An optimization method for the process parameters of aluminum foil rolling of pop cans

Abstract

The present invention relates to the technical field of rolling optimization, and specifically includes an optimization method for the rolling process parameters of aluminum foil for cans, which includes: optimizing the rolling of aluminum foil for cans: setting the rolling speed and pressure to ensure uniform thickness and smooth surface; adjusting the parameters through multiple rounds of rolling to establish a joint optimization cycle; introducing microwave and electromagnetic heating, and synergistically iteratively optimizing rolling and heating to obtain the optimal parameter combination, solving the technical problem that the non-uniform distribution of the aluminum foil thickness and the decline of the surface quality during the production process of cans are directly caused by the limited control accuracy of key parameters such as temperature and pressure, thereby affecting the overall quality of the can products, realizing the synergistic iterative optimization of rolling and multi-stage heating, carrying out refined control on the rolling process parameters of aluminum foil for cans, significantly improving the thickness uniformity and surface smoothness of aluminum foil for cans, and providing technical effects to support the overall improvement of the quality of can products.

Description

Technical Field

[0001] The present invention relates to the technical field related to rolling optimization, and particularly relates to a method for optimizing the rolling process parameters of aluminum foil for beverage cans. Background Art

[0002] The rolling process of aluminum foil for beverage cans is an important link in aluminum processing, directly affecting the quality of beverage can products, such as thickness uniformity, surface finish, and the forming performance of the final product. Conventional aluminum foil rolling processes often rely on empirical function adjustment. First, small differences in aluminum foil thickness may cause a series of problems during beverage can manufacturing, such as uneven can body strength and decreased sealing performance, thereby affecting the overall quality of beverage can products. Second, due to the inaccuracy of parameter adjustment and the difficulty of process control, it is difficult to ensure the absolute smoothness of the aluminum foil surface, and defects such as scratches are likely to occur. At the same time, with the continuous improvement of the quality requirements for beverage can products and the increasing demand for production efficiency, the limitations of conventional aluminum foil rolling processes have gradually emerged.

[0003] In summary, in the prior art, there are technical problems that due to the limited control accuracy of key parameters such as temperature and pressure, it directly leads to non-uniform distribution of aluminum foil thickness and a decrease in surface quality during the production of beverage cans, thereby affecting the overall quality of beverage can products. Summary of the Invention

[0004] The present application provides a method for optimizing the rolling process parameters of aluminum foil for beverage cans, aiming to solve the technical problems in the prior art that due to the limited control accuracy of key parameters such as temperature and pressure, it directly leads to non-uniform distribution of aluminum foil thickness and a decrease in surface quality during the production of beverage cans, thereby affecting the overall quality of beverage can products.

[0005] In view of the above problems, the technical solution of the present application is as follows:

[0006] The present application provides a method for optimizing the rolling process parameters of aluminum foil for beverage cans. The method includes: determining the rolling indexes of aluminum foil for beverage cans based on the rolling process of aluminum foil for beverage cans, where the rolling indexes of aluminum foil for beverage cans include rolling speed and rolling pressure; reading the quality specifications of aluminum foil for beverage cans and setting the quality indexes of beverage cans, where the quality indexes of beverage cans include thickness uniformity and surface finish; based on the rolling indexes of aluminum foil for beverage cans, after removing the surface oxide layer from the raw materials for rolling aluminum foil for beverage cans, connecting a rolling mill for primary rolling configuration to obtain a first set of rolling parameters, where the first set of rolling parameters includes the single-roll speed, single-roll pressure, and single-roll gap corresponding to N columns of rolling rollers; through the rolling mill, performing M rounds of rolling repeatedly and clamping the rolling rollers successively to collect a second set of rolling parameters, a third set of rolling parameters,..., and an Mth set of rolling parameters; based on the first set of rolling parameters, the second set of rolling parameters, the third set of rolling parameters,..., and the Mth set of rolling parameters, establishing a combined optimization cycle of rolling parameters corresponding to the N columns of rolling rollers; based on the combined optimization cycle of rolling parameters, introducing an internal microwave heating process and an external electromagnetic induction heating process, and combining the quality indexes of beverage cans to perform collaborative iterative optimization of multi-stage heating and M rounds of rolling to obtain an optimal parameter combination.

[0007] In summary, one or more technical solutions provided in the present application solve the technical problem that the non-uniform distribution of the aluminum foil thickness and the decline of the surface quality during the production process of beverage cans are directly caused by the limited control accuracy of key parameters such as temperature and pressure, thereby affecting the overall quality of beverage can products. It realizes the collaborative iterative optimization of rolling and multi-stage heating, finely controls the rolling process parameters of aluminum foil for beverage cans, significantly improves the thickness uniformity and surface finish of aluminum foil for beverage cans, and provides technical support for comprehensively improving the quality of beverage can products. BRIEF DESCRIPTION OF THE DRAWINGS

[0008] Figure 1 It is a schematic flow chart of a method for optimizing the rolling process parameters of aluminum foil for beverage cans provided by the present application.

[0009] Figure 2 It is a schematic flow chart of the loop jump of the nested loop in a method for optimizing the rolling process parameters of aluminum foil for beverage cans provided by the present application. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0010] The present application will be specifically described below with reference to the accompanying drawings. As Figure 1 shown, the present application provides a method for optimizing the rolling process parameters of aluminum foil for beverage cans. The method includes:

[0011] S1: Based on the rolling process of aluminum foil for beverage cans, determine the rolling indexes of aluminum foil for beverage cans, where the rolling indexes of aluminum foil for beverage cans include rolling speed and rolling pressure.

