WO2024087179A1 - 极片检测方法、极片检测装置以及终端 - Google Patents

极片检测方法、极片检测装置以及终端 Download PDF

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Publication number
WO2024087179A1
WO2024087179A1 PCT/CN2022/128309 CN2022128309W WO2024087179A1 WO 2024087179 A1 WO2024087179 A1 WO 2024087179A1 CN 2022128309 W CN2022128309 W CN 2022128309W WO 2024087179 A1 WO2024087179 A1 WO 2024087179A1
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WIPO (PCT)
Prior art keywords
pole piece
width
preset
difference
defect detection
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PCT/CN2022/128309
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English (en)
French (fr)
Inventor
吴凯
彭怡
瞿飞
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宁德时代新能源科技股份有限公司
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Application filed by 宁德时代新能源科技股份有限公司 filed Critical 宁德时代新能源科技股份有限公司
Priority to CN202280006697.6A priority Critical patent/CN118284903A/zh
Priority to PCT/CN2022/128309 priority patent/WO2024087179A1/zh
Publication of WO2024087179A1 publication Critical patent/WO2024087179A1/zh

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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis

Definitions

  • the present application relates to the field of batteries, and in particular to a pole piece detection method, a pole piece detection device and a terminal.
  • pole piece defects are a common pole piece surface defect that may cause power battery safety problems. Since the causes of pole piece defects are complicated and difficult to cure, and the morphology, location and severity of various defects are very different, the method of realizing pole piece defect detection by establishing a pole piece defect classification model in related technologies cannot effectively realize pole piece defect detection, and there is a problem of limited detection range.
  • One of the purposes of the embodiments of the present application is to provide a pole piece detection method, a pole piece detection device and a terminal, which can solve the problem that the detection range of the current pole piece detection method is relatively limited.
  • the present application provides a pole piece detection method, comprising:
  • the defect detection result of the pole piece is determined according to the width data.
  • pole piece detection method provided in the embodiment of the present application is implemented based on the size information of the pole piece, that is, the width data of the pole piece, there is no need to spend a lot of manpower to develop a complex pole piece defect classification model to identify pole piece defects, thereby effectively reducing the cost of pole piece defect detection and improving product production efficiency.
  • defect detection can be performed during the entire tape transport process of the electrode, that is, automated detection of electrode defect problems can be performed in different battery production processes, such as cold pressing, die-cutting, striping and winding processes. Therefore, it has the characteristics of a wide detection range, can effectively reduce the occurrence of missed detections, is beneficial to improving the quality of batteries, and reducing the outflow of risky products.
  • the width data of the pole piece includes the pole piece width of the pole piece
  • Determining the defect detection result of the pole piece according to the width data includes:
  • the width data includes a membrane width of a membrane on the pole piece
  • Determining the defect detection result of the pole piece according to the width data includes:
  • the width data of the pole piece includes the pole piece width of the pole piece and the membrane width of the membrane on the pole piece;
  • Determining the defect detection result of the pole piece according to the width data includes:
  • pole piece width and the diaphragm width calculating the pole piece width difference of the pole piece in two adjacent frames of the pole piece image and the diaphragm width difference of the diaphragm in two adjacent frames of the pole piece image;
  • the width data of the pole piece includes the distance from a feature point on the pole piece to a preset reference line
  • Determining the defect detection result of the pole piece according to the width data includes:
  • the feature points include edge feature points of the pole piece and/or center feature points of the pole piece.
  • the preset reference line is a reference line generated by the camera when capturing the pole piece image, and the preset reference line is parallel to a longitudinal edge of the pole piece.
  • multiple frames of the pole piece images are obtained by sampling by a camera based on a preset sampling time interval during the pole piece walking process.
  • the preset sampling time interval is the time used for the pole piece to be wound once in the pole piece winding process.
  • the method further includes:
  • the width data of the pole piece includes the distance from a feature point on the pole piece to a preset reference line
  • Determining the defect detection result of the pole piece according to the width data includes:
  • the method further includes:
  • the pole piece detection method further includes:
  • the present application provides a pole piece detection device, the pole piece detection device comprising:
  • An acquisition unit is used to acquire multiple frames of pole piece images; the multiple frames of pole piece images are sampled by a camera during the pole piece tape walking process;
  • a first determining unit used to determine the width data of the pole piece in each frame of the pole piece image
  • the second determination unit is used to determine the defect detection result of the pole piece according to the width data.
  • the present application provides a terminal comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the steps of the method as described in any one of the embodiments of the first aspect are implemented.
  • the present application provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the method described in any one of the embodiments of the first aspect above are implemented.
  • the width data of the pole piece is determined by acquiring the pole piece image obtained by the camera sampling based on a preset sampling interval during the pole piece walking process, and then the defect detection result of the pole piece is obtained based on the width data, thereby realizing pole piece defect detection based on the size information of the pole piece, which solves the problem that there has been no effective detection means for pole piece defects in the process flow for a long time, resulting in the outflow of risky products affecting product quality. There is no need to spend a lot of manpower to develop a complex pole piece defect classification model for automatic identification of pole piece defects, thereby effectively reducing the cost of pole piece defect detection and improving product production efficiency.
  • FIG1 is a schematic diagram of a first implementation flow of a pole piece detection method provided in an embodiment of the present application
  • FIG2 is a first schematic diagram of a pole piece image provided in an embodiment of the present application.
  • FIG3 is a second schematic diagram of a pole piece image provided in an embodiment of the present application.
  • FIG4 is a schematic diagram of obtaining a pole piece image provided in an embodiment of the present application.
  • FIG5 is a schematic diagram of the winding end position of the pole piece provided in an embodiment of the present application.
  • FIG6 is a schematic diagram of a first implementation flow of step S300 of the pole piece detection method provided in an embodiment of the present application.
  • FIG. 7 is a schematic diagram of a second implementation flow of step S300 of the pole piece detection method provided in an embodiment of the present application.
  • FIG8 is a schematic diagram of a third implementation flow of step S300 of the pole piece detection method provided in an embodiment of the present application.
  • FIG9 is a schematic diagram of a fourth implementation flow of step S300 of the pole piece detection method provided in an embodiment of the present application.
  • FIG. 10 is a schematic diagram of a fifth implementation flow of step S300 of the pole piece detection method provided in an embodiment of the present application.
  • FIG11 is a schematic diagram of a second implementation flow of a pole piece detection method provided in an embodiment of the present application.
  • FIG12 is a structural block diagram of a pole piece detection device provided in an embodiment of the present application.
  • FIG. 13 is a schematic diagram of the structure of a terminal provided in an embodiment of the present application.
  • the term "and/or" is only a description of the association relationship of associated objects, indicating that three relationships may exist.
  • a and/or B can represent: A exists alone, A and B exist at the same time, and B exists alone.
  • the character "/" in this article generally indicates that the associated objects before and after are in an "or" relationship.
  • multi-frame refers to more than two (including two).
  • pole piece defect detection can be achieved by establishing a pole piece defect classification model, but this method generally only detects the defects of pole pieces in some processes.
  • a CCD camera charge coupled device camera
  • the pole ear image is compared and analyzed with the preset image model to determine whether there is a pole piece defect phenomenon.
  • the pole piece defects caused by the pole piece wave edge, deviation correction overrun, roller jamming, etc. in the winding process Therefore, there are problems such as limited detection range, high development cost and long development cycle.
  • an embodiment of the present application provides a pole piece detection method, which is suitable for situations where pole piece defect detection is required, and can be executed by a pole piece detection device configured on a terminal, which can be a server, computer or other terminal equipment, and the present application does not impose any restrictions on this.
  • the pole piece detection method in this embodiment includes steps S100 to S300 .
  • step S100 multiple frames of polar slice images are acquired.
  • multiple frames of pole piece images can be obtained by the camera sampling the pole piece during the pole piece conveying process. Since the pole piece is in the conveying process, the camera samples the specified position of the pole piece during the conveying process to obtain pole piece images corresponding to multiple different sampling positions.
  • multiple frames of pole pieces can also be obtained by sampling images of the pole piece while moving the camera. For example, the pole piece remains stationary at this time, and the moving camera samples pole piece images at multiple sampling positions on the pole piece.
  • the movement process of the camera can be a uniform movement of the camera, and the pole piece is photographed at a preset sampling time interval to obtain pole piece images at multiple sampling positions.
  • the sampling time between adjacent pole piece images in the multiple frames of pole piece images is set to a preset sampling time interval.
  • multiple frames of pole piece images are obtained by sampling by the camera based on preset sampling time intervals during the pole piece conveying process.
  • Battery production requires the use of rollers to continuously roll and compact the pole pieces to obtain battery cells.
  • the pole pieces are in the conveying process and the pole pieces move relative to the camera. Therefore, the camera samples the pole piece images of the pole pieces at specified positions on the production line based on preset sampling time intervals, and thus pole piece images corresponding to different sampling positions of the pole piece can be obtained, while ensuring that the distances between adjacent sampling positions are the same.
  • the pole piece conveying process is the process in which the pole piece moves with the rotation of the roller.
  • the camera and the roller are relatively stationary.
  • the camera samples the image of the pole piece at a preset sampling time interval, thereby sampling multiple sampling positions on the pole piece to obtain corresponding pole piece images.
  • the designated position for the camera to perform image sampling may be located at the entry side of the roller or at the exit side of the roller, wherein the entry side of the roller refers to the side where the pole piece enters the roller, and the exit side of the roller refers to the side where the pole piece exits after being processed by the roller.
  • the distance between the designated position where the camera samples the image and the roller may range from 10 to 100 cm.
  • the vertical distance between the photosensitive surface of the camera and the pole piece may range from 10 to 100 cm.
  • the spacing between adjacent sampling positions on the electrode piece can be adjusted by adjusting the duration of the preset sampling time interval.
  • the spacing distance between adjacent sampling positions on the pole piece is positively correlated with the width of the pole piece.
  • the spacing distance between adjacent sampling positions on the pole piece is 20%-1000% of the width of the pole piece.
  • the spacing distance between adjacent sampling positions on the pole piece is related to the process of the pole piece.
  • the duration of the preset sampling time interval is set, and the spacing distance between adjacent sampling positions on the pole piece is adjusted to achieve the purpose of targeted image sampling of each process of the pole piece, thereby reducing the cost of online defect detection of the pole piece.
  • the duration of the preset sampling time interval is set so that the spacing distance between adjacent sampling positions on the pole piece can be the width of the pole piece.
  • the electrode sheet includes an anode sheet and a cathode sheet.
  • the cathode sheet, the anode sheet and the separator are wound on the same winding needle to form a battery cell.
  • the preset sampling time interval is the time required for one circle of the electrode sheet in the winding process, and image sampling can be performed on each circle of the electrode sheet in the battery cell.
  • the camera can be an industrial camera, which can be used in processes such as cold pressing, die cutting, striping and winding of the pole piece, so as to perform image sampling on different sampling positions of the pole piece during the production process, and determine whether the pole piece has defects based on the width data of the pole piece in the pole piece image.
  • step S200 the width data of the pole piece in each frame of the pole piece image is determined.
  • the size information of the pole piece in each frame of the pole piece image can be determined by image recognition to obtain the width data of the pole piece.
  • the pole piece width data may include the pole piece width.
  • the pole piece width refers to the distance between the longitudinal edges of the pole piece.
  • the pole piece image includes the edge feature point 21 of the pole piece 110 and the edge feature point 22 opposite to the edge feature point 21 of the pole piece 110.
  • the pole piece width W1 is the distance between the edge feature point 21 and the edge feature point 22 of the pole piece 110.
  • the pole piece width data may include the diaphragm width of the diaphragm on the pole piece.
  • the diaphragm can be a film structure such as an active material layer attached to the electrode current collector; the diaphragm width refers to the distance between the longitudinal edges of the diaphragm.
  • the electrode image includes the edge feature point 23 of the diaphragm 120 on the electrode 110 and the edge feature point 24 opposite to the edge feature point 23.
  • the diaphragm width W2 is the distance between the edge feature point 23 and the edge feature point 24 of the diaphragm 120.
  • the longitudinal edge refers to the edge of the strip object extending along the length direction, which can also be called the “long side”. It can be understood that the distance between the longitudinal edges represents the width of the strip object.
