Copper foil rolling plate shape detection and dynamic control method and equipment

Abstract

The invention is suitable for the technical field of copper foil rolling, and particularly relates to a copper foil rolling plate shape detection and dynamic control method and device, and the method comprises the steps that a first control parameter and the thickness of each segmented area are obtained in real time; global plate shape features and local plate shape features of the segmented areas are obtained according to the thicknesses of the segmented areas; obtaining defect propagation probabilities among the segmented areas according to the local plate shape features; according to the global plate shape feature and each local plate shape feature, obtaining a defect influence coefficient of each segmented region on the global plate shape; obtaining the contribution degree of each segmented region according to the propagation probability of each defect and the influence coefficient of each defect; sorting the segmented regions according to the contribution degrees to obtain a plurality of key regions; and a second control parameter of next rolling is adjusted based on the first control parameter and the thickness of each key area. Therefore, according to the method provided by the invention, refined area control can be realized, so that the rolling parameters are adjusted in a targeted manner.

Description

Technical Field

[0001] This application belongs to the field of copper foil rolling technology, and in particular relates to methods and equipment for copper foil rolling shape detection and dynamic control. Background Technology

[0002] Copper foil rolling uses copper ingots or relatively thick copper strips as initial raw materials. These are placed in a specially designed rolling mill, and under the strong pressure of the rolls, the copper material is rolled thinner in multiple passes through continuous rolling.

[0003] In existing technologies, copper foil rolling control mostly focuses on the average parameters of the entire copper foil, insufficiently considering regional differences along the foil's width. When thickness deviations occur in the middle region of the copper foil, the mill cannot adjust that region individually due to the lack of regional feedback signals, relying solely on overall adjustment, which may affect the thickness and shape quality of other regions. Using the overall average thickness and material performance parameters when calculating rolling force and other data, without considering the differences between different regions of the copper foil, leads to inaccurate thickness control in different regions during actual rolling, making precise regional control impossible. Therefore, existing copper foil rolling technologies suffer from the problem of difficulty in achieving precise regional control and thus hindering targeted adjustment of rolling parameters. Summary of the Invention

[0004] This application provides a method and equipment for detecting and dynamically controlling the shape of rolled copper foil, which can solve the problem of difficulty in achieving precise regional control, thereby enabling targeted adjustment of rolling parameters.

[0005] In a first aspect, embodiments of this application provide a method for detecting and dynamically controlling the shape of rolled copper foil, including: The copper foil is divided into multiple segmented regions along the rolling direction; The first control parameter and the thickness of each segmented region are acquired in real time; wherein the first control parameter is used to control the rolling and inspection of the copper foil; The global plate shape features and the local plate shape features of each segmented region are obtained based on the thickness of each segmented region; wherein, the global plate shape features include the overall waviness and warpage of the copper foil, and the local plate shape features are used to reflect the shape features of each segmented region; The probability of defect propagation between the segmented regions is obtained based on the local plate shape features described above. The defect influence coefficient of each segmented region on the global plate shape is obtained based on the global plate shape features and the local plate shape features. The contribution of each segmented region is obtained based on the propagation probability of each defect and the influence coefficient of each defect. Based on the contribution level, the segmented regions are sorted to obtain multiple key regions; The second control parameter for the next rolling process is adjusted based on the first control parameter and the thickness of each of the key regions.

[0006] The technical solutions described in this application embodiment have at least the following technical effects: The copper foil rolling shape detection and dynamic control method provided in this application divides the copper foil into multiple segmented regions along the rolling direction; acquires first control parameters and the thickness of each segmented region in real time; obtains global shape features and local shape features of each segmented region based on the thickness of each segmented region; obtains the defect propagation probability between each segmented region based on the local shape features; obtains the defect influence coefficient of each segmented region on the global shape based on the global shape features and the local shape features; obtains the contribution of each segmented region based on the defect propagation probability and the defect influence coefficient; sorts each segmented region according to the contribution to obtain multiple key regions; and adjusts the second control parameters for the next rolling based on the first control parameters and the thickness of each key region. Therefore, the copper foil rolling shape detection and dynamic control method provided in this application comprehensively grasps the shape of the copper foil from both local and overall perspectives, and makes targeted adjustments to key regions, which is beneficial for achieving precise control of the copper foil shape and improving the quality of the copper foil shape.

[0007] In one possible implementation of the first aspect, the second control parameter includes monitoring frequency, rolling speed, and / or rolling pressure; the second control parameter, based on the first control parameter and the thickness of each of the key regions, adjusts the next rolling operation, including: The first parameter range in the initial rolling stage, the second parameter range in the steady-state stage, and the third parameter range in the deceleration stage are determined based on the first control parameter. Each of the key regions is divided into multiple corresponding sub-regions; In the initial stage of rolling, the second control parameters of each sub-region are adjusted within the range of the first parameter according to the thickness of each sub-region; During the steady-state phase, the second control parameters of each of the key regions are adjusted within the range of the second parameters according to the thickness of each key region. During the deceleration phase, the second control parameter of each sub-region is adjusted within the range of the third parameter according to the thickness of each sub-region.

[0008] In one possible implementation of the first aspect, adjusting the second control parameter of each of the sub-regions within the first parameter range according to the thickness of each sub-region during the initial stage of rolling includes: In the initial stage of rolling, the weight of the sub-region located at the edge of the copper foil is increased; Within the first parameter range, a first parameter value and a first adjustment priority are obtained based on the weight of each sub-region and the corresponding thickness; The second control parameters of each sub-region are adjusted according to the first parameter value and the first adjustment priority.

[0009] In one possible implementation of the first aspect, adjusting the second control parameter of each of the key regions within the range of the second parameter according to the thickness of each key region during the steady-state phase includes: If the contribution of the key area is greater than the preset threshold, then within the range of the second parameter, the second parameter value is obtained according to the corresponding thickness; Adjust the second control parameter according to the second parameter value; If the contribution of the key region is less than or equal to the preset threshold, then the second parameter range is adjusted according to the corresponding thickness to obtain the first parameter range; Adjust the second control parameter according to the first parameter range.

