High-speed and high-stability rolling process for aluminum foil

Abstract

The invention relates to the technical field of aluminum foil rolling, and particularly discloses an aluminum foil high-speed and high-stability rolling technology which comprises the steps that in the heating process after aluminum foil rolling, electromagnetic heating control monitoring is conducted on the heating process, and abnormal data in a monitoring period are obtained; calculating an abnormal coefficient of the heating process based on the monitoring data; the heating process is analyzed based on the abnormal coefficient, whether the heating process is in an abnormal state or not in the monitoring period is judged, and a state evaluation signal is generated; the temperature in the integrated electromagnetic heating device is regulated and controlled by controlling electromagnetic heating on the basis of the state abnormal signal, and the regulation and control precision in the face of temperature abnormity during electromagnetic heating in the aluminum foil rolling process is effectively improved through real-time monitoring, multi-dimensional analysis calculation and intelligent regulation and control; and the stability and consistency of the heating process can be ensured, and the quality of a final product can be remarkably improved.

Description

Technical Field

[0001] The present invention relates to the technical field of aluminum foil rolling, and particularly relates to a high-speed and highly stable aluminum foil rolling process. Background Art

[0002] Most traditional aluminum foil rolling heating methods adopt the way of manually setting the heating power or monitoring the temperature through a small number of measuring points, lacking the perception and analysis of the overall temperature field distribution, resulting in control lag and untimely response, and unable to meet the requirements of high-precision rolling for temperature stability. In addition, during the actual production process, due to the change of strip speed, the difference in heat capacity between the edge and the middle, and the interference of environmental factors, local temperature anomalies often occur. If the electromagnetic heating power fails to be adjusted in time, it will have an adverse impact on the shape control, rolling force fluctuation, and product consistency.

[0003] At present, although some systems have introduced temperature feedback control technology, there are still problems such as single monitoring dimension, insufficient analysis granularity, and rough regulation response. Especially when facing sub-regions with large local temperature deviations, the system cannot accurately judge the heat conduction influence relationship between it and adjacent regions, resulting in a lack of pertinence and systematicness in the regulation strategy. Therefore, there is an urgent need for an electromagnetic heating control technology with real-time monitoring capabilities, a multi-dimensional analysis and calculation mechanism, and an intelligent regulation logic, which can achieve accurate judgment and dynamic optimization adjustment of the heating process, so as to comprehensively improve the automation and intelligence level of the aluminum foil rolling process and ensure the stable and reliable quality of the final product. Summary of the Invention

[0004] The purpose of the present invention is to provide a high-speed and highly stable aluminum foil rolling process to solve the above technical problems in the background.

[0005] The purpose of the present invention can be achieved through the following technical solutions: In the first aspect, the present invention provides a high-speed and highly stable aluminum foil rolling process, which is characterized in that a high-speed rolling mill rolls an aluminum strip to a target thickness, and heats the strip or the roll through an integrated electromagnetic heating control system to improve stability and shape accuracy; it includes the following steps: S1: During the heating process after aluminum foil rolling, conduct electromagnetic heating control monitoring on the heating process to obtain abnormal data within the monitoring period; Among them, the abnormal data includes: an abnormal degree characterization value and an abnormal uniformity characterization value; S2: Calculate the abnormal coefficient of the heating process based on the monitoring data; S3: Analyze the heating process based on the abnormal coefficient, determine whether the heating process is in an abnormal state within the monitoring period, and generate a state evaluation signal; Among them, the state evaluation signal includes: a state abnormal signal and a state normal signal; S4: Based on the status exception signal, control the electromagnetic heating to regulate the temperature inside the integrated electromagnetic heating device.

[0006] As a further solution of the present invention: The process of obtaining abnormal data is as follows: During the electromagnetic heating process, evenly divide the total heating area in space to obtain several heating sub-areas; During the monitoring period, monitor the temperature of each heating sub-area respectively to obtain the temperature anomaly characterization value of each heating sub-area; Based on the temperature anomaly characterization values of each heating sub-area, calculate the anomaly degree characterization value and the anomaly uniformity characterization value respectively.

[0007] As a further solution of the present invention: The process of obtaining the temperature anomaly characterization value is as follows: Based on a single heating sub-area, obtain the average temperature of this heating sub-area during the monitoring period, calculate the difference between the average temperature and the preset temperature to obtain the temperature deviation value; Calculate the ratio of the temperature deviation value to the preset temperature to obtain the temperature anomaly characterization value.

