Adhesive quality detection method, detection device, electronic equipment and storage medium

Abstract

The application discloses a rubber coating quality detection method, a detection device, an electronic device and a storage medium. The method comprises the following steps: obtaining a to-be-detected image of a to-be-detected area of an electric core; performing gray contrast on the to-be-detected image to obtain a rubber coating overlapping area; determining a first edge curve and a second edge curve of the rubber coating overlapping area; obtaining an actual width of the rubber coating overlapping area according to the intersection of the first edge curve and the second edge curve with a preset straight line; and judging whether the actual width is within a tolerance range of a preset width. By comparing whether the actual width of the rubber coating overlapping area is within the tolerance range of the preset width, it can be judged whether the rubber coating overlapping area is qualified, so that it can be detected whether the rubber coating overlapping area has defects.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of battery cell quality inspection, and in particular to a method for detecting the quality of a rubber tape, a detection device, an electronic device and a storage medium. BACKGROUND

[0002] In the production process of full-tab cylindrical batteries, the end of the battery cell needs to be treated with rubber tape, that is, the rubber tape is pasted on the end of the battery cell to prevent short circuit when the battery cell is put into the shell. However, due to the defects that may occur during the pasting process, it is necessary to detect the quality of the pasted rubber tape after the pasting is completed. SUMMARY

[0003] Therefore, the purpose of the present application is to provide a method for detecting the quality of a rubber tape, a detection device, an electronic device and a storage medium, so as to discover defects in the pasting of the battery cell in a timely manner.

[0004] To achieve the above technical purpose, the first aspect of the present application provides a method for detecting the quality of a rubber tape, comprising the following steps:

[0005] Obtaining a detection image of a detection area of a battery cell;

[0006] Performing a gray scale comparison on the detection image to obtain a rubber tape overlapping area;

[0007] Determining a first edge curve and a second edge curve of the rubber tape overlapping area;

[0008] According to the intersection of the first edge curve and the second edge curve with a preset straight line, the actual width of the rubber tape overlapping area is obtained;

[0009] Judging whether the actual width is within the tolerance range of the preset width.

[0010] Further, the determination of the first edge curve and the second edge curve of the rubber tape overlapping area comprises:

[0011] Outputting a gray scale change curve of the rubber tape overlapping area according to the gray scale comparison result of the detection image;

[0012] Determining an edge point of the rubber tape overlapping area according to the gray scale change curve;

[0013] Performing curve fitting on the edge point to obtain the first edge curve and the second edge curve of the rubber tape overlapping area.

[0014] Further, the obtaining of the detection image of the detection area of the battery cell is specifically: obtaining a plurality of detection images of the detection area of the battery cell at a plurality of angles along the circumferential surface of the battery cell.

[0015] Further, after the step of obtaining the encapsulation overlapping area by contrasting the grayscale of the image to be detected, and before the step of determining the first edge curve and the second edge curve of the encapsulation overlapping area, the method further comprises:

[0016] determining whether the image to be detected is distorted, and if so, performing a restoration process on the image to be detected.

[0017] Further, the step of determining whether the image to be detected is distorted, and if so, performing a restoration process on the image to be detected, comprises a dividing step and a determining step.

[0018] The dividing step comprises dividing the image to be detected into a divided image comprising a first area and a second area.

[0019] The determining step comprises contrasting the divided image with a template image to determine whether the encapsulation overlapping area is completely located in the first area, and if not, performing a restoration process on the divided image.

[0020] Further, the restoration process comprises synthesizing the divided image with other images to be detected so that the encapsulation overlapping area on the synthesized divided image is completely located in the first area.

[0021] Further, the step of determining whether the image to be detected is distorted, and if so, performing a restoration process on the image to be detected, further comprises a pre-determining step.

[0022] The pre-determining step comprises performing grayscale recognition on the image to be detected to determine whether the grayscale value of the image to be detected is within a preset grayscale value tolerance range, and if so, entering the dividing step.

[0023] Further, after the step of obtaining the image to be detected of the region to be detected of the battery, the method further comprises:

[0024] performing grayscale processing on the image to be detected to obtain a grayscale change curve of the image to be detected;

[0025] obtaining a lower edge point of the adhesive tape according to the grayscale change curve;

[0026] determining a height maximum value and a height minimum value of the adhesive tape according to the distance between the lower edge point and a preset reference line;

[0027] determining whether the height maximum value and the height minimum value are both within a preset height standard range.

