Electrode detection methods, devices and systems

Abstract

This application provides a method, apparatus, and system for detecting electrode tabs, relating to the field of battery manufacturing technology. The method includes: acquiring photodetector data of a target; wherein the target has at least one electrode tab; during the passage of the target between a light emitting device and a light receiving device, the light receiving device samples the detection light emitted by the light emitting device and detects the light intensity value of the sampled detection light; the photodetector data includes multiple light intensity detection data points; the light intensity detection data includes the light intensity value and the detection time of the light intensity value; and based on the photodetector data, performing electrode tab quality detection to obtain a quality detection result for the electrode tab. This application can improve the accuracy of electrode tab detection, reduce the occurrence of missed detections and over-detection, improve the detection precision of electrode tab detection, ensure product quality, reduce production costs, and reduce detection costs.

Description

Technical Field

[0001] This application relates to the field of battery manufacturing technology, and in particular to a method, apparatus and system for detecting electrode tabs. Background Technology

[0002] Tabs are the metallic conductors that connect the positive and negative electrodes in a battery cell. Because tabs are made of relatively soft material, they are prone to loss or folding during handling and production. Loss or folding of tabs can affect the safety of the battery cell, for example, reducing its charge / discharge performance, causing short circuits, or even fires. Therefore, it is crucial to inspect the tabs before processes such as electrode winding. Currently, tab inspection typically uses image detection technology. This involves acquiring images of the tabs and detecting missing or folded tabs based on these images. However, because the acquired tab images may contain significant noise, this process is prone to missed or over-detection, resulting in low accuracy. Summary of the Invention

[0003] In view of the above problems, this application provides a method, apparatus and system for detecting electrode tabs to improve the detection accuracy of electrode tabs.

[0004] According to a first aspect of this disclosure, a method for detecting electrodes is provided, comprising: acquiring photodetector data of a target; wherein the target has at least one electrode; during the passage of the target between a light emitting device and a light receiving device, the light receiving device samples a detection light emitted by the light emitting device and detects the light intensity value of the sampled detection light; the photodetector data includes: multiple light intensity detection data; the light intensity detection data includes: the light intensity value and the detection time; and performing electrode quality detection based on the photodetector data to obtain a quality detection result for the electrode.

[0005] In this embodiment, the tabs are detected by collecting time-series light intensity detection data. The noise of the light intensity detection data is less than that of the tab image data, which can improve the accuracy of tab detection, reduce the occurrence of missed detection and over-detection, improve the detection precision of tab detection, ensure product quality and reduce production costs.

[0006] In some embodiments, the electrode quality detection includes: electrode quantity detection; the light intensity value includes: the light intensity value of the detection light that is blocked or not blocked by the electrode; the electrode quality detection based on the light detection data includes: detecting the electrode quantity based on the light detection data to obtain the electrode detection quantity; obtaining a preset electrode quantity for the detection target; and determining whether the electrode quantity is correct based on the electrode detection quantity and the preset electrode quantity.

[0007] In this embodiment, by collecting time-series light intensity detection data to detect the number of tabs, the outline information of the tabs can be obtained based on the light intensity detection data, which can improve the accuracy of tab number detection and reduce the occurrence of missed detections and over-detection. By setting a preset number of tabs, it can adapt to the detection of the number of various tabs, reduce the parameter adjustment cost, and improve the detection efficiency.

[0008] In some embodiments, the step of detecting the number of electrodes based on the optical detection data to obtain the number of electrodes detected includes: determining a regional light intensity threshold based on the light intensity value of the light intensity detection data in the optical detection data; and determining the number of electrodes detected based on the optical detection data and the regional light intensity threshold.

[0009] In this embodiment, the light intensity threshold of the electrode area is determined by the light intensity value of the light intensity detection data. Based on the light intensity detection data and the regional light intensity threshold, the accurate number of electrodes can be obtained, which can improve the accuracy of electrode number detection.

[0010] In some embodiments, determining the number of electrode detections based on the optical detection data and the regional light intensity threshold includes: generating a light intensity fitting curve based on the light intensity detection data in the optical detection data; determining two regional discrimination points of the electrode in the light intensity fitting curve according to the regional light intensity threshold; wherein the light intensity value of the regional discrimination point is the same as the regional light intensity threshold; and determining the number of electrode detections based on the total number of regional discrimination points of all electrodes.

[0011] In this embodiment, two regional discrimination points of the electrode are determined based on the light intensity fitting curve and the regional light intensity threshold. The number of electrode detections is determined based on the total number of regional discrimination points of all electrodes. The light intensity fitting curve can visualize the outline of the electrode, which can improve the accuracy of electrode number detection and reduce the occurrence of missed detections and over-detection.

[0012] In some embodiments, determining a region light intensity threshold based on the light intensity values ​​of the light intensity detection data in the light detection data includes: acquiring all light intensity detection data in the light detection data; calculating the average light intensity value of all light intensity detection data; and using the average light intensity value as the region light intensity threshold.

[0013] In this embodiment, by using the average light intensity value of all light intensity detection data as the regional light intensity threshold, the electrode region can be determined more accurately based on the light intensity fitting curve, which can improve the accuracy of electrode number detection.

[0014] In some embodiments, determining whether the number of electrodes is correct based on the number of electrodes detected and the preset number of electrodes includes: determining that the number of electrodes is correct when the number of electrodes detected is equal to the preset number of electrodes; and determining that the number of electrodes is abnormal when the number of electrodes detected is not equal to the preset number of electrodes.

