WO2024032002A1 - 电芯检测方法、装置、系统、计算机设备和存储介质 - Google Patents

电芯检测方法、装置、系统、计算机设备和存储介质 Download PDF

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Publication number
WO2024032002A1
WO2024032002A1 PCT/CN2023/084104 CN2023084104W WO2024032002A1 WO 2024032002 A1 WO2024032002 A1 WO 2024032002A1 CN 2023084104 W CN2023084104 W CN 2023084104W WO 2024032002 A1 WO2024032002 A1 WO 2024032002A1
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WIPO (PCT)
Prior art keywords
detection
picture
battery cell
battery core
computer
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Ceased
Application number
PCT/CN2023/084104
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English (en)
French (fr)
Inventor
屠银行
刘晓锋
宋世闯
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Contemporary Amperex Technology Co Ltd
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Contemporary Amperex Technology Co Ltd
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Filing date
Publication date
Application filed by Contemporary Amperex Technology Co Ltd filed Critical Contemporary Amperex Technology Co Ltd
Priority to EP26150573.9A priority Critical patent/EP4700974A3/en
Priority to EP23793981.4A priority patent/EP4350334B1/en
Priority to US18/503,156 priority patent/US20240077432A1/en
Publication of WO2024032002A1 publication Critical patent/WO2024032002A1/zh
Anticipated expiration legal-status Critical
Ceased legal-status Critical Current

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Classifications

    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
    • G01N21/84—Systems specially adapted for particular applications
    • G01N21/88—Investigating the presence of flaws or contamination
    • G01N21/95—Investigating the presence of flaws or contamination characterised by the material or shape of the object to be examined
    • G01N21/956—Inspecting patterns on the surface of objects
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/0002—Inspection of images, e.g. flaw detection
    • G06T7/0004—Industrial image inspection
    • H—ELECTRICITY
    • H01—ELECTRIC ELEMENTS
    • H01M—PROCESSES OR MEANS, e.g. BATTERIES, FOR THE DIRECT CONVERSION OF CHEMICAL ENERGY INTO ELECTRICAL ENERGY
    • H01M10/00—Secondary cells; Manufacture thereof
    • H01M10/05—Accumulators with non-aqueous electrolyte
    • H01M10/052—Li-accumulators
    • H01M10/0525—Rocking-chair batteries, i.e. batteries with lithium insertion or intercalation in both electrodes; Lithium-ion batteries
    • H—ELECTRICITY
    • H01—ELECTRIC ELEMENTS
    • H01M—PROCESSES OR MEANS, e.g. BATTERIES, FOR THE DIRECT CONVERSION OF CHEMICAL ENERGY INTO ELECTRICAL ENERGY
    • H01M50/00—Constructional details or processes of manufacture of the non-active parts of electrochemical cells other than fuel cells, e.g. hybrid cells
    • H01M50/50—Current conducting connections for cells or batteries
    • H01M50/543—Terminals
    • H01M50/564—Terminals characterised by their manufacturing process
    • H01M50/566—Terminals characterised by their manufacturing process by welding, soldering or brazing
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
    • G01N21/84—Systems specially adapted for particular applications
    • G01N21/88—Investigating the presence of flaws or contamination
    • G01N21/8851—Scan or image signal processing specially adapted therefor, e.g. for scan signal adjustment, for detecting different kinds of defects, for compensating for structures, markings, edges
    • G01N2021/8854—Grading and classifying of flaws
    • G01N2021/8867—Grading and classifying of flaws using sequentially two or more inspection runs, e.g. coarse and fine, or detecting then analysing
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/30—Subject of image; Context of image processing
    • G06T2207/30108—Industrial image inspection
    • G06T2207/30136—Metal
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/30—Subject of image; Context of image processing
    • G06T2207/30108—Industrial image inspection
    • G06T2207/30152—Solder
    • H—ELECTRICITY
    • H01—ELECTRIC ELEMENTS
    • H01M—PROCESSES OR MEANS, e.g. BATTERIES, FOR THE DIRECT CONVERSION OF CHEMICAL ENERGY INTO ELECTRICAL ENERGY
    • H01M10/00—Secondary cells; Manufacture thereof
    • H01M10/04—Construction or manufacture in general
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
    • Y02E60/00—Enabling technologies; Technologies with a potential or indirect contribution to GHG emissions mitigation
    • Y02E60/10—Energy storage using batteries

Definitions

  • the present application relates to the technical field of battery adapter sheet welding, and in particular to a battery core detection method, device, computer equipment, computer readable storage medium, computer program product and battery core detection system.
  • lithium-ion batteries have been widely used in electric vehicles and have become one of the main power sources for electric vehicles.
  • the lithium batteries used in electric vehicles are mainly lithium iron phosphate batteries.
  • Lithium iron phosphate batteries have the characteristics of high capacity, high output voltage, and good charge and discharge cycle performance.
  • this application provides a battery core detection method, device, computer equipment, computer-readable storage medium, computer program product and battery core detection system.
  • this application provides a battery core detection method, which is applied to control equipment, including:
  • the above-mentioned battery core detection method captures the battery core behind the welding pole lug under the shadowless light source to obtain the battery core picture, which reduces the risk of misdetection caused by the light spot effect caused by the slight lifting of the adapter piece, thereby improving the battery core electrode. Accuracy of defect detection after ear welding.
  • the cell picture includes the first cell picture taken of the cell before the identification layer is attached, and the detection object includes the solder joint detection area; determining the detection object in the battery cell picture includes: transferring according to a preset The chip model determines the reference position of the adapter piece in the first battery cell picture; the solder joint detection area is determined based on the reference position of the adapter piece.
  • the first cell picture taken of the cell before the label layer is attached is obtained to avoid the presence of the label layer. Wrinkles cause reflection and affect solder joint detection.
  • the reference position of the adapter plate in the first battery cell picture is determined to facilitate accurate and rapid acquisition of the solder joint detection area.
  • the detection result information includes solder joint detection results; performing defect detection based on the detection object, and obtaining the detection result information includes: searching and obtaining spot information in the solder joint detection area, and analyzing the spot information to obtain the solder joint detection results.
  • spot information is searched and obtained in the solder joint detection area, and the solder joint is detected based on the obtained spot information.
  • the battery cell picture includes a second battery cell picture taken of the battery core after the label layer is attached, and the detection objects include the edge of the label layer and the edge of the pole piece; determining the detection object in the battery cell picture includes: according to the preset Assume that the adapter piece model determines the reference position of the adapter piece in the second battery cell picture; determines the edge of the identification layer and the edge of the tab according to the reference position of the adapter piece.
  • the second battery cell picture taken against the battery cell with the logo layer attached is obtained, and combined with the preset adapter sheet model, the reference position of the adapter sheet in the second battery cell picture is determined, and the edge of the logo layer is accurately and quickly extracted. and pole ear edges.
  • the detection result information includes the tab coverage detection result; performing defect detection based on the detection object to obtain the detection result information includes: performing tab coverage detection based on the edge of the marking layer and the tab edge to obtain the tab coverage detection result.
  • the tab coverage detection is performed by combining the edge of the marking layer and the edge of the tab to accurately analyze whether the tab is exposed.
  • the cell image is captured by a dual camera under shadowless light source illumination.
