Battery cell detection method, device, apparatus, readable storage medium and program product

Abstract

The application relates to a battery cell detection method, device, equipment, readable storage medium and program product. The method comprises the following steps: acquiring a first image, wherein the first image comprises a first region where a battery cell is located; determining a first edge line of the battery cell according to the first region; and determining a detection result of the battery cell based on the gray values of each pixel point in a preset region in the first image, wherein the detection result is used for indicating whether a bottom support sheet exists in the battery cell, and the preset region is a region within a preset range from the first edge line. According to the application, the position relationship between the bottom support sheet and the battery cell can be determined, the first edge line of the battery cell can be determined in the first image, the gray values of the pixel points near the first edge line are used to detect whether the bottom support sheet exists in the battery cell, the automation of the battery cell detection process is realized, manual detection is not needed, the labor cost is effectively reduced, and the detection efficiency is improved.

Description

Technical Field

[0001] This application relates to the field of battery cell testing technology, and in particular to a battery cell testing method, apparatus, equipment, readable storage medium, and program product. Background Technology

[0002] During battery manufacturing, bare cells typically need to be coated with a thin film after manufacturing before being installed in a rigid casing to complete assembly. To prevent direct contact between the cell and the casing, which could cause a short circuit, a support plate is often added to the bottom of the bare cell during the film coating process to ensure the performance stability of the cell.

[0003] Currently, to detect whether a battery cell has a base plate after the film coating process has been completed, manual inspection is often required, which results in low efficiency and high manpower costs for battery cell inspection. Summary of the Invention

[0004] This application provides a battery cell testing method, apparatus, device, readable storage medium, and program product to solve the technical problems of low efficiency and high manpower consumption in existing battery cell testing methods.

[0005] In a first aspect, embodiments of this application provide a cell testing method, including:

[0006] Acquire a first image, which includes a first region where the battery cell is located;

[0007] Based on the first region, determine the first edge line of the battery cell;

[0008] Based on the grayscale values ​​corresponding to each pixel in the preset region of the first image, the detection result of the battery cell is determined. The detection result is used to indicate whether the battery cell has a bottom support plate. The preset region is the area within a preset range from the first edge line.

[0009] In this embodiment, since the base plate is attached to the battery cell and its size is often smaller than the battery cell, the first edge line of the battery cell can be determined in the first image based on the positional relationship between the base plate and the battery cell. Then, the presence of the base plate in the battery cell can be detected based on the gray value of the pixels near the first edge line. This automates the battery cell detection process, eliminating the need for manual detection, effectively reducing manpower costs, and improving detection efficiency.

[0010] Optionally, in some embodiments, after acquiring the first image and before determining the first edge line of the cell based on the first region, the cell detection method further includes:

[0011] Based on the grayscale value corresponding to each pixel in the first image, determine the first pixel whose grayscale value is greater than or equal to the first threshold.

[0012] The smallest bounding rectangle of the first pixel is defined as the first region.

[0013] In this way, the first region where the battery cell is located can be determined directly based on the gray values ​​corresponding to each pixel in the first image, which can effectively save computing resources and improve the efficiency of identifying the first region.

[0014] Optionally, in some embodiments, acquiring the first image includes:

[0015] Get the initial image;

[0016] The initial image is preprocessed to obtain the first image.

[0017] In this embodiment, considering that there is often adhesive tape on the outside of the battery cell, which may interfere with the subsequent detection of whether the battery cell has a base plate, the acquired initial image can be preprocessed to reduce the interference of the adhesive tape on the battery cell detection and improve the accuracy of the battery cell detection results.

[0018] Optionally, in some embodiments, the initial image is preprocessed to obtain a first image, including:

[0019] The initial image is processed to obtain a grayscale image;

[0020] Adjust the contrast of the grayscale image to obtain the first image.

[0021] This embodiment can make the grayscale value of the tape part close to that of the cell part by grayscale processing and contrast adjustment, thereby reducing the interference of the tape on cell detection and improving the accuracy of cell detection results.

[0022] Optionally, in some embodiments, the initial image is preprocessed to obtain a first image, including:

[0023] The initial image is split into a three-channel image, which includes a red channel image, a green channel image, and a blue channel image;

[0024] The first image is determined from any one of the red, green, and blue channel images that meets the preset interference conditions.

[0025] In this embodiment, the initial image can be split into three-channel images, and the single-channel image with the least interference among the three-channel images can be selected as the first image, thereby improving the accuracy of the cell detection results.

[0026] Optionally, in some embodiments, the detection result of the battery cell is determined based on the grayscale values ​​corresponding to each pixel in a preset region of the first image, including:

[0027] Based on the gray values ​​of each pixel in the preset region of the first image, target pixels whose gray values ​​meet the preset conditions are determined.

[0028] The target edge line is obtained by fitting the target pixels;

[0029] The detection results of the battery cell are determined based on the number of target edge lines.

[0030] This embodiment can filter out target pixels whose grayscale values ​​meet preset conditions, fit the target edge lines, and determine whether the battery cell has a bottom support plate based on the number of target edge lines. The detection process is simple, effectively saves computing resources, and improves the efficiency of battery cell detection.

[0031] Optionally, in some embodiments, determining target pixels whose grayscale values ​​satisfy preset conditions based on the grayscale values ​​corresponding to each pixel in a preset region of the first image includes:

[0032] The preset area is divided along the extension direction of the first edge line to obtain N sub-regions, each sub-region including M pixels, where N and M are integers greater than 1;

[0033] The target pixel is determined from the M pixels in each sub-region, and the difference between the gray value of the target pixel and the gray value of its neighboring pixels is greater than or equal to the second threshold.

[0034] In this way, by dividing the preset area into multiple sub-regions and filtering the target pixels based on the difference in grayscale values ​​between pixels in each sub-region, the target pixels can be determined more accurately, thereby more precisely fitting the target edge line and further improving the accuracy of the cell detection results.

[0035] Optionally, in some embodiments, the target edge line is fitted based on the target pixel points, including:

[0036] Obtain the pixel coordinates of the target pixel;

[0037] The target pixel whose pixel coordinates meet the preset coordinate conditions is determined as the second pixel;

[0038] If the number of second pixels is greater than or equal to a preset threshold, a target edge line is obtained by fitting the second pixels.

