Electrode surface analysis method and electrode surface analysis system

Abstract

The present invention relates to an electrode surface analysis method and an electrode surface analysis system and, more particularly, to an electrode surface analysis method and an electrode surface analysis system capable of improving process efficiency and product reliability by precisely analyzing foreign substances remaining on an electrode surface during an electrode manufacturing process, by using a hyperspectral CCD.

Description

Electrode surface analysis method and electrode surface analysis system

[0001] Cross-citation with related applications

[0002] This application claims the benefit of priority from Korean Patent Application No. 10-2024-0069391, dated May 28, 2024, the entire contents of which are incorporated herein by reference.

[0003] Technology field

[0004] The present invention relates to an electrode surface analysis method and an electrode surface analysis system for precisely analyzing foreign substances on an electrode surface, for analyzing an electrode surface during a secondary battery manufacturing process.

[0005] As technological development and demand for mobile devices increase, the demand for secondary batteries as an energy source is rapidly increasing, and accordingly, extensive research is being conducted on secondary batteries that can meet various needs.

[0006] These secondary batteries are manufactured by having an electrode assembly housed in a battery case together with an electrolyte. These electrode assemblies are categorized into stacked, folded, and stack-folded types, depending on the manufacturing method. Stacked or stack-folded electrode assemblies have a structure in which the unit assemblies are sequentially stacked, with a separator between the positive and negative electrodes. To manufacture these electrode assemblies, it is necessary to first manufacture positive and negative electrodes with electrode tabs formed thereon.

[0007] The electrode process for manufacturing electrodes of secondary batteries includes (1) a mixing process, (2) a coating process, (3) a rolling process, and (4) a slitting and notching process, and these processes are performed as in-line processes.

[0008] The above (1) mixing process is a process for preparing a slurry for forming an active material layer of an electrode. The slurry can be prepared by measuring and mixing various raw materials necessary for forming the active material layer, including electrode active material, binder, and conductive material.

[0009] In addition, the above (2) coating process is a process of forming an electrode active material layer by thinly coating the slurry on a current collector and drying it. The current collector and the electrode active material layer formed on the current collector are referred to as an electrode sheet.

[0010] In addition, the above (3) rolling process is a process of uniformly stretching the electrode sheet by passing it between two rolls. The rolling process is also called a roll pressing process.

[0011] In addition, the above (4) slitting and notching process is a process for cutting the electrode sheet according to the battery size. The slitting process can cut the battery sheet vertically according to the battery design specifications. The notching process is a process for forming a V-groove and an electrode tab after the slitting process. At this time, in the notching process, the electrode sheet is generally positioned on a die, and a part of the electrode sheet can be punched out using a press, or the electrode tab can be formed by etching. Meanwhile, in a small pouch line, an etching process may be performed between the rolling process and the slitting process.

[0012] However, foreign substances generated during this etching process can remain on the electrode surface, potentially degrading its quality. If the type and amount of foreign substances remaining on the electrode surface could be identified, the etching process could be designed and implemented to minimize their generation. Here, the foreign substances may refer to residues such as binder contained in the electrode's active material layer.

[0013] Typically, vision systems installed in inline equipment for inline electrode manufacturing processes are used to detect residual foreign matter. However, vision systems typically have a large field of view (FOV), making it difficult to determine the specific type and amount of residual foreign matter. The electrode etching process is performed inline, and the limitations of inline equipment necessitate the installation of vision systems. Furthermore, installing cameras capable of more precise foreign matter analysis beyond vision systems presents technical challenges.

[0014] Therefore, it is necessary to develop a technology for an electrode surface analysis method that can identify the type and amount of foreign substances remaining on the electrode surface after the electrode etching process.

[0015] [Prior Art Literature]

[0016] (Patent Document 1) Korean Patent Publication No. 2011-0029011

[0017] The inventors of the present invention have conducted multifaceted research to solve the above problems and have confirmed that by introducing a hyperspectral CCD (Charge Coupled Device) as offline equipment in addition to the vision, which is an inline equipment equipped in the inline process for manufacturing electrodes, the electrode surface can be analyzed more precisely.

