melt temperature and splash on-line monitoring system and method applied to a top-blown converter. Summary of the Invention

[0007] The main object of the present invention is to provide a high-temperature melt temperature and splash on-line monitoring system and method for a top-blown converter to solve the problems of poor accuracy and real-time performance of temperature monitoring and small monitoring coverage in the prior art.

[0008] To achieve the above object, the present invention provides the following technical solutions:

[0009] A high-temperature melt temperature and splash on-line monitoring system for a top-blown converter, comprising:

[0010] The top-blown converter data acquisition module is used to detect the temperature at different positions of the molten bath and the splash situation of the melt by the thermocouples at the slag height position on the inner wall of the top-blown converter and the infrared thermometer on the inner wall of the top-blown converter, and transmit the detected data to the data calculation module in real time;

[0011] The furnace body splash data calculation module is used to obtain the specific situation of the melt splashing onto the wall surface by using the interface reconstruction method for the real-time data, and realize the visualization of the splash impact on the furnace body according to the specific situation of the melt splashing onto the wall surface; and transmit the visualized data to the smelting process control module;

[0012] The smelting process control module is used to adjust the flow rates of pulverized coal, dry powder and gas based on the temperature distribution of the molten bath and the splash situation of the melt, construct a melt temperature and liquid level model, evaluate the temperature of the molten bath and the splash situation of the melt, and control the smelting process according to the evaluation results.

[0013] As a further improvement of the present invention, the top-blown converter data acquisition module includes:

[0014] The installed infrared thermometer sub-module is used to add a fourth layer of sleeve in the top-blown lance, and arrange the infrared thermometer on the inner wall of the fourth layer of sleeve of the top-blown furnace; isolate the particles outside the infrared ray irradiation path of the infrared thermometer to normally monitor the temperature of the molten bath;

[0015] The infrared thermometer cooling sub-module is used to form a high-speed gas channel between the third layer of sleeve and the fourth layer of sleeve, and cool the infrared thermometer through the gas in this channel; and the third layer of sleeve and the fourth layer of sleeve are connected by welding, and four infrared thermometers are evenly arranged on the outer wall of the fourth layer;

[0016] The thermocouple arrangement sub-module is used to arrange the thermocouples around the wall of the top-blown furnace, part of them are located at the slag layer height and part of them are located above the molten bath liquid level.

[0017] As a further improvement of the present invention, the furnace body splash data calculation module includes:

[0018] The reduced melt interface sub-module is used to restore the interface situation of the melt splashing onto the wall surface by using the interface reconstruction method based on the temperature data of the thermocouples. The abscissa of the thermocouples is represented by English letters and the ordinate is represented by numbers; group every four adjacent thermocouples as a group;

[0019] The thermocouple grouping sub-module is used to divide the thermocouples into 13 groups horizontally and 9 groups vertically, and a total of 117 groups can be divided;

[0020] The visualization display sub-module is used to transfer the collected data to the computer in real time; when the thermocouple is covered by splashing droplets, the temperature data transferred to the computer increases significantly; each group of thermocouples has four ways to restore the shape of the phase interface of the melt splashing onto the wall surface.

[0021] As a further improvement of the present invention, the melt interface restoration sub-module includes:

[0022] The melt temperature acquisition unit is used to collect melt temperature data through thermocouples. The abscissa of the thermocouple is represented by English letters, and the ordinate is represented by numbers. Group the data of adjacent four thermocouples to form a data block;

[0023] The interface reconstruction unit is used to update the position of the melt interface according to the collected temperature data by using interface interpolation technology; perform interpolation calculation on the interface position according to the thermocouple data to obtain the interface shape; adjust the grid structure according to the interface shape;

[0024] The simulation verification unit is used to simulate the reconstructed melt interface to verify whether its dynamic behavior conforms to the preset physical phenomena; if it conforms to the preset physical phenomena, analyze and store the physical signs of the reconstructed melt interface; if not, perform interface interpolation and meshing processing again.

[0025] As a further improvement of the present invention, the interface reconstruction unit includes:

[0026] The thermocouple coupling data processing sub-unit is used to analyze the heat conduction characteristics of the melt interface according to the collected thermocouple coupling data and extract key parameters; among them, the key parameters include temperature gradient and heat flux;

[0027] The new interface position calculation sub-unit is used to take the collected temperature data as input and calculate the new position of the melt interface through an interpolation algorithm; for complex scenarios, combine momentum interpolation and mass conservation conditions to calculate the new position of the melt interface;

[0028] The interface shape acquisition sub-unit is used to obtain the set shape of the interface based on the updated interface position; adjust the grid structure according to the interface shape, and adopt adaptive grid reconstruction technology to dynamically adjust the grid density according to the complexity of the interface;

[0029] Among them, the thermocouple coupling data processing sub-unit is used to analyze the heat conduction characteristics of the melt interface and extract key parameters such as temperature gradient and heat flux. The calculation formula:

[0030]

[0031] In the formula, T(x,y,t) represents the temperature distribution of the melt interface at coordinates (x,y) and time t; represents the temperature gradient;

[0032] The new interface position calculation subunit is used to calculate the new position of the melt interface through an interpolation algorithm based on the collected temperature data. The calculation formula is:

[0033]

[0034] In the formula, L new (x, y, t) represents the updated melt interface position; ΔL(x, y, t) represents the change in the interface position.

[0035] As a further improvement of the present invention, the simulation verification unit includes:

[0036] The grid structure adjustment subunit is used to perform grid interpolation at the new interface position to generate a new grid structure for continuous interpolation; and adjust the grid structure through an optimization algorithm;

[0037] The structure verification subunit is used to compare the interpolated structure with the analytical solution, calculate and evaluate the interpolation accuracy; if it is greater than the preset interpolation accuracy value, adjust the interpolation parameters; iterate sequentially until it is less than the preset interpolation accuracy value;

[0038] The melt simulation subunit is used to simulate the reconstructed melt interface to verify whether its dynamic behavior conforms to the preset physical phenomena; if it conforms to the preset physical phenomena, analyze the physical signs of the reconstructed melt interface and store them; if not, re-perform interface interpolation and meshing processing;

[0039] Among them, in the structure verification subunit, the interpolated structure is compared with the analytical solution, and the interpolation accuracy is calculated and evaluated. The interpolation error calculation formula is:

[0040]

[0041] In the formula, X interp represents the interpolated structure, which is the grid data generated by the grid structure adjustment subunit; X analytic represents the analytical solution, that is, the theoretically accurate structure data; N represents the total number of grid points; w i represents the weight coefficient of the i-th grid point, which is used to reflect the importance in the actual system; γ represents the smoothing constraint coefficient, which is used to control the smoothness of the interpolation result; M represents the total number of dimensions; f j represents the smoothing factor of the j-th dimension, which is used to impose additional constraints on a specific dimension;

[0042] The dynamic iterative adjustment formula:

[0043]

[0044] In the formula, Denote the interpolation structure of the k-th iteration; η represents the iteration step size, controlling the adjustment amplitude; Denote the gradient of the interpolation error function Ψ, which is used to guide the iteration direction; L represents the total number of additional constraint conditions; k l Denote the weight coefficient of the l-th constraint condition; A l Denote the coefficient matrix of the l-th constraint condition; B l Denote the target value matrix of the l-th constraint condition;

[0045] Precision evaluation convergence formula:

[0046]

[0047] In the formula, Z represents the normalization coefficient, which is used to ensure that the convergence value is within a reasonable range; Q represents the number of key feature points; g m Denote the evaluation weight of the m-th feature point; Denote the eigenvalue of the interpolation structure at the m-th feature point; Denote the eigenvalue of the analytical solution at the m-th feature point; ∈ represents a small value offset term to prevent the denominator from being zero;

[0048] Adaptive parameter adjustment formula:

[0049]

[0050] In the formula, α adapt Denote the adaptive adjustment coefficient, which is used to dynamically adjust the interpolation parameters; X prev Denote the interpolation structure of the previous iteration; ρ represents the smoothing parameter to prevent the denominator from being zero; ω represents the second derivative weight coefficient; Θ(X interp ) represents the smoothing function of the interpolation structure.