[0010] In one possible implementation of the first aspect, adjusting the second control parameter of each of the sub-regions within the range of the third parameter according to the thickness of each sub-region during the deceleration phase includes: During the deceleration phase, the weight of the sub-region located in the middle of the copper foil is increased; Within the range of the third parameter, the value of the third parameter and the second adjustment priority are obtained according to the weight of each sub-region and the corresponding thickness; The second control parameters of each sub-region are adjusted according to the third parameter value and the second adjustment priority.

[0011] In one possible implementation of the first aspect, obtaining the defect propagation probability between each of the segmented regions based on each of the local plate shape features includes: Acquire historical defect data; wherein, the historical defect data includes historical local features of each of the segmented regions; A Bayesian network is trained based on the historical defect data; wherein, the nodes of the Bayesian network refer to each segmented region, the edges of the Bayesian network refer to the dependencies between nodes, and the edge weights of the Bayesian network refer to the defect propagation probability. The edge weights of the Bayesian network are updated based on the local plate shape features to obtain the defect propagation probability between the segmented regions.

[0012] In one possible implementation of the first aspect, obtaining the defect influence coefficient of each segmented region on the global plate shape based on the global plate shape features and each of the local plate shape features includes: The global Moran index and the local Giselle index of each segmented region are calculated based on the global plate shape features and the local plate shape features. The defect influence coefficients are obtained based on the global Moran index and each of the local Giselle indices.

[0013] In one possible implementation of the first aspect, obtaining the global plate shape feature and the local plate shape feature of each of the segmented regions based on the thickness of each segmented region includes: The overall transverse wavyity of the copper foil is obtained based on the thickness of each segment region; The warpage of the copper foil in the longitudinal direction is obtained based on the thickness of each segment region.

[0014] In one possible implementation of the first aspect, the local plate shape features include local waviness and local warping; obtaining the global plate shape features and the local plate shape features of each segmented region based on the thickness of each segmented region further includes: Perform a Fourier transform on the thickness of each segmented region, extract the main frequency amplitude and wavelength, and obtain the corresponding local waviness. The local warpage is obtained by calculating the corresponding thickness range and average thickness based on the thickness of each segmented region.

[0015] Secondly, embodiments of this application provide a copper foil rolling sheet shape detection and dynamic control device, including: The segmented region module is used to divide the copper foil into multiple segmented regions along the rolling direction; The acquisition module is used to acquire the first control parameter and the thickness of each segmented region in real time; wherein, the first control parameter is used to control the rolling and detection of the copper foil; The plate shape feature module is used to obtain global plate shape features and local plate shape features of each segmented region based on the thickness of each segmented region; wherein, the global plate shape features include the overall waviness and warp of the copper foil, and the local plate shape features are used to reflect the shape features of each segmented region; The defect propagation probability module is used to obtain the defect propagation probability between each segmented region based on each of the local plate shape features. The defect influence coefficient module is used to obtain the defect influence coefficient of each segmented region on the global plate shape based on the global plate shape features and each of the local plate shape features; The contribution module is used to obtain the contribution of each segmented region based on the propagation probability of each defect and the influence coefficient of each defect. The key region module is used to sort the segmented regions according to their respective contributions to obtain multiple key regions; The second control parameter module is used to adjust the second control parameters for the next rolling process based on the first control parameters and the thickness of each of the key regions.

[0016] Thirdly, embodiments of this application provide a copper foil rolling sheet shape detection and dynamic control device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the method as described in any one of the first aspects above.

[0017] Fourthly, embodiments of this application provide a computer-readable storage medium storing a computer program that, when executed by a processor, implements the method described in any of the first aspects above.

[0018] Fifthly, embodiments of this application provide a computer program product that, when run on a copper foil rolling sheet shape detection and dynamic control device, causes the copper foil rolling sheet shape detection and dynamic control device to perform the method described in any one of the first aspects above.

[0019] It is understood that the beneficial effects of the second to fifth aspects mentioned above can be found in the relevant descriptions in the first aspect mentioned above, and will not be repeated here. Attached Figure Description

[0020] 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.

[0021] Figure 1 This is a schematic flowchart of a method for detecting and dynamically controlling the shape of rolled copper foil provided in an embodiment of this application; Figure 2 This is a schematic diagram of the implementation process of steps S800, S830, S840 and S850 in the copper foil rolling shape detection and dynamic control method provided in an embodiment of this application. Figure 3 This is a schematic diagram of the implementation process of steps S300, S400 and S500 in the copper foil rolling shape detection and dynamic control method provided in an embodiment of this application; Figure 4 This is an example diagram of thickness deviation in the copper foil rolling sheet shape detection and dynamic control method provided in an embodiment of this application; Figure 5 This is a schematic diagram of the structure of the copper foil rolling sheet shape detection and dynamic control device provided in the embodiments of this application; Figure 6 This is a schematic diagram of the structure of the copper foil rolling sheet shape detection and dynamic control equipment provided in the embodiments of this application. Detailed Implementation

[0022] 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.

[0023] It should be understood that, when used in this application specification and the appended claims, the term "comprising" indicates the presence of the described features, integrals, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components and / or a collection thereof.

[0024] It should also be understood that the term “and / or” as used in this application specification and the appended claims means any combination of one or more of the associated listed items and all possible combinations, and includes such combinations.

[0025] As used in this application specification and the appended claims, the term "if" may be interpreted, depending on the context, as "when," "once," "in response to determination," or "in response to detection." Similarly, the phrase "if determined" or "if detected [the described condition or event]" may be interpreted, depending on the context, as meaning "once determined," "in response to determination," "once detected [the described condition or event]," or "in response to detection [the described condition or event]."

[0026] Furthermore, in the description of this application and the appended claims, the terms "first," "second," "third," etc., are used only to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0027] References to "one embodiment" or "some embodiments" as described in this specification mean that one or more embodiments of this application include a specific feature, structure, or characteristic described in connection with that embodiment. Therefore, the phrases "in one embodiment," "in some embodiments," "in other embodiments," "in still other embodiments," etc., appearing in different parts of this specification do not necessarily refer to the same embodiment, but rather mean "one or more, but not all, embodiments," unless otherwise specifically emphasized. The terms "comprising," "including," "having," and variations thereof mean "including but not limited to," unless otherwise specifically emphasized.

