Control method and device for inhibiting generation of hot-rolled strip steel oxide scale

Abstract

The invention provides a control method and device for inhibiting generation of hot-rolled strip steel oxide scale, and belongs to the technical field of strip steel machining control. The method comprises the steps that the oxide scale thickness and the oxidation component content of target strip steel are subjected to deviation value calculation, and a first deviation value set is obtained; determining a data deviation judgment result based on the first deviation value set; if the data deviation judgment result is data deviation, deviation value calculation is conducted on the oxidation distribution uniformity of the target strip steel, the temperature field data and the working roller state data, and a second deviation value set is obtained; calculating a parameter regulation priority sequence based on the second deviation value set and the multi-parameter coupling weight coefficient; generating a target parameter regulation instruction based on the parameter regulation priority sequence, the first deviation value set and the second deviation value set; the target parameter regulation and control instruction is used for indicating strip steel production control equipment to carry out parameter regulation and control. The method can improve the scale generation inhibition effect and improve the strip steel quality.

Description

Technical Field

[0001] This application belongs to the field of strip steel processing control technology, and more specifically, relates to a control method and device for suppressing the formation of iron oxide scale in hot-rolled strip steel. Background Technology

[0002] Excessive oxide scale formation during hot-rolled strip steel production has become a key bottleneck restricting product quality improvement. The oxide layer formed on the strip surface not only directly affects the product's appearance but also significantly impacts subsequent processing steps such as pickling, cold rolling, and coating. From the perspective of oxide scale formation mechanism, during hot rolling, the steel billet undergoes an oxidation reaction with oxygen and water vapor in the furnace atmosphere at high temperatures, generating oxides composed of FeO, ... and The multi-layered structure of the oxide layer makes it prone to breakage and peeling during rolling deformation and cooling, resulting in defects such as pits and dents on the surface of the strip.

[0003] Furthermore, the problem of iron oxide scale can propagate downstream along the industrial chain. For example, in the cold rolling process, residual oxide layers increase roll wear and energy consumption; in the pickling process, uneven oxide layers lead to increased acid consumption and over-pickling defects; and in the coating process, the presence of iron oxide scale reduces the bonding strength of the coating.

[0004] As end-users increasingly demand higher surface quality from strip steel, the steel industry's current quality upgrade requirements have made the control of iron oxide scale more prominent. For example, in the face of stringent requirements for defect-free surfaces in fields such as new energy vehicles and high-end home appliances, existing traditional control technologies based on single-parameter adjustment have shown significant limitations, including: fluctuations in control performance due to insufficient parameter coordination at different process stages, and a lack of adaptability when dealing with different steel grades and specifications.

[0005] Chinese patent application CN116329289B discloses a method and system for controlling iron oxide scale on the surface of hot-rolled strip steel. The laminar flow cooling employs a front-stage rapid cooling + rear-stage sparse cooling mode to reduce FeO oxidation. The change involves adding an air-jet drying device before coiling to dry residual moisture on the strip surface, preventing secondary oxidation caused by the formation of a water film during cooling. This patent describes conventional post-rolling cooling control methods, lacking temperature control during the rolling process and control to inhibit the formation of iron oxide scale in the furnace.

[0006] The invention patent with application number CN109940043B discloses a method for preparing easily pickled hot-rolled strip steel, which adopts a high-temperature rapid heating process. This patent focuses on the means of controlling iron oxide scale in the pre-finishing process, but lacks a method for suppressing secondary iron oxide scale in the finishing and post-rolling areas.

[0007] In summary, current methods for suppressing iron oxide scale in hot-rolled strip steel suffer from both insufficient suppression and excessive suppression leading to energy waste. Therefore, developing novel iron oxide scale suppression technologies has become an urgent need to improve the quality of hot-rolled strip steel products. Summary of the Invention

[0008] The purpose of this application is to provide a control method and apparatus for suppressing the formation of iron oxide scale in hot-rolled strip steel, so as to improve the effect of suppressing iron oxide scale formation.

[0009] A first aspect of this application provides a control method for suppressing the formation of iron oxide scale in hot-rolled strip steel, comprising: The deviation values ​​of the iron oxide scale thickness and oxide content of the target strip are calculated to obtain a first set of deviation values; the data deviation judgment result is determined based on the first set of deviation values; if the data deviation judgment result is data deviation, the deviation values ​​of the oxide distribution uniformity, temperature field data and work roll state data of the target strip are calculated to obtain a second set of deviation values. The parameter control priority sequence is calculated based on the second set of deviation values ​​and multi-parameter coupled weighting coefficients. The target parameter control instruction is generated based on the parameter control priority sequence, the first deviation value set, and the second deviation value set; the target parameter control instruction is used to instruct the strip steel production control equipment to perform parameter control.

[0010] A second aspect of this application provides a control device for suppressing the formation of iron oxide scale in hot-rolled strip steel, comprising: The oxidation deviation analysis module is used to calculate the deviation values ​​of the iron oxide scale thickness and oxide content of the target strip steel to obtain a first set of deviation values; the data deviation judgment result is determined based on the first set of deviation values; if the data deviation judgment result is data deviation, the deviation values ​​of the oxidation distribution uniformity, temperature field data and work roll state data of the target strip steel are calculated to obtain a second set of deviation values. The parameter control priority module is used to calculate the parameter control priority sequence based on the second set of deviation values ​​and the multi-parameter coupling weight coefficients. The parameter control module is used to generate target parameter control instructions based on the parameter control priority sequence, the first deviation value set, and the second deviation value set; the target parameter control instructions are used to instruct the strip steel production control equipment to perform parameter control.

[0011] A third aspect of this application provides an electronic device, including a memory, a processor, and a computer program stored in the memory and running on the processor, wherein the processor executes the computer program to implement the steps of the control method described above for suppressing the generation of iron oxide scale in hot-rolled strip steel.

[0012] A fourth aspect of this application provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps of the control method for suppressing the generation of iron oxide scale in hot-rolled strip steel described above.

[0013] The beneficial effects of the control method and apparatus for suppressing the formation of iron oxide scale in hot-rolled strip steel provided in this application are as follows: In this embodiment, a first set of deviation values ​​is formed by calculating the deviation values ​​of iron oxide scale thickness and oxide content. This allows for a quick determination of whether the core indicators of iron oxide scale on the strip steel exceed the standards. If they do, the deviation values ​​of oxidation distribution uniformity, temperature field data, and work roll status data are further calculated to form a second set of deviation values. This achieves comprehensive coverage of the factors affecting iron oxide scale, avoiding the limitations of traditional technologies that only control a single process. It can locate and solve the problem of iron oxide scale formation from multiple dimensions, reducing defects such as pits and dents on the strip steel surface.

[0014] This application embodiment calculates the parameter control priority sequence based on the second deviation value set and the multi-parameter coupling weight coefficient, and then generates the target parameter control instruction by combining the two types of deviation value sets. It can accurately determine the parameters that need to be controlled first according to the actual situation of the strip steel, avoiding blind adjustment. This ensures the stability of the iron oxide scale suppression effect and prevents energy waste caused by excessive suppression, which meets the needs of efficient and energy-saving production. It enables steel companies to better meet the strict requirements of new energy vehicles, high-end home appliances and other fields for the surface quality of strip steel.

[0015] In summary, the embodiments of this application can effectively solve the problems of excessive iron oxide scale formation, isolated control methods, and energy waste in the prior art for hot-rolled strip steel, and provide a practical solution for improving strip steel quality and reducing production losses. Attached Figure Description

[0016] To more clearly illustrate the technical solutions in the embodiments of this application, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0017] Figure 1 A schematic flowchart illustrating a control method for suppressing the formation of iron oxide scale in hot-rolled strip steel according to an embodiment of this application; Figure 2 This is a structural block diagram of a control device for suppressing the formation of iron oxide scale in hot-rolled strip steel according to an embodiment of this application; Figure 3 This is a schematic block diagram of an electronic device provided in an embodiment of this application. Detailed Implementation

[0018] In the following description, specific details such as particular system architectures and techniques are set forth for illustrative purposes and not for limitation, in order to provide a thorough understanding of the embodiments of this application. However, those skilled in the art will understand that this application may also be implemented in other embodiments without these specific details. In other instances, detailed descriptions of well-known systems, apparatuses, circuits, and methods have been omitted so as not to obscure the description of this application with unnecessary detail.

[0019] To make the objectives, technical solutions, and advantages of this application clearer, the following description will be provided in conjunction with the accompanying drawings and specific embodiments.

[0020] Please refer to Figure 1 , Figure 1 This is a flowchart illustrating a control method for suppressing the formation of iron oxide scale in hot-rolled strip steel according to an embodiment of this application. The method can be executed by an electronic device, and specifically, the method may include S101 to S103.