[0051] As a further improvement of the present invention, the smelting process control module includes:

[0052] A real-time data dynamic acquisition sub-module, which is used to receive the real-time data of the data acquisition module and the furnace body flying sword data calculation module, including the molten pool temperature distribution, the melt splashing situation, and the lance position information, analyze the data, and obtain a data set;

[0053] A temperature and liquid level analysis sub-module, which is used to preprocess the data set, divide the data set into a training set, a test set, and a validation set; construct a melt temperature and liquid level analysis model, and use the training set to train the melt temperature and liquid level analysis model;

[0054] A simulation and verification liquid level model sub-module, which is used to input the high-temperature melt temperature and splashing data in the top-blown furnace collected in real time into the melt temperature and liquid level analysis model for analysis, and automatically adjust the injection position and angle of the lance according to the analysis results.

[0055] As a further improvement of the present invention, the temperature and liquid level analysis sub-module includes:

[0056] A data collection and preprocessing unit, which is used to obtain key parameter data of the liquid level and temperature in real time and store them in a database, and perform preprocessing operations such as removing missing values and outliers. The temperature and liquid level are used as the main input variables, and the factors affecting the spray gun adjustment are used as the secondary input variables;

[0057] A unit for constructing a melt temperature and liquid level model, which is used to form a data set from the preprocessed data, and divide the data set into a training set, a validation set, and a test set; construct a melt temperature and liquid level model, and use the training set to fit the melt temperature and liquid level model;

[0058] An evaluation and optimization unit, which is used to learn the relationship between the melt temperature and liquid level model for temperature and liquid level changes; input real-time data into the melt temperature and liquid level model for evaluation, obtain the probability values of temperature and liquid level changes according to the evaluation results, and adjust the spray gun according to the probability values.

[0059] As a further improvement of the present invention, the evaluation and optimization unit includes:

[0060] An output feedback sub-unit, which is used to input real-time data into the melt temperature and liquid level model for evaluation, obtain the probability values of temperature and liquid level changes according to the evaluation results, and trigger the spray gun adjustment mechanism when the probability value exceeds the preset threshold;

[0061] An intelligent decision-making sub-unit, which is used to obtain the end pressure value of the spray gun, calculate the immersion depth difference of the spray gun by comparing it with the standard value; and judge whether the current liquid level height and temperature meet the set standard values. If it exceeds the preset range, trigger the spray gun adjustment mechanism;

[0062] A dynamic spray gun adjustment sub-unit, which is used to monitor the high-temperature melt parameters of the top-blown converter in real time. If it exceeds the evaluation value of the melt temperature and liquid level model, give an early warning; and continuously update the parameters of the melt temperature and liquid level model according to the real-time high-temperature melt parameters, and store the adjustment process.

[0063] To achieve the above object, the present invention also provides the following technical solutions:

[0064] A method for on-line monitoring of the high-temperature melt temperature and splash of a top-blown converter, which is applied to the on-line monitoring system of the high-temperature melt temperature and splash of the top-blown converter. The method for on-line monitoring of the high-temperature melt temperature and splash of the top-blown converter includes:

[0065] Thermocouples at the slag height position on the inner wall of the top-blown converter and infrared thermometers on the inner wall of the top-blown converter detect the temperature at different positions of the molten pool and the splash situation of the melt, and transmit the detected data to the data calculation module in real time;

[0066] The method of punching the interface with real-time data is used to obtain the specific situation of the melt splashing onto the wall surface, and the visualization of the splash impact on the furnace body is realized according to the specific situation of the melt splashing onto the wall surface; and the visualized data is transmitted to the smelting process control module;

[0067] Based on the molten bath temperature distribution and the melt splashing situation, the flow rates of pulverized coal, dry powder and gas are adjusted, a melt temperature and liquid level model is constructed, the molten bath temperature and the melt splashing situation are evaluated, and the smelting process is controlled according to the evaluation results.

[0068] The data acquisition module of the top-blown furnace of the present invention uses thermocouples and infrared thermometers installed at the slag height position on the inner wall surface of the top-blown furnace to detect the temperature and melt splashing situation at different positions of the molten bath in real time; the detected data is transmitted to the data calculation module in real time to provide a basis for analysis and control; the furnace body splash data calculation module processes the real-time data using the interface reconstruction method to obtain the specific situation of the melt splashing onto the wall surface; according to the specific situation of the melt splashing, the visualization of the splash impact on the furnace body is realized, and the visualized data is transmitted to the smelting process control module; the smelting process control module automatically adjusts the flow rates of pulverized coal, dry powder and gas based on the molten bath temperature distribution and the melt splashing situation; by precisely controlling these smelting parameters, the optimization and control of the smelting process are realized. Description of the Drawings

[0069] Figure 1 It is a schematic diagram of the functional modules of an embodiment of the high-temperature melt temperature and splash on-line monitoring system of the top-blown furnace of the present invention;

[0070] Figure 2 It is the overall flow chart of the high-temperature melt temperature on-line monitoring system of an embodiment of the high-temperature melt temperature and splash on-line monitoring system of the top-blown furnace of the present invention;

[0071] Figure 3 It is a schematic diagram of the functional modules of the data acquisition module of the top-blown furnace of an embodiment of the high-temperature melt temperature and splash on-line monitoring system of the top-blown furnace of the present invention;

[0072] Figure 4 It is a schematic diagram of the layout method of the first infrared thermometer of an embodiment of the high-temperature melt temperature and splash on-line monitoring system of the top-blown furnace of the present invention;

[0073] Figure 5 It is a schematic diagram of the layout method of the second infrared thermometer of an embodiment of the high-temperature melt temperature and splash on-line monitoring system of the top-blown furnace of the present invention;

[0074] Figure 6 It is a schematic diagram of the arrangement of the first thermocouple of an embodiment of the high-temperature melt temperature and splash on-line monitoring system of the top-blown furnace of the present invention;

[0075] Figure 7Schematic diagram of the functional module of the splash data calculation module in an embodiment of the high-temperature melt temperature and splash on-line monitoring system for the top-blown converter of the present invention;

[0076] Figure 8 Schematic diagram of the arrangement mode of the second hot thermocouple in an embodiment of the high-temperature melt temperature and splash on-line monitoring system for the top-blown converter of the present invention;

[0077] Figure 9 Schematic diagram of the reconstruction method of the splash melt interface with different numbers of high-temperature points in an embodiment of the high-temperature melt temperature and splash on-line monitoring system for the top-blown converter of the present invention;

[0078] Figure 10 Schematic diagram of the melt profile obtained by interface reconstruction in an embodiment of the high-temperature melt temperature and splash on-line monitoring system for the top-blown converter of the present invention;

[0079] Figure 11 Schematic diagram of the functional module of the reduced melt interface sub-module in an embodiment of the high-temperature melt temperature and splash on-line monitoring system for the top-blown converter of the present invention;

[0080] Figure 12 Schematic diagram of the functional module of the interface reconstruction unit in an embodiment of the high-temperature melt temperature and splash on-line monitoring system for the top-blown converter of the present invention;

[0081] Figure 13 Schematic diagram of the functional module of the simulation verification unit in an embodiment of the high-temperature melt temperature and splash on-line monitoring system for the top-blown converter of the present invention;

[0082] Figure 14 Schematic diagram of the functional module of the smelting process control module in an embodiment of the high-temperature melt temperature and splash on-line monitoring system for the top-blown converter of the present invention;

[0083] Figure 15 Schematic diagram of the functional module of the temperature and liquid level analysis sub-module in an embodiment of the high-temperature melt temperature and splash on-line monitoring system for the top-blown converter of the present invention;

[0084] Figure 16 Schematic diagram of the functional module of the evaluation and optimization unit in an embodiment of the high-temperature melt temperature and splash on-line monitoring system for the top-blown converter of the present invention;

[0085] Figure 17 Flowchart of the steps in an embodiment of the high-temperature melt temperature and splash on-line monitoring method for the top-blown converter of the present invention;

[0086] Figure 18 Schematic diagram of the structure of an embodiment of the electronic device of the present invention;

[0087] Figure 19 Schematic diagram of the structure of an embodiment of the storage medium of the present invention. Specific Embodiments

[0088] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0089] The terms "first", "second", and "third" in the present invention are only used for descriptive purposes and cannot be construed as indicating or implying relative importance or implicitly specifying the quantity of the indicated technical features. Thus, the features defined with "first", "second", and "third" may explicitly or implicitly include at least one of such features. In the description of the present invention, the meaning of "a plurality" is at least two, such as two, three, etc., unless otherwise specifically defined. All directional indications (such as up, down, left, right, front, back...) in the embodiments of the present invention are only used to explain the relative positional relationship and movement conditions between components in a specific posture (as shown in the accompanying drawings). If the specific posture changes, the directional indications will also change accordingly. In addition, the terms "comprising" and "having" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or device that includes a series of steps or units is not limited to the listed steps or units, but optionally further includes steps or units not listed, or optionally further includes other steps or units inherent to these processes, methods, products, or devices.