  • this application provides a battery core detection device, including:
  • the picture acquisition module is used to obtain the battery core picture taken by the battery core behind the welding lug; the battery core picture is taken under the shadowless light source;
  • An image processing module used to determine the detection object in the battery cell image
  • the image detection module is used to detect defects based on the detection object and obtain detection result information.
  • the application provides a computer device, including a memory and one or more processors.
  • Computer-readable instructions are stored in the memory.
  • processors When the computer-readable instructions are executed by one or more processors, one or more processors A processor executes the steps of the above-mentioned battery core detection method.
  • the present application provides one or more computer storage media storing computer readable instructions. When executed by one or more processors, the computer readable instructions cause one or more processors to perform the above-mentioned battery core detection. Method steps.
  • the present application provides a computer program product.
  • the computer program When the computer program is executed by one or more processors, it causes the one or more processors to execute the steps of the above-mentioned battery core detection method.
  • this application provides a battery core detection system, including an image acquisition device and a host computer.
  • the image acquisition device is used to align the position of the edge tab of the bare battery core to capture a battery core picture, and send the battery core picture to Upper computer, upper computer Used to conduct battery core detection according to the above method.
  • Figure 1 is a schematic diagram of a scene of a cell detection method in some embodiments
  • Figure 2 is a flow chart of a cell detection method in some embodiments
  • Figure 3 is a schematic diagram of battery core pictures taken by a camera before the battery core is pasted with a logo layer in some embodiments;
  • Figure 4 is a schematic diagram of battery core pictures taken by a camera before the battery core is pasted with a logo layer in some embodiments;
  • Figure 5 is a schematic diagram of battery core pictures taken by a camera after the battery core is attached with a logo layer in some embodiments;
  • Figure 6 is a schematic diagram of a cell image taken by a camera after the cell is pasted with a logo layer in some embodiments;
  • Figure 7 is a flow chart of a cell detection method in other embodiments.
  • Figure 8 is a schematic diagram of the soldering marks in the cell pictures in some embodiments.
  • Figure 9 is a flow chart of a cell detection method in some embodiments.
  • Figure 10 is a structural block diagram of a cell detection device in some embodiments.
  • Figure 11 is an internal structure diagram of a computer device in some embodiments.
  • an embodiment means that a particular feature, structure or characteristic described in connection with the embodiment may include In at least some embodiments of the present application.
  • the appearances of this phrase in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments. Those skilled in the art understand, both explicitly and implicitly, that the embodiments described herein may be combined with other embodiments.
  • multiple refers to more than two (including two).
  • multiple groups refers to two or more groups (including two groups), and “multiple pieces” refers to It is more than two pieces (including two pieces).
  • Power batteries are the power sources that provide power for tools. They mostly use valve-sealed lead-acid batteries, open tubular lead-acid batteries and lithium iron phosphate batteries, which have the characteristics of high energy, high power and high energy density. After ultrasonic welding of the cell adapter piece and the cell tabs and the adapter piece are welded, the welding process affects the cell capacity and is an extremely important process in the battery cell production process.
  • this application provides a battery core detection method, which obtains the battery core picture taken under the shadowless light source after the battery lug is welded, and determines the detection object in the battery core picture; performs defect detection based on the detection object, Get test result information. Under the shadowless light source, the battery core behind the welding lug is photographed to obtain a picture of the battery core, thereby reducing the risk of misdetection caused by the light spot effect caused by the slight lifting of the adapter piece.
  • the battery core detection method provided by the embodiment of the present application can be applied in the application environment as shown in Figure 1.
  • the control equipment is used to control the battery core strap to transport the battery core 1 behind the welding pole lug to the detection station.
  • the detection station is equipped with a camera 2 and a light source 3 located above the battery core 1.
  • the light source 3 uses a shadowless light source.
  • the camera 2 takes a picture of the battery cell 1 under the shadowless light source, and uploads the battery cell picture to the control device.
  • the control device determines the detection object in the battery core picture, and performs defect detection based on the detection object to obtain the detection Result information.
  • the number of cameras 2 is two, and dual cameras are used to measure the battery cells respectively.
  • the camera 2 may be a CCD (Charge Coupled Device) camera or other camera.
  • the control device may include a control module and a host computer.
  • the control module controls the battery core belt to transport the battery core 1.
  • the host computer controls the camera 2 to photograph the battery core 1 to obtain a picture of the battery core, and performs image analysis to obtain detection result information.
  • the control module can be a PLC (Programmable Logic Controller, programmable logic controller), MCU (Microcontroller Unit, microcontroller unit), etc.
  • the host computer can be a notebook, desktop computer or logic controller, etc.
  • the detection station may include an inspection station before the label layer is applied and an inspection station after the identification layer is applied.
  • an upper camera, an upper light source, a lower light source and a lower camera may be arranged in sequence from top to bottom.
  • the cell 1 is located within the camera shooting range of the upper camera and the lower camera, and within the light range of the upper light source and the lower light source.
  • the upper camera and the upper light source can be located above the cell 1
  • the lower camera and the lower light source can be located above the cell.
  • the upper camera and the lower camera are dual cameras, and the upper light source and the lower light source are both shadowless light sources.
  • the battery core 1 behind the welding tab first reaches the inspection station before the marking layer, and images are collected through the upper camera and lower camera of the inspection station. After the image collection is completed, the host computer performs defect detection on the cell pictures taken before the labeling layer.
  • the control module transports the cell 1 to the labeling layer station, and controls the labeling layer station to affix the cell 1. on the marking layer, and then transport the battery core 1 with the marking layer to the inspection station after the marking layer is applied.
  • the image is collected through the upper camera and the lower camera of the inspection station.
  • the upper computer determines the position after the marking layer is attached.
  • the battery core pictures taken are used for defect detection.
  • the host computer also outputs instructions to the control module, and the control module transports the battery core 1 to the next work station.
  • PLC PLC as an example for the control module.
  • a battery core detection method is provided.
  • the method is applied to the control device.
  • the control device can be implemented through a host computer.
  • the method includes the following steps:
  • Step S110 Obtain a picture of the battery core taken behind the welding lug.
  • the shadowless light source can specifically use a planar shadowless light source.
  • the shadowless light source is a diffuse reflection light source.
  • the use of a shadowless light source can reduce the effects of the adapter plate lifting and tab wrinkles on the detection stability. It can be understood that there is no unique way to weld the tab to the adapter piece, and ultrasonic welding or other welding methods can be used.
  • the senor can be used to detect that the battery core is transported to the detection station before the marking layer is attached or the detection station after the marking layer is attached, and the upper camera and lower camera on the corresponding station are triggered to take pictures to obtain pictures of the battery cells.
  • the upper camera receives the photographing instruction
  • the upper light source emits light and the lower camera takes pictures at the same time, and obtains two sets of images, one is the upper camera and the upper light source takes the front view, and the other is the lower camera and the upper light source takes the backlight image;
  • the lower camera receives The same applies to the photo command, and a total of four sets of images are obtained.
  • the images taken by the upper camera are used to detect cracking of the tabs after welding, etc., and the images taken by the lower camera are used to detect the solder print area, etc.
  • the cell picture taken of the cell before the logo layer is attached includes the adapter piece 11, the tab 12, the welding mark 13, the area to be welded in the post-process 14 and the cell isolation.