[0015] In this embodiment, the correctness of the electrode quantity is determined based on the number of electrode detected and the preset number of electrode. Different preset numbers of electrode can be used for different models of electrode, which can adapt to the quantity detection of multiple models of electrode, reduce the parameter adjustment cost, and improve the detection efficiency.

[0016] In some embodiments, the electrode quality detection includes: fold detection; the electrode quality detection based on the optical detection data includes: obtaining a region detection dataset of the electrode based on two region discrimination points of the electrode and the light intensity fitting curve in the optical detection data; and performing the fold detection based on the region detection dataset.

[0017] In this embodiment, a region detection dataset for the electrode is obtained based on two region discrimination points and a light intensity fitting curve. The outline information of the electrode can be obtained based on the region detection dataset. Fold detection can be performed based on the outline information of each electrode, which can improve the accuracy of fold detection and reduce the occurrence of missed detections and over-detection.

[0018] In some embodiments, obtaining the region detection dataset of the electrode based on the two region discrimination points of the electrode and the light intensity fitting curve in the light detection data includes: taking the two region discrimination points as starting points and respectively following the upward direction of the light intensity fitting curve, performing a search process on the light intensity fitting curve to obtain the two region boundary points of the electrode; wherein, during the search process, when the difference between the light intensity value of a light intensity detection data and a preset maximum light intensity value is determined to be less than a preset light intensity difference threshold, this light intensity detection data is taken as the region boundary point; in the light detection data, the light intensity detection data whose detection time is within a first time interval is taken as the region light intensity detection data; wherein, the first time interval includes: the time interval between the detection times of the two region boundary points; generating the region detection dataset, wherein the region detection dataset includes: the region light intensity detection data and the two region boundary points.

[0019] In this embodiment, by performing a search process on the light intensity fitting curve based on the regional discrimination point, a regional detection dataset is obtained, which can obtain the light intensity detection data corresponding to the tab region for fold detection, thereby improving the accuracy of fold detection.

[0020] In some embodiments, performing the flip detection based on the region detection dataset includes: generating a corresponding region shading dataset based on the region detection dataset; wherein, the region shading dataset includes: region shading amount data corresponding to each data in the region detection dataset; the region shading amount data includes: shading amount, and the detection time corresponding to the shading amount; and performing the flip detection based on the region shading dataset.

[0021] In this embodiment, the amount of light blocking is obtained by light intensity detection data, and the shape contour information of each tab can be determined based on the amount of light blocking data for folding detection, which can improve the accuracy of folding detection.

[0022] In some embodiments, the maximum light intensity value of a region is determined from the light intensity values ​​of all data in the region detection dataset; the amount of shading is determined based on the light intensity values ​​of the data in the region detection dataset and the maximum light intensity value of the region.

[0023] In this embodiment, the amount of shading is obtained based on the maximum light intensity of the region and the light intensity values ​​of all data in the region detection dataset. The shape and outline of the electrode can be determined more accurately based on the amount of shading data.

[0024] In some embodiments, the fold detection includes: width direction detection; the fold detection based on the regional shading dataset includes: determining shading amount change information for each of the regional shading amount data in the regional shading dataset; determining two waist shading amount data for the electrode tab based on the shading amount change information in the regional shading dataset; determining two shading amount data corresponding to the two regional boundary points in the regional shading dataset as two boundary shading amount data; and performing the width direction detection based on the two waist shading amount data and the two boundary shading amount data.

[0025] In this embodiment, by using waist shading data and boundary shading data for width direction detection, the width direction detection can be performed based on the shape contour information of the tab, which can improve the accuracy of detection and reduce the occurrence of missed detections and over-detection.

[0026] In some embodiments, the shading amount change information includes: shading amount change value; determining the shading amount change information of each of the shading amount data includes: calculating the shading amount difference between each of the shading amount data of the shading amount of the shading amount of the shading amount of the adjacent shading amount data of the shading amount data of the shading amount of the shading amount of the shading amount of the shading amount of the shading amount data ...

[0027] In this embodiment, the shading difference can be used to accurately determine the waist shading data based on the shape and contour information of the tab, which can improve the accuracy of width direction detection.

[0028] In some embodiments, determining the two waist shading data of the electrode ear in the regional shading dataset based on the shading amount change information includes: determining two regional shading data in the regional shading dataset based on the maximum and minimum values ​​of the shading amount change value, as two waist shading data.

[0029] In this embodiment, the waist shading data is determined by using the extreme values ​​of the shading difference, which makes the determination of waist shading data more accurate.

[0030] In some embodiments, the width direction detection based on the two waist shading data and the two boundary shading data includes: determining a first spacing based on the two waist shading data; determining a second spacing based on the two boundary shading data; and performing the width direction detection based on the ratio of the first spacing to the second spacing.

[0031] In this embodiment, the first and second spacings determined based on the two waist shading data and the two boundary shading data can correspond to the waist width and bottom width of the tab, enabling width direction detection based on the tab's outline information, which can improve detection accuracy.

[0032] In some embodiments, the width direction detection based on the ratio of the first spacing and the second spacing includes: determining that the tab width is abnormal when the ratio is less than a preset ratio threshold; and determining that the tab width is normal when the ratio is greater than or equal to the ratio threshold.

[0033] In this embodiment, a preset ratio threshold is used for width direction detection. The ratio threshold and other electrode detection parameters can be set, and different detection parameters can be used for electrodes of different shapes and types. This can adapt to the width direction detection of various electrodes, reduce parameter tuning costs, and improve detection efficiency.

