Inspection methods, inspection equipment, and programs

Abstract

This invention provides an inspection method, inspection apparatus, and program that can streamline the determination of the state of a mixture. [Solution] An inspection method performed by an inspection device 3, comprising the steps of: acquiring data of an image of a mixture M obtained by mixing a fibrous auxiliary agent and an active material; quantifying the color tone of each pixel of the image data in multiple gradations; determining whether the numerical value based on the color tone of the pixels is less than the maximum value of a predetermined reference value and greater than or equal to the minimum value of a reference value, and determining that the mixture M is a good product if the numerical value is less than the maximum value of a reference value and greater than or equal to the minimum value of a reference value.

Description

Technical Field

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[0001] The present invention relates to an inspection method, an inspection apparatus, and a program.

Background Art

[0002] The electrodes of a solid-state battery are manufactured by applying a mixture of an active material, a conductive aid, a thickener, a binder (adhesive, bonding agent), etc. to a current collector, which is a metal foil, and drying it. The conductive aid may be not only a particulate conductive material but also a fibrous conductive material. For example, Patent Document 1 discloses a technique for forming a positive electrode layer using vapor-grown carbon fibers as the conductive aid.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] When manufacturing the electrodes of a solid-state battery, since the negative electrode active material constituting the negative electrode often uses a carbon-based material, conductivity can be ensured. However, since the positive electrode active material constituting the positive electrode often uses a transition metal compound with poor conductivity, it is necessary to add a conductive aid to ensure conductivity. There are fibrous conductive aids such as carbon fibers for the conductive aid. However, when mixing with the positive electrode active material by dry mixing, if the mixing is excessive, the fibers of the conductive aid will be cut in some places, and the resistance value of the mixture will increase compared to the case where the fibers of the conductive aid are not cut. Therefore, it is desirable to be able to quickly check the state of the mixture after mixing.

[0005] Patent Document 1 discloses a method for checking the state of gas-phase carbon fibers, which are conductive additives, by measuring the contact angle using the surface tension of a water droplet dropped onto the surface of a pellet hardened with gas-phase carbon fibers. However, the contact angle measurement procedure is complicated and places a heavy burden on workers. Patent Document 1 also discloses other methods besides contact angle measurement, such as measuring the internal resistance and observing the cross-section using an SEM (Scanning Electron Microscope). However, since all of these are performed after the manufacture of the battery cell, it is not possible to quickly check the state of the mixture after mixing. Therefore, if the conductive additive fibers break due to overmixing and the resistance value changes, it is difficult for workers to notice this change before the manufacture of the battery cell.

[0006] This invention has been made in view of the above circumstances, and aims to provide an inspection method, inspection apparatus, and program that can efficiently determine the state of a mixture. [Means for solving the problem]

[0007] To achieve the above objective, the inspection method according to the present invention is an inspection method performed by an inspection device, comprising the steps of: acquiring data of an image of a mixture of a fibrous auxiliary agent and an active material; quantifying the color tone of each pixel of the image data in multiple gradations; determining whether the numerical value based on the color tone of the pixels is less than the maximum value of a predetermined reference value and greater than or equal to the minimum value of a reference value, and determining that the mixture is a good product if the numerical value is less than the maximum value of a reference value and greater than or equal to the minimum value of a reference value. [Effects of the Invention]

[0008] According to the present invention, the inspection method can efficiently determine the state of a mixture. [Brief explanation of the drawing]

[0009] [Figure 1]This is a configuration diagram showing the configuration of the inspection system according to Embodiment 1. [Figure 2] This is an explanatory diagram for illustrating the color tone of an image captured by imaging a mixture according to Embodiment 1. [Figure 3A] This graph shows the relationship between the color tone and resistivity of the mixture according to Embodiment 1. [Figure 3B] This is an explanatory diagram illustrating a well-mixed mixture according to Embodiment 1. [Figure 3C] This is an explanatory diagram illustrating the mixture of materials without any mixing according to Embodiment 1. [Figure 3D] This is an explanatory diagram illustrating a mixture containing a fibrous conductive additive that has been broken due to overmixing of the materials according to Embodiment 1. [Figure 3E] This is an explanatory diagram illustrating a mixture that is even more overmixed than the mixture shown in Figure 3D. [Figure 4] This is a flowchart showing the mixture inspection process according to Embodiment 1. [Figure 5] This is a flowchart showing the image determination process according to Embodiment 1. [Figure 6] This is a configuration diagram showing the configuration of the inspection system according to Embodiment 2. [Figure 7A] This is an explanatory diagram illustrating the imaging of the mixture according to Embodiment 2 before and after stretching. [Figure 7B] This is an explanatory diagram illustrating the process of imaging a mixture according to Embodiment 2 after stretching it. [Figure 8A] This is an explanatory diagram illustrating the process of photographing a slurry of a mixture applied to a metal foil according to Embodiment 2 after it has dried. [Figure 8B] This is an explanatory diagram illustrating the imaging of the mixture according to Embodiment 2 before stretching. [Figure 9] This is a flowchart showing the electrode inspection process according to Embodiment 2. [Modes for carrying out the invention]

[0010] (Embodiment 1) Referring to the drawings, the inspection system according to Embodiment 1 will be described. In each drawing, the same or equivalent parts are denoted by the same reference numerals.

