Intelligent control method and system for converter steelmaking

Abstract

The invention provides an intelligent control method and system for converter steelmaking, and belongs to the technical field of converter steelmaking, and the method comprises the steps that a target control strategy is determined from multiple standard control strategies based on multiple steelmaking characteristics, and control parameters of the multiple standard control strategies are different; controlling a reaction monitoring device to monitor the converter steelmaking process based on the target control strategy to obtain reaction monitoring data; and determining supply parameters of converter steelmaking based on the reaction monitoring data. According to the converter steelmaking intelligent control method and system, the accuracy and reliability of converter steelmaking control can be improved.

Description

Technical Field

[0001] The present disclosure belongs to the technical field of converter steelmaking, and more specifically, to an intelligent control method and system for converter steelmaking. Background Art

[0002] As a key link in modern steel production, converter steelmaking plays a vital role in converting raw materials such as molten iron and scrap steel into high-quality molten steel. The monitoring parameters of the auxiliary gun have a great influence on the monitoring results. In today's converter steelmaking control, the control of the auxiliary gun is not accurate enough, and the steelmaking process is monitored only by a single monitoring mode, resulting in deviations between the monitoring results and the actual results, which leads to deviations in the results of converter steelmaking.

[0003] It can be seen that an accurate and reliable intelligent control method and system for converter steelmaking is urgently needed. Summary of the invention

[0004] The purpose of the present disclosure is to provide an intelligent control method and system for converter steelmaking to improve the accuracy and reliability of converter steelmaking control.

[0005] A first aspect of the embodiments of the present disclosure provides a converter steelmaking intelligent control method, comprising: determining a target control strategy from a plurality of standard control strategies based on a plurality of steelmaking characteristics, wherein the plurality of standard control strategies have different control parameters; Based on the target control strategy, the reaction monitoring device is controlled to monitor the converter steelmaking process to obtain reaction monitoring data; Determine supply parameters for converter steelmaking based on reaction monitoring data.

[0006] A second aspect of the embodiments of the present disclosure provides a converter steelmaking intelligent control system, comprising: a strategy decision module, for determining a target control strategy from a plurality of standard control strategies based on a plurality of steelmaking characteristics, wherein the plurality of standard control strategies have different control parameters; A monitoring module, which is used to control the reaction monitoring device to monitor the converter steelmaking process based on the target control strategy to obtain reaction monitoring data; A control module is used to determine supply parameters for converter steelmaking based on reaction monitoring data.

[0007] According to a third aspect of an embodiment of the present disclosure, an electronic device is provided, including a memory, a processor, and a computer program stored in the memory and running on the processor, wherein the processor implements the steps of the above-mentioned intelligent control method for converter steelmaking when executing the computer program.

[0008] According to a fourth aspect of the embodiments of the present disclosure, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the above-mentioned converter steelmaking intelligent control method are implemented.

[0009] The beneficial effects of the converter steelmaking intelligent control method and system provided by the embodiments of the present disclosure are: The present disclosure selects a target control strategy from a plurality of standard control strategies based on a plurality of steelmaking characteristics, and can flexibly adjust the target control strategy according to different steelmaking conditions and requirements, which helps to improve the adaptability and efficiency of the monitoring of the steelmaking process and ensures that the expected monitoring effect can be achieved under various circumstances. The present disclosure can ensure the adaptability of the control parameters by selecting a strategy suitable for the current steelmaking characteristics, which helps to improve the monitoring stability of the steelmaking process, thereby improving product quality, while reducing unnecessary energy consumption and waste, improving the automation and intelligence level of the steelmaking process, and improving the accuracy and reliability of converter steelmaking control. BRIEF DESCRIPTION OF THE DRAWINGS

[0010] In order to more clearly illustrate the technical solutions in the embodiments of the present disclosure, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present disclosure. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0011] Figure 1 A schematic diagram of a process flow of an intelligent control method for converter steelmaking provided in one embodiment of the present disclosure; Figure 2 A schematic diagram of a test process flow for calculating metal recovery rate provided in one embodiment of the present disclosure; Figure 3 A structural block diagram of a converter steelmaking intelligent control system provided in one embodiment of the present disclosure; Figure 4 A schematic block diagram of an electronic device provided by an embodiment of the present disclosure. DETAILED DESCRIPTION

[0012] In the following description, specific details such as specific system structures and technologies are provided for the purpose of illustration rather than limitation, so as to provide a thorough understanding of the embodiments of the present disclosure. However, it should be clear to those skilled in the art that the present disclosure may be implemented in other embodiments without these specific details. In other cases, detailed descriptions of well-known systems, devices, circuits, and methods are omitted to avoid obstructing the description of the present disclosure with unnecessary details.

[0013] In order to make the purpose, technical solutions and advantages of the present disclosure more clear, specific embodiments will be described below in conjunction with the accompanying drawings.

[0014] Please refer to Figure 1 , Figure 1 A schematic flow chart of a converter steelmaking intelligent control method provided in one embodiment of the present disclosure, the method comprising: S101: determining a target control strategy from a plurality of standard control strategies based on a plurality of steelmaking characteristics, wherein the plurality of standard control strategies have different control parameters.

[0015] In this embodiment, the steelmaking characteristics may be the converter capacity and the height of the molten steel level. The standard control strategy may be the control strategy of the corresponding sub-lance when the steelmaking characteristics are fixed, and the control strategy may include: monitoring duration, monitoring position and monitoring depth. The target control strategy refers to the control strategy of the corresponding sub-lance under the condition of the steelmaking characteristics.

[0016] The capacity of the converter will affect the time it takes to insert the auxiliary lance. When the capacity of the converter is large, the mass of the molten steel and the scale of the reaction will increase accordingly. For a large-capacity converter, the mass of the molten steel is large, the inertia of the reaction is also large, and the composition and temperature change relatively slowly. Therefore, the insertion time of the auxiliary lance can be appropriately extended to a certain extent. For example, in the middle of the reaction of a large-capacity converter, when measuring the composition, the insertion time may be extended from 15-20 seconds for small and medium-sized converters to 20-25 seconds to ensure that the reaction inside the molten steel can be accurately reflected.

[0017] The capacity of the converter will also affect the insertion position of the auxiliary gun. The reaction conditions in different areas of the converter are different. The area near the oxygen spray gun is the main area of ​​decarburization reaction, with high temperature and rapid composition changes. In large converters, due to the large volume of molten steel, the distribution of reaction areas is more complex. In order to comprehensively and accurately monitor the state of molten steel, it is necessary to set auxiliary gun insertion points at multiple locations. For example, for a converter with a capacity of more than 300 tons, in addition to inserting auxiliary guns in the central area and near the oxygen spray gun, insertion points can also be set at a first distance from the furnace wall to monitor the reaction of molten steel at different positions. Specifically, in response to the capacity of the converter being greater than the first capacity threshold, monitoring of the first distance from the converter wall is added. The first capacity threshold and the first distance are both set manually, and the first distance can also change according to changes in the size of the converter.

[0018] The liquid level will affect the insertion depth of the auxiliary lance. When the liquid level is low, in order to avoid inserting too deep and touching the furnace bottom, the insertion position of the auxiliary lance should be relatively high in the vertical direction. For example, in a converter with a liquid level of 2-3 meters, the insertion position can be 1-2 meters below the liquid level. When the liquid level is higher, such as 4-5 meters, the insertion position can be appropriately deepened, 2-3 meters below the liquid level, to ensure that the probe can be in the main part of the molten steel, while avoiding interference from the surface slag layer.

[0019] The steelmaking characteristics corresponding to each standard control strategy are different, and since the steelmaking characteristics determine the control strategy, the parameters in each control strategy are also different.