[0090] Referring to "embodiments" herein means that the specific features, structures, or characteristics described in connection with the embodiments can be included in at least one embodiment of the present invention. The phrase appears in various places in the specification and does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment mutually exclusive with other embodiments. Those skilled in the art will explicitly and implicitly understand that the embodiments described herein can be combined with other embodiments.

[0091] As Figure 1 shown, this embodiment provides an embodiment of an online monitoring system for the temperature and splash of high-temperature melt in a top-blown converter. In this embodiment, the online monitoring system for the temperature and splash of high-temperature melt in the top-blown converter specifically includes:

[0092] A top-blown converter data acquisition module 1, which is used to detect the temperature at different positions of the molten pool and the splash situation of the melt by the thermocouples at the slag height position on the inner wall surface of the top-blown converter and the infrared thermometer on the inner wall surface of the top-blown converter, and transmit the detected data to the data calculation module 2 in real time;

[0093] The furnace body splash data calculation module 2 is used to reconstruct the interface of real-time data to obtain the specific situation of the melt splashing onto the wall surface, visualize the splash impact on the furnace body according to the specific situation of the melt splashing onto the wall surface; and transmit the visualized data to the smelting process control module 3;

[0094] The smelting process control module 3 is used to adjust the flow rates of pulverized coal, dry powder and gas based on the molten pool temperature distribution and the melt splash situation, construct a molten metal temperature and liquid level model, evaluate the molten pool temperature and the melt splash situation, and control the smelting process according to the evaluation results.

[0095] Preferably, in this embodiment, the top-blown furnace data acquisition module 1 uses thermocouples and infrared thermometers installed at the slag height position on the inner wall surface of the top-blown furnace to detect the temperature and melt splash situation at different positions of the molten pool in real time; the detected data is transmitted to the data calculation module in real time to provide a basis for analysis and control; the furnace body splash data calculation module 2 processes the real-time data using the interface reconstruction method to obtain the specific situation of the melt splashing onto the wall surface; according to the specific situation of the melt splash, visualize the splash impact on the furnace body and transmit the visualized data to the smelting process control module; the smelting process control module 3 automatically adjusts the flow rates of pulverized coal, dry powder and gas based on the molten pool temperature distribution and the melt splash situation; by precisely controlling these smelting parameters, optimize and control the smelting process.

[0096] In summary, the real-time and accurate data acquisition of the top-blown furnace data acquisition module 1 in this embodiment is the premise for realizing precise control of the smelting process; through this module, abnormalities in the molten pool temperature and melt splash can be detected in a timely manner, providing a basis for timely adjustment of smelting parameters; the visualization technology of the furnace body splash data calculation module 2 makes the melt splash situation in the smelting process more intuitive, facilitating the understanding and judgment of operators; through this module, the impact of melt splash on the furnace body can be evaluated more precisely, providing an important reference for formulating and adjusting smelting strategies; the precise smelting process control of the smelting process control module 3 can improve the smelting efficiency and reduce energy consumption; through this module, smelting quality problems caused by melt splash and temperature unevenness can be reduced, improving product quality; automatic control can also reduce the labor intensity of operators and improve production safety (for the specific principle, refer to the appendix Figure 2, specifically including an electronic computer 4, a first blower 5, a second blower 6, a third blower 7, a dry powder feeding device 8, a pulverized coal feeding device 9, a top-blown converter 10, an infrared thermometer 14, and a thermocouple 15; among them, the electronic computer 4 is connected to the top-blown converter data acquisition module 1, and the first blower 5, the second blower 6, the third blower 7, the dry powder feeding device 8, and the pulverized coal feeding device 9 are connected to the electronic computer 4 through data lines. The first blower 5, the second blower 6, the third blower 7, the dry powder feeding device 8, and the pulverized coal feeding device 9 are connected to the infrared thermometer 14. The infrared thermometer 14 is placed inside the top-blown converter 10, and several thermocouples 15 are installed on the inner wall of the top-blown converter 10. The thermocouple 15 is connected to the top-blown converter data acquisition module 1).

[0097] Furthermore, as Figure 3 shown, the top-blown converter data acquisition module 1 specifically includes:

[0098] An infrared thermometer installation sub-module 11, which is used to add a fourth layer of sleeve inside the top-blown lance, and arrange the infrared thermometer on the inner wall of the fourth layer of sleeve of the top-blown converter; isolate the particles outside the infrared ray irradiation path of the infrared thermometer, and monitor the temperature of the molten bath normally;

[0099] An infrared thermometer cooling sub-module 12, which is used to form a high-speed gas channel between the third layer of sleeve and the fourth layer of sleeve, and cool the infrared thermometer through the gas in this channel; and the third layer of sleeve and the fourth layer of sleeve are connected by welding, and four infrared thermometers are evenly arranged on the outer wall of the fourth layer;

[0100] A thermocouple arrangement sub-module 13, which is used to arrange the thermocouples around the wall of the top-blown converter, part of them are at the height of the slag layer, and part of them are above the height of the molten bath surface.

[0101] Preferably, in this embodiment, the infrared thermometer installation sub-module 11 adds a fourth layer of sleeve inside the top-blown lance and arranges the infrared thermometer on the inner wall of the fourth layer of sleeve; it can effectively isolate the particles outside the infrared ray irradiation path of the infrared thermometer and avoid the interference of particles on temperature measurement; the infrared thermometer can monitor the temperature of the molten bath normally and accurately; the infrared thermometer cooling sub-module 12 forms a high-speed gas channel between the third layer of sleeve and the fourth layer of sleeve; the gas in this channel cools the infrared thermometer to prevent it from being damaged due to high temperature; at the same time, the third layer of sleeve and the fourth layer of sleeve are connected by welding, enhancing the structural stability and reliability; four infrared thermometers are evenly arranged on the outer wall of the fourth layer to ensure the comprehensive monitoring of the temperature of the molten bath; the thermocouple arrangement sub-module 13 arranges the thermocouples around the wall of the top-blown converter, part of them are at the height of the slag layer, and part of them are above the height of the molten bath surface; it can comprehensively and accurately monitor the temperature at different heights of the molten bath.

[0102] In summary, the infrared thermometer installation sub-module 11 in this embodiment ensures that the infrared thermometer can work stably in a harsh smelting environment and provide reliable temperature data; it helps to improve the accuracy and stability of the smelting process; the infrared thermometer cooling sub-module 12 is an important measure to protect it from high-temperature damage; it extends the service life of the infrared thermometer, reduces the maintenance cost; it improves the accuracy and comprehensiveness of temperature monitoring; the thermocouple arrangement sub-module 13 is a commonly used temperature monitoring tool in the smelting process; it realizes the accurate monitoring of the molten bath temperature and provides an important basis for the control of the smelting process; the arrangement of thermocouples at different heights helps to understand the temperature distribution inside the molten bath and provides a reference for optimizing smelting parameters (for the specific principle, refer to Appendix Figure 4 Appendix Figure 5 Appendix Figure 6 , the first blower 5, the second blower 6, the third blower 7, the infrared thermometer 14, the first-layer sleeve 16, the second-layer sleeve 17, the third-layer sleeve 18, the fourth-layer sleeve 19, the cyclone 26; among them, the outlet of the first blower 5 is connected to the first-layer sleeve 16, the second blower 6 is connected to the second-layer sleeve 17, the third blower 7 is connected to the third-layer sleeve 18, the cyclone 26 is installed on the first-layer sleeve 16, the second-layer sleeve 17, the third-layer sleeve 18, the fourth-layer sleeve 19 is installed inside the bottom of the top-blown furnace, and the infrared thermometer 14 is installed on the fourth-layer sleeve 19; Figure 4 Figure (a) of Figure 4 shows the structural schematic diagram of the first-layer sleeve 16, the second-layer sleeve 17, and the third-layer sleeve 18, Figure 5 Figure (b) of

[0103] shows the structural schematic diagram of the fourth-layer sleeve 19; Figure 7 Figure (a) and (b) of

[0104] both show the structural schematic diagrams of the infrared thermometer 14, the third-layer sleeve 18, and the fourth-layer sleeve 19).