  • Film area 15, as shown in Figure 5 and Figure 6, the battery cell picture taken after the label layer is attached includes the adapter sheet 11, the tab 12, the welding mark 13, and the area to be welded in the subsequent process 14 , cell isolation film area 15 and identification layer 16.
  • the identification layer 16 is used to set the identification information (such as a QR code, etc.) of the battery core 1.
  • the identification layer 16 can be made of blue glue.
  • the QR code of the battery core is set in the center of the blue glue.
  • the position of the blue glue needs to be ensured to prevent the code scanner at the back of the production line from failing to read the code, causing equipment downtime.
  • the host computer sends a signal to the PLC, and the PLC controls the battery core belt to transport the battery core to the next station.
  • Step S120 Determine the detection object in the battery cell picture.
  • the detection object refers to the characteristics related to defect detection in the battery cell picture. It can be understood that depending on the detection content of the battery core, the battery cell picture used for testing and the detection objects in the battery cell picture will also be different. .
  • battery core defect detection can include solder print area detection, whether the solder print completely falls on the tab, tab crack detection, tab eversion detection, marking layer offset detection, exposed tab detection, and adapter piece spacing detection. And the adapter piece is placed in reverse detection, etc.
  • the host computer detects battery core defects, it extracts relevant features from the corresponding battery core pictures as detection objects.
  • the position of the adapter sheet is extracted based on the backlight pictures taken by the upper camera and the lower camera in the inspection station after the marking layer is attached, and the edge of the marking layer and the edge of the pole piece are determined based on the position of the adapter sheet as Detect objects for exposed ear detection.
  • Step S130 Perform defect detection according to the detection object and obtain detection result information. After determining the detection object in the battery cell picture, the host computer can determine the relevant detection area based on the detection object, perform corresponding defect detection in the detection area, and obtain the detection result information.
  • the above-mentioned battery core detection method captures the battery core behind the welding pole lug under the shadowless light source to obtain the battery core picture, which reduces the risk of misdetection caused by the light spot effect caused by the slight lifting of the adapter piece, thereby improving the battery core electrode. Accuracy of defect detection after ear welding.
  • the cell picture includes a first cell picture taken of the cell before the identification layer is attached, and the detection object includes a solder joint detection area.
  • step S120 includes step S122: determining the reference position of the adapter plate in the first battery cell picture according to the preset adapter plate model, and determining the solder joint detection area according to the reference position of the adapter plate.
  • the reference position is a reference starting point used to determine the detection object.
  • the specific setting method of the reference position is not unique.
  • the center position of the adapter piece or other positions can be selected as the reference position.
  • the host computer obtains the color image captured by the lower camera of the inspection station before the battery cell is pasted with the marking layer, and converts the color image into a black and white image as the first battery cell picture.
  • the host computer establishes a coordinate system based on the center position of the adapter piece 11, grabs the edge of the adapter piece 11 to determine the adapter piece area, and establishes positioning through the adapter piece area. space to ensure the stability of the solder print detection area.
  • the adapter plate model can be established through the CogPMAligTool tool, the adapter plate model can be matched from the first battery cell picture, the position center coordinates (X, Y, R) of the adapter plate can be obtained, and the spatial coordinate system can be established using the CogFixtureTool tool.
  • the edge-grabbing tool through CCD vision CogFindLineTool, using the spatial following mode to set the edge-grabbing area, the corresponding edge can be obtained, and by setting the corresponding edge-grabbing tool properties (for example, the polarity setting is from black to white/from white to Black; edge calculation method priority, such as area center, search direction, etc.) to obtain the corresponding edge position.
  • a post-welding inspection station is added (before glue is applied), and the first battery cell picture taken before the label layer is attached is obtained to avoid the wrinkles in the label layer causing reflection and affecting the solder joints. check Test, and combine it with the preset adapter plate model to determine the reference position of the adapter plate in the first battery cell picture, so as to facilitate accurate and rapid acquisition of the solder joint detection area.
  • the detection result information includes solder joint detection results.
  • step S130 includes step S132: searching and obtaining spot information in the solder joint detection area, and obtaining the solder joint detection result according to the spot information analysis.
  • the host computer After the host computer determines the solder print inspection area, it can use the Blob operator tool to detect spot information in the area to determine whether it meets the specifications. Search and obtain spot information in the solder joint detection area, and detect the solder joints based on the obtained spot information.
  • the specific type of spot information is not unique.
  • the spot information includes the number of spots and/or the total area of spots. According to the actual situation, one or more of the number of spots and the total area of spots can be used to detect solder joints to improve the convenience of detection.
  • Figure 8 is a schematic diagram of the soldering marks in the battery cell picture.
  • the CogBlobTool tool can be used to use the template to follow the space to ensure that the Blob tool detection area is the solder joint detection area. Since the solder joints are imaged as black spots, use the Blob tool to obtain the black spots in the area (number of spots in the area, area of each spot). After knowing the number of spots, calculate and accumulate the sum of the areas of each spot through a loop statement, and use Set the solder joint area comparison to determine whether the solder joint meets the specifications.
  • CogBlobTool1 use the CogBlobTool1 operator to capture the welding mark detection area in real time
  • CogBlobTool1.Results.GetBlobs().count to obtain the number of captured spots in real time
  • For(int i 0; i ⁇ Count-1,i++)
  • the loop statement loops to obtain the area of all spots in the corresponding area.
  • CogBlobTool1.Results.GetBlobs()[i].Area the obtained area data is stored in the array. The areas are accumulated to obtain the total area to determine whether the soldering area meets the specifications.
  • the host computer will send an unqualified instruction to the PLC, and the PLC will control the cell pull tape to transport the cells without a label layer to the unqualified tank. If the solder joint inspection meets the specifications, the host computer sends a qualified instruction to the PLC, and the PLC controls the cell pull tape to transport the cells to the station where the marking layer is attached.
  • the cell image includes a second cell image taken from the cell after the identification layer is attached, and the detection object includes the edge of the identification layer and the edge of the pole piece.
  • step S120 includes step S124: determining the reference position of the adapter plate in the second battery cell picture according to the preset adapter plate model, and determining the edge of the identification layer and the edge of the tab according to the reference position of the adapter plate.
  • the host computer obtains the backlight image captured by the upper camera and the lower camera in the detection station after the marking layer is affixed as the second battery cell picture.
  • the backlight principle to perform tab coverage detection can improve edge contrast and prevent light spots caused by wrinkles and reflections on the marking layer from affecting the edge-grabbing stability.
  • the center position of the adapter piece 11 in the second battery cell picture is also used as the reference position. Then the host computer establishes a coordinate system based on the center position of the adapter piece 11 and grabs the adapter piece.
  • the edge of 11 determines the area of the adapter piece, and the left and right edges of the tab 12 and the left and right edges of the identification layer 16 are located through the adapter piece.
  • the adapter plate model can also be established through the CogPMAligTool tool, the adapter plate model can be matched from the second battery cell picture, the position center coordinates (X, Y, R) of the adapter plate can be obtained, and the spatial coordinates can be established using the CogFixtureTool tool.
  • the corresponding edge can be obtained, and by setting the corresponding edge-grabbing tool properties (for example, the polarity is set from black to white/from white to black; edge calculation method priority, such as area center, search direction, etc.), Get the corresponding edge position.