[0039] This embodiment can eliminate interference items in the target pixel points based on pixel coordinates to improve the fitting accuracy of the target edge line, thereby improving the accuracy of the cell detection results.

[0040] Optionally, in some embodiments, the detection result of the battery cell is determined based on the number of target edge lines, including:

[0041] If the number of target edge lines is 0, it is determined that the cell does not have a bottom support plate.

[0042] In this way, the presence of a bottom support plate in the battery cell can be determined directly based on the number of target edge lines. The detection process is simple and convenient, consumes less computing power, and is highly efficient.

[0043] Optionally, in some embodiments, determining that the cell does not have a bottom support sheet when the number of target edge lines is 0 includes:

[0044] When the number of target edge lines is 0, the first image is input into the fuzzy recognition model to determine whether the first image is a fuzzy image;

[0045] If the first image is not a blurred image, it is determined that the battery cell does not have a base plate.

[0046] In this embodiment, when the number of target edge lines is 0, it can be determined whether the first image is a blurred image, verify the reliability of the number of target edge lines, and thus improve the accuracy of the cell detection results.

[0047] Optionally, in some embodiments, when the number of target edge lines is 0, after inputting the first image into the fuzzy recognition model to determine whether the first image is a fuzzy image, the cell detection method further includes:

[0048] If the first image is blurry, re-acquire the first image.

[0049] In this embodiment, if the first image is detected as a blurry image, the first image can be reacquired, and then the target edge lines can be identified based on the reacquired clear first image to obtain the accurate number of target edge lines, which can ensure the accuracy of the cell detection results.

[0050] Optionally, in some embodiments, the detection result of the battery cell is determined based on the number of target edge lines, including:

[0051] When the number of target edge lines is 2, it is determined that the battery cell has a bottom support plate.

[0052] In this way, the presence of a bottom support plate in the battery cell can be determined directly based on the number of target edge lines. The detection process is simple and convenient, consumes less computing power, and is highly efficient.

[0053] Optionally, in some embodiments, when the number of target edge lines is 2, determining that the cell has a base plate includes:

[0054] When the number of target edge lines is 2, and at least one target edge line is located in the first region, it is determined that the battery cell has a base plate.

[0055] In this embodiment, the presence of a base plate in a battery cell can be determined by combining the number of target edge lines and the position between the base plate and the battery cell, thereby further ensuring the accuracy of the battery cell detection results.

[0056] Optionally, in some embodiments, when the first image includes a first end of the battery cell, determining the detection result of the battery cell based on the number of target edge lines includes:

[0057] When the number of target edge lines is 1, a second image is obtained. The second image includes the second end of the battery cell, which is opposite to the first end.

[0058] If the number of target edge lines in the second image is 1, it is determined that the battery cell does not have a bottom support plate.

[0059] In this embodiment, by detecting the number of target edge lines in the image at the other end of the battery cell, the situation where the bottom support is misaligned and therefore cannot be detected can be ruled out, thereby improving the accuracy of the battery cell detection results.

[0060] Optionally, in some embodiments, when the number of target edge lines is 1, after acquiring the second image, the method further includes:

[0061] When the number of target edge lines in the second image is 2, it is determined that the battery cell has a base plate.

[0062] In this embodiment, the number of target edge lines in the image at the other end of the battery cell can be detected. By combining the number of target edge lines at both ends of the battery cell, it is possible to more accurately determine whether the battery cell has a bottom support plate.

[0063] Secondly, embodiments of this application provide a battery cell testing device, comprising:

[0064] The acquisition module is used to acquire a first image, the first image including a first region where the first end of the battery cell is located;

[0065] The first determining module is used to determine the first edge line of the battery cell based on the first region;

[0066] The second determining module is used to determine the detection result of the battery cell based on the gray value corresponding to each pixel in the preset area of ​​the first image. The detection result is used to indicate whether the battery cell has a bottom support piece. The preset area is the area within a preset range from the first edge line.

[0067] Thirdly, embodiments of this application provide an electronic device, the device including: a processor and a memory storing program instructions; the processor executes the program instructions to implement the method of the first aspect.

[0068] Fourthly, embodiments of this application provide a readable storage medium storing program instructions, which, when executed by a processor, implement the method of the first aspect.

[0069] Fifthly, embodiments of this application provide a computer program product in which instructions, when executed by a processor of an electronic device, cause the electronic device to perform the method of the first aspect.

[0070] 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

[0071] To more clearly illustrate the technical solutions of the embodiments of this application, the drawings used in the embodiments of this application will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on the drawings without creative effort.

[0072] Figure 1 This is a schematic flowchart of a cell testing method provided in one embodiment of this application;

[0073] Figure 2 This is a schematic diagram of the first region in the cell testing method provided in the embodiments of this application;

[0074] Figure 3 This is a schematic diagram of the state of preprocessing the first image in the cell detection method provided in the embodiments of this application;

[0075] Figure 4a This is a schematic diagram of the red channel image in the cell testing method provided in the embodiments of this application;

[0076] Figure 4b This is a schematic diagram of the green channel image in the cell testing method provided in the embodiments of this application;

[0077] Figure 4c This is a schematic diagram of the blue channel image in the cell testing method provided in the embodiments of this application;

[0078] Figure 5 This is a schematic diagram of a sub-region in the cell detection method provided in the embodiments of this application;

[0079] Figure 6 This is a schematic diagram of the target edge line in the cell detection method provided in the embodiments of this application;

[0080] Figure 7This is a schematic diagram of the structure of a battery cell testing device provided in another embodiment of this application;

[0081] Figure 8 This is a schematic diagram of the structure of an electronic device provided in another embodiment of this application.

[0082] The accompanying drawings are not necessarily drawn to scale. Detailed Implementation

[0083] The embodiments of this application will be described in further detail below with reference to the accompanying drawings and examples. The detailed description of the following embodiments and the accompanying drawings are used to illustrate the principles of this application by way of example, but should not be used to limit the scope of this application, that is, this application is not limited to the described embodiments.