  • the longitudinal direction of the pole piece refers to the length direction of the pole piece, and the distance between the longitudinal edges of the pole piece is the pole piece width;
  • the longitudinal direction of the diaphragm refers to the length direction of the diaphragm, and the distance between the longitudinal edges of the diaphragm is the diaphragm width.
  • the width data of the pole piece may include the distance from the characteristic point on the pole piece to the preset reference line.
  • the characteristic points on the pole piece may include at least one of the edge characteristic points and the center characteristic points of the pole piece.
  • the characteristic points on the pole piece may include one or more characteristic points of the edge characteristic points 21, 22, 23, 24 and 25 shown in FIG. 2 .
  • the preset reference line 26 in the above embodiment may be a reference line built into the camera, and the preset reference line 26 may be automatically added to the pole piece image each time the image is sampled.
  • the preset reference line 26 may be automatically added to the pole piece image each time the image is sampled, and at this time, the preset reference line 26 is located at a fixed position in the pole piece image, and the feature points on the pole piece in the pole piece images of adjacent frames may be displaced relative to the preset reference line 26.
  • the preset reference line 26 may be located within the image area of the pole piece 110 or outside the image area of the pole piece 110 .
  • the preset reference line 26 needs to be set parallel to the edges of the pole piece 110 and the diaphragm 120 .
  • the anode electrode sheet 303, the first diaphragm 302, the second diaphragm 304 and the cathode electrode sheet 307 are sequentially stacked and wound on the winding needle 301, and the width of the anode electrode sheet 303 is greater than the width of the cathode electrode sheet 307; cameras 331 and 332 perform image sampling on the left and right areas of the anode electrode sheet 303, and cameras 333 and 334 perform image sampling on the left and right areas of the cathode electrode sheet 307, and the points on the left edge 305 and the right edge 306 of the cathode electrode sheet 307 can be used as edge feature points of the cathode electrode sheet 307, and the preset baseline 320 is a baseline that is automatically added to the electrode sheet image each time the image is sampled, and is used to provide a reference for the feature points on the electrode sheet.
  • the distance between the right edge 306 of the cathode electrode piece 307 and the preset baseline 320 fluctuates to a certain extent, see the shaded area in the figure. If the distance between the feature point on the right edge 306 of the cathode electrode piece 307 and the preset baseline 320 exceeds the set range, it can be determined that the cathode electrode piece 307 has a defect.
  • cameras 331, 332, 333, and 334 can use their own baselines as preset baselines during the image sampling process, and the preset baselines can be automatically added to the pole piece image each time the image is sampled.
  • Cameras 331 and 332 perform image sampling on the left and right sides of the anode pole piece 303, and cameras 333 and 334 perform image sampling on the left and right sides of the cathode pole piece 307. If the distance from the feature point on the pole piece to the preset baseline in the pole piece image in any area is abnormal, it can be determined that the pole piece has a defect.
  • the preset baseline in the above embodiment can also be a baseline that is relatively stationary with respect to the roller, and is used to provide a reference for the position of the feature point on the pole piece. Moreover, the preset baseline can be captured when the camera performs image sampling, and then presented in the pole piece image.
  • the width data of the pole piece may include the position difference between the winding end positions of the pole piece on two adjacent battery cells.
  • battery cell n and battery cell n+1 are the two battery cells in the winding process
  • the ending position of battery cell n is position A
  • the ending position of battery cell n+1 is position B.
  • the position difference L1 represents the distance between position A and position B, that is, the position difference between the ending position of battery cell n and the ending position of battery cell n+1.
  • the width data of the pole piece may also include other width data.
  • the width data of the pole piece may also include the distance between the edge feature point of the pole piece and the edge feature point of the diaphragm.
  • the width data of the pole piece may be the distance between the edge feature point 21 of the pole piece 110 and the edge feature point 23 of the diaphragm 120.
  • the width data of the above-mentioned pole piece may include any combination of width data including the pole piece width, the diaphragm width, the distance from a feature point on the pole piece to a preset baseline, and the difference in the ending position of the pole piece at the end of the winding process of the battery cell.
  • the width data of the pole piece may include both the pole piece width and the diaphragm width.
  • the electrode width data may also simultaneously include the above-mentioned electrode width, diaphragm width, the distance from the characteristic point on the electrode to the preset baseline, and the difference in the end position of the electrode at the end of the winding process of the battery cell.
  • step S300 the defect detection result of the pole piece is determined according to the width data.
  • a defect detection result of whether the electrode piece is a defective electrode piece can be determined according to the width data.
  • the pole piece width data includes the pole piece width and the diaphragm width
  • the pole piece width is greater than the first preset width threshold, or the diaphragm width is greater than the second preset width threshold, it means that the pole piece width is abnormal or the diaphragm width is abnormal due to defects in the tape walking process. Therefore, it can be determined that the pole piece has defects and the corresponding defect detection results are generated, thereby realizing defect detection of the pole piece based on the pole piece size information, that is, the pole piece width data.
  • the first preset width threshold is positively correlated with the width of the pole piece.
  • the first preset width threshold may be between one thousandth of the width of the pole piece and five thousandths of the width of the diaphragm piece.
  • the second preset width threshold is positively correlated with the width of the diaphragm.
  • the second preset width threshold may be between one thousandth of the width of the diaphragm and five thousandths of the width of the diaphragm.
  • pole piece detection method provided in the embodiment of the present application is implemented based on the size information of the pole piece, that is, the width data of the pole piece, there is no need to spend a lot of manpower to develop a complex pole piece defect classification model to identify pole piece defects, thereby effectively reducing the cost of pole piece defect detection and improving product production efficiency.
  • defect detection can be performed during the entire tape transport process of the electrode, that is, automated detection of electrode defect problems can be performed in different battery production processes, such as cold pressing, die-cutting, striping and winding processes. Therefore, it has the characteristics of a wide detection range, can effectively avoid the occurrence of missed detection, is beneficial to improving the quality of batteries, and reducing the outflow of risky products.
  • determining the defect detection result of the pole piece according to the width data may specifically include step S311 and step S312 .
  • step S311 the difference in pole piece width between pole pieces in two adjacent frames of pole piece images is calculated according to the pole piece width.
  • the camera and the roller are relatively stationary during the pole piece conveying process, when the pole piece moves with the rotation of the roller, the camera samples the pole piece according to a preset sampling time interval, and the pole piece images corresponding to different sampling positions of the pole piece can be obtained.
  • the pole piece width of the pole piece in each frame of the pole piece image represents the pole piece width at the sampling position corresponding to the frame of the pole piece image.
  • the camera takes a plurality of consecutive frames of pole piece images of the pole piece at the specified position of the production line, which is equivalent to sampling images at a plurality of consecutive sampling positions on the pole piece.
  • step S312 when the pole piece width difference is greater than the first preset width threshold, a defect detection result indicating that the pole piece is a defective pole piece is obtained.
  • the pole piece width difference is compared with a first preset width threshold. If the pole piece width difference is less than the first preset width threshold, it indicates that the pole piece may not have defects. If the pole piece width difference is greater than the first preset width threshold, it indicates that the pole piece is abnormal. In this case, the pole piece is determined to be a defective pole piece, that is, a defect detection result that the pole piece is a defective pole piece is obtained.
  • the difference in pole piece width of the pole piece in two adjacent pole piece images represents the difference in pole piece width of two corresponding adjacent sampling positions on the pole piece.
  • the difference in the width of the pole piece in two adjacent pole piece images includes: the difference in the width of the pole piece in each two adjacent pole piece images, that is, the difference in the width of the pole piece between any two adjacent pole piece images.
  • the difference in the width of the pole piece at the two adjacent sampling positions includes k-1 pole piece width differences.
  • any pole piece width difference is greater than the first preset width threshold, it indicates that the pole piece is abnormal.
  • the pole piece is determined to be a defective pole piece, that is, a defect detection result that the pole piece is a defective pole piece is obtained.
  • determining the defect detection result of the pole piece according to the width data may specifically include step S321 and step S322 .
  • step S321 the difference in diaphragm width between the diaphragms in two adjacent frames of pole piece images is calculated according to the diaphragm width.
  • a diaphragm is provided on the pole piece, and the width of the diaphragm is smaller than the width of the pole piece. Since the camera and the roller are relatively stationary, when the pole piece rotates with the rotation of the roller, the camera samples the image of the pole piece at the specified position according to the preset sampling time interval, and the pole piece images corresponding to different sampling positions of the pole piece can be obtained.
  • the diaphragm width of the diaphragm on the pole piece in each frame of the pole piece image represents the diaphragm width of the sampling position corresponding to the frame of the pole piece image.
  • the camera takes a plurality of consecutive frames of pole piece images of the pole piece at the specified position of the production line, which is equivalent to sampling images of a plurality of consecutive sampling positions on the pole piece.
  • the difference in diaphragm width between the diaphragms on the pole piece in two adjacent frames of pole piece images represents the difference in diaphragm width of the pole piece at two corresponding adjacent sampling positions on the pole piece.
  • the difference in diaphragm width between any two adjacent pole piece images on the pole piece can be calculated based on the diaphragm width of the pole piece in multiple consecutive frames of pole piece images.
  • step S322 when the diaphragm width difference is greater than the second preset width threshold, a defect detection result indicating that the pole piece is a defective pole piece is obtained.
  • the diaphragm width difference is compared with the second preset width threshold. If the diaphragm width difference is less than the second preset width threshold, it indicates that no defect may have occurred. If the pole piece width difference is greater than the second preset width threshold, it indicates that the pole piece is abnormal. In this case, the pole piece is determined to be a defective pole piece.
  • the difference in width of the diaphragm on the pole piece in two adjacent frames of pole piece images includes the difference in the width of the pole piece diaphragm in every two adjacent frames of pole piece images, that is, the diaphragm width difference includes the difference in the diaphragm width at any two adjacent sampling positions on the pole piece.
  • the diaphragm width difference at two adjacent sampling positions includes k-1 diaphragm width differences.
  • any pole piece width difference is greater than a second preset width threshold, it indicates that the pole piece is abnormal.
  • the pole piece is determined to be a defective pole piece, that is, a defect detection result that the pole piece is a defective pole piece is obtained.
  • determining the defect detection result of the pole piece according to the width data may specifically include step S331 and step S332.
  • step S331 the difference between the pole piece widths in two adjacent pole piece image frames and the difference between the membrane piece widths in two adjacent pole piece image frames are calculated according to the pole piece width and the membrane piece width.
  • step S332 when the pole piece width difference is greater than the first preset width threshold or the membrane width difference is greater than the second preset width threshold, a defect detection result indicating that the pole piece is a defective pole piece is obtained.
  • the pole piece width difference is compared with the first preset width threshold, and the diaphragm width difference is compared with the second preset width threshold. If the pole piece width difference is less than the first preset width threshold and the diaphragm width difference is less than the second preset width threshold, it indicates that the pole piece may not be defective. If the pole piece width difference is greater than the first preset width threshold or the pole piece width difference is greater than the second preset width threshold, it indicates that the pole piece is abnormal, and the pole piece is determined to be a defective pole piece. If the pole piece width difference is greater than the first preset width threshold and the pole piece width difference is greater than the second preset width threshold, it indicates that the pole piece is abnormal, and the pole piece is determined to be a defective pole piece.
  • the first preset width threshold may be in the range of 0.1-0.5 mm.
  • the second preset width threshold may be in the range of 0.1-0.5 mm.
  • the pole piece width difference is compared with a first preset width upper limit value. If the pole piece width difference is greater than the first preset width upper limit value, it is determined that the pole piece is abnormally damaged, and a defect detection result indicating that the pole piece is a damaged pole piece is obtained.
  • the first preset width upper limit value is greater than the first preset width threshold value.
  • the first preset width upper limit value is 3-5 times the first preset width threshold value.
  • the diaphragm width difference is compared with a second preset width upper limit value. If the pole piece diaphragm width difference is greater than the second preset width upper limit value, it is determined that the pole piece is abnormally damaged, and a defect detection result indicating that the pole piece is a damaged pole piece is obtained.
  • the second preset width upper limit value is greater than the second preset width threshold value.
  • the second preset width upper limit value is 3-5 times the second preset width threshold value.
  • the first preset width upper limit may be 1-3 mm.
  • determining the defect detection result of the pole piece based on the width data specifically includes step S341 and step S342.
