A method for eliminating edge cracks of ultra-thin copper strip

Abstract

The present invention discloses a method for eliminating edge cracks of ultra-thin copper strip. Aiming at the problem of edge cracks in the production of ultra-thin copper strip, the present invention proposes an efficient elimination method, and the process includes: a multi-annealing process to balance the internal stress of the ingot and optimize the material properties; using machine vision technology to accurately determine the crack position and automatically cut and remove the defective area; local edge heating treatment; and dynamically adjusting the rolling speed according to the measured edge stress during the rolling process to prevent cracks and optimize the production rate. This method significantly reduces the risk of strip breakage and raw material waste, and improves the product qualification rate and production efficiency.

Description

Technical Field

[0001] The present invention relates to the field of copper strip production, and particularly to a method for eliminating edge cracks of ultra-thin copper strips. Background Art

[0002] Ultra-thin copper strips are high-precision and high-performance metal materials, mainly characterized by a very thin thickness, usually referring to copper alloy plates or strips with a thickness between 0.05 mm and 0.1 mm. Due to their unique physical and chemical properties and good workability, such materials have a wide range of applications in multiple fields such as electronics, communication, electrical appliances, new energy, precision instruments, and aerospace.

[0003] When the copper strip casting blank is melted and cast into a mold, due to factors such as stress, cracks will exist at the edges. The cracks will cause the ultra-thin copper strip to break during the rolling process and make the upper and lower rollers come into direct contact, causing greater damage to the rolling mill. The current solution is to uniformly cut off a part of both sides of the entire copper strip casting blank and then perform rolling. This method causes a large loss of casting blank raw materials, greatly increases the production cost, and still cannot completely solve the problem of strip breakage caused by cracks at the edges of the raw materials. Summary of the Invention

[0004] To solve the above technical problems, a method for eliminating edge cracks of ultra-thin copper strips adopted by the present invention includes the following steps:

[0005] S1: Perform multiple annealing treatments on the initial copper strip casting blank;

[0006] The multiple annealing method includes:

[0007] Preheating stage: Slowly heat the above copper strip casting blank to a preset value lower than the recrystallization temperature to make the internal stress of the copper strip casting blank evenly distributed;

[0008] First-stage annealing: Continue to heat the copper strip casting blank to a first preset temperature, and the first preset temperature is 650 °C. This temperature is sufficient to restore the lattice distortion generated during the cold working process, promote the re-growth of grains, thereby reducing the material hardness, improving the plasticity, and maintaining this temperature for 20 - 30 minutes to ensure sufficient recrystallization.

[0009] Rapid cooling: After the first-stage annealing is completed, use forced air cooling for rapid cooling strategy to fix the new grain structure; rapid cooling can prevent the grains from growing too fast, resulting in performance degradation, and rapid cooling also helps to reduce oxidation and improve production efficiency.

[0010] In the second-stage annealing, the copper strip casting blank is heated to a second preset temperature, which is 400 degrees Celsius, and this temperature is maintained for 10 to 15 minutes; to further refine the grains, homogenize the structure or meet specific mechanical property requirements. Then the copper strip casting blank is naturally cooled to the rolling preset temperature.

[0011] During the annealing process, inert gas protection is used, such as nitrogen or argon, to avoid oxidation and ensure the surface quality of the copper material. At the same time, by precisely controlling the composition and pressure of the furnace atmosphere, the material properties are further optimized and the possibility of crack formation is reduced.

[0012] S2: Use machine vision to detect cracks on the edge of the processed copper strip casting blank, mark the position and length of the cracks, calculate the minimum width to be cut, and according to the calculation result, automatically adjust the cutting equipment to remove the part of the copper strip casting blank containing cracks;

[0013] S3: Locally heat the edge of the processed copper strip casting blank, and the local heating position is 20 mm from each side of the copper strip casting blank;

[0014] S4: During the process of rolling the copper strip casting blank into an ultra-thin copper strip, the edge stress of the copper strip is monitored in real time. Based on the detected stress magnitude, the rolling speed is dynamically adjusted, and a model of stress and rolling speed is constructed to predict and adjust the feed speed of the copper strip rolling mill.

