Detection method, detection device and production equipment of gravure aluminum foil for battery

Abstract

The invention provides a detection method and device of gravure aluminum foil for a battery and production equipment, and relates to the technical field of aluminum foil detection. The detection method comprises the following steps: acquiring reference parameters which comprise a chroma reference value and a sheet resistance reference value R0; the chromatic value of the gravure aluminum foil to be measured is measured, and the sheet resistance value R of the gravure aluminum foil to be measured is obtained through a preset chromatic sheet resistance relation model; based on the chromaticity reference value and the chromaticity value of the gravure aluminum foil to be measured, component deviation values (delta L, delta a and delta b) and a tolerance value delta E are obtained; and comparing the component deviation value and the tolerance value delta E with a preset component deviation threshold value, a preset tolerance threshold value range and a sheet resistance threshold value range, and if the component deviation value and the tolerance value delta E fall into the preset component deviation threshold value, the sheet resistance threshold value range and the preset tolerance threshold value range, judging that the gravure aluminum foil to be detected is qualified, otherwise, judging that the gravure aluminum foil to be detected is unqualified. According to the method, shutdown sampling is not needed, sample damage is not needed, and efficient and nondestructive detection is achieved.

Description

Technical Field

[0001] This application relates to the field of aluminum foil testing technology, and in particular to a testing method, testing device, and production equipment for gravure aluminum foil used in batteries. Background Technology

[0002] Gravure aluminum foil is widely used as the positive electrode current collector in lithium-ion batteries. This gravure aluminum foil requires a functional undercoating to improve its adhesion to the active material. The coating quality directly affects the battery's interfacial resistance and conductivity.

[0003] Current technologies primarily rely on scanning electron microscopy (SEM) or sheet resistance testing to assess coating quality. These methods suffer from sample destruction and low detection efficiency. Furthermore, they are difficult to implement in real-time on production lines. They cannot meet the requirements for efficient, non-destructive testing of coating uniformity and conductivity.

[0004] Therefore, there is an urgent need for a detection method and device for gravure aluminum foil used in batteries, which can efficiently and non-destructively detect the quality of gravure aluminum foil. Summary of the Invention

[0005] This application provides a method and apparatus for testing gravure aluminum foil for batteries, which solves the problems of low efficiency and destructive testing in current testing methods, and achieves efficient and non-destructive testing.

[0006] In a first aspect, this application provides a method for testing gravure aluminum foil for batteries, comprising the steps of: acquiring reference parameters, including chromaticity reference values ​​(L0, a0, b0) and sheet resistance reference values ​​R0; measuring the chromaticity values ​​(L1, a1, b1) of the gravure aluminum foil to be tested, and obtaining the sheet resistance value R of the gravure aluminum foil to be tested through a preset chromaticity-sheet resistance relationship model; obtaining component deviation values ​​(ΔL, Δa, Δb) and tolerance values ​​ΔE based on the chromaticity reference values ​​and the chromaticity values ​​of the gravure aluminum foil to be tested; comparing the component deviation values ​​(ΔL, Δa, Δb), the tolerance value ΔE, and the sheet resistance value R with preset component deviation thresholds, preset tolerance threshold ranges, and preset sheet resistance threshold ranges; if the component deviation values, ΔE, and sheet resistance all fall within the preset component deviation thresholds, sheet resistance threshold ranges, and preset tolerance threshold ranges, then the gravure aluminum foil to be tested is determined to be of qualified quality; otherwise, it is determined to be unqualified.

[0007] The above-described method establishes a comprehensive testing process for the gravure aluminum foil, beginning with the acquisition of optical colorimetric values. This high-speed, non-contact measurement method eliminates the need for machine downtime for sampling and avoids damaging the samples, thus achieving zero disruption to the production process and zero product loss. It also ensures that quality assessment covers every section of aluminum foil. Furthermore, this method does not solely rely on a single result value to determine the quality of the gravure aluminum foil; instead, it uses component deviation values ​​(ΔL, Δa, Δb) and the overall tolerance value ΔE to assess quality. This makes the overall test results more reliable and significantly improves battery quality.

[0008] In one possible design, the chromaticity reference values ​​include: lightness reference value L0, red-green axis reference value a0, and yellow-blue axis reference value b0; the chromaticity values ​​of the gravure aluminum foil to be tested include: lightness measurement value L1, red-green axis measurement value a1, and yellow-blue axis measurement value b1; the component deviation values ​​include: lightness deviation ΔL, red-green axis deviation Δa, and yellow-blue axis deviation Δb; the preset component deviation thresholds include: -3.0≤ΔL≤3; |Δa|≤2 and |Δb|≤2; the sheet resistance threshold range is: R≤1.2R0; the tolerance threshold range is: ΔE≤3.5.

[0009] The above scheme transforms abstract quality issues into concrete, actionable parameters and thresholds. By using the threshold ranges of ΔL, Δa, Δb, R, and ΔE, the quality of the gravure aluminum foil under test can be accurately determined. This allows the detection method to not only make a "pass / fail" judgment but also provide clear and targeted guidance for adjusting the production process (e.g., whether to adjust the coating amount or check the slurry formula), thereby achieving a sublimation from "quality control" to "quality assurance and process optimization". In one possible design, the preset chromaticity sheet resistance relationship model is: R=k1∣L1-L0∣+k2∣a1-a0∣+k3∣b1-b0∣+R0, where k1 is the lightness difference weighting coefficient, k2 is the red-green difference weighting coefficient, and k3 is the yellow-blue difference weighting coefficient.