  • step S341 the distance difference between the pole piece feature point and the preset reference line in two adjacent pole piece images is calculated according to the distance between the feature point and the preset reference line.
  • the preset baseline can be a baseline built into the camera. By determining the feature points of the pole piece in each frame of the pole piece image and calculating the distance between the feature points of the pole piece in each frame of the pole piece image and the preset baseline, the distance difference between the feature points of the pole piece in two adjacent frames of the pole piece image and the preset baseline can be calculated based on the distance.
  • step S342 when the distance difference is greater than the preset distance threshold, a defect detection result indicating that the pole piece is a defective pole piece is obtained.
  • the distance difference between the feature points in two adjacent frames of the pole piece image and the preset baseline is less than the preset distance threshold, it indicates that the pole piece may not have defects. If the material line distance difference is greater than the preset distance threshold, it indicates that the pole piece is abnormal, and the pole piece can be determined as a defective pole piece, thereby obtaining a defect detection result that the pole piece is a defective pole piece.
  • the feature points may include edge feature points of the pole piece.
  • the distance between the feature points and the preset baseline can be the distance between the edge feature points of the pole piece in the pole piece image and the preset baseline, that is, the distance between the edge feature points of the pole piece sampling position on the pole piece at the moment of shooting and the preset baseline. Based on this distance, the distance difference from the edge feature points of the pole piece in two adjacent frames of the pole piece image to the preset baseline can be calculated.
  • the edge feature point may be an edge feature point on the left edge of the pole piece on the pole piece image.
  • the edge feature point may be an edge feature point 21 on the pole piece image.
  • the edge feature point may be an edge feature point on the right edge of the pole piece on the pole piece image.
  • the edge feature point may be an edge feature point 22 on the pole piece image.
  • the feature points include edge feature points of the pole piece
  • a plurality of continuous frames of pole piece images are obtained, each frame of the pole piece image corresponds to a sampling image of a sampling position on the pole piece, and the distance between the edge feature points on the pole piece and the preset baseline in each frame of the pole piece image is counted.
  • material line distance the distance between the edge feature points on the pole piece in the pole piece image and the preset baseline
  • multiple material line distances are counted, and a correction curve is generated based on the multiple material line distances. The correction curve is used to characterize the displacement of the edge of the pole piece relative to the preset baseline.
  • the fluctuation value of the correction curve is the difference in material line distance from the edge feature points of the pole piece in two adjacent frames of the pole piece image to the preset baseline. If the material line distance difference is greater than the preset distance threshold, the pole piece is determined to be a defective pole piece.
  • the preset distance threshold in this embodiment may be 0.5-1.5 mm.
  • the preset distance threshold in this embodiment is referred to as a “first preset distance threshold”.
  • the first preset distance threshold is positively correlated with the width of the pole piece.
  • the feature point may include the central feature point of the pole piece.
  • the material line distance between the feature point and the preset baseline can be the distance between the central feature point of the pole piece in the pole piece image and the preset baseline, that is, the distance between the central feature point of the sampling position on the pole piece by the camera at the moment of shooting and the preset baseline. Based on the material line distance, the distance difference from the central feature point of the pole piece in two adjacent frames of the pole piece image to the preset baseline can be calculated.
  • the central feature point may be the midpoint between the left edge and the right edge of the pole piece on the pole piece image, that is, the midpoint between the left edge and the right edge of the sampling position on the pole piece.
  • the central feature point may be the midpoint of the line connecting the edge feature point 21 and the edge feature point 22.
  • the characteristic point includes the central characteristic point of the pole piece
  • multiple continuous frames of pole piece images are obtained, each frame of the pole piece image corresponds to a sampling image of a sampling position on the pole piece, and the distance between the central characteristic point on the pole piece and the preset reference line in each frame of the pole piece image is counted to obtain multiple material line distances.
  • a correction curve is generated based on the multiple material line distances. The correction curve is used to characterize the displacement of the center of the pole piece relative to the preset reference line.
  • the fluctuation value of the correction curve is the material line distance difference from the central characteristic point of the pole piece in two adjacent frames of the pole piece image to the preset reference line. If the material line distance difference is greater than the preset distance threshold, the pole piece is determined to be a defective pole piece.
  • the preset distance threshold in this embodiment is referred to as the "second preset distance threshold”.
  • the second preset distance threshold is positively correlated with the width of the pole piece.
  • the first preset distance threshold and the second preset distance threshold may be the same or different, and may be between one thousandth and five thousandths of the width of the pole piece.
  • the first preset distance threshold and the second preset distance threshold may be 0.1-0.5 mm.
  • the preset sampling time interval is the time taken for the pole piece to be wound once in the winding process.
  • the cathode sheet, the anode sheet and the separator are wound on the same winding needle to form a battery cell.
  • the preset sampling time interval to the time required for one circle of winding in the electrode sheet winding process, the electrode sheets of each circle in the battery cell can be image sampled. If the difference in electrode sheet width between any adjacent circles is greater than the first preset width threshold, the electrode sheet is determined to be a defective electrode sheet.
  • the preset sampling time interval to the time required for winding one circle of the electrode in the winding process, image sampling can be performed on the electrode of each circle in the battery cell. If the difference in diaphragm width of the diaphragms on any adjacent circles of electrode is greater than a second preset width threshold, the electrode is determined to be a defective electrode.
  • the battery cell is marked as an abnormal battery cell and is scrapped.
  • step S300 after obtaining the defect detection result that the electrode piece is a defective electrode piece, the step further includes: outputting electrode piece defect prompt information.
  • the electrode defect prompt information is output to remind the user that the electrode defect has occurred.
  • the production equipment in the current production process can be controlled to shut down.
  • defects of the electrodes in the current production process may be marked and then the production may be resumed.
  • the defect mark may be a physical mark.
  • a defect mark may be affixed to the electrode in the current production process.
  • the previous process includes cold pressing, die cutting, and slitting processes of the electrode
  • the assembly process includes a winding process. If a defect mark occurs in the previous process, the defect mark is detected in the assembly process. If the defect mark is detected, the battery cell in the assembly process is scrapped.
  • the pole piece is discharged after hot pressing, and the pole piece with the defect mark is retested, for example, using an offline high-power X-ray instrument to detect the microscopic image of the pole piece. If it is re-judged as a defective pole piece, the pole piece is scrapped.
  • the multiple frames of pole piece images can be obtained by sampling by a camera when the pole piece is walking a preset walking distance; the width data of the pole piece includes the distance from a feature point on the pole piece to a preset baseline.
  • a preset walking distance Y for the pole piece is selected for every walking distance X, and multiple frames of pole piece images are collected within the preset walking distance Y.
  • the interval time for the camera to collect images within the preset walking distance Y of the pole piece can be the preset sampling time interval in any of the above embodiments.
  • the running distance X may be the sum of the lengths of the pole pieces in a plurality of battery cells.
  • X may be equal to Y.
  • step S300 the defect detection result of the pole piece is determined according to the width data, which specifically includes step S351 and step S352 .
  • step S351 according to the distances from the feature points on the pole piece to the preset baseline, the average value and the peak value of the distances from the feature points on the pole piece to the preset baseline in multiple frames of pole piece images are calculated.
  • a preset walking distance is selected during the walking process of the pole piece, and the pole piece is sampled at intervals according to a preset sampling time within the preset walking distance to obtain pole piece images at multiple sampling positions, and the distance between the feature point on the pole piece and the preset baseline in each frame of the pole piece image is counted to obtain multiple material line distances, and the average value of the multiple material line distances and the peak value of the multiple material line distances are calculated.
  • the peak value of the multiple material line distances may be the minimum value among the multiple material line distances, or may be the maximum value among the multiple material line distances.
  • step S352 when the difference between the average value and the peak value is greater than the first preset difference, a defect detection result indicating that the pole piece is a defective pole piece is obtained.
  • the peak value is compared with the average value, and the difference between the peak value and the average value is calculated. If the difference is greater than the first preset difference, the pole piece is determined to be a defective pole piece.
  • a correction curve is generated based on multiple material line distances.
  • the correction curve is used to characterize the displacement of a characteristic point of a pole piece relative to a preset reference line.
  • the peaks and troughs of the correction curve correspond to the peak values in the multiple material line distances. If the difference between the peak value and the average value is greater than a first preset difference, the pole piece is determined to be a defective pole piece.
  • the correction curve can also be a trend line composed of the distance between the characteristic point of the pole piece identified by the correction sensor and the preset reference line.
  • Excessive winding correction is a common cause of lateral defects of the pole piece.
  • the common features of such pole piece defects are: deviation of the reference material line, sudden change of material width, and deviation of the correction material line. Therefore, the correction sensor can be used to monitor the fluctuation of the material line distance to warn of pole piece defects.
  • the distance between the characteristic points of the pole piece identified by the correction sensor and a preset baseline constitutes a correction curve pole piece. If the distance between adjacent characteristic points on the pole piece correction curve is greater than the preset distance difference, the pole piece can also be determined to be a defective pole piece.
  • the first preset difference and the preset distance difference may be positively correlated with the width of the pole piece.
  • the first preset difference and the preset distance difference may be between one thousandth and five thousandths of the width of the pole piece.
  • the first preset difference and the preset distance difference may be 0.1-0.5 mm.
  • step S300 after obtaining the defect detection result that the electrode piece is a defective electrode piece, the step further includes: outputting correction prompt information.
  • a defect detection result that the pole piece is a defective pole piece is obtained, and a correction prompt message is output to remind the user that a winding correction phenomenon has occurred.
  • the pole piece is optional, and the equipment can be controlled to shut down after outputting the pole piece defect prompt information.
  • defects of the electrodes in the current production process can be marked and then the production can be resumed.
  • the pole piece detection method in this embodiment further includes steps S610 to S630 .
  • step S610 multiple frames of final images of the pole piece are acquired.
  • multiple frames of finishing images are captured by a camera when the winding of the pole pieces of adjacent battery cells is completed.
  • the cathode electrode sheet, the anode electrode sheet and the separator are wound on the same winding needle to form a battery cell, and the final image of the electrode sheet is an image taken by a camera when the electrode sheet is wound to the last circle or close to the last circle (for example, the second to last circle, the third to last circle, etc.).
  • the cathode electrode sheet, the anode electrode sheet and the separator are wound on the same winding needle to form a battery cell.
  • the final image of the cathode electrode sheet of each battery cell at the end of the battery cell winding can be taken as a multi-frame final image of the electrode sheet.
  • step S620 the finishing position of the electrode piece on each battery cell is determined according to the finishing image, and the position difference between the finishing positions of two adjacent battery cells is calculated.
  • the end position of the electrode sheet in each battery cell is determined according to the end image, and the position difference between the end positions of two adjacent battery cells is calculated.
  • step S630 when the position difference is greater than the second preset difference, the pole piece is determined to be a defective pole piece.
  • the parameters of the electrode sheets of two adjacent battery cells are usually the same, for example, the lengths of the electrode sheets of two adjacent battery cells are the same, when the winding process of the battery cells is completed, their ending positions are also the same. If there is a deviation in the ending positions of the two adjacent battery cells, it means that the electrode sheet of the current battery cell may be abnormal during the winding process, for example, a lateral defect occurs on the electrode sheet, resulting in a reduction in the length of the electrode sheet. Specifically, if the position difference between the ending positions of the two adjacent battery cells is greater than a second preset difference, the electrode sheet is determined to be a defective electrode sheet.
  • the second preset difference may be in direct proportion to the length of the electrode of the battery cell.
  • the second preset difference may be 1/1000 to 5/1000 of the length of the electrode piece of the battery cell.
  • the second preset difference may be 1-5 mm.
  • FIG. 12 it is a schematic diagram of the structure of a pole piece detection device 800 provided in an embodiment of the present application.
  • the pole piece detection device can be configured on the above-mentioned terminal, and includes: an acquisition unit 801 , a first determination unit 802 and a second determination unit 803 .
  • An acquisition unit 801 is used to acquire multiple frames of pole piece images; the multiple frames of pole piece images are sampled by a camera during the pole piece tape conveying process;
  • a first determining unit 802 is used to determine the width data of the pole piece in each frame of the pole piece image
  • the second determination unit 803 is used to determine the defect detection result of the pole piece according to the width data.