[0028] Further, the preset reference line is a straight line where the height of the battery is located.

[0029] The second aspect of the present application provides a rubber bonding quality detection device for implementing the rubber bonding quality detection method of any one of the above.

[0030] The device comprises an image acquisition module, a comparison module, an analysis module and a judgment module.

[0031] The image acquisition module is configured to acquire a to-be-detected image of a to-be-detected region of the battery cell and transmit the to-be-detected image to the comparison module.

[0032] The comparison module is configured to perform gray scale comparison on the to-be-detected image to obtain a rubber bonding overlap region.

[0033] The analysis module is configured to determine a first edge curve and a second edge curve of the rubber bonding overlap region, and then obtain an actual width of the rubber bonding overlap region according to the intersection of the first edge curve and the second edge curve with a preset straight line.

[0034] The judgment module is configured to determine whether the actual width is within a tolerance range of a preset width to detect whether the rubber bonding quality is qualified.

[0035] The third aspect of the present application provides an electronic device comprising a memory and a processor.

[0036] The memory is configured to store program instructions.

[0037] The processor is configured to execute the program instructions to perform the steps of the rubber bonding quality detection method of any one of the above.

[0038] The fourth aspect of the present application provides a computer-readable storage medium, wherein the computer-readable storage medium stores computer program instructions.

[0039] The computer program instructions are configured to be executed by a processor to perform the steps of the rubber bonding quality detection method of any one of claims 1 to 9.

[0040] As can be seen from the above technical solutions, the present application provides a rubber bonding quality detection method, a detection device, an electronic device and a storage medium. The method comprises the following steps: acquiring a to-be-detected image of a to-be-detected region of a battery cell; performing gray scale comparison on the to-be-detected image to obtain a rubber bonding overlap region; determining a first edge curve and a second edge curve of the rubber bonding overlap region; obtaining an actual width of the rubber bonding overlap region according to the intersection of the first edge curve and the second edge curve with a preset straight line; and determining whether the actual width is within a tolerance range of a preset width. By comparing whether the actual width of the rubber bonding overlap region is within the tolerance range of the preset width, it can be determined whether the rubber bonding overlap region is qualified, so as to detect whether the rubber bonding overlap region has defects. BRIEF DESCRIPTION OF DRAWINGS

[0041] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings needed to be used in the embodiments or prior art description. Obviously, the drawings described below are only some embodiments of the present application, and for those skilled in the art, other drawings can be obtained based on these drawings without creative labor.

[0042] Figure 1 A flow chart of a rubber bonding quality detection method provided by an embodiment of the present application;

[0043] Figure 2 A software processing diagram for performing gray contrast on a to-be-detected image provided by an embodiment of the present application;

[0044] Figure 3 A flow chart of a rubber bonding quality detection method provided by a more specific embodiment of the present application;

[0045] Figure 4 A flow chart of a rubber bonding quality detection method provided by another embodiment of the present application;

[0046] Figure 5 A flow chart of a rubber bonding quality detection method provided by another embodiment of the present application;

[0047] Figure 6 A flow chart of a rubber bonding quality detection method provided by an embodiment of the present application with a division step and a judgment step;

[0048] Figure 7 A flow chart of a rubber bonding quality detection method provided by an embodiment of the present application with a pre-judgment step;

[0049] Figure 8 A flow chart of a rubber bonding quality detection method provided by an embodiment of the present application with a rubber bonding height detection step;

[0050] Figure 9 A software processing diagram for performing rubber bonding height detection on a to-be-detected image provided by an embodiment of the present application;

[0051] Figure 10 A top view of an image acquisition module of a rubber bonding quality detection device provided by an embodiment of the present application. DETAILED DESCRIPTION

[0052] The technical solutions of the embodiments of the present application will be described clearly and completely below with reference to the drawings. Obviously, the described embodiments are only some of the embodiments of the present application, not all the embodiments. Based on the embodiments in the embodiments of the present application, all other embodiments obtained by those skilled in the art without creative labor are within the scope of the present application.

[0053] In the description of the embodiments of the present application, it should be noted that the terms "center", "upper", "lower", "left", "right", "vertical", "horizontal", "inner", "outer" and the like indicate the orientation or positional relationship shown in the drawings, and are only for the convenience of describing the embodiments of the present application and simplifying the description, and do not indicate or imply that the device or element referred to must have a particular orientation, be constructed and operated in a particular orientation, and therefore cannot be understood as a limitation on the embodiments of the present application. In addition, the terms "first", "second", "third" are only for descriptive purposes and cannot be understood as indicating or implying relative importance.