[0021] S101: Calculate the deviation values ​​for the iron oxide scale thickness and oxide content of the target strip steel to obtain a first set of deviation values; determine the data deviation judgment result based on the first set of deviation values; if the data deviation judgment result is data deviation, calculate the deviation values ​​for the oxide distribution uniformity, temperature field data and work roll state data of the target strip steel to obtain a second set of deviation values.

[0022] In this embodiment, the target strip steel refers to a specific batch or specification of strip steel that requires oxide scale control during hot rolling production. This is the object of this method, and deviation calculations and adjustments need to be made for its specific production parameters. The first deviation value set is a dataset composed of oxide scale thickness deviation values ​​and oxide composition content deviation values. It is the core basis for initially judging whether the oxide scale on the strip steel exceeds the standard, reflecting the degree of deviation of key oxide scale indicators. The data deviation judgment result is a conclusion based on the first deviation value set, divided into two categories: data deviation and no data deviation. It is used to determine whether further collection and analysis of other relevant data is needed for parameter adjustment. Oxidation distribution uniformity refers to the spatial uniformity of the oxide scale on the strip steel surface. Uneven distribution can lead to subsequent processing defects. Oxidation distribution uniformity is an important supplementary indicator for judging the quality of oxide scale.

[0023] Temperature field data is a set of temperature data related to hot rolling of strip steel, including the surface temperature of the strip steel and the temperatures of each temperature zone in the heating furnace. Temperature field data affects the oxidation reaction rate and is a key parameter for controlling the formation of iron oxide scale. Work roll condition data describes the operating status of the finishing mill work rolls, and may include, for example, work roll surface roughness and work roll temperature. Work roll condition affects the secondary oxidation of the strip steel. The second set of deviation values ​​is a dataset composed of deviation values ​​for oxidation distribution uniformity, strip steel temperature, temperature deviation values ​​of each temperature zone in the heating furnace, work roll roughness, and work roll temperature. This dataset provides detailed data support for subsequent calculations of parameter adjustment priorities and the generation of control commands.

[0024] For example, when producing Q235 strip steel on a hot-rolled strip steel production line, the first deviation value set is calculated. In this embodiment, the oxide scale thickness threshold can be set to 10 μm, and the composition content threshold (FeO percentage) can be set to 80%. In this embodiment, the target strip steel can be detected by laser-induced breakdown spectroscopy, and the oxide scale thickness is found to be 13 μm, from which a thickness deviation value of 3 μm is calculated; the oxide composition FeO percentage is 85%, from which a composition content deviation value of 5% is calculated, thus forming the first deviation value set.

[0025] Furthermore, this embodiment can perform data deviation determination. This embodiment can set a thickness deviation threshold corresponding to a deviation value of 2μm and a component content deviation threshold corresponding to a deviation value of 3%. Because the thickness deviation value of 3μm is greater than the threshold of 2μm, and the component content deviation value of 5% is greater than the threshold of 3%, the data deviation result is determined to be data deviation.

[0026] Furthermore, this embodiment can calculate a second set of deviation values. This embodiment can set the distribution uniformity threshold to 90%, and in this embodiment, the oxidation distribution uniformity of the target strip steel can be detected as 82% using a surface scanning device, calculating a uniformity deviation value of 8%. This embodiment can also set the strip steel surface temperature threshold to 750-850℃, and in this embodiment, the strip steel surface temperature can be detected as 880℃ using an infrared thermometer, calculating a temperature deviation value of 30℃.

[0027] The heating furnace can be divided into a preheating zone (600-800℃), a heat spreader zone (1100-1200℃), and a temperature equalization zone (1200-1250℃). Assuming that the preheating zone temperature is 830℃, the heat spreader temperature is 1230℃, and the temperature equalization zone temperature is 1270℃ in this embodiment, the temperature deviation values ​​for each zone are calculated to be 30℃, 30℃, and 20℃, respectively. In this embodiment, the surface roughness threshold of the working roller can be set to 0.6-0.8μm. Assuming that the roughness is detected to be 0.9μm, the roughness deviation value is calculated to be 0.1μm. In this embodiment, the working roller temperature threshold can be set to the normal operating temperature ±20℃. Assuming that the working roller temperature exceeds the normal range by 25℃, the temperature deviation value is calculated to be 5℃. In this embodiment, the above deviation values ​​can be integrated into a second set of deviation values.

[0028] For example, in the process of producing SPHC low-carbon steel on a 2000mm hot-rolling production line of a steel company, calculating a second set of deviation values ​​after determining data deviation based on a first set of deviation values, and generating control instructions, additional content related to the control of the air-fuel ratio of the heating furnace can be added. Given that the first set of deviation values ​​contains an oxide scale thickness deviation of 2.5μm and an FeO content deviation of 6%; and a heating furnace air-fuel ratio threshold of 1.0-1.05 (1.0 in Example 1, 1.05 in Example 2), and the current heating furnace air-fuel ratio is detected to be 0.95 (below the lower threshold of 1.0), the air-fuel ratio deviation value is calculated to be -0.05.

[0029] First, in the second deviation value set stage, the air-fuel ratio deviation value of the heating furnace is included in the temperature field data correlation deviation value. Together with the temperature deviation values ​​of each temperature zone of the heating furnace (30℃ in the preheating zone, 30℃ in the soaking zone, and 20℃ in the soaking zone), they constitute the complete temperature field related deviation data. It is clear that a low air-fuel ratio leads to an excessively strong reducing atmosphere in the furnace, which, although inhibiting oxidation, easily causes decarburization of the steel billet. Therefore, it is necessary to coordinate the temperature of the temperature zones for regulation.

[0030] Secondly, when calculating the priority sequence of parameter control, the impact of the added air-fuel ratio deviation is calculated in the heating furnace temperature zone control demand value: heating furnace temperature zone control demand value = (sum of absolute values ​​of temperature deviation values ​​of each temperature zone + absolute value of air-fuel ratio deviation value × 100) × weighting coefficient (100 is the conversion coefficient between air-fuel ratio and temperature deviation, since the effect of air-fuel ratio deviation of 0.01 on oxidation is equivalent to temperature deviation of 5℃), that is (30+30+20+0.05×100)×0.4=(80+5)×0.4=34, which more accurately reflects the overall control demand of the heating furnace compared with the original calculated value (80×0.4=32).

[0031] Finally, when generating the target parameter control instructions, for the heating furnace temperature zone parameters, in addition to the instructions to reduce the preheating zone temperature from 830℃ to 800℃, the soaking zone temperature from 1230℃ to 1200℃, and the soaking zone temperature from 1270℃ to 1250℃, a new heating furnace air-fuel ratio adjustment instruction is added: by adjusting the fuel and air flow ratio valve, the air-fuel ratio is increased from 0.95 to 1.02 to ensure the formation of a weak oxidizing atmosphere in the furnace, which suppresses the excessive formation of iron oxide scale, avoids decarburization of the billet, and ensures the mechanical properties of the strip steel.

[0032] S102: Calculate the parameter control priority sequence based on the second set of deviation values ​​and multi-parameter coupling weight coefficients.

[0033] In this embodiment, the multi-parameter coupling weight coefficient is a weight value set for different types of parameters in the second deviation value set, based on the process mechanism of iron oxide scale formation in hot-rolled strip steel. It reflects the degree of influence of each parameter on iron oxide scale formation and is used to quantify the control priority of each parameter. The parameter control priority sequence is calculated using the second deviation value set and the multi-parameter coupling weight coefficient, arranged from high to low importance of parameters in suppressing iron oxide scale formation. This sequence clarifies the order of subsequent parameter control work, ensuring that key parameter issues are addressed first.

[0034] In this embodiment, considering that the formation of iron oxide scale is affected by multiple parameters such as the uniformity of oxidation distribution, temperature field, and working roll condition, and that each parameter has a different weight, relying solely on a single parameter for adjustment can easily lead to imbalance in regulation. This embodiment sets a multi-parameter coupling weight coefficient to quantify the degree of influence of each parameter; based on this, a parameter regulation priority sequence is calculated, which can avoid blind regulation, prioritize the resolution of parameters that have a greater impact on the formation of iron oxide scale, and improve the targeting of regulation.

[0035] Considering the continuous and dynamic nature of hot-rolled strip steel production, with parameters changing in real time, this embodiment uses priority sequence control to quickly respond to abnormalities in key parameters, reduce fluctuations in the control effect of iron oxide scale caused by insufficient parameter coordination, ensure stable production, and lay the foundation for generating precise control instructions in the future, meeting the need for efficient suppression of iron oxide scale formation.

[0036] For example, when producing high-strength steel on a hot-rolled strip steel production line of a steel enterprise, this embodiment can first obtain a set of calculated second deviation values, such as an oxidation distribution uniformity deviation value of 8%, a strip steel surface temperature deviation value of 30°C, a preheating zone temperature deviation value of 30°C, a homogenizing zone temperature deviation value of 30°C, a homogenizing zone temperature deviation value of 20°C, a work roll roughness deviation value of 0.1μm, and a work roll temperature deviation value of 5°C.