  • pole piece detection device 800 can refer to the description in the above-mentioned various pole piece detection method embodiments, and will not be repeated here.
  • the above-mentioned various embodiments can be combined with each other to obtain a variety of different embodiments, all of which belong to the protection scope of this application.
  • the embodiment of the present application further provides a terminal.
  • the terminal may be configured with the pole piece detection device shown in the above-mentioned various embodiments.
  • the terminal 8 may include: a processor 80, a memory 81, and a computer program 82 stored in the memory 81 and executable on the processor 80.
  • the processor 80 executes the computer program 82, the steps in the above-mentioned various pole piece detection method embodiments are implemented, for example, steps S100 to S300 shown in FIG1 .
  • the processor 80 may be a central processing unit (CPU), other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc.
  • the general-purpose processor may be a microprocessor or any conventional processor, etc.
  • the memory 81 may be an internal storage unit of the terminal 8, such as a hard disk or a memory.
  • the memory 81 may also be an external storage device for the terminal 8, such as a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, etc. equipped on the terminal 8.
  • the memory 81 may also include both an internal storage unit of the terminal 8 and an external storage device. The memory 81 is used to store the above-mentioned computer program and other programs and data required by the terminal.
  • the above-mentioned computer program can be divided into one or more units, and the above-mentioned one or more units are stored in the above-mentioned memory 81 and executed by the above-mentioned processor 80 to complete the present application.
  • the above-mentioned one or more units can be a series of computer program instruction segments that can complete specific functions, and the instruction segments are used to describe the execution process of the above-mentioned computer program in the above-mentioned terminal for performing pole piece defect detection.
  • the above-mentioned computer program can be divided into: an acquisition unit, a first determination unit, and a second determination unit, and the specific functions are as follows:
  • An acquisition unit is used to acquire multiple frames of pole piece images; the multiple frames of pole piece images are sampled by a camera during the pole piece tape walking process;
  • a first determining unit used to determine the width data of the pole piece in each frame of the pole piece image
  • the second determination unit is used to determine the defect detection result of the pole piece according to the width data.
  • the technicians in the relevant field can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional units and modules is used as an example for illustration.
  • the above-mentioned function allocation can be completed by 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 embodiment can be integrated in a processing unit, or each unit can exist physically separately, or two or more units can be integrated in one unit.
  • the above-mentioned integrated unit can be implemented in the form of hardware or in the form of software functional units.
  • the disclosed devices and methods can be implemented in other ways.
  • the terminal embodiments described above are merely schematic.
  • the division of modules or units is only a logical function division, and there may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed.
  • Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be an indirect coupling or communication connection through some interfaces, devices or units, which can be electrical, mechanical or other forms.
  • the units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
  • each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.
  • the above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.
  • the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium.
  • the present application implements all or part of the processes in the above-mentioned embodiment method, and can also be completed by instructing the relevant hardware through a computer program.
  • the computer program can be stored in a computer-readable storage medium, and the computer program can implement the steps of the above-mentioned various method embodiments when executed by the processor.
  • the computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or some intermediate form.
  • the computer-readable medium may include: any entity or device that can carry computer program code, recording medium, U disk, mobile hard disk, disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electric carrier signal, telecommunication signal and software distribution medium.
  • ROM read-only memory
  • RAM random access memory
  • electric carrier signal telecommunication signal and software distribution medium.
  • the content contained in the computer-readable medium can be appropriately increased or decreased according to the requirements of legislation and patent practice in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, the computer-readable medium does not include electric carrier signals and telecommunication signals.

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Abstract

一种极片检测方法、极片检测装置以及终端，通过获取相机在极片走带过程中基于预设采样间隔采样得到的极片图像确定极片的宽度数据，再基于该宽度数据得到极片的缺陷检测结果，从而基于极片的尺寸信息实现极片的缺陷检测，解决了极片缺陷长期以来在制程工序上无有效检测手段，存在风险品流出影响产品品质的问题，无需耗费大量的人力开发复杂的图像处理算法进行极片缺陷的自动识别，因而能够有效降低极片的缺陷检测成本，提高产品的生产效率。