[0011] Since the positive electrode active material constituting the positive electrode of a solid-state battery often uses a transition metal compound with poor conductivity, it is necessary to add a conductive assistant to ensure conductivity. When using a fibrous conductive assistant, the color of the mixture is different between the case where the fibers of the conductive assistant are not cut due to appropriate mixing and the case where the fibers of the conductive assistant are partly cut due to overmixing. Therefore, as a result of earnest efforts, the present inventor has found that there is a correlation between the color of the mixture and the resistivity, and has come to the idea that it is possible to determine whether the mixture is good or bad by using the color tone of the image obtained by imaging the mixture, leading to the present invention.

[0012] FIG. 1 is a configuration diagram showing the configuration of an inspection system 100 according to Embodiment 1. The inspection system 100 is a system capable of inspecting a mixture when materials for producing a positive electrode are dry-mixed, and includes a mixing device 1, an imaging device ②, and an inspection device 3. The mixing device 1 dry-mixes each material such as a positive electrode active material, a fibrous conductive assistant, and a binder (a binder, an adhesive) for producing a positive electrode to produce a mixture M. For example, as the positive electrode active material, a layered oxide such as LiCoO2, a spinel-type oxide such as LiMn2O4, a polyanion oxide of LiFePO4, etc. can be used, and as the fibrous conductive assistant, a single substance such as carbon nanofiber, carbon fiber, or a mixture with other materials can be used, and as the binder, polyvinylidene fluoride, PTFE (Polytetrafluoroethylene), etc. can be used. By performing dry mixing with the mixing device 1, the number of trial production steps when prototyping the mixture M can be reduced.

[0013] The imaging device 2 is a device that images the mixture M mixed by the mixing device 1. The imaging device 2 can be configured using a camera using an imaging element such as a CCD (Charge Coupled Device) or a CMOS (Complementary Metal Oxide Semiconductor) image sensor, a video camera, or the like.

[0014] The inspection device 3 includes a connection part 31, a display part 32, an operation input part 33, a storage part 34, and a control part 35. The connection part 31 is, for example, a connection interface capable of transmitting and receiving data such as Bluetooth (registered trademark) and USB (Universal Serial Bus). The connection part 31 is connected to the mixing device 1 and receives information such as the mixing method executed by the mixing device 1 and the type of the produced mixture M (for the positive electrode, for the negative electrode). Further, the connection part 31 is connected to the imaging device 2 and receives the image data of the mixture M imaged by the imaging device 2. The display part 32 displays various data, images, etc. according to the input by the operation input part 33 or the instruction from the control part 35. The display part 32 can be configured using a display device such as a liquid crystal display or an organic EL (Electro-Luminescence) display. The operation input part 33 is a user interface that receives instructions and operation inputs from the user, and can be configured by, for example, a push button switch or a touch panel integrated with the display part 32.

[0015] The storage part 34 stores data and programs necessary for the processing executed by the control part 35, including threshold data 341. The storage part 34 can be configured using, for example, a RAM (Random Access Memory), a ROM (Read Only Memory), a flash memory, or the like. The threshold data 341 is data of a determination threshold for determining whether the mixture M to be inspected is good or bad, and is created in advance before inspection based on the data of the mixture M with good mixing condition.

[0016] The control unit 35 can be composed of a processor such as a CPU (Central Processing Unit) or a DSP (Digital Signal Processor). The control unit 35 functions as an image acquisition unit 351, an image processing unit 352, and an image determination unit 353 by executing a program stored in the storage unit 34. The image acquisition unit 351 acquires image data of the mixture M from the imaging device 2 via the connection unit 31. The image processing unit 352 digitizes the image data of the mixture M acquired by the image acquisition unit 351 in pixel units. The more pixels in the image the better the accuracy of the determination, but any number of pixels appropriate for the determination is acceptable. The image determination unit 353 compares the numerical values ​​of the image of the mixture M digitized by the image processing unit 352 with threshold data 341 to determine whether the mixture M is good or bad.