[0034] In some embodiments, determining the first spacing based on the two waist shading data includes: adding 2 to the number of shading data points in the region where the detection time falls within a second time interval, and using this as the first spacing; wherein the second time interval includes the time interval between the detection times of the two waist shading data points.

[0035] In this embodiment, the first spacing is determined based on the number of regional shading data points located between the detection times of the two waist shading data points and the two waist shading data points. This can accurately determine the waist width information of the tab and improve the accuracy of width direction detection.

[0036] In some embodiments, determining the second spacing based on the two boundary shading data includes: adding 2 to the number of shading data points in the region where the detection time falls within the third time interval, and using this as the second spacing; wherein the third time interval includes the time interval between the detection times of the two boundary shading data points.

[0037] In this embodiment, the second spacing is determined based on the number of regional shading data between the detection times of the two boundary shading data and the two boundary shading data. This can accurately determine the bottom width information of the tab and improve the accuracy of width direction detection.

[0038] In some embodiments, the folding detection includes: height direction detection; the folding detection based on the regional shading dataset includes: determining the theoretical shading amount and shading amount threshold of the tab; determining the top shading dataset based on two boundary shading amount data and two waist shading amount data in the regional shading dataset; and performing the height direction detection based on the theoretical shading amount and the shading amount threshold, and based on the top shading dataset.

[0039] In this embodiment, by using theoretical shading amount, shading amount threshold, and top shading dataset for height direction detection, height direction detection can be performed based on the shape contour information of the electrode, which can improve the accuracy of height direction detection and reduce the occurrence of missed detections and over-detection.

[0040] In some embodiments, determining the theoretical shading amount and shading amount threshold of the electrode includes: determining the theoretical shading amount using a height shading fitting formula and based on the height information of the electrode; and determining the shading amount threshold based on the theoretical shading amount and a preset shading deviation threshold.

[0041] In this embodiment, the theoretical shading amount is determined by using a height shading fitting formula, which enables the determination of the theoretical shading amount for various electrodes, adapts to the height direction detection of various electrodes, reduces parameter adjustment costs, and improves detection efficiency.

[0042] In some embodiments, experimental data on the height and shading amount of various electrodes are obtained; the experimental data on the height and shading amount are fitted to obtain the shading fitting formula.

[0043] In this embodiment, the experimental data is fitted to obtain a height shading fitting formula, which improves the accuracy of the theoretical shading amount and the accuracy of height direction detection.

[0044] In some embodiments, determining the top shading dataset based on the two boundary shading data and the two waist shading data includes: determining two regional shading data in the regional shading dataset based on the two boundary shading data and the two waist shading data, as two top shading boundary data; using the regional shading data whose detection time falls within the fourth time interval as the top shading data; wherein the fourth time interval includes the time interval between the acquisition data of the two top shading boundary data; generating the top shading dataset; wherein the top shading dataset includes the top shading data and the top shading boundary data.

[0045] In this embodiment, the top shading dataset is determined based on the boundary shading data and the waist shading data. This allows for the determination of the top width region of the tab and the detection of the height direction, thereby improving the accuracy of the height direction detection.

[0046] In some embodiments, the ratio between the number of shading data in the first region and the number of shading data in the second region is a preset ratio; wherein, the number of shading data in the first region is the number of shading data in the region whose detection time is within the fifth time interval, the fifth time interval including the interval between the detection time of the top shading boundary data and the detection time of the adjacent waist shading data; the number of shading data in the second region is the number of shading data in the region whose detection time is within the sixth time interval, the sixth time interval including the interval between the detection time of this waist shading data and the detection time of the adjacent boundary shading data.

[0047] In this embodiment, a top shading dataset can be determined for various electrodes by using a preset ratio, which is applicable to various electrodes, reduces parameter tuning costs, and improves detection efficiency.

[0048] In some embodiments, the height orientation detection based on the theoretical shading amount and the shading amount threshold, and based on the top shading dataset, includes: determining an ear height anomaly when the shading amount of at least one data point in the top shading dataset is less than the shading threshold.

[0049] In this embodiment, the comparison between the shading amount of the top shading dataset and the shading threshold is used to determine whether the electrode height is abnormal, which can improve the accuracy of height direction detection.

[0050] In some embodiments, the maximum shading amount is determined from the shading amounts of all data in the top shading dataset; if the difference between the theoretical shading amount and the maximum shading amount is greater than a preset difference threshold, the height shading fitting formula is determined to be abnormal.

[0051] In this embodiment, by detecting the height shading fitting formula, errors in the calculated theoretical shading amount can be avoided, thereby improving the accuracy of height direction detection.

[0052] In some embodiments, a display interface including a first area is presented; in response to a detection instruction triggered based on a detection control in the first area, the photodetector data is acquired; in response to the detection instruction, the second area is displayed in the display interface, and detection result display processing is performed in the second area according to the quality detection result.

[0053] In this embodiment, a detection control is provided to facilitate the user's control over the quality inspection of the electrode; by displaying the quality inspection results in the second area of ​​the display interface, the user can intuitively obtain the quality inspection results through the display interface, enabling staff to quickly obtain the quality inspection results and take effective measures in a timely manner to ensure production safety.

[0054] In some embodiments, the process of displaying the detection result in the second area based on the quality detection result includes: when the quality detection result is abnormal, determining abnormality prompt color information and / or abnormality prompt information; wherein, the abnormality prompt information includes: abnormal detection category information, or abnormal detection category information and abnormal electrode information; displaying the abnormality prompt icon and / or abnormality display area in the second area; controlling the color of the prompt icon located in the second area based on the abnormality prompt color information, and / or displaying the abnormality prompt information in the abnormality display area.