[0012] In the rolling process of aluminum foil for cans, the rolling speed and rolling pressure are two crucial rolling indicators that directly affect the finished product quality and production efficiency of aluminum foil. Among them, the rolling speed is an important parameter in the aluminum foil rolling process, directly affecting the production efficiency and surface quality of aluminum foil. Further, the higher the rolling speed, the greater the amount of aluminum foil produced per unit time, thus improving the production efficiency. However, the choice of rolling speed is not the higher the better, and the comprehensive influence of other factors also needs to be considered; too fast rolling speed may cause fine bubbles and patterns on the aluminum foil surface, affecting the surface finish. Therefore, when choosing the rolling speed, it is necessary to balance the relationship between production efficiency and surface quality. Generally speaking, the maximum speed of the roughing mill can reach 1800m / min - 2000m / min, the medium rolling mill can reach 1500m / min, while the finishing mill should not exceed 1200m / min; there is a speed effect in the aluminum foil rolling process, that is, the thickness of the foil material becomes thinner as the rolling speed increases, which is caused by the change of the friction state between the work roll and the rolling material and the temperature rise in the rolling deformation zone. Therefore, corresponding measures need to be taken to control the thickness of aluminum foil during high-speed rolling.

[0013] The rolling pressure is another key parameter in the aluminum foil rolling process, directly affecting the thickness uniformity and surface quality of aluminum foil. Further, too small rolling pressure will lead to uneven thickness of aluminum foil and defects such as wavy patterns; while too large pressure has a certain probability of making the aluminum foil surface rough and increasing brittleness. Therefore, it is necessary to select an appropriate rolling pressure to ensure the thickness uniformity of aluminum foil; the rolling pressure also has a significant impact on the surface quality of aluminum foil; a reasonable rolling pressure will make the aluminum foil surface more flat and smooth; during the aluminum foil rolling process, the rolling pressure needs to be adjusted in real time according to factors such as the thickness, width and rolling speed of the aluminum foil. Modern aluminum foil rolling mills are usually equipped with advanced automatic control systems to achieve precise control of the rolling pressure.

[0014] To sum up, the rolling speed and rolling pressure in the rolling process of aluminum foil for cans are two interrelated and crucial parameters. In actual production, it is necessary to select appropriate rolling speed and rolling pressure according to specific conditions to ensure the finished product quality and production efficiency of aluminum foil. At the same time, other factors in the rolling process, such as temperature, lubrication, etc., also need to be concerned to ensure the smooth progress of the rolling process.

[0015] S2: Read the quality specifications of aluminum foil for cans and set the quality indicators of cans. The quality indicators of cans include thickness uniformity and surface finish.

[0016] The quality specifications of aluminum foil for beverage cans usually include multiple aspects. Among them, thickness uniformity and surface finish are two important quality indicators. Further, the thickness of the aluminum foil for beverage cans needs to be precisely controlled to ensure its stability and durability during use. Generally speaking, the thickness tolerance of the aluminum foil for beverage cans will vary according to specific application requirements and manufacturing processes. For example, in some occasions with high requirements, the thickness tolerance is controlled within ±0.005 mm. The specific thickness range will also be determined according to the use of the aluminum foil and the design requirements of the beverage can. For example, for the commonly used 5052 aluminum sheet and 3104 aluminum sheet for beverage can lids, their thickness is usually between 0.208 mm and 0.360 mm. During the production process, various detection means are used to monitor the thickness uniformity of the aluminum foil. For example, high-precision measuring tools are used to measure the thickness of the aluminum foil at multiple points to ensure that it maintains a consistent thickness in the entire width and length directions.

[0017] Specifically, the surface finish of the aluminum foil for beverage cans is usually measured by surface roughness. Surface roughness refers to the number and degree of tiny protrusions and depressions on the surface of the aluminum foil, and is commonly represented by the Ra value (arithmetic mean deviation of the profile). Generally speaking, the surface roughness of the aluminum foil for beverage cans needs to be controlled within a certain range to ensure its surface is flat and smooth. The specific Ra value range will vary according to the use of the aluminum foil and the manufacturing process. For example, for some aluminum foils for beverage cans, the required Ra value range is between 0.38 μm and 0.64 μm. There should be no obvious defects on the surface of the aluminum foil for beverage cans, such as cracks, scratches, bubbles, missed coating, corrosion, oil stains, peeling, stripes, color differences, mottles, roll marks, periodic ripples, etc. Surface defects will affect the appearance quality and use performance of the aluminum foil. Commonly, in order to improve the surface finish and subsequent processing performance of the aluminum foil for beverage cans, the surface of the aluminum foil is usually pre-treated. For example, a uniform pre-coating oil is applied to protect the surface of the aluminum foil from corrosion and contamination, and to improve its lubricity and workability.

[0018] To sum up, the quality indicators of the aluminum foil for beverage cans include two aspects: thickness uniformity and surface finish. Thickness uniformity and surface finish jointly determine the finished product quality and use performance of the aluminum foil for beverage cans. In actual production, corresponding quality specifications and detection standards need to be formulated according to specific application requirements and manufacturing processes to ensure that the quality of the aluminum foil for beverage cans meets the requirements.

[0019] S3: Based on the rolling indexes of the aluminum foil for beverage cans, after removing the surface oxide layer from the raw materials for beverage can rolling, connect a rolling mill for primary rolling configuration to obtain a first set of rolling parameters. The first set of rolling parameters includes the single-roll speed, single-roll pressure, and single-roll gap corresponding to N columns of rolling rollers.

[0020] In the production process of aluminum foil for cans, the rolling process of aluminum foil for cans is a key link, directly affecting the finished product quality of the aluminum foil. Further refine the rolling process, and after removing the oxide layer on the surface of the raw material, carry out the configuration and parameter acquisition of primary rolling. Specifically, first, select the raw materials for rolling aluminum foil for cans that meet the requirements; removing the oxide layer on the surface of the raw material is crucial for ensuring the subsequent processing performance and finished product quality of the aluminum foil. Common methods for removing the oxide layer include chemical cleaning, mechanical grinding, electrochemical polishing, etc.

[0021] Connect the processed raw materials to the rolling mill for rolling. The rolling mill is the core equipment for aluminum foil rolling, and its performance stability and accuracy directly affect the rolling quality of the aluminum foil. Further, before rolling, it is necessary to configure the primary rolling of the rolling mill according to the rolling index and raw material characteristics, including adjusting parameters such as the rolling force, rolling speed, and roll gap of the rolling mill to ensure the smooth progress of the rolling process and the finished product quality of the aluminum foil; during the primary rolling process, monitor and record the rolling parameters in real time to obtain the first set of rolling parameters, providing strong support for the subsequent rolling process optimization and quality control.