Description

极片检测方法、极片检测装置以及终端 技术领域
本申请涉及电池领域，具体涉及一种极片检测方法、极片检测装置以及终端。
 背景技术
随着锂电新能源行业的迅猛发展，动力电池的生产制造技术越来越受到广泛关注。为了管控制程质量问题，极片表面缺陷的检测技术成为风险品防流出的关键技术。
其中，极片缺陷是一种较为常见的可能引发动力电池安全问题的极片表面缺陷。由于极片缺陷的发生原因错综复杂，较难根治，并且，各类缺陷的形貌、位置和严重程度迥然不同，导致相关技术中，通过建立极片缺陷分类模型实现极片缺陷检测的方式无法较好的实现极片的缺陷检测，存在检测范围较为局限的问题。
 技术问题
本申请实施例的目的之一在于：提供一种极片检测方法、极片检测装置以及终端，可以解决目前的极片检测方法检测范围较为局限的问题。
 技术解决方案
为解决上述技术问题，本申请实施例采用的技术方案是：
第一方面，本申请提供了一种极片检测方法，包括：
获取多帧极片图像；多帧所述极片图像由相机在极片走带过程中采样得到；
确定每帧所述极片图像中所述极片的宽度数据；
根据所述宽度数据确定所述极片的缺陷检测结果。
本申请实施例的技术方案中，通过获取相机在极片走带过程中采样得到的极片图像，并确定每帧极片图像中极片的宽度数据，再基于该宽度数据得到极片的缺陷检测结果，可以实现极片缺陷的有效检测，能够适用于多种类型的极片缺陷检测。
另外，由于本申请实施例提供的极片检测方法是基于极片的尺寸信息实现的，即，极片的宽度数据，无需耗费大量的人力开发复杂的极片缺陷分类模型进行极片缺陷的识别，因而能够有效降低极片的缺陷检测成本，提高产品的生产效率。
并且，由于本申请实施例的技术方案，可以通过在极片整个走带过程中进行缺陷检测，即，在电池不同生成工序中均可以进行极片缺陷问题的自动化检测，例如，冷压、模切、分条和卷绕工序，因而具有检测范围广的特点，能够有效减少漏检情况的发生，有利于提高电池的品质，减少风险品流出。
在一些实施例中，所述极片的宽度数据包括所述极片的极片宽度；
所述根据所述宽度数据确定所述极片的缺陷检测结果，包括：
根据相邻两帧所述极片图像中的所述极片宽度计算极片宽度差值；
在所述极片宽度差值大于第一预设宽度阈值的情况下，得到所述极片为缺陷极片的缺陷检测结果。
本申请实施例的技术方案中，通过计算相邻两帧极片图像中的极片的极片宽度差值，在极片宽度差值大于第一预设宽度阈值的情况下，可以判定极片出现纵向缺陷，得到极片为缺陷极片的缺陷检测结果，从而只需要获取极片图像中极片的宽度，并基于极片的宽度的简单计算和比较即可实现对极片的缺陷的识别，有效降低了极片的缺陷检测成本，提高了产品的生产效率。
在一些实施例中，所述宽度数据包括所述极片上的膜片的膜片宽度；
所述根据所述宽度数据确定所述极片的缺陷检测结果，包括：
根据相邻两帧所述极片图像中的所述膜片宽度计算膜片宽度差值；
在所述膜片宽度差值大于第二预设宽度阈值的情况下，得到所述极片为缺陷极片的缺陷检测结果。
本申请实施例的技术方案中，通过计算相邻两帧极片图像中的极片上膜片的膜片宽度差值，在膜片宽度差值大于第二预设宽度阈值的情况下，可以判定极片出现纵向缺陷，得到极片为缺陷极片的缺陷检测结果，从而只需要获取极片图像中极片上膜片的宽度，并基于膜片的宽度的简单计算和比较即可实现对极片的缺陷的识别，有效降低了极片的缺陷检测成本，提高了产品的生产效率。
在一些实施例中，所述极片的宽度数据包括所述极片的极片宽度和所述极片上的膜片的膜片宽度；
所述根据所述宽度数据确定所述极片的缺陷检测结果，包括：
根据所述极片宽度以及所述膜片宽度，计算相邻两帧所述极片图像中的极片的极片宽度差值和相邻两帧所述极片图像中的膜片的膜片宽度差值；
在所述极片宽度差值大于第一预设宽度阈值和/或所述膜片宽度差值大于第二预设宽度阈值的情况下，得到所述极片为缺陷极片的缺陷检测结果。
本申请实施例的技术方案中，通过计算相邻两帧极片图像中的极片的极片宽度差值以及极片上膜片的膜片宽度差值，在满足极片宽度差值大于第一预设宽度阈值，膜片宽度差值大于第二预设宽度阈值中的至少一项条件的情况下，可以判定极片出现纵向缺陷，得到极片为缺陷极片的缺陷检测结果，从而基于极片宽度、极片上膜片的膜片宽度中的至少一项进行简单计算和比较即可实现对极片的缺陷的识别，避免了缺陷极片的漏检，有效降低了极片的缺陷检测成本，并提高了产品的生产效率。
在一些实施例中，所述极片的宽度数据包括所述极片上的特征点到预设基准线的距离；
所述根据所述宽度数据确定所述极片的缺陷检测结果，包括：
根据相邻两帧所述极片图像中的所述特征点到所述预设基准线的距离，计算相邻两帧所述极片图像中的所述特征点到所述预设基准线的距离差值；
在所述距离差值大于预设距离阈值的情况下，得到所述极片为缺陷极片的缺陷检测结果。
本申请实施例的技术方案中，通过计算相邻两帧极片图像中的极片的特征点到预设基准线的距离差值，在距离差值大于预设距离阈值的情况下，可以判定极片出现纵向缺陷，得到极片为缺陷极片的缺陷检测结果，从而基于特征点到预设基准线的距离进行简单计算和比较即可实现对极片的缺陷的识别，有效降低了极片的缺陷检测成本，并提高了产品的生产效率。
在一些实施例中，所述特征点包括所述极片的边缘特征点和/或所述极片的中心特征点。
在一些实施例中，所述预设基准线为所述相机在拍摄所述极片图像时生成的基准线，所述预设基准线平行于所述极片的纵向边缘。
在一些实施例中，多帧所述极片图像由相机在极片走带过程中基于预设采样时间间隔采样得到。
在一些实施例中，所述预设采样时间间隔为所述极片在极片卷绕工序中卷绕一圈使用的时间。
在一些实施例中，在所述得到所述极片为缺陷极片的缺陷检测结果之后，还包括：
输出极片缺陷提示信息。
在一些实施例中，所述极片的宽度数据包括所述极片上的特征点到预设基准线的距离；
所述根据所述宽度数据确定所述极片的缺陷检测结果，包括：
根据所述极片上的所述特征点到所述预设基准线的距离，计算所述多帧极片图像中极片上的所述特征点到所述预设基准线的距离的平均值和峰值；
在所述平均值与所述峰值的差值大于第一预设差值的情况下，得到所述极片为缺陷极片的缺陷检测结果。
在一些实施例中，在所述得到所述极片为缺陷极片的缺陷检测结果之后，还包括：
输出纠偏提示信息。
在一些实施例中，所述极片检测方法还包括：
获取所述极片的多帧收尾图像；多帧所述收尾图像由所述相机在相邻电芯完成所述极片的卷绕时拍摄得到；
根据所述收尾图像确定所述极片在各个所述电芯上的收尾位置，并计算相邻两个电芯的所述收尾位置的位置差值；
在所述位置差值大于第二预设差值的情况下，得到所述极片为缺陷极片的缺陷检测结果。
本申请实施例的技术方案中，通过计算相邻两个电芯的收尾位置的位置差值，位置差值大于第二预设差值的情况下，判断电芯的卷绕工序中极片出现横向缺陷，导致相邻的电芯的极片在卷绕工序中的收尾位置出现差值，得到极片为缺陷极片的缺陷检测结果，从而基于极片的收尾位置即可实现对极片的缺陷的识别，有效降低了极片的缺陷检测成本，并提高了产品的生产效率。
第二方面，本申请提供了一种极片检测装置，所述极片检测装置包括：
获取单元，用于获取多帧极片图像；多帧所述极片图像由相机在极片走带过程中采样得到；
第一确定单元，用于确定每帧所述极片图像中极片的宽度数据；
第二确定单元，用于根据所述宽度数据确定所述极片的缺陷检测结果。
第三方面，本申请提供了一种终端，包括存储器、处理器以及存储在所述存储器中并可在所述处理器上运行的计算机程序，所述处理器执行所述计算机程序时实现如上述第一方面任意一项实施例所述方法的步骤。
第四方面，本申请提供了一种计算机可读存储介质，所述计算机可读存储介质存储有计算机程序，所述计算机程序被处理器执行时实现如上述第一方面任意一项实施例所述方法的步骤。
 有益效果
本申请实施例的技术方案中，通过获取相机在极片走带过程中基于预设采样间隔采样得到的极片图像确定极片的宽度数据，再基于该宽度数据得到极片的缺陷检测结果，从而基于极片的尺寸信息实现极片的缺陷检测，解决了极片缺陷长期以来在制程工序上无有效检测手段，存在风险品流出影响产品品质的问题，无需耗费大量的人力开发复杂的极片缺陷分类模型进行极片缺陷的自动识别，因而能够有效降低极片的缺陷检测成本，提高产品的生产效率。
 附图说明
通过阅读对下文优选实施方式的详细描述，各种其他的优点和益处对于本领域普通技术人员将变得清楚明了。附图仅用于示出优选实施方式的目的，而并不认为是对本申请的限制。而且在全部附图中，用相同的附图标号表示相同的部件。在附图中：
图1为本申请实施例的提供的极片检测方法的第一种实现流程示意图；
图2为本申请实施例的提供的极片图像的第一种示意图；
图3为本申请实施例的提供的极片图像的第二种示意图；
图4为本申请实施例的提供的获取极片图像的示意图；
图5为本申请实施例提供的极片卷绕收尾位置的示意图；
图6为本申请实施例提供的极片检测方法步骤S300的第一种实现流程示意图；
图7为本申请实施例提供的极片检测方法步骤S300的第二种实现流程示意图；
图8为本申请实施例提供的极片检测方法步骤S300的第三种实现流程示意图；
图9为本申请实施例提供的极片检测方法步骤S300的第四种实现流程示意图；
图10为本申请实施例提供的极片检测方法步骤S300的第五种实现流程示意图；
图11为本申请实施例的提供的极片检测方法的第二种实现流程示意图；
图12为本申请实施例的提供的极片检测装置的结构框图；
图13为本申请实施例的提供的终端的结构示意图。
 本发明的实施方式
上述说明仅是本申请技术方案的概述，为了能够更清楚了解本申请的技术手段，而可依照说明书的内容予以实施，并且为了让本申请的上述和其它目的、特征和优点能够更明显易懂，以下特举本申请的具体实施方式。
下面将结合附图对本申请技术方案的实施例进行详细的描述。以下实施例仅用于更加清楚地说明本申请的技术方案，因此只作为示例，而不能以此来限制本申请的保护范围。
除非另有定义，本文所使用的所有的技术和科学术语与属于本申请的技术领域的技术人员通常理解的含义相同；本文中所使用的术语只是为了描述具体的实施例的目的，不是旨在于限制本申请；本申请的说明书和权利要求书及上述附图说明中的术语“包括”和“具有”以及它们的任何变形，意图在于覆盖不排他的包含。
在本申请实施例的描述中，技术术语“第一”“第二”等仅用于区别不同对象，而不能理解为指示或暗示相对重要性或者隐含指明所指示的技术特征的数量、特定顺序或主次关系。在本申请实施例的描述中，“多个”的含义是两个以上，除非另有明确具体的限定。
在本文中提及“实施例”意味着，结合实施例描述的特定特征、结构或特性可以包含在本申请的至少一个实施例中。在说明书中的各个位置出现该短语并不一定均是指相同的实施例，也不是与其它实施例互斥的独立的或备选的实施例。本领域技术人员显式地和隐式地理解的是，本文所描述的实施例可以与其它实施例相结合。
在本申请实施例的描述中，术语“和/或”仅仅是一种描述关联对象的关联关系，表示可以存在三种关系，例如A和/或B，可以表示：单独存在A，同时存在A和B，单独存在B这三种情况。另外，本文中字符“/”，一般表示前后关联对象是一种“或”的关系。
在本申请实施例的描述中，术语“多帧”指的是两个以上（包括两个）。
在本申请实施例的描述中，技术术语“中心”“纵向”“横向”“长度”“宽度”“厚度”“上”“下”“前”“后”“左”“右”“竖直”“水平”“顶”“底”“内”“外”“顺时针”“逆时针”“轴向”“径向”“周向”等指示的方位或位置关系为基于附图所示的方位或位置关系，仅是为了便于描述本申请实施例和简化描述，而不是指示或暗示所指的装置或元件必须具有特定的方位、以特定的方位构造和操作，因此不能理解为对本申请实施例的限制。
为了管控制程质量问题，极片表面缺陷的探测技术成为风险品（例如电解液、不合格电池等）防流出的关键措施。其中，极片缺陷是一种较为常见的可能引发锂电池安全问题的高风险失效模式，但由于极片缺陷的发生原因错综复杂，较难根治，再者各类缺陷的形貌、位置和严重程度迥然不同，导致此类缺陷长期以来在制程工艺上无有效探测手段实现防流出管控。在相关技术中，可以通过建立极片缺陷分类模型实现极片缺陷检测，但是该方式一般仅对部分工序中的极片的缺陷进行检测，例如，利用CCD相机（charge coupled device camera）采集极耳图像，并将极耳图像与预设的图像模型进行比对分析判断是否存在极片缺陷现象，在电芯的装配阶段，无法对卷绕工序中由于极片波浪边、纠偏超限、过辊卡滞等导致的极片缺陷进行检测，因此存在检测范围较为局限、开发成本较高且开发周期长的问题。
为了解决极片缺陷检测存在的问题，本申请实施例提供了一种极片检测方法，该极片检测方法适用于需要对极片进行缺陷检测的情形，可以由终端上配置的极片检测装置执行，该终端可以为服务器、电脑等终端设备，本申请对此不做限制。
参见图1所示，本实施例中的极片检测方法包括步骤S100至步骤S300。
在步骤S100中，获取多帧极片图像。
在本实施例中，多帧极片图像可以由相机在极片走带过程中对极片进行图像采样得到，由于极片处于走带过程中，相机对极片走带过程中的指定位置进行采样即可得到多个不同采样位置对应的极片图像。