[0017] The imaging device 2 may directly image the powder mixture M placed on paper, a table, etc., or it may image the powder mixture M placed in a container such as a bottle or petri dish. As shown in Figure 2, imaging by the imaging device 2 is performed using a grayscale representing 256 shades of gray from black (0) to white (255). This allows for the digitization of each pixel in the image 21 of the image of the mixture M, and the resistivity of the mixture M can be predicted based on the color of each pixel. Note that the color image may be converted to grayscale, and this conversion to grayscale may be performed by either the imaging device 2 or the inspection device 3. Furthermore, the number of gradations may be other than 16 gradations, as long as there are multiple levels of gradation. Also, the gradation may be the same as that of a color image.

[0018] The captured image 21 includes an image S of the mixture M, and a black reference image CB and a white reference image CW that serve as references for the black (0) and white (255) color tones. The black reference image CB and the white reference image CW are predetermined standard colors and can be used to calibrate the color tone of the image S of the mixture M. For example, by imaging black paper and white paper together with the mixture M, the captured image 21 can include the image S of the mixture M, the black reference image CB, and the white reference image CW. This makes it possible to obtain an captured image 21 without differences between each image, even if the imaging location, the type of light source at the time of imaging (natural light, indoor light, etc.), and the amount of light differ. Therefore, captured images 21 can be compared using the same standard.

[0019] The inventors have found, through experiments, that there is a correlation between the color tone and resistivity of mixture M, as shown in Figure 3A. The graph in Figure 3A has the color tone of mixture M on the horizontal axis and the resistivity of mixture M on the vertical axis. The resistivity of mixture M is low (approaching 0) when the mixing is good and high (greater than 0) when the mixing is poor. Therefore, by examining the color tone of mixture M, which correlates with resistivity, it is possible to determine whether mixture M is good or bad. For example, in the graph shown in Figure 3A, the range of color tones of mixture M in which the resistivity is less than or equal to the reference resistivity (the resistivity when mixture M is well mixed), for example, 10% before and after the reference color tone, can be set as the upper and lower limits of the reference value (normal range), and by determining whether or not it falls within the range between the upper and lower limits of the reference value (whether or not it falls within the normal range), it is possible to determine whether mixture M is good or bad. Note that the upper and lower limits of the reference value may be values ​​obtained by adding or dividing the reference value by an acceptable error.

[0020] The upper and lower limits (normal range) of the reference values ​​for determining the quality of mixture M are created in advance before inspection based on data for a well-mixed mixture M. Figure 3B shows a mixture M in which each material, such as the positive electrode active material, fibrous conductive additive, and binder (adhesive), is well mixed. In this case, the particles of the positive electrode active material and binder, and the fibers of the conductive additive are evenly distributed throughout the mixture M. For example, among the numerical values ​​of each pixel of the image S of mixture M contained in the captured image 21 of this mixture M, the color tone of mixture M in which the resistivity is less than or equal to the reference resistivity is set as the reference value, and the upper and lower limits (normal range) are set within 10% before and after this value.

[0021] However, as shown in Figure 3C, the mixing of each material is uneven, and the mixture M may contain areas where each material is well mixed, areas where the mixing is insufficient, and areas where particles such as the positive electrode active material and binder, and fibers of the conductive additive, have solidified. In this case, when each pixel of the image 21 of the mixture M is quantified, the numerical values ​​for the areas where each material is well mixed will be similar to the values ​​within the range from the upper to lower limit of the reference value (the range of colors in which the resistivity of a well-mixed mixture M is below the reference resistivity). However, the areas where the mixing is insufficient and the areas where particles such as the positive electrode active material and fibers of the conductive additive have solidified will be closer in color to the particles such as the positive electrode active material or fibers of the conductive additive than in the case of good mixing, and may not fall within the range from the upper to lower limit of the reference value (normal range). In particular, the areas where particles such as the positive electrode active material and fibers of the conductive additive have solidified will have numerical values ​​that represent the color of the particles such as the positive electrode active material and the conductive additive itself.

[0022] For example, if the color of the conductive additive is closer to black (0) than the color of the well-mixed parts of the materials, the color value of the solidified conductive additive fibers will be lower than the lower limit of the standard. Also, if the color of the particles of the positive electrode active material, etc., is closer to white (255) than the color of the well-mixed parts of the materials, the color value of the particles of the positive electrode active material, etc., will be higher than the upper limit of the standard. Furthermore, the color of the poorly mixed parts will be closer to black (0) than the color of the well-mixed parts of the materials, depending on the ratio of each material contained, and the color value will be lower than the lower limit of the standard. Alternatively, depending on the ratio of each material contained, the color will be closer to white (255) than the color of the well-mixed parts of the materials, and the color value will be higher than the upper limit of the standard.