[0084] In the description of this application, it should be noted that, unless otherwise stated, "a plurality of" means two or more; the terms "upper," "lower," "left," "right," "inner," and "outer," etc., indicating orientation or positional relationships, are only for the convenience of describing this application and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as a limitation on this application. Furthermore, the terms "first," "second," and "third," etc., are used for descriptive purposes only and should not be construed as indicating or implying relative importance. "Vertical" is not vertical in the strict sense, but within the allowable tolerance range. "Parallel" is not parallel in the strict sense, but within the allowable tolerance range.

[0085] In this application, the reference to "embodiment" means that a specific 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 mutually exclusive, independent, or alternative embodiment. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described in this application can be combined with other embodiments.

[0086] This application provides a battery cell testing method, apparatus, device, readable storage medium, and program product to solve the technical problems of low efficiency and high manpower consumption in existing battery cell testing methods. The battery cell testing method provided in this application is described below first.

[0087] Please see Figure 1 , Figure 1 This is a schematic flowchart of a battery cell testing method provided in one embodiment of this application. The battery cell testing method may include the following steps:

[0088] Step 101: Obtain a first image, the first image including a first region where the battery cell is located;

[0089] Step 102: Determine the first edge line of the battery cell based on the first region;

[0090] Step 103: Based on the grayscale values ​​corresponding to each pixel in the preset area of ​​the first image, determine the detection result of the battery cell. The detection result is used to indicate whether the battery cell has a bottom support plate. The preset area is the area within a preset range from the first edge line.

[0091] In this embodiment, a first image can be acquired. Based on the first region where the battery cell is located in the first image, the first edge line of the battery cell is determined. A preset region in the first image is located within a preset range from the first edge line. Then, based on the grayscale values ​​of each pixel in the preset region, it is determined whether a base plate is detected near the first edge line. This allows for the determination of the battery cell's detection result, i.e., whether the battery cell has a base plate. Since the base plate is attached to the battery cell and is often smaller than the battery cell, the presence of a base plate can be automated by determining the first edge line of the battery cell in the first image based on the positional relationship between the base plate and the battery cell, and then detecting whether the battery cell has a base plate based on the grayscale values ​​of the pixels near the first edge line. This eliminates the need for manual inspection, effectively reducing manpower costs and improving detection efficiency.

[0092] In step 101, a first image can be acquired, which may be an image obtained by an image acquisition device capturing the battery cell. It is understood that the first image may include the captured content of at least one end of the battery cell.

[0093] After acquiring the first image, a first region of the battery cell within the first image can be identified. For example, the first image can be input into a pre-trained object detection network, and the first region can be identified through feature detection, semantic detection, or other methods. Alternatively, the first region in the first image can be determined by identifying the pixel to which the battery cell belongs based on the grayscale values ​​of each pixel in the first image.

[0094] In step 102, after identifying the first region where the battery cell is located in the first image, the first edge line of the battery cell can be determined. The first edge line can be used to characterize the position of one end of the battery cell in the first image.

[0095] In step 103, the area in the first image that is within a preset range from the first edge line can be defined as the preset area. The preset range can be set according to the actual situation and is not specifically limited here. The preset area can represent the area near one end of the battery cell.

[0096] Understandably, the thin film is typically wrapped around the outside of the battery cell, while the base plate is attached to the outside of the battery cell, and the size of the base plate is usually smaller than that of the battery cell. Based on this positional relationship, a preset area can be detected to determine whether a base plate is present on a battery cell covered with a thin film.

[0097] For example, the presence of a base plate in the battery cell can be determined based on the grayscale values ​​of each pixel in a preset area. For instance, the grayscale value range corresponding to the base plate area can be determined according to the actual situation. By identifying the pixels in the preset area whose grayscale values ​​satisfy the grayscale value range corresponding to the base plate area, and then determining whether the area of ​​these pixels satisfies the positional relationship of the base plate, such as whether it is located within the first area, it can be determined whether the battery cell has a base plate.

[0098] For example, it could also detect whether a target edge line exists within a preset area. This target edge line is understood to be an edge line distinct from the first edge line of the battery cell. If a target edge line exists, its position can be used to determine whether a base plate exists within the battery cell. Since the base plate is typically smaller than the battery cell, if the target edge line is located within the first area, it can be considered the edge line of the base plate, and therefore, the battery cell can be considered to have a base plate.

[0099] For example, if a target edge line is detected in a preset area, the presence of a base plate in the battery cell can be determined based on the number of target edge lines. Since a base plate and a thin film are usually present on the outside of the battery cell, if two target edge lines are detected in the preset area, one of them can be considered to be the edge line of the thin film and the other to be the edge line of the base plate. Therefore, it can be concluded that a base plate is present in the battery cell.

[0100] Optionally, in some embodiments, after step 101 and before step 102, the cell detection method may further include the following steps:

[0101] Based on the grayscale value corresponding to each pixel in the first image, determine the first pixel whose grayscale value is greater than or equal to the first threshold.

[0102] The smallest bounding rectangle of the first pixel is defined as the first region.

[0103] It is understandable that, such as Figure 2 As shown, the battery cell portion is often the brightest area (white) in the first image. Based on this feature, the first pixel with a grayscale value greater than or equal to a first threshold in the first image can be identified as the pixel to which the battery cell belongs. Then, based on the region where the first pixel is located, its minimum bounding rectangle can be drawn, and this minimum bounding rectangle can be determined as the first region 201 of the battery cell. It can be understood that the first edge line of the battery cell can be one side length of the minimum bounding rectangle.

[0104] In this way, the first region where the battery cell is located can be determined directly based on the gray values ​​corresponding to each pixel in the first image, which can effectively save computing resources and improve the efficiency of identifying the first region.

[0105] Optionally, in some embodiments, step 101 above may include the following steps:

[0106] Get the initial image;

[0107] The initial image is preprocessed to obtain the first image.