[0010] Through the above scheme, the pre-defined chromaticity sheet resistance relationship model enables this scheme to move from theory to practice and from qualitative judgment to quantitative prediction. The model structure is a weighted absolute value linear model, which achieves efficient and robust linear quantification of complex physical phenomena. It has a fast calculation speed and is very suitable for industrial online applications. Taking the absolute value of the chromaticity deviation ensures the monotonicity and universality of the model, and can correctly reflect its negative impact on conductivity regardless of the direction of the deviation. The introduction of weighting coefficients k1, k2, and k3 related to the coating material takes into account the different correlations between the optical properties and electrical properties of different coating materials (such as carbon coating layers, conductive polymer layers, etc.). This ensures that the method in this scheme can maintain the accuracy of prediction regardless of the type of aluminum foil produced, guaranteeing versatility and high precision.

[0011] In one possible design, k1 is the brightness difference weighting coefficient, k2 is the red-green difference weighting coefficient, and k3 is the yellow-blue difference weighting coefficient, which is determined through multiple linear regression analysis.

[0012] The above approach, employing multiple linear regression analysis to obtain k1, k2, and k3, ensures that the model originates from objective data, not subjective experience, thus establishing a scientific and reliable quantitative predictive relationship. Without regression analysis, k1, k2, and k3 would have to be estimated based on engineers' experience, leading to poor model accuracy, low stability, and potentially vastly different results from different individuals. Multiple linear regression, based on a large amount of real sample data (chromaticity values ​​and corresponding sheet resistance values), objectively calculates the optimal coefficients that best reflect the true relationship between variables through mathematical optimization algorithms (such as least squares). When a pre-defined chromaticity-sheet resistance relationship model needs to be established for a new coating material (such as a novel conductive adhesive or carbon), only a batch of standard samples of the material needs to be prepared, their chromaticity and sheet resistance values ​​measured, and then a single multiple linear regression analysis performed to quickly obtain a set of specific k1, k2, and k3 coefficients. This makes the pre-defined chromaticity-sheet resistance relationship model not a fixed model, but an adaptable model framework. This allows for the creation of proprietary, high-precision predictive models for all production lines and product lines, forming a core technological barrier.

[0013] In one possible design, based on the colorimetric reference value and the sheet resistance reference value R0, as well as the colorimetric value and sheet resistance value R of the gravure aluminum foil to be tested, the component deviation values ​​(ΔL, Δa, Δb) and the tolerance value ΔE are obtained, including: ΔL = L1-L0; Δa = a1-a0; Δb = b1-b0; .

[0014] The above scheme calculates component deviations ΔL, Δa, and Δb using the direct difference method, giving their values ​​clear physical meaning. A negative ΔL explicitly indicates the presence of a coating causing a decrease in brightness; its absolute value directly correlates with the degree of thickness change. The sign of Δa or Δb indicates whether the chromaticity coordinates have shifted towards red / yellow or green / blue, providing crucial clues for tracing the type of component changes (such as oxidation or contamination). This method not only identifies whether a deviation exists but also pinpoints the direction of the deviation, providing direct and targeted feedback for precise process adjustments on the production line (e.g., whether to increase or decrease the coating amount, or to check which raw materials). It is the standard color difference calculation formula in color space. It synthesizes the deviations in the three dimensions in the form of Euclidean distance, meaning that a significant change in any of ΔL, Δa, or Δb will be sensitively reflected in an increase in the ΔE value. Therefore, ΔE, as a single, comprehensive indicator, can effectively capture coating appearance inconsistencies caused by any reason, whether it is uneven thickness, compositional fluctuations, or localized contamination. It provides an irreplaceable and efficient macroscopic indicator for rapid initial screening and overall compliance judgment.

[0015] In one possible design, obtaining the reference parameters includes the following steps: preparing a standard sample with acceptable conductivity, wherein the standard sample has a sheet resistance reference value R0 ≤ 25 mΩ / □; measuring the colorimetric reference value (L0, a0, b0) of the standard sample using a spectrophotometer; and measuring the sheet resistance reference value R0 of the standard sample using the four-probe method.

[0016] The above scheme establishes the baseline parameters for the entire testing system. This step is the fundamental prerequisite for ensuring the accuracy, reliability, and consistency of all subsequent measurements, calculations, and judgments. It explicitly requires that the core electrical performance (sheet resistance) must first meet the standard (≤25mΩ / □). This ensures that the subsequently established colorimetric baseline values ​​(L0, a0, b0) correspond to an ideal state with known excellent electrical performance. The entire testing system built upon this baseline has the clear ultimate goal of determining whether the tested gravure aluminum foil matches this qualified sample. This prevents the systemic risk of mistakenly setting a slightly defective product as the baseline, leading to a lower standard for the entire batch. The spectrophotometer provides accurate colorimetric data based on CIE standards, completely avoiding subjective judgment biases caused by visual differences or ambient light effects among different operators. The four-probe method is a classic and authoritative method for measuring the sheet resistance of thin films, and its measurement results have high industry acceptance. Using it as a means of measuring R0 essentially involves calibrating a novel, non-contact, rapid, online method with an authoritative, contact-based, destructive approach. This step significantly enhances the scientific rigor and persuasiveness of the entire technical solution. It demonstrates that the accuracy of the sheet resistance R predicted subsequently through colorimetry has been calibrated using industry-standard methods. This allows the conclusions of this non-contact testing method to achieve the same or even higher level of confidence as traditional methods, facilitating its promotion and application in serious quality control scenarios.