[0020] The converter capacity in the steelmaking characteristics can be obtained through the converter parameters, the liquid level can be obtained through the liquid level sensor, and the similarity between the steelmaking characteristics and the standard steelmaking characteristics can be calculated, and the standard control strategy corresponding to the standard steelmaking characteristics with the highest similarity can be used as the target control strategy. The standard steelmaking characteristics refer to the steelmaking characteristics corresponding to the standard control strategy.

[0021] The present disclosure can also select a target control strategy from a plurality of standard control strategies through a first mapping table. The first mapping table contains standard control strategies corresponding to each converter capacity and liquid level. The first mapping table can be as shown in Table 1: Table 1 First mapping table

[0022] S102: Based on the target control strategy, the reaction monitoring device is controlled to monitor the converter steelmaking process to obtain reaction monitoring data.

[0023] In this embodiment, the target control strategy is determined from multiple pre-set standard control strategies based on the steelmaking characteristics of the converter. It is a control scheme specifically used under the current steelmaking conditions. The purpose is to enable the reaction monitoring device to obtain accurate status information of the molten steel during the converter steelmaking process in an appropriate manner.

[0024] The reaction monitoring device can be an auxiliary gun, which is equipped with various probes. For example, a thermocouple probe can measure the temperature of the molten steel, and an electrochemical probe can monitor the composition content of the molten steel. By inserting it into a specific position of the molten steel and keeping it for a certain period of time, the state of the molten steel can be monitored.

[0025] Reaction monitoring data refers to various data information about molten steel in the converter steelmaking process obtained by the reaction monitoring device after performing monitoring operations according to the target control strategy. It may include the temperature of the molten steel, component content data (such as carbon content, sulfur content, phosphorus content, etc.) and other data that may reflect the quality and reaction state of the molten steel. These data provide a basis for subsequent operations such as judging the steelmaking reaction stage and adjusting steelmaking parameters.

[0026] For example, a steel plant has a converter with a capacity of 250 tons. The current molten steel level is 3.5 meters as measured by the liquid level sensor. According to the pre-defined first mapping table (such as the similar table mentioned above), the corresponding target control strategy is searched and determined as follows: Monitoring duration: set to 18-23 seconds.

[0027] Monitoring location: Select the center area of ​​the converter, near the oxygen lance, and 0.8 meters away from the furnace wall for monitoring.

[0028] Monitoring depth: The insertion depth of the auxiliary gun is controlled within the range of 2-3.5 meters below the liquid level.

[0029] In the above-mentioned monitoring duration area and monitoring depth area, a value can be randomly selected as a control strategy.

[0030] S103: Determine supply parameters for converter steelmaking based on the reaction monitoring data.

[0031] In this embodiment, the supply parameters may be the oxygen supply, the addition amount of slag forming agent or the addition amount of alloy material, etc. Reasonable control of these parameters has a key impact on the final indicators such as the quality, composition and temperature of the molten steel.

[0032] Oxygen supply is an important factor in supply parameters. Oxygen is mainly used to oxidize impurity elements (such as carbon, silicon, manganese, etc.) in molten steel during converter steelmaking. The intensity and speed of the reaction can be adjusted by controlling the oxygen supply. Appropriate oxygen supply can ensure the effective removal of impurities while allowing the molten steel to meet the expected composition and temperature requirements.

[0033] In this embodiment, the supply parameters can be determined by a preset supply table, in which the supply parameters corresponding to each temperature and each component content are preset. The calculation can also be performed according to a preset algorithm formula.

[0034] For example, during the converter steelmaking process, the auxiliary gun monitors that the temperature of the molten steel is 1600℃ and the carbon content is 0.8%. At this time, according to the steelmaking process requirements and the composition requirements of the target steel grade, the final carbon content of the target steel grade is required to be 0.05%-0.1%, and the temperature is required to be 1620℃-1630℃.

[0035] According to the empirical formula and steelmaking model, a certain amount of oxygen is required to oxidize 1% of carbon. For example, 10m³ / t of oxygen is required to oxidize 1% of carbon. T refers to the tons of molten steel. Assume that the molten steel in the converter is 100t. Then, in order to reduce the carbon content from 0.8% to the target range, the preliminary calculation shows that the amount of oxygen required is (0.8-0.1)×10×100=700m³. The empirical formula can be determined based on experience.

[0036] At the same time, considering the temperature increase requirement, the oxidation reaction will generate heat. According to the heat balance calculation, the heat generated by each cubic meter of oxygen participating in the reaction can increase the temperature of the molten steel by a certain degree. For example, each cubic meter of oxygen reaction can increase the temperature of the molten steel by 10°C. At present, the temperature is still 20°C-30°C short. In order to meet the temperature requirements, additional oxygen is needed to generate enough heat. Assume that 200m³-300m³ of oxygen is needed.

[0037] Taking into account the need to reduce carbon content and increase temperature, the oxygen supply was finally determined to be around 900m³-1000m³. In addition, in the subsequent steelmaking process, the oxygen supply will continue to be adjusted in real time based on the reaction monitoring data to ensure that the composition and temperature of the molten steel accurately reach the target value.

[0038] It can be concluded from the above that the present disclosure can flexibly adjust according to different steelmaking conditions and requirements by selecting a target control strategy from multiple standard control strategies based on multiple steelmaking characteristics, which helps to improve the adaptability and efficiency of monitoring of the steelmaking process and ensure that the expected monitoring effect can be achieved under various circumstances. The present disclosure can ensure the adaptability of control parameters by selecting a strategy suitable for the current steelmaking characteristics, which helps to improve the monitoring stability of the steelmaking process, thereby improving product quality, while reducing unnecessary energy consumption and waste, improving the automation and intelligence level of the steelmaking process, and improving the accuracy and reliability of converter steelmaking control.

[0039] In one embodiment of the present disclosure, a target control strategy is determined from a plurality of standard control strategies based on a plurality of steelmaking characteristics, including: Determining a target matching degree between a first steelmaking feature and a first standard steelmaking feature, the first steelmaking feature being a feature among the plurality of steelmaking features, and the first standard steelmaking feature being a steelmaking feature among the standard steelmaking features corresponding to the first steelmaking feature; Determine the standard control strategy corresponding to the first standard steelmaking characteristic with the highest target matching degree among all targets as the target control strategy; Among them, the standard steelmaking characteristics are the steelmaking characteristics corresponding to the standard control strategy.

[0040] In this embodiment, the multiple steelmaking characteristics refer to relevant characteristic indicators that can affect steelmaking operations and controls during the converter steelmaking process and can be used to distinguish different steelmaking conditions, and may be converter capacity and molten steel level height.

[0041] Multiple standard control strategies are a series of pre-set control schemes. Each standard control strategy is formulated for a specific steelmaking situation and covers the relevant parameter settings for operating the reaction monitoring device. These parameters specifically include the monitoring time, monitoring position, and monitoring depth of the secondary gun. Different standard control strategies have different control parameters in order to match the needs under different steelmaking characteristics.

[0042] The first steelmaking feature is a specific feature selected from many steelmaking features, which is used to participate in subsequent operations such as matching judgment with standard steelmaking features. For example, the converter capacity feature can be selected as the first steelmaking feature to compare and analyze the converter capacity in the corresponding standard steelmaking feature.

[0043] The first standard steelmaking feature is an element in the standard steelmaking feature set, and it corresponds to the first steelmaking feature. In other words, if the first steelmaking feature is the converter capacity, then the first standard steelmaking feature is the description of the converter capacity in the steelmaking conditions corresponding to each standard control strategy, which is used to calculate the matching degree with the actual converter capacity (first steelmaking feature).

[0044] Standard steelmaking characteristics refer to the set of characteristics that describe the steelmaking conditions corresponding to each standard control strategy.