[0022] The first set of rolling parameters includes the single-roll speed, single-roll pressure, and single-roll gap corresponding to N columns of rolling rollers. Specifically, the single-roll speed refers to the rotational speed of each column of rollers on the rolling mill during the rolling process. The speeds of different columns of rollers need to be adjusted according to the rolling process and aluminum foil characteristics to ensure the uniformity and stability of rolling; the single-roll pressure refers to the pressure exerted by each column of rollers on the aluminum foil on the rolling mill. The single-roll pressure needs to be adjusted according to parameters such as the thickness, width, and rolling speed of the aluminum foil to ensure that the aluminum foil can deform uniformly during the rolling process and reach the required thickness and surface quality; the single-roll gap refers to the gap between adjacent columns of rollers on the rolling mill. The size of the single-roll gap will affect the deformation degree and surface quality of the aluminum foil during the rolling process. Therefore, during the rolling process, it is necessary to finely adjust the roll gap according to the actual situation.

[0023] S4: Through the rolling mill, repeatedly roll M rounds and clamp the rolling rollers successively to collect the second set of rolling parameters, the third set of rolling parameters,..., the Mth set of rolling parameters.

[0024] Perform multiple rounds of rolling to further process the aluminum foil. At the same time, gradually adjust the rolling parameters to achieve the required thickness and surface quality. Specifically, repeatedly roll the aluminum foil through the rolling mill, and the number of rounds is recorded as M. Each round of rolling is a further processing of the aluminum foil, making its thickness gradually decrease and the surface quality gradually improve; before each round of rolling, it is necessary to make necessary adjustments to the rolling parameters according to the results of the previous round of rolling and the current state of the aluminum foil. The adjusted corresponding rolling parameters include but are not limited to the rolling speed, rolling pressure, and roll gap.

[0025] Subsequently, the rolling rollers are clamped successively. As the number of rolling passes increases, the thickness of the aluminum foil gradually decreases. Therefore, it is necessary to clamp the rolling rollers successively to reduce the roll gap, ensuring that the aluminum foil can pass through the rollers evenly and stably and reach the required thickness. At the same time, the process of clamping the rolling rollers needs to be precisely controlled to avoid excessive pressure on the aluminum foil or uneven rolling. Further, during each rolling pass, the corresponding rolling parameters are collected and recorded to form the second rolling parameter set, the third rolling parameter set, …, the Mth rolling parameter set. The second rolling parameter set, the third rolling parameter set, …, the Mth rolling parameter set all include key parameters such as the speed, pressure, and gap of the rolling rollers during each rolling pass. By comparing and analyzing the rolling parameters of different passes, the key factors affecting the quality of the aluminum foil are identified, and the rolling process is improved accordingly.

[0026] Specifically, the specific value of M depends on the initial thickness, target thickness of the aluminum foil, and the requirements of the rolling process. In actual production, the value of M needs to be determined according to specific circumstances. Before and during each rolling pass, fine adjustments need to be made to the rolling parameters. The corresponding adjustments are based on the results of the previous rolling pass and the current state of the aluminum foil, aiming to ensure that the aluminum foil can pass through the rollers evenly and stably and reach the required thickness and surface quality. As the number of rolling passes increases and the thickness of the aluminum foil decreases, it is necessary to clamp the rolling rollers successively to reduce the roll gap. The process of clamping the rolling rollers successively needs to be precisely controlled to ensure the stability of rolling and the quality of the aluminum foil.

[0027] By repeatedly rolling M times and successively clamping the rolling rollers, the aluminum foil is gradually processed to the required thickness and surface quality. At the same time, the parameter sets of each rolling pass are collected and recorded to provide support for subsequent analysis and optimization of the rolling process. In actual production, it is necessary to precisely control the number of rolling passes, rolling parameters, and the clamping degree of the rolling rollers according to specific circumstances to ensure the finished product quality of the aluminum foil for beverage cans.

[0028] S5: Based on the first rolling parameter set, the second rolling parameter set, the third rolling parameter set, …, the Mth rolling parameter set, establish a combined optimization cycle for the rolling parameters corresponding to the N columns of rolling rollers.

[0029] Perform detailed data analysis and comparison on each collected rolling parameter set (the first to the Mth rolling parameter set); the analysis content includes the change trends of key parameters such as rolling speed, rolling pressure, and roll gap, as well as the influence on quality indicators such as the thickness and surface finish of the aluminum foil. Through data analysis, identify the key rolling parameters that have the greatest impact on the quality of the aluminum foil, and the change trends of the parameters in different rolling passes. For example, it is found that as the number of rolling passes increases, it is necessary to gradually reduce the roll gap to maintain uniform rolling of the aluminum foil.

[0030] Based on the results of data analysis, a combined optimization model of rolling parameters corresponding to N columns of rolling rollers is established. The combined optimization model of rolling parameters needs to comprehensively consider all key rolling parameters, as well as the interactions and influences between parameters, so as to obtain the optimal combination of rolling parameters. In the combined optimization model of rolling parameters, optimization algorithms (such as genetic algorithm, particle swarm optimization algorithm, etc.) are introduced to search for the optimal solution, and the optimal combination of rolling parameters that can optimize the aluminum foil quality indicators (such as thickness uniformity, surface finish) can be found through iterative calculation within the given parameter range.

[0031] When establishing the combined optimization model of rolling parameters, it is necessary to clarify the optimization objectives (such as maximizing thickness uniformity, minimizing surface roughness, etc.) and constraint conditions (such as the range of rolling speed, the limit of rolling pressure, etc.). The objectives and constraints will guide the search process of the optimization algorithm to ensure that the solution found meets both the quality requirements and the actual production conditions.

