A method for intelligent and stable control of molten steel quality in a narrow window

Abstract

The present invention relates to a method for intelligent and stable control of molten steel quality within a narrow window. First, a refining target parameter is determined; second, the refining target parameter is used as an adaptive factor; then, using the adaptive factor as a condition, an optimal refining path that meets the condition is found in a molten steel quality narrow window control database; the refining exit parameters, refining entry parameters, converter parameters, and molten iron pretreatment exit parameters on the optimal refining path are evaluated and calculated to obtain control target values ​​for each parameter; finally, the molten steel is stably controlled based on the optimal refining path and the control target values ​​for each parameter. The present invention determines the optimal refining path and control target values ​​based on the set refining target parameters, thereby achieving intelligent and stable control of molten steel quality within a narrow window, providing key technical support for the intelligent development of steel process technology.

Description

Technical Field

[0001] The present invention relates to the field of steel smelting, and in particular to a method for intelligent and stable control of a narrow window of molten steel quality. Background Art

[0002] Within the entire steelmaking process, hot metal pretreatment primarily controls the [S] content; the converter process primarily controls the [C] and [P] contents, as well as the tapping temperature. The LF furnace performs heating, desulfurization, deoxidation, and alloying. Due to its relatively simple equipment and low smelting costs, it is suitable for most steel grades except ultra-low carbon steel, or as a refining step in a refining duplex. RH refining performs vacuum decarburization and degassing, homogenizes the composition and temperature, alloys, and improves steel cleanliness. RH refining offers a short processing cycle, high throughput, excellent refining results, and precise endpoint control. With an endpoint [C] of <0.003%, RH refining is suitable for steel grades with stringent carbon and gas content requirements, including low-carbon thin plate steel, ultra-low carbon deep drawing steel, heavy plate steel, silicon steel, bearing steel, and heavy rail steel. Currently, hot metal pretreatment, the converter, LF refining, and RH refining are all automated.

[0003] Although the existing converter, LF refining and RH refining models can provide certain guidance for smelting operations, the selection of the best process route for the entire steelmaking section, the optimization of process interface functions, and the narrow window control of process parameters still need to be further improved. Summary of the Invention

[0004] The purpose of the present invention is to solve the shortcomings of the prior art. The present invention aims to provide a method for intelligent and stable control of the narrow window of molten steel quality to solve the above-mentioned problems in the prior art.

[0005] The above technical objectives of the present invention will be achieved through the technical solutions described below.

[0006] A method for intelligent and stable control of molten steel quality within a narrow window comprises the following steps:

[0007] S1. Determine the refining target parameters;

[0008] S2. The refined target parameter is used as an adaptive factor;

[0009] S3. Using the adaptive factor as a condition, find the optimal refining path that satisfies the condition in the narrow window control database for molten steel quality;

[0010] S4. The optimal refining path on the refining station parameters, refining station parameters, converter parameters and molten iron pretreatment station parameters are evaluated and calculated to obtain the control target value of each parameter;

[0011] S5. Stably control the molten steel according to the optimal refining path and the control target values ​​of the parameters.

[0012] According to the aspects and any possible implementations described above, an implementation is further provided, wherein the refining target parameters in step S1 include target composition of the refined molten steel, target molten steel temperature, target total oxygen TO content of the molten steel, target smelting time and target production cost.

[0013] According to the aspects and any possible implementation methods described above, an implementation method is further provided, wherein S3 is specifically: using the above-mentioned adaptive factor as a condition, in the narrow window historical control database of molten steel quality, an iterative + adaptive calculation method is used to find data that meets the adaptive factor conditions, that is, the iterative calculation is stopped, and the optimal refining path that meets the adaptive factor conditions is output according to the data found.

