Methods, apparatus, computing devices, and readable storage media for testing battery separators

Abstract

This application provides a method, apparatus, computing device, and readable storage medium for detecting battery separators, belonging to the field of battery technology. The method for detecting battery separators includes: extracting a first short-circuit trace region from a first detection image, wherein the first detection image is obtained by imaging the battery separator using a microscopic imaging device, and the first short-circuit trace region indicates ablation marks on the battery separator caused by a short circuit due to a metallic foreign object in the battery separator; extracting predetermined image features from a second detection image, wherein the second detection image is obtained by imaging a cross-section of the battery separator across the first short-circuit trace region using a microscopic imaging device, and the cross-section of the first short-circuit trace region contains a metallic foreign object; and determining the type of metallic foreign object based on the extraction result of the predetermined image features.

Description

Technical Field

[0001] This application relates to the field of battery technology, and in particular to a method, apparatus, computing device, computer-readable storage medium, and computer program product for detecting battery separators. Background Technology

[0002] During the production of lithium-ion batteries, issues such as raw material purity and processing technology often lead to the introduction of metallic foreign objects into the battery. These foreign objects can then deposit on the surfaces of the positive and negative electrodes during battery formation or use due to electrochemical reactions, damaging the battery separator and causing short circuits or micro-short circuits.

[0003] To ensure batteries meet customer requirements, it is necessary to inspect and attribute micro-short circuits in the battery separator. However, inspecting the battery separator often leads to a series of problems. Summary of the Invention

[0004] In view of the above problems, this application provides a method, apparatus, computing device, computer-readable storage medium and computer program product for detecting battery separators, aiming to alleviate, reduce or eliminate the problem of being unable to determine the type of metallic foreign matter when detecting battery separators.

[0005] In a first aspect, this application provides a method for detecting a battery separator, comprising: extracting a first short-circuit trace region from a first detection image, wherein the first detection image is obtained by imaging the battery separator using a microscopic imaging device, and the first short-circuit trace region indicates ablation marks on the battery separator caused by a short circuit due to a metal foreign object in the battery separator; extracting predetermined image features from a second detection image, wherein the second detection image is obtained by imaging a cross-section of the battery separator across the first short-circuit trace region using a microscopic imaging device, and a metal foreign object is present in the cross-section of the first short-circuit trace region; and determining the type of metal foreign object based on the extraction result of the predetermined image features.

[0006] In the technical solution of this application embodiment, the type of metallic foreign object is determined based on the extraction result of predetermined image features obtained from the second detection image obtained by imaging the cross section of the battery separator across the first short-circuit trace region through a microscopic imaging device. This allows the ablation traces caused by the battery short circuit on the battery separator to be found first, and then the cross-sectional morphology of the cross section processed through the ablation trace to be analyzed, thereby alleviating the problem of not being able to determine the type of metallic foreign object when detecting the battery separator.

[0007] In some embodiments, extracting predetermined image features from a second detection image includes: identifying a first target image region in the second detection image, the first target image region corresponding to the internal region of the diaphragm in the cross-section; and extracting predetermined image features from the first target image region. By identifying the first target image region corresponding to the internal region of the diaphragm in the cross-section from the second detection image, the recognition interference from image regions other than the internal region of the diaphragm in the cross-section (e.g., the surface region of the diaphragm in the cross-section) in the second detection image can be reduced, thereby improving the accuracy of extracting predetermined image features.

[0008] In some embodiments, identifying a first target image region from a second detection image includes: performing edge detection on the second detection image to detect a first edge and a second edge of a cross-section, wherein the first edge and the second edge respectively correspond to the edges of two opposing surfaces of the separator body of the battery separator on the cross-section; and identifying an image region in the second detection image located between the first edge and the second edge as the first target image region. By performing edge detection on the second detection image, the first target image region corresponding to the internal region of the separator in the cross-section can be quickly identified, thereby improving detection efficiency.

[0009] In some embodiments, the first edge corresponds to the negative electrode side of the battery separator, and the second edge corresponds to the positive electrode side of the battery separator. The predetermined image feature includes at least one image sub-region extending from the first edge to the second edge, wherein each image sub-region includes a first portion closer to the first edge and a second portion closer to the second edge, and the size of the first portion along the first edge is larger than the size of the second portion along the second edge. By setting the predetermined image feature to include at least one image sub-region comprising a first portion with a larger size along the first edge and closer to the first edge, and a second portion with a smaller size along the second edge and closer to the second edge, a criterion for determining the type of metallic foreign object can be preset, thereby increasing the likelihood of determining the type of metallic foreign object.

[0010] In some embodiments, extracting predetermined image features from a first target image region includes: performing edge detection on the first target image region to detect a third edge in the first target image region, the third edge being located between a first edge and a second edge and corresponding to a partial outline of a metallic foreign object on a cross-section, wherein the average gray value of the image region between the first edge and the third edge is greater than the average gray value of the image region between the third edge and the second edge; detecting peak points and valley points on the line of the third edge relative to the line of the second edge; and based on the peak points and valley points, segmenting the image region in the first target image region located between the first edge and the third edge into at least one image sub-region arranged along the first edge, wherein every two adjacent peak points and a valley point located between the two adjacent peak points jointly define an image sub-region. This design allows for convenient image segmentation of the first target image region and its division into at least one image sub-region.

[0011] In some embodiments, determining the type of metallic foreign object based on the extraction result of predetermined image features includes: in response to extracting predetermined image features from a second detection image, determining the metallic foreign object to be of a first type, wherein the first type indicates that the metallic foreign object was introduced during the preparation of the electrode sheet slurry and precipitated during battery cycling; and in response to failure to extract predetermined image features from the second detection image, determining the metallic foreign object to be of a second type, wherein the second type indicates that the metallic foreign object was introduced during battery production after the preparation of the electrode sheet slurry. By determining whether predetermined image features are extracted, the type of metallic foreign object can be determined, thereby identifying its specific source and providing a basis for improvement measures.

[0012] In some embodiments, extracting the first short-circuit trace region from the first detection image includes: extracting the second short-circuit trace region from a third detection image, wherein the third detection image is obtained by imaging the battery negative electrode sheet stacked with the battery separator using a microscopic imaging device, and the second short-circuit trace region indicates the ablation trace on the battery negative electrode sheet caused by a short circuit due to a metal foreign object in the battery separator; and locating the first short-circuit trace region corresponding to the second short-circuit trace region in the first detection image. By tracing the first short-circuit trace region on the battery separator by finding the second short-circuit trace region on the negative electrode sheet, the first short-circuit trace region on the battery separator can be found more conveniently, thereby improving detection efficiency.

[0013] In some embodiments, extracting the second short-circuit trace region from the third detection image includes: identifying candidate short-circuit trace regions from the third detection image; and determining the candidate short-circuit trace region as the second short-circuit trace region in response to the candidate short-circuit trace region meeting a preset condition. By identifying candidate short-circuit trace regions and determining whether they meet the preset conditions, the second short-circuit trace region on the negative electrode plate can be found more conveniently, thereby improving detection efficiency.

[0014] In some embodiments, the preset conditions include: the similarity between the candidate short-circuit trace region and the circle is greater than a similarity threshold, and the area of ​​the candidate short-circuit trace region is between a first threshold and a second threshold. By setting preset conditions, it is easier to identify which candidate short-circuit trace regions on the third detection image can be used as the second short-circuit trace region.

[0015] In some embodiments, locating the first short-circuit trace region corresponding to the second short-circuit trace region in the first detection image includes: determining a first coordinate of the center of the second short-circuit trace region in the image coordinate system of the third detection image; converting the first coordinate into a second coordinate in the image coordinate system of the first detection image based on the relative positional relationship between the battery negative electrode and the battery separator, wherein the second coordinate indicates the center of the first short-circuit trace region; and locating the first short-circuit trace region in the first detection image with the second coordinate as the center. Through coordinate transformation between the first and second coordinates, the first short-circuit trace region can be located more conveniently in the first detection image, thereby improving detection efficiency.