[0054] In the description of the embodiments of the present application, unless otherwise explicitly specified and limited, the terms "mounting", "connecting", "connecting" should be understood in a broad sense, for example, it can be fixedly connected, or it can be replaceably connected, or it can be integrally connected, it can be mechanically connected, or it can be electrically connected, it can be directly connected, or it can be indirectly connected through an intermediate medium, it can be the communication inside two elements. For those skilled in the art, the specific meaning of the above terms in the embodiments of the present application can be understood according to the specific circumstances.

[0055] Please refer to Figure 1 , the first aspect of the present application provides a rubber quality detection method, comprising the following steps:

[0056] S1, obtaining a to-be-detected image of a to-be-detected area of the battery cell;

[0057] Among them, corresponding to the pasting position of the adhesive tape, the to-be-detected area of the battery cell can be the end of the battery cell.

[0058] S2, performing gray scale comparison on the to-be-detected image to obtain a rubber-coated overlapping area;

[0059] Please refer to Figure 2 , in the to-be-detected image, the part with darker gray scale is the rubber-coated overlapping area, so after the gray scale comparison of the to-be-detected image, the rubber-coated overlapping area in the to-be-detected image can be obtained.

[0060] S3, determining a first edge curve and a second edge curve of the rubber-coated overlapping area;

[0061] In application, the adhesive tape is generally a square strip, so the rubber-coated overlapping area is generally rectangular. In this embodiment, as Figure 2 indicated, the first edge curve and the second edge curve can be two straight lines on the left and right sides of the rubber-coated overlapping area.

[0062] S4, obtaining the actual width of the rubber-coated overlapping area according to the intersection of the first edge curve and the second edge curve with a preset straight line.

[0063] In the embodiment, the preset straight line can be a transverse straight line where the middle position of the adhesive tape height is located, and intersects with both the first edge curve and the second edge curve; or the preset straight line can be obtained by taking a plurality of transverse straight lines intersecting with both the first edge curve and the second edge curve, obtaining a plurality of width values, and taking an average value from the plurality of width values, and taking the straight line corresponding to the average value as the preset straight line, that is, the length of the intersection point of the preset straight line and the first edge curve and the second edge curve is the average value of the width of the rubber coating overlap area, and the actual width of the rubber coating overlap area is taken as the actual width of the rubber coating overlap area, and then the actual width of the rubber coating overlap area is obtained by obtaining the two intersection points.

[0064] S5, determining whether the actual width is within the tolerance range of the preset width.

[0065] Specifically, if the actual width is within the tolerance range of the preset width, it indicates that the current battery cell has a qualified rubber coating quality.

[0066] The rubber coating quality detection method provided by the scheme can provide a reference basis for whether the battery cell rubber coating quality is qualified by the width of the rubber coating overlap area, and the rubber coating quality can be quickly detected.

[0067] In a more specific embodiment, please refer to Figure 3 On the basis of the above embodiment, step S3 comprises:

[0068] S31, outputting a gray scale change curve of the rubber coating overlap area according to the gray scale contrast result of the image to be detected.

[0069] The gray scale contrast result of the image to be detected refers to the comparison after the gray scale analysis of the image, for example, the gray scale feature information in the image can be extracted by a gray scale analysis tool, and then a gray scale change curve is generated. The gray scale change curve can be a line gray scale distribution curve (line profile), an image line gray scale average (linear averages) R01 boundary gray scale curve, etc.

[0070] Taking the line gray scale distribution curve as an example, the line gray scale distribution curve analyzes and draws the pixel gray scale change along a certain line segment in the image. Its horizontal axis is the pixel position index on the line segment, and the vertical axis is the gray scale of each point. The line gray scale distribution curve can be used to detect the boundary of adjacent parts in the image, quantitatively represent the gray scale change, and detect whether there is a certain feature in the image. In the line gray scale curve, the wave crest and the wave trough represent the increase and decrease of the gray scale of a region in the image along the selected line segment, and the width and amplitude of the wave crest and the wave trough represent the size and brightness of the region in the image, respectively. For example, if the image contains a region with higher brightness, a wave crest will appear in the gray scale distribution curve drawn along the line segment passing through it, and the higher the brightness of the region relative to the background, the steeper the wave crest.