[0055] In this embodiment, different anomalies can be indicated by color-coded alerts and specific messages. This allows staff to quickly identify anomalies and take timely and effective measures, thus preventing production accidents.

[0056] In some embodiments, when the quality inspection result is abnormal, an abnormality prompt message and / or alarm message are sent to the target device; wherein, the target device is used to process the inspection target.

[0057] In this embodiment, when an anomaly occurs, sending an anomaly alert or alarm message to the target device used to process the detection target can enable staff to take timely and effective measures to prevent production accidents from occurring.

[0058] In some embodiments, the detection light includes: linear detection light and strip detection light; the time interval between two adjacent detection times is the same.

[0059] In this embodiment, using linear detection light rays, strip detection light rays, and making the time intervals between detection times the same allows the light intensity detection data to more accurately correspond to the shape contour of the tab, thereby improving the accuracy of tab quality detection.

[0060] According to a second aspect of this disclosure, a tab detection device is provided, comprising: a memory; and a processor coupled to the memory, the processor being configured to perform the tab detection method as described above based on instructions stored in the memory.

[0061] According to a third aspect of this disclosure, a tab detection system is provided, comprising: a light emitting device, a light receiving device, and a tab detection device as described above; wherein, during the process of a detection target passing between the light emitting device and the light receiving device, the light receiving device samples and detects the detection light emitted by the light emitting device to generate photodetection data; and the tab detection device performs tab quality detection based on the photodetection data.

[0062] In this embodiment, the cost of devices such as light emitting devices and light receiving devices is low, and the storage amount of light intensity detection data is less than that of image data, which can reduce detection costs; the data noise of light intensity detection data is less than that of electrode image data, which can improve the accuracy of electrode detection and reduce the occurrence of missed detections and over-detection.

[0063] In some embodiments, the detection light includes: a linear detection light and a strip detection light; when the detection target passes between the light emitting device and the light receiving device, the center line of the electrode is parallel to the linear detection light and the strip detection light.

[0064] In this embodiment, using linear detection rays, strip detection rays, and aligning the centerline of the electrode with the detection rays allows the light intensity detection data to more accurately correspond to the shape contour of the electrode, thereby improving the accuracy of electrode quality detection.

[0065] In some embodiments, the system further includes: a data acquisition device and a message server; the data acquisition device receives optical detection data sent by the optical receiving device; the message server obtains the optical detection data from the data acquisition device and sends it to the electrode detection device.

[0066] In some embodiments, the data acquisition device controls the light receiving device to start or stop sampling the detection light and detect the light intensity value of the sampled detection light according to the start or stop signal sent by the target device, wherein the target device is used to process the detection target.

[0067] In this embodiment, the data acquisition device controls the optical receiving device to sample and detect based on the start or stop signal sent by the target device. It can trigger the optical receiving device to sample and detect based on the working state of the target device, and can be linked with the target device to ensure that the quality detection and the processing of the target by the target device are synchronized, thereby ensuring product quality.

[0068] The above description is only an overview of the technical solution of this application. In order to better understand the technical means of this application and to implement it in accordance with the contents of the specification, and to make the above and other objects, features and advantages of this application more obvious and understandable, the following are specific embodiments of this application. Attached Figure Description

[0069] To more clearly illustrate the technical solutions of the embodiments of this application, the accompanying drawings used in the embodiments of this application will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on the accompanying drawings without creative effort.

[0070] Figure 1 This is a schematic flowchart of some embodiments of the electrode detection method disclosed herein;

[0071] Figure 2 This is a schematic diagram of the process for detecting the number of electrodes in some embodiments of the electrode detection method disclosed herein;

[0072] Figure 3 This is a flowchart illustrating the process of determining the number of electrodes to be detected in some embodiments of the electrode detection method of this disclosure;

[0073] Figure 4A This is a schematic diagram illustrating the determination of the number of tabs to be detected based on optical detection data. Figure 4B A schematic diagram showing the light intensity fitting curve corresponding to a single electrode and the two regional discrimination points;

[0074] Figure 5 This is a schematic diagram of the process for performing folding detection in some embodiments of the electrode detection method of this disclosure;

[0075] Figure 6 This is a schematic diagram of the electrode contour fitting curve of the electrode detection method of this disclosure;

[0076] Figure 7 This is a schematic flowchart illustrating the width direction detection process in some embodiments of the tab detection method disclosed herein;

[0077] Figure 8A A schematic diagram showing the change in shading amount in the region of a normal electrode;

[0078] Figure 8B This is a schematic diagram showing the changes in shading amount in the region of the irregular electrode tab;

[0079] Figure 9 This is a schematic diagram of the process for height direction detection in some embodiments of the electrode detection method of this disclosure;

[0080] Figure 10 This is a schematic diagram showing the fitting of the electrode height and the amount of light blocking in the electrode detection method of this disclosure;

[0081] Figure 11 This is a schematic diagram of the detection process of the electrode detection method disclosed herein;

[0082] Figure 12 This is a schematic diagram showing the outlines of the cathode and anode electrodes in the electrode detection method of this disclosure;

[0083] Figure 13 This is a schematic diagram of the display interface in some embodiments of the electrode detection method of this disclosure;

[0084] Figure 14 The diagram shows a module schematic of some other embodiments of the tab detection device of this disclosure;

[0085] Figure 15A The diagram shows some modules of the tab detection system disclosed herein. Figure 15B The diagram shows a module schematic of some other embodiments of the tab detection system disclosed herein. Detailed Implementation

[0086] The embodiments of the technical solution of this application will now be described in detail with reference to the accompanying drawings. These embodiments are only used to more clearly illustrate the technical solution of this application and are therefore merely examples, and should not be used to limit the scope of protection of this application.