[0014] According to the above aspects and any possible implementation method, an implementation method is further provided. If no data meeting the adaptive factor conditions is found, the data obtained after 4 iterative calculations are used as a basis to output the optimal refining path corresponding to the adaptive factor conditions, specifically: if 20 furnace data cannot be matched according to the conditions, then under the condition of ensuring the consistency of the target composition of the molten steel, the upper and lower limits of the refining target parameter value range are increased by 10% for the first iteration; if the 20 furnace data are still not met, the upper and lower limits of the refining target parameter value range are increased by 12% for the second iteration; if the 20 furnace data are still not met, the upper and lower limits of the refining target parameter value range are increased by 15% for the third iteration; if the 20 furnace data are still not met, the upper and lower limits of the refining target parameter value range are increased by 20% for the fourth iteration.

[0015] According to the aspects and any possible implementation methods described above, an implementation method is further provided, in which the refining entry parameters, converter parameters and molten iron pretreatment exit parameters are evaluated in step S4 to obtain the deduction points corresponding to each parameter, and the deduction points are obtained by multiplying the absolute values ​​of the differences between the refining entry parameters, converter parameters and molten iron pretreatment exit parameters and the corresponding refining target parameters by the corresponding weights and coefficients.

[0016] In the above aspects and any possible implementation, a further implementation is provided, wherein the calculation formula for the control target value of each parameter is:

[0017]

[0018] Where S Tot Indicates the control target value of each parameter, and n can be any value from 2 to 5.

[0019] According to the aspects and any possible implementation methods described above, an implementation method is further provided, wherein the refining exit parameters in S4 include the molten steel composition, molten steel temperature, TO content, smelting time and production cost at the time of refining exit; the refining entry parameters include the molten steel composition, molten steel temperature and TO content at the time of refining entry.

[0020] According to the aspects described above and any possible implementation methods, an implementation method is further provided, wherein the converter parameters include converter steel composition, molten steel temperature, TO content, time rhythm, corresponding converter production cost, molten iron composition and molten iron temperature.

[0021] According to the aspects and any possible implementations described above, there is further provided an implementation, wherein the molten iron pretreatment outlet parameters include the pretreatment outlet molten iron composition and the molten iron outlet temperature.

[0022] The present invention also provides molten steel, which is prepared by the method provided by the present invention.

[0023] Beneficial technical effects of the present invention

[0024] The method for intelligent and stable control of molten steel quality within a narrow window provided by an embodiment of the present invention comprises the following steps: first, determining a refining target parameter; second, using the refining target parameter as an adaptive factor; then, using the adaptive factor as a condition, finding an optimal refining path that meets the condition in a molten steel quality narrow window control database; evaluating and calculating the refining exit parameters, refining entry parameters, converter parameters, and molten iron pretreatment exit parameters on the optimal refining path to obtain control target values ​​for each parameter; and finally, stably controlling the molten steel based on the optimal refining path and the control target values ​​for each parameter. The present invention determines the optimal refining path and control target values ​​based on the set refining target parameters, thereby achieving intelligent and stable control of molten steel quality within a narrow window, and can provide key technical support for the intelligent development of steel process technology. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] The embodiments of the present invention are described in detail below with reference to the accompanying drawings, in which:

[0026] Figure 1 A schematic diagram of a method flow in an embodiment of the present invention;

[0027] Figure 2 Schematic diagram of the narrow window control implementation process in an embodiment of the present invention. DETAILED DESCRIPTION

[0028] To make the technical problems, technical solutions and advantages to be solved by the present invention clearer, the present invention will be described in detail below with reference to the accompanying drawings and specific embodiments, but the embodiments of the present invention are not limited thereto.

[0029] like Figure 1 As shown, a method for intelligent and stable control of molten steel quality narrow window of the present invention comprises the following steps:

[0030] S1. Determine the refining target parameters;

[0031] S2. The refined target parameter is used as an adaptive factor;

[0032] S3. Using the adaptive factor as a condition, find the optimal refining path that satisfies the condition in the narrow window control database for molten steel quality;

[0033] S4. The optimal refining path on the refining station parameters, refining station parameters, converter parameters, molten iron pretreatment station parameters are evaluated and calculated to obtain the control target value of each parameter;

[0034] S5. Stably control the molten steel according to the optimal refining path and the control target values ​​of the parameters.

