A method for controlling the roughness of a rolled surface of a laser-textured work roll of a four-high aluminum cold rolling mill

Abstract

The application relates to a kind of four-roll aluminum cold rolling mill laser texturing work roll rolling surface roughness control method, it is characterized in that: step S1: before production, different specifications aluminum strip and aluminum strip roller are rolled, and roughness mapping relationship model of rolling force-time is established;Step S2: the rolling reduction of aluminum strip is simulated and optimized using finite element, and dynamic adjustment is carried out in combination with real-time thickness monitoring;Step S3: according to the shape change of aluminum strip and the adjustment of bending force of associated database;Stable tension is maintained through tension sensor;Material and equipment performance are combined to optimize rolling speed;Step S4: through the real-time monitoring of each parameter and the collaborative control model, ensure that the surface roughness of aluminum strip meets the predetermined requirements.The present application ensures that the surface roughness of the produced strip meets the predetermined requirements by optimizing and adjusting the key parameters such as calibration rolling force, calibration time, reduction, bending, tension and rolling speed in the production process.

Description

Technical fields: This invention relates to the field of aluminum cold rolling technology, and in particular to a method for controlling the surface roughness of laser-textured work rolls in a four-roll aluminum cold rolling mill. Background technology: In aluminum cold rolling production, the surface roughness of the strip has a significant impact on its subsequent applications; for example, applications such as electronic device housings and packaging materials have strict requirements for the surface roughness of aluminum strip. Laser texturing work rolls have been widely used in aluminum cold rolling mills to improve the surface quality of the strip. However, in actual production, even if the roll roughness and the initial condition of the rolling equipment are qualified, ensuring that the surface roughness of the produced strip meets the requirements still faces many challenges. Summary of the Invention: In view of the shortcomings of the prior art, the purpose of this invention is to provide a method for controlling the surface roughness of the laser texturing work rolls in a four-roll aluminum cold rolling mill. Without considering the grinding process and the original quality of the rolls, the method ensures that the surface roughness of the produced strip meets the predetermined requirements by optimizing and adjusting key parameters such as the calibrated rolling force, calibration time, reduction amount, roll bending, tension, and rolling speed during the production process.

[0001] This invention discloses a method for controlling the surface roughness of laser-textured work rolls in a four-roll aluminum cold rolling mill, characterized in that: Step S1: Before production, conduct rolling tests on aluminum strips and aluminum strip rolls of different specifications to establish a rolling force-time-roughness mapping model; Step S2: Optimize the aluminum strip rolling reduction using finite element simulation and make dynamic adjustments in conjunction with real-time thickness monitoring; Step S3: Adjust the bending roll force based on the changes in aluminum strip shape and the associated database; maintain stable tension using a tension sensor; optimize the rolling speed by combining material properties and equipment performance; Step S4: Through real-time monitoring and collaborative control models of various parameters, ensure that the surface roughness of the aluminum strip is stable and meets the predetermined requirements.

[0002] Furthermore, in step 1, before production, rolling force, time, and surface roughness data are recorded through multiple rolling tests for aluminum strips and aluminum strip rolls of different specifications, thereby constructing a mapping relationship model. In actual production, the model is queried according to the target roughness, and the initial rolling force and time parameters are set. The hydraulic system of the aluminum strip rolls is automatically adjusted when the rolling force fluctuates by more than ±50kN to ensure that the parameters are stable within the set range.

[0003] Furthermore, step 2, based on the aluminum strip material, initial thickness, and target thickness, uses finite element simulation software to analyze the influence of different reduction amounts on deformation, stress distribution, and roughness, in order to select the optimal reduction amount for aluminum strip rolling. During the rolling process, the reduction device is precisely controlled, and the strip thickness is monitored in real time. When the deviation exceeds ±0.01mm, the reduction amount is dynamically fine-tuned. At the same time, the chain effect on rolling force and speed is comprehensively considered to carry out coordinated optimization.