[0018] Accordingly, the purpose of the present invention is to provide a method for analyzing an electrode surface using a hyperspectral CCD.

[0019] In addition, another object of the present invention is to provide an electrode surface analysis system using a hyperspectral CCD.

[0020] In order to achieve the above purpose, the present invention provides an electrode surface analysis method that analyzes an electrode surface using a hyperspectral CCD (Charge Coupled Device),

[0021] (a) A step of photographing an electrode surface with a hyperspectral CCD to obtain a spectrum of the electrode surface;

[0022] (b) a step of visualizing the electrode surface using the spectrum of the electrode surface; and

[0023] (c) a step of quantifying the above visualized electrode surface; including,

[0024] Using the following equation 1, the discrimination coefficient (T) is obtained from the spectrum of the electrode surface obtained in step (a). A / B ) and calculate the discrimination coefficient (T A / B ) is distinguished based on the intensity of brightness of the electrode surface corresponding to the electrode surface, and then the distinguished individual areas are visualized and quantified to analyze the electrode surface.

[0025] <Formula 1>

[0026]

[0027] In the above formula 1, A and B are any different substances present on the electrode surface,

[0028] T A / B is the discrimination coefficient between A and B,

[0029] μ is the average of multiple intensities of brightness corresponding to multiple wavelengths in the electrode surface spectrum, and σ is the deviation of multiple intensities of brightness corresponding to the multiple wavelengths.

[0030] In one embodiment of the present invention, a method for analyzing an electrode surface is provided, wherein A and B are different materials selected from the group consisting of a current collector, an electrode active material layer, and a foreign material, respectively.

[0031] In one embodiment of the present invention, a method for analyzing an electrode surface is provided, wherein the individual zones include a surface zone of a current collector, a surface zone of an electrode active material layer, and a foreign matter zone.

[0032] In one embodiment of the present invention, in step (b), a method for analyzing an electrode surface is provided, wherein visually distinct colors are matched for the individual areas distinguished in step (a), and the individual areas are visualized by implementing them with the matched colors.

[0033] In one embodiment of the present invention, in step (c), a method for analyzing an electrode surface is provided, wherein the electrode surface is quantified by calculating the ratio of pixels of each individual area included in the electrode surface based on the total pixels of the electrode surface visualized in step (b).

[0034] In one embodiment of the present invention, the hyperspectral CCD provides an electrode surface analysis method for precisely inspecting foreign substances in any specific area included in the electrode surface.

[0035] In one embodiment of the present invention, a method for analyzing an electrode surface is provided, wherein the field of view (FOV) of the specific region is an region including a width of 0.1 mm to 5 mm and a length of 0.1 mm to 5 mm.

[0036] In one embodiment of the present invention, a method for analyzing an electrode surface is provided, wherein the electrode is an electrode after an electrode etching process for forming an electrode tab during an electrode manufacturing process.

[0037]

[0038] The present invention also comprises a hyperspectral CCD unit that photographs an electrode surface using a hyperspectral CCD to obtain a spectrum of the electrode surface;

[0039] A visualization unit that visualizes the electrode surface using the spectrum of the electrode surface; and

[0040] An electrode surface analysis system including a quantification unit that quantifies the above visualized electrode surface;

[0041] Using the following equation 1, the discrimination coefficient (T) is obtained from the spectrum of the electrode surface obtained from the hyperspectral CCD section. A / B ) and calculate the discrimination coefficient (T A / B ) is distinguished based on the intensity of brightness of the electrode surface, and then the distinguished individual areas are visualized and quantified to analyze the electrode surface.

[0042] <Formula 1>

[0043]

[0044] In the above formula 1, A and B are any different substances present on the electrode surface,

[0045] T A / B is the discrimination coefficient between A and B,

[0046] μ is the average of multiple intensities of brightness corresponding to multiple wavelengths in the electrode surface spectrum, and σ is the deviation of multiple intensities of brightness corresponding to the multiple wavelengths.