[0032] Embed the established combined optimization model into the rolling process to form a combined optimization cycle of rolling parameters. Before each round of rolling, use the optimization model to calculate the optimal combination of rolling parameters for the current round, and adjust the settings of the rolling mill to apply the optimal combination of rolling parameters for the current round. During the rolling process, monitor the quality of the aluminum foil and the changes in rolling parameters in real time, and make adjustments as needed. At the same time, collect a new set of rolling parameters as the input data for the next round of optimization. The combined optimization cycle of rolling parameters is a continuous process. With the accumulation of production experience and data, the optimization model is continuously optimized and improved, and the accuracy and efficiency of the optimization algorithm are improved, thereby further improving the finished product quality of the aluminum foil.

[0033] By establishing a combined optimization cycle of rolling parameters corresponding to N columns of rolling rollers based on multiple sets of rolling parameters, the fine control and optimization of the rolling process of aluminum foil for cans are realized. While ensuring the quality of aluminum foil for cans and improving production efficiency, in actual production, it is necessary to closely monitor the changes in rolling parameters and make timely adjustments and optimizations as needed.

[0034] S6: Based on the combined optimization cycle of rolling parameters, introduce an internal microwave heating process and an external electromagnetic induction heating process, and combine the quality indicators of the cans to carry out collaborative iterative optimization of multi-stage heating and M rounds of rolling to obtain the optimal parameter combination.

[0035] Based on the combined optimization cycle of rolling parameters, an internal microwave heating process and an external electromagnetic induction heating process are introduced. Among them, internal microwave heating is to heat the inside of the aluminum foil by microwave radiation during the rolling process. The internal microwave heating method can quickly and evenly increase the temperature of the aluminum foil, which helps to improve its plasticity and workability, and reduce stress concentration and crack generation during rolling. External electromagnetic induction heating is to heat the surface of the aluminum foil using the principle of electromagnetic induction. The external electromagnetic induction heating method can precisely control the heating area and temperature, which helps to improve the surface finish of the aluminum foil and reduce the formation of the oxide layer.

[0036] Integrate the internal microwave heating and external electromagnetic induction heating processes into the combined optimization cycle of rolling parameters. Before or during each round of rolling, adjust the heating parameters (such as heating time, heating temperature, heating area, etc.) according to the current state of the aluminum foil and the rolling parameters to achieve the best synergistic effect between heating and rolling. By real-time monitoring the changes in the quality of the aluminum foil and the rolling parameters, conduct multi-stage collaborative iteration of heating and rolling. Each round of iteration adjusts and optimizes the parameters based on the results of the previous round to gradually approach the optimal parameter combination.

[0037] During the collaborative iteration process, always take the quality indicators of the aluminum can (such as thickness uniformity, surface finish, etc.) as feedback signals. By measuring and analyzing the changes in the quality indicators of the aluminum can, evaluate the effect of the current heating and rolling parameter combination, and use this as a guide for the next round of iterative optimization. After multiple rounds of collaborative iterative optimization, gradually converge to a set of optimal heating and rolling parameter combinations. The optimal parameter combination can maximize the processing efficiency on the premise of ensuring the quality of the aluminum can aluminum foil. Further, verify the optimal parameter combination in the actual production environment to ensure its effectiveness and stability in practical applications. If any deviation or problem is found, adjust and optimize the parameters in a timely manner to ensure the smooth progress of the production process and the stable improvement of the aluminum foil quality.

[0038] By introducing the internal microwave heating and external electromagnetic induction heating processes and combining them with the combined optimization cycle of rolling parameters, conduct multi-stage collaborative iterative optimization of heating and M rounds of rolling, effectively improving the processing efficiency and finished product quality of the aluminum can aluminum foil.

[0039] Furthermore, based on the combined optimization cycle of the rolling parameters, introduce the internal microwave heating process and the external electromagnetic induction heating process, combine the quality indicators of the aluminum can, conduct multi-stage collaborative iterative optimization of heating and M rounds of rolling, and obtain the optimal parameter combination. The method of this application includes:

[0040] Connect to the temperature real-time feedback control unit. The temperature real-time feedback control unit uses a PID controller and interacts with an infrared thermometer via the Internet of Things protocol. Based on the internal microwave heating process and the external electromagnetic induction heating process, a fuzzy logic algorithm is used to perform smooth control of multi-stage heating. During the process of performing smooth control of multi-stage heating, a machine learning model is adopted to predict the temperature change trend, and combined with the quality indicators of the aluminum can, a power adjustment instruction is issued. The power adjustment instruction is used to activate the temperature real-time feedback control unit.

[0041] Connect to the temperature real-time feedback control unit. The temperature real-time feedback control unit is equipped with a PID controller and conducts data interaction with an infrared thermometer through the Internet of Things protocol. The PID controller can automatically adjust the heating power based on the current temperature deviation to ensure that the temperature is stable within the set range. Introduce the internal microwave heating process and the external electromagnetic induction heating process. During the rolling process of the aluminum foil of the aluminum can, the internal microwave heating process and the external electromagnetic induction heating process are used to control the temperature of the material to ensure that the material remains in an ideal state at different processing stages. Use the fuzzy logic algorithm to handle the uncertainties in the heating process, making the heating control more flexible and smooth, and ensuring that the temperature change meets the expectations.

[0042] Adopt a machine learning model to predict the temperature change trend over time based on historical data, calculate the corresponding temperature fluctuations in advance, so as to adjust the heating power in a timely manner. Comprehensively consider the quality indicators of the aluminum foil of the aluminum can, such as thickness uniformity and surface finish, to ensure that while optimizing the parameters, the product quality is guaranteed. According to the prediction results of the machine learning model and the quality indicators of the aluminum can, a power adjustment instruction will be automatically issued. The power adjustment instruction is used to activate the temperature real-time feedback control unit, that is, the PID controller, to adjust the heating power and maintain precise control of the heating process.

[0043] Through continuous iteration, while adjusting the heating parameters and rolling parameters, the coordinated optimization of multi-stage heating and M-round rolling is realized. The process of coordinated optimization will continue until the optimal parameter combination that can meet all the quality indicators of the aluminum foil of the aluminum can is found. After multiple iterations and optimizations, a set of parameters will be determined, which can not only ensure the efficient operation of the heating and rolling processes, but also ensure that the aluminum foil of the aluminum can has the best physical properties and product quality.