[0023] However, even if there are inconsistencies in how the materials are mixed, if the inconsistencies are small and within an acceptable range, the mixture M with inconsistencies can be treated in the same way as a mixture with good mixing. Therefore, the upper limit of the acceptable range (the maximum value that the reference value can take) is set by adding a predetermined value (for example, 10% of the upper limit) to the upper limit of the reference value, and the lower limit of the acceptable range (the minimum value that the reference value can take) is set by subtracting a predetermined value (for example, 10% of the lower limit) from the lower limit of the reference value. Then, it is determined whether the maximum value of the color numerical value of mixture M is equal to or greater than the maximum value of the reference value, or whether the color numerical value of mixture M is less than the minimum value of the reference value. Furthermore, it is determined whether the proportion of numerical values ​​obtained by quantifying each pixel of the captured image 21 of mixture M that is equal to or greater than the upper limit of the reference value (upper limit of the normal range) (for example, 10% of the total), or whether the proportion that is less than the lower limit of the reference value (lower limit of the normal range) is equal to or greater than a predetermined proportion (for example, 10% of the total). This makes it possible to determine whether the mixing is good or not.

[0024] Furthermore, as shown in the mixture M in Figure 3D, overmixing can cause the conductive additive fibers to partially break, and as shown in the mixture M in Figure 3E, even more overmixing than in Figure 3D can cause the conductive additive fibers to become pulverized. In these cases, the color of the mixture M will be close to the color of the conductive additive itself. If the color of the conductive additive is close to black (0), for example, the color of the mixture M will be black overall. When the color of the mixture M is close to black (0), the color value will be smaller than the lower limit of the standard value. In this case, by determining whether the minimum value of the color of the mixture M is greater than or equal to the minimum value of the standard value (lower limit of the acceptable range), it is possible to determine whether the conductive additive fibers are partially broken or pulverized. Therefore, it is not necessary to measure the properties (good / bad) of the mixture M in the state of the battery cell, and the properties can be evaluated while it is still in powder form. This reduces the evaluation man-hours required to evaluate the battery cell.

[0025] Next, the mixture inspection process performed by the inspection device 3 will be explained below with reference to the flowcharts shown in Figures 4 and 5. The mixture inspection process is stored as a mixture inspection process program in the storage unit 34 of the inspection device 3, and is activated, for example, by the user tapping an icon associated with the mixture inspection process program displayed on the display unit 32 using the operation input unit 33.

[0026] In Figure 4, the image determination unit 353 of the control unit 35 of the inspection device 3 acquires information on the type of mixture M and the mixing method from the mixing device 1 connected to the connection unit 31 (step S101). The information on the type of mixture M and the mixing method is information that the user input to the mixing device 1 when preparing the mixture M, and is held by the mixing device 1. Alternatively, the user may input the information on the type of mixture M and the mixing method to the inspection device 3. Alternatively, a label printed with the information on the type of mixture M and the mixing method may be attached to the paper or table on which the powder of mixture M is placed, or to the container containing the powder, and read by the imaging device 2. Alternatively, the information on the type of mixture M and the mixing method may be printed directly on the paper or table on which the powder of mixture M is placed, or to the container containing the powder.

[0027] The image determination unit 353 determines whether the mixture M is for use as a positive electrode (step S102). If it is for use as a positive electrode (step S102; YES), the image determination unit 353 determines whether the mixing method of the mixture M is dry mixing or not (step S103). If the mixing method of the mixture M is dry mixing (step S103; YES), the image acquisition unit 351 of the control unit 35 of the inspection device 3 acquires the data of the captured image 21 of the mixture M from the imaging device 2 connected to the connection unit 31 (step S104). The method by which the image acquisition unit 351 acquires the data of the captured image 21 of the mixture M may be via a recording medium, a network, etc. Any method is acceptable as long as the data of the captured image 21 can be input to the inspection device 3 as a result.

[0028] The image processing unit 352 of the control unit 35 of the inspection apparatus 3 shown in Figure 1 digitizes the data of the captured image 21 on a pixel-by-pixel basis (step S105). This allows the image processing unit 352 to obtain a numerical value for each pixel. The image determination unit 353 of the control unit 35 performs image determination processing (step S106). The image determination processing will be explained with reference to the flowchart shown in Figure 5.