[0015] The specific steps for real-time monitoring of the edge stress of the copper strip include:

[0016] Step 1: Install temperature sensors at the edges of the copper strip before and after rolling, and record the temperatures of the copper strip before and after rolling;

[0017] Step 2: Compare the temperature change rate before and after rolling to reflect the stress magnitude inside the copper strip. The calculation formula for the stress magnitude inside the copper strip and the temperature change rate is:

[0018] + , where is the stress, E is the elastic modulus, is the coefficient of thermal expansion, is the temperature change, k is the thermal conductivity, is the specific heat capacity, is the temperature change rate;

[0019] Step 3: According to the analysis result of the temperature change, draw the internal stress distribution map of the copper strip, and adjust the processing process parameters according to the stress distribution.

[0020] As a further solution of the present invention, in step S2, the specific steps for using machine vision for crack detection are:

[0021] S21: using a high-definition camera to continuously photograph the copper plate and strip cast embryo to be rolled, and segmenting the image into the edge portion of the copper plate and strip cast embryo according to a preset size, wherein the preset size of the copper plate and strip cast embryo edge is 10 mm on each side;

[0022] S22: De-noise and enhance the image, use Canny to extract feature values, and mark this area as a crack area;

[0023] S23: Use contour detection in the crack area to identify the contour of the crack, and determine the starting and ending coordinates P1 (x1, y1) and P2 (x2, y2) of the crack, and calculate the pixel width of the crack based on the starting and ending coordinates , the formula is: ;

[0024] S24: Calculate the true crack width based on the pixel width of the crack. The calculation formula is: , where R is the pixel resolution of the camera;

[0025] S25: Based on the calculated true crack width The control system automatically adjusts the blade position and cutting path to accurately cut out the crack area.

[0026] As a further solution of the present invention, in step S4, the step of dynamically adjusting the rolling speed according to the detected stress magnitude is:

[0027] S41: According to the internal stress value of the copper strip obtained in step S4, the speed, temperature, and roller pressure during rolling are collected simultaneously;

[0028] S42: cleaning the data, removing outliers and missing values, normalizing the data, and extracting the characteristic value of stress change rate from the processed data;

[0029] S43: Based on the goal of edge stress control, the following model can be established to predict the risk factor R of copper strip breakage: ,in is the stress value at the edge of the ultra-thin copper strip after rolling, is the stress value of the edge of the copper strip casting before rolling, P is the roller pressure, V is the current rolling speed, , , is a constant coefficient; when R is greater than the predetermined threshold, it means that the risk of copper strip breaking during rolling is high, and the rolling speed needs to be reduced to reduce the R value; when R is less than the predetermined threshold, it means that the risk of copper strip breaking during rolling is low, and the rolling speed can be increased to achieve the optimal production rate.

[0030] The sudden increase in edge stress is one of the main causes of cracks. By slowing down the rolling speed, more time can be given for the material to adapt to deformation, thereby reducing stress concentration and avoiding crack formation. The speed adjustment is to maintain or improve production efficiency as much as possible while ensuring product quality. Excessive reduction in speed will reduce production efficiency, while appropriate adjustment can find the optimal production speed point on the premise of ensuring product quality.

[0031] Beneficial effects: The present invention adopts a multiple annealing strategy to improve the plasticity of the material, introduces machine vision to detect cracks, and performs automated and precise cutting, reducing raw material loss. By using the local heating strategy and dynamically adjusting the rolling speed, the edge stress of the copper strip is effectively controlled, greatly reducing the generation of cracks and the risk of strip breakage, ensuring equipment safety, and at the same time improving production flexibility and production capacity. Description of the Drawings

[0032] Figure 1 It is a schematic flow chart of a method for eliminating edge cracks of an ultra-thin copper strip according to the present invention. Detailed Embodiments

[0033] The present invention will be further described in detail below with reference to the embodiments.