[0087] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application pertains; the terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the application; the terms “comprising” and “having”, and any variations thereof, in the specification, claims, and foregoing description of the drawings are intended to cover non-exclusive inclusion.

[0088] In the description of the embodiments of this application, technical terms such as "first" and "second" are used only to distinguish different objects and should not be construed as indicating or implying relative importance or implicitly specifying the number, specific order, or primary and secondary relationship of the indicated technical features. In the description of the embodiments of this application, "multiple" means two or more, unless otherwise explicitly defined.

[0089] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of this application. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0090] In the description of the embodiments in this application, the term "and / or" is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, and B existing alone. Additionally, the character " / " in this document generally indicates that the preceding and following related objects have an "or" relationship.

[0091] In the description of the embodiments of this application, the term "multiple" refers to two or more (including two), similarly, "multiple sets" refers to two or more (including two sets), and "multiple pieces" refers to two or more (including two pieces).

[0092] In the description of the embodiments of this application, the technical terms "center," "longitudinal," "lateral," "length," "width," "thickness," "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "top," "bottom," "inner," "outer," "clockwise," "counterclockwise," "axial," "radial," and "circumferential" indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are only for the convenience of describing the embodiments of this application and simplifying the description, and are not intended to indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on the embodiments of this application.

[0093] In the description of the embodiments of this application, unless otherwise expressly specified and limited, technical terms such as "installation," "connection," "joining," and "fixing" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral part; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; they can refer to the internal communication of two components or the interaction between two components. For those skilled in the art, the specific meaning of the above terms in the embodiments of this application can be understood according to the specific circumstances.

[0094] In the related technologies known to the inventor, the winding process involves winding the cathode and anode electrodes and the separator together using a winding machine to form a bare cell, which is one of the important processes in the lithium battery production assembly stage. Since tabs are prone to loss or folding during handling and production, inspecting for missing or folded tabs before the winding process can improve the finished cell yield and reduce assembly and rework costs.

[0095] Currently, electrode tab detection typically employs image detection technology, which involves acquiring electrode tab images and performing checks such as folding. However, due to the potential for significant noise in the acquired electrode tab images, issues such as missed detections and over-detection (e.g., classifying qualified electrodes as unqualified) occur during detection, resulting in low accuracy. Furthermore, image detection is costly. Therefore, this disclosure provides a technical solution for electrode tab detection to address the aforementioned technical problems.

[0096] Figure 1 This is a flowchart illustrating some embodiments of the tab detection method disclosed herein, such as... Figure 1 As shown:

[0097] In step S101, optical detection data of the target is acquired.

[0098] In some embodiments, the detection target may be a cathode electrode, an anode electrode, etc., and the edges of the cathode electrode, anode electrode, etc., are provided with at least one tab. During the process of the detection target passing between the light emitting device and the light receiving device, the light emitting device emits detection light rays, the detection target may block the detection light rays during its movement, and the light receiving device samples and detects the detection light rays to obtain the light intensity value and detection time of the sampled detection light rays.

[0099] The light emitting device and the light receiving device can be various types of devices. For example, a through-beam photoelectric sensor is a non-contact sensor based on the photoelectric conversion principle, consisting of a transmitter and a receiver. The light emitting device and the light receiving device are respectively the transmitter and receiver of the through-beam photoelectric sensor. Through-beam photoelectric sensors can be various types of sensors.

[0100] When testing the electrode tabs, the cathode and anode electrodes pass between the light emitting device and the light receiving device (which can be the transmitter and receiver of a through-beam photoelectric sensor). As the cathode and anode electrodes pass between the light emitting and receiving devices, the light generating device emits detection light, which is then blocked by the cathode and anode electrodes.

[0101] Tabs are provided on the sides of cathode and anode electrodes, with gaps between them. As the cathode and anode electrodes pass between the light emitting and receiving devices, the tabs may or may not block the detection light. The light receiving device samples the received detection light and detects its intensity. The sampling period can be set, for example, to 20 or 30 milliseconds. When the tabs do not block the detection light, the light intensity value sampled and detected by the light receiving device can be 1500; when the tabs block the detection light, the light intensity value sampled and detected by the light receiving device will decrease.

[0102] Optical detection data is generated based on the detection results from the optical receiving device. This data includes multiple light intensity detection data points, which contain the light intensity value and the detection time (sampling time). The time intervals between two adjacent detection times can be identical, partially identical, or completely different.

[0103] The detection light can be linear, strip-shaped, or other types, and can be laser light, etc. To achieve accurate detection, the centerline of the cathode or anode electrode is parallel to the linear or strip-shaped detection light as it passes between the light emitting and receiving devices. Using linear or strip-shaped detection light, and ensuring the centerline of the electrode is parallel to the detection light, allows the light intensity detection data to more accurately correspond to the shape and contour of the electrode, thus improving the accuracy of electrode quality detection.

[0104] In step S102, electrode quality is detected based on optical detection data to obtain the electrode quality detection results. Electrode quality detection may include various detection methods such as electrode quantity detection, folding detection, and electrode edge defect detection.