[0071] Taking the image line gray mean ROl boundary gray curve as an example, the four types of line gray means of the pixels in the entire image or the specified rectangular region can be calculated, including the linear average of the gray of each column of pixels along the X-axis direction, the linear average of the gray of each row of pixels along the Y-axis direction, the average of the gray of the pixels perpendicular to the diagonal line along the diagonal line from the lower left to the upper right, and the average of the gray of the pixels perpendicular to the diagonal line along the diagonal line from the upper left to the lower right.

[0072] S32, determining the edge points of the rubber-coated overlapping region according to the gray change curve;

[0073] S33, performing curve fitting on the edge points to obtain the first edge curve and the second edge curve of the rubber-coated overlapping region.

[0074] Specifically, the gray change curve is used to represent the degree of gray change on the to-be-detected image. Through the gray change curve, the edge points of the rubber-coated overlapping region can be better determined. Then, the first edge curve and the second edge curve are fitted through the edge points.

[0075] In another embodiment, referring to Figure 4 The step S1 in any of the above embodiments can specifically be: acquiring a plurality of to-be-detected images of the battery cell at a plurality of angles of the to-be-detected region of the battery cell.

[0076] In the process of photographing the battery cell, since the rubber-coated overlapping regions of different battery cells can be located at different angles when the battery cells are delivered, in the present embodiment, the circumferential surface of the battery cell can be detected by acquiring a plurality of to-be-detected images of the circumferential surface of the battery cell, thereby improving the accuracy of the rubber coating quality detection.

[0077] In other embodiments, referring to Figure 5 After the step S2 and before the step S3, the method further includes:

[0078] S20, judging whether the to-be-detected image is distorted, and if so, performing restoration processing on the to-be-detected image.

[0079] Specifically, when applied to a cylindrical battery cell, photographing the battery cell from the side of the battery cell can cause a distorted region in the image due to the curvature of the battery cell; therefore, if the to-be-detected image with the distorted region is directly subjected to gray comparison, the rubber-coated overlapping region obtained will also be distorted, resulting in inaccurate detection structure.

[0080] In the present embodiment, by performing restoration processing on the to-be-detected image with the distortion, the situation of directly detecting the distorted image can be avoided, thereby improving the accuracy of detection.

[0081] In a further improved embodiment, referring to Figure 6The step S20 includes a division step S21 and a judgment step S22.

[0082] The division step S21 includes dividing the image to be detected into a divided image including a first region and a second region.

[0083] The judgment step S22 includes comparing the divided image with a template image to determine whether the encapsulation overlap region is completely located in the first region, and if not, performing restoration processing on the divided image.

[0084] Specifically, the first region can be a verification region in which no distortion region exists, and the second region can be an image distortion region. In the judgment step S22, when it is determined that the encapsulation overlap region in the divided image is completely displaced in the first region, step S3 can be entered; when it is determined that the divided image is partially or entirely located in the second region, the encapsulation overlap region partially or entirely displays distortion on the image, and then the divided image is processed to restore the encapsulation overlap region to normal display on the image.

[0085] The template image is a preset image in which the encapsulation overlap region in a plurality of angles of the side surface of the battery cell is normally displayed. By comparing the divided image with the template image, it can be determined whether the encapsulation overlap region is located in the first region or the second region.

[0086] In an embodiment, the restoration processing includes synthesizing the divided image with other images to be detected so that the encapsulation overlap region in the synthesized divided image is completely located in the first region.

[0087] Specifically, after the divided image is synthesized with other images to be detected at different angles, a normal image in which the encapsulation overlap region is normally displayed on the image can be obtained, that is, the encapsulation overlap region is completely located in the first region, and then step S3 can be entered.

[0088] As a further improvement, please refer to Figure 7 The step S20 further includes a pre-judgment step S200.

[0089] The pre-judgment step S200 includes performing gray scale recognition on the image to be detected to determine whether the gray scale value of the image to be detected is within a preset gray scale value tolerance range, and if so, the division step S21 is entered.

[0090] Specifically, if the gray scale value of the image to be detected is within the preset gray scale value tolerance range, it indicates that the encapsulation overlap region exists in the image to be detected, and then the division step S21 is entered. If the gray scale value of the image to be detected is not within the preset gray scale value tolerance range, it indicates that the encapsulation overlap region does not exist in the image to be detected, and the image can be discarded.