在一个实施例中，多帧极片还可以通过在移动相机的过程中对极片进行图像采样得到，例如，极片此时保持静止，移动相机对极片上的多个采样位置进行极片图像采样。
在一个实施例中，相机的移动过程可以按照相机匀速运动，并按照预设采样时间间隔拍摄极片得到多个采样位置的极片图像。
在一个实施例中，多帧极片图像中相邻的极片图像之间的采样时间设置为预设采样时间间隔。
在本实施例中，多帧极片图像由相机在极片走带过程中基于预设采样时间间隔采样得到，电池生产需要采用轧辊对极片进行连续辊压压实得到电池的电芯，在采用轧辊对极片进行辊压的情况下，极片处于走带过程，极片相对相机运动，因此，相机基于预设采样时间间隔对位于生产线的指定位置的极片进行极片图像采样，即可得到极片不同采样位置对应的极片图像，且保证相邻的采样位置之间的距离相同。
在一个实施例中，极片的走带过程为极片随轧辊的转动而运动的过程，此时，相机与轧辊相对静止，当极片随轧辊的转动而运动的情况下，相机按照预设采样时间间隔对极片进行图像采样，即可实现对极片上的多个采样位置进行图像采样得到对应的极片图像。
在一个实施例中，相机进行图像采样的指定位置可以位于轧辊的进入侧，也可以位于轧辊的离开侧。其中，轧辊的进入侧是指极片进入轧辊的一侧，轧辊的离开侧是指极片由轧辊处理后出来的一侧。
在一个实施例中，相机进行图像采样的指定位置与轧辊之间的距离范围可以为10-100cm。
在一个实施例中，相机的感光面与极片之间的垂直距离的范围可以为10-100cm。
在一个实施例中，通过调节预设采样时间间隔的时长可以调整极片上相邻采样位置的间隔距离。
极片上相邻采样位置的间隔距离S=v*t，其中，t为预设采样时间间隔，v表示轧辊的转速。具体的，若轧辊带动极片进行运动的走带速度为10cm/s，预设采样时间间隔为1s，则表示极片上相邻采样位置的间隔距离为10cm。
在一个实施例中，极片上相邻采样位置的间隔距离与极片的宽度呈正相关关系，例如，极片上相邻采样位置的间隔距离为极片宽度的20%-1000%。
在一个实施例中，极片上相邻采样位置的间隔距离与极片的工序相关，通过获取极片的生产工序，对预设采样时间间隔的时长进行设置，从而对极片上相邻采样位置的间隔距离进行调整，达到对极片各个工序的针对性图像采样的目的，降低极片在线缺陷检测的成本。
在一个实施例中，在极片的模切工序中，通过对预设采样时间间隔的时长进行设置，使得极片上相邻采样位置的间隔距离可以为极片的宽度。
在一个实施例中，极片包括阳极片和阴极片，在极片的卷绕工序中，阴极片、阳极片以及隔膜在同一卷针上进行卷绕形成电芯，预设采样时间间隔为极片卷绕工序中卷绕一圈所需的时间，则可以对电芯中每一圈的极片进行图像采样。
在一个实施例中，相机可以为工业相机，该工业相机可以应用于极片的冷压、模切、分条和卷绕等工序中，从而在生产过程中对极片的不同采样位置进行图像采样，由极片图像中极片的宽度数据确定极片是否出现缺陷现象。
在步骤S200中，确定每帧极片图像中极片的宽度数据。
在本实施例中，获取多帧极片图像后，可以通过图像识别的方式确定每帧极片图像中极片的尺寸信息，得到极片的宽度数据。
由于极片宽度出现异常的情况下，可以判定极片发生缺陷，因此，在一个实施例中，极片的宽度数据可以包括极片宽度。
其中，极片宽度是指极片的纵向边缘之间的距离，例如，参见图2所示，极片图像中包括极片110的边缘特征点21以及与极片110的边缘特征点21相对的边缘特征点22，此时极片宽度W1即为极片110的边缘特征点21与边缘特征点22之间的距离。
由于极片上的膜片的膜片宽度出现异常的情况下，可以判定极片发生缺陷，因此，在一个实施例中，极片的宽度数据可以包括极片上的膜片的膜片宽度。
其中，膜片可以是附着于电极集流体上的活性物质层等膜状结构；膜片宽度是指膜片的纵向边缘之间的距离，例如，参见图2所示，极片图像中包括极片110上的膜片120的边缘特征点23以及与边缘特征点23相对的边缘特征点24，此时膜片宽度W2即为膜片120的边缘特征点23与边缘特征点24之间的距离。
其中，上述的“纵向”是指条形物体的长度方向，纵向边缘则是指条形物体的沿长度方向延伸的边缘，也可以称为“长边”，可以理解，纵向边缘之间的距离则代表条形物体的宽度。自然，极片的纵向指极片的长度方向，极片的纵向边缘之间的距离即是极片宽度；膜片的纵向是指膜片的长度方向，膜片的纵向边缘之间的距离即是膜片宽度。
由于极片上的特征点到预设基准线的距离出现异常的情况下，可以判定极片发生缺陷，因此，在一个实施例中，极片的宽度数据可以包括极片上的特征点到预设基准线的距离。
其中，极片上的特征点可以包括极片的边缘特征点、中心特征点中的至少一项。例如，极片上的特征点可以包括参见图2所示的边缘特征点21、边缘特征点22、边缘特征点23、边缘特征点24和中心特征点25中的一个或多个特征点。
在一个实施例中，上述实施例中的预设基准线26可以为相机中自带的基准线，该预设基准线26可以在每次图像采样时自动增加至极片图像中。例如，参考图3所示，预设基准线26可以在每次图像采样时自动增加至极片图像中，此时预设基准线26位于极片图像中的固定位置，相邻帧极片图像中极片上的特征点可能相对预设基准线26发生位移。
在一个实施例中，预设基准线26可以为位于极片110的图像区域内，也可以位于极片110的图像区域外，预设基准线26需要与极片110和膜片120的边缘平行设置。
在一个实施例中，结合图4所示，在极片的卷绕工序中，阳极极片303、第一隔膜302、第二隔膜304以及阴极极片307依序层叠卷绕在卷针301上，阳极极片303的宽度大于阴极极片307的宽度；相机331和相机332对阳极极片303左右两侧的区域进行图像采样，相机333和相机334对阴极极片307左右两侧的区域进行图像采样，阴极极片307的左侧边缘305上的点和右侧边缘306上的点可以作为阴极极片307的边缘特征点，预设基准线320为每次图像采样时自动增加至极片图像中的基准线，用于为极片上的特征点提供参考。如图4所示，在阴极极片307的走带过程中，阴极极片307的右侧边缘306与预设基准线320之间的距离出现一定的波动，参见图中的阴影区域，若阴极极片307的右侧边缘306上的特征点与预设基准线320之间的距离超出设定的范围，则可以判定阴极极片307发生缺陷。
在一个实施例中，相机331、相机332、相机333和相机334在图像采样过程中均可以将自带的基准线作为预设基准线，该预设基准线可以在每次图像采样时自动增加至极片图像中。相机331和相机332对阳极极片303左右两侧的区域进行图像采样，相机333和相机334对阴极极片307左右两侧的区域进行图像采样，若任一区域内的极片图像中极片上的特征点到预设基准线的距离出现异常的情况下，可以判定极片发生缺陷。
在一个实施例中，上述实施例中的预设基准线也可以为与轧辊相对静止的基准线，用于为极片上的特征点的位置提供参考，并且，该预设基准线可以在相机进行图像采样时被拍摄到，进而呈现在极片图像中。
由于极片在各个电芯上的收尾位置出现异常的情况下，可以判定极片发生在卷绕过程中发生横向缺陷，因此，在一个实施例中，极片的宽度数据可以包括相邻两个电芯上的极片卷绕收尾位置的位置差值。
在一个实施例中，结合图5所示，电芯n与电芯n+1在电芯的卷绕工序为前后两个电芯，电芯n的收尾位置为位置A，电芯n+1的收尾位置为位置B，位置差值L1表示位置A与位置B的距离，即，电芯n的收尾位置与电芯n+1的收尾位置之间的位置差值。
需要说明的是，上述仅仅是对极片的宽度数据进行举例说明，不表示为对本申请保护范围的限制。在本申请的其他实施例中，极片的宽度数据还可以包括其他宽度数据，例如，在一个实施例中，极片的宽度数据还可以包括极片的边缘特征点与膜片的边缘特征点之间的距离。例如，极片的宽度数据可以为极片110的边缘特征点21与膜片120的边缘特征点23之间的距离。
还需要说明的是，在本申请的一些实施例中，上述极片的宽度数据可以包括上述极片宽度、膜片宽度、极片上的特征点到预设基准线的距离、电芯在卷绕工序结束时极片的收尾位置差值中的任意多种宽度数据的组合。
例如，在一个实施例中，极片的宽度数据可以同时包括上述极片宽度以及上述膜片宽度。
并且，为了尽可能避免发生极片缺陷漏检的情况，在一个实施例中，极片的宽度数据还可以同时包括上述极片宽度、膜片宽度、极片上的特征点到预设基准线的距离、电芯在卷绕工序结束时极片的收尾位置差值这四种宽度数据。
在步骤S300中，根据宽度数据确定极片的缺陷检测结果。
在本实施例中，在得到上述宽度数据之后，即可根据该宽度数据确定极片是否为缺陷极片的缺陷检测结果。
例如，当极片的宽度数据包括极片宽度和膜片宽度的情况下，若极片宽度大于第一预设宽度阈值，或者膜片宽度大于第二预设宽度阈值，则表示极片在走带过程中由于缺陷导致极片宽度出现异常或膜片宽度出现异常，因而可以判定极片出现缺陷现象，并生成对应的缺陷检测结果，从而实现基于极片尺寸信息，即，极片的宽度数据完成对极片的缺陷检测。
可选地，第一预设宽度阈值与极片的宽度呈正相关。
在一个实施例中，第一预设宽度阈值可以位于极片的宽度的千分之一至膜片的宽度的千分之五之间。
可选地，第二预设宽度阈值与膜片的宽度呈正相关。
在一个实施例中，第二预设宽度阈值可以位于膜片的宽度的千分之一至膜片的宽度的千分之五之间。
本申请实施例的技术方案中，通过获取相机在极片走带过程中采样得到的极片图像，并确定多帧极片图像中极片的宽度数据，再基于该宽度数据得到极片的缺陷检测结果，可以实现极片缺陷的有效检测，减少出现风险品流出，影响产品品质的问题。
另外，由于本申请实施例提供的极片检测方法是基于极片的尺寸信息实现的，即，极片的宽度数据，无需耗费大量的人力开发复杂的极片缺陷分类模型进行极片缺陷的识别，因而能够有效降低极片的缺陷检测成本，提高产品的生产效率。
并且，由于本申请实施例的技术方案，可以通过在极片整个走带过程中进行缺陷检测，即，在电池不同生成工序中均可以进行极片缺陷问题的自动化检测，例如，冷压、模切、分条和卷绕工序，因而具有检测范围广的特点，能够有效避免漏检情况的发生，有利于提高电池的品质，减少风险品流出。
在一个实施例中，参见图6所示，当极片的宽度数据包括极片宽度的情况下，上述步骤S300中，根据宽度数据确定极片的缺陷检测结果可以具体包括步骤S311和步骤S312。
在步骤S311中，根据极片宽度计算相邻两帧极片图像中的极片的极片宽度差值。
在一个实施例中，由于极片走带过程中，相机与轧辊相对静止，当极片随轧辊的转动而运动的情况下，相机按照预设采样时间间隔对极片进行图像采样，即可得到极片不同采样位置对应的极片图像。每帧极片图像中极片的极片宽度即表示与该帧极片图像对应的采样位置的极片宽度，相机对位于生产线的指定位置的极片拍摄连续多帧极片图像，即等同于对极片上连续多个采样位置进行图像采样。
在步骤S312中，在极片宽度差值大于第一预设宽度阈值的情况下，得到极片为缺陷极片的缺陷检测结果。
在本实施例中，将极片宽度差值与第一预设宽度阈值进行比较，若极片宽度差值小于第一预设宽度阈值，则表示极片可能未发生缺陷，若极片宽度差值大于第一预设宽度阈值，则表示极片异常，此时将极片确定为缺陷极片，即，得到极片为缺陷极片的缺陷检测结果。
在一个实施例中，相邻两帧极片图像中极片的极片宽度差值即表示极片上对应的相邻的两个采样位置的极片宽度差值。
在一个实施例中，相邻两帧极片图像中的极片宽度的差值包括：两两相邻的每两帧极片图像中的极片宽度的差值，即任意相邻的两帧极片图像的极片宽度的差值，例如，若相机采样了k帧极片图像，k帧极片图像对应极片上的k个采样位置的采样图像，k为大于2的正整数，此时，两两相邻的采样位置的极片宽度差值包括k-1个极片宽度差值， k-1个极片宽度差值中，任一极片宽度差值大于第一预设宽度阈值，则表示极片异常，此时将极片确定为缺陷极片，即，得到极片为缺陷极片的缺陷检测结果。
在一个实施例中，当极片的宽度数据包括极片上的膜片的膜片宽度的情况下，参见图7所示，上述步骤S300中，根据宽度数据确定极片的缺陷检测结果可以具体包括步骤S321和步骤S322。
在步骤S321中，根据膜片宽度计算相邻两帧极片图像中的膜片的膜片宽度差值。
在本实施例中，极片上设有膜片，膜片的宽度小于极片的宽度，由于相机与轧辊相对静止，当极片随轧辊的转动而转动的情况下，相机按照预设采样时间间隔对指定位置的极片进行图像采样，即可得到极片不同采样位置对应的极片图像。每帧极片图像中极片上膜片的膜片宽度即表示与该帧极片图像对应的采样位置的膜片宽度，相机对位于生产线的指定位置的极片拍摄连续多帧极片图像，即等同于对极片上连续多个采样位置进行图像采样。
在一个实施例中，相邻两帧极片图像中极片上膜片之间的膜片宽度差值即表示极片上对应的相邻的两个采样位置的极片膜片宽度的差值，基于连续多帧极片图像中的极片的膜片宽度可以计算得到极片上任意相邻的两个极片图像的膜片宽度差值。
在步骤S322中，在膜片宽度差值大于第二预设宽度阈值的情况下，得到极片为缺陷极片的缺陷检测结果。
在本实施例中，将膜片宽度差值与第二预设宽度阈值进行比较，若膜片宽度差值小于第二预设宽度阈值，则表示可能未发生缺陷，若极片宽度差值大于第二预设宽度阈值，则表示极片异常，此时将极片确定为缺陷极片。