[0035] The specific steps are as follows:

[0036] A01. Determine the target composition, target temperature, target total oxygen (TO) content, target smelting time, and target production cost of the refined steel liquid based on the process requirements;

[0037] A02. The target composition of the refined molten steel, the target molten steel temperature, the target total oxygen TO content of the molten steel, the target smelting time, the target production cost as an adaptive factor, and in order as a basis for determining the optimal refining path;

[0038] A03. Using the above-mentioned adaptive factors as conditions, in the narrow window historical control database of molten steel quality, an iterative + adaptive calculation method is used to find data that meets the adaptive factor conditions, that is, the iterative calculation is stopped, and the optimal refining path that meets the adaptive factor conditions is output based on the data found; if no data that meets the adaptive factor conditions is found, the data obtained after 4 iterative calculations are used as the basis to output the optimal refining path that meets the adaptive factor conditions.

[0039] A04. After determining the optimal refining path, the refining exit parameters along the selected optimal refining path are scored through iterative calculations. A subtraction calculation is first performed to evaluate the refining entry parameters, converter parameters, and hot metal pretreatment exit parameters, yielding a subtraction score corresponding to each parameter. The subtraction score is the product of the absolute value of the difference between the refining entry parameters, converter parameters, and hot metal pretreatment exit parameters and the refining target parameters, multiplied by the corresponding weight and coefficient. The formula is as follows:

[0040]

[0041] In the above formula, S ei Indicates the deduction of refined outbound parameters;

[0042] Q ei It represents the refining exit parameters, which can be obtained from the narrow window historical control database of molten steel quality;

[0043] Q * ei Represents the pre-determined refinement target parameters;

[0044] γ represents the weight of the refined outbound parameter;

[0045] η represents the coefficient of refined outbound parameters;

[0046] i can take any value from 1 to 5.

[0047] The weight is used to distinguish the calculation priority of different refined outbound parameters, and the coefficient is used to reduce the calculation difference caused by the order of magnitude coefficients of different refined outbound parameters.

[0048] Taking the calculation of refined exit score reduction as an example, the remaining target parameters are scored according to the above process. e1 Indicates the deduction of the target composition parameter of the refined steel liquid; when i is 2, S e2 Indicates the deduction of the target temperature parameter of the refined steel liquid at the exit station; when i is 3, S e3 Indicates the deduction of the target total oxygen content parameter of the refined steel liquid; when i is 4, S e4 The deduction of the target smelting time parameter of refined steel liquid; when i is 5, S e5 Deduction of target production cost parameters for refined outgoing steel liquid.

[0049] A05. Calculate the score of the refined outbound parameters based on the deduction of the refined outbound parameters calculated in step A04. The calculation formula is as follows:

[0050]

[0051] Among them, S Tot Indicates the score of refined outbound parameters. Here, n is 5.

[0052] As can be seen from the above calculation, the score is calculated based on a 100-point scale. The deduction for the refined outbound parameters is subtracted from 100 points to obtain the final score for the refined outbound parameters. The highest refined outbound parameters are the instance that best matches the pre-determined target parameters and will be used to find the next step in refining the inbound parameters.

[0053] A06. Use the same calculation method as steps A04-A05 to deduct the steel composition, steel temperature, and TO content in the refining station, and control the steel composition, steel temperature, and TO content in the refining station according to the corresponding parameters to finally obtain the scores of the above refining station parameters. In this step, the value of n in the above formula is 3, and the refining station parameter example with the highest score is selected to find the parameters for the next step of converter tapping.

[0054] A07. Use the same calculation method as steps A04-A05 to calculate the converter steel composition, molten steel temperature, TO content, smelting time, and corresponding converter production cost to obtain their respective scores. In this step, the value of n in the above formula is 5. Select the converter steel parameter example with the highest score to find the converter steel parameter for the next step.