[0037] Furthermore, this embodiment can obtain and determine the multi-parameter coupling weight coefficients. In this embodiment, the weight coefficient of the heating furnace temperature zone parameter can be set to 4, the weight coefficient of the rolling line speed related parameter (corresponding to the strip surface temperature deviation) can be set to 2, the weight coefficient of the cooling system parameter (corresponding to the oxidation distribution uniformity deviation) can be set to 3, and the weight coefficient of the work roll state parameter can be set to 1.

[0038] Furthermore, this embodiment can calculate the control requirements for various parameters. The control requirements for the heating furnace temperature zone are obtained by summarizing the influence of temperature deviation values ​​in each zone. Since the temperature deviations in the preheating zone, soaking zone, and uniform temperature zone all exceed the standard and have the highest weight, the calculated requirement value for this type is the highest. The control requirements for the cooling system are calculated based on the oxidation distribution uniformity deviation value and its corresponding weight. The control requirements for the rolling speed-related parameters are obtained by combining the strip surface temperature deviation value and its weight. The control requirements for the work roll state parameters are calculated by comprehensively weighting the roughness deviation value and the temperature deviation value.

[0039] Finally, in this embodiment, the control demand values ​​can be sorted from high to low to obtain the parameter control priority sequence as follows: heating furnace temperature zone parameters > cooling system parameters > rolling line speed related parameters > work roll status parameters, thus clarifying the control order for subsequent generation of target parameter control instructions.

[0040] S103: Generate target parameter control instructions based on parameter control priority sequence, first deviation value set and second deviation value set; target parameter control instructions are used to instruct strip steel production control equipment to perform parameter control.

[0041] In this embodiment, the target parameter control instruction is generated by combining the parameter control priority sequence, the first deviation value set, and the second deviation value set. It is used to specify the exact adjustment direction and value of the strip steel production control equipment, ensuring that the parameter adjustment accurately matches the iron oxide scale suppression requirements. The strip steel production control equipment includes equipment involved in parameter control throughout the entire hot-rolled strip steel production process, such as heating furnaces, finishing mills, laminar flow cooling systems, and coiling machines. It is the main body executing the target parameter control instruction, and its parameter adjustment directly affects the state of iron oxide scale formation.

[0042] In this embodiment, the parameter control priority sequence clearly defines the order of control, avoiding inefficiency caused by disordered adjustments. The first set of deviation values ​​reflects the core indicator problem of iron oxide scale, and the second set of deviation values ​​reflects the process parameter deviations affecting the core indicator. Combining these three sets to generate instructions ensures that the instructions focus on the core problem and accurately locate the control object, solving the problem of insufficient targeting in traditional single-parameter adjustments. Considering the continuous production characteristics of hot-rolled strip steel, the parameters of various equipment are interconnected. Generating instructions based on only a single data source can easily lead to parameter inconsistencies. However, combining the three types of data to generate instructions enables coordinated adjustment of parameters of various equipment, avoiding fluctuations in iron oxide scale control effect due to parameter conflicts. At the same time, it ensures that the instructions can directly guide equipment operation, improving production control efficiency.

[0043] For example, when producing Q355 strip steel on a hot rolling production line, the known parameter control priority sequence is: heating furnace temperature zone parameters > cooling system parameters > rolling line speed related parameters > work roll status parameters; the first set of deviation values ​​includes an oxide scale thickness deviation of 4 μm and an oxide composition FeO content deviation of 9%; the second set of deviation values ​​includes an oxide distribution uniformity deviation of 7%, a strip steel surface temperature deviation of 25℃, a heating furnace preheating zone temperature deviation of 28℃, a soaking zone temperature deviation of 32℃, a soaking zone temperature deviation of 18℃, a work roll roughness deviation of 0.12 μm, and a work roll temperature deviation of 6℃.

[0044] Firstly, this embodiment can generate instructions for the heating furnace temperature zone parameters with the highest priority. Based on the weight of the heating furnace temperature zone parameters and the temperature deviation value, the instructions are to reduce the temperature of the preheating zone from the current 828℃ to 800℃, reduce the temperature of the soaking zone from 1232℃ to 1200℃, and maintain the temperature of the soaking zone at 1268℃ (a deviation of 18℃ is within an acceptable range). The adjustment time is set to 40 seconds to ensure a smooth transition of the furnace temperature and reduce billet oxidation.

[0045] Furthermore, this embodiment can generate instructions for the cooling system parameters, combining the deviation values ​​of oxidation distribution uniformity and FeO content, to instruct the upper nozzle flow rate of the layer cooling system to increase by 18% and the lower nozzle flow rate to decrease by 5%, so that the strip is cooled uniformly in the width direction, while increasing the cooling rate from the current 22℃ / s to 28℃ / s, and suppressing excessive FeO formation.

[0046] Furthermore, this embodiment can generate instructions for the rolling line speed-related parameters. Based on the strip surface temperature deviation value, the rolling speed of the finishing mill is instructed to be increased from 7.5m / s to 8.2m / s, thereby shortening the exposure time of the strip in the high-temperature zone and reducing the formation of iron oxide scale.

[0047] Finally, this embodiment can generate instructions based on the working roll state parameters. According to the working roll roughness and temperature deviation values, the laser texturing equipment is instructed to perform secondary processing on the working roll, adjusting the roughness from 0.92μm to 0.8μm, while increasing the working roll cooling water flow rate by 10% to restore the working roll temperature to the normal range.

[0048] As can be seen from the above, this embodiment first calculates the deviation values ​​of the iron oxide scale thickness and the content of the oxide components to form a first set of deviation values, which can quickly determine whether the core indicators of the iron oxide scale of the strip steel exceed the standard. If they exceed the standard, the deviation values ​​of the oxidation distribution uniformity, temperature field data and work roll state data are further calculated to form a second set of deviation values, so as to achieve comprehensive coverage of the factors affecting the iron oxide scale. This avoids the limitation of traditional technology that only controls a single process, and can locate and solve the problem of iron oxide scale formation from multiple dimensions, reducing defects such as pits and dents on the strip steel surface.

[0049] This embodiment calculates the parameter control priority sequence based on the second set of deviation values ​​and the multi-parameter coupling weight coefficient, and then generates the target parameter control instruction by combining the two sets of deviation values. It can accurately determine the parameters that need to be controlled first according to the actual situation of the strip steel, avoiding blind adjustment. This ensures the stability of the iron oxide scale suppression effect and prevents energy waste caused by excessive suppression, which meets the needs of high-efficiency and energy-saving production. It enables steel companies to better meet the strict requirements of new energy vehicles, high-end home appliances and other fields for the surface quality of strip steel.

[0050] In summary, this embodiment can effectively solve the problems of excessive iron oxide scale formation, isolated control methods, and energy waste in the prior art for hot-rolled strip steel, and provides a practical solution for improving strip steel quality and reducing production losses.

[0051] In one embodiment of this application, deviation values ​​are calculated for the iron oxide scale thickness and oxide content of the target strip steel to obtain a first set of deviation values, including: The iron oxide scale thickness deviation value is calculated based on the thickness threshold and the iron oxide scale thickness of the target strip steel; The deviation value of oxide content is calculated based on the component content threshold and the oxide content of the target strip steel; The deviation values ​​of iron oxide scale thickness and oxide content are used as the first set of deviation values.

[0052] In this embodiment, determining the data deviation judgment result based on the first deviation value set includes: The thickness deviation is determined based on the iron oxide scale thickness deviation value and the allowable thickness deviation range; The degree of deviation of component content is determined based on the deviation value of oxidized component content and the allowable deviation range of component content. The data deviation judgment result is determined based on the thickness deviation and the component content deviation.

[0053] In this embodiment, the data deviation determination result is based on the thickness deviation and the component content deviation, including: If the thickness deviation is less than or equal to the thickness deviation threshold and the component content deviation is less than or equal to the component content deviation threshold, then the data deviation determination result is determined to be no data deviation. If the thickness deviation is greater than the thickness deviation threshold and / or the component content deviation is greater than the component content deviation threshold, then the data deviation judgment result is determined to be data deviation.

[0054] In this embodiment, the thickness threshold is an upper limit value for iron oxide scale thickness set according to the quality standards of hot-rolled strip steel products and the control targets for iron oxide scale. The thickness threshold is the benchmark for judging whether the iron oxide scale thickness exceeds the standard. Different steel grades (such as high-strength steel and low-carbon steel) correspond to different thickness thresholds, which need to be determined in conjunction with the requirements of downstream processes (such as pickling and coating). The composition content threshold is an upper limit value set for the content of key components (such as FeO) in iron oxide scale. The composition content threshold can be determined based on the stability of iron oxide scale and its adaptability to subsequent processing. If this value is exceeded, it is easy to cause oxide layer breakage or increase the difficulty of pickling. The allowable thickness deviation range is the range within which the iron oxide scale thickness deviation is allowed to fluctuate, reflecting the reasonable fluctuation range of thickness control during the production process. It can be set comprehensively in combination with the accuracy of the detection equipment and the stability of the process. The allowable composition content deviation range is the range within which the oxide composition content deviation is allowed to fluctuate, used to ensure that the oxide composition is within a reasonable range and avoid abnormal oxide layer structure caused by composition fluctuation.