[0008] As a further solution of the present invention: The process of obtaining the anomaly degree characterization value is as follows: Obtain the temperature anomaly characterization values of each heating sub-area, and respectively perform absolute value processing on the temperature anomaly characterization values to obtain the absolute anomaly characterization values of each heating sub-area; Sum up all the absolute anomaly characterization values to obtain the total anomaly degree value; At the same time, respectively compare and analyze the absolute anomaly characterization values of all heating sub-areas with the absolute anomaly characterization threshold; If the absolute anomaly characterization value is less than or equal to the absolute anomaly characterization threshold, generate a small deviation signal; If the absolute anomaly characterization value is greater than the absolute anomaly characterization threshold, generate a large deviation signal and mark this heating sub-area as a large deviation sub-area; Extract the total number of all large deviation sub-areas to obtain the number of large deviation sub-areas, calculate the ratio of the number of large deviation sub-areas to the total number of sub-areas to obtain the ratio of the number of large deviation sub-areas; At the same time, sum up the temperature anomaly characterization values of all heating sub-areas to obtain the abnormal deviation degree value; Calculate the product of the abnormal deviation degree value and the ratio of the number of large deviation sub-areas to obtain the anomaly degree adjustment value; Sum up the anomaly degree adjustment value and the total anomaly degree value to obtain the anomaly degree characterization value.

[0009] As a further solution of the present invention: The process of obtaining the anomaly uniformity characterization value is as follows: Obtain the absolute abnormal characterization values of each heating sub-region, calculate the variance values of the absolute abnormal characterization values of all heating sub-regions, and obtain the abnormal uniformity characterization value.

[0010] As a further solution of the present invention: The process of generating the status evaluation signal is as follows: Preset the abnormal coefficient threshold, and conduct a comparative analysis of the abnormal coefficient and the abnormal coefficient threshold; If the abnormal coefficient is less than or equal to the abnormal coefficient threshold, generate a normal status signal; If the abnormal coefficient is greater than the abnormal coefficient threshold, generate an abnormal status signal.

[0011] As a further solution of the present invention: The process of regulating the temperature inside the electromagnetic heating device is as follows: When receiving the abnormal status signal, based on a single large-deviation sub-region, calculate the regulation power pre-value and the influence coefficient respectively; Multiply the regulation power pre-value by the influence coefficient to obtain the regulation power; Based on the regulation power, adjust the electromagnetic heating power of the large-deviation sub-region, so as to regulate the temperature of the large-deviation sub-region.

[0012] As a further solution of the present invention: The process of obtaining the regulation power pre-value is as follows: Based on the large-deviation sub-region, obtain the average temperature and average power within the monitoring period; Through the formula: , calculate the regulation power pre-value TKY, where WD is the average temperature, YWD is the preset temperature, and GL is the average power.

[0013] As a further solution of the present invention: The process of obtaining the influence coefficient is as follows: Extract the large-deviation sub-regions among all adjacent heating sub-regions of the large-deviation sub-region, and mark them as adjacent large-deviation sub-regions; Sum up the temperature abnormal characterization values of all adjacent large-deviation sub-regions to obtain the total adjacent large-deviation abnormality value.

[0014] As a further solution of the present invention: Calculate the ratio of the total adjacent large-deviation abnormality value to the total adjacent abnormality value to obtain the influence coefficient.

[0015] Advantages of the present invention: (1) In the present invention, by monitoring the heating process in real time, and evaluating the heating process from the overall abnormal degree of the temperature and the uniformity of the temperature distribution, real-time monitoring, multi-dimensional analysis and automatic determination are achieved, effectively improving the intelligent level of aluminum foil heating rolling and ensuring the quality of aluminum foil; at the same time, manual intervention is reduced and work efficiency is improved.

[0016] (2) In the present invention, by comparing the temperature anomaly degrees of the sub-regions with large deviations and their adjacent sub-regions, the potential influence of the adjacent regions on the current regulation is evaluated; finally, the preset regulation power value is multiplied by the influence coefficient to obtain an accurate regulation power value; thereby, the electromagnetic heating power of the sub-regions with large deviations is adjusted accordingly to achieve instant and accurate temperature control; the technical solution of the embodiments of the present invention effectively improves the regulation accuracy in the electromagnetic heating during the aluminum foil rolling process in the face of temperature anomalies through real-time monitoring, multi-dimensional analysis and calculation, and intelligent regulation, which not only helps to ensure the stability and consistency of the heating process, but also can significantly improve the quality and quality of the final product. Description of the Drawings

[0017] The present invention will be further described below with reference to the drawings.