[0045] The target matching degree is an indicator value used to measure the similarity or fit between the first steelmaking feature and the first standard steelmaking feature. The similarity between the two features can be calculated by linear interpolation, proportional method, etc. The control strategy corresponding to the target matching degree with the highest similarity is used as the target control strategy to control the sub-gun for monitoring.

[0046] It can be concluded from the above that the present disclosure ensures the accurate correspondence between the steelmaking characteristics and the actual steelmaking conditions by determining the target matching degree between the first steelmaking characteristics and the first standard steelmaking characteristics. By calculating the matching degree, this embodiment can accurately find the standard control strategy that best matches the current steelmaking characteristics, reduce steelmaking quality problems caused by improper control strategies, improve the stability and controllability of the steelmaking process, and enhance the accuracy and reliability of converter steelmaking control.

[0047] In one embodiment of the present disclosure, the converter steelmaking intelligent control method further includes: determining a first reaction stage value based on the flame characteristics; determining a second reaction stage value based on the gas characteristic; determining a third reaction stage value based on the reaction monitoring data; A reaction phase is determined based on the first reaction phase value, the second reaction phase value, and the third reaction phase value.

[0048] In this embodiment, the flame characteristics refer to various performances of the flame during the converter steelmaking process, including the color, brightness, length or stability of the flame. In the early stage of converter steelmaking, silicon, manganese and other elements in the molten iron are first oxidized. Due to the characteristics of the oxidation reaction of these elements, the flame color is usually dark red. This is because the initial reaction is relatively mild, the energy released is limited, and the flame temperature is low. According to this feature, a lower first reaction stage value can be set, such as 0.2-0.3, indicating the early stage of steelmaking.

[0049] As the steelmaking process progresses, carbon begins to oxidize in large quantities, which is a critical and violent stage in the steelmaking process. At this time, the flame color will become brighter, showing orange or white. This is because carbon oxidation releases a lot of heat, which increases the flame temperature and changes the color significantly. At this time, the corresponding first reaction stage value can be set to 0.5-0.7, indicating that it is in the middle stage of steelmaking.

[0050] As steelmaking nears its end, the reaction gradually weakens and the flame color becomes lighter again, possibly turning back to light red or slightly yellow. This is because the main reaction is basically completed, the heat release decreases, and the flame temperature drops. At this time, the first reaction stage value can be set to 0.8-0.9, indicating that it is close to the end of steelmaking.

[0051] The color of the flame can be obtained through a camera, and the flame characteristics can be processed by a first neural network model to obtain the corresponding first reaction stage value. The first neural network model has been trained with a large number of flame characteristics and the corresponding first reaction stage values.

[0052] The first reaction stage value is a numerical value that quantifies or classifies the converter steelmaking reaction stage based on flame characteristics. This value is obtained by matching flame characteristics with reaction stages based on pre-set rules or experience. For example, when the flame color is dark red and short, the first reaction stage value can be set to 0.3, indicating that it is in the early stage of steelmaking; when the flame is bright and long, the first reaction stage value can be set to 0.6, indicating that it is in the middle stage of steelmaking, etc.

[0053] Gas characteristics refer to the relevant characteristics of the gas produced and discharged during the converter steelmaking process. For example, in the early stage of steelmaking, silicon, manganese and other elements in the molten iron are oxidized, mainly producing carbon dioxide. At this time, the carbon monoxide content is relatively low, for example, the carbon monoxide content may be 10%-20%, and the carbon dioxide content is higher. According to this gas composition characteristic, the second reaction stage value can be set to 0.2-0.3, indicating that it is in the early stage of steelmaking.

[0054] In the middle stage of steelmaking, carbon is oxidized in large quantities, and the amount of carbon monoxide produced increases sharply. At this time, the carbon monoxide content may reach 40%-60%, and the carbon dioxide content is relatively reduced. The second reaction stage value corresponding to this change in gas composition can be set to 0.5-0.7, indicating that it is in the middle stage of steelmaking.

[0055] At the end of steelmaking, as the carbon content decreases, the amount of carbon monoxide produced decreases, and the carbon dioxide content gradually increases. When the carbon monoxide content drops to 20%-30% and the carbon dioxide content rises, the second reaction stage value can be set to 0.8-0.9, indicating that it is close to the end of steelmaking.

[0056] The second reaction stage value is a value used to indicate the reaction stage, determined based on gas characteristics. According to the changing rules of gas composition and flow rate, the corresponding value range is set to correspond to different reaction stages.

[0057] In this embodiment, the gas content can be obtained by infrared spectroscopy or gas chromatography, and the current second reaction stage value can be obtained by a preset second mapping table. The second mapping table contains the second reaction stage values ​​corresponding to different gas component contents.

[0058] The reaction monitoring data may include temperature and molten steel composition, and the corresponding third reaction stage value may be obtained through a third mapping table, which contains the corresponding third reaction stage values ​​under various preset molten steel temperature and molten steel composition conditions.

[0059] The third reaction stage value is a quantitative value of the reaction stage determined based on the reaction monitoring data. For example, when the carbon content of the molten steel is high and the temperature rises rapidly, the third reaction stage value may be 0.4, indicating that it is in the early stage of steelmaking; when the carbon content drops to near the target range and the temperature is close to the tapping temperature requirement, the third reaction stage value is 0.8, indicating that it is close to the end of the reaction.

[0060] In this embodiment, a reaction stage value can be calculated by weighted calculation or the like to calculate the first reaction stage value, the second reaction stage value, and the third reaction stage value to obtain a reaction stage value, and the current reaction stage is determined by the reaction stage value. The reaction stage value and the reaction stage have a predetermined corresponding relationship. For example, when the reaction stage value is 0, the reaction stage has not started; when the reaction stage value is greater than 0 and less than or equal to 0.4, the corresponding reaction stage is the early reaction stage; when the reaction stage value is greater than 0.4 and less than or equal to 0.75, the corresponding reaction stage is the middle reaction stage; and when the reaction stage value is greater than 0.75 and less than or equal to 1, the corresponding reaction stage is the late reaction stage.

[0061] It can be concluded from the above that the present disclosure can accurately determine the reaction stage of steelmaking by monitoring flame characteristics such as flame color and brightness, providing an important basis for subsequent control. This embodiment can more accurately understand the material transformation and energy release in the steelmaking process by monitoring flame characteristics, gas characteristics and reaction monitoring data, thereby improving the accuracy of the judgment of the reaction stage. After accurately determining the reaction stage in this embodiment, corresponding control strategies can be adopted according to the characteristics of different stages, such as adjusting the oxygen blowing amount, adding slag making materials, etc., to optimize the steelmaking process, improve product quality and output, and enhance the accuracy and reliability of converter steelmaking control.

[0062] In one embodiment of the present disclosure, the converter steelmaking intelligent control method further includes: Adjust the target control strategy based on the reaction stage to obtain a second control strategy; Based on the second control strategy, the reaction monitoring device is controlled to monitor the converter steelmaking process to obtain reaction monitoring data.

[0063] In this embodiment, the target control strategy includes: initial monitoring duration, initial monitoring position and initial monitoring depth, and the second control strategy includes: monitoring duration, monitoring position and monitoring depth.

[0064] In response to the reaction stage being the initial stage of the reaction, reducing the initial monitoring duration by the first duration to obtain the monitoring duration; and using the initial monitoring position as the monitoring position; and reducing the initial monitoring depth by the first depth to obtain the monitoring depth; In response to the reaction stage being in the middle of the reaction, increasing the initial monitoring duration by the second duration to obtain the monitoring duration; and increasing the first range area of ​​the supply device to obtain the monitoring position; and using the initial monitoring depth as the monitoring depth; In response to the reaction stage being the end of the reaction, the initial monitoring duration is increased by a third duration to obtain a monitoring duration; and the position at a first distance close to the furnace wall in the initial monitoring position is eliminated to obtain a monitoring position; and the initial monitoring depth is increased by a second depth to obtain a monitoring depth.