[0028] In related technologies, the rolling control of copper foil mostly focuses only on the average parameters of the entire copper foil, with insufficient consideration for regional differences in the width direction. When the thickness exceeds the tolerance in the middle area of ​​the copper foil, the rolling mill cannot adjust that area individually due to the lack of regional feedback signals, and can only rely on overall adjustment, which may affect the thickness and shape quality of other areas. Using the overall average thickness and material performance parameters when calculating rolling force and other data, without considering the differences in different areas of the copper foil, leads to inaccurate thickness control in different areas during actual rolling, making it impossible to achieve fine-grained regional control. Therefore, existing copper foil rolling technologies suffer from the problem of difficulty in achieving fine-grained regional control and thus making it difficult to adjust rolling parameters specifically.

[0029] To address the aforementioned issues, this application provides a method and apparatus for detecting and dynamically controlling the shape of rolled copper foil. In this method, the copper foil is divided into multiple segmented regions along the rolling direction; a first control parameter and the thickness of each segmented region are acquired in real time; local shape features are obtained based on the thickness of each segmented region; global shape features and defect propagation probabilities between segmented regions are obtained based on the local shape features; the defect influence coefficient of each segmented region on the global shape is obtained based on the global shape features and local shape features; the contribution of each segmented region is obtained based on the defect propagation probabilities and defect influence coefficients; the segmented regions are sorted according to their contribution to obtain multiple key regions; and a second control parameter for the next rolling cycle is adjusted based on the first control parameter and the thickness of each key region. Therefore, the copper foil rolling shape detection and dynamic control method provided in this application comprehensively grasps the shape of the copper foil from both local and overall perspectives, and makes targeted adjustments to key regions, which is beneficial for achieving precise control of the copper foil shape and improving the quality of the copper foil shape.

[0030] The copper foil rolling shape detection and dynamic control method provided in this application embodiment can be applied to copper foil rolling shape detection and dynamic control equipment. In this case, the copper foil rolling shape detection and dynamic control equipment is the execution subject of the copper foil rolling shape detection and dynamic control method provided in this application embodiment. This application embodiment does not impose any restrictions on the specific type of copper foil rolling shape detection and dynamic control equipment.

[0031] For example, the copper foil rolling shape detection and dynamic control equipment is communicatively connected to copper foil rolling equipment with roll shifting function (such as a multi-roll mill). The copper foil rolling shape detection and dynamic control equipment can be a programmable logic controller (PLC), a distributed control system (DCS), an industrial personal computer (IPC), a mobile phone, a tablet computer, a wearable device, a laptop computer, an ultra-mobile personal computer (UMPC), a netbook, a personal digital assistant (PDA), a desktop computer, a handheld device with wireless communication function, a computing device or other processing device connected to a wireless modem, a laptop computer, a handheld computing device, etc., but is not limited to these.

[0032] To better understand the copper foil rolling shape detection and dynamic control method provided in the embodiments of this application, the specific implementation process of the copper foil rolling shape detection and dynamic control method provided in the embodiments of this application will be described by way of example below.

[0033] Figure 1 This illustration shows a schematic flowchart of a copper foil rolling shape detection and dynamic control method provided in an embodiment of this application. The copper foil rolling shape detection and dynamic control method includes: S100 divides the copper foil into multiple segmented regions along the rolling direction.

[0034] For example, the copper foil can be divided into multiple equal-length segments along the rolling direction (i.e., the length direction). For instance, assuming the total length of the copper foil is 1000 mm, it can be divided into 10 segments, each segment being 100 mm long.

[0035] S200 acquires the first control parameter and the thickness of each segment region in real time. The first control parameter is used to control the rolling and inspection of the copper foil.

[0036] It is understandable that the first control parameters include monitoring frequency, rolling speed, and rolling pressure.

[0037] For example, the thickness of each segment can be acquired in real time using a laser thickness gauge (such as a non-contact laser thickness gauge); the rolling speed and rolling pressure can be acquired in real time using a laser velocimeter (such as a Doppler laser velocimeter) and a pressure sensor (such as a piezomagnetic pressure sensor); the monitoring frequency of the segment is matched with the rolling speed, for example, f=v n / L, where f is the monitoring frequency (Hz, i.e., the number of samples per second), v is the rolling speed (m / s), n is the number of segmented areas, and L is the effective scanning length (m) of the laser thickness gauge along the length direction of the copper foil. The laser thickness gauge, laser speedometer, and pressure sensor are all communicatively connected to the copper foil rolling shape detection and dynamic control device. The laser thickness gauge is installed on the outlet side of the copper foil rolling equipment and arranged parallel to the roll; the laser speedometer is installed on the inlet and outlet sides of the copper foil rolling equipment; the pressure sensor is installed inside the roll bearing block.

[0038] S300. Obtain the global shape characteristics and the local shape characteristics of each segmented area based on the thickness of each segmented area. Among them, the global shape characteristics include the waviness and warping degree of the overall copper foil, and the local shape characteristics are used to reflect the shape characteristics of each segmented area.

[0039] Exemplarily, the local shape characteristics can be calculated based on the thickness data. The local shape characteristics can include local waviness and local warping degree, etc. Using the fast Fourier transform (FFT) algorithm, the thickness data is converted into a spectrum to obtain the local waviness. For example, the wavelength of the main wave peak is 200 mm and the amplitude is 0.01 mm, and the amplitude is determined as the local waviness; the maximum warping height is measured by a surface profiler, and the ratio of the maximum warping height to the area length of each segmented area is calculated to obtain the local warping degree. For example, 0.1 mm / 100 mm = 0.001. The global shape characteristics can be obtained according to all the local shape characteristics. The waviness is the weighted average of the waviness of each area, and the weight is determined by the area ratio of each segmented area; the warping degree takes the maximum value.

[0040] S400. Obtain the defect propagation probability between each segmented area based on each local shape characteristic.

[0041] Exemplarily, the defect propagation probability can be calculated based on the spatial correlation between each segmented area. For the thickness deviation sequence of adjacent segmented areas, the Pearson correlation coefficient is calculated. Establish the mapping relationship between the correlation coefficient (r) and the propagation probability. For example, when r > 0.8, the propagation probability is set to 0.7; when 0.5 < r ≤ 0.8, it is set to 0.4; when r ≤ 0.5, it is set to 0.1. The correlation coefficient calculation window can be adjusted in real time according to the rolling speed. For example, at a speed of 300 m / min, the thickness data within 1 second is taken to calculate the correlation coefficient; at a speed of 500 m / min, the thickness data within 0.6 seconds is taken.