  • the polarity is set from black to white/from white to black; edge calculation method priority, such as area center, search direction, etc.
  • the second battery cell picture taken by the battery cell with the logo layer attached is obtained, and combined with the preset adapter sheet model, the reference position of the adapter sheet in the second battery cell picture is determined, and the edge of the logo layer is accurately and quickly extracted. and pole ear edges.
  • the detection result information includes the tab coverage detection result.
  • step S130 includes step S134: performing tab coverage detection based on the edge of the marking layer and the edge of the tab to obtain a tab coverage detection result.
  • the adapter sheet After locating the left and right edges of the tab and the left and right edges of the marking layer through the adapter sheet, compare the edge coordinates of the marking layer with the coordinates of the tab edge to determine whether the marking layer completely covers the tab.
  • the tab coverage detection is performed by combining the edge of the marking layer and the edge of the tab to accurately analyze whether the tab is exposed.
  • the host computer will send a qualified instruction to the PLC, and the PLC will control the cell pull strap to transport the cells to the next station. If the tabs are exposed, the host computer sends an unqualified instruction to the PLC, and the PLC controls the cell pull strap to transport the cells to the unqualified slot.
  • embodiments of the present application also provide a battery core detection device for implementing the above-mentioned battery core detection method.
  • the solution to the problem provided by this device is similar to the solution recorded in the above method. Therefore, the specific limitations in the embodiments of one or more battery detection devices provided below can be found in the above description of the battery detection method. Limitations will not be repeated here.
  • a battery core detection device including: a picture acquisition module 110, a picture processing module 120 and a picture detection module 130, wherein:
  • the picture acquisition module 110 is used to obtain a picture of the battery core photographed behind the welding electrode lug; the picture of the battery core is photographed under the illumination of a shadowless light source.
  • the image processing module 120 is used to determine the detection object in the battery cell image.
  • the picture detection module 130 is used to detect defects according to the detection object and obtain detection result information.
  • the cell picture includes a first cell picture taken of the cell before the identification layer is attached, and the detection object includes a solder joint detection area.
  • the image processing module 120 determines the reference position of the adapter plate in the first cell image based on the preset adapter plate model, and determines the solder joint detection area based on the reference position of the adapter plate.
  • the detection result information includes solder joint detection results.
  • the picture detection module 130 is in the solder joint detection area Domain search is used to obtain spot information, and solder joint detection results are obtained based on spot information analysis.
  • the cell image includes a second cell image taken from the cell after the identification layer is attached, and the detection object includes the edge of the identification layer and the edge of the pole piece.
  • the image processing module 120 determines the reference position of the adapter plate in the second cell image according to the preset adapter plate model, and determines the edge of the identification layer and the edge of the tab according to the reference position of the adapter plate.
  • the detection result information includes a tab coverage detection result.
  • the picture detection module 130 performs tab coverage detection based on the edge of the marking layer and the edge of the tab, and obtains the tab coverage detection result.
  • Each module in the above-mentioned battery core detection device can be implemented in whole or in part by software, hardware and combinations thereof.
  • Each of the above modules may be embedded in or independent of the processor of the computer device in the form of hardware, or may be stored in the memory of the computer device in the form of software, so that the processor can call and execute the operations corresponding to the above modules.
  • a computer device is provided.
  • the computer device can be a server or a terminal. Taking the server as an example, its internal structure diagram can be shown in Figure 11.
  • the computer device includes a processor, memory, and network interfaces connected through a system bus. Wherein, the processor of the computer device is used to provide computing and control capabilities.
  • the memory of the computer device includes non-volatile storage media and internal memory.
  • the non-volatile storage medium stores operating systems, computer programs and databases. This internal memory provides an environment for the execution of operating systems and computer programs in non-volatile storage media.
  • the computer device's database is used to store data.
  • the network interface of the computer device is used to communicate with external terminals through a network connection.
  • the computer program implements a battery core detection method when executed by the processor.
  • Figure 11 is only a block diagram of a partial structure related to the solution of the present application, and does not constitute a limitation on the computer equipment to which the solution of the present application is applied.
  • Specific computer equipment can May include more or fewer parts than shown, or combine certain parts, or have a different arrangement of parts.
  • a computer device including a memory and one or more processors.
  • Computer-readable instructions are stored in the memory. When executed by one or more processors, the computer-readable instructions cause one or more A processor executes the steps in the above embodiment of the battery core detection method.
  • a computer storage medium stores one or more computer readable instructions, which when executed by one or more processors, cause the one or more processors to perform implementation The steps in the above embodiment of the battery core detection method.
  • a computer program product including a computer program that, when executed by one or more processors, causes the one or more processors to perform the steps in the above embodiment of the battery core detection method.
  • a battery core detection system including an image acquisition device and a host computer.
  • the image acquisition device is used to photograph the battery core behind the welding pole lug under the shadowless light source to obtain a battery core picture, and
  • the battery cell picture is sent to the host computer, which is used to detect the battery core according to the above method.
  • the image acquisition device uses dual cameras, specifically dual CCD cameras.
  • a dual camera is installed above the battery core as the upper camera, and a dual camera is installed below the battery core as the lower camera.
  • the shadowless light source specifically adopts a plane shadowless light source.
  • the plane shadowless light source installed above the battery core serves as the upper layer light source and is installed below the battery core.
  • the plane shadowless light source is used as the lower light source.
  • the host computer can be a notebook, desktop computer, etc.
  • the dual cameras can use 12MP color area array cameras.
  • the camera's field of view in the X direction can be 260 millimeters (mm), and the pixel accuracy can be 0.06mm/pixel, so that The dual camera field of view can achieve full field of view coverage of the battery cell.
  • two cameras are used to photograph the welding area of the battery core corresponding to the tab adapter while ensuring accuracy. It can be compatible with a variety of products.
  • the camera field of view can be compatible with a maximum of 90° and a minimum of 20 °.
  • the distance between the two cameras and the battery core can be set to 193 ⁇ 25mm.
  • the distance between the two cameras can be adjusted according to the different models of the battery core.
  • Shadowless light source The distance from the battery core can be set to 40 ⁇ 10mm, and the angle is parallel to the battery core.
  • the computer program can be stored in a computer-readable storage medium.
  • the program can be stored in a computer-readable storage medium.
  • the process may include the processes of the above method embodiments.
  • the aforementioned storage media can be non-volatile storage media such as magnetic disks, optical disks, read-only memory (Read-Only Memory, ROM), or random access memory (Random Access Memory, RAM), etc.