[0055] A08. Calculate the composition and temperature of the molten iron entering the converter using the same calculation method as steps A04-A05 to obtain their respective scores. In this step, the value of n in the above formula is 2.

[0056] A09. Use the same calculation method as steps A04-A05 to calculate the composition and temperature of the molten iron at the outlet of the molten iron pretreatment station to obtain the corresponding score. In this step, the value of n in the above formula is 2.

[0057] A10. Through the above steps A04-A05, the corresponding scores of the relevant parameters of each process on the optimal path are obtained, and each score is used as the target control value. The molten iron pretreatment, converter, refining process, etc. are stably controlled according to the aforementioned target control value using the optimal refining path. The final result is molten steel with excellent composition, appropriate temperature, qualified total oxygen content (TO) of the molten steel, reasonable smelting time in the refining stage, and the lowest production cost of the refining process.

[0058] Preferably, in an embodiment of the present invention, the refining exit parameters include the molten steel composition, molten steel temperature, TO content, smelting time and production cost at the time of refining exit; the refining entry parameters include the molten steel composition, molten steel temperature and TO content at the time of refining entry; the converter parameters include the converter tapping composition, molten steel temperature, TO content, time rhythm, corresponding converter production cost, inlet molten iron composition and inlet molten iron temperature; the molten iron pretreatment exit parameters include the pretreatment exit molten iron composition and molten iron exit temperature.

[0059] Preferably, step A03 in the embodiment of the present invention is specifically as follows for the iterative + adaptive calculation method: for the adaptive factors: target molten steel composition, target molten steel temperature, target total oxygen TO content, target smelting time and target production cost, 20 furnaces of completely consistent or similar refining exit data are matched in the molten steel quality narrow window control database, and the optimal refining path that meets the adaptive factor conditions is output based on the found data. The specific process is as follows:

[0060] A031: Since only the RH refining furnace has the function of removing gas components from steel among the refining equipment, the optimal path is first determined based on the adaptive factor - the target composition of the molten steel. The gas component content in the target composition of the molten steel includes but is not limited to nitrogen content [N], hydrogen content [H], target molten steel temperature, and target total oxygen content TO of the molten steel. Based on the target composition of the molten steel, it is determined whether the molten steel needs to be smelted in the RH vacuum furnace. If necessary, the current refining steps are preset to molten iron pretreatment - converter (BOF) - RH refining - continuous casting (CC). If it is determined that RH refining is not necessary after this step, the current refining steps are preset to molten iron pretreatment - converter (BOF) - LF refining - continuous casting (CC).

[0061] A032, since the LF (Ladle Furnace) has the functions of heating, deoxidation, desulfurization and alloying in the refining equipment, the need for smelting in the LF ladle furnace is determined based on the target molten steel composition, carbon [C], sulfur [S] and other alloying element contents (including but not limited to manganese, silicon, aluminum, chromium, niobium, copper, vanadium, molybdenum, nickel, etc.), and the target molten steel temperature in the adaptive factor;

[0062] A0321: If it is determined according to A031 that LF refining is not required, the preset refining path of hot metal pretreatment - converter (BOF) - RH refining - continuous casting (CC) is determined to be hot metal pretreatment - converter (BOF) - RH refining - continuous casting (CC);

[0063] A0322: If it is determined according to A031 that LF refining is required, then the preset molten iron pretreatment-converter (BOF)-RH refining-continuous casting (CC) path is changed to molten iron pretreatment-converter (BOF)-LF refining-RH refining-continuous casting (CC).

[0064] A0323: If the refining steps are preset as hot metal pretreatment - converter (BOF) - LF refining - continuous casting (CC), the refining path is determined to be hot metal pretreatment - converter (BOF) - LF refining - continuous casting (CC);

[0065] A033: If all three refining paths determined in A032 can achieve a certain target composition and target temperature, then continue to comprehensively consider the target smelting time and target production cost, and ultimately obtain the optimal refining path with consistent molten steel composition, appropriate molten steel temperature, compact production rhythm and ideal cost.