[0004] Furthermore, in step 3, the bending roller force is monitored in real time by a bending roller force sensor, and the bending roller force is adjusted in combination with the changes in the shape of the aluminum strip. A database relating bending roller force, strip shape, and roughness is established. Based on the real-time measurement results of the surface quality of the aluminum strip, the optimal adjustment strategy is matched from the database to ensure that the strip shape is improved without affecting the roughness.

[0005] Furthermore, in step 3, the initial tension is set according to the specifications of the aluminum strip. The tension sensors of the uncoiler and coiler are used for real-time monitoring. When deviation occurs and tension fluctuations occur, the motor speed is adjusted to maintain the tension within the range of 80kN±5kN. In other words, by optimizing the tension balance, the flatness of the strip and the risk of tensile deformation are reduced, and abnormal roughness caused by tension instability is avoided.

[0006] Furthermore, step 3 combines the material, roll wear, and equipment performance to determine the initial rolling speed, monitors the surface quality of the aluminum strip in real time, and dynamically adjusts the rolling speed when uneven roughness occurs.

[0007] Furthermore, step 4 uses the established parameter association model and database to monitor and dynamically adjust rolling force, reduction, bending force, tension, and speed parameters in real time. When a parameter fluctuates, the system automatically triggers the collaborative optimization of associated parameters to quickly adapt to production changes caused by material differences and equipment fluctuations, thereby achieving precise control of surface roughness throughout the entire process.

[0008] Advantages of this invention: The control method of this invention enables comprehensive and systematic optimization and adjustment of key parameters in the rolling process based on the default roll roughness and rolling equipment. This effectively improves the control accuracy of strip surface roughness, ensuring that the surface roughness of the produced strip consistently meets predetermined requirements, thereby improving product quality and satisfying the stringent surface quality requirements of aluminum strip in different application fields.

[0009] The method of this invention is based on real-time monitoring and dynamic adjustment of various parameters, which can quickly adapt to various changes in the production process, such as slight differences in strip material and fluctuations in equipment operation. This improves the stability and reliability of the production process, reduces the scrap rate, lowers production costs, and improves the production efficiency and economic benefits of enterprises.

[0010] The established parameter correlation models and databases provide data support and decision-making basis for optimizing the aluminum cold rolling production process, which helps enterprises achieve intelligent production management and promotes technological progress in the aluminum cold rolling industry. Detailed implementation method:

[0011] The detailed scheme of the method for controlling the surface roughness of the laser texturing work rolls in a four-roll aluminum cold rolling mill according to the present invention is as follows: 1. Calibrate rolling force and calibration time. Before production, for aluminum strips and rolls of different specifications, multiple rolling tests are conducted under standard rolling conditions using pressure sensors and timers. The curve of rolling force versus time and the corresponding surface roughness measurement value of the strip are recorded in each test. Through data analysis, a mapping relationship model of rolling force-time-roughness is established. For example, for a certain type of aluminum strip with a thickness of 0.5mm, when the rolling force is F1, after time t1, the surface roughness of the strip is Ra1; when the rolling force is F2, after time t2, the surface roughness of the strip is Ra2, and so on, obtaining multiple sets of data points to construct the model.

[0012] 2. Reduction Optimization: Based on the material characteristics, initial thickness, and target thickness of the aluminum strip, and combined with the equipment parameters of the rolling mill, finite element simulation software is used to simulate and analyze the rolling process under different reduction amounts, predicting the deformation, internal stress distribution, and final surface roughness of the strip under various reduction conditions. For example, for a specific aluminum alloy strip, the simulation results show that when the reduction amount is Δh1, the surface roughness of the strip is relatively uniform and meets the requirements; when the reduction amount is Δh2, local roughness anomalies may occur on the surface of the strip.

[0013] In actual production, a suitable reduction amount is selected based on the simulation results. During the rolling process, the reduction amount is precisely controlled by the rolling mill's reduction device, and the thickness change of the strip is monitored in real time. If the actual thickness of the strip is found to deviate from the target thickness beyond the allowable range, the reduction amount is finely adjusted in time. At the same time, the impact of the reduction amount adjustment on other parameters such as rolling force and rolling speed is considered, and comprehensive optimization is carried out to ensure the stability of the strip surface roughness.