[0017] Secondly, this application provides a testing device for gravure aluminum foil used in batteries, comprising: a reference parameter acquisition unit for acquiring reference parameters, including chromaticity reference values ​​(L0, a0, b0) and sheet resistance reference value R0; a gravure aluminum foil colorimetric measurement unit for measuring the chromaticity values ​​(L1, a1, b1) of the gravure aluminum foil to be tested, and obtaining the sheet resistance value R of the gravure aluminum foil to be tested through a preset chromaticity-sheet resistance relationship model; and a calculation unit for calculating the gravure aluminum foil to be tested based on the chromaticity reference values ​​and the gravure aluminum foil to be tested. The colorimetric values ​​are used to obtain component deviation values ​​(ΔL, Δa, Δb) and tolerance values ​​ΔE. The quality judgment unit is used to compare the component deviation values ​​(ΔL, Δa, Δb), the tolerance value ΔE, and the sheet resistance value R with preset component deviation thresholds, preset tolerance threshold ranges, and sheet resistance threshold ranges. If the component deviation values, ΔE, and sheet resistance all fall within the preset component deviation thresholds, sheet resistance threshold ranges, and preset tolerance threshold ranges, then the quality of the gravure aluminum foil to be tested is determined to be qualified; otherwise, it is determined to be unqualified. In one possible design, the quality determination unit is also used to determine the quality of the gravure aluminum foil to be tested based on the following preset component deviation thresholds and preset tolerance threshold ranges: the preset component deviation thresholds include: -3.0≤ΔL≤3; |Δa|≤2 and |Δb|≤2; the sheet resistance threshold range is: R≤1.2R0; and the tolerance threshold range is: ΔE≤3.5. In one possible design, the colorimetric measurement unit of the gravure aluminum foil under test is also used to obtain the sheet resistance value R of the gravure aluminum foil under test according to the following colorimetric sheet resistance relationship model: R=k1|L1-L0|+k2|a1-a0|+k3|b1-b0|+R0, where k1 is the lightness difference weighting coefficient, k2 is the red-green difference weighting coefficient, and k3 is the yellow-blue difference weighting coefficient.

[0018] The beneficial effects of the detection device provided in the second aspect and the various possible designs of the second aspect can be found in the first aspect and the various possible implementations of the first aspect, and will not be repeated here.

[0019] In one possible design, the quality judgment unit is also used to mark the location and issue an alarm when it is determined that the quality of the gravure aluminum foil to be tested is unqualified.

[0020] Through the above solution, the quality judgment unit integrates marking and alarm functions, enabling precise defect location and physical traceability, and achieving instantaneous response to quality anomalies, greatly shortening the cycle from problem discovery to action. In subsequent slitting and winding processes, operators or automated equipment can accurately cut off and isolate defective segments based on the markings, thereby saving the remaining qualified parts of the roll of aluminum foil, significantly improving raw material utilization (premium yield), and avoiding the huge waste caused by scrapping the entire roll.

[0021] Thirdly, this application provides a production equipment for gravure aluminum foil, including the testing device for gravure aluminum foil for batteries according to any one of the second aspects.

[0022] The beneficial effects of the production equipment provided in the third aspect and the various possible designs of the third aspect can be found in the first aspect and the various possible implementations of the first aspect, and will not be repeated here.

[0023] The above description is merely an overview of the technical solutions of the embodiments of this application. In order to better understand the technical means of the embodiments of this application and to implement them in accordance with the contents of the specification, and to make the above and other objects, features and advantages of the embodiments of this application more obvious and understandable, specific implementation methods of this application are described below. Attached Figure Description

[0024] To more clearly illustrate the technical solutions of the embodiments of this application, the drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are some embodiments of this application. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0025] Figure 1 Enlarged surface views of qualified and unqualified gravure aluminum foil for batteries provided by this invention.

[0026] Figure 2 This is a flowchart of a method for detecting gravure aluminum foil for batteries provided in one embodiment of the present invention.

[0027] Figure 3 This is a flowchart of a method for obtaining benchmark parameters provided in one embodiment of the present invention. Figure 4 This is a schematic diagram of a detection device for gravure aluminum foil for batteries provided in one embodiment of the present invention. Detailed Implementation

[0028] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0029] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application pertains; the terminology used herein in the specification of the application is for the purpose of describing particular embodiments only and is not intended to limit the application; the terms “comprising” and “having”, and any variations thereof, in the specification, claims and drawings of this application are intended to cover non-exclusive inclusion.

[0030] The term "embodiment" as used herein means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of this application. The appearance of the phrase "embodiment" in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0031] In this article, the term "and / or" is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can mean: A exists, A and B exist simultaneously, or B exists. Additionally, the character " / " in this article generally indicates that the preceding and following related objects have an "or" relationship.

[0032] Furthermore, the terms "first," "second," etc., in the specification and claims of this application or in the aforementioned drawings are used to distinguish different objects rather than to describe a specific order, and may explicitly or implicitly include one or more of the features.

[0033] In the description of this application, unless otherwise stated, "multiple" means two or more (including two), and similarly, "multiple groups" means two or more (including two groups).

[0034] Gravure aluminum foil specifically refers to aluminum foil used as current collectors in lithium-ion batteries, which undergoes a special treatment called "gravure printing." Its surface is not smooth; instead, it features very fine embossed textures created through the gravure printing process. A thin functional coating (such as a carbon coating or adhesive layer) is then applied to these textures. Therefore, aluminum foil is a basic raw material. Gravure aluminum foil is a further processed, high-value-added product obtained by gravure printing and coating on this basic raw material to meet the specific needs of lithium-ion batteries (enhanced adhesion and reduced resistance).