[0066] If no data meeting the adaptive factor conditions are found in A03, the data obtained after 4 iterative calculations are used as the basis to output the optimal refining path that meets the adaptive factor conditions. Specifically, if 20 furnace data cannot be matched according to the target composition of the molten steel, the target molten steel temperature, the target TO content, the target smelting time, and the target production cost, then under the condition that the target parameters of the molten steel, including all the target composition of the molten steel, the target molten steel temperature, the target TO content, the target smelting time, and the target production cost are complete, the upper and lower limits of the value range of the molten steel target composition, the target molten steel temperature, the target TO content, the target smelting time, and the target production cost are increased by 10% for the first iteration; if the 20 furnace data are still not met, the target composition of the molten steel, the target molten steel temperature, the target TO content, the target smelting time, and the target production cost are increased by 10%. The lower limit is increased by 12% for the second iteration; if the 20-furnace data is still not met, the upper and lower limits of the range of target composition, target molten steel temperature, target TO content, target smelting time, and target production cost are increased by 15% for the third iteration; if the 20-furnace data is still not met, the upper and lower limits of the range of target composition, target molten steel temperature, target TO content, target smelting time, and target production cost are increased by 20% for the fourth iteration. According to this iteration, 20 furnace data are found to score the molten steel in the next step, and each score is used as the target control value. The molten iron pretreatment, converter, refining process, etc. are stably controlled according to the above-mentioned target control value using the optimal refining path, and finally the molten steel with excellent composition, appropriate temperature, qualified TO content, reasonable smelting time in the refining stage, and the lowest production cost of the refining process is obtained.

[0067] Preferably, step A05 in the embodiment of the present invention specifically includes the following contents:

[0068] A051, Table 1 is a rule database specification table based on molten steel composition, temperature, production rhythm, cleanliness and production cost.

[0069] Table 1 Rule database calculation specification table

[0070]

[0071]

[0072] A052. As can be seen from Table 1, the data are roughly divided into four priorities. The highest priority is the composition of the molten steel, among which [C], [P], and [S] are the most strictly controlled element compositions; [Si], [Mn], [Ti], [Al] s ], [Ni], [Cr], [V] and other alloy components are given the second priority because the process is adjustable; the molten steel temperature is also considered as the second priority; the third priority is the smelting time and the molten steel total oxygen TO, which is an important indicator of the molten steel cleanliness and is used here as a reference for the molten steel cleanliness; the production cost is also taken into consideration in the rule database and is given the last priority in the database.

[0073] A053. The rule database specification table is used in the rule database to iteratively calculate the calculation items in the calculation specification table using the component weights, component score ratios, and the difference in the number of calculation times. The component weights and component score ratios are adjusted through the self-learning method. Through continuous self-learning and self-correction, the optimal score calculation rules that are closest to the on-site production data are gradually realized.

[0074] The foregoing description shows and describes several preferred embodiments of the present invention. However, as previously mentioned, it should be understood that the present invention is not limited to the forms disclosed herein and should not be construed as excluding other embodiments. Rather, the present invention can be used in various other combinations, modifications, and environments and can be modified within the scope of the present invention through the teachings above or through techniques or knowledge in the relevant field. Modifications and variations made by those skilled in the art that do not depart from the spirit and scope of the present invention are intended to be protected by the appended claims.