[0018] Figure 1 is the working flowchart of the electromagnetic heating control system of the present invention; Figure 2 is the process flowchart of the present invention. Detailed Embodiments

[0019] The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention. Embodiment 1

[0020] Please refer to Figure 2 As shown, a high-speed and high-stability rolling process for aluminum foil described in the embodiments of the present invention includes: Step 1: Pretreatment: Clean the oil and impurity on the surface of the aluminum coil, and perform annealing treatment to improve the metal plasticity and cleanliness, laying a good foundation for the subsequent rolling; Step 2: Intermediate rolling: Roll the initially rolled aluminum strip to a medium thickness through multiple passes to ensure thickness uniformity and provide suitable raw materials for the finish rolling stage; Step 3: Precision rolling: The high-speed rolling mill rolls the aluminum strip to the target thinness, and heats the strip or the roll through an integrated electromagnetic heating control system to improve stability and flatness accuracy; Step 4: Detection and coiling: Detect the rolled aluminum foil, remove the defective products, and perform post-treatment such as slitting and rewinding according to requirements; Step 5: Annealing treatment: Eliminate internal stress through heat treatment, improve the tissue performance, and improve the ductility and softness of the aluminum foil to meet the use performance requirements of users. Embodiment 2

[0021] Refer toFigure 1 As shown in the above embodiments, this embodiment provides an integrated electromagnetic heating control system, including: S1: During the heating process after aluminum foil rolling, monitor the electromagnetic heating process to obtain abnormal data within the monitoring period; Among them, the abnormal data includes: an abnormal degree characterization value and an abnormal uniformity characterization value; It should be noted that: the monitoring period can be 10 seconds, 30 seconds, or 1 minute; In some embodiments, during the electromagnetic heating process, the total area of the aluminum foil is evenly divided on a plane to obtain several heating sub-regions; Within the monitoring period, monitor the temperature of each heating sub-region respectively to obtain the temperature abnormal characterization value of each heating sub-region; Based on the temperature abnormal characterization values of each heating sub-region, calculate the abnormal degree characterization value and the abnormal uniformity characterization value respectively; First specifically, the process of obtaining the temperature abnormal characterization value is as follows: Based on a single heating sub-region, obtain the average temperature of this heating sub-region within the monitoring period (the average temperature is the average value of the temperature of this heating sub-region within this monitoring period), calculate the difference between the average temperature and the preset temperature to obtain the temperature deviation value; Calculate the ratio of the temperature deviation value to the preset temperature to obtain the temperature abnormal characterization value; It should be noted that the preset temperature is the heating temperature preset by those skilled in the art according to the current heating state, that is, the current monitoring period, during the heating process, and this value is an empirical value; Second specifically, the process of obtaining the abnormal degree characterization value is as follows: Obtain the temperature abnormal characterization values of each heating sub-region, and respectively perform absolute value processing on the temperature abnormal characterization values to obtain the absolute abnormal characterization values of each heating sub-region; Sum up all the absolute abnormal characterization values to obtain the total abnormal degree value; At the same time, compare and analyze the absolute abnormal characterization values of all heating sub-regions with the absolute abnormal characterization threshold respectively; It should be noted that the absolute abnormal characterization threshold is obtained by those skilled in the art considering the deviation between the average temperature of the current monitoring period and the preset temperature. The absolute abnormal characterization threshold is a division of the absolute abnormal characterization value and is an empirical value; If the absolute abnormal characterization value is less than or equal to the absolute abnormal characterization threshold, it indicates that the deviation between the average temperature of this heating sub-region and the preset temperature is not large, and a small deviation signal is generated; If the absolute abnormal characterization value is greater than the absolute abnormal characterization threshold, it indicates that the average temperature of the heating sub-region deviates significantly from the preset temperature. A large deviation signal is generated, and the heating sub-region is marked as a large deviation sub-region; Extract the total number of all large deviation sub-regions to obtain the number of large deviation sub-regions. Calculate the ratio of the number of large deviation sub-regions to the total number of sub-regions (the total number of sub-regions is the total number of heating sub-regions) to obtain the ratio of the number of large deviation sub-regions; At the same time, sum up the temperature abnormal characterization values of all heating sub-regions to obtain the abnormal deviation degree value; Multiply the abnormal deviation degree value by the ratio of the number of large deviation sub-regions to obtain the abnormal degree adjustment value; Sum up the abnormal degree adjustment value and the total abnormal degree value to obtain the abnormal degree characterization value; Thirdly, specifically, the process of obtaining the abnormal uniformity characterization value is as follows: Obtain the absolute abnormal characterization value of each heating sub-region, and calculate the variance value of the absolute abnormal characterization values of all heating sub-regions to obtain the abnormal uniformity characterization value; S2: Based on the monitoring data, calculate the abnormal coefficient of the heating process; In some embodiments, based on the abnormal degree characterization value CD and the abnormal uniformity characterization value JY, calculate the abnormal coefficient YC through a weighted formula, where a1 is the preset proportional factor of the abnormal degree characterization value, a2 is the preset proportional factor of the abnormal uniformity characterization value, and both are greater than 0. a1 is 2.47 and a2 is 2.23; S3: Based on the abnormal coefficient, analyze the heating process to determine whether the heating process is in an abnormal state during the monitoring period, and generate a state evaluation signal; Among them, the state evaluation signal includes: a state abnormal signal and a state normal signal; In some embodiments, preset an abnormal coefficient threshold, and compare and analyze the abnormal coefficient with the abnormal coefficient threshold; If the abnormal coefficient is less than or equal to the abnormal coefficient threshold, it indicates that during the monitoring period, the heating temperature deviates less from the preset temperature, and the internal temperature of the heating is relatively uniform, that is, a state normal signal is generated; If the abnormal coefficient is greater than the abnormal coefficient threshold, it indicates that during the monitoring period, the heating temperature deviates significantly from the preset temperature, and the internal temperature of the heating is relatively non-uniform, that is, a state abnormal signal is generated; The technical solution of the embodiment of the present invention is mainly as follows: First, set the monitoring period and regularly collect the temperature data during the heating process; Subsequently, evenly divide the heating area into multiple sub-areas, monitor the temperature of each sub-area, and calculate the abnormal data based on this; The abnormal data includes an abnormal degree characterization value and an abnormal uniformity characterization value; The former is comprehensively obtained by calculating the deviation between the temperature of each sub-area and the preset temperature, and considering the magnitude and distribution range of the deviation, which reflects the overall abnormal degree of the heating process; The latter measures the uniformity of the temperature distribution by calculating the variance of the temperature deviation of each sub-area; Next, use the abnormal degree characterization value and the abnormal uniformity characterization value to calculate the abnormal coefficient of the heating process; This coefficient is the key index for evaluating whether the heating process is abnormal; Finally, compare the abnormal coefficient with the preset threshold; If the abnormal coefficient is lower than the threshold, it indicates that the heating process is normal and a normal state signal is generated; If it is higher than the threshold, it indicates that there is an abnormality in the heating process and an abnormal state signal is generated; The embodiment of the present invention monitors the heating process in real time, and evaluates the heating process from the overall abnormal degree of the temperature and the uniformity of the temperature distribution, so as to achieve real-time monitoring, multi-dimensional analysis and automatic determination, effectively improving the intelligent level of aluminum foil heating rolling and ensuring the quality of aluminum foil; At the same time, it reduces manual intervention and improves work efficiency. Embodiment 3:

[0022] Based on Embodiment 2, the integrated electromagnetic heating control system described in the embodiment of the present invention further includes, and the specific method is as follows: S4: Based on the abnormal state signal, control the electromagnetic heating to regulate the temperature inside the integrated electromagnetic heating device. In some implementation schemes, when receiving the abnormal state signal, based on a single large-deviation sub-area, calculate the regulation power pre-value and the influence coefficient respectively. Multiply the regulation power pre-value by the influence coefficient to obtain the regulation power. Based on the regulation power, adjust the electromagnetic heating power of the large-deviation sub-area to regulate the temperature of the large-deviation sub-area. First specifically, the process of obtaining the regulation power pre-value is as follows: Based on the large-deviation sub-area, obtain the average temperature and average power within the monitoring period (the average power is the average value of the electromagnetic heating power of the large-deviation sub-area within the monitoring period). Through the formula: , calculate the regulation power pre-value TKY, where WD is the average temperature, YWD is the preset temperature, and GL is the average power. Second specifically, the process of obtaining the influence coefficient is as follows: Extract the large-deviation sub-areas in all adjacent heating sub-areas of the large-deviation sub-area and mark them as adjacent large-deviation sub-areas. Sum up the temperature anomaly characterization values of all sub-regions with large adjacent deviations to obtain the total adjacent deviation large anomaly value; Calculate the ratio of the total adjacent deviation large anomaly value to the total adjacent anomaly value (the total adjacent anomaly value is the total value of the temperature anomaly characterization values of all adjacent heating sub-regions) to obtain the influence coefficient; The technical solution of the embodiment of the present invention is mainly as follows: when a status anomaly signal is received, for each sub-region with a large deviation, according to its average temperature and average power during the monitoring period, and the preset target temperature, calculate the pre-adjustment power value; this step aims to determine the basic power adjustment amount required to reach the ideal temperature; Subsequently, in order to more comprehensively consider the complexity of temperature regulation, the method also calculates the influence coefficient; this coefficient evaluates the potential influence of adjacent regions on the current regulation by comparing the temperature anomaly degree of the sub-region with large deviation and its adjacent sub-regions; Finally, multiply the pre-adjustment power value by the influence coefficient to obtain the accurate regulation power value; thereby correspondingly adjusting the electromagnetic heating power of the sub-region with large deviation to achieve immediate and accurate control of the temperature; The technical solution of the embodiment of the present invention effectively improves the regulation accuracy of electromagnetic heating during the aluminum foil rolling process in the face of temperature anomalies through real-time monitoring, multi-dimensional analysis and calculation, and intelligent regulation, which not only helps to ensure the stability and consistency of the heating process, but also can significantly improve the quality and quality of the final product. Example 4:

[0023] Based on Embodiments 2 and 3, an electromagnetic heating control system described in an embodiment of the present invention includes: Data acquisition module: During the heating process after aluminum foil rolling, monitor the electromagnetic heating control of the heating process to obtain abnormal data during the monitoring period; Among them, the abnormal data includes: anomaly degree characterization value and anomaly uniformity characterization value; Data processing module: Based on the monitoring data, calculate the anomaly coefficient of the heating process; Status evaluation module: Based on the anomaly coefficient, analyze the heating process to determine whether the heating process is in an abnormal state during this monitoring period, and generate a status evaluation signal; Among them, the status evaluation signal includes: status anomaly signal and status normal signal; Temperature regulation module: Based on the status anomaly signal, control the electromagnetic heating to regulate the temperature inside the integrated electromagnetic heating device.

[0024] The setting of the magnitude of the above threshold is for the convenience of comparison. Regarding the magnitude of the threshold, it depends on the amount of sample data and the base quantity set by those skilled in the art for each group of sample data; The above formulas are all obtained by collecting a large amount of data for software simulation and selecting a formula close to the true value. The factors in the formula are set by those skilled in the art according to the actual situation; those skilled in the art collect multiple groups of monitoring data and set corresponding anomaly coefficients for each group of monitoring data; substitute the set anomaly coefficients and the collected monitoring data into the formula, and any two formulas form a system of binary linear equations. Screen the calculated factors and take the average value to obtain the values of a1 and a2 as 2.47 and 2.23 respectively; The magnitude of the factor is a specific value obtained by quantifying each parameter for subsequent comparison. Regarding the magnitude of the factor, it depends on the amount of monitoring data and the initial setting of corresponding anomaly coefficients for each group of monitoring data by those skilled in the art; as long as it does not affect the proportional relationship between the parameter and the quantified value, for example, the anomaly coefficient is proportional to the value of the anomaly degree characterization value.

[0025] The above has described a specific embodiment of the present invention in detail, but the content described is only a preferred embodiment of the present invention and cannot be considered as limiting the scope of implementation of the present invention. Any equivalent changes and improvements made within the scope of the application of the present invention shall still fall within the scope covered by the patent of the present invention.

Claims

1. A high-speed and high-stability rolling process for aluminum foil, characterized in that, The high-speed rolling mill rolls the aluminum strip to the target thickness, heats the strip or the roll through an integrated electromagnetic heating control system, and improves stability and shape accuracy; it includes the following steps: S1: During the heating process after aluminum foil rolling, conduct electromagnetic heating control monitoring on the heating process to obtain abnormal data within the monitoring period; Among them, the abnormal data includes: an abnormal degree characterization value and an abnormal uniformity characterization value; S2: Based on the monitoring data, calculate the abnormal coefficient of the heating process; S3: Based on the abnormal coefficient, analyze the heating process to determine whether the heating process is in an abnormal state within the monitoring period, and generate a status evaluation signal; Among them, the status evaluation signal includes: a status abnormal signal and a status normal signal; S4: Based on the status abnormal signal, control the electromagnetic heating to regulate the temperature inside the integrated electromagnetic heating device.