[0065] In this embodiment, it is considered that in the early stage of steelmaking, the composition and temperature of molten steel change relatively slowly. Mainly, silicon, manganese and other elements in the molten iron begin to oxidize, and the reaction speed is not fast. At this time, the reaction monitoring device does not need too long a monitoring time to obtain relatively stable initial data. Therefore, the initial monitoring time can be appropriately reduced by the first time, and both the initial monitoring time and the first time can be set by experience.

[0066] Considering that the mid-reaction is the most intense stage in the steelmaking process, carbon is oxidized in large quantities, and the temperature and composition of the molten steel change rapidly. In order to accurately capture these rapidly changing data, the monitoring time needs to be extended. At the end of the reaction, the composition and temperature of the molten steel gradually approach the target value, and the reaction tends to be stable, but the accuracy requirements are higher. Sufficient monitoring time is required to ensure that the molten steel meets the expected quality requirements. Therefore, the initial monitoring time is increased by the second and third time periods respectively, and the second and third time periods can be determined based on experiments.

[0067] Considering that in the early stage, in order to obtain the initial state of the entire molten steel, the monitoring position is mainly concentrated in the area that can represent the main body of the molten steel. Therefore, the initial monitoring position can be used as the monitoring position for monitoring, and the mid-term reaction is violent and the regional differences are obvious. The carbon-oxygen reaction is mainly concentrated near the oxygen spray gun, but the composition and temperature changes of the entire molten steel also need to be fully mastered. The supply equipment can be an oxygen spray gun that supplies oxygen. The first range area can be the area 0.5m-1m below the oxygen spray gun. The first range area can be set based on experience. The final stage is mainly to ensure that the overall quality of the molten steel meets the target requirements, focusing on whether the main part of the molten steel has evenly reached the expected composition and temperature. Reduce monitoring of local areas such as near the furnace wall and spray gun, because the impact of these areas is relatively small at this time, and focus on whether the overall molten steel meets the steelmaking standards.

[0068] Considering that there may be unmelted charge at the bottom of the molten steel in the initial stage, and the composition and temperature of the molten steel are relatively uniform in the vertical direction, the main purpose is to obtain the initial state of the molten steel. Therefore, the initial monitoring depth can be reduced by the first depth to obtain more accurate data. In the middle stage of the reaction, the initial monitoring depth can monitor relatively accurate data; at the end of the reaction, the final state of the main body of the molten steel must be accurately measured to ensure that the quality of the molten steel is uniform and meets the standards, so the monitoring depth must ensure that accurate data of the core part of the molten steel can be obtained. It focuses more on a slightly deeper position to check whether the bottom of the molten steel has also reached the target composition and temperature. Therefore, the initial monitoring depth can be increased by the second depth, and the initial monitoring depth, the first depth and the second depth can all be set by experience.

[0069] The control strategy adjusted according to the reaction stage is used as the second control strategy to control the reaction monitoring device for monitoring.

[0070] It can be concluded from the above that, in the early stage of steelmaking, the present disclosure can quickly obtain the initial state of molten steel by appropriately reducing the monitoring time and monitoring depth, while avoiding unnecessary waste of resources. In the middle stage of steelmaking, the monitoring time is extended and the monitoring range is expanded (such as increasing the monitoring of the area near the supply equipment), which can accurately capture the rapid changes in the composition and temperature of molten steel and improve the real-time and accuracy of monitoring. At the end of steelmaking, by extending the monitoring time and adjusting the monitoring depth, it is ensured that the overall quality of molten steel meets the target requirements, the qualified rate and quality stability of the product are improved, and the accuracy and reliability of the patented steelmaking control are improved.

[0071] In one embodiment of the present disclosure, determining the reaction stage based on the first reaction stage value, the second reaction stage value, and the third reaction stage value includes: Determining a first stage value based on the first reaction stage value and the first weight; determining a second stage value based on the second reaction stage value and the second weight; Determining a third stage value based on the third reaction stage value and the third weight; The sum of the first stage value, the second stage value, and the third stage value is taken as the reaction stage value; determining a reaction stage based on the reaction stage value; Among them, the first weight is the weight corresponding to the first reaction stage value, the second weight is the weight corresponding to the second reaction stage value, and the third weight is the weight corresponding to the third reaction stage value.

[0072] In one embodiment of the present disclosure, before determining the reaction stage based on the first reaction stage value, the second reaction stage value and the third reaction stage value, the method further includes: Determine a first initial weight, a second initial weight, and a third initial weight respectively; Determine the reaction stage by performing weighted calculation based on the first reaction stage value, the first initial weight, the second reaction stage value, the second initial weight, the third reaction stage value and the third initial weight; In response to the reaction stage being the first stage, increasing the first initial weight with the first flame step length to obtain the first weight; and decreasing the second initial weight with the first gas step length to obtain the second weight; and decreasing the third initial weight with the first monitoring step length to obtain the third weight; In response to the reaction stage being the second stage, reducing the first initial weight with a second flame step length to obtain a first weight; and increasing the second initial weight with a second gas step length to obtain a second weight; and increasing the third initial weight with a second monitoring step length to obtain a third weight; In response to the reaction stage being the third stage, the first initial weight is reduced by a third flame step to obtain a first weight; and the third initial weight is reduced by a third gas step to obtain a second weight; and the third initial weight is increased by a third monitoring step to obtain a third weight.

[0073] In this embodiment, the first initial weight refers to the weight corresponding to the first reaction stage value obtained according to the flame characteristics when the monitoring is started, the second initial weight refers to the weight corresponding to the second reaction stage value obtained according to the gas characteristics when the monitoring is started, and the third initial weight refers to the weight corresponding to the third reaction stage value obtained according to the reaction monitoring data when the monitoring is started. The first initial weight, the second initial weight and the third initial weight can be determined based on experience.

[0074] The first weight, the second weight and the third weight are weights adjusted according to the first initial weight and the reaction stage.

[0075] In this embodiment, since the influence of various characteristics on the reaction stage is different in different reaction stages, the reaction stage should be determined first. Therefore, by setting three initial weights, a more accurate reaction stage value can be obtained.

[0076] For example, the first reaction stage value is 0.3, the second reaction stage value is 0.2, the third reaction stage value is 0.2, the first initial weight is 0.3, the second initial weight is 0.3, and the third initial weight is 0.4.

[0077] Calculate the first stage value: first stage value = first reaction stage value × first initial weight = 0.3 × 0.3 = 0.09.

[0078] Calculate the second stage value: second stage value = second reaction stage value × second initial weight = 0.2 × 0.3 = 0.06.

[0079] Calculate the third stage value: third stage value = third reaction stage value × third initial weight = 0.2 × 0.4 = 0.08.

[0080] Calculate the reaction stage value: Reaction stage value = first stage value + second stage value + third stage value = 0.09 + 0.06 + 0.08 = 0.23.

[0081] Since the reaction stage value is set to be less than 0.4 as the initial stage, the current determination is the initial stage of steelmaking.

[0082] In this embodiment, the first stage may be the initial stage of the reaction, the second stage may be the middle stage of the reaction, and the third stage may be the final stage of the reaction.