[0042] S500. Obtain the defect influence coefficient of each segmented area on the global shape based on the global shape characteristics and each local shape characteristic.

[0043] For example, a regression model can be used to calculate the defect impact coefficient of each segmented region on the global plate shape. The model input is local plate shape features (local waviness and local warp), and the output is global plate shape features (global waviness and warp). For example, with local waviness (x1) and local warp (x2) as independent variables and global waviness (Y1) and global warp (Y2) as dependent variables, a regression equation is established. Using the least squares method, historical local plate shape features and historical global plate shape features are obtained based on historical thickness data. The regression coefficients of the waviness regression model are calculated based on the global waviness of the historical local plate shape features and the local waviness of the historical global plate shape features to obtain the waviness regression model; the regression coefficients of the warp regression model are calculated based on the global warp of the historical local plate shape features and the local warp of the historical global plate shape features to obtain the warp regression model. For the local undulation of each segmented region, its contribution to the global undulation is calculated based on the corresponding regression coefficient of the undulation regression model; for the local warpage of each segmented region, its contribution to the global warpage is calculated based on the corresponding regression coefficient of the warpage regression model; and the contribution values ​​to the global undulation and the global warpage are normalized and then weighted and summed to obtain the defect influence coefficient of each segmented region on the global plate shape.

[0044] S600, the contribution of each segment region is obtained based on the propagation probability of each defect and the influence coefficient of each defect.

[0045] For example, the contribution of each segment region can be calculated based on the propagation probability and the influence coefficient of each defect. For instance, the initial contribution is calculated as follows: initial contribution = defect propagation probability × defect influence coefficient. The propagation probability of segment region 2 is 0.7, the influence coefficient is 0.8, and the initial contribution is 0.56. The initial contribution of all segment regions is then normalized to obtain the contribution of each segment region.

[0046] S700 sorts the segmented regions according to their contribution to obtain multiple key regions.

[0047] For example, the regions can be sorted in descending order of contribution, and the top N% (e.g., 30%) of the segments can be selected as key regions.

[0048] S800, based on the first control parameter and the thickness of each key region, adjusts the second control parameter for the next rolling process.

[0049] For example, the monitoring frequency of the next rolling can be adjusted based on the deviation between the thickness of the critical region and the preset thickness. The adjustment amount of rolling speed and rolling pressure is determined by a PID control algorithm based on the first control parameter and the deviation between the thickness of the critical region and the preset thickness. The coefficients of the PID control algorithm can be dynamically adjusted according to the contribution.

[0050] In one possible implementation, please refer to Figure 2 The second control parameters include monitoring frequency, rolling speed, and / or rolling pressure. S800, based on the first control parameters and the thickness of each key region, adjusts the second control parameters for the next rolling operation, including: S810, based on the first control parameter, determines the first parameter range in the initial rolling stage, the second parameter range in the steady-state stage, and the third parameter range in the deceleration stage.

[0051] For example, the first parameter range for the initial rolling stage, the second parameter range for the steady-state stage, and the third parameter range for the deceleration stage can be determined based on the first control parameters. For instance, if the first control parameters are a rolling pressure of 500 kN and a rolling speed of 10 m / min, a three-stage parameter mapping model can be established through a process database: In the initial rolling stage (e.g., the first 20% of the copper foil length), the first parameter range is set to a rolling pressure of 450-550 kN and a rolling speed of 8-12 m / min; in the steady-state stage (e.g., the middle 60% of the copper foil length), the second parameter range is a rolling pressure of 480-520 kN and a rolling speed of 9-11 m / min to improve thickness uniformity; in the deceleration stage (e.g., the last 20% of the copper foil length), the third parameter range is a rolling pressure of 400-480 kN and a rolling speed of 5-8 m / min to prevent overpressure at the end.

[0052] S820 divides each key area into multiple corresponding sub-regions.

[0053] For example, each critical region can be divided into multiple equal-width sub-regions along the width direction, such as each sub-region being 100mm wide (total critical region width 1000mm). A grid-based partitioning strategy can be adopted, with the sub-region boundaries aligned with the contact points of rolls that can be shifted, allowing each sub-region to undergo independent rolling control.

[0054] S830, in the initial stage of rolling, adjusts the second control parameters of each sub-region within the first parameter range according to the thickness of each sub-region.

[0055] For example, each sub-region can be independently controlled using PID control based on its thickness, adjusting a second control parameter for each sub-region within a first parameter range. Examples include adjustments to the rolling speed and rolling pressure. , where K p,i It is the proportionality coefficient, K i,i It is the integral coefficient, K d,i It is the differential coefficient, e i (t) represents the deviation between the thickness of each sub-region and the preset thickness collected in real time, and if e i If (t) is not within the preset thickness range, increase the monitoring frequency; otherwise, decrease the monitoring frequency.

[0056] S840, in the steady state phase, adjusts the second control parameters of each key region within the second parameter range according to the thickness of each key region.

[0057] For example, the optimal parameter combination can be solved within the range of the second parameter by using a global optimization algorithm (such as particle swarm optimization, genetic algorithm, etc.) based on historical rolling data (including historical thickness data and corresponding historical parameters, including monitoring frequency, rolling speed and rolling pressure) to adjust the second control parameters of the key area.

[0058] S850, during the deceleration phase, adjusts the second control parameters of each sub-region within the range of the third parameter according to the thickness of each sub-region.

[0059] For example, a gradient decrease control strategy can be adopted to adjust the second control parameters of each sub-region within the range of the third parameter according to the gradient direction of the thickness deviation, and increase the monitoring frequency to capture thickness abrupt changes in real time.

[0060] Traditional rolling control uses globally uniform parameters, which cannot adapt to the needs of different stages, resulting in large initial thickness fluctuations, poor steady-state thickness uniformity, and susceptibility to overpressure defects during the deceleration stage. Through steps S810 to S850, the staged parameter range division and sub-regional refined control solve the problems of parameter adjustment lag and insufficient control precision. By quantifying the staged and regional control strategies, a closed-loop dynamic adjustment system is formed, achieving precise shape control from local to global levels.