[0091] In an embodiment, please refer to Figure 8 andFigure 9 After step S1, the following steps are further included:

[0092] S61, performing gray processing on the to-be-detected image to obtain a gray change curve of the to-be-detected image;

[0093] S62, obtaining a lower edge point of the adhesive tape according to the gray change curve;

[0094] S63, determining a height maximum value and a height minimum value of the adhesive tape according to a distance between the lower edge point and a preset reference line;

[0095] S64, judging whether the height maximum value and the height minimum value are both within a preset height standard range.

[0096] Specifically, step S61 can occur after step S1 or after step S5. If step S61 occurs after step S5, the gray change curve obtained in step S31 can be directly used.

[0097] In an embodiment, the preset reference line can be a line on which the heights of the battery cells lie, because the heights of the battery cells vary little and can be regarded as a straight line. The height of the battery cell can be calculated through the distance between the lower edge point and the preset reference line, and then the height maximum value and the height minimum value of the adhesive tape attached to the side surface of the battery cell are obtained. Then, the height maximum value and the height minimum value are compared with the preset height standard range. If both of them are within the preset height standard range, the adhesive tape is qualified.

[0098] As an implementation, the preset reference line can also be a fitting straight line of the upper edge of the adhesive tape. The height maximum value and the height minimum value of the adhesive tape can be determined by comparing the distance between the lower edge point and the fitting straight line of the upper edge of the adhesive tape.

[0099] The second aspect of the embodiment of the present application provides an adhesive quality detection device for implementing any of the above adhesive quality detection methods.

[0100] The device can include an image acquisition module, a comparison module, an analysis module and a judgment module.

[0101] The image acquisition module is configured to acquire a to-be-detected image of a to-be-detected region of a battery cell and transmit the to-be-detected image to the comparison module.

[0102] The comparison module is configured to perform gray comparison on the to-be-detected image to obtain a wrapped adhesive overlap region.

[0103] The analysis module is configured to determine a first edge curve and a second edge curve of the wrapped adhesive overlap region, and then obtain an actual width of the wrapped adhesive overlap region according to the intersection points of the first edge curve and the second edge curve with a preset straight line.

[0104] The judgment module is configured to judge whether the actual width is within a tolerance range of the preset width, so as to detect whether the rubberizing quality is qualified.

[0105] In the above embodiments, the image acquisition module 1 can be a camera, and the plurality of image acquisition modules 1 are evenly distributed around the circumferential surface of the battery cell. Figure 10

[0106] The third aspect of the embodiments of the present application provides an electronic device, including a memory and a processor; the memory is configured to store program instructions; the processor is configured to run the program instructions to execute the steps of the rubberizing quality detection method of any one of the above.

[0107] The fourth aspect of the embodiments of the present application provides a computer readable storage medium, and the computer readable storage medium stores computer program instructions; the computer program instructions are configured to be run by a processor to execute the steps of the rubberizing quality detection method of any one of the above.

[0108] It should be noted that each functional module in each embodiment of the present application can be integrated together to form an independent part, or each module can exist independently, or two or more modules can be integrated to form an independent part. If the functions are realized in the form of software functional modules and sold or used as independent products, they can be stored in a computer readable storage medium.

[0109] Therefore, the present embodiment further provides a computer readable storage medium storing computer program instructions, which are read and run by a processor to execute the steps of any one of the block data storage methods. Based on this understanding, the technical solutions of the present application or parts of the technical solutions that essentially contribute to the prior art can be embodied in the form of a software product, which is stored in a storage medium and includes instructions to make a computer device (which can be a personal computer, a server, or a network device, etc.) execute all or part of the steps of the methods described in the embodiments of the present application. The aforementioned storage medium includes a U disk, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, and various program code storage media.

[0110] ​The above are preferred embodiments of the present application, and are not used to limit the present application, and for those skilled in the art, the aforementioned examples can be modified, or some technical features can be replaced by equivalent, but any modification, equivalent replacement, improvement, etc. within the spirit and principle of the present application shall be included in the protection scope of the present application.