[0035] As is known from the background art, the coating quality of gravure aluminum foil for batteries affects the quality of the battery. However, current quality inspection of gravure aluminum foil suffers from problems such as low efficiency and destructive testing.

[0036] Figure 1These are enlarged images of the surface of qualified and unqualified gravure aluminum foil for batteries. Please refer to them. Figure 1 The images show the surface of the gravure aluminum foil. The left image is a photograph of a standard sample with acceptable conductivity, while the right image is a photograph of a gravure aluminum foil with unacceptable conductivity. Through the inventor's creative work, it was discovered that the thickness of the functional coatings (such as carbon layers and adhesive layers) on the surface of the gravure aluminum foil is strongly correlated with its colorimetric value.

[0037] In view of this, embodiments of this application provide a method, apparatus, and production equipment for detecting gravure aluminum foil for batteries. The detection method includes the following steps: obtaining reference parameters, including chromaticity reference values ​​(L0, a0, b0) and sheet resistance reference values ​​R0; measuring the chromaticity values ​​(L1, a1, b1) of the gravure aluminum foil to be tested, and obtaining the sheet resistance value R of the gravure aluminum foil to be tested through a preset chromaticity-sheet resistance relationship model; obtaining component deviation values ​​(ΔL, Δa, Δb) and tolerance values ​​ΔE based on the chromaticity reference values ​​and the chromaticity values ​​of the gravure aluminum foil to be tested; comparing the component deviation values ​​(ΔL, Δa, Δb), the tolerance value ΔE, and the sheet resistance value R with preset component deviation thresholds, preset tolerance threshold ranges, and preset sheet resistance threshold ranges; if the component deviation values, ΔE, and sheet resistance all fall within the preset component deviation thresholds, sheet resistance threshold ranges, and preset tolerance threshold ranges, then the gravure aluminum foil to be tested is deemed to be of qualified quality; otherwise, it is deemed to be unqualified. The entire testing process begins with the acquisition of optical colorimetric values, a high-speed, non-contact measurement method. It requires no downtime for sampling and no damage to the sample, thus achieving zero disruption to the production process and zero waste of the product, while ensuring quality assessment covers every section of aluminum foil.

[0038] To enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings.

[0039] Figure 2 This is a flowchart of the detection method for gravure aluminum foil for batteries provided in this embodiment. Please refer to the reference. Figure 2 This application provides a method for detecting gravure aluminum foil for batteries, comprising: Step 1: Obtain the reference parameters, which include the chromaticity reference value (L0, a0, b0) and the sheet resistance reference value R0.

[0040] The benchmark parameters can be understood as a standard for qualification, used to quantify and compare the color and sheet resistance deviation of each roll of gravure aluminum foil to determine whether it meets the standard.

[0041] The chromaticity reference values ​​(L0, a0, b0) include the lightness reference value L0, which represents the brightness of the standard color, ranging from 0 (black) to 100 (white).

[0042] The red-green axis reference value a0 indicates the position of the standard color on the red-green axis: positive value = reddish, negative value = greenish.

[0043] The yellow-blue axis reference value b0 indicates the position of the standard color on the yellow-blue axis: positive value = yellowish, negative value = bluish.

[0044] How are the baseline parameters for the entire testing system established? This step is the fundamental prerequisite for ensuring that all subsequent measurements, calculations, and judgments are accurate, reliable, and consistent. Figure 3 For a flowchart of the method for obtaining benchmark parameters provided in this embodiment, please refer to [link / reference]. Figure 3 In this embodiment, obtaining the reference parameters includes: Step 101: Prepare a standard sample with qualified conductivity. The standard sample has a sheet resistance reference value R0 ≤ 25mΩ / □.

[0045] Only samples with acceptable electrical conductivity can be used as standard samples. It's understood that gravure aluminum foil is considered acceptable when R0 ≤ 25 mΩ / □. Therefore, it's explicitly required that its sheet resistance must first meet the standard. This ensures that the subsequently established colorimetric reference values ​​(L0, a0, b0) correspond to an ideal state with known excellent electrical properties. The entire testing system built upon this reference has the clear ultimate goal of determining whether the gravure aluminum foil under test matches this acceptable sample. This prevents, from the outset, the systemic risk of mistakenly setting a slightly defective product as the reference, leading to a lowering of the overall batch standard.

[0046] Step 102: Measure the colorimetric reference values ​​(L0, a0, b0) of the standard sample using a spectrophotometer, and measure the sheet resistance reference value R0 of the standard sample using the four-probe method.

[0047] Spectrophotometers provide accurate chromaticity data based on CIE (Commission Internationale de l'Éclairage, International Association for Illumination) standards, completely avoiding subjective judgment biases caused by differences in visual perception or the influence of ambient light among different operators.

[0048] The four-probe method is a classic and authoritative method for measuring sheet resistance of thin films, and its measurement results are highly recognized in the industry. Using it as a means of measuring R0 essentially involves using an authoritative, contact-based, destructive method to calibrate a new, non-contact, rapid, online method. This step greatly enhances the scientific rigor and persuasiveness of the entire technical solution. It proves that the accuracy of the sheet resistance R predicted subsequently through colorimetry has been calibrated using industry-standard methods. This allows the conclusions of the non-contact detection method in this embodiment to obtain the same level of confidence as traditional methods, facilitating its promotion and application.

[0049] Step 2: Measure the chromaticity values ​​(L1, a1, b1) of the gravure aluminum foil to be tested, and obtain the sheet resistance value R of the gravure aluminum foil to be tested through the preset chromaticity sheet resistance relationship model.