在一个实施例中，相邻两帧极片图像中的极片上膜片的宽度差值包括两两相邻的每两帧极片图像中的极片膜片宽度的差值，即，膜片宽度差值包括极片上任意相邻的两个采样位置的膜片宽度的差值，例如，若相机采样了k帧极片图像，k帧极片图像对应极片上的k个采样位置的采样图像，此时，两两相邻的采样位置的膜片宽度差值包括k-1个膜片宽度差值，k-1个极片宽度差值中，任一极片宽度差值大于第二预设宽度阈值，则表示极片异常，此时将极片确定为缺陷极片，即，得到极片为缺陷极片的缺陷检测结果。
在一个实施例中，当极片的宽度数据包括极片的极片宽度和极片上的膜片的膜片宽度的情况下，参见图8所示，上述步骤S300中，根据宽度数据确定极片的缺陷检测结果可以具体包括步骤S331和步骤S332。
在步骤S331中，根据极片宽度以及膜片宽度，计算相邻两帧极片图像中的极片宽度的差值和相邻两帧极片图像中的膜片宽度的差值。
在步骤S332中，在极片宽度差值大于第一预设宽度阈值或者膜片宽度差值大于第二预设宽度阈值的情况下，得到极片为缺陷极片的缺陷检测结果。
在本实施例中，将极片宽度差值与第一预设宽度阈值进行比较，将膜片宽度差值与第二预设宽度阈值进行比较，若极片宽度差值小于第一预设宽度阈值且膜片宽度差值小于第二预设宽度阈值，则表示极片可能未发生缺陷，若极片宽度差值大于第一预设宽度阈值或者极片宽度差值大于第二预设宽度阈值，则表示极片异常，此时将极片确定为缺陷极片。若极片宽度差值大于第一预设宽度阈值，并且极片宽度差值大于第二预设宽度阈值，则表示极片异常，此时将极片确定为缺陷极片。
在一个实施例中，第一预设宽度阈值的范围可以为0.1-0.5mm。
在一个实施例中，第二预设宽度阈值的范围可以为0.1-0.5mm。
在其他实施例中，将极片宽度差值与第一预设宽度上限值进行比较，若极片宽度差值大于第一预设宽度上限值，则确定极片出现破损异常，得到极片为破损极片的缺陷检测结果。
其中，第一预设宽度上限值大于上述的第一预设宽度阈值，例如，第一预设宽度上限值为第一预设宽度阈值3-5倍。
在其他实施例中，将膜片宽度差值与第二预设宽度上限值进行比较，若极片膜片宽度差值大于第二预设宽度上限值，则确定极片出现破损异常，得到极片为破损极片的缺陷检测结果。
其中，第二预设宽度上限值大于上述的第二预设宽度阈值，例如，第二预设宽度上限值为第二预设宽度阈值3-5倍。
在一个实施例中，第一预设宽度上限值可以为1-3mm。
在一个实施例中，当极片的宽度数据包括极片上的特征点到预设基准线的距离的情况下，参见图9所示，上述步骤S300中，根据宽度数据确定极片的缺陷检测结果具体包括步骤S341和步骤S342。
在步骤S341中，根据特征点到预设基准线的距离，计算相邻两帧极片图像中的极片特征点到预设基准线的距离差值。
在本实施例中，预设基准线可以为相机中自带的基准线，通过在每帧极片图像上确定极片的特征点，并计算每帧极片图像上极片的特征点与该预设基准线之间的距离，即可根据该距离计算得到相邻两帧极片图像中的极片的特征点与该预设基准线之间的距离差值。
在步骤S342中，在距离差值大于预设距离阈值的情况下，得到极片为缺陷极片的缺陷检测结果。
在本实施例中，若相邻两帧极片图像中的特征点到预设基准线的距离差值小于预设距离阈值，则表示极片可能未发生缺陷，若料线距离差值大于预设距离阈值的情况下，则表示极片异常，可以将极片确定为缺陷极片，进而得到极片为缺陷极片的缺陷检测结果。
在一个实施例中，特征点可以包括极片的边缘特征点，此时特征点到预设基准线之间的距离可以为极片图像中极片的边缘特征点与预设基准线之间的距离，即相机在拍摄瞬间极片上采样位置的边缘特征点与预设基准线之间的距离，基于该距离可以计算相邻两帧极片图像中的极片的边缘特征点到预设基准线的距离差值。
在特征点包括极片的边缘特征点的实施例中，该边缘特征点可以为极片图像上极片的左侧边缘上的边缘特征点，例如，如图2所示，该边缘特征点可以为极片图像上的边缘特征点21。
在特征点包括极片的边缘特征点的实施例中，该边缘特征点可以为极片图像上极片的右侧边缘上的边缘特征点，例如，参见图2所示，该边缘特征点可以为极片图像上的边缘特征点22。
在特征点包括极片的边缘特征点的实施例中，获取连续的多帧极片图像，每帧极片图像对应为极片上一个采样位置的采样图像，统计每帧极片图像中极片上的边缘特征点与预设基准线之间的距离，为了便于描述，本申请实施例中将“极片图像中极片上的边缘特征点与预设基准线之间的距离”称为“料线距离”，本实施例统计多个料线距离，基于多个料线距离生成纠偏曲线，该纠偏曲线用于表征极片的边缘相对预设基准线的位移，纠偏曲线的波动值即为相邻两帧极片图像中的极片的边缘特征点到预设基准线的料线距离差值，若该料线距离差值大于预设距离阈值，则将极片确定为缺陷极片。
在一个实施例中，本实施例中的预设距离阈值可以为0.5-1.5mm。
为了便于描述，本实施例中的预设距离阈值称为“第一预设距离阈值”。
其中，该第一预设距离阈值与极片的宽度呈正相关。
在另一个实施例中，特征点可以包括极片的中心特征点，此时特征点到预设基准线之间的料线距离可以为极片图像中极片的中心特征点与预设基准线之间的距离，即相机在拍摄瞬间极片上采样位置的中心特征点与预设基准线之间的距离，基于该料线距离可以计算相邻两帧极片图像中的极片的中心特征点到预设基准线的距离差值。
在特征点包括极片的中心特征点的实施例中，该中心特征点可以为极片图像上极片的左侧边缘与右侧边缘之间的中点，即极片上采样位置的左侧边缘与右侧边缘之间的中点，例如，参见图2所示，该中心特征点可以为边缘特征点21与边缘特征点22连线的中点。
在特征点包括极片的中心特征点的实施例中，获取连续的多帧极片图像，每帧极片图像对应为极片上一个采样位置的采样图像，统计每帧极片图像中极片上的中心特征点与预设基准线之间的距离，得到多个料线距离，基于多个料线距离生成纠偏曲线，该纠偏曲线用于表征极片的中心相对预设基准线的位移，纠偏曲线的波动值即为相邻两帧极片图像中的极片的中心特征点到预设基准线的料线距离差值，若该料线距离差值大于预设距离阈值，则将极片确定为缺陷极片。为了便于描述，本实施例中的预设距离阈值称为“第二预设距离阈值”。
其中，该第二预设距离阈值与极片的宽度呈正相关。
在一个实施例中，第一预设距离阈值和第二预设距离阈值可以相同或者不同，可以位于极片的宽度的千分之一至极片的宽度的千分之五之间。
在一个实施例中，第一预设距离阈值、第二预设距离阈值可以为0.1-0.5mm。
在一个实施例中，预设采样时间间隔为极片在卷绕工序中卷绕一圈使用的时间。
在本实施例中，在卷绕工序中，阴极片、阳极片以及隔膜在同一卷针上进行卷绕形成电芯，通过将预设采样时间间隔设置为极片卷绕工序中卷绕一圈所需的时间，则可以对电芯中每一圈的极片进行图像采样，若任意相邻圈极片的极片宽度差值大于第一预设宽度阈值，则将该极片确定为缺陷极片。
在一个实施例中，在卷绕工序中，通过将预设采样时间间隔设置为极片卷绕工序中卷绕一圈所需的时间，则可以对电芯中每一圈的极片进行图像采样，若任意相邻圈极片上膜片的膜片宽度差值大于第二预设宽度阈值，则将该极片确定为缺陷极片。
在一个实施例中，在卷绕工序中，若每个电芯中的任意一圈极片被确定为缺陷极片，则将该电芯标记为异常电芯，并报废处理。
在一个实施例中，步骤S300中，在得到极片为缺陷极片的缺陷检测结果之后还包括：输出极片缺陷提示信息。
在本实施例中，若得到极片为缺陷极片的缺陷检测结果，则输出极片缺陷提示信息，提醒用户出现极片缺陷现象，可选的，输出极片缺陷提示信息后可以控制当前生产工序上的生产设备停机。
在一个实施例中，当前生产工序上的生产设备停机之后，还可以对当前生产工序上的极片进行缺陷标记，然后复机生产。
在本实施例中，该缺陷标记可以为物理标记，例如在得到当前生产工序上的极片为缺陷极片的缺陷检测结果后，可以在当前生产工序上的极片上贴上缺陷标识。
在一个实施例中，前工序包括极片的冷压、模切、分条工序，装配工序包括卷绕工序，若缺陷标记发生在前工序，则在装配工序对缺陷标记进行检测，若检测到该缺陷标记，则将装配工序中的电芯报废处理。
在一个实施例中，若缺陷标记发生在前工序，极片在热压后排出，对具有缺陷标记的极片进行复测，例如采用离线大功率X射线仪器检测极片微观图像，若复判为缺陷极片，则将极片报废处理。
在一个实施例中，多帧极片图像可以为极片在行走预设走带距离的过程中，由相机采样得到；极片的宽度数据包括极片上的特征点到预设基准线的距离。
具体的，每隔一段走带距离X即选取极片行走的预设走带距离Y，在预设走带距离Y内采集多帧极片图像，相机在极片的预设走带距离Y内采集图像的间隔时间可以为上述任一项实施例中的预设采样时间间隔。
在一个实施例中，走带距离X可以为多个电芯内的极片长度之和。
在一个实施例中，X可以等于Y。
参见图10所示，步骤S300中，根据宽度数据确定极片的缺陷检测结果，具体包括步骤S351和步骤S352。
在步骤S351中，根据极片上的特征点到预设基准线的距离，计算多帧极片图像中极片上的特征点到预设基准线的距离的平均值和峰值。
本实施例中，在极片的走带过程中选取预设走带距离，并在该预设走带距离内对极片按照预设采样时间进行间隔采样得到多个采样位置的极片图像，统计每帧极片图像中极片上的特征点到预设基准线之间的距离得到多个料线距离，并计算多个料线距离的平均值以及多个料线距离的峰值。
在一个实施例中，多个料线距离的峰值可以为多个料线距离中的最小值，也可以为多个料线距离中的最大值。
在步骤S352中，在平均值与峰值的差值大于第一预设差值的情况下，得到极片为缺陷极片的缺陷检测结果。
在本实施例中，计算多个料线距离的平均值和峰值后，将峰值与平均值进行比较，计算峰值与平均值之间的差值，若该差值大于第一预设差值，则将极片确定为缺陷极片。
在一个实施例中，基于多个料线距离生成纠偏曲线，该纠偏曲线用于表征极片的特征点相对预设基准线的位移，纠偏曲线的波峰与波谷即对应多个料线距离中的峰值，若峰值与平均值之间的差值大于第一预设差值，则将极片确定为缺陷极片。
在一个实施例中，纠偏曲线还可以由纠偏感应器识别的极片的特征点与预设基准线之间的距离组成的趋势线。卷绕纠偏过激是导致极片横向缺陷的常见原因，这类极片缺陷的共同点为：基准料线偏移、料宽突变、纠偏料线偏移，因此可利用纠偏感应器监控料线距离的波动来预警极片缺陷。
在一个实施例中，极片行走预设走带距离的过程中，由纠偏感应器识别的极片的特征点与预设基准线之间的距离组成纠偏曲线极片，极片纠偏曲线上相邻特征点之间的距离大于预设距离差值，则同样可以判定极片为缺陷极片。
在一个实施例中，第一预设差值和预设距离差值可以与极片的宽度呈正相关。
在一个实施例中，第一预设差值和预设距离差值可以位于极片的宽度的千分之一至极片的宽度的千分之五之间。
在一个实施例中，第一预设差值和预设距离差值可以为0.1-0.5mm。
在一个实施例中，步骤S300中，在得到极片为缺陷极片的缺陷检测结果之后还包括：输出纠偏提示信息。
在本实施例中，计算多个料线距离的平均值和峰值后，若峰值与平均值之间的差值大于第一预设差值，则得到极片为缺陷极片的缺陷检测结果，并输出纠偏提示信息，提醒用户出现卷绕纠偏现象。
极片可选的，输出极片缺陷提示信息后可以控制设备停机。
在一个实施例中，生产设备停机之后，可以对当前生产工序上的极片进行缺陷标记，然后复机生产。
在一个实施例中，参见图11所示，本实施例中的极片检测方法还包括步骤S610至步骤S630。
在步骤S610中，获取极片的多帧收尾图像。
在本实施例中，多帧收尾图像由相机在相邻电芯完成极片的卷绕时拍摄得到。
在一个实施例中，阴极极片、阳极极片以及隔膜在同一卷针上进行卷绕形成电芯，极片的收尾图像为相机在极片卷绕至最后一圈或者接近最后一圈（例如倒数第二圈、倒数第三圈等）时拍摄得到的图像。
在一个实施例中，阴极极片、阳极极片以及隔膜在同一卷针上进行卷绕形成电芯，在电芯的卷绕工序中，通过在卷绕轧辊的一侧设置相机，可以拍摄每个电芯的阴极极片在电芯卷绕结束的收尾图像作为极片的多帧收尾图像。
在步骤S620中，根据收尾图像确定极片在各个电芯上的收尾位置，并计算相邻两个电芯的收尾位置的位置差值。
在本实施例中，根据收尾图像确定每个电芯中极片的收尾位置，计算前后相邻的两个电芯的收尾位置的位置差值。
在步骤S630中，在位置差值大于第二预设差值的情况下，将极片确定为缺陷极片。
在本实施例中，由于前后相邻的两个电芯的极片的参数通常相同，例如，前后相邻的两个电芯的极片的长度相同，在完成电芯的卷绕工序的情况下，其收尾位置也相同，若前后相邻的两个电芯的收尾位置出现偏差，则表示当前的电芯的极片在卷绕过程中可能出现异常，例如，极片上出现横向缺陷导致极片的长度减小，具体的，若前后相邻的两个电芯的收尾位置之间的位置差值大于第二预设差值，则将极片确定为缺陷极片。
在一个实施例中，第二预设差值可以与电芯的极片的长度呈正比例关系。
在一个实施例中，第二预设差值可以为电芯的极片的长度的千分之一至千分之五。
在一个实施例中，第二预设差值可以为1-5mm。