[0044] By introducing the temperature real-time feedback control unit, PID controller, Internet of Things protocol, fuzzy logic algorithm and machine learning model, it is possible to predict the temperature change trend based on real-time data and perform dynamic adjustment in combination with quality indicators, realizing precise control and optimization of the heating and rolling processes of the aluminum foil of the aluminum can.

[0045] Furthermore, the method of this application includes:

[0046] A thickness detection sensor is introduced, and the thickness detection sensor is used to measure the thickness of the aluminum foil rolling blank in real time; based on the thickness of the aluminum foil rolling blank, an adaptive control algorithm is used to dynamically adjust the single-roll gap of the N columns of rolling rollers controlled by the servo motor, synchronously capture the thickness change of the aluminum foil rolling blank, and perform thickness uniformity control for M rounds of rolling.

[0047] Furthermore, the method of the present application includes:

[0048] The servo motor performs synchronous correction of timing information according to the response time corresponding to the thickness detection sensor and the dynamic characteristics of the servo system.

[0049] A thickness detection sensor is introduced. The thickness detection sensor is installed at a key position on the aluminum foil rolling production line. The thickness detection sensor can monitor the thickness of the aluminum foil during the rolling process in real time and immediately feedback the actual thickness data of the aluminum foil; at the beginning, the aluminum foil rolling blank is a cube, and after M rounds of rolling, aluminum foil for cans is obtained. The thickness detection sensor continuously collects the thickness data of the aluminum foil, and the thickness data of the aluminum foil will be used in subsequent control algorithms to adjust the rolling parameters, so as to achieve precise control of the thickness.

[0050] Based on the collected thickness data, an adaptive control algorithm is used to dynamically adjust the single-roll gap of the N columns of rolling rollers controlled by the servo motor. As the thickness of the aluminum foil changes, the distance between each roller is automatically adjusted to compensate for the thickness difference and maintain the consistency of the overall thickness; further, the timing information of the servo motor is synchronously corrected. In order to ensure that the data of the thickness detection sensor can be reflected in the control of the servo motor in a timely manner, the servo motor needs to perform synchronous correction of timing information according to the response time of the sensor and its own dynamic characteristics (including the acceleration and deceleration of the motor and the inertia of mechanical transmission components, etc.), ensuring the timeliness and accuracy of the control signal and avoiding control errors caused by signal delay or system response time differences.

[0051] During the entire M-round rolling process, the thickness of the aluminum foil will be continuously collected to ensure the thickness uniformity of the aluminum foil. Each thickness detection result will trigger an adjustment of the servo motor. Through continuous feedback and control, the thickness consistency of the aluminum foil after multiple rounds of rolling is achieved. The data feedback of the thickness detection sensor is compared with the preset thickness standard to optimize the roll gap until the aluminum foil thickness meets the requirements.

[0052] Introducing a thickness detection sensor and an adaptive control algorithm, combined with the precise control of the servo motor, significantly improves the thickness uniformity of the aluminum foil rolling blank for cans, captures the change of the aluminum foil thickness in real time, and dynamically adjusts the rolling parameters to ensure that the quality of the aluminum foil finished product meets the production requirements.

[0053] Furthermore, to synchronously capture the thickness change of the aluminum foil rolling die blank and control the thickness uniformity during M-round rolling, the method of this application further includes:

[0054] Based on the thickness change of the aluminum foil rolling die blank, generate a first collaborative cycle corresponding to the internal microwave heating process; based on the thickness change of the aluminum foil rolling die blank, generate a second collaborative cycle corresponding to the external electromagnetic induction heating process; use the rolling parameter joint optimization cycle as the outer cycle, and use the first collaborative cycle corresponding to the internal microwave heating process and the second collaborative cycle corresponding to the external electromagnetic induction heating process as the inner cycle to establish a nested cycle, and use the nested cycle to perform collaborative iterative optimization of multi-stage heating and M-round rolling to obtain the optimal parameter combination.

[0055] According to the thickness change of the aluminum foil rolling die blank, generate a first collaborative cycle associated with the internal microwave heating process, which involves analyzing the influence of internal microwave heating on the internal temperature of the material, forming a temperature distribution map, and based on this, establishing a first parameter space. In the first parameter space, search by maximizing the quality grade of the aluminum can and the energy consumption utilization rate to determine the best combination of internal microwave heating (such as microwave power) and rolling.

[0056] Similarly, by monitoring the thickness change of the aluminum foil rolling die blank and dynamically adjusting the parameters of electromagnetic induction heating (such as current intensity, heating frequency, etc.) using a control algorithm, generate a second collaborative cycle associated with the external electromagnetic induction heating process to achieve precise control of the aluminum foil heating process. The second collaborative cycle tends to the synergistic effect of heating and rolling, but focuses on the influence of the external heat source on the material surface; regard the rolling parameter joint optimization cycle as the outer cycle, while the first collaborative cycle (internal microwave heating) and the second collaborative cycle (external electromagnetic induction heating) are used as the inner cycle, nested within the outer cycle, to establish a nested cycle. The nested cycle structure allows optimization of heating and rolling parameters at different levels.

[0057] Using nested loops, start the collaborative iterative optimization of multi-stage heating and M-round rolling. Further, before or during each round of rolling, the heating and rolling parameters are dynamically adjusted according to the real-time data of the aluminum foil thickness and the heating effect. Through continuous collaborative iterative optimization, the heating and rolling parameters are fine-tuned until the optimal parameter combination that can simultaneously meet the requirements of thickness uniformity, surface finish, and production efficiency is found. This step involves a large amount of data collection, simulation runs, and actual tests to ensure the effectiveness and reliability of the parameters. After finding a set of feasible parameter combinations, regular feedback and adjustment are also required to cope with the influence of factors such as material property changes and equipment aging, ensuring stability and consistency during the long-term production process. Establish a collaborative cycle corresponding to the internal microwave heating process and the external electromagnetic induction heating process to achieve precise control of multi-stage heating and M-round rolling during the rolling process of aluminum cans for aluminum foil.