[0029] The image determination unit 353 acquires threshold data 341 from the storage unit 34 of the inspection device 3 (step S201). The threshold data 341 is created in advance before inspection based on data of a mixture M with good mixing. For example, the threshold data 341 is created by using the color tone of the mixture M in which the resistivity is less than or equal to the reference resistivity as the reference value, among the numerical values ​​of each pixel of the image S of the mixture M included in the captured image 21 of the mixture M with good mixing, and setting the upper and lower limits (normal range) as 10% before and after the reference value. Furthermore, the threshold data 341 sets the maximum value of the reference value (upper limit of the acceptable range) by adding a predetermined value (for example, 10% of the upper limit) to the upper limit of the reference value, and the minimum value of the reference value (lower limit of the acceptable range) by subtracting a predetermined value (for example, 10% of the lower limit) from the lower limit of the reference value. Furthermore, threshold data 341 also defines the percentage of values ​​that are above the upper limit of the reference value (for example, 10% of the total) and the percentage of values ​​that are below the lower limit (for example, 10% of the total).

[0030] The image determination unit 353 determines whether the maximum value of all pixels in the image S of the mixture M contained in the data of the captured image 21, which was digitized by the image processing unit 352 in step S105 of Figure 4, is less than the maximum value of the reference value (step S202). In other words, this determination determines whether the pixels in the image S of the mixture M to be determined contain pixels that are too white compared to a mixture M with good mixing. If the maximum value of all pixels in the image S of the mixture M contained in the data of the captured image 21 is greater than or equal to the maximum value of the reference value (step S202; NO), that is, the pixels in the image S of the mixture M contain pixels that are too white, and the image determination unit 353 sets the determination result for the mixture M to "poor" (step S203). Also, if the maximum value of all pixels in the image S of the mixture M contained in the data of the captured image 21 is less than the maximum value of the reference value (step S202; YES), the image determination unit 353 determines whether the minimum value of all pixels in the image S of the mixture M contained in the data of the captured image 21 is greater than or equal to the minimum value of the reference value (step S204). In other words, this determination determines whether the pixels in the image S of the mixture M being evaluated contain pixels that are too dark compared to a mixture M with good mixing. This makes it possible to detect cases where the conductive additive fibers are partially broken due to overmixing, as shown in Figure 3D, or cases where the conductive additive fibers are completely pulverized due to even more overmixing than in Figure 3D, as shown in Figure 3E.

[0031] If the minimum value of all pixels in the image S of mixture M contained in the data of the captured image 21 is less than the minimum value of the reference value (step S204; NO), that is, if the pixels in the image S of mixture M contain pixels that are too black, the image determination unit 353 sets the determination result of mixture M to "poor" (step S203). Also, if the minimum value of all pixels in the image S of mixture M contained in the data of the captured image 21 is greater than or equal to the minimum value of the reference value (step S204; YES), the image determination unit 353 determines whether the proportion of the total numerical values ​​of all pixels in the image S of mixture M contained in the data of the captured image 21 that are greater than or equal to the upper limit of the reference value is less than a predetermined proportion set in the threshold data 341 (step S205). In other words, this determination determines whether the portion of pixels in the image S of mixture M to be determined that is too white compared to a well-mixed mixture M, i.e., the portion that is not mixed, is less than a predetermined proportion (for example, 10% of the total). This makes it possible to determine when there is unevenness in the mixing of each material, as shown in Figure 3C.

[0032] If the proportion of the numerical values ​​of all pixels in the image S of the mixture M contained in the data of the captured image 21 that are above the upper limit of the reference value is a predetermined proportion (step S205; NO), that is, if there is a predetermined proportion (for example, 10% of the total) or more of pixels in the image S of the mixture M to be judged that are too white (unmixed), the image judgment unit 353 sets the judgment result of the mixture M to "poor" (step S203). Also, if the proportion of the numerical values ​​of the data of the captured image 21 that are above the upper limit of the reference value is less than a predetermined proportion (step S205; YES), that is, if there is a predetermined proportion (for example, 10% of the total) of pixels in the image S of the mixture M to be judged that are too white (unmixed), the image judgment unit 353 determines whether the proportion of the numerical values ​​of all pixels in the image S of the mixture M contained in the data of the captured image 21 that are below the lower limit of the reference value is less than a predetermined proportion set in the threshold data 341 (step S206). In other words, this determination checks whether the pixels in the image S of the mixture M being evaluated contain more pixels that are too dark than those of a well-mixed mixture M, i.e., unmixed areas, which make up a predetermined percentage (for example, 10% of the total). This allows for the detection of uneven mixing of each material, as shown in Figure 3C.