[0047] According to the present invention, the type and amount of foreign substances present on the electrode surface after the etching process for forming electrode tabs during the manufacturing process of secondary battery electrodes can be more precisely analyzed, thereby improving process efficiency and product reliability of the manufactured electrode. Furthermore, the advantage of being able to precisely analyze foreign substances can be utilized to check the performance of equipment used in the etching process, such as an etching laser.

[0048] Figures 1a to 1c are schematic diagrams showing the process of obtaining a discrimination coefficient using Equation 1 from an electrode surface spectrum obtained from a hyperspectral CCD.

[0049] Figure 2 shows the correlation between wavelength and intensity of brightness that can be obtained from an image captured by a hyperspectral CCD.

[0050] Figure 3 shows individual spectra for the current collector surface, electrode active material layer surface, and foreign substances contained in the cathode surface, captured by a hyperspectral CCD.

[0051] Hereinafter, the present invention will be described in more detail to help understand the present invention.

[0052] The terms and words used in this specification and claims should not be interpreted as limited to their usual or dictionary meanings, but should be interpreted as meanings and concepts that conform to the technical idea of ​​the present invention, based on the principle that the inventor can appropriately define the concept of the term to explain his or her own invention in the best way.

[0053] The term “electrode surface analysis” as used herein means detecting or measuring materials forming the electrode surface to derive their types and amounts. In this specification, the electrode subject to electrode surface analysis may be an electrode after an etching process during the electrode manufacturing process. The etching process refers to a process of etching and removing the electrode active material layer from an electrode on which a current collector and an electrode active material layer are formed during the electrode manufacturing process in order to form an electrode tab. Therefore, the electrode surface after the etching process may include the current collector surface, the electrode active material layer surface, and foreign substances. The foreign substances may be binders contained in the electrode active material layer. Ultimately, the electrode surface analysis may be for analyzing the types and amounts of foreign substances contained in the electrode surface. In this case, since the electrode active material layer is formed by being coated on a current collector, it may also be called an electrode coating layer.

[0054]

[0055] Electrode surface analysis method

[0056] The present invention relates to a method for analyzing an electrode surface.

[0057] The electrode surface analysis method according to the present invention is an electrode surface analysis method that analyzes the electrode surface using a hyperspectral CCD (Charge Coupled Device),

[0058] (a) A step of photographing an electrode surface with a hyperspectral CCD to obtain a spectrum of the electrode surface;

[0059] (b) a step of visualizing the electrode surface using the spectrum of the electrode surface; and

[0060] (c) a step of quantifying the above visualized electrode surface; including,

[0061] Using the following equation 1, the discrimination coefficient (T) is obtained from the spectrum of the electrode surface obtained in step (a). A / B ) and calculate the discrimination coefficient (T A / B ) is distinguished based on the intensity of brightness of the electrode surface corresponding to the electrode surface, and then the distinguished individual areas are visualized and quantified to analyze the electrode surface.

[0062] <Formula 1>

[0063]

[0064]

[0065] In the above formula 1, A and B are any different substances present on the electrode surface,

[0066] T A / B is the discrimination coefficient between A and B,

[0067] μ is the average of multiple intensities of brightness corresponding to multiple wavelengths in the electrode surface spectrum, and σ is the deviation of multiple intensities of brightness corresponding to the multiple wavelengths.

[0068] The above A and B may each include different materials selected from the group consisting of a current collector, an electrode active material layer, and a foreign substance. More specifically, the above A and B may each include a surface of a current collector, a surface of an electrode active material, and a foreign substance such as a binder.

[0069]

[0070] In the present invention, in the step (a), the electrode surface is photographed using a hyperspectral CCD, thereby obtaining the spectrum of the electrode surface.