[0050] It is understandable that the colorimetric value of the gravure aluminum foil to be tested can be obtained by measuring it with a spectrophotometer. The colorimetric value of the gravure aluminum foil to be tested includes: lightness measurement value L1, red-green axis measurement value a1, and yellow-blue axis measurement value b1. However, the sheet resistance value R of the gravure aluminum foil to be tested cannot be measured by the four-probe method because the four-probe method is not real-time and is destructive.

[0051] In this embodiment, the sheet resistance value R of the gravure aluminum foil to be tested is obtained through a preset colorimetric sheet resistance relationship model, wherein the preset colorimetric sheet resistance relationship model is: R=k1|L1-L0|+k2|a1-a0|+k3|b1-b0|+R0, where k1 is the brightness difference weighting coefficient, k2 is the red-green difference weighting coefficient, and k3 is the yellow-blue difference weighting coefficient.

[0052] The pre-defined chromaticity sheet resistance relationship model enables this scheme to move from theory to practice and from qualitative judgment to quantitative prediction. The model structure is a weighted absolute value linear model, achieving efficient and robust linear quantification of complex physical phenomena. Its fast computation speed makes it highly suitable for industrial online applications. Taking the absolute value of chromaticity deviation ensures the model's monotonicity and universality, accurately reflecting its negative impact on conductivity regardless of the deviation direction. Introducing weighting coefficients k1, k2, and k3 related to the coating material accounts for the varying degrees of correlation between the optical and electrical properties of different coating materials (such as carbon coatings and conductive polymer layers). This ensures that the method in this scheme maintains predictive accuracy regardless of the type of aluminum foil produced, guaranteeing versatility and high precision.

[0053] In this embodiment, k1 is the brightness difference weighting coefficient, k2 is the red-green difference weighting coefficient, and k3 is the yellow-blue difference weighting coefficient, which are determined by multiple linear regression analysis.

[0054] The use of multiple linear regression analysis to obtain k1, k2, and k3 ensures that the model originates from objective data, rather than subjective experience, thus establishing a scientific and reliable quantitative predictive relationship. Without regression analysis, k1, k2, and k3 can only be estimated based on engineers' experience, leading to poor model accuracy, low stability, and potentially vastly different results from different personnel. Multiple linear regression, based on a large amount of real sample data (chromaticity values ​​and corresponding sheet resistance values), objectively calculates the optimal coefficients that best reflect the true relationship between variables through mathematical optimization algorithms (such as least squares). When a pre-defined chromaticity-sheet resistance relationship model needs to be established for a new coating material (such as a new type of conductive adhesive or carbon), only a batch of standard samples of the material needs to be prepared, their chromaticity and sheet resistance values ​​measured, and then a single multiple linear regression analysis performed to quickly obtain a set of specific k1, k2, and k3 coefficients. This makes the pre-defined chromaticity-sheet resistance relationship model not a fixed model, but an adaptable model framework. Based on this, specific, high-precision predictive models can be established for all production lines and all product series, forming a core technological barrier.

[0055] For example, in this embodiment, the determination of k1, k2, and k3 can be achieved through the following steps: First, take i=30 rolls of gravure aluminum foil from the same batch of batteries to be tested, and use a spectrometer to measure the colorimetric value (L) of each roll of gravure aluminum foil. i a i b i The corresponding sheet resistance R was measured using four probes. i .

[0056] Then, calculate the color difference: ΔL i =L0-L i Δa=|a i -a0|,Δb=|b i -b0|(L0, a0, b0 are the standard colorimetric reference values ​​for this batch of aluminum foil).

[0057] Finally, based on the measured R... i As the dependent variable, ΔL i , Δa i Δb i Using k1ΔL as the independent variable, perform multivariate linear regression: R = k1ΔL + k2Δa + k3Δb + R0; directly obtain k1, k2, k3 and intercept R0, and obtain k1, k2, k3 as the colorimetric-sheet resistance sensitivity coefficients of this batch of gravure aluminum foil.

[0058] Step 3: Based on the colorimetric reference value and the colorimetric value of the gravure aluminum foil to be tested, obtain the component deviation values ​​(ΔL, Δa, Δb) and the tolerance value ΔE.

[0059] The component deviation values ​​include: brightness deviation ΔL, red-green axis deviation Δa, and yellow-blue axis deviation Δb.

[0060] Based on the colorimetric reference value and the colorimetric value of the gravure aluminum foil to be tested, the component deviation values ​​(ΔL, Δa, Δb) can be obtained, where ΔL = L1-L0; Δa = a1-a0; Δb = b1-b0.

[0061] The tolerance value ΔE needs to be determined jointly by the colorimetric reference value and the colorimetric value of the gravure aluminum foil to be tested; it is a comprehensive, overall value. ,Right now, .

[0062] In this embodiment, the component deviations are calculated using the direct difference method to obtain ΔL, Δa, and Δb, giving their values ​​clear physical meaning. A negative ΔL explicitly indicates the presence of a coating causing a decrease in brightness; its absolute value directly relates to the degree of thickness change. The sign of Δa or Δb indicates whether the chromaticity coordinates have shifted towards red / yellow or green / blue, providing crucial clues for tracing the type of component changes (such as oxidation or contamination). This method not only clarifies whether a deviation exists but also identifies the direction of the deviation, providing direct and targeted feedback for precise process adjustments on the production line (e.g., whether to increase or decrease the coating amount, or to check which raw materials). It is the standard color difference calculation formula in color space. It synthesizes the deviations in the three dimensions in the form of Euclidean distance, meaning that a significant change in any of ΔL, Δa, or Δb will be sensitively reflected in an increase in the ΔE value. Therefore, ΔE, as a single, comprehensive indicator, can effectively capture coating appearance inconsistencies caused by any reason, whether it is uneven thickness, compositional fluctuations, or localized contamination. It provides an irreplaceable and efficient macroscopic indicator for rapid initial screening and overall compliance judgment.