[0055] Thickness deviation is calculated by comparing the thickness deviation value of iron oxide scale with the allowable thickness deviation range. Thickness deviation quantifies the degree to which the thickness deviation exceeds the reasonable range and is a key basis for determining whether the thickness indicator needs adjustment. Composition content deviation is calculated by comparing the oxide content deviation value with the allowable composition content deviation range. Composition content deviation quantifies the degree to which the composition deviation exceeds the reasonable range and is used to determine whether the composition indicator needs adjustment. The thickness deviation threshold is the critical value for determining whether the thickness deviation exceeds the standard. If the thickness deviation exceeds this value, it indicates that the iron oxide scale thickness problem has affected product quality, and control measures need to be initiated. The composition content deviation threshold is the critical value for determining whether the composition content deviation exceeds the standard. If the composition content deviation exceeds this value, it indicates abnormal oxide composition, which will cause problems in subsequent processes and requires adjustment.

[0056] In this embodiment, the thickness and composition of the iron oxide scale are core indicators affecting the quality of the strip steel, directly determining its appearance and adaptability to subsequent processing. This embodiment first sets thickness and composition thresholds to clarify the quality qualification standard; then, it divides a reasonable fluctuation range by defining the allowable deviation range, which can take into account both actual production and quality requirements, avoiding excessive adjustment due to minor fluctuations.

[0057] This embodiment introduces thickness deviation and composition content deviation to quantify the severity of deviations, providing greater accuracy than simply comparing deviation values. This embodiment employs a dual-indicator judgment rule, ensuring no deviation is detected when all core indicators are within acceptable limits, thus avoiding mis-control; and enabling timely detection of deviations when either indicator exceeds the limit, preventing the escalation of quality problems. This meets the quality control requirements for precise identification and timely intervention in continuous hot-rolled strip steel production, providing a scientific basis for deciding whether to initiate in-depth control and avoiding resource waste or quality omissions.

[0058] For example, when producing SPHC low-carbon steel strip on a 2000mm hot-rolling production line of a steel company, this embodiment can first determine the relevant judgment benchmark parameters. Specifically, this embodiment can set the thickness threshold to 10μm based on the requirements for iron oxide scale in the subsequent cold rolling process of SPHC steel; this embodiment can set the component content threshold (FeO percentage) to 80% in conjunction with the restriction on FeO content in the pickling process. Considering that the accuracy of the detection equipment (laser-induced breakdown spectrometer) on this production line is ±0.5μm, and the thickness deviation caused by process fluctuations is about ±1μm, this embodiment can set the allowable thickness deviation range to ±2μm; considering that the component detection accuracy is ±2%, and the component deviation caused by process fluctuations is about ±3%, this embodiment can set the allowable component content deviation range to ±5%. At the same time, this embodiment can set the thickness deviation threshold to 1.0 and the component content deviation threshold to 1.0 based on historical production data and quality risk assessment.

[0059] Furthermore, this embodiment can perform a first deviation value set calculation. In this embodiment, the target strip (3.0mm × 1250mm) can be detected online using a laser-induced breakdown spectrometer. The measured thickness of the iron oxide scale is 12.5μm. Based on the calculation method of iron oxide scale thickness deviation value = measured value - thickness threshold, the thickness deviation value is calculated to be 2.5μm. The measured proportion of FeO oxide is 86%. Based on the calculation method of oxide content deviation value = measured value - component content threshold, the component content deviation value is calculated to be 6%. This embodiment can combine these two deviation values ​​into a first deviation value set.

[0060] Furthermore, this embodiment can determine the deviation. When calculating the thickness deviation, this embodiment can use the calculation method of thickness deviation = absolute value of thickness deviation / upper limit of allowable thickness deviation range, that is, thickness deviation = |2.5| / 2 = 1.25; when calculating the component content deviation, this embodiment can use the calculation method of component content deviation = absolute value of component content deviation / upper limit of allowable component content deviation range, that is, component content deviation = |6| / 5 = 1.2.

[0061] Finally, this embodiment can perform data deviation determination. This embodiment can compare the calculated deviation with the corresponding threshold. The thickness deviation of 1.25 is greater than the thickness deviation threshold of 1.0, and the composition content deviation of 1.2 is greater than the composition content deviation threshold of 1.0. According to the determination rules, the data deviation determination result of the target strip steel is determined to be data deviation. Subsequently, a second deviation value set needs to be calculated and parameter adjustment needs to be carried out.

[0062] Assuming that in another batch of SPHC steel production, the measured thickness of the iron oxide scale is 9.2 μm, the calculated thickness deviation is -0.8 μm (absolute value 0.8 μm), and the thickness deviation is 0.8 / 2 = 0.4; the measured FeO percentage is 77%, the composition content deviation is -3% (absolute value 3%), and the composition content deviation is 3 / 5 = 0.6. Since the thickness deviation of 0.4 is less than the thickness deviation threshold of 1.0, and the composition content deviation of 0.6 is less than the composition content deviation threshold of 1.0, the data deviation judgment result is no data deviation, and no further adjustment is required; the current production parameters can be maintained.

[0063] This embodiment can accurately identify abnormalities in the core indicators of iron oxide scale on strip steel, avoiding quality omissions and over-regulation. By clearly defining benchmark parameters and quantifying deviation, this embodiment can scientifically determine the data deviation status, reducing the probability of misjudgment and ensuring the accuracy of quality assessment compared to traditional fuzzy judgment methods. When no deviation is determined, no subsequent regulation needs to be initiated, reducing energy and manpower consumption; when deviation is determined, this embodiment can promptly trigger the regulation process to prevent the iron oxide scale problem from escalating, reduce strip steel surface defects and subsequent process losses, and help enterprises stably produce qualified strip steel to meet the quality requirements of downstream industries.

[0064] In one embodiment of this application, the temperature field data includes the strip surface temperature and the temperatures of multiple temperature zones in the heating furnace; the work roll condition data includes the work roll surface roughness and the work roll temperature; The deviation values ​​of the oxidation distribution uniformity, temperature field data, and work roll condition data of the target strip were calculated to obtain a second set of deviation values, including: The distribution uniformity deviation value is calculated based on the distribution uniformity threshold and the distribution uniformity of the target strip. The strip temperature deviation value is calculated based on the strip temperature threshold and the strip surface temperature of the target strip. For each of the multiple temperature zones in the heating furnace, the zone temperature deviation value is calculated based on the temperature of that zone and the zone temperature threshold of that zone. The roughness deviation value of the working roll is calculated based on the working roll surface roughness threshold and the working roll surface roughness. The working roll temperature deviation value is calculated based on the working roll temperature threshold and the working roll temperature. The distribution uniformity deviation value, strip temperature deviation value, regional temperature deviation value of all temperature zones, work roll roughness deviation value, and work roll temperature deviation value are used as the second set of deviation values.

[0065] In this embodiment, the multi-parameter coupling weighting coefficients include the weighting coefficients corresponding to the heating furnace temperature zone parameters, the rolling mill speed correlation parameters, the cooling system parameters, and the work roll state parameters, respectively. The parameter control priority sequence is calculated based on the second set of deviation values ​​and multi-parameter coupled weighting coefficients, including: The temperature zone control requirements of the heating furnace are calculated based on the regional temperature deviation values ​​of all temperature zones; the absolute values ​​of the regional temperature deviation values ​​of all temperature zones are positively correlated with the temperature zone control requirements of the heating furnace. The required value for adjusting the rolling line speed is calculated based on the strip temperature deviation value; the absolute value of the strip temperature deviation value is positively correlated with the required value for adjusting the rolling line speed. The cooling system regulation demand is calculated based on the distribution uniformity deviation value; the absolute value of the distribution uniformity deviation value is positively correlated with the cooling system regulation demand value. The required adjustment value of the working roll is calculated based on the working roll roughness deviation value and the working roll temperature deviation value; the absolute values ​​of the working roll roughness deviation value and the absolute values ​​of the working roll temperature deviation value are both positively correlated with the required adjustment value of the working roll. The parameter control priority sequence is determined based on the heating furnace temperature zone control demand value, rolling line speed control demand value, cooling system control demand value, work roll control demand value, and multi-parameter coupling weight coefficient. The parameter control priority sequence includes the heating furnace temperature zone parameters, rolling line speed related parameters, cooling system parameters, and work roll status parameters, arranged from high to low priority.