[0071]

[0072] A hyperspectral CCD is a type of camera capable of capturing hyperspectral images (HSI). While RGB has three channels, HSI measures a wide range of wavelengths, sometimes exceeding 200 bands. To achieve this, HSI detects complex features not found in RGB images. While RGB images have only spatial features, HSI possesses both spectral and spatial features, demonstrating superior classification performance. Therefore, HSI can precisely classify even similar colors, making it widely applicable to various fields, including remote sensing.

[0073]

[0074] In one embodiment of the present invention, the hyperspectral CCD is applied to electrode surface analysis, so that the electrode surface can be analyzed more precisely.

[0075] The above hyperspectral CCD includes (i) an optical section that scans and measures a measurement target, (ii) a spectroscopic section that spectroscopically analyzes light received by the optical section, and (iii) a detector that converts the spectroscopic light into a spectrum.

[0076] The above (i) optical section includes an optical lens. Using the optical lens, the electrode surface, which is the measurement target, can be scanned and measured. Light is received from the electrode surface through the optical lens. The wavelength of the light received may vary depending on the properties of the electrode surface, the presence or absence of foreign substances, and their type and amount.

[0077] Additionally, the above (ii) spectroscopic unit includes a dispersive element that disperses light.

[0078] In addition, the above (iii) detection unit is also called a sensor unit and can convert the dispersed light into a spectrum.

[0079]

[0080] In one embodiment of the present invention, the hyperspectral CCD can precisely inspect or measure any specific area included in the electrode surface.

[0081] The field of view (FOV) of the above specific area enables inspection or measurement of a narrow area including 0.1 mm to 5 mm in width and 0.1 mm to 5 mm in height.

[0082] Existing vision cameras have a field of view (FOV) that can only inspect or measure a wide area (400 mm wide and 400 mm high), resulting in poor accuracy. This large field of view (FOV) allows for only a cursory inspection of the presence of residual foreign matter on the electrode surface, making precise analysis of the type and amount of foreign matter difficult.

[0083]

[0084] In the above formula 1 according to one embodiment of the present invention, the electrode surface spectrum may be an integrated spectrum in which individual spectra are superimposed.

[0085] In the above integrated spectrum, there was a problem of reduced accuracy when the measurer arbitrarily selected a discrimination criterion. However, by calculating the discrimination coefficient using Equation 1 and setting it as the discrimination criterion, arbitrary substances contained on the electrode surface can be more precisely distinguished, visualized, and quantified, thereby analyzing the amount and / or type of these arbitrary substances.

[0086] In addition, the above equation 1 can be interpreted as having a higher discrimination coefficient as the difference (gap) in intensity of brightness between the arbitrary materials is greater and the deviation is smaller.

[0087]

[0088] Figures 1a to 1c are schematic diagrams showing the process of obtaining a discrimination coefficient using Equation 1 from an electrode surface spectrum obtained from a hyperspectral CCD.

[0089] Figure 1a shows a graph for calculating the average (μ, Avg.) and deviation (σ, sigma) calculated using multiple intensities corresponding to multiple wavelengths in an electrode surface spectrum obtained from a hyperspectral CCD for an arbitrary material. The arbitrary material is a current collector (Foil), a foreign material (binder), and an electrode active material (Coating). The average and deviation calculated using multiple intensities corresponding to multiple wavelengths can be obtained. The average and deviation calculated using the multiple intensities are substituted into Equation 1 to obtain the discrimination coefficient (T A / B ) can be calculated.

[0090] For example, as shown in Fig. 1a, the wavelengths are divided into regions A, B, C, and D, multiple specific wavelengths are selected within each region, and then multiple luminosities corresponding to the selected wavelengths are used to obtain the average (Avg.) and deviation (Sigma) of the luminosity, and this can be applied to Equation 1 to obtain the discrimination coefficient.

[0091]

[0092] Figure 1b is a graph showing the discrimination coefficient according to wavelength. The discrimination coefficient (T) calculated using multiple luminosities corresponding to the multiple wavelengths A / B ) is shown as a graph.