[0105] The thermocouple grouping sub-module 22. For the thermocouples, they can be divided into 13 groups horizontally and 9 groups vertically, with a total of 117 groups. That is, the first row consists of 13 groups such as (TA1, TA2, TB1, TB2), (TB1, TB2, TC1, TC2), (TC1, TC2, TD1, TD2), (TD1, TD2, TE3, TE4), (TE3, TE4, TF1, TF2), (TF1, TF2, TG1, TG2) ……; the second row consists of 13 groups such as (TA2, TA3, TB2, TB3), (TB2, TB3, TC2, TC3), (TC2, TC3, TD2, TD3), (TD2, TD3, TE2, TE3), (TE2, TE3, TF2, TF3), (TF2, TF3, TG2, TG3) ……, and so on;

[0106] The visualization display sub-module 23 is used to transfer the collected data to the computer in real time. When the thermocouples are covered by splashing droplets, the temperature data transferred to the computer increases significantly; for each group of thermocouples, there are four ways to restore the shape of the phase interface of the melt at the position where it splashes onto the wall surface.

[0107] Preferably, in this embodiment, the melt interface restoration sub-module 21 is based on the temperature data of the thermocouples and uses the interface reconstruction method to restore the situation of the melt interface splashing onto the wall surface; the abscissa of the thermocouples is represented by English letters, and the ordinate is represented by numbers. This identification method makes the position information of the thermocouples clearer and easier to manage; by grouping every four adjacent thermocouples into one group, the changes in the melt interface can be monitored and analyzed more carefully; the thermocouple grouping sub-module 22 divides the thermocouples into 13 groups horizontally and 9 groups vertically, with a total of 117 groups; each group consists of four adjacent thermocouples. This grouping method makes the data monitoring and analysis more systematic and structured; through the detailed grouping, the tiny changes in the melt interface can be captured more accurately; the visualization display sub-module 23 transfers the collected data to the computer in real time, realizing the visualization display of the data; when the thermocouples are covered by splashing droplets, the temperature data transferred to the computer increases significantly, and this change can be intuitively reflected in the visualization display; each group of thermocouples has four ways to restore the shape of the phase interface of the melt at the position where it splashes onto the wall surface. This diverse restoration method makes the visualization display of the melt interface richer and more accurate.

[0108] In summary, the reduction of the melt interface in the melt interface sub-module 21 of this embodiment helps to understand the behavior characteristics of the melt during the smelting process and provides an important reference for optimizing smelting parameters; the application of the interface reconstruction method improves the accuracy and reliability of melt interface monitoring, helps to detect and handle abnormal situations during the smelting process in a timely manner; through clear thermocouple position identification and detailed grouping methods, data analysis and processing are made more efficient and accurate; the thermocouple grouping sub-module 22 improves the resolution and sensitivity of melt interface monitoring, helps to detect and handle potential problems during the smelting process in a timely manner; the systematic and structured data monitoring and analysis methods make the control of the smelting process more precise and efficient; it is possible to understand more comprehensively the behavior characteristics of the melt during the smelting process and provide an important basis for optimizing smelting strategies; the visualization display sub-module 23 makes the data monitoring and analysis during the smelting process more intuitive and easy to understand; by transmitting data to the computer in real time and performing visualization display, abnormal situations during the smelting process can be detected in a timely manner, providing the possibility for quick response and handling; the diverse melt interface shape reduction methods improve the accuracy and reliability of visualization display, helping operators to more accurately judge the behavior characteristics of the melt and take corresponding control measures (for specific principles, refer to Appendix Figure 8 Appendix Figure 9 Appendix Figure 10 , Figure 8 In which, 20 represents the melt splashed onto the wall surface, and 15 represents the thermocouple; Appendix Figure 9 (a) One high-temperature point, (b) two high-temperature points, (c) three high-temperature points, (d) four high-temperature points in Appendix

[0109] Furthermore, as Figure 11 shown, the melt interface reduction sub-module 21 specifically includes:

[0110] A melt temperature acquisition unit 211, which is used to collect melt temperature data through a thermocouple. The abscissa of the thermocouple is represented by an English letter, and the ordinate is represented by a number. Four adjacent thermocouple data are grouped to form a data block;

[0111] An interface reconstruction unit 212, which is used to utilize interface interpolation technology to update the position of the melt interface according to the collected temperature data; perform interpolation calculation on the interface position according to the thermocouple data to obtain the interface shape; adjust the grid structure according to the interface shape;

[0112] A simulation verification unit 213, which is used to simulate the reconstructed melt interface to verify whether its dynamic behavior conforms to the preset physical phenomena; if it conforms to the preset physical phenomena, analyze the physical signs of the reconstructed melt interface and store them; if not, perform interface interpolation and grid processing again.

[0113] Preferably, in this embodiment, the melt temperature acquisition unit 211 accurately acquires the temperature data of the melt through a thermocouple; the abscissa of the thermocouple is represented by English letters, and the ordinate is represented by numbers. This identification method is clear and convenient for data recording and analysis; this unit groups the data of four adjacent thermocouples to form a data block. This data processing method improves the locality and correlation of the data, which is beneficial for subsequent data analysis and processing; the interface reconstruction unit 212 uses the interface interpolation technology to dynamically update the position of the melt interface according to the acquired temperature data; the shape of the melt interface is obtained through interpolation calculation, and the grid structure is adjusted according to the interface shape to adapt to the change of the melt interface; the accuracy and efficiency of the simulation are improved; the simulation verification unit 213 simulates the reconstructed melt interface to verify whether its dynamic behavior conforms to the preset physical phenomena; if the simulation result is consistent with the preset physical phenomena, the characteristics of the reconstructed melt interface are analyzed and stored; if not, the interface interpolation and meshing processing are performed again; this feedback mechanism ensures the accuracy and reliability of the simulation result.

[0114] In summary, the melt temperature acquisition unit 211 in this embodiment is the basis for melt interface reconstruction and simulation verification, which helps to improve the accuracy and reliability of the entire system; it makes the management and analysis of data more efficient and reduces the complexity of data processing; through this unit, the temperature information of the melt can be obtained in real time, providing strong support for the monitoring and optimization of the production process; the interface reconstruction unit 212 helps to improve the controllability and stability of the production process; through interpolation calculation and grid adjustment, the flow and change process of the melt can be simulated more accurately, providing a scientific basis for production optimization; it makes the monitoring and analysis of the melt interface more intelligent and automated, reducing the cost and risk of manual intervention; the simulation verification unit 213 helps to improve the robustness and adaptability of the entire system; by storing and analyzing the characteristics of the reconstructed melt interface, a scientific basis can be provided for production optimization and decision-making; the efficiency and accuracy of simulation verification are improved, and the decision-making risk caused by inaccurate simulation results is reduced.

[0115] Furthermore, as Figure 12 shown, the interface reconstruction unit 212 specifically includes:

[0116] The hot spot coupling data processing subunit 2121 is used to analyze the heat conduction characteristics of the melt interface and extract key parameters according to the acquired hot spot coupling data; among them, the key parameters include temperature gradient and heat flux, etc.;

[0117] The new interface position calculation subunit 2122 is used to take the acquired temperature data as input and calculate the new position of the melt interface through an interpolation algorithm; for complex scenarios, the new position of the melt interface is calculated in combination with momentum interpolation and mass conservation conditions;

[0118] The interface shape acquisition subunit 2123 is configured to obtain the collective shape of the interface based on the updated interface position; adjust the grid structure according to the interface shape, and adopt an adaptive grid reconstruction technique to dynamically adjust the grid density according to the complexity of the interface.