[0016] In some embodiments, the cross-section of the battery separator across the first short-circuit trace region is obtained by cross-section processing of the battery separator using a cross-section processing apparatus. The cross-section processing apparatus includes at least one of an ion beam profile polishing apparatus and a focused ion beam apparatus. Cross-section processing of the battery separator using the cross-section processing apparatus includes: measuring the maximum planar dimension of the portion of the metal foreign object exposed on the surface of the battery separator within the first short-circuit trace region; performing cross-section processing on the battery separator using the ion beam profile polishing apparatus in response to the maximum planar dimension being greater than or equal to a third threshold; and performing cross-section processing on the battery separator using the focused ion beam apparatus in response to the maximum planar dimension being less than the third threshold. By measuring the maximum planar dimension of the portion of the metal foreign object exposed on the surface of the battery separator within the first short-circuit trace region and selecting different cross-section processing methods based on this maximum planar dimension, the possibility of short-circuit point loss due to the accuracy of the processing apparatus can be reduced while ensuring processing efficiency.

[0017] In some embodiments, the method further includes: determining the dominant element in the metallic foreign object, wherein the dominant element indicates the element of the metallic foreign object penetrating the battery separator. By determining the dominant element in the metallic foreign object, when multiple metallic elements are present on the separator surface near the short circuit point, the dominant and minor elements causing the micro-short circuit can be better distinguished, thereby enabling more accurate and efficient source investigation and the implementation of improvement measures.

[0018] In some embodiments, determining the principal element of a metallic foreign object includes: identifying a second target image region from a fourth detection image, the second target image region corresponding to the internal region of the diaphragm in the cross-section, wherein the fourth detection image is obtained by imaging the cross-section using an energy dispersive spectroscopy (EDS) device, and the fourth detection image indicates the distribution of various elements present in the cross-section; for each element, determining whether the element exists in the second target image region and whether the ratio of the number of pixels of the element in the second target image region to the total number of pixels in the second target image region is greater than or equal to a fourth threshold; and determining the element as a principal element in response to determining that the element exists in the second target image region and that the ratio of the number of pixels of the element in the second target image region to the total number of pixels in the second target image region is greater than or equal to the fourth threshold. By analyzing the fourth detection image obtained by imaging the cross-section using an EDS device, the principal element piercing the diaphragm can be more easily determined, thereby enabling a more accurate analysis of the cause of the self-discharge anomaly.

[0019] In some embodiments, identifying the second target image region from the fourth detection image includes: performing edge detection on the fourth detection image to extract a first image region and a second image region from the fourth detection image, wherein the first image region and the second image region correspond to a first coating and a second coating on two opposing surfaces of the battery separator, respectively; and identifying the image region in the fourth detection image located between the first region and the second region as the second target image region. By performing edge detection to identify the upper and lower coatings, it is easier to identify the second target image region corresponding to the internal region of the separator in the cross-section, thereby improving detection efficiency.

[0020] Secondly, this application provides a battery separator detection device, comprising: a first module for extracting a first short-circuit trace region from a first detection image, wherein the first detection image is obtained by imaging the battery separator using a microscopic imaging device, and the first short-circuit trace region indicates ablation marks on the battery separator caused by a short circuit due to a metal foreign object in the battery separator; a second module for extracting predetermined image features from a second detection image, wherein the second detection image is obtained by imaging a cross-section of the battery separator across the first short-circuit trace region using a microscopic imaging device, and a metal foreign object is present in the cross-section of the first short-circuit trace region; and a third module for determining the type of metal foreign object based on the extraction result of the predetermined image features.

[0021] In some embodiments, the apparatus further includes a fourth module for determining the main element of the metallic foreign object, wherein the main element indicates the element of the metallic foreign object penetrating the battery separator.

[0022] Such a device can provide the advantages described above regarding the detection method for battery separators, which will not be repeated for the sake of brevity.

[0023] Thirdly, this application provides a computing device, including: at least one processor; and at least one memory communicatively connected to the at least one processor, the at least one memory storing instructions that, when executed individually or jointly by the at least one processor, cause the computing device to perform the methods described above.

[0024] Such computing devices offer the advantages described above regarding the detection methods for battery separators, which will not be repeated for the sake of brevity.

[0025] Fourthly, this application provides a computer-readable storage medium storing instructions that, when executed individually or jointly by one or more processors of a computing device, cause the computing device to perform the methods described above.

[0026] Such computer-readable storage media can provide the advantages described above regarding the detection method for battery separators, which will not be repeated for the sake of brevity.

[0027] Fifthly, this application provides a computer program product including instructions that, when executed individually or jointly by one or more processors of a computing device, cause the computing device to perform the methods described above.

[0028] Such computer program products can provide the advantages described above regarding the testing method for battery separators, which will not be repeated for the sake of brevity.

[0029] The above description is only an overview of the technical solution of this application. In order to better understand the technical means of this application and to implement it in accordance with the contents of the specification, and to make the above and other objects, features and advantages of this application more obvious and understandable, the following are specific embodiments of this application. Attached Figure Description

[0030] Various other advantages and benefits will become apparent to those skilled in the art upon reading the detailed description of the preferred embodiments below. The accompanying drawings are for illustrative purposes only and are not intended to limit the scope of this application. Furthermore, the same reference numerals denote the same parts throughout the drawings. In the drawings:

[0031] Figure 1 A flowchart illustrating a method for detecting a battery separator according to an exemplary embodiment;

[0032] Figure 2 A microscopic image illustrating a first detection image of a battery separator according to an exemplary embodiment;

[0033] Figure 3 A microscopic image illustrating a second detection image of a battery separator according to an exemplary embodiment;

[0034] Figure 4 For illustration purposes, according to an exemplary embodiment, Figure 1 A flowchart of a portion of the example process in the method;

[0035] Figure 5 For illustration purposes, according to an exemplary embodiment, Figure 4 A flowchart of a portion of the example process in the method;

[0036] Figure 6 This is a schematic diagram illustrating the first target image region in the second detected image according to an exemplary embodiment;

[0037] Figure 7 For illustration purposes, according to an exemplary embodiment, Figure 4 A flowchart of a portion of the example process in the method;

[0038] Figure 8 For illustration purposes, according to an exemplary embodiment, Figure 1 A flowchart of a portion of the example process in the method;

[0039] Figure 9 For illustration purposes, according to an exemplary embodiment, Figure 1 A flowchart of a portion of the example process in the method;

[0040] Figure 10 A microscopic image illustrating a third detection image of a battery negative electrode sheet according to an exemplary embodiment;

[0041] Figure 11 For illustration purposes, according to an exemplary embodiment, Figure 9 A flowchart of a portion of the example process in the method;

[0042] Figure 12 For illustration purposes, according to an exemplary embodiment, Figure 9 A flowchart of a portion of the example process in the method;

[0043] Figure 13 For illustration purposes, according to an exemplary embodiment, Figure 1 A flowchart of a portion of the example process in the method;

[0044] Figure 14 An energy dispersive spectroscopy (EDS) image illustrating a fourth detection image of chromium according to an exemplary embodiment;

[0045] Figure 15 An energy dispersive spectroscopy (EDS) image illustrating a fourth detection image of iron according to an exemplary embodiment;

[0046] Figure 16 For illustration purposes, according to an exemplary embodiment, Figure 13 A flowchart of a portion of the example process in the method;

[0047] Figure 17 An energy dispersive spectroscopy (EDS) image illustrating a fourth detection image of chromium according to another exemplary embodiment;

[0048] Figure 18 This is a schematic block diagram illustrating a battery separator detection device according to an exemplary embodiment;

[0049] Figure 19 An example configuration of a computing device that can be used to implement the methods described herein is shown. Detailed Implementation

[0050] The embodiments of the technical solution of this application will now be described in detail with reference to the accompanying drawings. These embodiments are only used to more clearly illustrate the technical solution of this application and are therefore merely examples, and should not be used to limit the scope of protection of this application.