[0014] 3. Bending Roll Adjustment: During the rolling mill operation, bending roll force sensors monitor the magnitude of the bending roll force in real time. Based on the strip width, thickness, and changes in strip shape during rolling, the bending roll force is adjusted through the mill's bending roll control system. For example, when strip exhibits shape defects such as central or edge waviness, the bending roll force is appropriately increased or decreased to improve the strip shape. Simultaneously, research has found that changes in bending roll force have a certain impact on the strip surface roughness; therefore, when adjusting the bending roll force, the real-time measurement results of the strip surface roughness must be considered comprehensively.

[0015] 4. Establish a correlation database of bending roll force, strip shape, and surface roughness: By collecting and analyzing a large amount of production data, summarize the relationship between bending roll force and strip surface roughness under different working conditions. In actual production, based on the strip shape and surface roughness requirements, query the database to determine a suitable bending roll force adjustment strategy to achieve indirect control of strip surface roughness.

[0016] 5. Tension Adjustment: Based on the material, specifications, and rolling process requirements of the aluminum strip, set appropriate initial tension on the uncoiler and coiler. During the rolling process, use tension sensors to monitor the tension changes of the strip in real time. If the tension fluctuates, adjust the motor speed of the uncoiler and coiler to keep the strip tension stable. For example, if the strip deviates during the rolling process, it may cause tension changes. Adjust the tension in time to avoid adverse effects on the surface roughness of the strip due to unstable tension.

[0017] This study investigates the variation of strip surface roughness under different tension conditions. Through experiments and production practice, it was found that appropriately increasing the tension can improve the surface smoothness of the strip to a certain extent, thereby affecting the surface roughness. However, excessive tension may lead to problems such as tensile deformation of the strip, which in turn affects the surface quality. Therefore, in actual production, the tension should be optimized and adjusted according to the specific conditions of the strip to achieve effective control of the strip surface roughness.

[0018] 6. Rolling Speed ​​Optimization: Based on the material of the aluminum strip, the wear condition of the rolls, and the performance limitations of the rolling equipment, combined with other parameters such as rolling force and reduction, a suitable rolling speed range is determined through theoretical calculations and experimental verification. During the rolling process, the operating status of the rolling mill and the surface quality of the strip are monitored in real time. If abnormal surface roughness is found, such as uneven roughness or roughness exceeding the allowable range, the rolling speed is adjusted appropriately. For example, when defects such as local scratches appear on the strip surface, the rolling speed is reduced, and it is observed whether the defects are improved. At the same time, the impact of rolling speed adjustment on other parameters is analyzed, and comprehensive optimization is carried out.

[0019] Establish a coordinated control model for rolling speed and other parameters (such as rolling force and rolling oil parameters). In actual production, based on the real-time quality of the strip and process requirements, use this model to synchronously adjust the rolling speed and other related parameters to ensure stable control of the strip surface roughness while maintaining production efficiency.

[0020] Example 1 - Rolling of aluminum strip for the casing of a certain type of electronic device: Rolling force and time calibration: For this type of aluminum strip with a thickness of 0.3 mm and a width of 1000 mm, laser texturing work rolls with a surface roughness conforming to the standard were selected. Ten sets of rolling tests were conducted under standard rolling conditions, and the rolling force, time, and strip surface roughness of each set of tests were recorded. For example, in the first set of tests, the rolling force was set to 1000 kN, the rolling time was 120 s, and the measured strip surface roughness was Ra 0.8 μm; in the second set of tests, the rolling force was 1100 kN, the rolling time was 110 s, and the strip surface roughness was Ra 0.75 μm. Through fitting analysis of these data, a rolling force-time-roughness mapping model suitable for this specification of strip was established. In actual production, the target strip surface roughness requirement is Ra0.7-0.8μm. According to the model, the appropriate rolling force setting value is 1050kN, and the expected rolling time is 115s. During the rolling process, the rolling force is monitored in real time by a pressure sensor. When the rolling force fluctuation range exceeds ±50kN, the hydraulic system of the rolling mill is automatically adjusted to restore the rolling force to about 1050kN. At the same time, the rolling time is precisely controlled by a timer to ensure that the rolling process is completed in about 115s.