[0066] In this embodiment, the uniformity threshold is a critical value set according to the standard for controlling the uniformity of iron oxide scale on hot-rolled strip steel. This threshold ensures a balanced distribution of the oxide layer on the strip surface, preventing localized excessive thickness or thinness from affecting subsequent pickling and cold rolling processes. It can be determined based on product specifications and processing requirements. The strip temperature threshold refers to the upper or lower limit of the reasonable range for controlling the strip surface temperature. It can be set based on the oxidation reaction rate characteristics to prevent excessively high temperatures from exacerbating oxidation or excessively low temperatures from affecting rolling quality. Different rolling stages (such as the entry and exit of the finishing mill) correspond to different thresholds. The zone temperature threshold is a temperature control critical value set separately for each temperature zone of the heating furnace (such as the preheating zone and the soaking zone). It is used to match the billet heating process requirements, ensuring uniform billet temperature and controllable oxidation levels. The threshold for each temperature zone can be determined based on the steel composition and heating time.

[0067] The work roll surface roughness threshold is a standard value for controlling the coarseness of the micro-texture on the work roll surface. It can be set in conjunction with the hardness and surface precision requirements of the rolled steel grade to ensure the lubrication and oxide layer protection effect at the contact interface between the roll and the strip. The heating furnace temperature zone control requirement value is a quantitative indicator derived from the temperature deviation values ​​of all temperature zones, reflecting the urgency of overall heating furnace temperature control. The larger the absolute value of the deviation, the higher the requirement value, and the more priority it needs to be controlled. The rolling line speed-related parameter is a control parameter related to the strip rolling speed. Its control requirement value is determined by the strip temperature deviation value. By adjusting the speed, the high-temperature exposure time of the strip can be changed, thereby controlling the formation of iron oxide scale. The cooling system control requirement value is a quantitative indicator determined based on the distribution uniformity deviation value, reflecting the degree of adjustment required for the cooling system. The larger the deviation value, the higher the requirement value, and the need to improve oxide layer uniformity by optimizing cooling parameters. The work roll control requirement value is a quantitative indicator derived from the work roll roughness deviation value and temperature deviation value, reflecting the necessity of work roll condition control. The larger the deviation value, the higher the requirement value, and the need for timely adjustment to suppress secondary oxidation.

[0068] In this embodiment, considering that the temperature of the heating furnace zone is the source factor for the formation of iron oxide scale, and that the high-temperature environment directly accelerates the oxidation of the billet, the weight of the heating furnace zone parameter can be set to the highest in this embodiment; considering that the rolling speed indirectly affects oxidation by influencing the high-temperature exposure time of the strip, the weight is second; considering that the cooling system determines the phase transformation and uniformity of the oxide layer, the weight is third; considering that the state of the work rolls mainly affects secondary oxidation and has a relatively small impact on the overall oxidation, the weight is the lowest.

[0069] This embodiment calculates the required values ​​for each parameter adjustment, transforming the deviation values ​​into quantifiable control priorities, thus avoiding disordered control caused by subjective judgment. Simultaneously, this embodiment clarifies the positive correlation between the absolute value of each deviation and the required control value, ensuring that parameters with larger deviations are prioritized for control. This solves the problem of insufficient parameter coordination in traditional single-parameter adjustment, achieving multi-parameter coordinated control, ensuring stable iron oxide scale suppression, and meeting the needs of continuous and high-precision hot-rolled strip steel production.

[0070] For example, when producing Q460 high-strength steel on a 1780mm hot-rolling production line in a steel company, this embodiment first determines the threshold values ​​for each parameter. Specifically, based on the heating process requirements of Q460 steel, this embodiment sets the temperature threshold values ​​for the preheating zone of the heating furnace to 600-800℃, the soaking zone to 1100-1200℃, and the uniform temperature zone to 1200-1250℃; combined with the oxidation control requirements of the finishing rolling stage, this embodiment sets the strip temperature threshold value to 750-850℃; referring to the oxide layer treatment standard before cold rolling of this steel grade, this embodiment sets the distribution uniformity threshold value to 90%; according to the surface protection requirements of the work rolls rolling Q460 steel, this embodiment sets the work roll surface roughness threshold value to 0.6-0.8μm and the work roll temperature threshold value to normal operating temperature ±20℃. Meanwhile, this embodiment can set multi-parameter coupling weight coefficients: heating furnace temperature zone parameter weight 0.4, rolling line speed related parameter weight 0.2, cooling system parameter weight 0.3, and work roll status parameter weight 0.1.

[0071] Furthermore, in this embodiment, the oxidation distribution uniformity of the target strip (12mm × 1500mm) can be detected using a strip surface scanning device. The measured value is 82%, and the deviation value is calculated as -8% based on the calculation method of distribution uniformity deviation value = measured value - distribution uniformity threshold. In this embodiment, the surface temperature of the strip can be detected using an infrared thermometer. The measured value is 880℃, and the deviation value is calculated as 30℃ based on the calculation method of strip temperature deviation value = measured value - upper limit of strip temperature threshold. In this embodiment, the temperature can be detected using thermocouples in each temperature zone of the heating furnace. For example, the measured temperature in the preheating zone is 830℃, and in the soaking zone... The temperature deviation values ​​for the preheating zone (240℃) and the uniform temperature zone (1270℃) are calculated as follows: Preheating zone: 830-800=30℃; Uniform temperature zone: 1240-1200=40℃; Uniform temperature zone: 1270-1250=20℃. In this embodiment, a surface topography scanner can be used to detect the surface roughness of the work roll. The measured value is 0.95μm. Using the calculation method of work roll roughness deviation value = measured value - upper limit of roughness threshold, the deviation value is calculated to be 0.15μm. In this embodiment, the temperature can be detected using an embedded temperature sensor on the work roll. The measured value exceeds the normal range by 28℃, and the calculated work roll temperature deviation value is 28℃. This embodiment can integrate all the above deviation values ​​into a second set of deviation values.

[0072] This embodiment can calculate the required values ​​for adjusting various parameters. Specifically, the required value for adjusting the temperature zone of the heating furnace can be calculated by summing the absolute values ​​of the temperature deviation values ​​of each temperature zone and combining them with weights, i.e., (30+40+20)×0.4=36; the required value for adjusting the parameters related to the rolling speed is the absolute value of the strip temperature deviation value multiplied by the weight, i.e., 30×0.2=6; the required value for adjusting the cooling system is the absolute value of the distribution uniformity deviation value multiplied by the weight, i.e., 8×0.3=2.4; the required value for adjusting the work roll is (absolute value of work roll roughness deviation value + absolute value of work roll temperature deviation value)×weight, i.e., (0.15+28)×0.1≈2.815.

[0073] Finally, this embodiment can determine the parameter control priority sequence. This embodiment can sort the control demand values ​​from high to low: heating furnace temperature zone parameters (36) > work roll status parameters (2.815) > rolling line speed related parameters (6) > cooling system parameters (2.4), and the resulting priority sequence is heating furnace temperature zone parameters > rolling line speed related parameters > work roll status parameters > cooling system parameters, which clarifies the control order for subsequent generation of target parameter control instructions.

[0074] If, in another batch of Q460 steel production, the distribution uniformity deviation is found to be -12%, the strip temperature deviation is 15℃, the total temperature deviation of each temperature zone in the heating furnace is 25℃, the work roll roughness deviation is 0.08μm, and the work roll temperature deviation is 12℃, then the calculated heating furnace temperature zone control requirements are 25×0.4=10, the rolling speed related parameter requirements are 15×0.2=3, the cooling system requirements are 12×0.3=3.6, and the work roll requirements are (0.08+12)×0.1≈1.208. In this case, the priority sequence is: heating furnace temperature zone parameters > cooling system parameters > rolling speed related parameters > work roll status parameters.

[0075] For example, in the process of producing Q460 high-strength steel on a 1780mm hot-rolling production line of a steel company, calculating the second set of deviation values, and generating target parameter control instructions, relevant content on the control of the cooling water quality of the work rolls can be added. The known work roll status parameters include a work roll temperature deviation of 28℃ (normal working temperature 180-200℃, actual measured 228℃), a work roll roughness deviation of 0.15μm, and a work roll cooling water pH control threshold of 8.5-9.0.

[0076] First, in the stage of calculating the second set of deviation values, a new step of cooling water quality detection is added: the pH value of the cooling water in the working roll is detected by a water quality sensor. The measured value is 7.8 (lower than the lower threshold limit of 8.5). The pH value deviation value is calculated as -0.7. The "cooling water pH value deviation value" is included in the second set of deviation values. Together with the working roll roughness deviation value and the working roll temperature deviation value, it constitutes the complete working roll state-related deviation data.

[0077] Secondly, when calculating the required value for parameter control, since a low pH value in the cooling water will accelerate the corrosion of the working roll, indirectly leading to an increase in the working roll temperature and abnormal attenuation of roughness, a pH value deviation influence coefficient is added to the calculation of the working roll control requirement value: Working roll control requirement value = (absolute value of working roll roughness deviation + absolute value of working roll temperature deviation + absolute value of cooling water pH value deviation × 0.5) × weighting coefficient, that is, (0.15 + 28 + 0.7 × 0.5) × 0.1 ≈ 2.85, which more accurately reflects the working roll state control requirement compared to the original calculated value of 2.815.