[0105] The electrode detection method in the above embodiments detects electrodes by collecting time-series light intensity detection data. Based on the light intensity detection data, the outline information of the electrodes can be obtained. The noise of the light intensity detection data is less than that of the electrode image data, which can improve the accuracy of electrode detection, reduce the occurrence of missed detection and over-detection, improve the detection precision of electrode detection, ensure the quality of products such as battery cells, and reduce assembly and rework costs. The storage capacity of image data is usually large, while the storage capacity of light intensity detection data is smaller than that of image data. The cost of equipment such as light emitting devices and light receiving devices is lower, which can reduce detection costs.

[0106] In some embodiments, during the winding process, the tab quality of both the cathode and anode electrodes can be simultaneously inspected, reducing assembly and rework costs. The tab detection method disclosed herein can be applied to a tab detection device, which can be various electronic devices. These devices can be terminal devices with computer program execution capabilities or the aforementioned servers. The terminal device can be a personal computer, tablet computer, mobile internet device, etc. A server refers to a device that provides computing services via a network, and can be an x86 server or a non-x86 server, etc.

[0107] Electrode quality inspection can include various tests, such as electrode quantity inspection and folding inspection. Folding inspection includes inspection in the height direction and width direction. Figure 2 This is a schematic flowchart illustrating the detection of the number of electrodes in some embodiments of the electrode detection method disclosed herein. The light intensity values ​​in the optical detection data include light intensity values ​​such as the light intensity values ​​of the detection light rays that are blocked or not blocked by the electrodes, for example... Figure 2 As shown:

[0108] In step S201, the number of electrodes is detected based on the optical detection data to obtain the number of electrodes detected.

[0109] In step S202, the preset number of electrodes of the detection target is obtained.

[0110] In some embodiments, the preset number of tabs can be set based on the tab data of the cathode and anode sheets under qualified conditions. For example, the number of die-cut tabs of the cathode and anode sheets after the die-cutting process can be queried as the preset number of tabs. For each model and batch of cathode and anode sheets, the preset number of tabs only needs to be queried once before tab quality inspection.

[0111] In step S203, the correctness of the number of electrodes is determined based on the number of electrodes detected and the preset number of electrodes.

[0112] By collecting time-series light intensity detection data for electrode quantity detection, the accuracy of electrode quantity detection can be improved, and the occurrence of missed detection and over-detection can be reduced. By setting parameters such as the preset number of electrodes, it is possible to adapt to the quantity detection of various electrodes, reduce parameter adjustment costs, and improve detection efficiency.

[0113] In some embodiments, if the number of detected electrodes is equal to the preset number of electrodes, the number of electrodes is determined to be correct; if the number of detected electrodes is not equal to the preset number of electrodes, the number of electrodes is determined to be abnormal. For example, the difference between the preset number of electrodes and the number of detected electrodes is calculated. If the difference is 0, the number of electrodes is determined to be correct; if the difference is not 0, the number of electrodes is determined to be abnormal, and the number of abnormal electrodes is the absolute value of the difference.

[0114] Figure 3 This is a flowchart illustrating the process of determining the number of electrodes to be detected in some embodiments of the electrode detection method of this disclosure, such as... Figure 3 As shown:

[0115] In step S301, the regional light intensity threshold is determined based on the light intensity value of the light intensity detection data in the light detection data.

[0116] In step S302, the number of electrodes to be detected is determined based on the optical detection data and the regional light intensity threshold.

[0117] The light intensity threshold of the electrode area is determined by the light intensity value of the light intensity detection data. Based on the light intensity detection data and the regional light intensity threshold, the accurate number of electrodes can be obtained, which can improve the accuracy of electrode number detection.

[0118] In some embodiments, the regional light intensity threshold can be determined using various methods. One method involves acquiring all light intensity detection data from the light detection data set, calculating the average light intensity value of all the light intensity detection data, and using this average light intensity value as the regional light intensity threshold.

[0119] Based on the light intensity detection data in the optical detection data, a light intensity fitting curve is generated. According to the regional light intensity threshold, two regional discrimination points for the electrode are determined in the light intensity fitting curve, and the light intensity value of the regional discrimination point is the same as the regional light intensity threshold. The number of electrode detections is determined based on the total number of regional discrimination points for all electrodes. The light intensity fitting curve can visually display the shape contour of the electrode, which can improve the accuracy of electrode number detection and reduce the occurrence of missed detections and over-detection.

[0120] like Figure 4A As shown, all light intensity detection data in the light detection data are obtained. Based on the light intensity values ​​and detection times of all light intensity detection data, a light intensity fitting curve 040 is generated. The light intensity fitting curve 040 includes the contour lines of multiple electrodes, wherein... Figure 4A The horizontal axis represents the detection time (in milliseconds), and the vertical axis represents the light intensity value. Various methods can be used to fit and generate a light intensity fitting curve based on all the light intensity detection data, such as using analytical expressions to approximate discrete data or the least squares method.

[0121] The average light intensity of all light intensity detection data is calculated and used as the regional light intensity threshold. Based on the regional light intensity threshold, a regional light intensity threshold dividing line 041 is generated. The light intensity value (vertical axis) of each point in the regional light intensity threshold dividing line 041 is the regional light intensity threshold. Based on the intersection of the light intensity threshold dividing line 041 and the light intensity fitting curve 040, two regional discrimination points of the electrode are determined in the light intensity fitting curve 04. The light intensity value of the regional discrimination points is the same as the regional light intensity threshold.