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Abstract

一种电芯检测方法、装置、计算机设备、计算机可读存储介质、计算机程序产品和电芯检测系统，检测方法包括：获取对焊接极耳（12）后的电芯（1）拍摄得到的电芯图片；电芯图片为无影光源（3）照射下拍摄得到（S110）；确定电芯图片中的检测对象（S120 ）；根据检测对象进行缺陷检测，得到检测结果信息（S130）。对无影光源（3）照射下焊接极耳（12）后的电芯（1）拍摄得到电芯图片，减小因转接片（11）轻微翘起导致的光斑影响而导致的误检风险，从而提高电芯极耳（12）焊接后缺陷检测的准确性。

Description

电芯检测方法、装置、系统、计算机设备和存储介质
交叉引用
本申请引用于2022年8月10日递交的名称为“电芯检测方法、装置、计算机设备和介质”的第2022109575761号中国专利申请，其通过引用被全部并入本申请。
技术领域
本申请涉及电池转接片焊接技术领域，特别是涉及一种电芯检测方法、装置、计算机设备、计算机可读存储介质、计算机程序产品和电芯检测系统。
背景技术
随着新能源汽车的不断进步，锂离子电池已在电动汽车中得到广泛应用，成为电动汽车的主要动力能源之一。目前电动汽车上使用的锂电池主要以磷酸铁锂电池为主，磷酸铁锂电池具有高容量、输出电压高、较好的充放电循环性能等特点。
在电芯的生产过程中，将电芯的极耳与转接片焊接后，焊接工艺的好坏直接影响到电芯容量，是电池电芯生产流程中极为重要的一道工序。
因此，如何提高电芯极耳焊接后缺陷检测的准确性，是一个亟待解决的问题。
发明内容
鉴于上述问题，本申请提供一种电芯检测方法、装置、计算机设备、计算机可读存储介质、计算机程序产品和电芯检测系统。
第一方面，本申请提供了一种电芯检测方法，该方法应用于控制设备，包括：
获取对焊接极耳后的电芯拍摄得到的电芯图片；电芯图片在无影光源照射下拍摄得到；
确定电芯图片中的检测对象；及
根据检测对象进行缺陷检测，得到检测结果信息。
上述电芯检测方法，对无影光源照射下焊接极耳后的电芯拍摄得到电芯图片，减小因转接片轻微翘起导致的光斑影响而导致的误检风险，从而提高电芯极耳焊接后缺陷检测的准确性。
在一些实施例中，电芯图片包括对贴标识层前的电芯拍摄得到的第一电芯图片，检测对象包括焊点检测区域；确定电芯图片中的检测对象包括：根据预设转接片模型确定第一电芯图片中转接片参考位置；根据转接片参考位置确定焊点检测区域。
上述实施例中，获取对贴标识层前的电芯拍摄得到的第一电芯图片，避免标识层存在 褶皱导致反光而影响焊点检测，并结合预设转接片模型确定第一电芯图片中转接片参考位置，方便准确快速获取焊点检测区域。
在一些实施例中，检测结果信息包括焊点检测结果；根据检测对象进行缺陷检测，得到检测结果信息包括：在焊点检测区域查找获取斑点信息，根据斑点信息分析得到焊点检测结果。
上述实施例中，在焊点检测区域查找获取斑点信息，根据获取的斑点信息实现对焊点的检测。
在一些实施例中，电芯图片包括对贴标识层后的电芯拍摄得到的第二电芯图片，检测对象包括标识层边缘和极片边缘；确定电芯图片中的检测对象包括：根据预设转接片模型确定第二电芯图片中转接片参考位置；根据转接片参考位置确定标识层边缘和极耳边缘。
上述实施例中，获取对贴标识层后的电芯拍摄得到的第二电芯图片，并结合预设转接片模型确定第二电芯图片中转接片参考位置，准确快速提取标识层边缘和极耳边缘。
在一些实施例中，检测结果信息包括极耳覆盖检测结果；根据检测对象进行缺陷检测，得到检测结果信息包括：根据标识层边缘和极耳边缘进行极耳覆盖检测，得到极耳覆盖检测结果。
上述实施例中，结合标识层边缘和极耳边缘进行极耳覆盖检测，可准确分析极耳是否裸露。
在一些实施例中，电芯图片由双相机在无影光源照射下拍摄得到。
第二方面，本申请提供了一种电芯检测装置，包括：
图片获取模块，用于获取对焊接极耳后的电芯拍摄得到的电芯图片；电芯图片在无影光源照射下拍摄得到；
图片处理模块，用于确定电芯图片中的检测对象；及
图片检测模块，用于根据检测对象进行缺陷检测，得到检测结果信息。
第三方面，本申请提供了一种计算机设备，包括存储器及一个或多个处理器，存储器中储存有计算机可读指令，计算机可读指令被一个或多个处理器执行时，使得一个或多个处理器执行上述的电芯检测方法的步骤。
第四方面，本申请提供了一个或多个存储有计算机可读指令的计算机存储介质，计算机可读指令被一个或多个处理器执行时，使得一个或多个处理器执行上述的电芯检测方法的步骤。
第五方面，本申请提供了一种计算机程序产品，该计算机程序被一个或多个处理器执行时，使得一个或多个处理器执行上述的电芯检测方法的步骤。
第六方面，本申请提供了一种电芯检测系统，包括图像获取装置和上位机，图像获取装置用于对准裸电芯边缘极耳位置拍摄得到电芯图片，并将电芯图片发送至上位机，上位机 用于根据上述的方法进行电芯检测。
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。
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为一些实施例中电芯检测方法的场景示意图；
图2为一些实施例中电芯检测方法的流程图；
图3为一些实施例中电芯贴标识层前上相机拍摄的电芯图片示意图；
图4为一些实施例中电芯贴标识层前下相机拍摄的电芯图片示意图；
图5为一些实施例中电芯贴标识层后上相机拍摄的电芯图片示意图；
图6为一些实施例中电芯贴标识层后下相机拍摄的电芯图片示意图；
图7为另一些实施例中电芯检测方法的流程图；
图8为一些实施例中电芯图片中的焊印示意图；
图9为又一些实施例中电芯检测方法的流程图；
图10为一些实施例中电芯检测装置的结构框图；
图11为一些实施例中计算机设备的内部结构图。
具体实施方式
为了使本申请的目的、技术方案及优点更加清楚明白，以下结合附图及实施例，对本申请进行进一步详细说明。应当理解，此处描述的具体实施例仅仅用以解释本申请，并不用于限定本申请。
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 在本申请的至少一些实施例中。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“多个”指的是两个以上(包括两个)，同理，“多组”指的是两组以上(包括两组)，“多片”指的是两片以上(包括两片)。
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。
在本申请实施例的描述中，除非另有明确的规定和限定，技术术语“安装”“相连”“连接”“固定”等术语应做广义理解，例如，可以是固定连接，也可以是可拆卸连接，或成一体；也可以是机械连接，也可以是电连接；可以是直接相连，也可以通过中间媒介间接相连，可以是两个元件内部的连通或两个元件的相互作用关系。对于本领域的普通技术人员而言，可以根据具体情况理解上述术语在本申请实施例中的具体含义。