[0078] Furthermore, when generating the target parameter control instructions, in addition to instructing the laser texturing equipment to process the roughness of the work roll from 0.95μm to 0.78μm and increase the cooling water flow rate by 10%, a new instruction for "cooling water pH adjustment" is added: by adding an alkaline regulator (such as sodium hydroxide solution) to the cooling water circulation system, the pH value of the cooling water is increased from 7.8 to 8.7, ensuring that it is within the threshold range of 8.5-9.0, preventing the work roll from corroding more severely, and ensuring the stability of the work roll temperature and the maintenance of the roughness.

[0079] This embodiment comprehensively covers the key parameters affecting iron oxide scale formation. By accurately calculating the second set of deviation values ​​and the required values ​​for each parameter adjustment, it clarifies the adjustment priorities and avoids the blindness of traditional control methods. Prioritizing the adjustment of the heating furnace temperature zone parameters with the greatest impact can reduce oxidation at its source. This embodiment also adjusts other parameters in an orderly manner according to the required values, which can synergistically optimize the oxidation control effect and solve the problem of insufficient parameter coordination. At the same time, the quantified adjustment requirements and clear priority sequence ensure that the control measures are highly targeted, improving the accuracy of iron oxide scale suppression while avoiding energy waste caused by over-control.

[0080] In one embodiment of this application, a target parameter control instruction is generated based on a parameter control priority sequence, a first set of deviation values, and a second set of deviation values, including: The parameter control strategy is determined based on the first set of deviation values ​​and the second set of deviation values. The target control parameter set is determined based on the parameter control strategy and the absolute value of each deviation value in the second deviation value set. The target control parameter sequence is determined based on the parameter control priority sequence and the target control parameter set; Target parameter control instructions are generated based on the target control parameter sequence.

[0081] In this embodiment, the parameter control strategy combines the first set of deviation values ​​(deviation of core indicators of iron oxide scale) and the second set of deviation values ​​(deviation of process parameters) to formulate the adjustment direction and principles. It clarifies the control measures to be taken for different deviation types, such as adjusting the furnace temperature zone and optimizing cooling intensity, providing guidance for subsequent parameter calculations. The target control parameter set is the specific process parameters to be adjusted and their initial adjustment range determined based on the parameter control strategy and the absolute values ​​of each deviation value in the second set of deviation values. These parameters may include furnace temperature, rolling speed, and cooling rate, reflecting the core content that needs to be adjusted for each parameter. The target control parameter sequence is an ordered list of parameters formed by sorting the target control parameter set according to the parameter control priority sequence. This clarifies the execution order of each control parameter, ensuring that key parameter deviation problems are addressed first.

[0082] In this embodiment, the parameter control strategy is first determined by combining two sets of deviation values. This ensures that the strategy focuses on the core problem of iron oxide scale formation while also taking into account the influence of process parameters, avoiding deviations in the control direction. Then, the target control parameter set is determined based on the absolute value of the deviation, which quantifies the parameter adjustment range and prevents blind control. This embodiment determines the target control parameter sequence according to a priority sequence, prioritizing parameters with the greatest impact on iron oxide scale formation and addressing the problem of insufficient parameter coordination in traditional control methods. Finally, instructions are generated based on the sequence, ensuring that the instructions can directly guide equipment operation and guaranteeing a stable iron oxide scale suppression effect.

[0083] For example, when producing Q355B strip steel on a 2050mm hot rolling production line of a steel company, the known parameter control priority sequence is: heating furnace temperature zone parameters > cooling system parameters > rolling line speed related parameters > work roll status parameters; the first set of deviation values ​​includes an oxide scale thickness deviation of 3μm and an oxide composition FeO content deviation of 7%; the second set of deviation values ​​includes an oxide distribution uniformity deviation of -9%, a strip steel surface temperature deviation of 28℃, a heating furnace preheating zone temperature deviation of 25℃, a soaking zone temperature deviation of 32℃, a soaking zone temperature deviation of 18℃, a work roll roughness deviation of 0.12μm, and a work roll temperature deviation of 6℃.

[0084] The first step in this embodiment is to determine the parameter control strategy. Combining the first set of deviation values ​​(excessive thickness and FeO content) and the second set of deviation values ​​(deviations in heating furnace temperature zone, strip temperature, uniformity, etc.), the parameter control strategy is as follows: firstly, reduce the temperature of the heating furnace temperature zone to reduce the source of oxidation; then, increase the cooling intensity to optimize the uniformity of the oxide layer; subsequently, increase the rolling speed to shorten the high-temperature exposure time; and finally, adjust the state of the work rolls to suppress secondary oxidation.

[0085] The second step in this embodiment is to determine the target set of control parameters. Regarding the furnace temperature parameters, a preheating zone deviation of 25°C needs to be adjusted to within the threshold, a homogenizing zone deviation of 32°C needs to be significantly reduced, and a homogenizing zone deviation of 18°C ​​needs to be finely adjusted. Regarding the cooling system parameters, a uniformity deviation of 9% requires an increase in the cooling rate by 15%-20%. Regarding the rolling mill speed-related parameters, a strip temperature deviation of 28°C requires an increase in speed by 0.6-0.8 m / s. Regarding the work roll condition parameters, a roughness deviation of 0.12 μm needs to be reduced to below 0.8 μm, and a temperature deviation of 6°C requires an increase in cooling water flow rate by 5%-8%. These parameters and ranges that need adjustment are integrated into the target set of control parameters.

[0086] Third, in this embodiment, the target control parameter sequence can be determined. The target control parameter set is sorted according to priority sequence: the first priority is the adjustment of the preheating zone temperature, the soaking zone temperature, and the uniform temperature zone temperature of the heating furnace; the second priority is the adjustment of the cooling rate of the cooling system; the third priority is the adjustment of the rolling line speed; and the last priority is the adjustment of the work roll roughness processing parameters and the cooling water flow rate, thus forming the target control parameter sequence.

[0087] Fourth, this embodiment can generate target parameter control commands. For the temperature zone parameters of the first heating furnace in the sequence, the command is to reduce the preheating zone temperature from 825℃ to 800℃, the soaking zone temperature from 1232℃ to 1200℃, and the soaking zone temperature from 1268℃ to 1255℃, with an adjustment time of 40 seconds. For the cooling system parameters, the command is to increase the cooling rate of the laminar flow system from 22℃ / s to 26℃ / s, and increase the flow rate of the upper nozzle by 18%. For the rolling mill speed parameters, the command is to increase the finishing mill speed from 7.4m / s to 8.1m / s. Based on the working roll's condition parameters, the laser texturing equipment is instructed to process the working roll's roughness from 0.92μm to 0.78μm and increase the working roll's cooling water flow rate by 6%, ultimately forming a complete target parameter adjustment instruction and sending it to each production control device.

[0088] For example, when producing Q355B strip steel on a 2050mm hot-rolling production line in a steel company, during the process of generating target parameter control instructions based on the parameter control priority sequence, the first set of deviation values, and the second set of deviation values, a related control step for adaptive adjustment of coiling temperature can be added. It is known that the first set of deviation values ​​contains an oxide scale thickness deviation of 3μm and an FeO content deviation of 7%; the second set of deviation values ​​contains a strip final rolling temperature deviation of 20℃ (final rolling temperature threshold 820-850℃, actual measured 870℃) and a strip thickness of 6mm; the weight of the coiling temperature-related parameter in the multi-parameter coupling weighting coefficient is 0.15.

[0089] First, in the stage of determining the parameter control strategy, considering the excessive FeO content and the high final rolling temperature, adaptive adjustment of the coiling temperature was incorporated into the control strategy. This clearly demonstrates how adjusting the coiling temperature can promote a more stable FeO content. Transformation helps inhibit the abnormal formation of iron oxide scale.

[0090] Secondly, when determining the target control parameter set, based on the strip thickness of 6mm, the final rolling temperature of 870℃ and the FeO content deviation of 7%, the optimal coiling temperature window was calculated to be 580-610℃ (the conventional Q355B steel coiling temperature threshold is 600-630℃, which needs to be lowered by 20℃ due to excessive FeO). The coiling temperature control range was set to 585-595℃, and the initial value of the coiling tension was set to 15KN (gradually reduced to 8KN as the coil diameter increases), which was included in the target control parameter set.

[0091] Furthermore, when determining the target control parameter sequence, since the weight of the coiling temperature related parameter is 0.15, which is lower than that of the heating furnace temperature zone parameter (0.4), cooling system parameter (0.3), and rolling speed related parameter (0.2), but higher than that of the work roll state parameter (0.1), the coiling temperature adjustment + coiling tension gradient control is inserted between the rolling speed related parameter and the work roll state parameter to form a new target control parameter sequence: heating furnace temperature zone parameter > cooling system parameter > rolling speed related parameter > coiling temperature related parameter > work roll state parameter.