[0122] For example, with Figure 4A The shape of the light intensity fitting curve for one of the electrodes corresponding to the dashed box in the figure can be... Figure 4B The shape of the light intensity fitting curve 042 in the image. Figure 4B In the diagram, the light intensity fitting curve 042 corresponding to one electrode intersects the light intensity threshold dividing line 041 at two points. These two intersections are two region discrimination points, which can determine the region where the electrode is located. Each electrode region in the light intensity threshold dividing line 041 and the light intensity fitting curve 040 has two intersections (region discrimination points). Obtaining the total number of intersections between the light intensity threshold dividing line 041 and the light intensity fitting curve 040 yields the total number of region discrimination points for all electrodes. Dividing this total number by 2 gives the number of electrode detections. Based on the number of electrode detections and the preset number of electrodes, it is determined whether the number of electrodes is correct.

[0123] By generating a light intensity fitting curve from light intensity detection data, and determining two regional discrimination points of the electrode in the light intensity fitting curve based on the regional light intensity threshold, the region where the electrode is located and the number of electrode detections can be determined. The detection efficiency is high, the number of electrode detections can be accurately determined, and the accuracy of electrode quantity detection is improved.

[0124] Figure 5 This is a schematic diagram of the folding detection process in some embodiments of the tab detection method of this disclosure, such as... Figure 5 As shown:

[0125] In step S401, based on the two region discrimination points of the electrode and the light intensity fitting curve, the region detection dataset of the electrode is obtained from the light detection data.

[0126] In step S402, fold detection is performed based on the region detection dataset.

[0127] The region detection dataset of the electrode is obtained based on two region discrimination points and light intensity fitting curves, and fold detection is performed. Fold detection can be performed based on the shape contour information of each electrode, which can improve the accuracy of fold detection and reduce the occurrence of missed detection and over-detection.

[0128] In some embodiments, the region detection dataset of the electrode can be obtained using various methods. Starting from the two region discrimination points of the electrode, a search is performed along the upward direction of the light intensity fitting curve. During the search process, when the difference between the light intensity value of a light intensity detection data point and a preset maximum light intensity value is less than a preset light intensity difference threshold, this light intensity detection data point is taken as the region boundary point, thus obtaining the two region boundary points of the electrode. The preset maximum light intensity value and the preset light intensity difference threshold can be set according to the shape, type, etc., of the electrode.

[0129] For example, such as Figure 4B As shown, the light intensity fitting curve 042 corresponding to one electrode intersects with the light intensity threshold dividing line 041 at two points. These two intersection points are two region discrimination points. Starting from these two region discrimination points, a search is performed on the light intensity fitting curve 042 along its upward direction. A preset maximum light intensity value and a preset light intensity difference threshold can be set. During the search process, when the difference between the light intensity value of a light intensity detection data point and the preset maximum light intensity value is less than the preset light intensity difference threshold, this light intensity detection data point is taken as a region boundary point, thus obtaining the two region boundary points of the electrode. Figure 4B Points 043 and 044 (corresponding to two light intensity detection data points) are used in the search. For each electrode, the same search method can be used to obtain two region boundary points corresponding to each electrode.

[0130] In the optical detection data, light intensity detection data whose detection time falls within a first time interval is used as regional light intensity detection data. The first time interval includes the time interval between the detection times of two regional boundary points. A regional detection dataset is generated, which includes regional light intensity detection data and two regional boundary points. By searching the light intensity fitting curve based on the regional discrimination points, the regional detection dataset is obtained. This dataset can then be used to obtain the light intensity detection data corresponding to the tab region for fold detection, thereby improving the accuracy of fold detection.

[0131] For example, such as Figure 4B As shown, the detection times corresponding to points 043 and 044 are T1 and T2, respectively. The first time interval includes the time interval between T1 and T2. In the light detection data, the light intensity detection data whose detection time is within the first time interval is taken as the regional light intensity detection data. The regional detection dataset includes the regional light intensity detection data and two regional boundary points (points 043 and 044). That is, the regional detection dataset can be regarded as a complete light intensity light detection dataset of a single electrode. The regional detection dataset includes points 043 and 044, as well as the light intensity detection data whose detection time is between points 043 and 044.

[0132] In some embodiments, a corresponding regional shading dataset is generated based on the regional detection dataset. The regional shading dataset includes regional shading amount data corresponding to each data point in the regional detection dataset. The regional shading amount data includes shading amount, detection time corresponding to the shading amount, etc. Folding detection is performed based on the regional shading dataset. Obtaining shading amount data through light intensity detection data allows for the determination of the shape contour information of each tab, which is then used for folding detection, improving the accuracy of the folding detection.

[0133] The maximum light intensity value among all data in the region detection dataset can be determined as the region's maximum light intensity. The shading amount can then be determined based on the light intensity values ​​of the data in the region detection dataset and the region's maximum light intensity. Alternatively, the difference between the region's maximum light intensity and the light intensity values ​​of each data point in the region detection dataset can be calculated, and the shading amount for each data point in the region detection dataset can be determined based on this difference. By obtaining the shading amount using both the region's maximum light intensity and the light intensity values ​​of all data in the region detection dataset, the shape and contour of the electrode can be determined more accurately.

[0134] In one embodiment, a region detection dataset corresponding to each electrode is obtained. Among the light intensity values ​​of all data in the region detection dataset, the maximum light intensity of the region is determined. The light intensity value of each data in the region detection dataset is subtracted from the maximum light intensity of the region, and then the absolute value is taken to obtain the shading amount. Based on the detection time of each data in the region detection dataset, the detection time corresponding to the shading amount is determined.