[0033] If the proportion of the total pixel values ​​of the image S of mixture M contained in the data of the captured image 21 that are below the lower limit of the reference value is greater than or equal to a predetermined proportion (step S206; NO), that is, if there is a predetermined proportion (for example, 10% of the total) or more of pixels in the image S of mixture M to be judged that are too black (unmixed parts), the image judgment unit 353 sets the judgment result of mixture M to "defective product" (step S203). Also, if the proportion of the total pixel values ​​of the image S of mixture M contained in the data of the captured image 21 that are below the lower limit of the reference value is less than a predetermined proportion (step S206; YES), the image judgment unit 353 sets the judgment result of mixture M to "good product" (step S207). The image judgment unit 353 terminates the image judgment process.

[0034] Now, we return to Figure 4. The image determination unit 353 displays the determination result set in the image determination process in step S106 on the display unit 32 of the inspection device 3 (step S107). Also, if in step S102 the mixture M is not for the positive electrode (step S102; NO), or if in step S103 the mixing method of the mixture M is not dry mixing (step S103; NO), the image determination unit 353 sets the determination result to "determination impossible" (step S108). The image determination unit 353 displays the determination result on the display unit 32 of the inspection device 3 (step S107).

[0035] As described above, in Embodiment 1, the data of the image 21 of the powder mixture M to be inspected, captured by the imaging device 2, is quantified in grayscale, and the mixing state of the mixture M can be confirmed based on the numerical value, thereby determining whether the mixture M is good or bad. Therefore, since the color of the mixture M can be evaluated numerically, the determination of the state of the mixture M can be made more efficient. Furthermore, since the mixing state of the mixture M can be confirmed while it is still in powder form, without forming a positive electrode or battery cell with the mixture M, the good or bad state of the mixture M can be determined without evaluating the characteristics of the positive electrode or battery cell. Consequently, the prototyping and evaluation man-hours for the positive electrode and battery cell can be reduced.

[0036] Furthermore, by including the image S of the mixture M and the black reference image CB and white reference image CW, which serve as the basis for the black (0) and white (255) color tones, the captured image 21 can be obtained without differences between each image, even if the imaging location, the type of light source at the time of imaging (natural light, indoor light, etc.), and the amount of light differ. Therefore, even if the environment and timing of the capture of the captured image 21 differ, the captured images 21 can be compared using the same criteria.

[0037] (Embodiment 2) In Embodiment 1, the quality of the mixture M was determined by checking its mixing state while it was still in powder form. However, the quality of the mixture M can also be determined by the electrode formed from the mixture M. Figure 6 shows the configuration of the inspection system 100A according to Embodiment 2. The inspection system 100A includes a mixing device 1, an inspection device 3, and an electrode forming device 4. The electrode forming device 4 is a device that forms a positive electrode using the mixture M mixed in the mixing device 1. The electrode forming device 4 is equipped with a first imaging device 2a and a second imaging device 2b, which can image the positive electrode to be formed.

[0038] In the electrode forming apparatus 4, as shown in Figure 7A, the mixture M prepared in the mixing apparatus 1 is stretched by a roller R to form a positive electrode E. When forming the positive electrode E, the mixture M is imaged by the first imaging device 2a before stretching, and the positive electrode E formed after stretching is imaged by the second imaging device 2b. Alternatively, as shown in Figure 7B, the mixture M may not be imaged by the first imaging device 2a before stretching, and the positive electrode E formed after stretching may be imaged by the second imaging device 2b. Furthermore, it is not necessary to image the mixture M with the first imaging device 2a before stretching and then image the positive electrode E formed after stretching with the second imaging device 2b.

[0039] Furthermore, in the electrode forming apparatus 4, as shown in Figure 8A, the powder of mixture M, a thickener such as carboxymethylcellulose, and a solvent are wet-mixed to produce a slurry MS. The solvent may or may not contain a dispersion medium to disperse the mixture M. The slurry MS is coated onto the current collector foil F and dried to form the electrode layer MD for the positive electrode. In this case, the electrode layer MD formed after drying is imaged by the first imaging device 2a. However, imaging may also be performed by the second imaging device 2b. Alternatively, in the electrode forming apparatus 4, as shown in Figure 8B, the electrode layer MD for the positive electrode may be further stretched with a roller R after drying to form the electrode layer MD for the positive electrode. In this case, the electrode layer MD formed after stretching is imaged by the first imaging device 2a. However, imaging may also be performed by the second imaging device 2b.

[0040] Next, the electrode inspection process performed by the inspection device 3 will be explained below with reference to the flowchart shown in Figure 9. The electrode inspection process is stored as an electrode inspection process program in the storage unit 34 of the inspection device 3, and is activated, for example, by the user tapping an icon associated with the electrode inspection process program displayed on the display unit 32 using the operation input unit 33.