随着科技的发展和社会的不断进步，动力电池的应用领域不断扩展，不仅被应用于电动自行车、电动摩托车、电动汽车等电动交通工具，还被应用于军事装备和航空航天等多个领域。动力电池即为工具提供动力来源的电源，多采用阀口密封式铅酸蓄电池、敞口式管式铅酸蓄电池以及磷酸铁锂蓄电池，具有高能量、高功率和高能量密度等特点。通过电芯转接片超声波焊接，将电芯极耳与转接片焊接后，焊接工艺影响到电芯容量，是电池电芯生产流程中极为重要的一道工序。基于此，本申请提供一种电芯检测方法，获取焊接极耳后的电芯在无影光源照射下拍摄得到的电芯图片，确定电芯图片中的检测对象；根据检测对象进行缺陷检测，得到检测结果信息。对无影光源照射下焊接极耳后的电芯拍摄得到电芯图片，减小因转接片轻微翘起导致的光斑影响而导致的误检风险。
本申请实施例提供的电芯检测方法，可以应用于如图1所示的应用环境中。通过控制设备控制电芯拉带运输焊接极耳后的电芯1到检测工位，检测工位设置有位于电芯1上方的相机2和光源3，光源3采用无影光源。由相机2对无影光源照射下的电芯1拍摄得到电芯图片，并将电芯图片上传至控制设备，控制设备确定电芯图片中的检测对象，并根据检测对象进行缺陷检测，得到检测结果信息。其中，相机2的数量为两个，采用双相机分别对电芯 的两个转接片区域拍照，相机2具体可采用CCD(Charge Coupled Device，电荷耦合器件)相机或其他相机。具体地，控制设备可包括控制模块和上位机，由控制模块控制电芯拉带运输电芯1，上位机控制相机2对电芯1拍摄得到电芯图片，并进行图像分析得到检测结果信息。控制模块可以是PLC(Programmable Logic Controller，可编程逻辑控制器)、MCU(Microcontroller Unit，微控制单元)等，上位机可以是笔记本、台式电脑或逻辑控制器等。
进一步地，检测工位可包括贴标识层前检测工位和贴标识层后检测工位，两个检测工位中，由上至下可依次设置有上层相机、上层光源、下层光源和下层相机，电芯1位于上层相机和下层相机的相机拍摄范围内，以及上层光源和下层光源的光线范围内，如上层相机和上层光源可位于电芯1的上方，下层相机和下层光源可位于电芯1的下方，具体的，上层相机和下层相机均为双相机，上层光源和下层光源均为无影光源。焊接极耳后的电芯1先达到贴标识层前检测工位，通过该检测工位的上层相机和下层相机进行图像采集。图像采集完成后，上位机对贴标识层前的电芯拍摄得到的电芯图片进行缺陷检测，控制模块将电芯1输送到贴标识层工位，控制贴标识层工位对电芯1贴上标识层，再将贴上标识层的电芯1输送到贴标识层后检测工位，通过该检测工位的上层相机和下层相机进行图像采集，图像采集完成后上位机根据贴标识层后摄得到的电芯图片进行缺陷检测。此外，在缺陷检测后，上位机还输出指令给控制模块，控制模块将电芯1运输到下一工位。为便于理解，以下均以控制模块采用PLC为例进行解释说明。
在一些实施例中，如图2所示，提供了一种电芯检测方法，该方法应用于控制设备，控制设备可具体通过上位机实现，方法包括以下步骤：
步骤S110：获取对焊接极耳后的电芯拍摄得到的电芯图片。
其中，电芯图片在无影光源照射下拍摄得到。无影光源具体可采用平面无影光源，无影光源属于漫反射光源，采用无影光源可减小转接片翘起，极耳褶皱等影响检测稳定性。可以理解的是，将极耳焊接到转接片的方式并不唯一，可以是采用超声波焊接或其他焊接方式。
具体地，可通过传感器检测到电芯运输到贴标识层前检测工位或贴标识层后检测工位后，触发对应工位上的上层相机和下层相机拍照，得到电芯图片。上层相机接收到拍照指令时，上层光源发光且下层相机同时拍照，获取两组图像，一组为上层相机、上层光源正面取像，一组为下层相机、上层光源背光取像；下层相机接收拍照指令时同理，共获取四组图像。上层相机拍摄的图像用于检测焊后极耳开裂等，下层相机拍摄的图像用于检测焊印面积等。
如图3和图4所示，对贴标识层前的电芯拍摄得到的电芯图片中，包括转接片11、极耳12、焊接焊印13、后工序待焊接区域14和电芯隔离膜区域15，如图5和图6所示，对贴标识层后的电芯拍摄得到的电芯图片中，包括转接片11、极耳12、焊接焊印13、后工序待焊接区域14、电芯隔离膜区域15和标识层16。其中，标识层16用作设置电芯1的标识信息(如二维码等)，标识层16具体可采用蓝胶，蓝胶中心设置电芯的二维码，在缺陷检测中 需确保蓝胶位置，以防止产线后面工位扫码枪扫码读取失败，导致设备宕机。此外，在相机拍照完成后，上位机发送信号至PLC，PLC控制电芯拉带运输电芯到下一工位。
步骤S120：确定电芯图片中的检测对象。
检测对象即指电芯图片中与缺陷检测相关的特征，可以理解，根据电芯的检测内容不同，进行检测时所使用的电芯图片，以及电芯图片中的检测对象也会对应有所不同。例如，电芯缺陷检测可包括焊印面积检测、焊印是否完全落在极耳上、极耳开裂检测、极耳外翻检测、标识层偏移检测、露极耳检测、转接片间距检测和转接片放反检测等。上位机在进行电芯缺陷检测时，从相应电芯图片中提取相关特征作为检测对象。例如，在进行露极耳检测时，则是结合贴标识层后检测工位中上层相机和下层相机拍摄的背光图片提取转接片位置，结合转接片位置确定标识层边缘和极片边缘作为检测对象，以进行露极耳检测。
步骤S130：根据检测对象进行缺陷检测，得到检测结果信息。在确定电芯图片中的检测对象之后，上位机可结合检测对象确定相关检测区域，在检测区域内进行对应的缺陷检测，得到检测结果信息。
上述电芯检测方法，对无影光源照射下焊接极耳后的电芯拍摄得到电芯图片，减小因转接片轻微翘起导致的光斑影响而导致的误检风险，从而提高电芯极耳焊接后缺陷检测的准确性。
在一些实施例中，电芯图片包括对贴标识层前的电芯拍摄得到的第一电芯图片，检测对象包括焊点检测区域。如图7所示，步骤S120包括步骤S122：根据预设转接片模型确定第一电芯图片中转接片参考位置，根据转接片参考位置确定焊点检测区域。
其中，参考位置为用作确定检测对象的参考起始点，参考位置的具体设置方式并不唯一，可以是选择转接片的中心位置或其他位置作为参考位置。如图4所示，上位机获取电芯贴标识层前检测工位的下层相机拍摄得到的彩色图像，将彩色图像转换为黑白图像后作为第一电芯图片。以转接片11的中心位置作为参考位置为例，则上位机以转接片11的中心位置建立坐标系，抓取转接片11的边缘确定转接片区域，通过转接片区域建立定位空间，确保焊印检测区域的稳定性。
具体地，可通过CogPMAligTool工具建立转接片模型，从第一电芯图片中匹配该转接片模型，获取转接片的位置中心坐标(X,Y,R)，使用CogFixtureTool工具建立空间坐标系，通过建立通过CCD视觉CogFindLineTool抓边工具，使用空间跟随模式设置好抓边区域，可以获取到对应的边缘，通过设置好对应抓边工具属性(例如，极性设置由黑到白/由白到黑；边缘计算方式优先级，如区域中心，搜索方向等)，获取对应边缘位置。