[0083] Considering that the flame characteristics can intuitively reflect whether the reaction is started normally in the early stage of the reaction. At this time, the color, brightness and length of the flame are mainly determined by the oxidation reaction of silicon, manganese and other elements in the molten iron. These characteristics are critical for the initial judgment of the reaction stage. Therefore, the weight of the flame characteristics can be appropriately increased. In the early stage of the reaction, the gas emission is mainly produced by the oxidation of silicon and manganese to produce carbon dioxide and other gases, and its composition and flow rate changes also have certain rules. However, compared with the flame characteristics, the changes in gas characteristics are not obvious, and are affected by factors such as sampling and analysis. Therefore, the weight of gas characteristics can be kept at a low level. In the early stage of the reaction, the reaction is relatively stable, and the speed of change of molten steel composition and temperature is relatively slow. At this time, although the reaction monitoring data is accurate, its weight can be appropriately reduced because its changes are not too drastic.

[0084] Therefore, when the reaction stage is at the initial stage of the reaction, the first initial weight can be increased by the first flame step to obtain the first weight; and the second initial weight can be reduced by the first gas step to obtain the second weight; and the third initial weight can be reduced by the first monitoring step to obtain the third weight. The first flame step, the first gas step and the first monitoring step can be set based on experience.

[0085] Considering that the flame is very bright and long in the middle stage of the reaction, the flame characteristics can well reflect the intensity of the reaction. However, since the importance of reaction monitoring data is more prominent at this time, the weight of flame characteristics can be appropriately reduced. In the middle stage of the reaction, the gas characteristics change significantly, the carbon monoxide emissions increase sharply, and the gas flow rate also increases. Gas characteristics play an important role in judging the progress of the decarburization reaction. The weight of gas characteristics can be appropriately increased. The middle stage of the reaction is the most intense stage of the reaction, and the temperature and composition of the molten steel change rapidly, especially the removal process of the carbon content. At this time, the accuracy and timeliness of the reaction monitoring data are particularly important, and the weight of the reaction monitoring data needs to be increased.

[0086] Therefore, when the reaction stage is in the middle of the reaction, the first initial weight can be reduced by the second flame step to obtain the first weight; and the second initial weight can be increased by the second gas step to obtain the second weight; and the third initial weight can be increased by the second monitoring step to obtain the third weight; the second flame step, the second gas step and the second monitoring step can be set based on experience.

[0087] Considering that at the end of the reaction, the flame color becomes lighter and the length shortens, the flame characteristics can help determine whether the reaction is close to completion. However, compared with the reaction monitoring data, the accuracy and importance of the flame characteristics are slightly lower, and the weight of the flame characteristics can be reduced. At the end of the reaction, changes in gas composition and flow rate can also reflect the end stage of the reaction. However, due to the dominance of reaction monitoring data, the weight of gas characteristics can be kept at a low level. The end of the reaction is close to the end point, and the temperature and composition accuracy of the molten steel are extremely high. Reaction monitoring data is the key basis for ensuring that the molten steel meets the target requirements, and its weight should be further increased.

[0088] Therefore, when the reaction stage is at the end of the reaction, the first initial weight can be reduced by the third flame step, the first weight; and the third initial weight can be reduced by the third gas step to obtain the second weight; and the third initial weight can be increased by the third monitoring step to obtain the third weight. The third flame step, the third gas step and the third monitoring step can be set based on experience.

[0089] After obtaining the first weight, the second weight, and the third weight, weighted calculation can be performed on the corresponding reaction stage values. It should be noted that the sum of the first weight, the second weight, and the third weight is 1. The reaction stage value obtained by weighted calculation is, for example, 0.85. In the preset corresponding relationship, when the reaction stage value is 0.85, the corresponding reaction stage is the end of the reaction.

[0090] Considering that the flame characteristics may be affected by some phenomena in the steelmaking process, the weight corresponding to the flame characteristics can be appropriately reduced when the situation that affects the flame characteristics occurs, for example: In response to the occurrence of a flame influence feature, the first weight is reduced by a first flame influence step length to obtain a first adjustment weight; and the second weight is increased by a second flame influence step length to obtain a second adjustment weight; and the third weight is increased by a third flame influence step length to obtain a third adjustment weight; determining a first adjustment stage value based on the first reaction stage value and the first adjustment weight; determining a second adjustment stage value based on the second reaction stage value and the second adjustment weight; determining a third adjustment stage value based on the third reaction stage value and the third adjustment weight; taking the sum of the first adjustment stage value, the second adjustment stage value and the third adjustment stage value as the reaction stage value; The reaction phase is determined based on the reaction phase value.

[0091] In this embodiment, the flame influence feature refers to a feature that may affect the flame, such as splashing or excessive external light. The flame influence feature may be acquired through a camera and a light intensity sensor. The first flame influence step, the second flame influence step, and the third flame influence step may be determined experimentally. It should be noted that the first flame image step is equal to the sum of the second flame influence step and the third flame influence step, so that the adjusted sum of the weights is 1.

[0092] It can be concluded from the above that the present disclosure can more comprehensively reflect the actual situation in the converter steelmaking process by comprehensively considering the information of three dimensions: flame characteristics, gas characteristics, and reaction monitoring data. This embodiment dynamically adjusts the weight of each feature according to the characteristics of different reaction stages, so that the judgment result is more in line with the changing law of the actual reaction process, and improves the accuracy of the reaction stage judgment. This embodiment can take different control measures according to different reaction stages, such as adjusting the oxygen blowing intensity, adding slag making materials, etc., to optimize the steelmaking process, improve product quality and output, and improve the accuracy and reliability of converter steelmaking control.

[0093] In one embodiment of the present disclosure, the converter steelmaking intelligent control method further includes: Determine monitoring frequency based on the stage of response; The reaction monitoring device is controlled to perform monitoring based on the monitoring frequency.

[0094] In this embodiment, in response to the reaction stage being the first stage, the first monitoring frequency is used as the monitoring frequency; in response to the reaction stage being the second stage, the second monitoring frequency is used as the monitoring frequency; in response to the reaction stage being the third stage, the third monitoring frequency is used as the monitoring frequency.

[0095] The first stage may be the initial stage of the reaction, the second stage may be the middle stage of the reaction, and the third stage may be the final stage of the reaction. The first monitoring frequency, the second monitoring frequency, and the third monitoring frequency may be determined based on experiments.

[0096] Considering that in the early stage of steelmaking, the reaction is relatively stable, and the composition and temperature of the molten steel change slowly. The first monitoring frequency can be 10 minutes / time. When steelmaking enters the middle stage, the reaction becomes violent, and the temperature and composition of the molten steel change rapidly. According to the changes in the reaction stage, the monitoring frequency needs to be increased, such as adjusting it to once every 3 minutes, that is, the second monitoring frequency. This is because a large amount of carbon is oxidized in the middle stage, and the temperature of the molten steel may rise rapidly from 1520℃ to 1600℃ in a short period of time, and the carbon content will also drop sharply. Frequent monitoring can obtain these rapidly changing data in time to better control the steelmaking process.

[0097] At the end of steelmaking, the reaction gradually stabilizes, and the molten steel approaches the target composition and temperature, but the accuracy requirement is higher. At this time, the monitoring frequency can be appropriately reduced, but sufficient monitoring times must still be ensured to ensure that the molten steel meets the steelmaking standards. For example, the monitoring frequency is adjusted to once every 5 minutes, which is the third monitoring frequency.

[0098] It can be concluded from the above that the present disclosure avoids unnecessary frequent monitoring by reasonably adjusting the monitoring frequency according to the characteristics of the reaction stage. In the middle stage of the reaction, this embodiment can capture the changes of key parameters such as molten steel composition and temperature more timely and accurately by increasing the monitoring frequency, providing more reliable data support for the adjustment of the control strategy. The dynamic adjustment of the monitoring frequency makes the monitoring data more consistent with the changing laws of the actual reaction process, improves the accuracy and reliability of the data, and enhances the accuracy and reliability of converter steelmaking control.