[0041] The image determination unit 353 of the control unit 35 of the inspection device 3 shown in Figure 6 acquires information on the type of mixture M produced and the mixing method from the mixing device 1 connected to the connection unit 31 (step S301). The image determination unit 353 determines whether or not the mixture M is for a positive electrode (step S302). If the mixture M is not for a positive electrode (step S302; NO), the image determination unit 353 sets the determination result to "determination impossible" (step S303). If the mixture M is for a positive electrode (step S302; YES), the image determination unit 353 determines whether or not the mixing method of the mixture M is dry mixing (step S304).

[0042] If the mixing method of mixture M is not dry mixing (step S304; NO), the image determination unit 353 determines whether the mixing method of mixture M is wet mixing or not (step S305). If the mixing method of mixture M is not wet mixing (step S305; NO), the image determination unit 353 sets the determination result to "undeterminable" (step S303). Also, if the mixing method of mixture M is wet mixing (step S305; YES), the image determination unit 353 determines whether the positive electrode E is dry or not (step S306). If the positive electrode E is not dry (step S306; NO), the image determination unit 353 sets the determination result to "undeterminable" (step S303).

[0043] Furthermore, if the positive electrode E is already dried (step S306; YES), and if the mixing method of the mixture M in step S304 is dry mixing (step S304; YES), the image acquisition unit 351 of the control unit 35 of the inspection apparatus 3 shown in Figure 6 acquires data of the captured image 21 of the positive electrode E from the first imaging device 2a connected to the connection unit 31 (step S307). The image processing unit 352 of the control unit 35 of the inspection apparatus 3 shown in Figure 6 digitizes the data of the captured image 21 on a pixel-by-pixel basis (step S308). This allows the image processing unit 352 to obtain a numerical value for each pixel. The image determination unit 353 of the control unit 35 executes image determination processing (step S309). For image determination processing, the flowchart shown in Figure 5 is executed.

[0044] The image determination unit 353 determines whether there are other imaging devices 2 besides the first imaging device 2a that acquired the data of the captured image 21 in step S307 (step S310). For example, as shown in Figure 7A, if imaging is being performed by both the first imaging device 2a and the second imaging device 2b (step S310; YES), the image determination unit 353 returns to step S307. The image acquisition unit 351 of the control unit 35 acquires the data of the captured image 21 acquired by the second imaging device 2b (step S307). Subsequently, the image processing unit 352 and the image determination unit 353 execute the steps from step S308 onwards.

[0045] Furthermore, in step S310, for example, if imaging is being performed only by the second imaging device 2b as shown in Figure 7B, or if there are no other imaging devices 2 other than the first imaging device 2a as shown in Figures 8A and 8B (step S310; NO), the image determination unit 353 displays the determination result on the display unit 32 of the inspection device 3 (step S311).

[0046] As described above, in Embodiment 2, in addition to the effects of Embodiment 1, the first imaging device 2a and the second imaging device 2b image the positive electrode E of the mixture M before and after stretching, and the inspection device 3 determines whether the mixture M is good or bad, thereby allowing defective electrodes and materials to be eliminated at an appropriate time. This reduces the prototyping time for electrodes.

[0047] (modified version) The present invention is not limited to the embodiments described above, and various modifications are, of course, possible without departing from the spirit of the invention.

[0048] In embodiments 1 and 2 described above, the inspection device 3 determines whether the mixture M is good or bad based on predetermined upper and lower limits of standard values. However, it is also possible to use AI to learn images of good and bad mixture M and then make the determination.

[0049] In embodiments 1 and 2 described above, the image data of mixture M was quantified on a pixel-by-pixel basis, and the quality of mixture M was determined based on these numerical values. However, the data is not limited to this; the numerical values ​​of multiple pixels may be processed to obtain processed values ​​such as the average or median, and the quality of mixture M may be determined based on these processed values.

[0050] Furthermore, in embodiments 1 and 2 of this disclosure, the inspection device 3 can be implemented as a dedicated system. However, it is possible to implement it using a normal computer system instead of a dedicated system. For example, a computer capable of implementing each of the functions of the inspection device 3 described above may be configured by distributing programs for implementing each of the functions of the inspection device 3 on a recording medium such as a computer-readable CD-ROM (Compact Disc Read Only Memory) or DVD-ROM (Digital Versatile Disc Read Only Memory), and installing these programs on a computer. In cases where each function is implemented by a division of labor between the OS (Operating System) and an application, or by cooperation between the OS and an application, only the application may be stored on the recording medium.