如果透过标识层检测黑色焊印，标识层存在褶皱情况下，导致反光严重，黑色焊印抓取存在漏抓，导致误检。因此，本实施例中增加一个焊后检测工位(未贴胶前)，通过获取对贴标识层前的电芯拍摄得到的第一电芯图片，避免标识层存在褶皱导致反光而影响焊点检 测，并结合预设转接片模型确定第一电芯图片中转接片参考位置，方便准确快速获取焊点检测区域。
对应地，在一些实施例中，检测结果信息包括焊点检测结果。继续参照图7，步骤S130包括步骤S132：在焊点检测区域查找获取斑点信息，根据斑点信息分析得到焊点检测结果。
上位机在确定焊印检测区域后，可采用Blob算子工具检测区域内的斑点信息，判断是否满足规格。在焊点检测区域查找获取斑点信息，根据获取的斑点信息实现对焊点的检测。其中，斑点信息的具体类型也并不唯一，在一些实施例中，斑点信息包括斑点个数和/或斑点面积总和。可根据实际情况设置通过斑点个数和斑点面积总和中的一种或多种进行焊点检测，提高检测便利性。
图8为电芯图片中的焊印示意图。具体地，可采用CogBlobTool工具使用模板跟随空间，确保Blob工具检测区域为焊点检测区域。由于焊点成像为黑色斑点，通过Blob工具获取区域内黑色斑点(区域内斑点个数，每个斑点面积)，在知道斑点个数后，通过循环语句计算累加每个斑点的面积总和，通过与设置焊点面积对比，判定焊点是否满足规格。例如，通过CogBlobTool1算子实时抓取焊印检测区域，采用CogBlobTool1.Results.GetBlobs().count获取实时抓取到的斑点个数，采用For(int i＝0；i<Count-1,i++)循环语句循环，获取对应区域所有斑点面积，通过CogBlobTool1.Results.GetBlobs()[i].Area，将获取得到的面积数据存入数组，面积累加得到面积总和，判断焊印面积是否满足规格。
此外，在完成焊点检测后，如果焊点检测不符合规格，则上位机发送不合格指令给PLC，PLC控制电芯拉带将未贴标识层的电芯输送至不合格槽。如果焊点检测符合规格，则上位机发送合格指令给PLC，PLC控制电芯拉带将电芯输送到贴标识层的工位。
在一些实施例中，电芯图片包括对贴标识层后的电芯拍摄得到的第二电芯图片，检测对象包括标识层边缘和极片边缘。如图9所示，步骤S120包括步骤S124：根据预设转接片模型确定第二电芯图片中转接片参考位置，根据转接片参考位置确定标识层边缘和极耳边缘。
具体地，电芯贴上标识层并到达贴标识层后检测工位后，上位机获取贴标识层后检测工位中上层相机和下层相机拍摄得到的背光图像作为第二电芯图片。通过背光原理进行极耳覆盖检测，可提高边缘对比度，防止因为标识层褶皱反光导致的光斑影响，影响抓边稳定性。如图5和图6所示，同样以第二电芯图片中转接片11的中心位置作为参考位置为例，则上位机以转接片11的中心位置建立坐标系，抓取转接片11的边缘确定转接片区域，通过转接片定位到极耳12左右边缘以及标识层16左右边缘。具体地，同样可通过CogPMAligTool工具建立转接片模型，从第二电芯图片中匹配该转接片模型，获取转接片的位置中心坐标(X,Y,R)，使用CogFixtureTool工具建立空间坐标系，通过建立通过CCD视觉CogFindLineTool抓边工具，使用空间跟随模式设置好抓边区域，可以获取到对应的边缘，通过设置好对应抓边工具属性(例如，极性设置由黑到白/由白到黑；边缘计算方式优先级，如区域中心，搜索方向等)， 获取对应边缘位置。
本实施例中，获取对贴标识层后的电芯拍摄得到的第二电芯图片，并结合预设转接片模型确定第二电芯图片中转接片参考位置，准确快速提取标识层边缘和极耳边缘。
对应地，在一些实施例中，检测结果信息包括极耳覆盖检测结果。继续参照图9，步骤S130包括步骤S134：根据标识层边缘和极耳边缘进行极耳覆盖检测，得到极耳覆盖检测结果。
通过转接片定位到极耳左右边缘以及标识层左右边缘之后，将标识层边缘坐标与极耳边缘坐标进行比较，从而判断标识层是否完全覆盖极耳。结合标识层边缘和极耳边缘进行极耳覆盖检测，可准确分析极耳是否裸露。
此外，在完成极耳覆盖检测后，如果极耳不存在裸露，则上位机发送合格指令给PLC，PLC控制电芯拉带将电芯输送到下一工位。如果极耳存在裸露，则上位机发送不合格指令给PLC，PLC控制电芯拉带将电芯输送至不合格槽。
应该理解的是，虽然如上的各实施例所涉及的流程图中的各个步骤按照箭头的指示依次显示，但是这些步骤并不是必然按照箭头指示的顺序依次执行。除非本文中有明确的说明，这些步骤的执行并没有严格的顺序限制，这些步骤可以以其它的顺序执行。而且，如上的各实施例所涉及的流程图中的至少一部分步骤可以包括多个步骤或者多个阶段，这些步骤或者阶段并不必然是在同一时刻执行完成，而是可以在不同的时刻执行，这些步骤或者阶段的执行顺序也不必然是依次进行，而是可以与其它步骤或者其它步骤中的步骤或者阶段的至少一部分轮流或者交替地执行。
基于同样的发明构思，本申请实施例还提供了一种用于实现上述所涉及的电芯检测方法的电芯检测装置。该装置所提供的解决问题的实现方案与上述方法中所记载的实现方案相似，故下面所提供的一个或多个电芯检测装置实施例中的具体限定可以参见上文中对于电芯检测方法的限定，在此不再赘述。
在一些实施例中，如图10所示，提供了一种电芯检测装置，包括：图片获取模块110、图片处理模块120和图片检测模块130，其中：
图片获取模块110，用于获取对焊接极耳后的电芯拍摄得到的电芯图片；电芯图片在无影光源照射下拍摄得到。
图片处理模块120，用于确定电芯图片中的检测对象。
图片检测模块130，用于根据检测对象进行缺陷检测，得到检测结果信息。
在一些实施例中，电芯图片包括对贴标识层前的电芯拍摄得到的第一电芯图片，检测对象包括焊点检测区域。图片处理模块120根据预设转接片模型确定第一电芯图片中转接片参考位置，根据转接片参考位置确定焊点检测区域。
在一些实施例中，检测结果信息包括焊点检测结果。图片检测模块130在焊点检测区 域查找获取斑点信息，根据斑点信息分析得到焊点检测结果。
在一些实施例中，电芯图片包括对贴标识层后的电芯拍摄得到的第二电芯图片，检测对象包括标识层边缘和极片边缘。图片处理模块120根据预设转接片模型确定第二电芯图片中转接片参考位置，根据转接片参考位置确定标识层边缘和极耳边缘。
在一些实施例中，检测结果信息包括极耳覆盖检测结果。图片检测模块130根据标识层边缘和极耳边缘进行极耳覆盖检测，得到极耳覆盖检测结果。
上述电芯检测装置中的各个模块可全部或部分通过软件、硬件及其组合来实现。上述各模块可以硬件形式内嵌于或独立于计算机设备中的处理器中，也可以以软件形式存储于计算机设备中的存储器中，以便于处理器调用执行以上各个模块对应的操作。