[0092] Finally, when generating the target parameter control command, for the winding temperature-related parameters, the winding machine is instructed to reduce the initial winding temperature from 620℃ to 590℃ and activate the tension gradient release model: the initial winding tension is set at 15KN, and the tension is reduced by 1KN for every 100mm increase in the winding diameter; at the same time, a laser-induced breakdown spectroscopy detection unit is deployed to monitor the FeO content on the strip surface in real time. If the FeO content is detected to drop below 75%, the winding temperature is instructed to be adjusted back by 5℃ to ensure the stability of the oxide layer structure.

[0093] This embodiment can generate target parameter control instructions in an orderly manner through multiple steps, ensuring that the instructions not only address the core issue of iron oxide scale but also take into account the synergistic optimization of process parameters, avoiding the blindness and disorder of traditional control methods. Prioritizing the control of key parameters can suppress iron oxide scale formation at its source; the orderly parameter adjustment sequence can ensure stable production, reduce quality fluctuations caused by parameter conflicts, effectively improve the accuracy of iron oxide scale suppression, and reduce energy consumption from excessive control, thereby producing high-quality strip steel.

[0094] Corresponding to the control method for suppressing the formation of iron oxide scale in hot-rolled strip steel in the above embodiments, Figure 2 This is a structural block diagram of a control device for suppressing the formation of iron oxide scale in hot-rolled strip steel, provided in one embodiment of this application. For ease of explanation, only the parts relevant to the embodiment of this application are shown. References Figure 2 The control device 20 for suppressing the formation of iron oxide scale in hot-rolled strip steel includes: an oxidation deviation analysis module 21, a parameter control priority module 22, and a parameter control module 23.

[0095] Among them, the oxidation deviation analysis module 21 is used to calculate the deviation value of the iron oxide scale thickness and the oxide content of the target strip steel respectively to obtain a first deviation value set; the data deviation judgment result is determined based on the first deviation value set; if the data deviation judgment result is data deviation, the deviation value is calculated for the oxidation distribution uniformity, temperature field data and work roll state data of the target strip steel respectively to obtain a second deviation value set. Parameter control priority module 22 is used to calculate the parameter control priority sequence based on the second deviation value set and the multi-parameter coupling weight coefficient; The parameter control module 23 is used to generate a target parameter control instruction based on the parameter control priority sequence, the first deviation value set, and the second deviation value set; the target parameter control instruction is used to instruct the strip steel production control equipment to perform parameter control.

[0096] In one embodiment of this application, when the oxidation deviation analysis module 21 calculates the deviation values ​​for the iron oxide scale thickness and oxide content of the target strip steel to obtain a first set of deviation values, it is specifically used for: The iron oxide scale thickness deviation value is calculated based on the thickness threshold and the iron oxide scale thickness of the target strip steel; The deviation value of oxide content is calculated based on the component content threshold and the oxide content of the target strip steel; The deviation values ​​of iron oxide scale thickness and oxide content are used as the first set of deviation values.

[0097] In one embodiment of this application, when determining the data deviation judgment result based on the first set of deviation values, the oxidation deviation analysis module 21 is specifically used for: The thickness deviation is determined based on the iron oxide scale thickness deviation value and the allowable thickness deviation range; The degree of deviation of component content is determined based on the deviation value of oxidized component content and the allowable deviation range of component content. The data deviation judgment result is determined based on the thickness deviation and the component content deviation.

[0098] In one embodiment of this application, the oxidation deviation analysis module 21, when determining the data deviation judgment result based on thickness deviation and component content deviation, is specifically used for: If the thickness deviation is less than or equal to the thickness deviation threshold and the component content deviation is less than or equal to the component content deviation threshold, then the data deviation determination result is determined to be no data deviation. If the thickness deviation is greater than the thickness deviation threshold and / or the component content deviation is greater than the component content deviation threshold, then the data deviation judgment result is determined to be data deviation.

[0099] In one embodiment of this application, the temperature field data includes the surface temperature of the strip steel and the temperatures of multiple temperature zones in the heating furnace; the work roll state data includes the surface roughness of the work roll and the work roll temperature; the oxidation deviation analysis module 21, when calculating the deviation values ​​of the oxidation distribution uniformity of the target strip steel, the temperature field data, and the work roll state data to obtain a second set of deviation values, is specifically used for: The distribution uniformity deviation value is calculated based on the distribution uniformity threshold and the distribution uniformity of the target strip. The strip temperature deviation value is calculated based on the strip temperature threshold and the strip surface temperature of the target strip. For each of the multiple temperature zones in the heating furnace, the zone temperature deviation value is calculated based on the temperature of that zone and the zone temperature threshold of that zone. The roughness deviation value of the working roll is calculated based on the working roll surface roughness threshold and the working roll surface roughness. The working roll temperature deviation value is calculated based on the working roll temperature threshold and the working roll temperature. The distribution uniformity deviation value, strip temperature deviation value, regional temperature deviation value of all temperature zones, work roll roughness deviation value, and work roll temperature deviation value are used as the second set of deviation values.

[0100] In one embodiment of this application, the multi-parameter coupling weighting coefficients include weighting coefficients corresponding to the heating furnace temperature zone parameters, rolling mill speed-related parameters, cooling system parameters, and work roll state parameters, respectively; the parameter control priority module 22, when calculating the parameter control priority sequence based on the second deviation value set and the multi-parameter coupling weighting coefficients, is specifically used for: The temperature zone control requirements of the heating furnace are calculated based on the regional temperature deviation values ​​of all temperature zones; the absolute values ​​of the regional temperature deviation values ​​of all temperature zones are positively correlated with the temperature zone control requirements of the heating furnace. The required value for adjusting the rolling line speed is calculated based on the strip temperature deviation value; the absolute value of the strip temperature deviation value is positively correlated with the required value for adjusting the rolling line speed. The cooling system regulation demand is calculated based on the distribution uniformity deviation value; the absolute value of the distribution uniformity deviation value is positively correlated with the cooling system regulation demand value. The required adjustment value of the working roll is calculated based on the working roll roughness deviation value and the working roll temperature deviation value; the absolute values ​​of the working roll roughness deviation value and the absolute values ​​of the working roll temperature deviation value are both positively correlated with the required adjustment value of the working roll. The parameter control priority sequence is determined based on the heating furnace temperature zone control demand value, rolling line speed control demand value, cooling system control demand value, work roll control demand value, and multi-parameter coupling weight coefficient. The parameter control priority sequence includes the heating furnace temperature zone parameters, rolling line speed related parameters, cooling system parameters, and work roll status parameters, arranged from high to low priority.

[0101] In one embodiment of this application, when the parameter control module 23 generates a target parameter control instruction based on the parameter control priority sequence, the first deviation value set, and the second deviation value set, it is specifically used for: The parameter control strategy is determined based on the first set of deviation values ​​and the second set of deviation values. The target control parameter set is determined based on the parameter control strategy and the absolute value of each deviation value in the second deviation value set. The target control parameter sequence is determined based on the parameter control priority sequence and the target control parameter set; Target parameter control instructions are generated based on the target control parameter sequence.

[0102] See Figure 3 , Figure 3 This is a schematic block diagram of an electronic device provided according to an embodiment of this application. Figure 3 The electronic device 300 in this embodiment 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 memories 304 store computer programs, including program instructions. The processors 301 execute the program instructions stored in the memories 304. Specifically, the processors 301 are configured to invoke the program instructions to perform the functions of the modules in the aforementioned device embodiments, for example... Figure 2 The functions of the oxidation deviation analysis module 21, parameter control priority module 22, and parameter control module 23 are shown.

[0103] It should be understood that, in the embodiments of this application, the processor 301 may be a central processing unit (CPU), but it may also be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or any conventional processor.

[0104] Input device 302 may include a touchpad, a fingerprint sensor (for collecting the user's fingerprint information and fingerprint orientation information), a microphone, etc., and output device 303 may include a display (LCD, etc.), a speaker, etc.

[0105] The memory 304 may include read-only memory and random access memory, and provides instructions and data to the processor 301. A portion of the memory 304 may also include non-volatile random access memory. For example, the memory 304 may also store information about the type of strip steel.

[0106] In specific implementations, the processor 301, input device 302, and output device 303 described in the embodiments of this application can execute the implementation methods described in the embodiments of the control method for suppressing the generation of iron oxide scale in hot-rolled strip steel provided in the embodiments of this application, or they can execute the implementation methods of the electronic device 300 described in the embodiments of this application, which will not be repeated here.