[0063] Step 4: Compare the component deviation values ​​(ΔL, Δa, Δb), tolerance value ΔE, and sheet resistance value R with the preset component deviation threshold, preset tolerance threshold range, and sheet resistance threshold range. If the component deviation value, ΔE, and sheet resistance all fall within the preset component deviation threshold, sheet resistance threshold range, and preset tolerance threshold range, the quality of the gravure aluminum foil to be tested is determined to be qualified; otherwise, it is determined to be unqualified.

[0064] The above-described method does not merely determine the quality of the gravure aluminum foil under test based on a single result value. Instead, it uses component deviation values ​​(ΔL, Δa, Δb) and the overall tolerance value ΔE to determine the quality, making the overall test results more reliable and significantly improving battery quality. Furthermore, the entire testing process for the gravure aluminum foil using this method begins with the acquisition of optical colorimetric values—a high-speed, non-contact measurement method. It eliminates the need for machine downtime for sampling and avoids damaging the sample, thus achieving zero interference with the production process and zero product loss, while ensuring that quality assessment covers every section of aluminum foil.

[0065] In this embodiment, the preset component deviation thresholds include: -3.0≤ΔL≤3; |Δa|≤2 and |Δb|≤2; the sheet resistance threshold range is: R≤1.2R0; and the tolerance threshold range is: ΔE≤3.5.

[0066] ΔL≤3 (Upper Limit): Ensures minimum effective coverage of the coating. If ΔL is greater than 3, it means the coating is too thin, which may result in incomplete coverage, leading to increased interfacial contact resistance between the current collector and the active material, or even localized delamination. This threshold ensures the coating's adhesion and conductivity.

[0067] ΔL ≥ -3.0 (lower limit): Prevents excessive coating thickness. Excessively thick coatings (ΔL much less than -3.0) not only waste raw materials but also increase lithium-ion transport paths, leading to increased internal resistance, decreased rate performance, and reduced energy density. This threshold optimizes coating thickness to a balance between performance and cost.

[0068] The values ​​of a and b are extremely sensitive to the chemical properties of the material (such as the degree of graphitization of carbon materials, the type of binder, and the curing state) as well as trace contaminants. |Δa|≤2 and |Δb|≤2, that is, -2≤Δa≤2 and -2≤Δb≤2. If the ranges of Δa and Δb cannot be guaranteed, it indicates that there are problems with compositional shift and increased interfacial impedance in the coating.

[0069] ΔE is a comprehensive representation of ΔL, Δa, and Δb. A ΔE exceeding 3.5 is typically a slight difference perceptible to the human eye in industrial vision. Any localized thickness unevenness, streaks, discoloration, or other defects will cause ΔE to exceed the standard. Therefore, ΔE ≤ 3.5 can quickly screen out products with any form of non-uniformity, ensuring a high degree of uniformity in the products leaving the factory.

[0070] 1.2R0 is a safety factor that balances normal production fluctuations with performance redundancy. It ensures that even if a product barely meets the optical parameters, its conductivity must remain stable within a safe range. Meeting the threshold range of R≤1.2R0 effectively blocks all risky products that could lead to excessively high battery internal resistance, increased heat generation during cycling, or even lithium plating short circuits.

[0071] This embodiment transforms abstract quality issues into concrete, actionable parameters and thresholds. By using the threshold ranges of ΔL, Δa, Δb, R, and ΔE, the quality of the gravure aluminum foil under test can be accurately determined. This allows the detection method to not only make a "pass / fail" judgment but also provide clear and targeted guidance for adjusting the production process (e.g., adjusting the coating amount or checking the slurry formula), thereby achieving an upgrade from "quality control" to "quality assurance and process optimization".

[0072] This embodiment provides a method for detecting positive electrode current collector gravure aluminum foil (carbon coating), as follows: Obtaining benchmark parameters: L0=82.5, a0=-0.3, b0=1.2, R0=18mΩ / □ The coefficients k1, k2, and k3 were determined using multiple linear regression analysis.

[0073] In this embodiment, determining the coefficients k1, k2, and k3 may include the following steps: First, take i=30 rolls of gravure aluminum foil from the same batch of batteries to be tested, and use a spectrometer to measure the colorimetric value (L) of each roll of gravure aluminum foil. i a i b i ), and the corresponding 30 measured sheet resistances R were obtained using a four-probe method. i , where i = 1, 2, 3, ..., 30.

[0074] Then, calculate the color deviation: ΔL i =L0-L i Δa=|a i -a0|,Δb=|b i -b0|(L0=82.5, a0=-0.3, b0=1.2, R0=18mΩ / □). That is, for each sample i, its color deviation from the reference value is calculated.

[0075] Finally, based on the measured R... i As the dependent variable, ΔL i , Δa i Δb i Using k1ΔL as the independent variable, perform multivariate linear regression: R = k1ΔL + k2Δa + k3Δb + R0; Using the least squares method, find a set of k1, k2, k3 and intercept R0 such that the model prediction R （predicted）i Compared with the measured value R i The sum of squared residuals between them is minimized. The regression results are interpreted and the coefficients are determined to obtain k1, k2, k3 and intercept R0. k1, k2, and k3 are the colorimetric-sheet resistance sensitivity coefficients of this batch of gravure aluminum foil.