在一些实施例中，提供了一种计算机设备，该计算机设备可以是服务器，还可以是终端，以服务器为例，其内部结构图可以如图11所示。该计算机设备包括通过系统总线连接的处理器、存储器和网络接口。其中，该计算机设备的处理器用于提供计算和控制能力。该计算机设备的存储器包括非易失性存储介质和内存储器。该非易失性存储介质存储有操作系统、计算机程序和数据库。该内存储器为非易失性存储介质中的操作系统和计算机程序的运行提供环境。该计算机设备的数据库用于存储数据。该计算机设备的网络接口用于与外部的终端通过网络连接通信。该计算机程序被处理器执行时以实现一种电芯检测方法。
本领域技术人员可以理解，图11中示出的结构，仅仅是与本申请方案相关的部分结构的框图，并不构成对本申请方案所应用于其上的计算机设备的限定，具体的计算机设备可以包括比图中所示更多或更少的部件，或者组合某些部件，或者具有不同的部件布置。
在一些实施例中，提供了一种计算机设备，包括存储器及一个或多个处理器，存储器中储存有计算机可读指令，计算机可读指令被一个或多个处理器执行时，使得一个或多个处理器执行上述电芯检测方法实施例中的步骤。
在一些实施例中，提供了一种一个或多个存储有计算机可读指令的计算机存储介质，计算机可读指令被一个或多个处理器执行时，使得所述一个或多个处理器执行实现上述电芯检测方法实施例中的步骤。
在一些实施例中，提供了一种计算机程序产品，包括计算机程序，该计算机程序被一个或多个处理器执行时，使得一个或多个处理器执行上述电芯检测方法实施例中的步骤。
在一些实施例中，还提供了一种电芯检测系统，包括图像获取装置和上位机，图像获取装置用于对无影光源照射下焊接极耳后的电芯拍摄得到电芯图片，并将电芯图片发送至上位机，上位机用于根据上述的方法进行电芯检测。
其中，图像获取装置采用双相机，具体可采用双CCD相机。在电芯上方设置双相机作为上层相机，电芯下方设置双相机作为下层相机，无影光源具体采用平面无影光源，设置在电芯上方的平面无影光源作为上层光源，设置在电芯下方的平面无影光源作为下层光源。 上位机可采用笔记本、台式电脑等。
具体地，为了提升检测效果，降低误检和漏检的的概率，双相机可采用12MP彩色面阵相机，相机X方向视野可为260毫米(mm)，像素精度可为0.06mm/pixel，使得双相机视野可做到电芯的全视野覆盖。随着电芯流入检测工位，在确保精度的情况下采用2只相机分别拍摄电芯对应极耳转接片的焊接区域，可以兼容多种产品，相机视野范围可兼容最大90°，最小20°。检测过程中，为了使得相机能够拍摄到更为清晰的电芯图片，可将双相机到电芯的间距设置为193±25mm，两个相机的距离可根据电芯的不同型号调节，无影光源与电芯间距可设置为40±10mm，角度与电芯平行。
本领域普通技术人员可以理解实现上述实施例方法中的全部或部分流程，是可以通过计算机程序来指令相关的硬件来完成，该计算机程序可存储于一计算机可读取存储介质中，该程序在执行时，可包括如上述各方法的实施例的流程。其中，前述的存储介质可为磁碟、光盘、只读存储记忆体(Read-Only Memory，ROM)等非易失性存储介质，或随机存储记忆体(Random Access Memory，RAM)等。
以上所述实施例的各技术特征可以进行任意的组合，为使描述简洁，未对上述实施例中的各个技术特征所有可能的组合都进行描述，然而，只要这些技术特征的组合不存在矛盾，都应当认为是本说明书记载的范围。
以上所述实施例仅表达了本申请的几种实施方式，其描述较为具体和详细，但并不能因此而理解为对发明专利范围的限制。应当指出的是，对于本领域的普通技术人员来说，在不脱离本申请构思的前提下，还可以做出若干变形和改进，这些都属于本申请的保护范围。因此，本申请专利的保护范围应以所附权利要求为准。

Claims (13)

  1. 一种电芯检测方法，包括：
    获取对焊接极耳后的电芯拍摄得到的电芯图片；所述电芯图片在无影光源照射下拍摄得到；
    确定所述电芯图片中的检测对象；及
    根据所述检测对象进行缺陷检测，得到检测结果信息。
  2. 根据权利要求1所述的方法，其中，所述电芯图片包括对贴标识层前的电芯拍摄得到的第一电芯图片，所述检测对象包括焊点检测区域；所述确定所述电芯图片中的检测对象包括：
    根据预设转接片模型确定所述第一电芯图片中转接片参考位置；及
    根据所述转接片参考位置确定焊点检测区域。
  3. 根据权利要求2所述的方法，其中，所述检测结果信息包括焊点检测结果；所述根据所述检测对象进行缺陷检测，得到检测结果信息包括：
    在所述焊点检测区域查找获取斑点信息，根据所述斑点信息分析得到焊点检测结果。
  4. 根据权利要求3所述的方法，其中，所述斑点信息包括斑点个数和/或斑点面积总和。
  5. 根据权利要求1所述的方法，其中，所述电芯图片包括对贴标识层后的电芯拍摄得到的第二电芯图片，所述检测对象包括标识层边缘和极片边缘；所述确定所述电芯图片中的检测对象包括：
    根据预设转接片模型确定所述第二电芯图片中转接片参考位置；及
    根据所述转接片参考位置确定标识层边缘和极耳边缘。
  6. 根据权利要求5所述的方法，其中，所述检测结果信息包括极耳覆盖检测结果；所述根据所述检测对象进行缺陷检测，得到检测结果信息包括：
    根据标识层边缘和极耳边缘进行极耳覆盖检测，得到极耳覆盖检测结果。
  7. 根据权利要求1至6任意一项所述的方法，其中，所述电芯图片由双相机在无影光源照射下拍摄得到。
  8. 一种电芯检测装置，包括：
    图片获取模块，用于获取对焊接极耳后的电芯拍摄得到的电芯图片；所述电芯图片在无影光源照射下拍摄得到；
    图片处理模块，用于确定所述电芯图片中的检测对象；及
    图片检测模块，用于根据所述检测对象进行缺陷检测，得到检测结果信息。
  9. 一种计算机设备，包括存储器及一个或多个处理器，所述存储器中储存有计算机可读指令，所述计算机可读指令被所述一个或多个处理器执行时，使得所述一个或多个处理器执 行权利要求1至7中任一项所述的方法的步骤。
  10. 一个或多个存储有计算机可读指令的计算机存储介质，所述计算机可读指令被一个或多个处理器执行时，使得所述一个或多个处理器执行权利要求1至7中任一项所述的方法的步骤。
  11. 一种计算机程序产品，包括计算机程序，该计算机程序被一个或多个处理器执行时，使得所述一个或多个处理器执行权利要求1至7中任一项所述的方法的步骤。
  12. 一种电芯检测系统，包括：图像获取装置和上位机，所述图像获取装置用于对无影光源照射下焊接极耳后的电芯拍摄得到电芯图片，并将所述电芯图片发送至所述上位机，所述上位机用于根据权利要求1-7任意一项所述的方法进行电芯检测。
  13. 根据权利要求12所述的系统，其中，所述图像获取装置包括双相机。
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