[0108] It is understandable that after the battery cell is coated with a thin film, it is often necessary to seal the battery cell with adhesive to prevent the film from falling off. Therefore, there is often adhesive tape on the outside of the battery cell, which may interfere with the subsequent detection of whether the battery cell has a base plate, resulting in inaccurate battery cell detection results.

[0109] Based on this, an initial image can be obtained first, and then preprocessed such as channel splitting and grayscale processing can be performed on the initial image to obtain the first image, so as to reduce the interference of tape on cell detection and improve the accuracy of cell detection results.

[0110] Optionally, in some embodiments, the preprocessing of the initial image to obtain the first image may include the following steps:

[0111] The initial image is processed to obtain a grayscale image;

[0112] Adjust the contrast of the grayscale image to obtain the first image.

[0113] In this embodiment, the initial image of the battery cell captured by the image acquisition device can be a color image. This initial image can be first processed into a grayscale image. In the grayscale image, the tape portion usually appears as a darker area. To reduce the interference of this area on subsequent detection of whether the battery cell has a base plate, such as... Figure 3 As shown, this method can enhance the contrast of the grayscale image, making the overall grayscale image brighter, resulting in the first image. This allows the brightness of the tape portion in the first image to approach that of the battery cell, thereby mitigating the impact of the tape area's grayscale value on the detection of the base plate and improving the accuracy of the battery cell detection results.

[0114] Adjusting the contrast of a grayscale image can be achieved, for example, by calculating the grayscale value of each pixel in the first image according to a preset linear equation y = kx + b. Here, x is the grayscale value before contrast adjustment, y is the grayscale value after contrast adjustment, and k and b are parameters to be adjusted, which can be set according to the actual situation.

[0115] Adjusting the k value directly affects the grayscale values ​​of the first image. When k is less than 1, the difference in grayscale values ​​between pixels decreases; when k is greater than 1, the difference in grayscale values ​​between pixels increases, achieving the effect of contrast adjustment. Adjusting the b value affects the overall brightness of the first image. When b is greater than 0, the overall brightness of the first image increases; when b is less than 0, the overall brightness of the first image decreases.

[0116] In the calculation, the grayscale value of each pixel can range from 0 to 255. When the grayscale value is 0, the pixel appears black; the larger the grayscale value, the closer the pixel is to white. When the calculated y value is greater than 255, it will be directly set to 255.

[0117] In this embodiment, since the tape portion is darker and has a smaller grayscale value, in order to make it closer to the grayscale value of the battery cell portion, the k value can be increased, so that the difference between the grayscale value of the tape portion and the grayscale value of the battery cell portion can be reduced.

[0118] Optionally, in some embodiments, the preprocessing of the initial image to obtain the first image may further include the following steps:

[0119] The initial image is split into a three-channel image, which includes a red channel image, a green channel image, and a blue channel image;

[0120] The first image is determined from any one of the red, green, and blue channel images that meets the preset interference conditions.

[0121] In this embodiment, the initial image captured by the image acquisition device of the battery cell can be a color image. Please refer to [link to relevant documentation]. Figure 4a , Figure 4b and Figure 4c The initial color image can be split into three single-channel images: a red channel image, a green channel image, and a blue channel image. Then, the single-channel image that satisfies a preset interference condition can be selected as the first image. This preset interference condition can be determined based on the color of the tape.

[0122] For example, existing battery cells typically use blue adhesive to encapsulate the thin film. Therefore, the interference in the blue adhesive portion is minimal in the blue channel. Thus, the blue channel image can be selected as the first image to improve the accuracy of battery cell detection results.

[0123] Optionally, in some embodiments, step 103 above may include the following steps:

[0124] Based on the gray values ​​of each pixel in the preset region of the first image, target pixels whose gray values ​​meet the preset conditions are determined.

[0125] The target edge line is obtained by fitting the target pixels;

[0126] The detection results of the battery cell are determined based on the number of target edge lines.

[0127] In this embodiment, target pixels whose grayscale values ​​meet preset conditions in a preset area can be identified. Then, based on an existing straight line fitting algorithm, the target pixels are fitted to obtain target edge lines. It can be understood that the number of target edge lines obtained by fitting can be 0, one, or multiple.

[0128] The gray value of the target pixel must meet a preset condition. This can be that the gray value of the target pixel is within a preset gray value range, or that the difference between the gray value of the target pixel and the gray values ​​of its neighboring pixels meets a preset difference condition, such as being greater than or equal to a certain threshold. No specific limitation is made here.

[0129] After fitting the target edge line, the presence or absence of a bottom support plate in the battery cell can be determined based on the number of target edge lines. For example, if the number of target edge lines is 0, it can be assumed that the battery cell does not have a bottom support plate; if the number of target edge lines is 2, it can be assumed that the battery cell has a bottom support plate.

[0130] This embodiment can filter out target pixels whose grayscale values ​​meet preset conditions, fit the target edge lines, and determine whether the battery cell has a bottom support plate based on the number of target edge lines. The detection process is simple, effectively saves computing resources, and improves the efficiency of battery cell detection.

[0131] Optionally, in some embodiments, determining the target pixel whose grayscale value satisfies the preset condition based on the grayscale value corresponding to each pixel in the preset region of the first image may include the following steps:

[0132] The preset area is divided along the extension direction of the first edge line to obtain N sub-regions, each sub-region including M pixels, where N and M are integers greater than 1;

[0133] The target pixel is determined from the M pixels in each sub-region, and the difference between the gray value of the target pixel and the gray value of its neighboring pixels is greater than or equal to the second threshold.

[0134] It is understandable that the brightness of an edge line often differs from the brightness of its surrounding area. Therefore, the target pixel that may belong to the target edge line can be determined based on the difference in grayscale values ​​between pixels.

[0135] In this embodiment, as Figure 5As shown, the preset area can be divided into multiple sub-regions 501 along the extension direction of the first edge line. The gray value difference between each pixel in each sub-region 501 and its neighboring pixels can be calculated. If the difference is greater than or equal to the second threshold, the pixel can be considered as the target pixel to which the target edge line belongs.

[0136] In this way, by dividing the preset area into multiple sub-regions and filtering the target pixels based on the difference in grayscale values ​​between pixels in each sub-region, the target pixels can be determined more accurately, thereby more precisely fitting the target edge line and further improving the accuracy of the cell detection results.