[0076] Based on the regression results, we obtain k1=0.35, k2=1.8, and k3=2.1. These three coefficients are the chromaticity-sheet resistance sensitivity coefficients obtained through data-driven analysis. Their physical meaning is: k1=0.35: For every unit increase in brightness deviation ΔL, the predicted sheet resistance R increases by an average of 0.35mΩ / □.

[0077] k2=1.8: For every unit increase in the red-green sample deviation Δa, the predicted sheet resistance R increases by an average of 1.8mΩ / □.

[0078] k3=2.1: For every unit increase in the deviation Δb of the yellow-blue product, the predicted sheet resistance R increases by an average of 2.1 mΩ / □.

[0079] Therefore, the sheet resistance model is obtained as: R = 0.35ΔL + 1.8Δa + 2.1Δb + 18.

[0080] Colorimetric values ​​of the gravure aluminum foil to be tested: The measurements were: L1=78.8, a1=2.1, b1=3.5.

[0081] calculate:

[0082] ΔL = L1 − L0 = −3.7.

[0083] Δa = a1 − a0 = 2.4.

[0084] Δb = b1 − b0 = 2.3.

[0085] R=0.35×3.7+1.8×2.4+2.1×2.3+18=28.445mΩ / □.

[0086] Result determination: The tested concave aluminum foil contains, |ΔL|=3.7>3, |Δb|=2.3>2, ΔE 4.97 > 3.5, therefore the coating of the aluminum foil on the test plate is not uniform. R = 28.445 > 21.6 (1.2R0), therefore the conductivity of the aluminum foil on the test plate is not qualified.

[0087] Based on the above embodiments, this application also provides a detection device for gravure aluminum foil for batteries. Figure 4 This is a schematic diagram of the detection device for the gravure aluminum foil used in batteries provided in this embodiment. Please refer to... Figure 4 The detection device 100 includes: a reference parameter acquisition unit 110, a colorimetric measurement unit 120 for the gravure aluminum foil to be tested, a calculation unit 130, and a quality judgment unit 140.

[0088] The reference parameter acquisition unit 110 is used to acquire reference parameters, which include chromaticity reference values ​​(L0, a0, b0) and sheet resistance reference value R0.

[0089] The reference parameter acquisition unit 110 is also used to prepare a standard sample with qualified conductivity, wherein the standard sample has a sheet resistance reference value R0≤25mΩ / □; the colorimetric reference value (L0, a0, b0) of the standard sample is measured using a spectrophotometer, and the sheet resistance reference value R0 of the standard sample is measured using the four-probe method.

[0090] The colorimetric measurement unit 120 of the gravure aluminum foil under test is used to measure the colorimetric values ​​(L1, a1, b1) of the gravure aluminum foil under test, and obtain the sheet resistance value R of the gravure aluminum foil under test through a preset colorimetric sheet resistance relationship model.

[0091] The calculation unit 130 is used to obtain component deviation values ​​(ΔL, Δa, Δb) and tolerance value ΔE based on the colorimetric reference value and the colorimetric value of the gravure aluminum foil to be tested.

[0092] The quality judgment unit 140 is used to compare the component deviation values ​​(ΔL, Δa, Δb), tolerance value ΔE, and sheet resistance value R with preset component deviation thresholds, preset tolerance threshold ranges, and sheet resistance threshold ranges. If the component deviation value, ΔE, and sheet resistance all fall within the preset component deviation threshold, sheet resistance threshold range, and preset tolerance threshold range, the quality of the gravure aluminum foil to be tested is determined to be qualified; otherwise, it is determined to be unqualified. In this embodiment, the quality determination unit 140 is also used to determine the quality of the gravure aluminum foil to be tested according to the following preset component deviation threshold and preset tolerance threshold range: the preset component deviation threshold includes: -3.0≤ΔL≤3; |Δa|≤2 and |Δb|≤2; R≤1.2R0; the tolerance threshold range is: ΔE≤3.5. In this embodiment, the colorimetric measurement unit 120 of the gravure aluminum foil under test is also used to obtain the sheet resistance value R of the gravure aluminum foil under test according to the following colorimetric sheet resistance relationship model: ΔL = L1-L0; Δa = a1-a0; Δb = b1-b0, k1 is the lightness difference weighting coefficient, k2 is the red-green difference weighting coefficient, and k3 is the yellow-blue difference weighting coefficient.

[0093] In this embodiment, in the colorimetric measurement unit 120 of the gravure aluminum foil to be tested, k1 is the lightness difference weighting coefficient, k2 is the red-green difference weighting coefficient, and k3 is the yellow-blue difference weighting coefficient, which are determined by multiple linear regression analysis.

[0094] In this embodiment, the calculation unit 130 is also used to calculate ΔL, Δa, Δb and ΔE using the following formulas: ΔL =L1-L0; Δa= a1-a0; Δb= b1-b0; ,Right now, .

[0095] Since the gravure aluminum foil used in this battery and its beneficial effects have been described in detail in the previous embodiments, they will not be repeated here.

[0096] In this embodiment, the quality judgment unit 140 is also used to mark the location and issue an alarm when the quality of the gravure aluminum foil to be tested is determined to be unqualified. The quality judgment unit 140 integrates marking and alarm functions, enabling precise location and physical traceability of defects, achieving instantaneous response to quality anomalies, and greatly shortening the cycle from problem discovery to action. In subsequent slitting and winding processes, operators or automated equipment can accurately cut off and isolate unqualified segments based on the markings, thereby saving the remaining qualified parts of the roll of aluminum foil, significantly improving raw material utilization (high-quality rate), and avoiding the huge waste caused by scrapping the entire roll.