[0099] In one embodiment of the present disclosure, in the process of converter steelmaking, since there are many types of scrap steel and the quality and price vary greatly, in order to control the quality of steel and production costs, it is necessary to determine the quality of scrap steel, and the yield rate is generally used to characterize the quality of scrap steel. The metal yield rate refers to the ratio of the output of steel billets produced per unit time in the steelmaking production process to the sum of steel and other alloy materials consumed in producing this batch of steel billets.

[0100] In this embodiment, the metal yield can be calculated by the following steps: Step 1: Determine the scrap steel types for the test and comparative experiments, prepare the raw materials, select the steel type for the test, arrange the production plan, and ensure that the experimental process meets the test requirements; Step 2: Measure and load molten iron and scrap steel, ensure that the loading amount of scrap steel is equivalent to the consumption of molten iron, and record the loading amount and material type of molten iron and scrap steel; Step 3: Use the same auxiliary material structure for smelting. The C (carbon content), P (phosphorus content), temperature, slag basicity and T.Fe (total iron content) at the end of converter smelting should be kept at the same level. Ensure that the process control level of the test heat is equivalent to that of the comparative test heat, eliminate the influence of the process control level on the yield, and record the usage of coolant and furnace iron blocks; Step 4: Ensure clean steel tapping and avoid slag. Add the same amount and type of alloy and top slag during steel tapping, and use a comparison algorithm to eliminate the influence of the metering system on the yield test results.

[0101] In step one, all weighing systems used in the test are calibrated, and all measurements are required to be completed when the material is stationary to ensure the accuracy of the measurement results; the test scrap steel and the scrap steel for the comparative test have the same quality grade; the same quality grade refers to steel types with equivalent C, P and temperature requirements at the converter smelting endpoint.

[0102] During the smelting process of step three, the same weighing equipment is used to weigh the molten iron, scrap steel and molten steel used in the test heat and the comparative test heat.

[0103] The composition and temperature of the molten iron are the same, and the molten iron consumption of the test and comparative test furnaces is the same. The molten iron consumption refers to the ratio of the molten iron loading to the steel output. The same molten iron composition and temperature are to eliminate the influence of the molten iron conditions on the yield, and the same molten iron consumption is to fully eliminate the influence of the systematic error. When comparing calculations, the systematic error of the added amount is transferred to the molten iron. Therefore, the greater the difference in molten iron consumption, the greater the impact on the accuracy of the yield.

[0104] In step 4, remove the data of the furnaces with process and measurement abnormalities, and ensure that the scrap steel used in the test furnace is of the same type; the number of test furnaces and comparison test furnaces should be no less than 10 to ensure that the system errors of the test furnaces and comparison furnaces are at the same level.

[0105] The recovery rate of molten iron can be calculated by the first formula, which can be: ,in, is the recovery rate of molten iron, For the comparison test of the amount of molten steel tapped, the results of the comparison test can be used to obtain: In order to compare the total amount of material added during the steel-making process, the data during the comparative test can be obtained by statistical analysis. To compare the amount of coolant added in the test, the data can be obtained through the statistics of the test process. is the yield of coolant, which is a known quantity, The loading amount of scrap steel can be obtained by comparing the statistical data during the test process. is the recovery rate of the scrap steel, is a known quantity, The amount of iron blocks used to replenish the furnace can be obtained through the statistics of the data during the comparative test. is the recovery rate of the iron blocks for the furnace repair, which is a known quantity. To compare the amount of molten iron charged in the test, the data during the comparative test can be obtained through statistics.

[0106] The recovery rate of the test scrap steel can be calculated by the second formula, which can be: ,in, To test the scrap steel recovery rate, To test the amount of molten steel produced, the data statistics during the test can be obtained. The total amount of material added during the steel-making process can be obtained through data statistics during the test. is the amount of coolant added in the test, which can be obtained through data statistics during the test. is the yield of coolant, which is a known quantity, The amount of molten iron charged in the test furnace can be obtained through data statistics during the test. is the recovery rate of molten iron, The amount of iron blocks used to fill the furnace during the test can be obtained through data statistics during the test. is the recovery rate of the iron blocks for the furnace repair, which is a known quantity. The loading amount of scrap steel for testing can be obtained through data statistics during the test process.

[0107] The experimental group and the control group were carried out at the same time. Figure 2 The process shown is carried out. Figure 2 A schematic diagram of a test process for calculating metal recovery rate provided in one embodiment of the present disclosure; see Figure 2 During the test, it is necessary to record the furnace number, the amount of self-produced scrap steel and test scrap steel added, the amount of molten iron added, the amount of alloy added, the weight of the empty package, the weight of the heavy package and other data, and take slag samples to analyze the total iron content in the slag.

[0108] The raw material admission stage requires statistics on the raw material entry specifications, molten iron, scrap steel, auxiliary raw materials, coolant, and ferroalloy quantities, and then the raw material ratios can be calculated based on the scrap steel ratio standards and molten iron standards. Then, loading, blowing, adjustment, tapping, slag splashing treatment, and slag dumping are carried out.

[0109] During the blowing process, blowing can be carried out according to the oxygen lance position standard, liquid level measurement standard, liquid level height calculation, oxygen lance position setting standard, stop blowing [C] range setting standard ([C] refers to the carbon content in the molten steel) and special blowing standards. During the blowing process, the value of the blowing calculation is used to control whether to lower the lance and blow, and the consumption of cooling energy, auxiliary raw materials and oxygen is collected in real time.

[0110] Adjustments can be made based on sampling standards, steel-tapping judgment standards, post-blowing standards, temperature adjustment standards, and low-temperature prevention standards. Whether to tap steel can be controlled based on tapping port management standards, anti-rephosphorus-slag use standards, alloy calculations, alloy element recovery rates, alloy input sequence, and steel-liquid overflow prevention standards. Slag splashing can be handled and monitored based on slag splashing furnace protection standards, and slag dumping can be performed based on slag handling standards.

[0111] The test adopts the charging mode of self-produced scrap steel and purchased scrap steel to determine the scrap steel recovery rate. At the same time, in order to reduce the influence of scrap steel quality, size, scrap steel state in the molten pool, incomplete melting, incomplete steel tapping and measurement error on the scrap steel recovery rate determination, this test sets up a comparison group and a test group to reduce such errors. The comparison group only adds a single self-produced scrap steel, and the test group uses self-produced scrap steel and a purchased scrap steel. The scrap steel matching mode is shown in Table 2. The above-mentioned various standards can be determined according to actual conditions.

[0112] Table 2 Scrap steel matching pattern of the experimental group

[0113] Since molten iron is a common variable for the control group and the test group, the molten iron recovery rate obtained by the control group is used as a known condition for the test group to determine the recovery rate of purchased scrap steel. At the same time, the quality of self-produced scrap steel is good and the recovery rate is stable. According to the analysis of actual production data, the recovery rate of self-produced scrap steel is always 96%. Therefore, the recovery rate of self-produced scrap steel is used as a known constant. Through the monitoring and analysis of alloying elements in molten steel before and after alloying, it can be known that the recovery rate of alloy is always 98%.

[0114] When calculating the recovery rate of each type of scrap steel, the comparison group and the test group each conducted 10 effective heats of tests, substituted the molten steel weight, alloy weight, and molten iron weight of the comparison group into the formula to obtain the molten iron recovery rate, and calculated the average of the molten iron recovery rates of the 10 heats. The recovery rate of other purchased scrap steel in each group of tests can be obtained, and finally the average recovery rate of the scrap steel in the test group can be obtained.