本申请中，对于前述的各方法实施例，为了简单描述，故将其都表述为一系列的动作组合，但是本领域技术人员应该知悉，本申请并不受所描述的动作顺序的限制，在本申请的一些实施例中，某些步骤可以采用其它顺序进行。
如图12所示，为本申请实施例提供的极片检测装置800的结构示意图，该极片检测装置可以配置于上述终端上，包括：获取单元801、第一确定单元802和第二确定单元803。
获取单元801，用于获取多帧极片图像；多帧极片图像由相机在极片走带过程中采样得到；
第一确定单元802，用于确定每帧极片图像中极片的宽度数据；
第二确定单元803，用于根据宽度数据确定极片的缺陷检测结果。
需要说明的是，为描述的方便和简洁，上述描述的极片检测装置800的具体工作过程，可以参考上述各个极片检测方法实施例中的描述，在此不再赘述。并且，还需要说明的是，上述各个实施方式可以进行相互组合，得到多种不同的实施方式，均属于本申请的保护范围。
如图13所示，本申请实施例还提供一种终端。该终端可以配置有上述各个实施方式所示的极片检测装置。如图13所示，终端8可以包括：处理器80、存储器81以及存储在存储器81中并可在处理器80上运行的计算机程序82。处理器80执行计算机程序82时实现上述各个极片检测方法实施例中的步骤，例如，图1所示的步骤S100至步骤S300。
所称处理器80可以是中央处理单元（Central Processing Unit，CPU），还可以是其他通用处理器、数字信号处理器（Digital Signal Processor，DSP）、专用集成电路（Application Specific Integrated Circuit，ASIC)、现成可编程门阵列（Field-Programmable Gate Array，FPGA）或者其他可编程逻辑器件、分立门或者晶体管逻辑器件、分立硬件组件等。通用处理器可以是微处理器，也可以是任何常规的处理器等。
存储器81可以是终端8的内部存储单元，例如，硬盘或内存。存储器81也可以是用于终端8的外部存储设备，例如，终端8上配备的插接式硬盘，智能存储卡（Smart Media Card，SMC），安全数字（Secure Digital，SD）卡，闪存卡（Flash Card）等。进一步地，存储器81还可以既包括终端8的内部存储单元也包括外部存储设备。存储器81用于存储上述计算机程序以及终端所需的其他程序和数据。
上述计算机程序可以被分割成一个或多个单元，上述一个或者多个单元被存储在上述存储器81中，并由上述处理器80执行，以完成本申请。上述一个或多个单元可以是能够完成特定功能的一系列计算机程序指令段，该指令段用于描述上述计算机程序在上述进行极片缺陷检测的终端中的执行过程。例如，上述计算机程序可以被分割成：获取单元、第一确定单元和第二确定单元，具体功能如下：
获取单元，用于获取多帧极片图像；多帧所述极片图像由相机在极片走带过程中采样得到；
第一确定单元，用于确定每帧所述极片图像中极片的宽度数据；
第二确定单元，用于根据所述宽度数据确定所述极片的缺陷检测结果。
所属领域的技术人员可以清楚地了解到，为了描述的方便和简洁，仅以上述各功能单元、模块的划分进行举例说明，实际应用中，可以根据需要而将上述功能分配由不同的功能单元、模块完成，即将装置的内部结构划分成不同的功能单元或模块，以完成以上描述的全部或者部分功能。实施例中的各功能单元、模块可以集成在一个处理单元中，也可以是各个单元单独物理存在，也可以两个或两个以上单元集成在一个单元中，上述集成的单元既可以采用硬件的形式实现，也可以采用软件功能单元的形式实现。另外，各功能单元、模块的具体名称也只是为了便于相互区分，并不用于限制本申请的保护范围。上述系统中单元、模块的具体工作过程，可以参考前述方法实施例中的对应过程，在此不再赘述。
在上述实施例中，对各个实施例的描述都各有侧重，某个实施例中没有详述或记载的部分，可以参见其它实施例的相关描述。
本领域普通技术人员可以意识到，结合本文中所公开的实施例描述的各示例的单元及算法步骤，能够以电子硬件或者计算机软件和电子硬件的结合来实现。这些功能究竟以硬件还是软件方式来执行，取决于技术方案的特定应用和设计约束条件。专业技术人员可以对每个特定的应用使用不同方法来实现所描述的功能，但是这种实现不应认为超出本申请的范围。
在本申请所提供的实施例中，应该理解到，所揭露的设备和方法，可以通过其它的方式实现。例如，以上所描述的终端实施例仅仅是示意性的。例如，模块或单元的划分，仅仅为一种逻辑功能划分，实际实现时可以有另外的划分方式，例如多个单元或组件可以结合或者可以集成到另一个系统，或一些特征可以忽略，或不执行。另一点，所显示或讨论的相互之间的耦合或直接耦合或通讯连接可以是通过一些接口、装置或单元的间接耦合或通讯连接，可以是电性，机械或其它的形式。
作为分离部件说明的单元可以是或者也可以不是物理上分开的，作为单元显示的部件可以是或者也可以不是物理单元，即可以位于一个地方，或者也可以分布到多个网络单元上。可以根据实际的需要选择其中的部分或者全部单元来实现本实施例方案的目的。
另外，在本申请各个实施例中的各功能单元可以集成在一个处理单元中，也可以是各个单元单独物理存在，也可以两个或两个以上单元集成在一个单元中。上述集成的单元既可以采用硬件的形式实现，也可以采用软件功能单元的形式实现。
集成的单元如果以软件功能单元的形式实现并作为独立的产品销售或使用的情况下，可以存储在一个计算机可读取存储介质中。基于这样的理解，本申请实现上述实施例方法中的全部或部分流程，也可以通过计算机程序来指令相关的硬件来完成，的计算机程序可存储于计算机可读存储介质中，该计算机程序在被处理器执行的情况下，可实现上述各个方法实施例的步骤。其中，计算机程序包括计算机程序代码，计算机程序代码可以为源代码形式、对象代码形式、可执行文件或某些中间形式等。计算机可读介质可以包括：能够携带计算机程序代码的任何实体或装置、记录介质、U盘、移动硬盘、磁碟、光盘、计算机存储器、只读存储器（Read-Only Memory，ROM）、随机存取存储器（Random Access Memory，RAM）、电载波信号、电信信号以及软件分发介质等。需要说明的是，计算机可读介质包含的内容可以根据司法管辖区内立法和专利实践的要求进行适当的增减，例如在某些司法管辖区，根据立法和专利实践，计算机可读介质不包括电载波信号和电信信号。
以上实施例仅用以说明本申请的技术方案，而非对其限制；尽管参照前述实施例对本申请进行了详细的说明，本领域的普通技术人员应当理解：其依然可以对前述各实施例所记载的技术方案进行修改，或者对其中部分技术特征进行等同替换；而这些修改或者替换，并不使相应技术方案的本质脱离本申请各实施例技术方案的精神和范围，均应包含在本申请的保护范围之内。

Claims (16)

  1. 一种极片检测方法，其特征在于，所述极片检测方法包括：
    获取多帧极片图像；多帧所述极片图像由相机在极片走带过程中采样得到；
    确定每帧所述极片图像中所述极片的宽度数据；
    根据所述宽度数据确定所述极片的缺陷检测结果。
  2. 如权利要求1所述的极片检测方法，其特征在于，所述宽度数据包括所述极片的极片宽度；
    所述根据所述宽度数据确定所述极片的缺陷检测结果，包括：
    根据相邻两帧所述极片图像中的所述极片宽度计算极片宽度差值；
    在所述极片宽度差值大于第一预设宽度阈值的情况下，得到所述极片的缺陷检测结果。
  3. 如权利要求1所述的极片检测方法，其特征在于，所述宽度数据包括所述极片上的膜片的膜片宽度；
    所述根据所述宽度数据确定所述极片的缺陷检测结果，包括：
    根据相邻两帧所述极片图像中的所述膜片宽度计算膜片宽度差值；
    在所述膜片宽度差值大于第二预设宽度阈值的情况下，得到所述极片为缺陷极片的缺陷检测结果。
  4. 如权利要求1所述的极片检测方法，其特征在于，所述极片的宽度数据包括所述极片的极片宽度和所述极片上的膜片的膜片宽度；
    所述根据所述宽度数据确定所述极片的缺陷检测结果，包括：
    根据所述极片宽度以及所述膜片宽度，计算相邻两帧所述极片图像中的极片宽度差值和相邻两帧所述极片图像中的膜片宽度差值；
    在所述极片宽度差值大于第一预设宽度阈值和/或所述膜片宽度差值大于第二预设宽度阈值的情况下，得到所述极片为缺陷极片的缺陷检测结果。
  5. 如权利要求1所述的极片检测方法，其特征在于，所述极片的宽度数据包括所述极片上的特征点到预设基准线的距离；
    所述根据所述宽度数据确定所述极片的缺陷检测结果，包括：
    根据相邻两帧所述极片图像中的所述特征点到所述预设基准线的距离，计算相邻两帧所述极片图像中的所述特征点到所述预设基准线的距离差值；
    在所述距离差值大于预设距离阈值的情况下，得到所述极片为缺陷极片的缺陷检测结果。
  6. 如权利要求5所述的极片检测方法，其特征在于，所述特征点包括所述极片的边缘特征点和/或所述极片的中心特征点。
  7. 如权利要求5所述的极片检测方法，其特征在于，所述预设基准线为所述相机在拍摄所述极片图像时生成的基准线，所述预设基准线平行于所述极片的纵向边缘。
  8. 如权利要求1至7任一项所述的极片检测方法，其特征在于，多帧所述极片图像由相机在极片走带过程中基于预设采样时间间隔采样得到。
  9. 如权利要求8所述的极片检测方法，其特征在于，所述预设采样时间间隔为所述极片在极片卷绕工序中卷绕一圈使用的时间。
  10. 如权利要求5或6所述的极片检测方法，其特征在于，在所述得到所述极片为缺陷极片的缺陷检测结果之后，还包括：
    输出极片缺陷提示信息。
  11. 如权利要求1所述的极片检测方法，其特征在于，所述宽度数据包括所述极片上的特征点到预设基准线的距离；
    所述根据所述宽度数据确定所述极片的缺陷检测结果，包括：
    根据每帧所述极片图像中所述极片上的特征点到所述预设基准线的距离，计算所述多帧极片图像中极片的所述特征点到所述预设基准线的距离的平均值和峰值；
    在所述平均值与所述峰值的差值大于第一预设差值的情况下，得到所述极片为缺陷极片的缺陷检测结果。
  12. 如权利要求11所述的极片检测方法，其特征在于，在所述得到所述极片为缺陷极片的缺陷检测结果之后，还包括：
    输出纠偏提示信息。
  13. 如权利要求1-12任一项所述的极片检测方法，其特征在于，所述极片检测方法还包括：
    获取所述极片的多帧收尾图像；多帧所述收尾图像由所述相机在相邻电芯完成所述极片的卷绕时拍摄得到；
    根据所述收尾图像确定所述极片在不同所述电芯上的收尾位置，并计算所述极片在不同所述电芯的所述收尾位置的位置差值；
    在所述位置差值大于第二预设差值的情况下，得到至少一个所述电芯上的所述极片为缺陷极片的缺陷检测结果。
  14. 一种极片检测装置，其特征在于，所述极片检测装置包括：
    获取单元，用于获取多帧极片图像；多帧所述极片图像由相机在极片走带过程中采样得到；
    第一确定单元，用于确定每帧所述极片图像中极片的宽度数据；
    第二确定单元，用于根据所述宽度数据确定所述极片的缺陷检测结果。
  15. 一种终端，包括存储器、处理器以及存储在所述存储器中并可在所述处理器上运行的计算机程序，其特征在于，所述处理器执行所述计算机程序时实现如权利要求1-13任意一项所述方法的步骤。
  16. 一种计算机可读存储介质，所述计算机可读存储介质存储有计算机程序，其特征在于，所述计算机程序被处理器执行时实现如权利要求1-13中任意一项所述方法的步骤。
PCT/CN2022/128309 2022-10-28 2022-10-28 极片检测方法、极片检测装置以及终端 WO2024087179A1 (zh)

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CN110211088A (zh) * 2019-04-16 2019-09-06 广州超音速自动化科技股份有限公司 改进式隔膜制片自动检测方法、电子设备及存储介质
CN113449883A (zh) * 2020-03-09 2021-09-28 松下知识产权经营株式会社 信息处理方法、学习完毕模型的生成方法以及装置
CN115063421A (zh) * 2022-08-16 2022-09-16 成都数联云算科技有限公司 极片区域检测方法及系统及装置及介质及缺陷检测方法
CN115205199A (zh) * 2022-05-07 2022-10-18 广州超音速自动化科技股份有限公司 一种极片卷绕对齐度检测方法、系统、设备及存储介质

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CN110211088A (zh) * 2019-04-16 2019-09-06 广州超音速自动化科技股份有限公司 改进式隔膜制片自动检测方法、电子设备及存储介质
CN113449883A (zh) * 2020-03-09 2021-09-28 松下知识产权经营株式会社 信息处理方法、学习完毕模型的生成方法以及装置
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