[0051] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application pertains; the terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the application; the terms “comprising” and “having”, and any variations thereof, in the specification, claims, and foregoing description of the drawings are intended to cover non-exclusive inclusion.

[0052] In the description of the embodiments of this application, technical terms such as "first" and "second" are used only to distinguish different objects and should not be construed as indicating or implying relative importance or implicitly specifying the number, specific order, or primary and secondary relationship of the indicated technical features. In the description of the embodiments of this application, "multiple" means two or more, unless otherwise explicitly defined.

[0053] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of this application. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0054] In the description of the embodiments in this application, the term "and / or" is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, and B existing alone. Additionally, the character " / " in this document generally indicates that the preceding and following related objects have an "or" relationship.

[0055] In the description of embodiments of this application, the term "multiple" refers to two or more (including two), similarly, "multiple sets" refers to two or more (including two sets), and "multiple pieces" refers to two or more (including two pieces). The term "based on" should be interpreted as "at least partially based on". Furthermore, as used herein, the term "at least one of..." covers any one of the listed items and all possible combinations thereof.

[0056] In the description of the embodiments of this application, the technical terms "center," "longitudinal," "lateral," "length," "width," "thickness," "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "top," "bottom," "inner," "outer," "clockwise," "counterclockwise," "axial," "radial," and "circumferential" indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are only for the convenience of describing the embodiments of this application and simplifying the description, and are not intended to indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on the embodiments of this application.

[0057] In the description of the embodiments of this application, unless otherwise expressly specified and limited, technical terms such as "installation," "connection," "joining," and "fixing" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral part; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; they can refer to the internal communication of two components or the interaction between two components. For those skilled in the art, the specific meaning of the above terms in the embodiments of this application can be understood according to the specific circumstances.

[0058] Currently, high-density laser beams are generally used to irradiate the surface of the battery separator after battery disassembly, causing the surface components to form plasma and then volatilize.

[0059] However, during the disassembly of a battery, when separating the battery separator from the electrodes, some electrode materials, such as carbon powder or active materials, often adhere to the battery separator. It is usually impossible to directly detect metallic foreign objects covered by other substances, thus making it impossible to accurately analyze the type of metallic foreign objects.

[0060] To mitigate or eliminate the problem of being unable to determine the type of metallic foreign object when inspecting battery separators, one can first locate the ablation marks on the battery separator caused by a battery short circuit, and then analyze the cross-sectional morphology of the section processed through the ablation marks to determine the type of metallic foreign object.

[0061] Based on the above considerations, a method for detecting battery separators was designed. By analyzing the cross-sectional morphology of the ablation marks caused by battery short circuits on the battery separator, the problem of being unable to determine the type of metallic foreign matter when detecting battery separators can be alleviated, reduced, or eliminated.

[0062] The battery separator detection method disclosed in this application can be used to detect separators used in electrical devices such as vehicles, ships, or aircraft, including, for example, battery separators.

[0063] Reference Figure 1 Please refer to further details. Figures 2 to 3 . Figure 1 This is a flowchart illustrating a method 100 for detecting a battery separator 125 according to an exemplary embodiment. Figure 2 This is a microscopic image illustrating a first detection image 115 of a battery separator 125 according to an exemplary embodiment. Figure 3 This is a microscopic image illustrating a second detection image 135 of the battery separator 125 according to an exemplary embodiment. Method 100 includes steps S110 to S130.

[0064] In step S110, the first short-circuit trace region 120 is extracted from the first detection image 115. The first detection image 115 is obtained by imaging the battery separator 125 using a microscopic imaging device. The first short-circuit trace region 120 indicates the ablation traces on the battery separator 125 caused by a short circuit due to a metal foreign object 130 in the battery separator 125.

[0065] In step S120, predetermined image features 140 are extracted from the second detection image 135. The second detection image 135 is obtained by imaging the cross section of the battery separator 125 across the first short-circuit trace region 120 using a microscopic imaging device. A metallic foreign object 130 is present in the cross section of the first short-circuit trace region 120.

[0066] In step S130, the type of the metallic foreign object 130 is determined based on the extraction result of the predetermined image features 140.

[0067] According to some embodiments of this application, the microscopic imaging device may include, but is not limited to, a scanning electron microscope (SEM). According to some embodiments of this application, the first detection image 115 can be obtained by imaging the surface of the battery separator 125 stacked with the negative electrode sheet of the battery using the microscopic imaging device. It is understood that the first detection image 115 can also be obtained by imaging the surface of the battery separator 125 stacked with the positive electrode sheet of the battery using the microscopic imaging device.

[0068] exist Figure 2 In the example shown, the first short-circuit trace region 120 exhibits an irregular enclosed shape on the first detection image 115, indicating an ablation mark on the battery separator 125 caused by a battery short circuit. This ablation mark typically presents as a yellowish-brown halo. In some embodiments, the ablation mark can be quickly located using the contrast resolution of a microscopic imaging device.

[0069] According to some embodiments of this application, the cross-section of the battery separator 125 across the first short-circuit trace region 120 can be any cross-section of the battery separator 125, as long as the cross-section cuts through the first short-circuit trace region 120 on the surface of the battery separator 125. Figure 3 In the example shown, the white dotted areas in the cross-section indicate the presence of a metallic foreign object 130.

[0070] Method 100 determines the type of metallic foreign object by analyzing the cross section. This allows for the first location of ablation marks on the battery separator caused by a battery short circuit, followed by analysis of the cross section morphology through which the ablation marks are processed. This alleviates the problem of being unable to determine the type of metallic foreign object when inspecting the battery separator.

[0071] Reference Figure 4 Please refer to further details. Figure 3 . Figure 4 For illustration purposes, according to an exemplary embodiment, Figure 1 The flowcharts for some example processes in Method 100 are shown below. Figure 4 As shown, according to some embodiments, step S120, extracting predetermined image features from the second detected image, may include:

[0072] In step S410, a first target image region 145 is identified from the second detection image 135, and the first target image region 145 corresponds to the internal region of the diaphragm in the cross-section;

[0073] In step S420, predetermined image features 140 are extracted from the first target image region 145.

[0074] To perform image recognition of the internal region of the diaphragm in the cross-section, it is necessary to identify a first target image region 145 corresponding to the internal region of the diaphragm from the second detection image 135. Furthermore, it is necessary to extract predetermined image features 140 from the first target image region 145 to further analyze the type of metallic foreign object 130 present in the cross-section.

[0075] By identifying the first target image region 145 corresponding to the internal region of the diaphragm in the cross section from the second detection image 135, the recognition interference of image regions other than the internal region of the diaphragm in the cross section (e.g., the diaphragm surface region 150 in the cross section, the redundant blank region 155 in the second detection image 135) in the second detection image 135 can be reduced, thereby improving the extraction accuracy of the predetermined image feature 140.

[0076] Reference Figure 5 Please refer to further details. Figure 3 . Figure 5 For illustration purposes, according to an exemplary embodiment, Figure 4 The flowchart shows a partial example process of the method. For example... Figure 5 As shown, according to some embodiments, step S410, identifying the first target image region 145 from the second detection image 135, may include:

[0077] In step S510, edge detection is performed on the second detection image 135 to detect the first edge 160 and the second edge 165 of the cross section from the second detection image 135. The first edge 160 and the second edge 165 correspond to the edges of two opposing surfaces of the separator body of the battery separator 125 on the cross section, respectively.