[0021] Reduction Optimization: The rolling process of the strip under different reduction amounts was simulated using finite element simulation software. The simulation results showed that when the reduction amount was 0.08 mm, the strip deformation was uniform and the surface roughness met the requirements. In actual production, the reduction amount was precisely set to 0.08 mm using the rolling mill's reduction device, and the strip thickness was monitored in real time using a thickness gauge during the rolling process. If the actual strip thickness deviated from the target thickness (0.3 mm) by more than ±0.01 mm, the reduction amount was finely adjusted according to the direction and magnitude of the deviation. For example, when the actual strip thickness was 0.31 mm, the reduction amount was appropriately increased; when the actual strip thickness was 0.29 mm, the reduction amount was appropriately decreased. At the same time, the impact of the reduction amount adjustment on the rolling force and rolling speed was comprehensively considered for coordinated optimization.

[0022] Bending roll adjustment: During the rolling process, bending roll force sensors are used to monitor the bending roll force in real time. When slight waviness is detected in the strip, the bending roll force is appropriately increased through the mill's bending roll control system, from the initial 150kN to 180kN. Simultaneously, based on the established bending roll force-strip shape-surface roughness correlation database and combined with real-time measurement results of the strip surface roughness, it is ensured that the bending roll force adjustment will not adversely affect the strip surface roughness. In this rolling process, the strip surface roughness remained within the target range after the bending roll force adjustment.

[0023] Tension adjustment: Based on the strip specifications and rolling process requirements, the initial tension is set to 80kN on the uncoiler and coiler. During the rolling process, the strip tension is monitored in real time using a tension sensor. When slight deviation of the strip causes tension fluctuations, the motor speeds of the uncoiler and coiler are adjusted to maintain the strip tension within the range of 80kN±5kN. By optimizing the tension adjustment, the stability of the strip during the rolling process is ensured, which plays a positive role in controlling the surface roughness of the strip.

[0024] Rolling speed optimization: Based on the strip material, roll wear, and other parameters, the initial rolling speed was determined to be 100 m / min. During the rolling process, the surface quality of the strip was monitored in real time. When slight unevenness in the surface roughness of the strip was detected, the rolling speed was reduced to 90 m / min, and the change in surface quality was observed. After a period of operation, the unevenness in the surface roughness of the strip was improved. At the same time, based on the collaborative control model of rolling speed and other parameters, the rolling force, rolling oil parameters, etc., were simultaneously fine-tuned to ensure the stability of the entire rolling process and that the surface roughness of the strip met the requirements. After the parameter optimization and adjustment in this embodiment, the surface roughness of the produced strip was stabilized between Ra0.72-0.78 μm, which fully meets the surface roughness requirements of aluminum strip for electronic device housings.

[0025] Example 2 – Rolling of aluminum strip for food packaging: Rolling force and time calibration: For aluminum strip with a thickness of 0.2 mm and a width of 800 mm used in food packaging, multiple rolling tests were conducted under standard rolling conditions to establish a rolling force-time-roughness mapping model. In actual production, the target strip surface roughness requirement is Ra0.5-0.6 μm. Based on the model, the rolling force setting was determined to be 800 kN, and the expected rolling time was 90 s. During the rolling process, the rolling force and time were strictly controlled according to the set values ​​to ensure the accuracy of the rolling process.

[0026] Reduction optimization: A suitable reduction of 0.06 mm was determined through finite element simulation. In actual rolling, the reduction is precisely controlled and fine-tuned based on real-time monitoring results of the strip thickness. For example, when the strip thickness fluctuates, the reduction is adjusted in a timely manner to ensure that the strip thickness tolerance is within ±0.008 mm, while also taking into account the impact on the surface roughness of the strip.

[0027] Bending roll adjustment: During the rolling process, the bending roll force is adjusted according to the changes in strip shape. When the strip has edge waviness, the bending roll force is appropriately reduced from the initial 120kN to 100kN. By referring to the bending roll force-strip shape-surface roughness correlation database, it is ensured that the bending roll force adjustment will not lead to the deterioration of the strip surface roughness.