[0119] Among them, the hot spot coupling data processing subunit is used to analyze the heat conduction characteristics of the melt interface and extract key parameters such as temperature gradient and heat flux. The calculation formula is:

[0120]

[0121] In the formula, T(x,y,t) represents the temperature distribution of the melt interface at coordinates (x,y) and time t; represents the temperature gradient;

[0122] The new interface position calculation subunit is used to calculate the new position of the melt interface through an interpolation algorithm based on the collected temperature data. The calculation formula is:

[0123]

[0124] In the formula, L new (x,y,t) represents the updated position of the melt interface; ΔL(x,y,t) represents the change in the interface position;

[0125] Preferably, the hot spot coupling data processing subunit 2121 in this embodiment can efficiently process and analyze the collected hot spot coupling data; accurately extract the heat conduction characteristics of the melt interface through a dedicated analysis algorithm; accurately calculate key parameters such as temperature gradient and heat flux to provide a basis for calculation and simulation; the new interface position calculation subunit 2122 can accurately calculate the new position of the melt interface based on the collected temperature data using the interpolation algorithm; in complex scenarios, combined with momentum interpolation and mass conservation conditions, it further improves the calculation accuracy and reliability; the interface shape acquisition subunit 2123 can accurately obtain the geometric shape of the interface based on the updated interface position using the shape interpolation algorithm; according to the complexity of the interface shape, it adopts an adaptive grid reconstruction technique to dynamically adjust the grid density and improve the accuracy and efficiency of the simulation.

[0126] In summary, the key parameters extracted by the hot spot coupling data processing subunit 2121 in this embodiment can be used to evaluate and optimize the heat conduction performance, improve the efficiency of material processing and manufacturing; provide reliable data support for the dynamic simulation and prediction of the melt interface; the calculation of the new interface position subunit 2122 to update the position of the melt interface in real time is crucial for monitoring and controlling the material processing process; accurately calculating the new interface position helps to optimize the process parameters, improve the product quality and processing efficiency; provides real-time and accurate position information for the dynamic simulation and prediction of the melt interface; the interface shape acquisition subunit 2123 accurately obtaining the geometric shape of the melt interface is crucial for understanding the interface evolution in the material processing process; the adaptive mesh reconstruction technology can adjust the mesh density according to the actual situation and optimize the use of computing resources; provides a reliable mesh basis and shape information for the high-precision simulation and prediction of the melt interface.

[0127] Further, as Figure 13 shown, the simulation verification unit 213 specifically includes:

[0128] The mesh structure adjustment subunit 2131 is used to perform mesh interpolation at the new interface position, generate a new mesh structure, and perform continuous interpolation; and adjust the mesh structure through an optimization algorithm;

[0129] The structure verification subunit 2132 is used to compare the interpolated structure with the analytical solution, calculate and evaluate the interpolation accuracy; if it is greater than the preset interpolation accuracy value, adjust the interpolation parameters; iterate sequentially until it is less than the preset interpolation accuracy value;

[0130] The melt simulation subunit 2133 is used to simulate the reconstructed melt interface to verify whether its dynamic behavior conforms to the preset physical phenomena; if it conforms to the preset physical phenomena, analyze the signs of the reconstructed melt interface and store them; if not, re-perform interface interpolation and meshing processing.

[0131] Among them, in the structure verification subunit 2132, the interpolated structure is compared with the analytical solution, and the interpolation accuracy is calculated and evaluated. The interpolation error calculation formula:

[0132]

[0133] In the formula, X interp represents the interpolated structure, the mesh data generated by the mesh structure adjustment subunit; X analytic represents the analytical solution, that is, the theoretically accurate structure data; N represents the total number of grid points; w i represents the weight coefficient of the i-th grid point, which is used to reflect the importance in the actual system; γ represents the smoothing constraint coefficient, which is used to control the smoothness of the interpolation result; M represents the total number of dimensions (such as the \(x,y,z\) dimensions in 2D or 3D); fj The smoothing factor for the j-th dimension, which is used to impose additional constraints in a specific dimension; represents the overall error comprehensively measuring the interpolation structure and the analytical solution, while adding smoothing constraints to enhance the physical feasibility of the interpolation result.

[0134] Dynamic iterative adjustment formula:

[0135]

[0136] In the formula, represents the interpolation structure of the k-th iteration; η represents the iteration step size, controlling the adjustment amplitude; represents the gradient of the interpolation error function Ψ, which is used to guide the iteration direction; L represents the total number of additional constraint conditions; κ l represents the weight coefficient of the l-th constraint condition; A l represents the coefficient matrix of the l-th constraint condition; B l represents the target value matrix of the l-th constraint condition. It means dynamically adjusting the interpolation structure by the gradient descent method to make it gradually approach the analytical solution and satisfy additional constraint conditions.

[0137] Precision evaluation convergence formula:

[0138]

[0139] In the formula, Z represents the normalization coefficient, which is used to ensure that the range of the convergence value is within a reasonable interval; Q represents the number of key feature points; g m represents the evaluation weight of the m-th feature point; represents the eigenvalue of the interpolation structure at the m-th feature point; represents the eigenvalue of the analytical solution at the m-th feature point; ∈ represents a small value offset term to prevent the denominator from being zero. It means measuring the local precision between the interpolation structure and the analytical solution through logarithmic error to ensure the accuracy of key feature points.

[0140] Adaptive parameter adjustment formula:

[0141]

[0142] In the formula, α adapt represents the adaptive adjustment coefficient, which is used to dynamically adjust the interpolation parameters; X prev represents the interpolation structure of the previous iteration; ρ represents the smoothing parameter to prevent the denominator from being zero; ω represents the second derivative weight coefficient; Θ(X interp)A smoothness function representing the interpolation structure. It represents dynamically adjusting the interpolation parameters according to the error change rate and smoothness to improve the convergence speed and accuracy. Calculate the interpolation error to evaluate the overall deviation between the current interpolation structure and the analytical solution; gradually optimize the interpolation structure through dynamic iterative adjustment formulas; use the precision evaluation convergence formula to verify the local precision of key feature points; dynamically optimize the interpolation parameters according to the adaptive parameter adjustment formula; jointly implement the functions of the structure verification subunit to ensure that the interpolation precision meets the preset requirements.

[0143] Preferably, the mesh structure adjustment subunit 2131 in this embodiment performs mesh interpolation at the new interface position to ensure that the mesh structure can accurately reflect the changes in the melt interface; generate a smooth and continuous mesh structure through continuous interpolation methods to improve the accuracy and stability of the simulation; use an optimization algorithm to adjust the mesh structure to reduce mesh distortion and improve the calculation efficiency; the structure verification subunit 2132 compares the interpolation structure with the analytical solution to quantitatively evaluate the interpolation accuracy; if the interpolation accuracy does not meet the preset requirements, adjust the interpolation parameters and gradually approach the true solution through an iterative process; ensure that the interpolation structure meets the accuracy requirements to provide a reliable guarantee for simulation and analysis; the melt simulation subunit 2133 simulates the reconstructed melt interface to verify whether its dynamic behavior conforms to the preset physical phenomena; if the simulation results are consistent with the preset physical phenomena, analyze the characteristics of the reconstructed melt interface, such as temperature distribution, flow velocity, etc.; store the analysis results to provide data support for material processing and optimization; if the simulation results do not conform to the preset physical phenomena, re-perform interface interpolation and meshing to ensure the accuracy of the simulation.

[0144] In summary, the precise mesh structure of the mesh structure adjustment subunit 2131 in this embodiment is the basis for simulating the dynamic behavior of the melt interface; mesh adjustment can ensure the accuracy of the simulation results and provide reliable data for subsequent analysis and storage; optimizing the mesh structure can reduce calculation errors and improve the convergence speed and stability of the simulation; the structure verification subunit 2132 verifying the accuracy of the interpolation structure is the key to ensuring the reliability of the simulation results; by iteratively adjusting the interpolation parameters, the simulation accuracy can be continuously improved to meet the actual application requirements; provide an accurate mesh structure and data support for melt simulation and analysis; the melt simulation subunit 2133 can intuitively display the dynamic behavior of the melt interface and provide a powerful tool for understanding and optimizing the material processing process; by analyzing the characteristics of the reconstructed melt interface, the physical properties and behavior laws of the melt interface can be deeply understood; the stored analysis results provide valuable data support for subsequent material processing optimization, process parameter adjustment, etc.; re-performing interface interpolation and meshing can ensure the accuracy of the simulation results and improve the reliability of the simulation.

[0145] Furthermore, as Figure 14 shown, the smelting process control module 3 specifically includes:

[0146] The real-time data dynamic acquisition sub-module 31 is used to receive the real-time data from the data acquisition module 1 and the furnace body flying sword data calculation module 2, including information such as the molten pool temperature distribution, the melt splashing situation, and the lance position, analyze the data, and obtain a data set;

[0147] The temperature and liquid level analysis sub-module 32 is used to preprocess the data set, divide the data set into a training set, a test set, and a validation set; construct a melt temperature and liquid level analysis model, and use the training set to train the melt temperature and liquid level analysis model;

[0148] The simulation and verification liquid level model sub-module 33 is used to input the high-temperature melt temperature and splashing data in the top-blown furnace collected in real time into the melt temperature and liquid level analysis model for analysis, and automatically adjust the spraying position and angle of the lance according to the analysis results.