[0093]

[0094] Figure 1c shows the discrimination coefficient (T) between each random material in the selected wavelength range. A / B ) is a graph showing the final discrimination criteria. The front and back of the foil can be displayed as Shiny and Matt, respectively. Therefore, Binder_shiny, Coating_shiny, and Foil_shiny represent the Binder and Coating based on the front of the foil.

[0095]

[0096] In one embodiment of the present invention, the electrode surface can be divided into individual zones based on the discrimination coefficient. For example, the individual zones divided on the electrode surface may include a surface zone of a current collector, a surface zone of an electrode active material layer, and a foreign matter zone.

[0097]

[0098] In the present invention, in the step (b), the electrode surface can be visualized using the spectrum of the electrode surface.

[0099] Different visually distinct colors can be matched to the individual areas identified in step (a) above. The matching colors are not limited to specific colors, and are not particularly limited as long as the individual areas are visually distinct colors.

[0100] Here, the visualization refers to implementing individual areas of the electrode surface, each of which is matched with a different color, with the matching color. The visualization can be implemented using a visualization software program, and is not particularly limited as long as it is a software program driven by logic capable of implementing each individual area on the electrode surface, distinguished by a discrimination criterion, with the matching color.

[0101]

[0102] In the present invention, in the step (c), the visualized electrode surface can be quantified.

[0103] Specifically, the electrode surface can be quantified by calculating the ratio of pixels corresponding to each individual zone based on the total pixels of the visualized electrode surface. In particular, the amount of each foreign substance remaining on the electrode surface can be obtained by calculating the ratio of pixels included in the individual zones corresponding to the identified foreign substances.

[0104] The above quantification can be performed by a quantification software program, and is not particularly limited as long as it is a software program driven by logic that calculates the ratio of pixels corresponding to each component based on the entire pixels of the electrode surface.

[0105]

[0106] Electrode Surface Analysis System

[0107] The present invention also relates to an electrode surface analysis system.

[0108] The electrode surface analysis system according to the present invention comprises: a hyperspectral CCD unit for photographing an electrode surface; a visualization unit for visualizing the electrode surface using a spectrum of the electrode surface photographed by the hyperspectral CCD; and a quantification unit for quantifying the visualized electrode surface.

[0109] Using the following equation 1, the discrimination coefficient (T) is obtained from the spectrum of the electrode surface obtained from the hyperspectral CCD section.A / B ) and calculate the discrimination coefficient (T A / B ) may be used to analyze the electrode surface by dividing the electrode surface based on the intensity of brightness of the electrode surface corresponding to the electrode surface, and then visualizing and quantifying the divided individual areas:

[0110] <Formula 1>

[0111]

[0112] In the above formula 1, A and B are any different substances present on the electrode surface,

[0113] T A / B is the discrimination coefficient between A and B,

[0114] μ is the average of multiple intensities of brightness corresponding to multiple wavelengths in the electrode surface spectrum, and σ is the deviation of multiple intensities of brightness corresponding to the multiple wavelengths.

[0115]

[0116] The above hyperspectral CCD unit may include a hyperspectral CCD.

[0117] In addition, the visualization unit may include a visualization software program, and is not particularly limited as long as it is a software program driven by logic that can implement the area of ​​each component distinguished by a discrimination criterion on the electrode surface with a matching color.

[0118] In addition, the quantification unit may include a quantification software program, and is not particularly limited as long as it is a software program driven by logic that calculates the ratio of pixels corresponding to each component based on the entire pixels of the electrode surface.

[0119]

[0120] According to a preferred embodiment of the present invention, since the correlation between wavelength and intensity of brightness can be obtained from an image captured by a hyperspectral CCD (Fig. 2), the spectrum of the cathode surface was secured and analyzed as follows using this. At this time, the correlation between wavelength and intensity of brightness is also called the spectrum of pixels.