[0034] Please refer to Figure 1 As shown, the specific steps of a method for eliminating edge cracks of an ultra-thin copper strip are as follows:

[0035] S1: Perform multiple annealing on the initial copper strip billet;

[0036] The multiple annealing method includes:

[0037] Preheating stage: Slowly heat the above copper strip billet to a preset value below the recrystallization temperature to make the internal stress of the copper strip billet evenly distributed;

[0038] First-stage annealing: Continue to heat the copper strip billet to a first preset temperature, which is 650 degrees Celsius. This temperature is sufficient to restore the lattice distortion generated during the cold working process, promote the re-growth of grains, thereby reducing the material hardness, improving plasticity, and maintaining this temperature for 20 - 30 minutes to ensure sufficient recrystallization.

[0039] Rapid cooling: After the first-stage annealing is completed, use forced air cooling for rapid cooling strategy to fix the new grain structure; rapid cooling can prevent the grains from growing too fast, resulting in performance degradation. Rapid cooling also helps to reduce oxidation and improve production efficiency.

[0040] In the second-stage annealing, the copper strip casting blank is heated to a second preset temperature, which is 400 degrees Celsius, and this temperature is maintained for 10 - 15 minutes; to further refine the grains, homogenize the structure or meet specific mechanical property requirements. Then the copper strip casting blank is naturally cooled to the rolling preset temperature.

[0041] During the annealing process, inert gas protection is used, such as nitrogen or argon, to avoid oxidation and ensure the surface quality of the copper material. At the same time, by precisely controlling the composition and pressure of the furnace atmosphere, the material properties are further optimized, and the possibility of crack formation is reduced.

[0042] S2: Use machine vision to detect cracks on the edge of the processed copper strip casting blank, mark the position and length of the cracks, calculate the minimum width to be cut off, and according to the calculation result, automatically adjust the cutting equipment to remove the part of the copper strip casting blank containing cracks;

[0043] S3: Locally heat the edge of the processed copper strip casting blank, and the local heating position is 20 mm from each side of the copper strip casting blank;

[0044] S4: During the process of rolling the copper strip casting blank into an ultra-thin copper strip, the edge stress of the copper strip is monitored in real time. Based on the detected stress magnitude, the rolling speed is dynamically adjusted, and a model of stress and rolling speed is constructed to predict and adjust the feed speed of the copper strip rolling mill.

[0045] The specific steps for real-time monitoring of the edge stress of the copper strip include:

[0046] Step 1: Install temperature sensors at the edges of the copper strip before and after rolling, and record the temperatures of the copper strip before and after rolling;

[0047] Step 2: Compare the temperature change rate before and after rolling to reflect the stress magnitude inside the copper strip. The calculation formula for the stress magnitude inside the copper strip and the temperature change rate is:

[0048] + , where is the stress, E is the elastic modulus, is the coefficient of thermal expansion, is the temperature change, k is the thermal conductivity, is the specific heat capacity, is the temperature change rate;

[0049] Step 3: According to the analysis result of the temperature change, draw the internal stress distribution map of the copper strip, and adjust the processing process parameters according to the stress distribution.

[0050] Furthermore, in step S2, the specific steps for crack detection using machine vision are as follows:

[0051] S21: Continuously photograph the copper strip slab to be rolled using a high-definition camera, and segment the edge part of the copper strip slab from the image according to a preset size. The preset size of the edge of the copper strip slab is 10 mm on each side;

[0052] S22: Denoise and enhance the image, extract eigenvalue using Canny, and mark this area as the crack area;

[0053] S23: Use contour detection in the crack area to identify the contour of the crack, and determine the starting and ending coordinates P1(x1, y1) and P2(x2, y2) of the crack. Calculate the pixel width of the crack according to the starting and ending coordinates , the formula is: ;

[0054] S24: Calculate the real crack width according to the pixel width of the crack. The formula for the real crack width is: , where R is the pixel resolution of the camera;

[0055] S25: According to the calculated real crack width , the control system automatically adjusts the blade position and cutting path to accurately cut out the area containing the crack.