[0078] In step S520, the image region located between the first edge 160 and the second edge 165 in the second detection image 135 is identified as the first target image region 145.

[0079] In this paper, the term "edge detection" refers to identifying points in a digital image where there are significant changes in brightness. In image processing and computer vision, significant changes in image attributes often reflect important events and changes in those attributes, including but not limited to discontinuities in depth, surface orientation discontinuities, changes in material properties, and changes in scene lighting.

[0080] In this document, the term "separator body" refers to the body portion of the battery separator 125 that does not include the upper and lower coating layers (e.g., aluminum oxide). According to some embodiments of this application, the edges of two opposing surfaces of the separator body of the battery separator 125 on a cross-section can be marked according to the placement position of the battery separator 125 in the second detection image 135, such that a first edge 160 corresponds to the edge of the upper surface of the separator body on the cross-section, and a second edge 165 corresponds to the edge of the lower surface of the separator body on the cross-section.

[0081] By performing edge detection on the second detection image 135, the first target image region 145 corresponding to the internal region of the diaphragm in the cross-section can be quickly and accurately identified, thereby improving detection efficiency.

[0082] Reference Figure 6 Please refer to further details. Figure 3 . Figure 6 This is a schematic diagram illustrating the first target image region 145 in the second detection image 135 according to an exemplary embodiment. Figure 6 As shown, the first edge 160 corresponds to the negative electrode side of the battery separator 125, and the second edge 165 corresponds to the positive electrode side of the battery separator 125. The predetermined image feature 140 includes at least one image sub-region 170 extending from the first edge 160 to the second edge 165. Each image sub-region 170 includes a first portion 175 closer to the first edge 160 and a second portion 180 closer to the second edge 165. The size of the first portion 175 along the first edge 160 is larger than the size of the second portion 180 along the second edge 165.

[0083] According to some embodiments of this application, the negative electrode side of the battery separator 125 refers to the side of the battery separator 125 adjacent to the negative electrode plate, and the positive electrode side of the battery separator 125 refers to the side of the battery separator 125 adjacent to the positive electrode plate. According to some embodiments of this application, the negative electrode side and the positive electrode side of the battery separator 125 can be marked before the microscopic imaging device images the cross section of the battery separator 125 across the first short-circuit trace region 120, so that the negative electrode side and the positive electrode side of the battery separator 125 can be found in the second detection image 135.

[0084] exist Figure 6In the example shown, the predetermined image feature 140 includes three image sub-regions 170 extending from a first edge 160 to a second edge 165. As an example, adjacent image sub-regions 170 are separated by dashed lines. Each image sub-region 170 includes a first portion 175 and a second portion 180. As an example, the first portion 175 and the second portion 180 are separated by a dotted-dashed line. Figure 6 As can be seen, the size of the first part 175 along the first edge 160 is larger than the size of the second part 180 along the second edge 165.

[0085] By setting the predetermined image feature 140 to include at least one image sub-region 170 comprising a first portion 175 that is larger in size and closer to the first edge 160 along the first edge 160 and a second portion 180 that is smaller in size and closer to the second edge 165 along the second edge 165, a criterion for determining the type of the metallic foreign object 130 can be preset, i.e., the size of the first portion 175 along the first edge 160 is greater than the size of the second portion 180 along the second edge 165, thereby increasing the likelihood of determining the type of the metallic foreign object 130.

[0086] Reference Figure 7 Please refer to further details. Figure 6 . Figure 7 For illustration purposes, according to an exemplary embodiment, Figure 4 The flowchart shows a partial example process of the method. For example... Figure 7 As shown, according to some embodiments, step S420, extracting predetermined image features 140 from the first target image region 145, may include:

[0087] In step S710, edge detection is performed on the first target image region 145 to detect a third edge 185. The third edge 185 is located between the first edge 160 and the second edge 165 and corresponds to the partial outline of the metal foreign object 130 on the cross-section. The average gray value of the image region between the first edge 160 and the third edge 185 is greater than the average gray value of the image region between the third edge 185 and the second edge 165.

[0088] In step S720, the peak point 190 and valley point 195 on the line of the third edge 185 relative to the line of the second edge 165 are detected;

[0089] In step S730, based on peak point 190 and valley point 195, the image region located between the first edge 160 and the third edge 185 in the first target image region 145 is divided into at least one image sub-region 170 arranged along the first edge 160, wherein every two adjacent peak points 190 and a valley point 195 located between the two adjacent peak points 190 jointly define an image sub-region 170.

[0090] exist Figure 3 In the example shown, the metallic foreign object 130 on the cross-section appears as the whitish areas of the pixels in the first target image area 145, and is presented as an inverted triangle or inverted cone ridge. It can be seen that... Figure 3 and Figure 6 As shown, the third edge 185 corresponds to those inverted triangular or inverted conical mountain peaks or waistlines.

[0091] In this article, the term "grayscale value" refers to a numerical value that divides white and black into several levels based on the different shades of gray that points on an image represent, following a logarithmic relationship. Generally, the higher the grayscale value, the whiter the pixel; for example, white is 255 and black is 0.

[0092] exist Figure 6 In the example shown, four peak points 190 (represented as solid black dots in the figure as an example) and three valley points 195 (represented as hollow black dots in the figure as an example) were detected on the line of the third edge 185 relative to the line of the second edge 165.

[0093] like Figure 6 As shown, every two adjacent peak points 190 and a valley point 195 located between the two adjacent peak points 190 jointly define an image sub-region 170. As an example, two adjacent image sub-regions 170 are separated by dashed lines.

[0094] By detecting the peak point 190 and valley point 195 on the line of the third edge 185, the first target image region 145 can be easily segmented into at least one image sub-region 170.

[0095] Reference Figure 8 Please refer to further details. Figure 6 . Figure 8 For illustration purposes, according to an exemplary embodiment, Figure 1 The flowchart shows a partial example process of the method. For example... Figure 8 As shown, according to some embodiments, step S130, determining the type of the metallic foreign object 130 based on the extraction result of the predetermined image features 140, may include:

[0096] In step S810, in response to extracting predetermined image features 140 from the second detection image 135, the metal foreign object 130 is determined to be of the first type, the first type indicating that the metal foreign object 130 is introduced during the preparation of the electrode sheet slurry and precipitated during battery cycling.

[0097] In step S820, in response to the failure to extract the predetermined image feature 140 from the second detection image 135, the metallic foreign object 130 is determined to be of the second type, which indicates that the metallic foreign object 130 was introduced during the battery production process after the process of preparing the slurry for the electrode sheet.

[0098] According to some embodiments of this application, the first type includes a precipitated type, characterized by a dendritic morphology under microscopic imaging and being wider on the negative electrode side and narrower on the positive electrode side. According to some embodiments of this application, the second type includes a hard type, which is defined as the absence of the regularity exhibited by the precipitated type.

[0099] Precipitated metal foreign matter 130 mainly originates from the paste used in preparing the electrode sheet. Therefore, if the type of metal foreign matter 130 is determined to be precipitated, its source can be traced through the paste supplier, and appropriate measures can be taken. Hard metal foreign matter 130 mainly originates from the processing technology, such as electrode sheet winding, equipment wear, etc. Therefore, if the type of metal foreign matter 130 is determined to be hard, its source can be traced through the processing technology, and appropriate measures can be taken.

[0100] By determining whether the predetermined image features 140 have been extracted, the type of the metallic foreign object 130 can be identified, thereby clarifying its specific source and providing a basis for improvement measures.