2. A high-speed and high-stability rolling process for aluminum foil according to claim 1, characterized in that, The process of obtaining abnormal data is as follows: During the electromagnetic heating process, evenly divide the total heating area spatially to obtain several heating sub-areas; Within the monitoring period, monitor the temperature of each heating sub-area respectively to obtain the temperature abnormal characterization value of each heating sub-area; Based on the temperature abnormal characterization values of each heating sub-area, calculate the abnormal degree characterization value and the abnormal uniformity characterization value respectively.

3. A high-speed and high-stability rolling process for aluminum foil according to claim 2, characterized in that, The process of obtaining the temperature abnormal characterization value is as follows: Based on a single heating sub-area, obtain the average temperature of this heating sub-area within the monitoring period, calculate the difference between the average temperature and the preset temperature to obtain the temperature deviation value; Calculate the ratio of the temperature deviation value to the preset temperature to obtain the temperature abnormal characterization value.

4. A high-speed and high-stability rolling process for aluminum foil according to claim 3, characterized in that The process of obtaining the abnormal degree characterization value is as follows: Obtain the temperature abnormal characterization values of each heating sub-area, respectively perform absolute value processing on the temperature abnormal characterization values to obtain the absolute abnormal characterization values of each heating sub-area; Sum up all the absolute abnormal characterization values to obtain the total abnormal degree value; At the same time, respectively compare and analyze the absolute abnormal characterization values of all heating sub-areas with the absolute abnormal characterization threshold; If the absolute abnormal characterization value is less than or equal to the absolute abnormal characterization threshold, generate a small deviation signal; If the absolute abnormal characterization value is greater than the absolute abnormal characterization threshold, generate a large deviation signal, and mark this heating sub-area as a large deviation sub-area; Extract the total number of all large deviation sub-areas to obtain the number of large deviation sub-areas, calculate the ratio of the number of large deviation sub-areas to the total number of sub-areas to obtain the ratio of the number of large deviation sub-areas; At the same time, sum up the temperature abnormal characterization values of all heating sub-areas to obtain the abnormal deviation degree value; Calculate the product of the abnormal deviation degree value and the ratio of the number of large deviation sub-areas to obtain the abnormal degree adjustment value; Sum up the abnormal degree adjustment value and the total abnormal degree value to obtain the abnormal degree characterization value.

5. A high-speed and high-stability rolling process for aluminum foil according to claim 4, characterized in that The process of obtaining the abnormal uniformity characterization value is as follows: Obtain the absolute abnormal characterization values of each heating sub-area, calculate the variance value of the absolute abnormal characterization values of all heating sub-areas to obtain the abnormal uniformity characterization value.

6. A high-speed and high-stability rolling process for aluminum foil according to claim 1, characterized in that The process of generating the status evaluation signal is as follows: Preset the abnormal coefficient threshold, and compare and analyze the abnormal coefficient with the abnormal coefficient threshold; If the abnormal coefficient is less than or equal to the abnormal coefficient threshold, then generate a status normal signal; If the anomaly coefficient is greater than the anomaly coefficient threshold, a status anomaly signal is generated.

7. A high-speed and high-stability rolling process for aluminum foil according to claim 1, characterized in that, The process of regulating the temperature inside the electromagnetic heating device is as follows: When the status anomaly signal is received, based on a single large deviation sub-region, the regulated power pre-value and the influence coefficient are calculated respectively; The regulated power is obtained by calculating the product of the regulated power pre-value and the influence coefficient; Based on the regulated power, the electromagnetic heating power of this large deviation sub-region is adjusted, so as to regulate the temperature of this large deviation sub-region.

8. A high-speed and high-stability rolling process for aluminum foil according to claim 7, characterized in that, The process of obtaining the regulated power pre-value is as follows: Based on this large deviation sub-region, the average temperature and average power within this monitoring period are obtained; Through the formula: , calculate the regulated power threshold value TKY, where WD is the average temperature, YWD is the preset temperature, and GL is the average power.

9. A high-speed and highly stable rolling process for aluminum foil according to claim 7, characterized in that The process of obtaining the influence coefficient is as follows: Extract the large deviation sub-regions in all adjacent heating sub-regions of this large deviation sub-region and mark them as adjacent large deviation sub-regions; The temperature anomaly characterization values of all adjacent large deviation sub-regions are summed up to obtain the total adjacent large deviation anomaly value.

10. A high-speed and high-stability rolling process for aluminum foil according to claim 9, characterized in that, It is characterized in that The influence coefficient is obtained by calculating the ratio of the total adjacent large deviation anomaly value to the total adjacent anomaly value.

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