[0028] Tension adjustment: The initial tension is set to 60kN, and the tension is monitored and adjusted in real time by a tension sensor during the rolling process to ensure that the tension fluctuation range is within ±4kN. Reasonable tension adjustment can improve the flatness of the strip during the rolling process and help control the surface roughness.

[0029] Rolling speed optimization: The initial rolling speed was set to 80 m / min. During the rolling process, if any abnormalities were found in the surface quality of the strip, such as the roughness exceeding the target range, the rolling speed was adjusted according to the actual situation and optimized in conjunction with other parameters. After a series of parameter optimization adjustments, the surface roughness of the produced aluminum strip for food packaging was stabilized between Ra0.53 and 0.58 μm, which met the requirements of food packaging for the surface roughness of aluminum strip.

[0030] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit them; although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications can still be made to the specific implementation of the present invention or equivalent substitutions can be made to some technical features without departing from the spirit of the technical solutions of the present invention, and all such modifications and substitutions should be covered within the scope of the technical solutions claimed in the present invention.

Claims

1. A method for controlling the surface roughness of laser-textured work rolls in a four-roll aluminum cold rolling mill, characterized in that: Step S1: Before production, conduct rolling tests on aluminum strips and aluminum strip rolls of different specifications to establish a rolling force-time-roughness mapping model; Step S2: Optimize the aluminum strip rolling reduction using finite element simulation and make dynamic adjustments in conjunction with real-time thickness monitoring; Step S3: Adjust the bending roll force based on the changes in aluminum strip shape and the associated database; maintain stable tension using a tension sensor; optimize the rolling speed by combining material properties and equipment performance; Step S4: Through real-time monitoring and collaborative control models of various parameters, ensure that the surface roughness of the aluminum strip is stable and meets the predetermined requirements; In step S1, before production, rolling force, time, and surface roughness data are recorded through multiple rolling tests for aluminum strips and aluminum strip rolls of different specifications, in order to construct a mapping relationship model. In actual production, the model is queried according to the target roughness, the initial rolling force and time parameters are set, and the pressure sensor and timer are used for real-time monitoring. When the rolling force fluctuates beyond ±50kN, the hydraulic system of the aluminum strip rolls is automatically adjusted to ensure that the parameters are stable within the set range. Step S2 is based on the aluminum strip material, initial thickness, and target thickness. Finite element simulation software is used to analyze the influence of different reduction amounts on deformation, stress distribution, and roughness to select the optimal reduction amount for aluminum strip rolling. During the rolling process, the reduction device is precisely controlled, and the strip thickness is monitored in real time. When the deviation exceeds ±0.01mm, the reduction amount is dynamically fine-tuned. At the same time, the chain effect on rolling force and speed is comprehensively considered to carry out coordinated optimization. Step S3 involves real-time monitoring of the force value using a bending roller force sensor, adjusting the bending roller force in conjunction with changes in the aluminum strip shape, and establishing a database linking bending roller force, strip shape, and roughness. Based on real-time measurements of the aluminum strip surface quality, the optimal adjustment strategy is matched from the database to ensure that the strip shape is improved without affecting the roughness. Step 3 sets the initial tension according to the aluminum strip specifications and monitors it in real-time using tension sensors on the uncoiler and coiler. When deviation causes tension fluctuations, the motor speed is adjusted to maintain the tension within the range of 80kN±5kN. This optimizes the tension balance between strip flatness and the risk of tensile deformation, avoiding roughness abnormalities caused by tension instability. Step S3 combines material properties, roll wear, and equipment performance to determine the initial rolling speed, monitors the surface quality of the aluminum strip in real time, and dynamically adjusts the rolling speed when uneven roughness occurs. Step S4 uses the established parameter association model and database to monitor and dynamically adjust rolling force, reduction, bending force, tension, and speed parameters in real time. When a parameter fluctuates, the system automatically triggers the collaborative optimization of associated parameters to quickly adapt to production changes caused by material differences and equipment fluctuations, thereby achieving precise control of surface roughness throughout the entire process.