[0101] Reference Figure 9 and Figure 10 . Figure 9 For illustration purposes, according to an exemplary embodiment, Figure 1 The flowchart shows a portion of the example process in the method. Figure 10 This is a microscopic image illustrating a third detection image 200 of the negative electrode 210 of a battery according to an exemplary embodiment. (See also...) Figure 9 As shown, according to some embodiments, step S110, extracting the first short-circuit trace region 120 from the first detection image 115, may include:

[0102] In step S910, the second short-circuit trace region 205 is extracted from the third detection image 200. The third detection image 200 is obtained by imaging the battery negative electrode 210 stacked with the battery separator 125 using a microscopic imaging device. The second short-circuit trace region 205 indicates the ablation traces on the battery negative electrode 210 caused by the battery short circuit caused by the metal foreign object 130 in the battery separator 125.

[0103] In step S920, the first short-circuit trace region 120 corresponding to the second short-circuit trace region 205 is located in the first detection image 115.

[0104] According to some embodiments of this application, the battery negative electrode 210 can be manually placed in a microscopic imaging device, such as under a microscope, for defect observation, or the battery negative electrode 210 can be conveyed to a microscopic imaging device, such as under a microscope, for automatic identification via a conveyor belt.

[0105] Under normal circumstances, the coating of the battery separator 125 will be heated due to a short circuit, and the coating of the battery separator 125 near the center of the second short circuit trace area 205 will fall off and adhere to the negative electrode plate 210 of the battery. The diameter of the fallen material is generally 10-100um.

[0106] According to some embodiments of this application, since the battery negative electrode 210 and the battery separator 125 are adjacent, when a short circuit occurs in the battery, ablation marks will be generated on both the battery negative electrode 210 and the battery separator 125. When the location of the short circuit is different, the location of the ablation marks on the battery negative electrode 210 will be different, and corresponding ablation marks will also be generated at different locations on the battery separator 125. It should be noted that the ablation marks generated on the battery negative electrode 210 due to the battery short circuit correspond to the ablation marks generated on the battery separator 125 due to the battery short circuit. Therefore, the corresponding ablation marks on the battery separator 125 can be found based on the ablation marks on the battery negative electrode 210 caused by the battery short circuit.

[0107] By tracing the first short-circuit trace area 120 on the battery separator 125 by locating the second short-circuit trace area 205 on the negative electrode plate 210, the first short-circuit trace area 120 on the battery separator 125 can be located more easily, thereby improving the detection efficiency.

[0108] Reference Figure 11 . Figure 11 For illustration purposes, according to an exemplary embodiment, Figure 9 The flowchart shows a partial example process of the method. For example... Figure 11 As shown, according to some embodiments, step S910, extracting the second short-circuit trace region 205 from the third detection image 200, may include:

[0109] In step S1110, candidate short-circuit trace regions are identified from the third detection image 200;

[0110] In step S1120, in response to the candidate short-circuit trace region meeting the preset conditions, the candidate short-circuit trace region is determined as the second short-circuit trace region 205.

[0111] Since areas resembling the second short-circuit trace region 205 may be identified in the third detection image 200, some of these areas are not ablation marks caused by a battery short circuit, but rather substances such as carbon powder. Therefore, to reduce the possibility of false identification, a preset condition can be set, and only candidate short-circuit trace regions that meet the preset condition can be identified as the second short-circuit trace region 205.

[0112] By identifying candidate short-circuit trace areas and determining whether they meet preset conditions, the second short-circuit trace area 205 on the negative electrode plate 210 of the battery can be found more easily, thereby improving detection efficiency.

[0113] According to some embodiments of this application, the preset conditions include: the similarity between the candidate short-circuit trace region and the circle is greater than a similarity threshold, and the area of ​​the candidate short-circuit trace region is between a first threshold and a second threshold.

[0114] In this article, the term "similarity" refers to a measure of how close two things are to each other. The closer two things are, the greater their similarity; conversely, the more distant two things are, the smaller their similarity. Therefore, the similarity to a circle can be understood as the degree of resemblance to a circle, which can be expressed as a percentage.

[0115] In some embodiments, the similarity threshold can be at least 70%. In some embodiments, the first threshold can be 0.282 mm. 2 The second threshold can be 0.785mm. 2 .

[0116] By setting preset conditions, it is easier to identify which candidate short-circuit trace regions on the third detection image 200 can be used as the second short-circuit trace region 205.

[0117] Reference Figure 12 . Figure 12 For illustration purposes, according to an exemplary embodiment, Figure 9 The flowchart shows a partial example process of the method. For example... Figure 12 As shown, according to some embodiments, step S920, locating the first short-circuit trace region 120 corresponding to the second short-circuit trace region 205 in the first detection image 115, may include:

[0118] In step S1210, the first coordinates of the center of the second short-circuit trace region 205 in the image coordinate system of the third detection image 200 are determined from the third detection image 200;

[0119] In step S1220, based on the relative positional relationship between the battery negative electrode 210 and the battery separator 125, the first coordinate is converted into a second coordinate in the image coordinate system of the first detection image 115, and the second coordinate indicates the center of the first short circuit trace area 120.

[0120] In step S1230, the first short-circuit trace region 120 is located in the first detection image 115 with the second coordinate as the center.

[0121] In this paper, the term "image coordinate system" refers to a coordinate system whose origin is located at the center of the image plane of the third detection image 200 or the first detection image 115, and whose x-axis and y-axis are parallel to two adjacent perpendicular sides of the image plane, respectively. Of course, other definitions of "image coordinate system" are also possible.

[0122] Therefore, even if the metal foreign object 130 is small enough, the coordinates of the center of the second short-circuit trace region 205 and the center of the first short-circuit trace region 120 can be matched by a microscopic imaging device, such as a microscope, for two-dimensional identification. The matching of their coordinates can accurately locate the short-circuit point on the battery separator 125.

[0123] By transforming the coordinates between the first and second coordinates, the first short-circuit trace region 120 can be located more easily in the first detection image 115, thereby improving detection efficiency.

[0124] According to some embodiments of this application, the cross-section of the battery separator 125 across the first short-circuit trace region 120 is obtained by cross-section processing of the battery separator 125 using a cross-section processing apparatus. The cross-section processing apparatus includes at least one of an ion beam profile polishing apparatus and a focused ion beam apparatus. According to some embodiments, cross-section processing of the battery separator 125 using the cross-section processing apparatus includes:

[0125] Measure the maximum planar dimension of the portion of the metallic foreign object within the first short-circuit trace region 120 exposed on the surface of the battery separator 125;

[0126] In response to the maximum planar dimension being greater than or equal to a third threshold, the battery separator 125 is cross-sectionally processed using an ion beam profile polishing apparatus; and

[0127] In response to the maximum planar dimension being less than a third threshold, the battery separator 125 is cross-sectionally processed using a focused ion beam apparatus.

[0128] According to some embodiments of this application, the maximum planar dimension of the portion of the metallic foreign object exposed on the surface of the battery separator can be measured using calipers under microscopic imaging, such as a microscope. If the portion of the metallic foreign object exposed on the surface of the battery separator is circular, the maximum planar dimension is the diameter of the portion of the metallic foreign object exposed on the surface of the battery separator. In some embodiments, the third threshold can be 200 μm.

[0129] According to some embodiments of this application, different cross-sectional processing methods are selected based on the maximum planar size of the portion of the metallic foreign object exposed on the surface of the battery separator as observed by a microscopic imaging device. Specifically, the maximum planar size is determined as follows: if there is detachment of active material from the battery negative electrode sheet, such as carbon powder, it is the maximum planar size of the active material detached from the battery negative electrode sheet; if there is no detachment of active material from the battery negative electrode sheet, it is the maximum planar size of the portion of the metallic foreign object exposed on the surface of the battery separator corresponding to the center of the ablation mark on the battery negative electrode sheet. The former indicates that the detached active material from the battery negative electrode sheet adheres to the battery separator and completely covers the metallic foreign object, while the latter indicates that the metallic foreign object is directly observed on the battery separator.