[0097] Based on the above embodiments, this application also provides a production equipment for gravure aluminum foil, including the detection device for gravure aluminum foil for batteries in any of the above embodiments.

[0098] The above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application.

Claims

1. A method for testing gravure aluminum foil for batteries, characterized in that, Including the following steps: Obtain reference parameters, which include chromaticity reference values ​​(L0, a0, b0) and sheet resistance reference value R0; The colorimetric values ​​(L1, a1, b1) of the gravure aluminum foil to be tested are measured, and the sheet resistance value R of the gravure aluminum foil to be tested is obtained through a preset colorimetric sheet resistance relationship model. Based on the colorimetric reference value and the colorimetric value of the gravure aluminum foil to be tested, the component deviation values ​​(ΔL, Δa, Δb) and the tolerance value ΔE are obtained. The component deviation values ​​(ΔL, Δa, Δb), the tolerance value ΔE, and the sheet resistance value R are compared with preset component deviation thresholds, preset tolerance threshold ranges, and sheet resistance threshold ranges. If the component deviation value, ΔE, and sheet resistance all fall within the preset component deviation threshold, sheet resistance threshold range, and preset tolerance threshold range, the quality of the gravure aluminum foil to be tested is determined to be qualified; otherwise, it is determined to be unqualified.

2. The detection method according to claim 1, characterized in that, The chromaticity reference values ​​include: lightness reference value L0, red-green axis reference value a0, and yellow-blue axis reference value b0; The colorimetric values ​​of the gravure aluminum foil to be tested include: lightness measurement value L1, red-green axis measurement value a1, and yellow-blue axis measurement value b1; The component deviation values ​​include: brightness deviation ΔL, red-green axis deviation Δa, and yellow-blue axis deviation Δb; The preset component deviation threshold includes: -3.0≤ΔL≤3; |Δa|≤2 and |Δb|≤2; The sheet resistance threshold range is: R≤1.2R0; The tolerance threshold range is: ΔE≤3.

5.

3. The detection method according to claim 2, characterized in that, The preset chromaticity sheet resistance relationship model is as follows: R = k1∣L1-L0∣+k2∣a1-a0∣+k3∣b1-b0∣+R0, where k1 is the brightness difference weighting coefficient, k2 is the red-green difference weighting coefficient, and k3 is the yellow-blue difference weighting coefficient.

4. The detection method according to claim 3, characterized in that, The weighting coefficients k1, k2, and k3 for the difference between red and green are determined through multiple linear regression analysis.

5. The detection method according to claim 1, characterized in that, The process of obtaining component deviation values ​​(ΔL, Δa, Δb) and tolerance value ΔE based on the colorimetric reference value and the colorimetric value of the gravure aluminum foil to be tested includes: ΔL = L1 - L0; Δa = a1 - a0; Δb = b1 - b0; 。 6. The detection method according to claim 1, characterized in that, Obtaining the baseline parameters includes the following steps: Prepare standard samples with qualified conductivity, wherein the standard sample has a sheet resistance reference value R0 ≤ 25mΩ / □; The colorimetric reference values ​​(L0, a0, b0) of the standard sample were measured using a spectrophotometer, and the sheet resistance reference value R0 of the standard sample was measured using the four-probe method.

7. A testing device for gravure aluminum foil for batteries, characterized in that, include: A reference parameter acquisition unit is used to acquire reference parameters, which include chromaticity reference values ​​(L0, a0, b0) and sheet resistance reference value R0. The colorimetric measurement unit for the gravure aluminum foil under test is used to measure the colorimetric values ​​(L1, a1, b1) of the gravure aluminum foil under test, and obtain the sheet resistance value R of the gravure aluminum foil under test through a preset colorimetric sheet resistance relationship model. The calculation unit is used to obtain component deviation values ​​(ΔL, Δa, Δb) and tolerance value ΔE based on the colorimetric reference value and the colorimetric value of the gravure aluminum foil to be tested. The quality judgment unit is used to compare the component deviation values ​​(ΔL, Δa, Δb), the tolerance value ΔE, and the sheet resistance value R with preset component deviation thresholds, preset tolerance threshold ranges, and sheet resistance threshold ranges. If the component deviation value, ΔE, and sheet resistance all fall within the preset component deviation threshold, sheet resistance threshold range, and preset tolerance threshold range, the quality of the gravure aluminum foil to be tested is determined to be qualified; otherwise, it is determined to be unqualified.

8. The detection device according to claim 7, characterized in that, The quality determination unit is also used to determine the quality of the gravure aluminum foil to be tested based on the following preset component deviation threshold and preset tolerance threshold range: The preset component deviation threshold includes: -3.0≤ΔL≤3; |Δa|≤2 and |Δb|≤2; R≤1.2R0; The tolerance threshold range is: ΔE≤3.

5.

9. The detection device according to claim 7, characterized in that, The colorimetric measurement unit of the gravure aluminum foil under test is also used to obtain the sheet resistance value R of the gravure aluminum foil under test according to the following colorimetric sheet resistance relationship model: R = k1∣L1-L0∣+k2∣a1-a0∣+k3∣b1-b0∣+R0, where k1 is the brightness difference weighting coefficient, k2 is the red-green difference weighting coefficient, and k3 is the yellow-blue difference weighting coefficient.

10. A production equipment for gravure aluminum foil, characterized in that, The device includes the detection apparatus for gravure aluminum foil for batteries as described in any one of claims 7-9.

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