[0061] Optionally, please refer to Figure 2 S830, in the initial stage of rolling, adjusts the second control parameters of each sub-region within the first parameter range according to the thickness of each sub-region, including: S831 increases the weight of the sub-regions located at the edge of the copper foil during the initial rolling stage.

[0062] For example, the copper foil can be divided into three regions along its width: the edge (10% width on each side), the secondary edge (20% width in the middle), and the center (the remaining 70% width). For instance, a critical region with a total width of 1000mm is divided into the edge (0-100mm, 900-1000mm), the secondary edge (100-300mm, 700-900mm), and the center (300-700mm). The weight of the edge region is set to 1.5, the weight of the secondary edge region to 1.2, and the weight of the center region to 1.0. If, during the initial rolling stage, the thickness deviation of the sub-regions located at the edge of the copper foil (the thickness deviation of each type of sub-region is as follows...) Figure 4 If the value exceeds a threshold (e.g., ±0.02 mm), the weight of the sub-region located at the edge of the copper foil will be increased to 2.0.

[0063] S832, within the first parameter range, obtain the first parameter value and the first adjustment priority according to the weight and corresponding thickness of each sub-region.

[0064] For example, a weighted scoring model can be used to determine the score of each sub-region based on its weight and the deviation of its corresponding thickness from a preset thickness. A proportional-integral (PI) controller is used to obtain a first parameter value, and the scores of each sub-region are arranged in order to obtain a first adjustment priority, with higher scores having higher priority. For example, the score S of each sub-region... i =w i (∣d i | / d max ) 2 The first parameter value P i =K p S i +K i ∫S i dt, where w i For weights, d i For thickness deviation, d max To allow the maximum deviation (e.g., 0.05 mm), K p K i For proportional and integral coefficients (e.g., K) p =0.5, K i =0.1).

[0065] S833, adjust the second control parameters of each sub-region according to the first parameter value and the first adjustment priority.

[0066] For example, high-priority sub-regions (such as edges) can use fast-response control with an adjustment step size of 1.5 times the normal value; low-priority sub-regions can use conservative adjustment with an adjustment step size of 0.8 times the normal value. Adjustments are made sequentially from high to low priority, and the score and priority are recalculated after each adjustment to form a closed-loop control. The adjustment values ​​must be within the range of the first parameter.

[0067] Global uniform adjustment cannot quickly respond to local thickness fluctuations, resulting in poor steady-state thickness uniformity. The lack of a priority mechanism may lead to over-adjustment in low-deviation areas, triggering new thickness fluctuations. Through steps S831 to S833, edge defect rate is reduced by increasing weights and implementing rapid response control; regional weighted control helps improve steady-state uniformity and board shape quality; the priority mechanism reduces the number of ineffective adjustments and optimizes adjustment efficiency; and the weights and parameter ranges can be dynamically configured based on different copper foil specifications.

[0068] Optionally, please refer to Figure 2S840, in the steady-state phase, adjusts the second control parameters of each key region within the second parameter range according to the thickness of each key region, including: S841, if the contribution of the key area is greater than the preset threshold, then within the range of the second parameter, the value of the second parameter is obtained according to the corresponding thickness.

[0069] For example, if the contribution of a critical region is greater than a preset threshold, then within the range of the second parameter, a proportional-integral-derivative (PID) controller is used to calculate the value of the second parameter based on the deviation between the thickness of the corresponding critical region and the preset thickness. For example, contribution C i =w i ∣d i | / j ∣d j |, where w i The weight of the key region, d i denoted as thickness deviation, and n as the total number of critical areas.

[0070] S842, adjust the second control parameter according to the second parameter value.

[0071] For example, feedforward compensation can be introduced based on the value of the second parameter to eliminate the effect of elastic deformation of the rolls (e.g., based on the current rolling pressure P(t) and the target pressure increment ΔP). i (t) Calculate the roll gap adjustment amount that needs to be compensated, roll gap adjustment amount = Where D is the roll diameter, E is the elastic modulus, and W is the roll width), and the second control parameter is adjusted according to the second parameter value.

[0072] S843, if the contribution of the key area is less than or equal to the preset threshold, the range of the second parameter is adjusted according to the corresponding thickness to obtain the range of the first parameter.

[0073] For example, if the contribution of a key region is less than or equal to a preset threshold, the range of the second parameter is shrunk to obtain the range of the first parameter according to the thickness deviation ratio. If the thickness deviation does not improve after n consecutive adjustments (e.g., 3 times), the preset threshold is lowered to strengthen the control of low contribution regions.

[0074] S844, adjust the second control parameter according to the range of the first parameter.

[0075] For example, within the range of the first parameter, a genetic algorithm can be used to adjust the second control parameter (where the objective function of the genetic algorithm is: min d i 2 +λ ΔP i2 (where λ is the parameter adjustment penalty coefficient and m is the number of iterations), when the adjustment amount exceeds 10% of the current parameter, it is implemented in multiple stages, and the contribution is recalculated and compared with the preset threshold after adjustment.

[0076] Through the above steps S841 to S844, the control resources are concentrated in the high contribution area by judging the contribution threshold; the parameter range is adaptive, which is conducive to optimizing the adjustment efficiency; the dynamic update mechanism of the contribution threshold enhances the robustness of the process.

[0077] Optionally, please refer to Figure 2 S850, during the deceleration phase, adjusts the second control parameters of each sub-region within the range of the third parameter based on the thickness of each sub-region, including: S851 increases the weight of the sub-region located in the middle of the copper foil during the deceleration phase.

[0078] For example, during the deceleration phase, a velocity-related weight correction coefficient can be introduced to increase the weight of the sub-region located in the middle of the copper foil. For instance, the velocity-related weight correction coefficient β(v) = 1 + k (1−v / v max ), where k is the modified intensity coefficient.

[0079] S852, within the range of the third parameter, obtains the third parameter value and the second adjustment priority based on the weight and corresponding thickness of each sub-region.