[0130] In some embodiments, the processing accuracy of the ion beam profile polishing apparatus can be ±100 μm. The ion beam profile polishing apparatus uses an ion beam, such as an argon ion beam, to cut a sample, such as the profile of a battery separator. During the cutting process, a light-shielding plate is used to shield areas of the sample that are not desired to be cut by the ion beam.

[0131] In some embodiments, the processing accuracy of the focused ion beam device can be ±1 μm. In particular, when the maximum planar dimension is around 10 μm, using a focused ion beam device can reduce the possibility of missing metal foreign matter exposed on the surface of the battery separator due to device inaccuracies, thus preventing the possibility of undetected faults.

[0132] By measuring the maximum planar dimension of the portion of the metal foreign object exposed on the surface of the battery separator within the first short-circuit trace area 120 and selecting different cross-sectional processing methods based on this maximum planar dimension, the possibility of short-circuit point loss due to the precision of the processing device can be reduced while ensuring processing efficiency.

[0133] Refer again Figure 1 Alternatively or additionally, method 100 may also include step S140. It is understood that step S140 may also be omitted in method 100.

[0134] In step S140, the main element in the metallic foreign object 130 is determined, wherein the main element indicates the element of the metallic foreign object 130 that penetrates the battery separator 125.

[0135] When multiple metallic elements are present on the surface of the battery separator 125 near the short circuit point, it is necessary to determine the main element that punctures the separator and causes the micro-short circuit. The main element is the cause of abnormal self-discharge. In addition to the main element, the other elements are secondary elements that, although they are deposited, do not puncture the separator.

[0136] By identifying the main element in the metallic foreign object, when multiple metallic elements are present on the diaphragm surface near the short circuit point, it is possible to better distinguish between the main and secondary elements that cause the micro-short circuit, thereby enabling more accurate and efficient source investigation and the implementation of improvement measures.

[0137] Reference Figure 13 , Figure 14 and Figure 15 . Figure 13 For illustration purposes, according to an exemplary embodiment, Figure 1 The flowchart shows a portion of the example process in the method. Figure 14 This is an energy dispersive spectroscopy (EDS) image illustrating the fourth detection image 215 of chromium according to an exemplary embodiment. Figure 15 This is an energy dispersive spectral analysis image of the fourth detection image 215 of iron according to an exemplary embodiment. (See also:) Figure 13 As shown, according to some embodiments, step S140, determining the main element in the metallic foreign object 130, may include:

[0138] In step S1310, a second target image region 220 is identified from the fourth detection image 215. The second target image region 220 corresponds to the internal region of the diaphragm in the cross section. The fourth detection image 215 is obtained by imaging the cross section using an energy spectrum analyzer. The fourth detection image 215 indicates the distribution of each element present in the cross section.

[0139] In step S1320, for each element, it is determined whether the element exists in the second target image region 220 and whether the ratio of the number of pixels of the element in the second target image region 220 to the total number of pixels in the second target image region is greater than or equal to the fourth threshold.

[0140] In step S1330, in response to determining that the element exists within the second target image region 220 and that the ratio of the number of pixels of the element in the second target image region to the total number of pixels in the second target image region is greater than or equal to a fourth threshold, the element is determined to be a principal element.

[0141] According to some embodiments of this application, the fourth threshold can be 40%. Figure 14 and Figure 15In the example shown, chromium and iron are present in the second target image region 220, and the ratio of the number of pixels containing chromium and iron in the second target image region 220 to the total number of pixels in the second target image region is greater than or equal to a fourth threshold. Therefore, chromium and iron can be identified as the main elements.

[0142] By analyzing the fourth detection image 215 obtained by imaging the cross-section using an energy spectrum analyzer, it is easier to determine the main element that punctured the diaphragm, thereby enabling a more accurate analysis of the cause of the self-discharge anomaly.

[0143] Reference Figure 16 and Figure 17 . Figure 16 For illustration purposes, according to an exemplary embodiment, Figure 13 The flowchart shows a portion of the example process in the method. Figure 17 This is an energy dispersive spectroscopy (EDS) image illustrating a fourth detection image 215 of chromium according to another exemplary embodiment. (See also:) Figure 13 As shown, according to some embodiments, step S1310, identifying the second target image region 220 from the fourth detection image 215, may include:

[0144] In step S1610, edge detection is performed on the fourth detection image 215 to extract the first image region 225 and the second image region 230 from the fourth detection image 215. The first image region 225 and the second image region 230 correspond to the first coating and the second coating on two opposing surfaces of the battery separator, respectively.

[0145] In step S1620, the image region located between the first image region 225 and the second image region 230 in the fourth detection image is identified as the second target image region 220.

[0146] exist Figure 17 In the example shown, edge detection can be used to identify the upper and lower edges of the first and second coatings, thereby determining the specific locations of the first image region 225 and the second image region 230. According to some embodiments of this application, at least one of the first and second coatings may include an alumina coating.

[0147] By performing edge detection to identify the upper and lower coatings, it is easier to identify the second target image region 220 corresponding to the internal region of the diaphragm in the cross-section, thereby improving detection efficiency.

[0148] According to some embodiments of this application, see Figure 1This application provides a method 100 for detecting a battery separator 125. The method 100 includes, in step S110, extracting a first short-circuit trace region 120 from a first detection image 115. The first detection image 115 is obtained by imaging the battery separator 125 using a microscopic imaging device. The first short-circuit trace region 120 indicates ablation marks on the battery separator 125 caused by a short circuit due to a metal foreign object 130 in the battery separator 125. In step S120, a predetermined image feature 140 is extracted from a second detection image 135. The second detection image 135 is obtained by imaging the cross section of the battery separator 125 across the first short-circuit trace region 120 using a microscopic imaging device. A metal foreign object 130 is present in the cross section of the first short-circuit trace region 120. In step S130, the type of the metal foreign object 130 is determined based on the extraction result of the predetermined image feature 140. In step S140, the principal element in the metal foreign object 130 is determined, wherein the principal element indicates the element of the metal foreign object 130 that penetrates the battery separator 125.

[0149] Figure 18 This is a schematic block diagram illustrating a detection device 1800 for a battery separator 125 according to an exemplary embodiment.

[0150] like Figure 18 As shown, the detection device 1800 for the battery separator 125 includes: a first module 1810, a second module 1820, and a third module 1830.

[0151] The first module 1810 is configured to extract a first short-circuit trace region 120 from a first detection image 115. The first detection image 115 is obtained by imaging a battery separator 125 using a microscopic imaging device, and the first short-circuit trace region 120 indicates ablation marks on the battery separator 125 caused by a short circuit due to a metallic foreign object 130 in the battery separator 125.

[0152] The second module 1820 is configured to extract predetermined image features 140 from the second detection image 135. The second detection image 135 is obtained by imaging a cross section of the battery separator 125 across a first short-circuit trace region 120 using a microscopic imaging device, in which a metallic foreign object 130 is present.

[0153] The third module 1830 is configured to determine the type of the metallic foreign object 130 based on the extraction results of the predetermined image features 140.

[0154] It should be understood that Figure 18 Modules 1810, 1820, and 1830 of the device 1800 shown can be used with reference to Figure 1Steps S110-S130 in the described method 100 correspond to these steps. Therefore, the operation, features, and advantages described above for method 100 also apply to device 1800 and its included modules.