[0137] Optionally, in some embodiments, the above-mentioned fitting of the target edge line based on the target pixel points may include the following steps:

[0138] Obtain the pixel coordinates of the target pixel;

[0139] The target pixel whose pixel coordinates meet the preset coordinate conditions is determined as the second pixel;

[0140] If the number of second pixels is greater than or equal to a preset threshold, a target edge line is obtained by fitting the second pixels.

[0141] In this embodiment, the coordinates of target pixels can be obtained, and target pixels whose coordinates satisfy a preset coordinate condition are determined as second pixels. The preset coordinate condition can be determined based on a first edge line. For example, an image coordinate system can be established based on the first edge line, where the Y-axis is parallel to the first edge line; in other words, the X-axis coordinates of all pixels on the first edge line are equal. Based on this, target pixels whose X-axis coordinate differences are less than a preset difference threshold can be determined as a group of second pixels.

[0142] It is understandable that the target pixel may include a group of second pixels or multiple groups of second pixels.

[0143] like Figure 6 As shown, when the number of a group of second pixels is greater than or equal to a preset threshold, a target edge line 601 can be fitted from this group of second pixels. If the number of a group of second pixels is less than the preset threshold, the pixels may be considered interference points and can be removed to improve the fitting accuracy of the target edge line, thereby improving the accuracy of cell detection.

[0144] This embodiment can eliminate interference items in the target pixels based on pixel coordinates to improve the fitting accuracy of the target edge line, thereby improving the accuracy of the cell detection results.

[0145] Optionally, in some embodiments, determining the cell detection result based on the number of target edge lines may include the following steps:

[0146] If the number of target edge lines is 0, it is determined that the cell does not have a bottom support plate.

[0147] In this embodiment, if the number of target edge lines is 0, it can be assumed that there are no edge lines of the film and the base plate in the first image, and therefore, it can be assumed that the battery cell does not have a base plate. Thus, the presence of a base plate in the battery cell can be directly determined based on the number of target edge lines. The detection process is simple and convenient, consumes less computing power, and is highly efficient.

[0148] Optionally, in some embodiments, determining that the cell does not have a bottom support sheet when the number of target edge lines is 0 may include the following steps:

[0149] When the number of target edge lines is 0, the first image is input into the fuzzy recognition model to determine whether the first image is a fuzzy image;

[0150] If the first image is not a blurred image, it is determined that the battery cell does not have a base plate.

[0151] It is understandable that during cell detection, the images captured by the image acquisition device may be blurry, which may affect the subsequent recognition of the target edge lines. In order to further improve the accuracy of the cell detection results, in this embodiment, when the number of target edge lines is 0, the first image can be input into the blur recognition model, wherein the blur recognition model can be pre-trained based on multiple blurry images and multiple clear images.

[0152] Fuzzy recognition models can be used to detect whether an input image is blurry. In other words, by inputting a first image into a fuzzy recognition model, it can be determined whether the first image is a blurry image.

[0153] If the first image is not a blurry image, it can be considered that the first image is clear. The first image itself will not affect the recognition of the target edge line. Therefore, the result that the number of target edge lines is 0 can be considered reliable. At this time, it can be determined that the battery cell does not have a bottom support plate.

[0154] Optionally, in some embodiments, after inputting the first image into the fuzzy recognition model to determine whether the first image is a fuzzy image when the number of target edge lines is 0, the cell detection method may further include the following steps:

[0155] If the first image is blurry, re-acquire the first image.

[0156] In this embodiment, if the first image is detected as a blurry image, the first image can be reacquired, and then the target edge lines can be identified based on the reacquired clear first image to obtain the accurate number of target edge lines, which can ensure the accuracy of the cell detection results.

[0157] Optionally, in some embodiments, determining the cell detection result based on the number of target edge lines may include the following steps:

[0158] When the number of target edge lines is 2, it is determined that the battery cell has a bottom support plate.

[0159] Understandably, since the film and the base plate are usually made of the same material, it is difficult to distinguish between the two. This embodiment can directly determine whether a base plate exists in the battery cell based on the number of target edge lines.

[0160] In this embodiment, if two target edge lines are detected, one can be considered the edge line of the thin film, and the other the edge line of the base plate. In other words, it can be determined that the battery cell has a base plate. Thus, the presence of a base plate in the battery cell can be directly determined based on the number of target edge lines. The detection process is simple and convenient, requires less computational power, and is highly efficient.

[0161] Optionally, in some embodiments, determining the presence of a base plate in the battery cell when the number of target edge lines is 2 may include the following steps:

[0162] When the number of target edge lines is 2, and at least one target edge line is located in the first region, it is determined that the battery cell has a base plate.

[0163] In this embodiment, in addition to the number of target edge lines, the position between the base plate and the battery cell can also be considered to jointly determine whether the battery cell has a base plate, further ensuring the accuracy of the battery cell detection results. For example, if the number of target edge lines is 2, and at least one target edge line is located in the first area, it can be considered that there is an edge line corresponding to the base plate among the target edge lines, and at this time it can be determined that the battery cell has a base plate.

[0164] Optionally, in some embodiments, when the first image includes the first end of the battery cell, the above-mentioned determination of the battery cell detection result based on the number of target edge lines may include the following steps:

[0165] When the number of target edge lines is 1, a second image is obtained. The second image includes the second end of the battery cell, which is opposite to the first end.

[0166] If the number of target edge lines in the second image is 1, it is determined that the battery cell does not have a bottom support plate.

[0167] In this embodiment, the first image can be an image captured by the image acquisition device at the first end of the battery cell. When the target edge line in the first image is 1, it can be considered that there are two situations: one is that the battery cell does not have a bottom support piece, and the target edge line is the edge line corresponding to the film; the other is that the battery cell has a bottom support piece, but the bottom support piece is misaligned, causing the edge line of the bottom support piece to coincide with the edge line of the film, so only one target edge line is detected.