Claims

1. A method for detecting the quality of a rubber coating, characterized by, The method comprises the following steps: acquiring a to-be-detected image of a to-be-detected area of a battery cell; performing gray contrast on the to-be-detected image to obtain an encapsulation overlap area; outputting a gray change curve of the encapsulation overlap area according to the gray contrast result of the to-be-detected image; determining an edge point of the encapsulation overlap area according to the gray change curve; performing curve fitting on the edge point to obtain a first edge curve and a second edge curve of the encapsulation overlap area; obtaining an actual width of the encapsulation overlap area according to the intersection of the first edge curve and the second edge curve with a preset straight line; judging whether the actual width is within a preset width tolerance range; wherein the preset straight line is a horizontal straight line at the middle position of the height of the encapsulation overlap area, and intersects with both the first edge curve and the second edge curve, or the preset straight line is a plurality of horizontal straight lines intersecting with both the first edge curve and the second edge curve, thereby obtaining a plurality of width values, and taking an average value of the plurality of width values as the preset straight line.

2. The method of claim 1, wherein The acquiring of the to-be-detected image of the to-be-detected area of the battery cell specifically comprises: acquiring a plurality of to-be-detected images of the to-be-detected area of the battery cell at a plurality of angles along the circumferential surface of the battery cell.

3. The method of claim 2, wherein After the performing of the gray contrast on the to-be-detected image to obtain the encapsulation overlap area, and before the determining of the first edge curve and the second edge curve of the encapsulation overlap area, the method further comprises: judging whether the to-be-detected image is distorted, and if so, performing restoration processing on the to-be-detected image.

4. The method of claim 3, wherein The judging whether the to-be-detected image is distorted, and if so, performing restoration processing on the to-be-detected image comprises a dividing step and a judging step. The dividing step comprises: dividing the to-be-detected image into a divided image comprising a first area and a second area. The judging step comprises: comparing the divided image with a template image to determine whether the encapsulation overlap area is completely located in the first area, and if not, performing restoration processing on the divided image.

5. The method of claim 4, wherein The restoration processing comprises: synthesizing the divided image with other to-be-detected images to make the encapsulation overlap area on the synthesized divided image completely located in the first area.

6. The method of claim 4, wherein The judging whether the to-be-detected image is distorted, and if so, performing restoration processing on the to-be-detected image further comprises a pre-judging step. The pre-judging step comprises: performing gray recognition on the to-be-detected image to determine whether the gray value of the to-be-detected image is within a preset gray value tolerance range, and if so, entering the dividing step.

7. The method of claim 1, wherein After the acquiring of the to-be-detected image of the to-be-detected area of the battery cell, the method further comprises: performing gray processing on the to-be-detected image to obtain a gray change curve of the to-be-detected image; obtaining a lower edge point of the encapsulation overlap area according to the gray change curve; determining a height maximum value and a height minimum value of the encapsulation overlap area according to the distance between the lower edge point and a preset reference line; judging whether the height maximum value and the height minimum value are both within a preset height standard range.

8. The method of claim 7, wherein The preset reference line is a straight line at the height of the battery cell.

9. A taping quality detection device characterized by comprising: The method comprises: an image acquisition module, a comparison module, an analysis module, and a judging module. The image acquisition module is configured to acquire a to-be-detected image of a to-be-detected region of the battery cell and transmit the to-be-detected image to the comparison module; The comparison module is configured to perform gray comparison on the to-be-detected image to obtain an encapsulation overlap region; The analysis module is configured to determine a first edge curve and a second edge curve of the encapsulation overlap region, and then determine an actual width of the encapsulation overlap region according to intersection points of the first edge curve and the second edge curve with a preset straight line; The determination of the first edge curve and the second edge curve of the encapsulation overlap region includes: outputting a gray variation curve of the encapsulation overlap region according to the gray comparison result of the to-be-detected image; determining edge points of the encapsulation overlap region according to the gray variation curve; and performing curve fitting on the edge points to obtain the first edge curve and the second edge curve of the encapsulation overlap region; The preset straight line is a horizontal straight line at a middle position of the adhesive tape height, and intersects with both the first edge curve and the second edge curve, or the preset straight line is a plurality of horizontal straight lines that all intersect with the first edge curve and the second edge curve, so as to obtain a plurality of width values, and an average value is obtained from the plurality of width values, and a straight line corresponding to the average value is taken as the preset straight line; The judgment module is configured to judge whether the actual width is within a tolerance range of a preset width, so as to detect whether the encapsulation quality is qualified.

10. An electronic device, comprising: The memory is configured to store program instructions; The processor is configured to run the program instructions to execute the steps of the encapsulation quality detection method in any one of claims 1 to 8. The readable storage medium stores computer program instructions; 11. A computer readable storage medium, characterized in that, The computer program instructions are configured to be run by the processor to execute the steps of the encapsulation quality detection method in any one of claims 1 to 8. ​

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