[0080] For example, the thickness deviation d of each sub-region can be... i The weighted sum of the weights is mapped to the range of the third parameter to obtain the value of the third parameter, for example, the value of the third parameter P. i =[w i final d i / max j (w j final ∣d j ∣)] (P max -P min )+P min , where P max It is the maximum value of the corresponding parameter within the range of the third parameter, P. min It is the minimum value of the corresponding parameter within the range of the third parameter. The second adjustment priority is determined by arranging the sub-regions in order of their weights and thickness deviations.

[0081] S853 adjusts the second control parameter of each sub-region based on the third parameter value and the second adjustment priority.

[0082] For example, the second control parameters of each sub-region can be adjusted sequentially according to priority, with each adjustment amount being the difference between the third parameter value and the current parameter, limited to the maximum adjustment amount per step. After adjustment, the thickness deviation of each sub-region is recalculated. If the thickness deviation of any sub-region is still greater than the preset threshold, S851-S853 are executed again until all deviations are no greater than the preset threshold.

[0083] Through the above steps S851 to S853, dynamic and precise compensation is achieved through dynamic weight adjustment during the deceleration phase, priority-driven precise resource allocation, and coupled compensation control, which helps to improve the uniformity of copper foil thickness and process stability.

[0084] In one possible implementation, please refer to Figure 3 S400, based on the local plate shape characteristics, obtains the defect propagation probability between each segment region, including: S410, Obtain historical defect data. This historical defect data includes historical local features of each segmented region.

[0085] It is understandable that historical defect data includes historical local features of each segmented region sorted by time.

[0086] For example, historical production data, including features such as local waviness and local warping of each segment area, can be obtained from a database through distributed sensors (such as tension sensors, laser thickness gauges, and shape gauges) in the copper foil rolling production line.

[0087] S420 uses a Bayesian network trained on historical defect data. In this network, nodes represent segmented regions, edges represent dependencies between nodes, and edge weights represent defect propagation probabilities.

[0088] As can be understood, the structure of a Bayesian network is as follows: Nodes: Each segment region (e.g., R1-R10), and each node represents the defect state of a segment region (e.g., segment region S). i ∈{0,1}, 0 = no defects, 1 = defective); Edge: the dependency relationship between nodes, representing the probability of a defect propagating from one segment region to another. The direction of the edge is determined according to the process flow (e.g., from upstream segment region to downstream segment region, or based on spatial proximity); Edge weight: the probability of defect propagation P(S j =1∣S i =1), representing the conditional probability that segment region j also has a defect when segment region i has a defect. This can be calculated by statistically analyzing node pairs (S) in historical data. i S j ) calculate the edge weights from the joint probability distribution of ).

[0089] For example, historical defect data can be divided into a training set (80%) and a test set (20%), and the defect prediction accuracy (such as F1 score) of the initial Bayesian network on the test set can be calculated to determine the Bayesian network.

[0090] S430 updates the edge weights of the Bayesian network based on the local plate shape features to obtain the probability of defect propagation between each segment region.

[0091] For example, the edge weights of the Bayesian network can be updated based on the local plate shape features, and the updated edge weights can be determined as the probability of defect propagation between the segmented regions.

[0092] Through the above steps S410 to S430, interpretability modeling of defect propagation is performed using a dynamic Bayesian network driven by local features; dynamic adaptive prediction is achieved, which is beneficial for dealing with changes in working conditions during continuous production; and multi-source data fusion analysis is performed, which is beneficial for improving the accuracy of defect prediction and the efficiency of root cause location.

[0093] In one possible implementation, please refer to Figure 3 S500, based on the global plate shape characteristics and the characteristics of each local plate shape, obtains the defect influence coefficient of each segment region on the global plate shape, including: S510 calculates the global Moran index and the local Giselle index of each segmented region based on the global plate shape characteristics and the local plate shape characteristics.

[0094] For example, the global Moran index and local Giselle index of each segmented region can be calculated based on the global plate shape features and the local plate shape features. For example, the global Moran index I = [N ij (x i - (x) j - )] / [W x i - ) 2 The local Giselle index G of each segmented region i = x i -x j / 2N Where N is the number of segmented regions; w ij This is a spatial weight matrix (usually an adjacency matrix, where adjacent regions have a weight of 1, otherwise 0); x i x j Local plate shape characteristics (such as flatness, thickness deviation, etc.) of each segmented region; For global plate shape features; W= ij W is the total weight.

[0095] S520, based on the global Moran index and the local Giselle indices, yields the influence coefficients of each defect.

[0096] For example, the defect impact coefficient of each segmented region can be calculated based on the global Moran index and the local Giselle indices. For instance, the defect impact coefficient C of each segmented region... i =α I G i +β Where α and β are weighting coefficients, I is the global Moran exponent, and G... i λ is the local Giselle index for each segmented region, and μ is the adjustment coefficient.

[0097] By combining global and local indicators through the above steps S510 to S520, and simultaneously capturing global correlation and local discreteness, it is beneficial to improve the accuracy of defect area identification.

[0098] In one possible implementation, please refer to Figure 3 S300, based on the thickness of each segmented region, obtains the global plate shape features and the local plate shape features of each segmented region, including: S310, based on the thickness of each segment area, obtain the overall transverse thickness deviation and longitudinal thickness deviation of the copper foil.

[0099] For example, the sequence of lateral thickness deviation and the sequence of longitudinal thickness deviation of each segmented region can be obtained based on the thickness of each segmented region.

[0100] S320, the wavyity and warping are obtained based on the transverse thickness deviation and the longitudinal thickness deviation.

[0101] For example, the lateral thickness deviation sequence of each segmented region can be converted into a frequency domain signal using Fourier transform, the amplitude and wavelength of the dominant frequency component can be extracted, and the waviness can be calculated; for the longitudinal thickness deviation sequence of each segmented region, the warp can be obtained by fitting a quadratic curve of the thickness deviation sequence using the least squares method, for example, the quadratic curve d(x)=ax 2 +bx+c, warpage Q=∣a∣ L 2 1000 (μm), where L is the length of the copper foil.

[0102] Through the above steps S310 to 320, the refined extraction of local features, dynamic correction of edge effects, evaluation of wave-warping separation, and intelligent correction of regional coupling are beneficial to improving the quality of copper foil shape and the level of process control.