[0058] Furthermore, based on the thickness change of the aluminum foil rolling die blank, a first collaborative cycle corresponding to the internal microwave heating process is generated. The method of the present application includes:

[0059] Based on the internal microwave heating process, generate an internal temperature distribution map of the aluminum foil rolling die blank; based on the internal temperature distribution map of the aluminum foil rolling die blank, the first rolling parameter set, the second rolling parameter set, the third rolling parameter set,..., the Mth rolling parameter set corresponding to M-round rolling, establish a first parameter space; based on the first parameter space, search with the maximized aluminum can quality grade and energy consumption utilization rate, and establish the first collaborative cycle.

[0060] Heat the aluminum foil rolling die blank through the internal microwave heating process. At the same time, use an infrared thermometer to monitor the temperature of the die blank in real time, collect temperature data, and the collected temperature data will be used to generate an internal temperature distribution map of the aluminum foil rolling die blank, which reflects the temperature changes at different positions and time points.

[0061] Based on the internal temperature distribution map and the first rolling parameter set, the second rolling parameter set up to the Mth rolling parameter set collected during M-round rolling, construct a parameter space. The first parameter space includes all parameters related to the rolling process, such as the roller speed, pressure, gap, etc. during each round of rolling, and parameters related to the internal microwave heating process, such as heating power, time, and frequency, etc.

[0062] Within the first parameter space, with the optimization goal of maximizing the quality grade of the aluminum can and the energy consumption utilization rate, based on the set optimization goal, search for the best parameter combination that can achieve the goal within the first parameter space. Usually, with the help of mathematical optimization algorithms, such as genetic algorithms, particle swarm optimization algorithms, or simulated annealing algorithms, etc., search the parameter space to find the parameter set that maximizes the objective function (the quality grade of the aluminum can and the energy consumption utilization rate); iterate repeatedly until a satisfactory solution is found or the predetermined number of iterations is reached.

[0063] Based on the search results corresponding to the first parameter space, establish the first collaborative loop. The first collaborative loop tightly links the internal microwave heating process, the internal temperature distribution map of the aluminum foil rolling blank, and the rolling parameter set of multiple rounds of rolling to form a closed-loop control system; during the loop process, according to the real-time monitored internal temperature distribution of the aluminum foil rolling blank and the data feedback during the rolling process, dynamically adjust the internal microwave heating parameters and rolling parameters, aiming to maintain the uniformity of the internal temperature distribution of the aluminum foil rolling blank, while optimizing the rolling effect to achieve the goal of maximizing the quality grade of the aluminum can and the energy consumption utilization rate; through continuous iteration and optimization, the first collaborative loop will gradually approach the optimal solution and realize an efficient and stable aluminum can aluminum foil rolling process in actual production.

[0064] Even if the expected effect is achieved, it is still necessary to regularly monitor factors such as the equipment status and raw material properties on the production line, because changes in factors such as the equipment status and raw material properties on the production line will affect the effectiveness of the parameters. Therefore, it is necessary to establish a continuous improvement mechanism to regularly re-evaluate and adjust the parameters to maintain the high efficiency of the aluminum foil rolling production line and product quality, realizing the deep collaboration between the internal microwave heating process and the aluminum foil rolling process.

[0065] Furthermore, as Figure 2 shown, taking the rolling parameter joint optimization loop as the outer loop, and taking the first collaborative loop corresponding to the internal microwave heating process and the second collaborative loop corresponding to the external electromagnetic induction heating process as the inner loop, establish a nested loop. The method of this application further includes:

[0066] Using fluid dynamics simulation technology, construct an aluminum foil rolling blank simulation model by comparing the single-row roller speed and single-row roller pressure corresponding to N rows of rolling rollers; based on the aluminum foil rolling blank simulation model, identify the thickness defect characteristics and surface defect characteristics, and the defect types corresponding to the surface defect characteristics include cracks and corrugations; based on the thickness defect characteristics and surface defect characteristics, with the thickness uniformity and surface finish in the aluminum can quality index as constraints and the acceleration of the production rate as the goal, perform loop jumps with multi-level branch pruning on the nested loop.

[0067] Set up the simulation environment. Further, select software suitable for hydrodynamic simulation, such as ANSYS Fluent, COMSOL Multiphysics, etc.; based on the geometric dimensions of the N-column rolling rollers and the single-column roller, establish a 3D model in CAD software and import it into the simulation software; define the physical properties of materials such as aluminum foil and rollers, such as density, elastic modulus, Poisson's ratio, thermal conductivity, etc.; set boundary conditions. Further, according to the speed of the single-column roller, set the linear velocity of the roller surface; according to the pressure of the single-column roller, set the contact pressure of the roller on the aluminum foil; define the fluid domain between the aluminum foil and the roller, considering the plastic deformation of the aluminum foil and the hydrodynamic effect; perform a fine mesh division on the roller, aluminum foil, and fluid domain to ensure the accuracy of the simulation results; run the aluminum foil rolling die blank simulation model and observe the deformation, temperature distribution, stress distribution, etc. during the aluminum foil rolling process.

[0068] Extract data such as the thickness distribution and surface topography of the aluminum foil from the simulation results; identify the thickness defect characteristics and surface defect characteristics. Further, by comparing the thicknesses of different regions of the aluminum foil, identify the regions with uneven thickness; the defect types corresponding to the surface defect characteristics include cracks and ripples. Among them, detect the regions of surface stress concentration or sudden changes. It can be known from theoretical analysis that the regions of surface stress concentration or sudden changes are the starting points of cracks; analyze the surface topography data and identify periodic or irregular fluctuations.

[0069] Take the thickness uniformity (the thickness of the aluminum foil fluctuates within the allowable range) and surface finish (reduce or eliminate surface defects such as cracks and ripples) in the quality indicators of the aluminum can as the constraint conditions. The goal is to accelerate the production rate while meeting these quality standards. Further, analyze each link in the rolling process, identify the steps for parallel processing or optimization, and perform loop jumps with multi-level branch cuts on the nested loop.