[0149] Preferably, the real-time data dynamic acquisition sub-module 31 of this embodiment can receive the data from the data acquisition module 1 and the furnace body flying sword data calculation module 2 in real time, ensuring the timeliness and accuracy of the data; the received data includes various information such as the molten pool temperature distribution, the melt splashing situation, and the lance position, providing a comprehensive data set for subsequent analysis; through preliminary analysis of the received data, a data set is formed, providing a basis for subsequent processing and modeling; the temperature and liquid level analysis sub-module 32 divides the data set into a training set, a test set, and a validation set, providing a basis for the training and verification of the model; construct a melt temperature and liquid level analysis model, which can analyze and predict the temperature and liquid level of the melt based on the input data; use the training set to train the model so that it can accurately identify and analyze the temperature and liquid level information of the melt; the simulation and verification liquid level model sub-module 33 inputs the high-temperature melt temperature and splashing data in the top-blown furnace collected in real time into the melt temperature and liquid level analysis model for analysis; according to the analysis results of the model, automatically adjust the spraying position and angle of the lance to optimize the temperature and liquid level state of the melt; through continuous simulation verification and adjustment, the model and analysis results can be further optimized, improving the stability and efficiency of the production process.

[0150] In summary, the real-time data dynamic acquisition sub-module 31 in this embodiment helps to promptly detect problems and take corresponding measures, improving production efficiency and safety; it provides rich information for modeling and analysis, contributing to enhancing the accuracy and reliability of the model; the temperature and liquid level analysis sub-module 32 provides strong support for simulation verification and automatic adjustment through data preprocessing and model construction; the training and optimization of the model help to improve the accuracy and efficiency of analysis, providing a scientific basis for decision-making in the production process; the simulation verification liquid level model sub-module 33 helps to realize the automation and intelligence of the production process, improving production efficiency and product quality; through simulation verification and continuous adjustment, the parameter settings in the production process can be continuously optimized, reducing production costs and energy consumption, and improving the overall economic benefits.

[0151] Furthermore, as Figure 15 shown, the temperature and liquid level analysis sub-module 33 specifically includes:

[0152] The data collection and preprocessing unit 331 is used to obtain key parameter data such as liquid level and temperature in real time and store them in the database, perform preprocessing operations such as removing missing values and outliers, take temperature and liquid level as the main input variables, and take factors affecting spray gun adjustment as secondary input variables;

[0153] Among them, the factors affecting spray gun adjustment include oxygen flow rate and spray gun height, etc.;

[0154] The melt temperature and liquid level model construction unit 332 is used to form a data set from the preprocessed data, divide the data set into a training set, a validation set, and a test set; construct a melt temperature and liquid level model, and use the training set to fit the melt temperature and liquid level model;

[0155] The evaluation and optimization unit 333 is used to learn the relationship between the melt temperature and liquid level model for temperature and liquid level changes; input real-time data into the melt temperature and liquid level model for evaluation, obtain the probability values of temperature and liquid level changes according to the evaluation results, and adjust the spray gun according to the probability values.

[0156] Preferably, the data collection and preprocessing unit 331 in this embodiment can collect key parameter data such as liquid level and temperature in real time to ensure the timeliness and accuracy of the data; store the collected data in a database for subsequent data analysis and processing; improve the data quality by removing missing values and outliers, etc., and provide a reliable data basis for modeling; use temperature and liquid level as the main input variables and the factors affecting the spray gun adjustment as the secondary input variables to provide clear input features for model construction; the melt temperature and liquid level model unit 332 divides the preprocessed data into a training set, a validation set, and a test set, providing a basis for model training and validation; constructs a melt temperature and liquid level model based on the divided data set, and this model can predict the temperature and liquid level of the melt based on the input variables; uses the training set to fit the model so that it can accurately reflect the relationship between temperature and liquid level; the evaluation and optimization unit 333 can accurately predict the future temperature and liquid level states; inputs the real-time data into the model for evaluation to obtain the probability values of temperature and liquid level changes; automatically adjusts the parameters of the spray gun according to the probability values output by the model to optimize the temperature and liquid level states of the melt; through continuous evaluation and feedback, the model can be further optimized to improve its prediction ability and adaptability.

[0157] In summary, the data collection and preprocessing unit 331 in this embodiment helps to detect problems in a timely manner and take corresponding measures to improve production efficiency and safety; data preprocessing and determination of input variables provide a clear data framework and feature selection for modeling, which helps to improve the accuracy and reliability of the model; the melt temperature model unit 332 provides strong support for model evaluation and optimization through data set division and model construction; model fitting and optimization help to improve the accuracy and efficiency of prediction, providing a scientific basis for decision-making in the production process; the real-time evaluation and adjustment function of the evaluation and optimization unit 333 helps to realize the automation and intelligence of the production process, improving production efficiency and product quality; through model learning and continuous optimization, the prediction accuracy can be continuously improved, production costs and energy consumption can be reduced, and overall economic benefits can be increased; automatically adjusting the parameters of the spray gun helps to achieve fine control of the production process and improve the stability and consistency of products.

[0158] Furthermore, as Figure 16 shown, the evaluation and optimization unit 333 specifically includes:

[0159] The output feedback subunit 3331 is used to input real-time data into the melt temperature and liquid level model for evaluation, obtain the probability values of temperature and liquid level changes according to the evaluation results, and trigger the spray gun adjustment mechanism when the probability value exceeds the preset threshold;

[0160] The intelligent decision-making sub-unit 332 is used to obtain the end pressure value of the spray gun, calculate the immersion depth difference of the spray gun by comparing with the standard value, and judge whether the current liquid level height and temperature meet the set standard values. If they exceed the preset range, the spray gun adjustment mechanism is triggered.

[0161] The dynamic spray gun adjustment sub-unit 333 is used to monitor the parameters of the high-temperature melt in the top-blown converter in real time. If the parameters exceed the evaluation values of the melt temperature and liquid level model, an early warning is given. The parameters of the melt temperature and liquid level model are continuously updated according to the real-time high-temperature melt parameters, and the adjustment process is stored.

[0162] Preferably, the output feedback sub-unit 3331 of this embodiment can receive data in real time and input it into the melt temperature and liquid level model for evaluation, so as to obtain the probability values of temperature and liquid level changes. Through the preset threshold, when the evaluation result exceeds the threshold, the spray gun adjustment mechanism can be automatically triggered to achieve timely response. The intelligent decision-making sub-unit 332 can obtain the end pressure value of the spray gun and compare it with the standard value, so as to calculate the immersion depth difference of the spray gun. The current liquid level height and temperature are monitored in real time and compared with the set standard values. When the preset range is exceeded, the spray gun adjustment mechanism is triggered. The dynamic spray gun adjustment sub-unit 333 can monitor the parameters of the high-temperature melt in the top-blown converter in real time. When the parameters exceed the evaluation values of the melt temperature and liquid level model, a warning signal can be sent. The parameters of the melt temperature and liquid level model are continuously updated according to the real-time high-temperature melt parameters to improve the accuracy and adaptability of the model. The adjustment process of the spray gun is stored for easy analysis and optimization.

[0163] In summary, the real-time data evaluation and threshold judgment of the output feedback sub-unit 3331 in this embodiment help to improve the automation level of the production process and reduce manual intervention. The automatic trigger adjustment mechanism can quickly respond to abnormal situations in the production process to ensure the safety and stability of production. The intelligent decision-making sub-unit 332 can accurately control the immersion depth of the spray gun by comparing the end pressure value with the standard value to ensure uniform heating of the melt and splash control. The real-time monitoring and judgment of the liquid level height and temperature help to timely detect and correct deviations in the production process, improving product quality and production efficiency. The real-time monitoring and early warning function of the dynamic spray gun adjustment sub-unit 333 help to timely detect potential risks in the production process and take corresponding measures for prevention. The update of the model parameters can improve the prediction ability of the model, making it better adapt to the changes in the production process. The storage of the adjustment process provides valuable data support for subsequent production optimization and fault troubleshooting.