Claims

1. A method for intelligent and stable control of molten steel quality within a narrow window, characterized in that: The steps include: A01 determine the refining target parameters, the refining target parameters include the target composition of the molten steel, the target molten steel temperature, the target total oxygen TO content of the molten steel, the target smelting time and target production cost; A02. The target composition of the refined molten steel, the target molten steel temperature, the target total oxygen TO content of the molten steel, the target smelting time, the target production cost as adaptive factors, and in order as the basis for determining the optimal refining path; A03. Using the adaptive factor as a condition, an iterative + adaptive calculation method is used in the narrow window control database of molten steel quality to find data that meets the adaptive factor condition, then the iterative calculation is stopped and the optimal refining path that meets the adaptive factor condition is output based on the found data; A04. After determining the optimal refining path, the refining exit parameters along the selected optimal refining path are scored through iterative calculation. A subtraction calculation is first performed to evaluate the refining entry parameters, converter parameters, and hot metal pretreatment exit parameters, yielding a subtraction score corresponding to each parameter. The subtraction score is the product of the absolute value of the difference between the refining entry parameters, converter parameters, and hot metal pretreatment exit parameters and the refining target parameters, multiplied by the corresponding weight and coefficient. The formula is: , where S ei Indicates the deduction of refined outbound parameters; Q ei Represents the refining exit parameters, obtained from the narrow window historical control database of molten steel quality; represents the pre-determined refinement target parameter; γ represents the weight of the refinement outbound parameter; η represents the coefficient of the refined exit parameter; i takes any value from 1 to 5. When i takes 1 in the refined exit deduction calculation, S e1 Indicates the deduction of the target composition parameter of the refined steel liquid; when i is 2, S e2 Indicates the deduction of the target temperature parameter of the refined steel liquid at the exit station; when i is 3, S e3 Indicates the deduction of the target total oxygen content parameter of the refined steel liquid; when i is 4, S e4 The deduction of the target smelting time parameter of refined steel liquid; when i is 5, S e5 Deduction of target production cost parameters for refined steel liquid; A05. Calculate the score of the refined outbound parameters based on the deduction of the refined outbound parameters calculated in step A04. The calculation formula is as follows: , S Tot Indicates the score of refined outbound parameters, n is 5; A06. Using the same calculation method as steps A04-A05, the steel composition, steel temperature, and TO content in the refining station are deducted, and the steel composition, steel temperature, and TO content of the refining station are controlled according to the corresponding parameters to obtain the scores of the various refining station parameters. In this step, n in the above formula is set to 3; A07. Calculate the converter tapping composition, molten steel temperature, TO content, smelting time, and the corresponding converter production cost using the same calculation method as in steps A04-A05 to obtain the corresponding scores. In this step, n in the above formula is set to 5. A08. Using the same calculation method as steps A04-A05, calculate the composition and temperature of the molten iron in the converter to obtain the corresponding scores. In this step, n in the above formula is set to 2; A09 using the same calculation method as steps A04-A05 molten iron pretreatment station molten iron composition, molten iron outlet temperature is calculated to obtain the corresponding score, in this step the above formula in the value of n is 2; A10. Through steps A04-A05 above, the corresponding scores of the relevant parameters of each process on the optimal refining path are obtained. Each score is used as the target control value. The molten iron pretreatment, converter, and refining processes are stably controlled according to the aforementioned target control values ​​using the optimal refining path. The result is molten steel with excellent composition, appropriate temperature, qualified total oxygen content (TO) of the molten steel, reasonable smelting time in the refining stage, and the lowest production cost of the refining process.

2. The method according to claim 1, characterized in that If no data meeting the adaptive factor conditions is found, the data obtained after four iterative calculations are used as a basis to output the optimal refining path that meets the adaptive factor conditions.

3. The method according to claim 1, characterized in that The refining exit parameters in A04 include the molten steel composition, molten steel temperature, TO content, smelting time and production cost at the time of refining exit; the refining entry parameters include the molten steel composition, molten steel temperature and TO content at the time of refining entry.

4. The method according to claim 1, wherein The parameters of molten iron pretreatment outgoing station include the composition of molten iron outgoing station and the temperature of molten iron outgoing station.

5. Molten steel, produced by the method according to any one of claims 1 to 4.

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