[0103] In one possible implementation, please refer to Figure 3 S300, local plate shape features include local waviness and local warping. Based on the thickness of each segment region, the global plate shape features and the local plate shape features of each segment region are obtained, including: S330 performs a Fourier transform on the thickness of each segmented region, extracts the main frequency amplitude and wavelength, and obtains the corresponding local waviness.

[0104] For example, the thickness obtained by multiple measurements of a certain segmented region can be Fourier transformed to convert the discrete thickness data into a frequency domain signal. The frequency component with the largest amplitude in the spectrum is selected as the main frequency, and the ratio of the main frequency amplitude to the average thickness is calculated to obtain the local waviness.

[0105] S340, calculate the corresponding thickness range and average thickness based on the thickness of each segment region to obtain the local warping.

[0106] For example, the thickness range and average thickness can be calculated based on the thickness of each segmented region, and the ratio of the thickness range to the average thickness can be determined as the local warpage of the corresponding segmented region.

[0107] By combining steps S330 to S340, along with waviness and warping, we can improve the accuracy of defect classification, adapt to complex working conditions, establish unified quantitative standards, and enhance the objectivity of assessment.

[0108] It should be understood that the sequence number of each step in the above embodiments does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application.

[0109] Corresponding to the copper foil rolling shape detection and dynamic control method described in the above embodiments, this application also provides a copper foil rolling shape detection and dynamic control device. Each module of the device can realize each step of the copper foil rolling shape detection and dynamic control method. Figure 5 The diagram shows a structural block diagram of the copper foil rolling sheet shape detection and dynamic control device provided in the embodiments of this application. For ease of explanation, only the parts related to the embodiments of this application are shown.

[0110] Reference Figure 5 The device includes: The segmented region module is used to divide the copper foil into multiple segmented regions along the rolling direction; The acquisition module is used to acquire the first control parameter and the thickness of each segmented region in real time; wherein, the first control parameter is used to control the rolling and detection of the copper foil; The plate shape feature module is used to obtain global plate shape features and local plate shape features of each segmented region based on the thickness of each segmented region; wherein, the global plate shape features include the overall waviness and warp of the copper foil, and the local plate shape features are used to reflect the shape features of each segmented region; The defect propagation probability module is used to obtain the defect propagation probability between each segmented region based on each of the local plate shape features. The defect influence coefficient module is used to obtain the defect influence coefficient of each segmented region on the global plate shape based on the global plate shape features and each of the local plate shape features; The contribution module is used to obtain the contribution of each segmented region based on the propagation probability of each defect and the influence coefficient of each defect. The key region module is used to sort the segmented regions according to their respective contributions to obtain multiple key regions; The second control parameter module is used to adjust the second control parameters for the next rolling process based on the first control parameters and the thickness of each of the key regions.

[0111] It should be noted that the information interaction and execution process between the above modules are based on the same concept as the method embodiments of this application. For details on their specific functions and technical effects, please refer to the method embodiments section, which will not be repeated here.

[0112] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional units and modules is merely an example. In practical applications, the above functions can be assigned to different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiments can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit. Furthermore, the specific names of the functional units and modules are only for easy differentiation and are not intended to limit the scope of protection of this application. The specific working process of the units and modules in the above device can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0113] This application also provides a copper foil rolling sheet shape detection and dynamic control device. Figure 6 This is a schematic diagram of the structure of a copper foil rolling sheet shape detection and dynamic control device provided in one embodiment of this application. Figure 6 As shown, the copper foil rolling sheet shape detection and dynamic control device 6 of this embodiment includes: at least one processor 60 ( Figure 6Only one is shown in the image), at least one memory 61 ( Figure 6 (Only one is shown in the image) and a computer program 62 stored in the at least one memory 61 and executable on the at least one processor 60. When the processor 60 executes the computer program 62, it causes the copper foil rolling shape detection and dynamic control device 6 to perform the steps in any of the above-described copper foil rolling shape detection and dynamic control method embodiments, or causes the copper foil rolling shape detection and dynamic control device 6 to perform the functions of each module / unit in the above-described device embodiments.

[0114] For example, the computer program 62 can be divided into one or more modules / units, which are stored in the memory 61 and executed by the processor 60 to complete this application. The one or more modules / units can be a series of computer program instruction segments capable of performing specific functions, which describe the execution process of the computer program 62 in the copper foil rolling shape detection and dynamic control equipment 6.

[0115] The copper foil rolling shape detection and dynamic control device 6 can be a desktop computer, laptop, handheld computer, or cloud server, etc. This copper foil rolling shape detection and dynamic control device may include, but is not limited to, a processor 60 and a memory 61. Those skilled in the art will understand that... Figure 6 This is merely an example of the copper foil rolling sheet shape detection and dynamic control device 6, and does not constitute a limitation on the copper foil rolling sheet shape detection and dynamic control device 6. It may include more or fewer components than shown, or combine certain components, or different components, such as input / output devices, network access devices, buses, etc.

[0116] The processor 60 can be a Central Processing Unit (CPU), or it can 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 can be a microprocessor or any conventional processor.

[0117] In some embodiments, the memory 61 can be an internal storage unit of the copper foil rolling shape detection and dynamic control device 6, such as a hard disk or memory of the copper foil rolling shape detection and dynamic control device 6. In other embodiments, the memory 61 can also be an external storage device of the copper foil rolling shape detection and dynamic control device 6, such as a plug-in hard disk, smart media card (SMC), secure digital (SD) card, flash card, etc., equipped on the copper foil rolling shape detection and dynamic control device 6. Further, the memory 61 can include both internal storage units and external storage devices of the copper foil rolling shape detection and dynamic control device 6. The memory 61 is used to store operating systems, applications, bootloaders, data, and other programs, such as the program code of the computer program. The memory 61 can also be used to temporarily store data that has been output or will be output.

[0118] This application also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps in any of the above method embodiments.

[0119] This application provides a computer program product that, when run on a copper foil rolling sheet shape detection and dynamic control device, enables the copper foil rolling sheet shape detection and dynamic control device to implement the steps in any of the above method embodiments.

[0120] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the methods of the above embodiments of this application can be implemented by a computer program instructing related hardware. 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 at least: any entity or device capable of carrying the computer program code to the copper foil rolling sheet shape detection and dynamic control equipment, a recording medium, 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. Examples include USB flash drives, portable hard drives, magnetic disks, or optical disks.