[0164] Such as Figure 17As shown in the figure, this embodiment also provides an embodiment of the online monitoring method for the temperature and splash of the high-temperature melt in the top-blown converter. In this embodiment, the online monitoring method for the temperature and splash of the high-temperature melt in the top-blown converter is applied to the online monitoring system for the temperature and splash of the high-temperature melt in the top-blown converter as described in the above embodiment. The online monitoring method for the temperature and splash of the high-temperature melt in the top-blown converter specifically includes:

[0165] Step S1: Thermocouples at the slag height position on the inner wall of the top-blown converter and an infrared thermometer on the inner wall of the top-blown converter detect the temperature at different positions of the molten pool and the splash situation of the melt, and transmit the detected data to the data calculation module 2 in real time;

[0166] Step S2: Use the interface punching method for the real-time data to obtain the specific situation of the melt splashing onto the wall, and visualize the splash impact on the furnace body according to the specific situation of the melt splashing onto the wall; and transmit the visualized data to the smelting process control module 3;

[0167] Step S3: Based on the temperature distribution of the molten pool and the splash situation of the melt, adjust the flow rates of pulverized coal, dry powder, and gas, construct a melt temperature and liquid level model, evaluate the temperature of the molten pool and the splash situation of the melt, and control the smelting process according to the evaluation results.

[0168] Preferably, in step S1 of this embodiment, thermocouples and infrared thermometers installed at the slag height position on the inner wall of the top-blown converter are used to detect the temperature at different positions of the molten pool and the splash situation of the melt in real time; the detected data is transmitted to the data calculation module in real time, providing a basis for analysis and control; in step S2, the interface reconstruction method is used to process the real-time data to obtain the specific situation of the melt splashing onto the wall; according to the specific situation of the melt splash, the visualization of the splash impact on the furnace body is realized, and the visualized data is transmitted to the smelting process control module; in step S3, based on the temperature distribution of the molten pool and the splash situation of the melt, the flow rates of pulverized coal, dry powder, and gas are automatically adjusted; by precisely controlling these smelting parameters, the optimization and control of the smelting process are realized.

[0169] In summary, the real-time and accurate data acquisition in step S1 of this embodiment is the prerequisite for realizing precise control of the smelting process; through this module, abnormalities in the temperature of the molten pool and the splash of the melt can be detected in a timely manner, providing a basis for timely adjustment of smelting parameters; the visualization technology in step S2 makes the splash situation of the melt in the smelting process more intuitive, facilitating the understanding and judgment of operators; through this module, the impact of the melt splash on the furnace body can be evaluated more precisely, providing an important reference for formulating and adjusting smelting strategies; the precise smelting process control in step S3 can improve smelting efficiency and reduce energy consumption; through this module, smelting quality problems caused by melt splash and temperature unevenness can be reduced, improving product quality; the automatic control can also reduce the labor intensity of operators and improve production safety.

[0170] AsFigure 18 As shown in Figure 18 , an embodiment of an electronic device is provided in this embodiment. In this embodiment, the electronic device 24 includes a processor 241 and a memory 242 coupled to the processor 241.

[0171] The memory 242 stores program instructions for implementing the layout method of the top-blown converter high-temperature melt temperature and splash online monitoring system according to any of the above embodiments.

[0172] The processor 241 is configured to execute the program instructions stored in the memory 242 to perform the layout of the top-blown converter high-temperature melt temperature and splash online monitoring system.

[0173] Among them, the processor 241 can also be referred to as a CPU (Central Processing Unit, central processing unit). The processor 241 may be an integrated circuit chip with signal processing capabilities. The processor 241 may also be a general-purpose processor, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components. The general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc.

[0174] Furthermore, Figure 19 As shown in the structural schematic diagram of the storage medium according to an embodiment of the present application, the storage medium 25 of the embodiment of the present application stores program instructions 251 capable of implementing all of the above methods. Among them, the program instructions 251 can be stored in the above storage medium in the form of a software product, including several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) or a processor to execute all or part of the steps of the methods described in various embodiments of the present application. The foregoing storage medium includes: various media that can store program codes such as USB flash drives, mobile hard disks, read-only memories (ROM, Read-Only Memory), random access memories (RAM, Random Access Memory), magnetic disks, or optical discs, or terminal devices such as computers, servers, mobile phones, and tablets.

[0175] In several embodiments provided by the present invention, it should be understood that the disclosed systems, devices, and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For example, the division of units is only a logical function division. In actual implementation, there may be other division methods. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the displayed or discussed coupling, direct coupling, or communication connection between each other can be through some interfaces. The indirect coupling or communication connection of devices or units can be in electrical, mechanical, or other forms.

[0176] In addition, each functional unit in various embodiments of the present invention can be integrated in a processing unit, or each unit can exist physically alone, or two or more units can be integrated in one unit. The above-mentioned integrated units can be implemented in the form of hardware or in the form of software functional units. The above is only the implementation manner of the present invention and does not limit the patent scope of the present invention. Any equivalent structure or equivalent process transformation made by using the content of the specification and drawings of the present invention, or directly or indirectly applied in other related technical fields, shall be equally included in the patent protection scope of the present invention.

[0177] The specific implementation manners of the invention have been described in detail above, but they are only examples. The present invention is not limited to the specific implementation manners described above. For those skilled in the art, any equivalent modification or substitution to the invention is also within the scope of the present invention. Therefore, all equal transformations, modifications, improvements, etc. made without departing from the spirit and principle of the present invention should be covered by the scope of the present invention.

Claims

1. An online monitoring system for high temperature melt temperature and splashing of a top-blown furnace, characterized in that: include: The top-blown furnace data acquisition module is used to detect the temperature at different positions of the molten pool and the melt splashing conditions through the thermocouple at the slag height position on the inner wall of the top-blown furnace and the infrared thermometer on the inner wall of the top-blown furnace, and transmit the detected data to the data calculation module in real time; The furnace body splash data calculation module is used to obtain the specific situation of the melt splashing onto the wall surface by the interface reconstruction method of the real-time data, and realize the visualization of the splash impact on the furnace body according to the specific situation of the melt splashing onto the wall surface; and transmit the visualization data to the smelting process control module; The smelting process control module is used to adjust the flow rates of pulverized coal, dry powder and gas based on the molten pool temperature distribution and melt splashing, build a melt temperature and liquid level model, evaluate the molten pool temperature and melt splashing, and control the smelting process according to the evaluation results.

2. The top-blown furnace high-temperature melt temperature and splashing online monitoring system according to claim 1, characterized in that: Top blowing furnace data acquisition module, including: Install the infrared thermometer submodule to add a fourth sleeve in the top-blowing spray gun, and place the infrared thermometer on the inner wall of the fourth sleeve of the top-blowing spray furnace; isolate the particles from the infrared ray irradiation path of the infrared thermometer to monitor the molten pool temperature normally; The infrared thermometer cooling submodule is used to form a high-speed gas channel between the third sleeve and the fourth sleeve, and the gas passing through the channel cools the infrared thermometer; the third sleeve and the fourth sleeve are connected by welding, and four infrared thermometers are evenly arranged on the outer wall of the fourth sleeve; The thermocouple arrangement submodule is used to arrange the thermocouple rings on the wall of the top-blown furnace, part of which is located at the height of the slag layer and part of which is located above the height of the molten pool liquid level.

3. The top-blown furnace high-temperature melt temperature and splashing online monitoring system according to claim 1, characterized in that: Furnace spatter data calculation module, including: The melt interface restoration submodule is used to restore the melt interface condition splashed onto the wall surface based on the temperature data of the thermocouple using the interface reconstruction method. The horizontal coordinate of the thermocouple is represented by English letters and the vertical coordinate is represented by numbers. Adjacent thermocouples are grouped into groups of four. Thermocouple grouping submodule, which can be used to divide thermocouples into 13 groups horizontally and 9 groups vertically, a total of 117 groups; The visualization submodule is used to transmit the collected data to the computer in real time. When the thermocouple is covered by splashing droplets, the temperature data transmitted to the computer increases significantly. Each group of thermocouples has four ways of restoring the shape of the phase interface of the melt splashed to the wall.