[0107] In another embodiment of this application, a computer-readable storage medium is provided. This computer-readable storage medium stores a computer program, which includes program instructions. When executed by a processor, the program instructions implement all or part of the processes in the methods described above. Alternatively, the computer program can instruct related hardware to complete the process. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. The computer-readable medium can include any entity or device capable of carrying computer program code, a recording medium, a USB flash drive, a portable hard drive, a magnetic disk, an optical disk, a computer memory, a read-only memory (ROM), a random access memory (RAM), an electrical carrier signal, a telecommunication signal, and a software distribution medium, etc.

[0108] The computer-readable storage medium can be an internal storage unit of the electronic device in any of the foregoing embodiments, such as a hard disk or memory of the electronic device. The computer-readable storage medium can also be an external storage device of the electronic device, such as a plug-in hard disk, smart media card (SMC), secure digital card (SD) card, flash card, etc., equipped on the electronic device. Furthermore, the computer-readable storage medium can include both internal and external storage units of the electronic 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 can also be used to temporarily store data that has been output or will be output.

[0109] Those skilled in the art will recognize that the modules / units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of both. To clearly illustrate the interchangeability of hardware and software, the components and steps of the various examples have been generally described in terms of functionality in the foregoing description. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementations should not be considered beyond the scope of this application.

[0110] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working process of the electronic devices and units described above can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0111] In the several embodiments provided in this 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 merely illustrative. For instance, the division of modules / units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple modules, units, or components may be combined or integrated into another system, or some features may be ignored or not executed. In addition, the mutual coupling or direct coupling or communication connection shown or discussed may be indirect coupling or communication connection through some interfaces or modules / units, or it may be an electrical, mechanical, or other form of connection.

[0112] The modules / units described as separate components may or may not be physically separate. Similarly, the components shown as modules / units may or may not be physical modules / units; they may be located in one place or distributed across multiple network modules / units. Some or all of the modules / units can be selected to achieve the purpose of the embodiments of this application, depending on actual needs.

[0113] Furthermore, the functional modules / units in the various embodiments of this application can be integrated into one processing module / unit, or each module / unit can exist physically separately, or two or more modules / units can be integrated into one module / unit. The integrated modules / units described above can be implemented in hardware or in the form of software functional modules / units.

[0114] The above are merely specific embodiments of this application, but the scope of protection of this application is not limited thereto. Any person skilled in the art can easily conceive of various equivalent modifications or substitutions within the technical scope disclosed in this application, and these modifications or substitutions should all be covered within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A method for controlling the formation of iron oxide scale in hot-rolled strip steel, characterized in that, include: The deviation values ​​of the iron oxide scale thickness and oxide content of the target strip steel are calculated to obtain the first set of deviation values; The data deviation determination result is determined based on the first set of deviation values; If the data deviation determination result is data deviation, then the deviation values ​​are calculated for the oxidation distribution uniformity, temperature field data and work roll state data of the target strip steel respectively, to obtain the second set of deviation values; Calculate the parameter control priority sequence based on the second set of deviation values ​​and the multi-parameter coupled weighting coefficients; A target parameter control instruction is generated based on the parameter control priority sequence, the first set of deviation values, and the second set of deviation values. The target parameter control command is used to instruct the strip steel production control equipment to adjust the parameters.

2. The control method for suppressing the formation of iron oxide scale in hot-rolled strip steel as described in claim 1, characterized in that, The deviation values ​​for the iron oxide scale thickness and oxide content of the target strip steel are calculated respectively to obtain a first set of deviation values, including: The iron oxide scale thickness deviation value is calculated based on the thickness threshold and the iron oxide scale thickness of the target strip steel; The deviation value of oxide content is calculated based on the component content threshold and the oxide content of the target strip steel; The deviation values ​​of the iron oxide scale thickness and the deviation values ​​of the oxide content are used as the first set of deviation values.

3. The control method for suppressing the formation of iron oxide scale in hot-rolled strip steel as described in claim 2, characterized in that, The step of determining the data deviation judgment result based on the first set of deviation values ​​includes: The thickness deviation is determined based on the iron oxide scale thickness deviation value and the allowable thickness deviation range; The degree of deviation of component content is determined based on the deviation value of oxidized component content and the allowable deviation range of component content. The data deviation determination result is determined based on the thickness deviation and the component content deviation.

4. The control method for suppressing the formation of iron oxide scale in hot-rolled strip steel as described in claim 3, characterized in that, The determination of data deviation based on the thickness deviation and the component content deviation includes: If the thickness deviation is less than or equal to the thickness deviation threshold and the component content deviation is less than or equal to the component content deviation threshold, then the data deviation determination result is determined to be no data deviation. If the thickness deviation is greater than the thickness deviation threshold and / or the component content deviation is greater than the component content deviation threshold, then the data deviation determination result is determined to be data deviation.

5. The control method for suppressing the formation of iron oxide scale in hot-rolled strip steel as described in claim 2, characterized in that, The temperature field data includes the surface temperature of the strip steel and the temperatures of multiple temperature zones in the heating furnace; the work roll status data includes the surface roughness of the work roll and the temperature of the work roll. The deviation values ​​are calculated for the oxidation distribution uniformity, temperature field data, and work roll condition data of the target strip, respectively, to obtain a second set of deviation values, including: The distribution uniformity deviation value is calculated based on the distribution uniformity threshold and the distribution uniformity of the target strip. The strip temperature deviation value is calculated based on the strip temperature threshold and the strip surface temperature of the target strip. For each of the multiple temperature zones in the heating furnace, the zone temperature deviation value is calculated based on the temperature of that zone and the zone temperature threshold of that zone. The roughness deviation value of the working roll is calculated based on the working roll surface roughness threshold and the working roll surface roughness. The working roll temperature deviation value is calculated based on the working roll temperature threshold and the working roll temperature. The distribution uniformity deviation value, the strip temperature deviation value, the regional temperature deviation value of all temperature zones, the work roll roughness deviation value, and the work roll temperature deviation value are used as the second set of deviation values.

6. The control method for suppressing the formation of iron oxide scale in hot-rolled strip steel as described in claim 5, characterized in that, The multi-parameter coupling weighting coefficients include the weighting coefficients corresponding to the heating furnace temperature zone parameters, rolling line speed correlation parameters, cooling system parameters, and work roll state parameters, respectively. The calculation of the parameter control priority sequence based on the second set of deviation values ​​and multi-parameter coupled weighting coefficients includes: The heating furnace temperature zone control requirement value is calculated based on the regional temperature deviation values ​​of all temperature zones; the absolute value of the regional temperature deviation value of all temperature zones is positively correlated with the heating furnace temperature zone control requirement value. The required value for adjusting the rolling line speed is calculated based on the strip temperature deviation value; the absolute value of the strip temperature deviation value is positively correlated with the required value for adjusting the rolling line speed. The cooling system regulation requirement is calculated based on the distribution uniformity deviation value; the absolute value of the distribution uniformity deviation value is positively correlated with the cooling system regulation requirement value. The required adjustment value of the working roll is calculated based on the roughness deviation value and the temperature deviation value of the working roll; the absolute values ​​of the roughness deviation value and the temperature deviation value of the working roll are both positively correlated with the required adjustment value of the working roll. The parameter control priority sequence is determined based on the heating furnace temperature zone control requirements, the rolling line speed control requirements, the cooling system control requirements, the work roll control requirements, and the multi-parameter coupling weight coefficient. The parameter control priority sequence includes heating furnace temperature zone parameters, rolling line speed related parameters, cooling system parameters, and work roll status parameters, arranged from high to low priority.

7. The control method for suppressing the formation of iron oxide scale in hot-rolled strip steel as described in claim 1, characterized in that, The step of generating a target parameter control instruction based on the parameter control priority sequence, the first set of deviation values, and the second set of deviation values ​​includes: The parameter control strategy is determined based on the first set of deviation values ​​and the second set of deviation values; The target control parameter set is determined based on the parameter control strategy and the absolute value of each deviation value in the second deviation value set. The target control parameter sequence is determined based on the parameter control priority sequence and the target control parameter set; The target parameter control command is generated based on the target control parameter sequence.

8. A control device for suppressing the formation of iron oxide scale in hot-rolled strip steel, characterized in that, include: The oxidation deviation analysis module is used to calculate the deviation values ​​of the iron oxide scale thickness and oxide content of the target strip steel, respectively, and obtain the first set of deviation values; The data deviation determination result is determined based on the first set of deviation values; If the data deviation determination result is data deviation, then the deviation values ​​are calculated for the oxidation distribution uniformity, temperature field data and work roll state data of the target strip steel respectively, to obtain the second set of deviation values; The parameter control priority module is used to calculate the parameter control priority sequence based on the second set of deviation values ​​and the multi-parameter coupling weight coefficients. The parameter control module is used to generate target parameter control instructions based on the parameter control priority sequence, the first set of deviation values, and the second set of deviation values; The target parameter control command is used to instruct the strip steel production control equipment to adjust the parameters.

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, it implements the steps of the method as described in any one of claims 1 to 7.

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

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