[0155] For the sake of brevity, certain operations, features, and advantages will not be elaborated upon here.

[0156] Refer again Figure 18 The detection device 1800 for the battery separator 125 may also include a fourth module 1840 (indicated by a dashed box).

[0157] The fourth module 1840 is configured to determine the principal element in the metallic foreign object 130, wherein the principal element indicates the element of the metallic foreign object 130 that penetrates the battery separator 125.

[0158] It should be understood that Figure 18 Module 1840 of the device 1800 shown can be used with reference Figure 1 This corresponds to step S140 in the described method 100.

[0159] For the sake of brevity, certain operations, features, and advantages will not be elaborated upon here.

[0160] While specific functions have been discussed above with reference to specific modules, it should be noted that the functions of the modules discussed herein can be divided into multiple modules, and / or at least some functions of multiple modules can be combined into a single module. The specific actions performed by the modules discussed herein include the specific module itself performing the action, or alternatively, the specific module calling or otherwise accessing another component or module that performs the action (or performs the action in conjunction with the specific module). Therefore, a specific module performing an action can include the specific module performing the action itself and / or another module that performs the action, called or otherwise accessed by the specific module.

[0161] It should also be understood that this article can describe various technologies in the general context of software and hardware components or program modules. The above regarding... Figure 18The various modules described can be implemented in hardware or in hardware in combination with software and / or firmware. For example, these modules can be implemented as computer program code / instructions configured to execute in one or more processors and stored in a computer-readable storage medium. Alternatively, these modules can be implemented as hardware logic / circuit. For example, in some embodiments, one or more of the first module 1810, the second module 1820, the third module 1830, and the fourth module 1840 can be implemented together in a System on Chip (SoC). The SoC may include an integrated circuit chip (which includes a processor (e.g., a Central Processing Unit (CPU), microcontroller, microprocessor, digital signal processor (DSP), etc.), memory, one or more communication interfaces, and / or one or more components of other circuitry) and may optionally execute received program code and / or include embedded firmware to perform functions.

[0162] In the following text, combined with Figure 19 Illustrative examples describing such computing devices, computer-readable storage media, and computer program products.

[0163] Figure 19 An example configuration of a computing device 1900 that can be used to implement the methods described herein is shown. The aforementioned apparatus 1800 may also be implemented wholly or at least partially by the computing device 1900 or similar devices or systems.

[0164] The computing device 1900 may include at least one processor 1902, memory 1904, multiple communication interfaces 1906, display device 1908, other input / output (I / O) devices 1910, and one or more mass storage devices 1912, which are capable of communicating with each other, such as via a system bus 1914 or other suitable connection.

[0165] Processor 1902 may be a single processing unit or multiple processing units, and all processing units may include single or multiple computing units or multiple cores. Processor 1902 may be implemented as one or more microprocessors, microcomputers, microcontrollers, digital signal processors, central processing units, state machines, logic circuits, and / or any device that manipulates signals based on operating instructions. Among other capabilities, processor 1902 may be configured to fetch and execute computer-readable instructions stored in memory 1904, mass storage device 1912, or other computer-readable media, such as program code for operating system 1916, program code for application program 1918, program code for other programs 1920, etc.

[0166] Memory 1904 and mass storage device 1912 are examples of computer-readable storage media for storing instructions executed by processor 1902 to perform the various functions described above. For example, memory 1904 can generally include both volatile and non-volatile memory (e.g., RAM, ROM, etc.). Furthermore, mass storage device 1912 can generally include hard disk drives, solid-state drives, removable media, including external and removable drives, memory cards, flash memory, floppy disks, optical disks (e.g., CDs, DVDs), storage arrays, network-attached storage, storage area networks, etc. Both memory 1904 and mass storage device 1912 can be collectively referred to herein as memory or computer-readable storage media, and can be non-transitory media capable of storing computer-readable, processor-executable program instructions as computer program code, which can be executed by processor 1902 as a specific machine configured to perform the operations and functions described in the examples herein.

[0167] Although Figure 19 The modules 1810, 1820, 1830, and 1840, or portions thereof, are illustrated as being stored in memory 1904 of computing device 1900; however, modules 1810, 1820, 1830, and 1840 may be implemented using any form of computer-readable medium accessible by computing device 1900. As used herein, “computer-readable medium” includes at least two types of computer-readable media: computer-readable storage media and communication media.

[0168] Computer-readable storage media include volatile and non-volatile, removable and non-removable media implemented by any method or technology for storing information such as computer-readable instructions, data structures, program modules, or other data. Computer-readable storage media include, but are not limited to, RAM, ROM, EEPROM, flash memory or other memory technologies, CD-ROM, DVD, or other optical storage devices, magnetic cassettes, magnetic tapes, disk storage devices or other magnetic storage devices, or any other non-transmission medium that can be used to store information for access by a computing device. In contrast, communication media can embody computer-readable instructions, data structures, program modules, or other data in modulated data signals such as carrier waves or other transmission mechanisms. Computer-readable storage media as defined herein do not include communication media.

[0169] Multiple programs may be stored on mass storage device 1912. These programs include operating system 1916, one or more application programs 1918, other programs 1920, and program data 1922, and they may be loaded into memory 1904 for execution. Examples of such application programs or program modules may include, for example, computer program logic (e.g., computer program code or instructions) for implementing components / functions such as method 100 (including any suitable steps of method 100), and / or other embodiments described herein.

[0170] One or more communication interfaces 1906 are used for exchanging data with other devices, such as via a network, direct connection, etc. Such communication interfaces can be one or more of the following: any type of network interface (e.g., a network interface card (NIC)), wired or wireless (such as IEEE 802.11 Wireless LAN (WLAN)) wireless interface, Wi-MAX interface, Ethernet interface, Universal Serial Bus (USB) interface, cellular network interface, Bluetooth™ interface, Near Field Communication (NFC) interface, etc. Communication interface 1906 can facilitate communication across a variety of network and protocol types, including wired networks (e.g., LAN, cable, etc.) and wireless networks (e.g., WLAN, cellular, satellite, etc.), the Internet, etc. Communication interface 1906 can also provide communication with external storage devices (not shown) such as storage arrays, network-attached storage, storage area networks, etc.

[0171] In some examples, a display device 1908, such as a monitor, may be included for displaying information and images to the user. Other I / O devices 1910 may be devices that receive various inputs from the user and provide various outputs to the user, and may include touch input devices, gesture input devices, cameras, keyboards, remote controls, mice, printers, audio input / output devices, and so on.

[0172] The techniques described herein can be supported by these various configurations of computing device 1900, and are not limited to specific examples of the techniques described herein. For example, the functionality can also be implemented wholly or partially on a “cloud” using a distributed system. A cloud includes and / or represents a platform for resources. The platform abstracts the underlying functionality of the cloud’s hardware (e.g., servers) and software resources. Resources may include applications and / or data that can be used when performing computational processing on servers remote from computing device 1900. Resources may also include services provided via the Internet and / or via subscriber networks such as cellular or Wi-Fi networks. The platform can abstract resources and functionality to connect computing device 1900 to other computing devices. Therefore, the implementation of the functionality described herein can be distributed throughout the cloud. For example, the functionality can be implemented partly on computing device 1900 and partly through a platform that abstracts the functionality of the cloud.

[0173] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of this application, and not to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features therein. These modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of this application, and they should all be covered within the scope of the claims and specification of this application. In particular, as long as there is no structural conflict, the various technical features mentioned in the embodiments can be combined in any way. This application is not limited to the specific embodiments disclosed herein, but includes all technical solutions falling within the scope of the claims.