[0115] Through field tests, the relevant data of self-produced scrap steel, alloy addition, and molten iron addition in the comparison group were recorded, as shown in Table 3. The relevant data of molten iron addition, self-produced scrap steel addition, and steel bar briquette addition in the test group were recorded, as shown in Table 4. Substituting the test data in Tables 3 and 4 into the first formula and the second formula, the recovery rate of purchased scrap steel can be obtained, as shown in Table 5.

[0116] Table 3 Comparison group data

[0117] Table 4 Experimental group data

[0118] Table 5 Scrap steel recovery rate

[0119] It can be seen from Table 5 that the recovery rate of each type of purchased scrap steel varies. The recovery rates of steel bar briquettes, automobile scrap parts, ship demolition plate briquettes and special grade crushed materials are all below 90%, while the recovery rates of high-quality refined materials, automobile plate briquettes, stamping parts, steel plate materials, fine scrap steel and punching iron are all above 90%.

[0120] The yield rate can be used as an important feedback indicator to adjust the monitoring and control strategy. If the metal yield rate is low over a period of time, by analyzing the production data, it may be found that there is a problem with the monitoring and control of a certain link. For example, if it is found that the yield rate is reduced due to incomplete melting of scrap steel, then the monitoring of scrap steel quality and melting process can be strengthened, such as increasing the frequency of scrap steel composition monitoring, optimizing the location of temperature monitoring points, etc., so as to more accurately grasp the scrap steel melting situation, timely adjust steelmaking parameters, and improve the yield rate.

[0121] For example, in response to the metal yield being less than a first yield threshold, increasing the monitoring frequency by a first frequency step to obtain a second monitoring frequency; controlling the reaction monitoring device to perform monitoring based on a second monitoring frequency; In response to controlling the reaction monitoring device to perform monitoring based on the second monitoring frequency and the metal yield being less than the first yield threshold, an alarm is issued.

[0122] In this embodiment, when the metal recovery rate is less than the first recovery rate threshold, it may be because the monitored value is not accurate enough, resulting in deviations in the supply parameters of the converter steelmaking process, thereby causing the metal recovery rate to decrease. The first recovery rate threshold and the first frequency step can be determined based on experience.

[0123] Changes in yield can also help optimize control parameters. When the yield fluctuates, in addition to checking the monitoring link, it is also necessary to examine whether the control parameters are reasonable. For example, if the yield drops due to inaccurate control of the carbon content at the end of the blowing, then it is necessary to re-evaluate and adjust the control parameters at the end of the blowing based on the data feedback of the yield, such as adjusting the oxygen supply curve, optimizing the insertion time and position of the auxiliary gun, and other monitoring and control methods, so as to more accurately control the carbon content and improve the yield.

[0124] It can be concluded from the above that by accurately calculating the metal recovery rate, enterprises can accurately understand the utilization efficiency of different types of scrap steel, thereby optimizing scrap steel procurement strategies, selecting more cost-effective types of scrap steel, and reducing production costs. At the same time, as a feedback indicator, the metal recovery rate can guide enterprises to adjust the monitoring and control strategies in the steelmaking process, reduce waste caused by incomplete melting of scrap steel, and improve the overall utilization rate of scrap steel. By comparing the data of the experimental group and the comparison group in this embodiment, the enterprise can more accurately grasp the influence of various factors in the steelmaking process on the metal recovery rate, thereby optimizing the steelmaking process parameters, such as the carbon content at the end of blowing, temperature control, etc., and improving the stability and controllability of the steelmaking process.

[0125] Corresponding to the intelligent control method for converter steelmaking in the above embodiment, Figure 3This is a block diagram of the structure of the converter steelmaking intelligent control system provided by an embodiment of the present disclosure. For the convenience of explanation, only the parts related to the embodiment of the present disclosure are shown. Figure 3 The converter steelmaking intelligent control system 20 includes: a strategy decision module 21, a monitoring module 22 and a control module 23.

[0126] Wherein, the strategy decision module 21 is used to determine the target control strategy from multiple standard control strategies based on multiple steelmaking characteristics, and the control parameters of the multiple standard control strategies are different; Monitoring module 22, used to control the reaction monitoring device to monitor the converter steelmaking process based on the target control strategy to obtain reaction monitoring data; The control module 23 is used to determine the supply parameters of the converter steelmaking based on the reaction monitoring data.

[0127] In one embodiment of the present disclosure, the strategy decision module 21 is specifically used to determine the target matching degree between the first steelmaking feature and the first standard steelmaking feature, the first steelmaking feature is a feature among multiple steelmaking features, and the first standard steelmaking feature is a steelmaking feature among the standard steelmaking features corresponding to the first steelmaking feature; Determine the standard control strategy corresponding to the first standard steelmaking characteristic with the highest target matching degree among all targets as the target control strategy; Among them, the standard steelmaking characteristics are the steelmaking characteristics corresponding to the standard control strategy.

[0128] In one embodiment of the present disclosure, the converter steelmaking intelligent control system 20 further includes: a reaction stage determination module; a reaction stage determination module, for determining a first reaction stage value based on flame characteristics; determining a second reaction stage value based on the gas characteristic; determining a third reaction stage value based on the reaction monitoring data; A reaction phase is determined based on the first reaction phase value, the second reaction phase value, and the third reaction phase value.

[0129] In one embodiment of the present disclosure, the converter steelmaking intelligent control system 20 further includes: a strategy adjustment module; A strategy adjustment module, used for adjusting the target control strategy based on the reaction stage to obtain a second control strategy; Based on the second control strategy, the reaction monitoring device is controlled to monitor the converter steelmaking process to obtain reaction monitoring data.

[0130] In one embodiment of the present disclosure, the reaction stage determination module is specifically configured to: determine a first stage value based on a first reaction stage value and a first weight; determining a second stage value based on the second reaction stage value and the second weight; Determining a third stage value based on the third reaction stage value and the third weight; The sum of the first stage value, the second stage value, and the third stage value is taken as the reaction stage value; determining a reaction stage based on the reaction stage value; Among them, the first weight is the weight corresponding to the first reaction stage value, the second weight is the weight corresponding to the second reaction stage value, and the third weight is the weight corresponding to the third reaction stage value.

[0131] In one embodiment of the present disclosure, the reaction stage determination module is specifically used to: determine the first initial weight, the second initial weight, and the third initial weight respectively; Determine the reaction stage by performing weighted calculation based on the first reaction stage value, the first initial weight, the second reaction stage value, the second initial weight, the third reaction stage value and the third initial weight; In response to the reaction stage being the first stage, increasing the first initial weight with the first flame step length to obtain the first weight; and decreasing the second initial weight with the first gas step length to obtain the second weight; and decreasing the third initial weight with the first monitoring step length to obtain the third weight; In response to the reaction stage being the second stage, reducing the first initial weight with a second flame step length to obtain a first weight; and increasing the second initial weight with a second gas step length to obtain a second weight; and increasing the third initial weight with a second monitoring step length to obtain a third weight; In response to the reaction stage being the third stage, the first initial weight is reduced by a third flame step to obtain a first weight; and the third initial weight is reduced by a third gas step to obtain a second weight; and the third initial weight is increased by a third monitoring step to obtain a third weight.

[0132] In one embodiment of the present disclosure, the converter steelmaking intelligent control system 20 further includes: a frequency adjustment module; A frequency adjustment module for determining a monitoring frequency based on a reaction stage; The reaction monitoring device is controlled to perform monitoring based on the monitoring frequency.

[0133] See also Figure 4 , Figure 4 A schematic block diagram of an electronic device provided by an embodiment of the present disclosure. Figure 4The electronic device 300 in the embodiment shown may include: one or more processors 301, one or more input devices 302, one or more output devices 303 and one or more memories 304. The processors 301, input devices 302, output devices 303 and memories 304 communicate with each other via a communication bus 305. The memory 304 is used to store computer programs, which include program instructions. The processor 301 is used to execute the program instructions stored in the memory 304. The processor 301 is configured to call the program instructions to execute the functions of each module / unit in the above-mentioned device embodiments, such as Figure 3 The functions of modules 21 to 23 are shown.