[0051] The present invention allows for various embodiments and modifications without departing from the broad spirit and scope of the invention. Furthermore, the embodiments described above are for illustrative purposes only and do not limit the scope of the invention. In other words, the scope of the invention is indicated by the claims, not by the embodiments. Various modifications made within the scope of the claims and the equivalent significance of disclosure are considered to be within the scope of the invention. [Explanation of symbols]

[0052] 1... Mixing device, 2... Imaging device, 2a... First imaging device, 2b... Second imaging device, 3... Inspection device, 4... Electrode forming device, 21... Acquired image, 31... Connection unit, 32... Display unit, 33... Operation input unit, 34... Storage unit, 35... Control unit, 100, 100A... Inspection system, 341... Threshold data, 351... Image acquisition unit, 352... Image processing unit, 353... Image determination unit, E... Positive electrode, F... Current collector foil, M... Mixture, CB... Black reference image, R... Roller, S... Image, MD... Electrode layer, CW... White reference image, MS... Slurry.

Claims

1. An inspection method performed by an inspection device, A step of acquiring data from an image of a mixture of a fibrous auxiliary agent and an active material. A step of quantifying the color tone of each pixel of the captured image data in multiple levels of gradation. The steps include determining whether the numerical value based on the color tone of the pixel is less than the maximum value of a predetermined standard and greater than or equal to the minimum value of a predetermined standard, and determining the mixture to be a good product if the numerical value is less than the maximum value of a standard and greater than or equal to the minimum value of a predetermined standard. An inspection method that includes the following features.

2. The aforementioned active material is an active material for the positive electrode. The inspection method according to claim 1.

3. The mixing method for the aforementioned mixture is dry mixing. The inspection method according to claim 1 or 2.

4. A step of stretching the mixture to form an electrode layer, A step of imaging the electrode layer, The inspection method according to claim 3, further comprising:

5. Before forming the electrode layer, a step of imaging the electrode layer, The inspection method according to claim 4, further comprising:

6. The mixture obtained by mixing the fibrous auxiliary agent and the active material is wet-mixed with a solvent containing a dispersion medium, and after mixing, it is coated onto the current collector foil and dried to form an electrode layer. After the formation of the electrode layer, the step of imaging the electrode layer, The inspection method according to claim 1 or 2, further comprising:

7. After stretching the electrode layer, the step of imaging the electrode layer, The inspection method according to claim 6, further comprising:

8. The step of converting the color tone of the captured image data to a grayscale with black being 0 and white being 255, The inspection method according to claim 1 or 2, further comprising:

9. If the maximum value obtained by quantifying all pixels of the image of the mixture contained in the data of the captured image is greater than or equal to the upper limit of the normal range of the reference value, the mixture is determined to be a defective product. The inspection method according to claim 1 or 2, further comprising:

10. If the minimum value obtained by quantifying all pixels of the image of the mixture contained in the data of the captured image is less than the lower limit of the normal range of the reference value, the mixture is determined to be a defective product. The inspection method according to claim 1 or 2, further comprising:

11. If the proportion of the numerical values ​​obtained by quantifying all pixels of the image of the mixture contained in the data of the captured image that are equal to or greater than the upper limit of the normal range of the reference value is equal to or greater than a predetermined proportion, the mixture is determined to be a defective product. The inspection method according to claim 1 or 2, further comprising:

12. If the percentage of the numerical values ​​obtained by quantifying all pixels of the image of the mixture contained in the data of the captured image that are below the lower limit of the normal range of the reference value is equal to or greater than a predetermined percentage, the mixture is determined to be a defective product. The inspection method according to claim 1 or 2, further comprising:

13. The data of the captured image includes a step that includes predetermined standard colors of white and black for calibration. The inspection method according to claim 1 or 2, further comprising:

14. A testing device equipped with a processor, The aforementioned processor, Data from an image of a mixture of fibrous auxiliary material and active material is acquired from the imaging device. The color tone of each pixel in the captured image data is quantified using multiple levels of gradation. The system determines whether the numerical value based on the color tone of the pixel is less than the maximum value of a predetermined standard and greater than or equal to the minimum value of a predetermined standard. If the numerical value of the pixel is less than the maximum value of a predetermined standard and greater than or equal to the minimum value of a predetermined standard, the system determines that the mixture is a good product. Inspection device.

15. On the computer, A process to acquire data from an image of a mixture of fibrous auxiliary material and active material. A process that quantifies the color tone of each pixel in the captured image data using multiple levels of gradation. A process to determine whether the numerical value based on the color tone of the pixel is less than the maximum value of a predetermined standard and greater than or equal to the minimum value of a predetermined standard, and if the numerical value of the pixel is less than the maximum value of a predetermined standard and greater than or equal to the minimum value of a predetermined standard, the mixture is determined to be a good product. A program to execute.

Images