[0168] Based on this, this embodiment can acquire a second image, which is an image captured by the image acquisition device of the second end of the battery cell, with the first end opposite to the second end. Then, the detection method described above can be used to detect the number of target edge lines in the second image.

[0169] If the number of target edge lines in the second image is also 1, then it can be assumed that the cell does not have a base plate, and one target edge line is the edge line corresponding to the thin film.

[0170] In this embodiment, by detecting the number of target edge lines in the image at the other end of the battery cell, the situation where the bottom support is misaligned and therefore cannot be detected can be ruled out, thereby improving the accuracy of the battery cell detection results.

[0171] Optionally, in some embodiments, when the number of target edge lines is 1, after acquiring the second image, the cell detection method may further include the following steps:

[0172] When the number of target edge lines in the second image is 2, it is determined that the battery cell has a base plate.

[0173] In this embodiment, if the number of target edge lines in the second image is 2, it can be considered that the bottom support of the battery cell is misaligned, that is, the battery cell has a bottom support.

[0174] In this embodiment, the number of target edge lines in the image at the other end of the battery cell can be detected. By combining the number of target edge lines at both ends of the battery cell, it is possible to more accurately determine whether the battery cell has a bottom support plate.

[0175] Based on the cell testing method provided in the above embodiments, this application also provides an embodiment of a cell testing device.

[0176] Figure 7 A schematic diagram of a cell testing device provided in another embodiment of this application is shown. For ease of explanation, only the parts related to the embodiments of this application are shown.

[0177] Reference Figure 7 The cell testing device 700 may include:

[0178] Acquisition module 701 is used to acquire a first image, the first image including a first region where the battery cell is located;

[0179] The first determining module 702 is used to determine the first edge line of the battery cell based on the first region;

[0180] The second determining module 703 is used to determine the detection result of the battery cell based on the gray value corresponding to each pixel in the preset area of ​​the first image. The detection result is used to indicate whether the battery cell has a bottom support piece. The preset area is the area within a preset range from the first edge line.

[0181] In the embodiments of this application,

[0182] Optionally, in some embodiments, the cell detection device 700 may further include:

[0183] The third determining module is used to determine the first pixel whose gray value is greater than or equal to the first threshold based on the gray value corresponding to each pixel in the first image.

[0184] The fourth determining module is used to determine the smallest bounding rectangle of the first pixel as the first region.

[0185] Optionally, in some embodiments, the acquisition module 701 may include:

[0186] The acquisition unit is used to acquire the initial image;

[0187] The preprocessing unit is used to preprocess the initial image to obtain the first image.

[0188] Optionally, in some embodiments, the preprocessing unit may be used for:

[0189] The initial image is processed to obtain a grayscale image;

[0190] Adjust the contrast of the grayscale image to obtain the first image.

[0191] Optionally, in some embodiments, the preprocessing unit may also be used for:

[0192] The initial image is split into a three-channel image, which includes a red channel image, a green channel image, and a blue channel image;

[0193] The first image is determined from any one of the red, green, and blue channel images that meets the preset interference conditions.

[0194] Optionally, in some embodiments, the second determining module 703 may include:

[0195] The first determining unit is used to determine target pixels whose gray values ​​satisfy preset conditions based on the gray values ​​corresponding to each pixel in a preset region of the first image.

[0196] The fitting unit is used to fit the target edge line based on the target pixel points;

[0197] The second determining unit is used to determine the detection result of the battery cell based on the number of target edge lines.

[0198] Optionally, in some embodiments, the first determining unit may be used to:

[0199] The preset area is divided along the extension direction of the first edge line to obtain N sub-regions, each sub-region including M pixels, where N and M are integers greater than 1;

[0200] The target pixel is determined from the M pixels in each sub-region, and the difference between the gray value of the target pixel and the gray value of its neighboring pixels is greater than or equal to the second threshold.

[0201] Optionally, in some embodiments, the fitting unit may be used for:

[0202] Obtain the pixel coordinates of the target pixel;

[0203] The target pixel whose pixel coordinates meet the preset coordinate conditions is determined as the second pixel;

[0204] If the number of second pixels is greater than or equal to a preset threshold, a target edge line is obtained by fitting the second pixels.

[0205] Optionally, in some embodiments, the second determining unit may be used to:

[0206] If the number of target edge lines is 0, it is determined that the cell does not have a bottom support plate.

[0207] Optionally, in some embodiments, the second determining unit may also be used for:

[0208] When the number of target edge lines is 0, the first image is input into the fuzzy recognition model to determine whether the first image is a fuzzy image;

[0209] If the first image is not a blurred image, it is determined that the battery cell does not have a base plate.

[0210] Optionally, in some embodiments, the acquisition module 70 may also be used for:

[0211] If the first image is blurry, re-acquire the first image.

[0212] Optionally, in some embodiments, the second determining unit may be used to:

[0213] When the number of target edge lines is 2, it is determined that the battery cell has a bottom support plate.

[0214] Optionally, in some embodiments, the second determining unit may also be used for:

[0215] When the number of target edge lines is 2, and at least one target edge line is located in the first region, it is determined that the battery cell has a base plate.

[0216] Optionally, in some embodiments, the acquisition module 701 may also be used for:

[0217] When the number of target edge lines is 1, a second image is obtained, wherein the first image includes the first end of the battery cell, and the second image includes the second end of the battery cell, with the second end opposite to the first end;

[0218] The second determining unit can also be used for:

[0219] If the number of target edge lines in the second image is 1, it is determined that the battery cell does not have a bottom support plate.

[0220] Optionally, in some embodiments, the second determining unit may also be used for:

[0221] When the number of target edge lines in the second image is 2, it is determined that the battery cell has a base plate.

[0222] It should be noted that the information interaction and execution process between the above-mentioned devices / units are based on the same concept as the method embodiments of this application. They are devices corresponding to the above-mentioned battery electrode alignment detection method. All implementation methods in the above-mentioned method embodiments are applicable to the embodiments of this device. For details on its specific functions and the resulting technical effects, please refer to the method embodiment section, which will not be repeated here.