[0121] In the above embodiments, the descriptions of each embodiment have different focuses. For parts that are not described in detail or recorded in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0122] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. 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 implementation should not be considered beyond the scope of this application.

[0123] In the embodiments provided in this application, it should be understood that the disclosed copper foil rolling sheet shape detection and dynamic control equipment and method can be implemented in other ways. For example, the copper foil rolling sheet shape detection and dynamic control equipment embodiments described above are merely illustrative. For instance, the division of modules or units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the mutual coupling or direct coupling or communication connection shown or discussed may be indirect coupling or communication connection through some interfaces, devices, or units, and may be electrical, mechanical, or other forms.

[0124] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0125] The above-described embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application, and should all be included within the protection scope of this application.

Claims

1. A method for detecting and dynamically controlling the shape of rolled copper foil, characterized in that, include: The copper foil is divided into multiple segmented regions along the rolling direction; The first control parameter and the thickness of each segmented region are acquired in real time; wherein the first control parameter is used to control the rolling and inspection of the copper foil; The global plate shape features and the local plate shape features of each segmented region are obtained based on the thickness of each segmented region; wherein, the global plate shape features include the overall waviness and warpage of the copper foil, and the local plate shape features are used to reflect the shape features of each segmented region; The probability of defect propagation between the segmented regions is obtained based on the local plate shape features described above. The defect influence coefficient of each segmented region on the global plate shape is obtained based on the global plate shape features and the local plate shape features. The contribution of each segmented region is obtained based on the propagation probability of each defect and the influence coefficient of each defect. Based on the contribution level, the segmented regions are sorted to obtain multiple key regions; The second control parameter for the next rolling process is adjusted based on the first control parameter and the thickness of each of the key regions.

2. The method for detecting and dynamically controlling the shape of rolled copper foil as described in claim 1, characterized in that, The second control parameters include monitoring frequency, rolling speed, and / or rolling pressure; the second control parameters for adjusting the next rolling operation based on the first control parameters and the thickness of each of the key regions include: The first parameter range in the initial rolling stage, the second parameter range in the steady-state stage, and the third parameter range in the deceleration stage are determined based on the first control parameter. Each of the key regions is divided into multiple corresponding sub-regions; In the initial stage of rolling, the second control parameters of each sub-region are adjusted within the range of the first parameter according to the thickness of each sub-region; During the steady-state phase, the second control parameters of each of the key regions are adjusted within the range of the second parameters according to the thickness of each key region. During the deceleration phase, the second control parameter of each sub-region is adjusted within the range of the third parameter according to the thickness of each sub-region.

3. The method for detecting and dynamically controlling the shape of rolled copper foil as described in claim 2, characterized in that, In the initial stage of rolling, adjusting the second control parameters of each sub-region within the first parameter range based on the thickness of each sub-region includes: In the initial stage of rolling, the weight of the sub-region located at the edge of the copper foil is increased; Within the first parameter range, a first parameter value and a first adjustment priority are obtained based on the weight of each sub-region and the corresponding thickness; The second control parameters of each sub-region are adjusted according to the first parameter value and the first adjustment priority.

4. The method for detecting and dynamically controlling the shape of rolled copper foil as described in claim 2, characterized in that, In the steady-state phase, adjusting the second control parameters of each key region within the range of the second parameter based on the thickness of each key region includes: If the contribution of the key area is greater than the preset threshold, then within the range of the second parameter, the second parameter value is obtained according to the corresponding thickness; Adjust the second control parameter according to the second parameter value; If the contribution of the key region is less than or equal to the preset threshold, then the second parameter range is adjusted according to the corresponding thickness to obtain the first parameter range; Adjust the second control parameter according to the first parameter range.

5. The method for detecting and dynamically controlling the shape of rolled copper foil as described in claim 2, characterized in that, During the deceleration phase, adjusting the second control parameters of each sub-region within the range of the third parameter based on the thickness of each sub-region includes: During the deceleration phase, the weight of the sub-region located in the middle of the copper foil is increased; Within the range of the third parameter, the value of the third parameter and the second adjustment priority are obtained according to the weight of each sub-region and the corresponding thickness; The second control parameters of each sub-region are adjusted according to the third parameter value and the second adjustment priority.

6. The method for detecting and dynamically controlling the shape of rolled copper foil as described in claim 1, characterized in that, The step of obtaining the defect propagation probability between each segmented region based on each of the local plate shape features includes: Acquire historical defect data; wherein, the historical defect data includes historical local features of each of the segmented regions; A Bayesian network is trained based on the historical defect data; wherein, the nodes of the Bayesian network refer to each segmented region, the edges of the Bayesian network refer to the dependencies between nodes, and the edge weights of the Bayesian network refer to the defect propagation probability. The edge weights of the Bayesian network are updated based on the local plate shape features to obtain the defect propagation probability between the segmented regions.

7. The method for detecting and dynamically controlling the shape of rolled copper foil as described in claim 1, characterized in that, The step of obtaining the defect influence coefficient of each segmented region on the global plate shape based on the global plate shape features and each of the local plate shape features includes: The global Moran index and the local Giselle index of each segmented region are calculated based on the global plate shape features and the local plate shape features. The defect influence coefficients are obtained based on the global Moran index and each of the local Giselle indices.

8. The method for detecting and dynamically controlling the shape of rolled copper foil as described in claim 1, characterized in that, The step of obtaining the global plate shape feature and the local plate shape feature of each segmented region based on the thickness of each segmented region includes: The overall transverse wavyity of the copper foil is obtained based on the thickness of each segment region; The warpage of the copper foil in the longitudinal direction is obtained based on the thickness of each segment region.

9. The method for detecting and dynamically controlling the shape of rolled copper foil as described in claim 1, characterized in that, The local plate shape features include local waviness and local warping; obtaining the global plate shape features and the local plate shape features of each segmented region based on the thickness of each segmented region further includes: Perform a Fourier transform on the thickness of each segmented region, extract the main frequency amplitude and wavelength, and obtain the corresponding local waviness. The local warpage is obtained by calculating the corresponding thickness range and average thickness based on the thickness of each segmented region.

10. A copper foil rolling sheet shape detection and dynamic control device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the method as described in any one of claims 1 to 9.

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