Claims

1. A method of detecting a battery separator, characterized by, The method comprises: extracting a first short-circuit trace region from a first detection image, wherein the first detection image is obtained by imaging the battery separator by a microscopic imaging device, and the first short-circuit trace region indicates a burn trace caused by a battery short circuit on the battery separator due to a metal foreign matter in the battery separator; extracting a predetermined image feature from a second detection image, wherein the second detection image is obtained by imaging a cross-section of the battery separator across the first short-circuit trace region by the microscopic imaging device, and the cross-section of the first short-circuit trace region has the metal foreign matter; and determining a type of the metal foreign matter according to an extraction result of the predetermined image feature.

2. The method of claim 1, wherein, The extracting a predetermined image feature from a second detection image comprises: identifying a first target image region from the second detection image, wherein the first target image region corresponds to an internal region of the battery separator in the cross-section; and extracting the predetermined image feature from the first target image region.

3. The method of claim 2, wherein, The identifying a first target image region from the second detection image comprises: detecting a first edge and a second edge of the cross-section from the second detection image by performing edge detection on the second detection image, wherein the first edge and the second edge correspond to two opposite surfaces of a separator body of the battery separator on the cross-section; identifying an image region between the first edge and the second edge in the second detection image as the first target image region.

4. The method of claim 3, wherein, The first edge corresponds to a negative electrode side of the battery separator, the second edge corresponds to a positive electrode side of the battery separator, and the predetermined image feature comprises at least one image sub-region extending from the first edge to the second edge, wherein each image sub-region comprises a first part closer to the first edge and a second part closer to the second edge, and a size of the first part along the first edge is greater than a size of the second part along the second edge.

5. The method of claim 4, wherein, The extracting the predetermined image feature from the first target image region comprises: detecting a third edge from the first target image region by performing edge detection on the first target image region, wherein the third edge is located between the first edge and the second edge, and corresponds to a partial profile of the metal foreign matter on the cross-section, an average gray value of an image region between the first edge and the third edge is greater than an average gray value of an image region between the third edge and the second edge; detecting a peak point and a valley point of a line of the third edge relative to a line of the second edge; and based on the peak point and the valley point, dividing an image region between the first edge and the third edge in the first target image region into the at least one image sub-region arranged along the first edge, wherein each two adjacent peak points and a valley point located between the two adjacent peak points jointly define one image sub-region.

6. The method according to any one of claims 1-5, characterized in that, The determining a type of the metal foreign matter according to the extraction result of the predetermined image feature comprises: in response to the predetermined image feature being extracted from the second detection image, determining that the metal foreign object is of a first type, the first type indicating that the metal foreign object is introduced in a process of preparing a slurry of an electrode sheet and is precipitated in a battery cycle process; in response to the predetermined image feature failing to be extracted from the second detection image, determining that the metal foreign object is of a second type, the second type indicating that the metal foreign object is introduced in a process of producing a battery after the process of preparing the slurry of the electrode sheet.

7. The method according to any one of claims 1-5, characterized in that, the extracting the first short-circuit trace region from the first detection image comprises: extracting a second short-circuit trace region from a third detection image, wherein the third detection image is obtained by imaging, by a microscopic imaging device, a battery negative electrode sheet stacked with the battery separator, the second short-circuit trace region indicating an ablation trace caused by a battery short circuit on the battery negative electrode sheet due to the metal foreign object in the battery separator; and locating, in the first detection image, the first short-circuit trace region corresponding to the second short-circuit trace region.

8. The method of claim 7, wherein, the extracting the second short-circuit trace region from the third detection image comprises: identifying a candidate short-circuit trace region from the third detection image; and in response to the candidate short-circuit trace region satisfying a preset condition, determining the candidate short-circuit trace region as the second short-circuit trace region.

9. The method of claim 8, wherein, the preset condition comprises that a similarity between the candidate short-circuit trace region and a circle is greater than a similarity threshold, and an area of the candidate short-circuit trace region is between a first threshold and a second threshold.

10. The method of claim 7, wherein, the locating, in the first detection image, the first short-circuit trace region corresponding to the second short-circuit trace region comprises: determining, from the third detection image, a first coordinate of a center of the second short-circuit trace region in an image coordinate system of the third detection image; based on a relative positional relationship between the battery negative electrode sheet and the battery separator, converting the first coordinate into a second coordinate of the center of the first short-circuit trace region in an image coordinate system of the first detection image; and locating, in the first detection image, the first short-circuit trace region centered at the second coordinate.

11. The method according to any one of claims 1-5, characterized in that, the cross-section of the battery separator across the first short-circuit trace region is obtained by cross-section processing the battery separator by a cross-section processing device, the cross-section processing device comprising at least one of an ion beam profile grinder and a focused ion beam device, the cross-section processing the battery separator by the cross-section processing device comprising: measuring a maximum planar dimension of a portion of the metal foreign object exposed to a surface of the battery separator within the first short-circuit trace region; in response to the maximum planar dimension being greater than or equal to a third threshold, cross-section processing the battery separator using the ion beam profile grinder; and in response to the maximum planar dimension being less than the third threshold, cross-section processing the battery separator using the focused ion beam device.

12. The method of any one of claims 1-5, wherein, the method further comprises: determining a main element in the metal foreign object, wherein the main element indicates an element of the metal foreign object penetrating through the battery separator.

13. The method of claim 12, wherein, The determining the main element of the metal foreign matter comprises: identifying a second target image region from a fourth detection image, the second target image region corresponding to an internal region of the diaphragm in the section, wherein the fourth detection image is obtained by imaging the section by a spectrum analysis device, and the fourth detection image indicates a distribution of each element present in the section; for each of the elements, determining whether the element exists in the second target image region and whether a ratio of a number of pixel points of the element in the second target image region to a total number of pixel points of the second target image region is greater than or equal to a fourth threshold value; and in response to determining that the element exists in the second target image region and that the ratio of the number of pixel points of the element in the second target image region to the total number of pixel points of the second target image region is greater than or equal to the fourth threshold value, determining that the element is the main element.

14. The method of claim 13, wherein, The identifying the second target image region from the fourth detection image comprises: extracting a first image region and a second image region from the fourth detection image by performing edge detection on the fourth detection image, the first image region and the second image region corresponding to a first coating layer and a second coating layer on two surfaces of the battery diaphragm opposite to each other, respectively; and identifying an image region between the first image region and the second image region in the fourth detection image as the second target image region.

15. A testing device for battery separators, characterized in that, comprises: a first module configured to extract a first short-circuit trace region from a first detection image, wherein the first detection image is obtained by imaging the battery diaphragm by a microscopic imaging device, and the first short-circuit trace region indicates an ablation trace caused by a battery short circuit on the battery diaphragm due to a metal foreign matter in the battery diaphragm; a second module configured to extract a predetermined image feature from a second detection image, wherein the second detection image is obtained by imaging a section of the battery diaphragm across the first short-circuit trace region by the microscopic imaging device, and the section of the first short-circuit trace region has the metal foreign matter present therein; and a third module configured to determine a type of the metal foreign matter according to an extraction result of the predetermined image feature.

16. The apparatus of claim 15, wherein, The device further comprises: a fourth module configured to determine a main element of the metal foreign matter, wherein the main element indicates an element of the metal foreign matter penetrating through the battery diaphragm.

17. A computing device, comprising: comprises: at least one processor; and at least one memory connected with the at least one processor, and the at least one memory stores instructions, which, when executed by the at least one processor alone or jointly, cause the computing device to perform the method in any one of claims 1 to 14.

18. A computer-readable storage medium, characterized in that, instructions, which, when executed by one or more processors of a computing device alone or jointly, cause the computing device to perform the method in any one of claims 1 to 14.

19. A computer program product, characterised in that, instructions, which, when executed by one or more processors of a computing device alone or jointly, cause the computing device to perform the method in any one of claims 1 to 14.

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