4. The top-blown furnace high-temperature melt temperature and splashing online monitoring system according to claim 3, characterized in that: The melt interface reduction submodule includes: The melt temperature acquisition unit is used to collect melt temperature data through thermocouples. The horizontal coordinate of the thermocouple is represented by English letters, and the vertical coordinate is represented by numbers. The data of four adjacent thermocouples are grouped to form a data block. The interface reconstruction unit is used to update the position of the melt interface according to the collected temperature data using the interface interpolation technology; interpolate the interface position according to the hot spot coupling data to obtain the interface shape; and adjust the grid structure according to the interface shape; The simulation verification unit is used to simulate the reconstructed melt interface to verify whether its dynamic behavior conforms to the preset physical phenomenon; if it conforms to the preset physical phenomenon, the reconstructed melt interface characteristics are analyzed and stored; if it does not conform, the interface interpolation and meshing are re-performed.

5. The top-blown furnace high-temperature melt temperature and splashing online monitoring system according to claim 4, characterized in that: Interface reconstruction unit, including: The hot spot coupling data processing subunit is used to analyze the heat conduction characteristics of the melt interface and extract key parameters based on the collected hot spot coupling data; wherein the key parameters include temperature gradient and heat flux; The new interface position calculation subunit is used to calculate the new position of the melt interface by using the interpolation algorithm using the collected temperature data as input; for complex scenarios, the new position of the melt interface is calculated by combining momentum interpolation and mass conservation conditions; The interface shape acquisition subunit is used to acquire the collective shape of the interface based on the updated interface position; adjust the grid structure according to the interface shape, and use adaptive grid reconstruction technology to dynamically adjust the grid density according to the complexity of the interface; Among them, the hot spot coupling data processing subunit is used to analyze the thermal conductivity characteristics of the melt interface and extract the key parameters temperature gradient and heat flux. The calculation formula is: Where T(x,y,t) represents the temperature distribution of the melt interface at coordinates (x,y) and time t; represents the temperature gradient; The calculation subunit of the new interface position is used to calculate the new position of the melt interface through the interpolation algorithm according to the collected temperature data. The calculation formula is: Where, L new (x, y, t) represents the updated melt interface position; ΔL(x, y, t) represents the change in the interface position.

6. The top-blown furnace high-temperature melt temperature and splashing online monitoring system according to claim 4, characterized in that: Simulation verification unit, including: The grid structure adjustment subunit is used to perform grid interpolation at the new interface position, generate a new grid structure, and perform continuous interpolation; and adjust the grid structure through an optimization algorithm; The structure verification subunit is used to compare the interpolation structure with the analytical solution, calculate and evaluate the interpolation accuracy; if it is greater than the preset interpolation accuracy value, adjust the interpolation parameters; iterate in sequence until it is less than the preset interpolation accuracy value; The melt simulation subunit is used to simulate the reconstructed melt interface to verify whether its dynamic behavior conforms to the preset physical phenomenon; if it conforms to the preset physical phenomenon, the reconstructed melt interface characteristics are analyzed and stored; if not, the interface interpolation and meshing are re-performed; Among them, in the structure verification subunit, the interpolation structure is compared with the analytical solution, and the interpolation accuracy is calculated and evaluated. The interpolation error calculation formula is: In the formula, X interp Represents the interpolation structure, the grid data generated by the grid structure adjustment sub-unit; X analytic represents the analytical solution, i.e., the theoretically accurate structural data; N represents the total number of grid points; w i represents the weight coefficient of the i-th grid point, which is used to reflect the importance in the actual system; γ represents the smoothness constraint coefficient, which is used to control the smoothness of the interpolation result; M represents the total number of dimensions; f j represents the smoothing factor of the jth dimension, which is used to impose additional constraints on a specific dimension; Dynamic iterative adjustment formula: In the formula, represents the interpolation structure of the kth iteration; η represents the iteration step size, which controls the amplitude of the adjustment; represents the gradient of the interpolation error function Ψ, which is used to guide the iteration direction; L represents the total number of additional constraints; κ l represents the weight coefficient of the lth constraint; A l represents the coefficient matrix of the lth constraint; B l represents the target value matrix of the lth constraint; Accuracy assessment convergence formula: In the formula, Z represents the normalization coefficient, which is used to ensure that the range of the convergence value is within a reasonable range; Q represents the number of key feature points; g m Represents the evaluation weight of the mth feature point; Represents the eigenvalue of the interpolation structure at the mth feature point; represents the eigenvalue of the analytical solution at the mth characteristic point; ∈ represents a small value offset term to prevent the denominator from being zero; Adaptive parameter adjustment formula: In the formula, α adapt Represents the adaptive adjustment coefficient, which is used to dynamically adjust the interpolation parameters; X prev represents the interpolation structure of the previous iteration; ρ represents the smoothing parameter to prevent the denominator from being zero; ω represents the second-order derivative weight coefficient; Θ(X interp ) represents the smoothness function of the interpolation structure.

7. The top-blown furnace high-temperature melt temperature and splashing online monitoring system according to claim 1, characterized in that: Smelting process control module, including: The real-time data dynamic acquisition submodule is used to receive the real-time data from the data acquisition module and the furnace body flying sword data calculation module, including the molten pool temperature distribution, melt splashing and spray gun position information, analyze the data and obtain a data set; The temperature and liquid level analysis submodule is used to preprocess the data set and divide the data set into a training set, a test set, and a validation set; construct a melt temperature and liquid level analysis model and use the training set to train the melt temperature and liquid level analysis model; The simulation verification liquid level model submodule is used to input the real-time collected high-temperature melt temperature and splashing data in the top-blown furnace into the melt temperature and liquid level analysis model for analysis, and automatically adjust the spray position and angle of the spray gun according to the analysis results.

8. The top-blown furnace high-temperature melt temperature and splashing online monitoring system according to claim 7, characterized in that: Temperature and liquid level analysis submodule, including: The data collection and preprocessing unit is used to obtain the key parameter data of liquid level and temperature in real time and store them in the database, remove missing values ​​and abnormal value preprocessing operations, take temperature and liquid level as input variables, and take factors affecting spray gun adjustment as secondary input variables; Constructing a melt temperature and liquid level model unit, which is used to form a data set from the preprocessed data, and divide the data set into a training set, a validation set, and a test set; constructing a melt temperature and liquid level model, and fitting the melt temperature and liquid level model using the training set; The evaluation and optimization unit is used to learn the relationship between temperature and liquid level changes in the melt temperature and liquid level model; real-time data is input into the melt temperature and liquid level model for evaluation, and the probability values ​​of temperature and liquid level changes are obtained based on the evaluation results, and the spray gun is adjusted based on the probability values.

9. The top-blown furnace high-temperature melt temperature and splashing online monitoring system according to claim 8, characterized in that: Evaluation and Optimization Unit, including: The output feedback subunit is used to input real-time data into the melt temperature and liquid level model for evaluation, and obtain the probability value of temperature and liquid level changes based on the evaluation results. When the probability value finds out the preset threshold, the spray gun adjustment mechanism is triggered; The intelligent decision-making subunit is used to obtain the end pressure value of the spray gun and calculate the difference in the immersion depth of the spray gun by comparing it with the standard value; and to judge whether the current liquid level and temperature meet the set standard value. If they exceed the preset range, the spray gun adjustment mechanism is triggered; The spray gun sub-unit is dynamically adjusted to monitor the high-temperature melt parameters of the top-blown furnace in real time. If the melt temperature-level model evaluation value is exceeded, an early warning is issued; and the melt temperature-level model parameters are continuously updated according to the real-time high-temperature melt parameters, and the adjustment process is stored.

10. A method for online monitoring of high temperature melt temperature and splashing of a top-blown furnace, which is applied to the online monitoring system for high temperature melt temperature and splashing of a top-blown furnace as claimed in any one of claims 1 to 9, characterized in that: The method for online monitoring of high temperature melt temperature and splashing of a top-blown furnace comprises: Thermocouples at the slag height position on the inner wall of the top-blown furnace and infrared thermometers on the inner wall of the top-blown furnace detect the temperature at different positions of the molten pool and the melt splashing conditions, and transmit the detected data to the data calculation module in real time; The real-time data is subjected to the interface punching method to obtain the specific situation of the melt splashing onto the wall surface, and the splash impacting the furnace body is visualized according to the specific situation of the melt splashing onto the wall surface; and the visualized data is transmitted to the smelting process control module; Based on the molten pool temperature distribution and melt splashing, the flow rates of pulverized coal, dry powder and gas are adjusted, a melt temperature and liquid level model is constructed, the molten pool temperature and melt splashing are evaluated, and the smelting process is controlled based on the evaluation results.

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