[0070] During the actual application process, continuously adjust and optimize the strategy, including updating the simulation model parameters, adjusting the structure and parameters of the nested loop, to adapt to the changes in the production environment, and continuously improve the product quality and production efficiency. Through the above steps, systematically optimize the rolling process of the aluminum foil for aluminum cans, ensure that the obtained aluminum foil for aluminum cans meets strict quality standards, and at the same time, ensure the production efficiency.

[0071] Furthermore, taking the thickness uniformity and surface finish in the quality indicators of the aluminum can as constraints and aiming to accelerate the production rate, perform loop jumps with multi-level branch cuts on the nested loop. The method of this application includes:

[0072] Based on the first parameter space, a multi-layer branch structure is established; in the multi-layer branch structure, in each layer of branches, taking the thickness uniformity and surface finish in the quality indicators of the aluminum can as constraints and aiming at accelerating the production rate, single-layer branch pruning is carried out; after completing the single-layer branch pruning, traverse the multi-layer branches and perform depth-first search and breadth-first exploration in sequence, and perform multi-layer branch pruning on the nested loop; the multi-layer branch pruning is associated with the nested loop jump logic one by one.

[0073] According to the key parameters (such as rolling pressure, speed, temperature, etc.) and corresponding operating variables in the aluminum can production process, a multi-layer branch structure is constructed. Each layer represents a decision point or parameter adjustment point and contains multiple branches. Each branch represents different parameter settings or operating choices; in each layer of the multi-layer branch structure, the following steps are performed for single-layer branch pruning: Clearly take the thickness uniformity and surface finish of the aluminum can as constraint conditions, which means that any branch that does not meet these quality standards will be pruned, and only the combinations that can meet the requirements of thickness uniformity and surface finish will be retained; with the main goal of accelerating the production rate, among the branches that meet the quality constraints, evaluate the impact of each branch on the production rate, and select the branch with the highest probability of increasing the production rate for retention; according to the above analysis and evaluation, prune the branches that do not meet the quality constraints or are not conducive to increasing the production rate.

[0074] After completing the single-layer branch pruning, it is necessary to traverse the entire multi-layer branch structure and perform further multi-layer branch pruning on the remaining branches, performing depth-first search and breadth-first exploration in sequence. Further, the depth-first search means starting from the root node and searching as deep as possible along a branch until reaching a leaf node or meeting a certain stop condition (such as reaching the maximum depth, finding a solution that meets all conditions, etc.); during the depth-first search process, further evaluate the branches retained in each layer, and prune the branches that do not meet the final goal as needed; the breadth-first exploration is different from the depth-first search. The breadth-first search will first explore all branches in the same layer and then go deeper into the next layer. During the breadth-first search process, it is easier to see the impact of different parameter combinations on the production rate and the quality of the aluminum can, so as to make a more comprehensive decision. However, due to the large amount of calculation involved in the breadth-first search, it is necessary to make a trade-off according to the specific situation in practical applications.

[0075] The multi-layer branch pruning is associated with the nested loop jump logic one by one. Further, in terms of logical association, the process of multi-layer branch pruning is actually an optimization of the nested loop. In the nested loop, each layer of the loop is regarded as one layer in the multi-layer branch structure. By pruning the branches that do not meet the conditions, it is actually skipping those invalid loop iterations, thereby accelerating the entire production process. For the jump logic, during the multi-layer branch pruning process, when encountering a branch that does not meet the quality constraint or is not conducive to improving the production rate, a jump logic is set to directly skip that branch and all its subsequent sub-branches, which is equivalent to exiting the inner loop in advance in the nested loop and adjusting the iteration of the outer loop according to the conditions. By gradually refining and screening the parameter space and combining the search strategies of depth and width, the production quality and efficiency of the aluminum foil for beverage cans are effectively balanced.

[0076] After multiple rounds of pruning and exploration, the optimized multi-layer branch structure and jump logic are applied to actual production. According to the feedback of actual production data, the multi-layer branch structure and jump logic are continuously adjusted and optimized to ensure the stability and efficiency of the production process.

[0077] In summary, the beneficial effects of the embodiments of this application are as follows:

[0078] 1. By introducing an automated parameter optimization loop and combining internal microwave heating and external electromagnetic induction heating, precise control of parameters such as temperature, pressure, and speed is achieved, thereby improving the thickness uniformity and surface finish of the aluminum foil.

[0079] 2. Using modern sensing technologies such as a temperature real-time feedback control unit and a thickness detection sensor, and an adaptive control algorithm, the intelligence of the production process is realized, and the production rate and stability are greatly improved.

[0080] 3. The collaborative iterative optimization of multi-stage heating and M-round rolling, as well as defect identification and optimization based on a simulation model, can effectively reduce energy consumption and at the same time reduce resource waste caused by unqualified quality.

[0081] 4. Since a multi-layer branch structure is established based on the first parameter space; in the multi-layer branch structure, in each layer of the branch, the thickness uniformity and surface finish in the quality index of the beverage can are used as constraints, and the production rate is accelerated as the goal, and single-layer branch pruning is performed; after completing the single-layer branch pruning, traverse the multi-layer branches and perform depth-first search and breadth-first exploration in turn to perform multi-layer branch pruning on the nested loop; the multi-layer branch pruning is associated with the nested loop jump logic one by one. By gradually refining and screening the parameter space and combining the search strategies of depth and width, the production quality and efficiency of the aluminum foil for beverage cans are effectively balanced.

[0082] In summary, any step can be stored as computer instructions or programs in an unrestricted computer memory and can be called and recognized by an unrestricted computer processor, without any additional restrictions here.

[0083] Furthermore, the above technical solutions only represent the preferred technical solutions of the technical solutions of the embodiments of the present application. Some changes that those skilled in the art may make to some parts thereof all reflect the principles of the embodiments of the present application. Obviously, those skilled in the art can make various changes and modifications to the present application without departing from the scope of the present application.