[0134] It should be understood that in the embodiment of the present disclosure, the processor 301 may be a central processing unit (CPU), and the processor may also be other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc.

[0135] The input device 302 may include a touch panel, a fingerprint collection sensor (for collecting the user's fingerprint information and fingerprint direction information), a microphone, etc., and the output device 303 may include a display (LCD, etc.), a speaker, etc.

[0136] The memory 304 may include a read-only memory and a random access memory, and provide instructions and data to the processor 301. A portion of the memory 304 may also include a non-volatile random access memory. For example, the memory 304 may also store information about the device type.

[0137] In a specific implementation, the processor 301, input device 302, and output device 303 described in the embodiments of the present disclosure can execute the implementation methods described in the first and second embodiments of the intelligent control method for converter steelmaking provided in the embodiments of the present disclosure, and can also execute the implementation methods of the electronic device described in the embodiments of the present disclosure, which will not be repeated here.

[0138] In another embodiment of the present disclosure, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores a computer program, wherein the computer program includes program instructions, and when the program instructions are executed by the processor, all or part of the processes in the above-mentioned embodiment method are implemented, and the computer program can also be completed by instructing the relevant hardware through the computer program. The computer program can be stored in a computer-readable storage medium, and when the computer program is executed by the processor, the steps of each of the above-mentioned method embodiments can be implemented. Among them, the computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or some intermediate form, etc. The computer-readable medium can include: any entity or device capable of carrying computer program code, recording medium, U disk, mobile hard disk, magnetic disk, optical disk, computer memory, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), electric carrier signal, telecommunication signal and software distribution medium, etc.

[0139] The computer-readable storage medium may be an internal storage unit of the electronic device of any of the aforementioned embodiments, such as a hard disk or memory of the electronic device. The computer-readable storage medium may also be an external storage device of the electronic device, such as a plug-in hard disk, a smart memory card (Smart Media Card, SMC), a secure digital (SecureDigital, SD) card, a flash card (Flash Card), etc. equipped on the electronic device. Furthermore, the computer-readable storage medium may also include both an internal storage unit of the electronic device and an external storage device. The computer-readable storage medium is used to store computer programs and other programs and data required by the electronic device. The computer-readable storage medium may also be used to temporarily store data that has been output or is to be output.

[0140] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of the two. In order to clearly illustrate the interchangeability of hardware and software, the composition and steps of each example have been generally described in terms of function in the above description. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this disclosure.

[0141] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the electronic devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0142] In the several embodiments provided in the present application, it should be understood that the disclosed electronic devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic, for example, the division of units is only a logical function division, and there may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the mutual coupling or direct coupling or communication connection shown or discussed can be an indirect coupling or communication connection through some interfaces or units, or it can be an electrical, mechanical or other form of connection.

[0143] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the embodiments of the present disclosure.

[0144] In addition, each functional unit in each embodiment of the present disclosure may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0145] The above are only specific embodiments of the present disclosure, but the protection scope of the present disclosure is not limited thereto. Any technician familiar with the technical field can easily think of various equivalent modifications or replacements within the technical scope disclosed in the present disclosure, and these modifications or replacements should be included in the protection scope of the present disclosure. Therefore, the protection scope of the present disclosure should be based on the protection scope of the claims.

Claims

1. A converter steelmaking intelligent control method, characterized in that: include: Determining a target control strategy from a plurality of standard control strategies based on a plurality of steelmaking characteristics, wherein the plurality of standard control strategies have different control parameters; Based on the target control strategy, a reaction monitoring device is controlled to monitor the converter steelmaking process to obtain reaction monitoring data; Supply parameters for converter steelmaking are determined based on the reaction monitoring data.

2. The intelligent control method for converter steelmaking according to claim 1, characterized in that: The determining of a target control strategy from a plurality of standard control strategies based on a plurality of steelmaking characteristics comprises: Determining a target matching degree between a first steelmaking feature and a first standard steelmaking feature, wherein the first steelmaking feature is a feature among the plurality of steelmaking features, and the first standard steelmaking feature is a steelmaking feature among the standard steelmaking features corresponding to the first steelmaking feature; Determine the standard control strategy corresponding to the first standard steelmaking feature with the highest target matching degree as the target control strategy; The standard steelmaking characteristics are steelmaking characteristics corresponding to the standard control strategy.

3. The intelligent control method for converter steelmaking according to claim 1, characterized in that: Also includes: determining a first reaction stage value based on the flame characteristics; determining a second reaction stage value based on the gas characteristic; determining a third reaction stage value based on the reaction monitoring data; A reaction phase is determined based on the first reaction phase value, the second reaction phase value, and the third reaction phase value.

4. The intelligent control method for converter steelmaking according to claim 3, characterized in that: Also includes: Adjust the target control strategy based on the reaction stage to obtain a second control strategy; Based on the second control strategy, the reaction monitoring device is controlled to monitor the converter steelmaking process to obtain the reaction monitoring data.

5. The intelligent control method for converter steelmaking according to claim 3, characterized in that: The determining the reaction stage based on the first reaction stage value, the second reaction stage value and the third reaction stage value comprises: Determining a first stage value based on the first reaction stage value and the first weight; determining a second stage value based on the second reaction stage value and the second weight; Determining a third stage value based on the third reaction stage value and the third weight; taking the sum of the first stage value, the second stage value and the third stage value as a reaction stage value; determining a reaction stage based on the reaction stage value; Among them, the first weight is the weight corresponding to the first reaction stage value, the second weight is the weight corresponding to the second reaction stage value, and the third weight is the weight corresponding to the third reaction stage value.

6. The intelligent control method for converter steelmaking according to claim 5, characterized in that: Before determining the reaction stage based on the first reaction stage value, the second reaction stage value and the third reaction stage value, the method further includes: Determine a first initial weight, a second initial weight, and a third initial weight respectively; Determine the reaction stage by performing weighted calculation based on the first reaction stage value, the first initial weight, the second reaction stage value, the second initial weight, the third reaction stage value and the third initial weight; In response to the reaction stage being the first stage, increasing the first initial weight with a first flame step length to obtain a first weight; and decreasing the second initial weight with a first gas step length to obtain a second weight; and decreasing the third initial weight with a first monitoring step length to obtain a third weight; In response to the reaction stage being the second stage, reducing the first initial weight with a second flame step length to obtain a first weight; and increasing the second initial weight with a second gas step length to obtain a second weight; and increasing the third initial weight with a second monitoring step length to obtain a third weight; In response to the reaction stage being the third stage, the first initial weight is reduced by a third flame step to obtain the first weight; and the third initial weight is reduced by a third gas step to obtain a second weight; and the third initial weight is increased by a third monitoring step to obtain a third weight.

7. The intelligent control method for converter steelmaking according to claim 1, characterized in that: Also includes: determining a monitoring frequency based on the reaction stage; The reaction monitoring device is controlled to perform monitoring based on the monitoring frequency.

8. An intelligent control system for converter steelmaking, characterized in that: include: a strategy decision module, for determining a target control strategy from a plurality of standard control strategies based on a plurality of steelmaking characteristics, wherein the plurality of standard control strategies have different control parameters; A monitoring module, used to control a reaction monitoring device to monitor the converter steelmaking process based on the target control strategy to obtain reaction monitoring data; A control module is used to determine supply parameters for converter steelmaking based on the reaction monitoring data.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and running on the processor, characterized in that: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 7 are implemented.

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