[0223] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional units and modules is merely an example. In practical applications, the above functions can be assigned to different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiments can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit. Furthermore, the specific names of the functional units and modules are only for easy differentiation and are not intended to limit the scope of protection of this application. The specific working process of the units and modules in the above system can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0224] Figure 8 A schematic diagram of the hardware structure of an electronic device provided in yet another embodiment of this application is shown.

[0225] The electronic device may include a processor 801 and a memory 802 storing programs or instructions. When the processor 801 executes the program, it implements the steps in any of the above method embodiments.

[0226] For example, the program can be divided into one or more modules / units, one or more of which are stored in memory 802 and executed by processor 801 to complete this application. The one or more modules / units can be a series of program instruction segments capable of performing a specific function, which describe the execution process of the program in the device.

[0227] Specifically, the processor 801 may include a central processing unit (CPU), an application-specific integrated circuit (ASIC), or one or more integrated circuits that can be configured to implement the embodiments of this application.

[0228] Memory 802 may include mass storage for data or instructions. For example, and not limitingly, memory 802 may include a hard disk drive (HDD), floppy disk drive, flash memory, optical disk, magneto-optical disk, magnetic tape, or Universal Serial Bus (USB) drive, or a combination of two or more of these. Where appropriate, memory 802 may include removable or non-removable (or fixed) media. Where appropriate, memory 802 may be internal or external to the integrated gateway disaster recovery device. In a particular embodiment, memory 802 is non-volatile solid-state memory.

[0229] Memory may include read-only memory (ROM), random access memory (RAM), disk storage media devices, optical storage media devices, flash memory devices, and electrical, optical, or other physical / tangible memory storage devices. Therefore, typically, memory includes one or more tangible (non-transitory) readable storage media (e.g., memory devices) encoded with software including computer-executable instructions, and when the software is executed (e.g., by one or more processors), it is operable to perform the operations described with reference to the methods according to one aspect of this disclosure.

[0230] The processor 801 implements any of the methods described in the above embodiments by reading and executing programs or instructions stored in the memory 802.

[0231] In one example, the electronic device may also include a communication interface 803 and a bus 804. The processor 801, memory 802, and communication interface 803 are connected via the bus 804 and communicate with each other.

[0232] The communication interface 803 is mainly used to realize communication between various modules, devices, units and / or equipment in the embodiments of this application.

[0233] Bus 804 includes hardware, software, or both, that couples components of an online data traffic metering device together. For example, and not limitingly, the bus may include an Accelerated Graphics Port (AGP) or other graphics bus, an Enhanced Industry Standard Architecture (EISA) bus, a Front Side Bus (FSB), HyperTransport (HT) interconnect, an Industry Standard Architecture (ISA) bus, an Infinite Bandwidth Interconnect, a Low Pin Count (LPC) bus, a memory bus, a Microchannel Architecture (MCA) bus, a Peripheral Component Interconnect (PCI) bus, a PCI-Express (PCI-X) bus, a Serial Advanced Technology Attachment (SATA) bus, a Video Electronics Standards Association Local (VLB) bus, or other suitable buses, or combinations of two or more of these. Where appropriate, bus 804 may include one or more buses. Although specific buses are described and illustrated in embodiments of this application, any suitable bus or interconnect is contemplated herein.

[0234] Furthermore, in conjunction with the methods in the above embodiments, this application embodiment can provide a readable storage medium for implementation. This readable storage medium stores a program or instructions; when executed by a processor, the program or instructions implement any of the methods in the above embodiments. This readable storage medium can be read by a machine such as a computer.

[0235] This application embodiment also provides a chip, which includes a processor and a communication interface. The communication interface is coupled to the processor. The processor is used to run programs or instructions to implement the various processes of the above method embodiments and achieve the same technical effect. To avoid repetition, it will not be described again here.

[0236] It should be understood that the chip mentioned in the embodiments of this application may also be referred to as a system-on-a-chip, system chip, chip system, or system-on-a-chip, etc.

[0237] This application provides a computer program product stored in a readable storage medium. The program product is executed by at least one processor to implement the various processes of the above method embodiments and achieve the same technical effect. To avoid repetition, it will not be described again here.

[0238] It should be clarified that this application is not limited to the specific configurations and processes described above and shown in the figures. For the sake of brevity, detailed descriptions of known methods are omitted here. In the above embodiments, several specific steps are described and shown as examples. However, the method process of this application is not limited to the specific steps described and shown. Those skilled in the art can make various changes, modifications, and additions, or change the order of steps, after understanding the spirit of this application.

[0239] The functional modules shown in the above-described block diagram can be implemented as hardware, software, firmware, or a combination thereof. When implemented in hardware, they can be, for example, electronic circuits, application-specific integrated circuits (ASICs), appropriate firmware, plug-ins, function cards, etc. When implemented in software, the elements of this application are programs or code segments used to perform the required tasks. Programs or code segments can be stored on a machine-readable medium or transmitted over a transmission medium or communication link via data signals carried on a carrier wave. "Machine-readable medium" can include any medium capable of storing or transmitting information. Examples of machine-readable media include electronic circuits, semiconductor memory devices, ROM, flash memory, erasable ROM (EROM), floppy disks, CD-ROMs, optical disks, hard disks, fiber optic media, radio frequency (RF) links, etc. Code segments can be downloaded via computer grids such as the Internet, intranets, etc.

[0240] It should also be noted that the exemplary embodiments mentioned in this application describe methods or systems based on a series of steps or apparatus. However, this application is not limited to the order of the above steps; that is, the steps can be performed in the order mentioned in the embodiments, or in a different order, or several steps can be performed simultaneously.

[0241] The aspects of this disclosure have been described above with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and program products according to embodiments of this disclosure. It should be understood that each block in the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by a computer program or instructions. These programs or instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing apparatus to produce a machine such that these instructions, executable via the processor of the computer or other programmable data processing apparatus, enable the implementation of the functions / actions specified in one or more blocks of the flowchart illustrations and / or block diagrams. Such a processor can be, but is not limited to, a general-purpose processor, a special-purpose processor, a special application processor, or a field-programmable logic circuit. It is also understood that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can also be implemented by special-purpose hardware performing the specified functions or actions, or can be implemented by a combination of special-purpose hardware and computer instructions.