Claims

1. A method for optimizing rolling process parameters of aluminum foil for cans, characterized in that: The method comprises: Based on the rolling process of aluminum foil for cans, determining rolling indicators of aluminum foil for cans, wherein the rolling indicators of aluminum foil for cans include rolling speed and rolling pressure; Read the quality specification of aluminum foil for cans and set the quality index of cans, wherein the quality index of cans includes thickness uniformity and surface finish; Based on the rolling index of the aluminum foil of the can, after the surface oxide layer of the rolling raw material of the can is removed, the rolling mill is connected to perform primary rolling configuration to obtain a first rolling parameter set, wherein the first rolling parameter set includes a single-row roller speed, a single-row roller pressure, and a single-row roller gap corresponding to N rows of rolling rollers; By means of the rolling mill, M rounds of rolling are repeatedly performed and rolling rollers are clamped successively, and a second rolling parameter set, a third rolling parameter set, ..., an Mth rolling parameter set are collected; According to the first rolling parameter set, the second rolling parameter set, the third rolling parameter set, ..., the Mth rolling parameter set, a rolling parameter joint optimization cycle corresponding to the N rows of rolling rollers is established; Based on the rolling parameter joint optimization cycle, an internal microwave heating process and an external electromagnetic induction heating process are introduced, and combined with the can quality index, a collaborative iterative optimization of multi-stage heating and M-round rolling is carried out to obtain the optimal parameter combination.

2. The method for optimizing rolling process parameters of aluminum foil for cans according to claim 1, characterized in that: Based on the rolling parameter joint optimization cycle, an internal microwave heating process and an external electromagnetic induction heating process are introduced, and combined with the can quality index, a collaborative iterative optimization of multi-stage heating and M-round rolling is performed to obtain an optimal parameter combination. The method includes: Connecting a temperature real-time feedback control unit, wherein the temperature real-time feedback control unit uses a PID controller to interact with the infrared thermometer using an Internet of Things protocol; Based on the internal microwave heating process and the external electromagnetic induction heating process, a fuzzy logic algorithm is used to smoothly control the multi-stage heating; In the process of smooth control of multi-stage heating, a machine learning model is used to predict the temperature change trend, and combined with the can quality index, a power adjustment instruction is issued, and the power adjustment instruction is used to activate the temperature real-time feedback control unit.

3. The method for optimizing rolling process parameters of aluminum foil for cans according to claim 2, characterized in that: The method comprises: A thickness detection sensor is introduced, and the thickness detection sensor is used to measure the thickness of the aluminum foil rolling mold base in real time; Based on the thickness of the aluminum foil rolling mold, an adaptive control algorithm is used to dynamically adjust the gap between the single-row rollers of the N-row rolling rollers controlled by the servo motor, synchronously capture the thickness change of the aluminum foil rolling mold, and perform thickness uniformity control of the M-round rolling.

4. The method for optimizing rolling process parameters of aluminum foil for cans according to claim 3, characterized in that: The servo motor performs synchronous correction of timing information based on the response time corresponding to the thickness detection sensor and the dynamic characteristics of the servo system.

5. The method for optimizing rolling process parameters of aluminum foil for cans according to claim 3, characterized in that: Synchronously capturing the thickness change of the aluminum foil rolling mold base and performing thickness uniformity control of M-round rolling, the method further includes: generating a first coordinated cycle corresponding to the internal microwave heating process based on a thickness change of the aluminum foil rolling mold base; Based on the thickness change of the aluminum foil rolling mold base, generating a second coordinated cycle corresponding to the external electromagnetic induction heating process; The rolling parameter joint optimization loop is used as the outer loop, and the first collaborative loop corresponding to the internal microwave heating process and the second collaborative loop corresponding to the external electromagnetic induction heating process are used as the inner loop to establish a nested loop. The nested loop is used to perform collaborative iterative optimization of multi-stage heating and M-round rolling to obtain the optimal parameter combination.

6. A method for optimizing rolling process parameters of aluminum foil for cans as claimed in claim 5, characterized in that: Based on the thickness change of the aluminum foil rolling mold base, generating a first coordinated cycle corresponding to the internal microwave heating process, the method comprising: Based on the internal microwave heating process, generating an internal temperature distribution map of the aluminum foil rolling mold base; Based on the internal temperature distribution map of the aluminum foil rolling mold base, the first rolling parameter set, the second rolling parameter set, the third rolling parameter set, ..., the Mth rolling parameter set corresponding to M rounds of rolling, a first parameter space is established; Based on the first parameter space, a search is performed with the maximized can quality grade and energy utilization rate, and the first collaborative cycle is established.

7. A method for optimizing rolling process parameters of aluminum foil for cans as claimed in claim 6, characterized in that: The rolling parameter joint optimization loop is used as an outer loop, and the first cooperative loop corresponding to the internal microwave heating process and the second cooperative loop corresponding to the external electromagnetic induction heating process are used as inner loops to establish a nested loop, and the method further includes: Using fluid dynamics simulation technology, the simulation model of aluminum foil rolling die was constructed by comparing the single-row roller speed and single-row roller pressure corresponding to N rows of rolling rollers; Based on the aluminum foil rolling die simulation model, thickness defect characteristics and surface defect characteristics are identified, and the defect types corresponding to the surface defect characteristics include cracks and ripples; Based on the thickness defect characteristics and surface defect characteristics, the thickness uniformity and surface finish of the can quality indicators are used as constraints, and the nested loops are subjected to loop jumps with multi-layer branch pruning with the goal of accelerating the production rate.

8. The method for optimizing rolling process parameters of aluminum foil for cans according to claim 7, characterized in that: Taking thickness uniformity and surface finish of the can quality index as constraints and accelerating the production rate as the goal, the nested loop is subjected to loop jump of multi-layer branch pruning, and the method comprises: Based on the first parameter space, establishing a multi-layer branch architecture; In the multi-layer branch architecture, in each layer of branches, the thickness uniformity and surface finish of the can quality indicators are used as constraints, and single-layer branch cutting is performed with the goal of accelerating the production rate; After completing the single-layer branch pruning, traverse the multi-layer branches and perform depth-first search and breadth-first exploration in sequence to perform multi-layer branch pruning on the nested loop; The multi-layer branch pruning is associated one-to-one with the nested loop jump logic.

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