[0121]

[0122] (1) Acquisition of spectrum for the cathode surface

[0123] Using a hyperspectral CCD (Hyper Spectral Camera, Mitutoyo Corporation), the surface of the electrode after the etching process for forming an electrode tab during the electrode manufacturing process was photographed. The electrode is a negative electrode and includes a Cu current collector and a negative electrode active material layer formed on one surface of the Cu current collector. The surface of the negative electrode includes the surface of the Cu current collector (bare foil), a binder separated from the negative electrode active material layer (binder residue), and a negative electrode active material layer (coating).

[0124] From the cathode surface images captured by the hyperspectral CCD, individual spectra were obtained for the bare foil, binder residue, and coating (Fig. 3). The individual spectra were implemented as boxplot spectra by securing raw data extracted from the hyperspectral CCD images. The microscope images were captured using an optical microscope, and the single wavelength images were captured using a single wavelength spectrophotometer.

[0125]

[0126] (2) Establishment of classification criteria for foreign substances on the cathode surface

[0127] After obtaining an integrated spectrum by integrating the individual spectra of the bare foil, binder residue, and coating, the discrimination coefficient was calculated using Equation 1 above.

[0128] First, in the individual spectra included in the integrated spectrum of the electrode surface, the average (μ) and deviation (σ) of the luminosity were calculated using multiple luminosities corresponding to multiple wavelengths. Using the luminosities corresponding to the multiple wavelengths, the average (μ) and deviation (σ) of the luminosity were obtained, respectively, and then applied to the above equation 1 to obtain multiple discrimination coefficients (T A / B ) was calculated.

[0129]

[0130] The above multiple discrimination coefficients (T A / B ) was selected as the wavelength region corresponding to the discrimination coefficient corresponding to the largest value, and the average luminosity value or median luminosity value of the luminosity region corresponding to the wavelength region was used as the discrimination criterion (threshold).

[0131]

[0132] For example, the final selected discrimination criteria are foil > 1.2, 1.2 > binder > 0.8, 0.9 > coating.

[0133] The cathode surface was classified using the above discrimination criteria.

[0134]

[0135] Table 1 below is a classification table of cathode surfaces classified using the above discrimination criteria.

[0136]

[0137] Cathode surface classification criteria foilfoil > 1.2binder1.2 > binder > 0.8coating0.9 > coating

[0138]

[0139] As shown in Table 1 above, based on the above discrimination criteria, the cathode surface and its matching color can be defined. The color is not particularly limited as long as it is a color that can visually distinguish the cathode surface classified by the discrimination criteria.

[0140]

[0141] (3) Visualization of the cathode surface

[0142] The cathode surface, including individual zones distinguished by the above-mentioned discrimination criteria, and the corresponding colors were used to visualize the cathode surface. The visualization was performed using a software program driven by logic capable of expressing the visualization target, i.e., the individual zones, in specific colors.

[0143]

[0144] (4) Quantification of the cathode surface

[0145] The quantification method measured the number of pixels corresponding to Bare Foil, Binder Residue, and Coating on the visualized cathode surface, and then calculated the ratio included in the total number of pixels on the cathode surface. At this time, the quantification was performed using a software program driven by logic capable of calculating the ratio of pixels corresponding to a specific area included in the quantification target, i.e., an individual area, to the total number of pixels on the cathode surface, i.e., the target of quantification.

[0146] Table 2 below quantifies the cathode surface, including individual areas: bare foil, binder, and coating. Noise is an indistinguishable substance, and the discrimination ability is low because it attempts to discriminate between materials in wavelengths where the luminosity difference between materials is not significant.

[0147]

[0148] Pixel quantity(number)Ratio(%)foil1,047,71399.94Binder6780.06Coating00.00Total1,048,391100.0Noise: 0.06%

[0149]

[0150] As a comparative implementation example according to the present invention, an electrode surface analysis was performed in the same manner as the above implementation example, except that instead of the discrimination coefficient calculated using the above equation 1, the measurer arbitrarily used an area where the difference in brightness between the foil, binder, and coating was large as a discrimination criterion from the electrode surface integrated spectrum.