[0056] Further, in step S4, the steps for dynamically adjusting the rolling speed according to the detected stress magnitude are:

[0057] S41: According to the internal stress value of the copper strip obtained in step S4, collect the speed, temperature, and roll pressure during rolling at the same time;

[0058] S42: Clean the data, remove outliers and missing values, and normalize the data. Extract the eigenvalue of stress change rate from the processed data;

[0059] S43: Based on the goal of edge stress control, the following model can be established to predict the risk factor R of copper strip breakage: , where is the stress value at the edge of the ultra-thin copper strip after rolling, is the stress value at the edge of the copper strip slab before rolling, P is the roll pressure, V is the current rolling speed, , , are constant coefficients; when R is greater than the predetermined threshold, it indicates a high risk of copper strip breakage during rolling, and the rolling speed needs to be reduced to make the R value decrease; when R is less than the predetermined threshold, it indicates a low risk of copper strip breakage during rolling, and the rolling speed can be increased to reach the optimal production rate.

Claims

1. A method for eliminating edge cracks of ultra-thin copper strips, characterized in that: The following steps are involved: S1: subjecting the initial copper strip casting to multiple annealing treatments; The multiple annealing method comprises: In the preheating stage, the copper strip casting embryo is slowly heated to a preset value below the recrystallization temperature so that the internal stress of the copper strip casting embryo is evenly distributed; The first stage annealing is to continue heating the copper strip casting to a first preset temperature, which is 650 degrees Celsius, and maintain this temperature for 20 to 30 minutes; Rapid cooling: After the first stage of annealing, forced air cooling is used to fix the new grain structure. The second stage annealing is to heat the copper strip cast embryo to a second preset temperature, which is 400 degrees Celsius, and maintain this temperature for 10 to 15 minutes; then the copper strip cast embryo is naturally cooled to a preset rolling temperature; S2: Use machine vision to detect cracks on the edge of the copper strip casting after processing, mark the location and length of the cracks, calculate the minimum width to be cut, and adjust the cutting equipment according to the calculation results to remove the cracked part of the copper strip casting; S3: heating the edge of the copper strip casting embryo after the treatment, wherein the heating position is 20 mm on the left and right of the copper strip casting embryo; S4: During the rolling process of copper strip casting into ultra-thin copper strip, the edge stress of the copper strip is monitored in real time. The rolling speed is dynamically adjusted according to the detected stress. A stress and rolling speed model is constructed to predict and adjust the feed speed of the copper strip rolling mill. The specific steps of real-time monitoring of the edge stress of the copper strip include: Step 1: Install a temperature sensor at the edge of the copper strip before and after rolling, and record the temperature of the copper strip before and after rolling; Step 2: Comparing the temperature change rate before and after rolling reflects the stress inside the copper strip. The calculation formula for the stress inside the copper strip and the temperature change rate is: ,in is the stress, E is the elastic modulus, is the coefficient of thermal expansion, is the temperature change, k is the thermal conductivity, is the specific heat capacity, is the rate of temperature change; Step 3: Based on the analysis results of temperature changes, draw the internal stress distribution diagram of the copper strip and adjust the processing parameters according to the stress distribution.

2. The method for eliminating edge cracks of an ultra-thin copper strip according to claim 1, characterized in that: In step S2, the specific steps of using machine vision to perform crack detection are: S21: using a high-definition camera to continuously photograph the copper plate and strip cast embryo to be rolled, and segmenting the image into the edge portion of the copper plate and strip cast embryo according to a preset size, wherein the preset size of the copper plate and strip cast embryo edge is 10 mm on each side; S22: De-noise and enhance the image, use Canny to extract feature values, and mark this area as a crack area; S23: Use contour detection in the crack area to identify the contour of the crack, and determine the starting and ending coordinates P1 (x1, y1) and P2 (x2, y2) of the crack, and calculate the pixel width of the crack based on the starting and ending coordinates , the formula is: ; S24: Calculate the true crack width based on the pixel width of the crack. The calculation formula is: , where R is the pixel resolution of the camera; S25: Based on the calculated true crack width The control system automatically adjusts the blade position and cutting path to accurately cut out the crack area.

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