[0242] Although this application has been described with reference to preferred embodiments, various modifications can be made thereto and components can be replaced with equivalents without departing from the scope of this application. In particular, the technical features mentioned in the various embodiments can be combined in any manner, provided there is no structural conflict. 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 for testing battery cells, characterized in that, include: Acquire a first image, the first image including a first region where the battery cell is located; Based on the first region, the first edge line of the battery cell is determined; Based on the grayscale values ​​corresponding to each pixel in the preset region of the first image, the detection result of the battery cell is determined, wherein the detection result is used to indicate whether the battery cell has a bottom support plate, and the preset region is the region within a preset range from the first edge line; After acquiring the first image, and before determining the first edge line of the battery cell based on the first region, the method further includes: Based on the grayscale value corresponding to each pixel in the first image, determine the first pixel whose grayscale value is greater than or equal to the first threshold. The smallest bounding rectangle of the first pixel is defined as the first region; The step of determining the detection result of the battery cell based on the grayscale values ​​corresponding to each pixel in a preset region of the first image includes: Based on the gray values ​​of each pixel in the preset region of the first image, target pixels whose gray values ​​meet the preset conditions are determined. Based on the target pixels, the target edge line is fitted to obtain the target edge line; The detection result of the battery cell is determined based on the number of target edge lines; Determining the detection result of the battery cell based on the number of target edge lines includes: If the number of target edge lines is 0, it is determined that the battery cell does not have the bottom support plate. When the number of target edge lines is 2, it is determined that the battery cell has the base plate.

2. The method according to claim 1, characterized in that, The acquisition of the first image includes: Get the initial image; The initial image is preprocessed to obtain the first image.

3. The method according to claim 2, characterized in that, The preprocessing of the initial image to obtain the first image includes: The initial image is processed to obtain a grayscale image; Adjust the contrast of the grayscale image to obtain the first image.

4. The method according to claim 2, characterized in that, The preprocessing of the initial image to obtain the first image includes: The initial image is split into a three-channel image, which includes a red channel image, a green channel image, and a blue channel image; The first image is determined from any one of the red channel image, the green channel image, and the blue channel image that satisfies the preset interference conditions.

5. The method according to claim 1, characterized in that, The step of determining target pixels whose grayscale values ​​satisfy preset conditions based on the grayscale values ​​corresponding to each pixel in a preset region of the first image includes: The preset area is divided along the extension direction of the first edge line to obtain N sub-regions, each of which includes M pixels, where N and M are integers greater than 1. A target pixel is determined from M pixels in each sub-region, wherein the difference between the gray value of the target pixel and the gray value of its neighboring pixels is greater than or equal to a second threshold.

6. The method according to claim 1, characterized in that, The step of fitting the target edge line based on the target pixel points includes: Obtain the pixel coordinates of the target pixel; The target pixel whose pixel coordinates satisfy the preset coordinate conditions is determined as the second pixel; If the number of the second pixel is greater than or equal to a preset threshold, the second pixel is fitted to obtain a target edge line.

7. The method according to claim 1, characterized in that, Determining that the battery cell does not have the base plate when the number of target edge lines is 0 includes: When the number of target edge lines is 0, the first image is input into the fuzzy recognition model to determine whether the first image is a fuzzy image; If the first image is not a blurred image, it is determined that the battery cell does not have the base plate.

8. The method according to claim 7, characterized in that, When the number of target edge lines is 0, after inputting the first image into the fuzzy recognition model to determine whether the first image is a fuzzy image, the method further includes: If the first image is a blurry image, re-acquire the first image.

9. The method according to claim 1, characterized in that, When the number of target edge lines is 2, determining that the battery cell has the base plate includes: If the number of target edge lines is 2, and at least one of the target edge lines is located within the first region, it is determined that the battery cell has the base plate.

10. The method according to claim 1, characterized in that, When the first image includes the first end of the battery cell, determining the detection result of the battery cell based on the number of target edge lines includes: When the number of target edge lines is 1, a second image is acquired, the second image including the second end of the battery cell, the second end being opposite to the first end; If the number of target edge lines in the second image is 1, it is determined that the battery cell does not have the base plate.

11. The method according to claim 10, characterized in that, When the number of target edge lines is 1, after acquiring the second image, the method further includes: If the number of target edge lines in the second image is 2, it is determined that the battery cell has the base plate.

12. A battery cell testing device, characterized in that, include: The acquisition module is used to acquire a first image, the first image including a first region where the first end of the battery cell is located; The first determining module is used to determine the first edge line of the battery cell based on the first region; The second determining module is used to determine the detection result of the battery cell based on the gray value corresponding to each pixel in the preset region of the first image, wherein the detection result is used to indicate whether the battery cell has a bottom support piece, and the preset region is a region within a preset range from the first edge line; The third determining module is used to determine, after acquiring the first image and before determining the first edge line of the battery cell based on the first region, a first pixel with a gray value greater than or equal to a first threshold based on the gray value corresponding to each pixel in the first image. The fourth determining module is used to determine the smallest bounding rectangle of the first pixel as the first region; The second determining module includes: The first determining unit is used to determine target pixels whose gray values ​​satisfy preset conditions based on the gray values ​​corresponding to each pixel in the preset region of the first image. A fitting unit is used to fit the target edge line based on the target pixel points; The second determining unit is used to determine the detection result of the battery cell based on the number of target edge lines; The second determining unit is used for: If the number of target edge lines is 0, it is determined that the battery cell does not have the bottom support plate. When the number of target edge lines is 2, it is determined that the battery cell has the base plate.

13. An electronic device, characterized in that, The device includes: a processor and a memory storing program instructions; the processor, when executing the program instructions, implements the method as described in any one of claims 1-11.

14. A readable storage medium, characterized in that, The readable storage medium stores program instructions that, when executed by a processor, implement the method as described in any one of claims 1-11.

15. A computer program product, characterized in that, When the instructions in the computer program product are executed by the processor of the electronic device, the electronic device causes the electronic device to perform the method as described in any one of claims 1-11.

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