[0151]

[0152] Pixel quantity(number)Ratio(%)foil1,046,40299.79Binder2,1740.06Coating00.00Total1,048,576100.0Noise: 0.21%

[0153]

[0154] Referring to Tables 2 and 3 above, it can be seen that the noise occurrence rate of Example 1, in which electrode surface analysis was performed using the discrimination coefficient calculated from Equation 1, was reduced.

[0155]

[0156] Although the present invention has been described above with reference to limited embodiments and drawings, the present invention is not limited thereto, and it is obvious that various modifications and variations are possible within the scope of the technical idea of ​​the present invention and the equivalent scope of the patent claims to be described below by a person having ordinary skill in the art to which the present invention pertains.

Claims

1. An electrode surface analysis method that analyzes the electrode surface using a hyperspectral CCD (Charge Coupled Device). (a) A step of photographing an electrode surface with a hyperspectral CCD to obtain a spectrum of the electrode surface; (b) a step of visualizing the electrode surface using the spectrum of the electrode surface; and (c) a step of quantifying the above visualized electrode surface; including, Using the following equation 1, the discrimination coefficient (T) is obtained from the spectrum of the electrode surface obtained in step (a). A / B ) and calculate the discrimination coefficient (T A / B ) is divided into electrode surfaces based on the intensity of brightness of the electrode surface corresponding to the electrode surface, and then the divided individual areas are visualized and quantified to analyze the electrode surface. <Formula 1> In the above formula 1, A and B are any different substances present on the electrode surface, T A / B is the discrimination coefficient between A and B, μ is the average of multiple intensities of brightness corresponding to multiple wavelengths in the electrode surface spectrum, and σ is the deviation of multiple intensities of brightness corresponding to the multiple wavelengths.

2. In paragraph 1, An electrode surface analysis method, wherein the above A and B are different materials selected from the group consisting of a current collector, an electrode active material layer, and a foreign substance, respectively.

3. In paragraph 1, An electrode surface analysis method, wherein the individual zones include a surface zone of the current collector, a surface zone of the electrode active material layer, and a foreign matter zone.

4. In paragraph 1, In the step (b), a method for analyzing an electrode surface is provided, wherein different visually distinct colors are matched for the individual areas distinguished in the step (a), and the individual areas are visualized by implementing them with the matched colors.

5. In paragraph 1, An electrode surface analysis method in which, in step (c), the electrode surface is quantified by calculating the ratio of pixels of each individual area included in the electrode surface based on the total pixels of the electrode surface visualized in step (b).

6. In paragraph 1, The above hyperspectral CCD is a method for analyzing an electrode surface, which precisely inspects any specific area included in the electrode surface for foreign substances.

7. In paragraph 6, A method for analyzing an electrode surface, wherein the field of view (FOV) of the above specific area is an area including 0.1 mm to 5 mm in width and 0.1 mm to 5 mm in height.

8. In paragraph 1, A method for analyzing an electrode surface, wherein the above electrode is an electrode after an electrode etching process for forming an electrode tab during an electrode manufacturing process.

9. A hyperspectral CCD section that photographs the electrode surface using a hyperspectral CCD and obtains a spectrum of the electrode surface; A visualization unit that visualizes the electrode surface using the spectrum of the electrode surface; and An electrode surface analysis system including a quantification unit that quantifies the above visualized electrode surface; Using the following equation 1, the discrimination coefficient (T) is obtained from the spectrum of the electrode surface obtained from the hyperspectral CCD section. A / B ) and calculate the discrimination coefficient (T A / B ) is a system for analyzing an electrode surface by visualizing and quantifying the distinguished individual areas after distinguishing the electrode surface based on the intensity of brightness of the electrode surface corresponding to the electrode surface: <Formula 1> In the above formula 1, A and B are any different substances present on the electrode surface, T A / B is the discrimination coefficient between A and B, μ is the average of multiple intensities of brightness corresponding to multiple wavelengths in the electrode surface spectrum, and σ is the deviation of multiple intensities of brightness corresponding to the multiple wavelengths.

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