[0135] Generate regional shading data, including shading amount and corresponding detection time. Based on the regional detection dataset, generate a corresponding regional shading dataset, which includes regional shading data corresponding to each data point in the regional detection dataset. Fit the regional shading data from the regional detection dataset to generate a tab fitting contour line, such as... Figure 6 As shown, Figure 6 The electrode fitting profile 45 contains 31 electrode profiles. The electrode fitting profiles can be generated using methods such as approximating discrete data with analytical expressions or the least squares method.

[0136] Figure 7 This is a schematic flowchart illustrating the width-direction detection process in some embodiments of the tab detection method of this disclosure, such as... Figure 7 As shown:

[0137] In step S501, the shading amount change information of each region in the regional shading dataset is determined.

[0138] In some embodiments, the shading amount change information can be the shading amount change value, which is calculated as the difference between the shading amount of each region's shading amount data and the shading amount of the adjacent region's shading amount data that was detected earlier.

[0139] like Figure 8AAs shown, the fitting curve 051 is the contour fitting curve corresponding to one electrode. Each solid point in the fitting curve 051 is the shading amount data of each region in the regional shading dataset. The vertical axis is the shading amount, and the horizontal axis values ​​1 to 39 are all sampling times (points). The horizontal axis values ​​1 to 39 can characterize the detection time corresponding to the shading amount. The time interval between adjacent sampling times can be 20, 30 milliseconds, etc.

[0140] The difference between the shading amount of each region's shading data (each solid point in the fitted curve 051) and the shading amount of the adjacent region's shading data that was detected earlier is calculated as the shading change value, which is equivalent to taking the derivative of the shading amount of the region's shading data.

[0141] For example, the change in shading amount corresponding to sampling time 1 is 0; the change in shading amount corresponding to sampling time 2 is equal to the shading amount of the area shading data corresponding to sampling time 2 minus the shading amount of the area shading data corresponding to sampling time 1; the change in shading amount corresponding to sampling time 3 is equal to the shading amount of the area shading data corresponding to sampling time 3 minus the shading amount of the area shading data corresponding to sampling time 2; and so on, the change in shading amount corresponding to sampling times 3-39 can be calculated.

[0142] A fitting curve 052 for the change in shading amount is generated based on the shading amount changes corresponding to all sampling times from 1 to 39. The hollow points in the fitting curve 052 represent the shading amount changes corresponding to each sampling time. The fitting curve 052 can be generated using methods such as approximating discrete data with analytical expressions or the least squares method.

[0143] In step S502, based on the shading amount change information, the shading amount data of the two waist parts of the electrode are determined in the regional shading dataset.

[0144] In some embodiments, within the regional shading dataset, two regional shading data points are determined based on the maximum and minimum values ​​of shading variation, serving as two waist-level shading data points. The shape of the tab can be normal or irregular. Normal shapes can be trapezoidal, trapezoidal-like, semi-circular, triangular, etc., while irregular shapes can be missing a top left or top right corner, etc. For different tabs, within the regional shading dataset, two regional shading data points can be determined using the maximum value of one or more shading variation values ​​and the minimum value of one or more shading variation values.

[0145] The most common shapes of electrode tabs are trapezoidal and trapezoidal-like. For example... Figure 8AAs shown, in the fitting curve 052 for the change in shading amount, the shading amount data of the two regions with the largest and smallest changes in shading amount are selected. These are the hollow points of the two triangles selected in the fitting curve 052. The sampling times corresponding to these two hollow points are sampling time 6 and sampling time 34. In the fitting curve 051, the shading amount data of the two regions corresponding to sampling time 6 and sampling time 34 are selected as the two waist-level shading amount data (the two regions enclosed in circles in the fitting curve 051).

[0146] In step S503, in the regional shading dataset, two shading amount data corresponding to the two regional boundary points are determined as the two boundary shading amount data.

[0147] In some embodiments, such as Figure 8A As shown, two shading data points corresponding to sampling time 1 and sampling time 39 are selected from the fitted curve 051 as two boundary shading data points.

[0148] In step S504, width direction detection is performed based on two waist shading data and two boundary shading data.

[0149] By using waist shading data and boundary shading data for width direction detection, the width direction can be detected based on the shape contour information of the tab, which can improve the accuracy of detection and reduce the occurrence of missed detection and over-detection.

[0150] In some embodiments, a first spacing is determined based on two waist shading data points. The first spacing is equivalent to the waist width of the electrode. Various methods can be used to determine the first spacing. For example, a second time interval includes the time interval between the detection times of the two waist shading data points. The number of shading data points in the region whose detection time falls within the second time interval is increased by 2 to obtain the first spacing.

[0151] like Figure 8A As shown, the shading data of the two circularly enclosed regions in the fitted curve 051 are determined to be the two waist shading data. Based on the sampling time 6 and sampling time 34 corresponding to the two waist shading data, the time interval between the detection time of the two waist shading data is determined to be the time interval between sampling time 6 and sampling time 34. The number of shading data in the fitted curve 051 located between sampling time 6 and sampling time 34 (the detection time is within the second time interval) is 27. Adding 2 to 27, the first spacing is obtained as 29.

[0152] The second spacing is determined based on the shading data from the two boundaries. This second spacing is equivalent to the tab width, and various methods can be used to determine it. For example, the third time interval includes the time interval between the detection times of the two boundary shading data. The number of shading data points in the region whose detection time falls within the third time interval is increased by 2, and this number is used as the second spacing.

[0153] like Figure 8A As shown, the boundary shading data in the fitted curve 051 corresponds to sampling time 1 and sampling time 39. The time interval between the detection times of the two boundary shading data is determined as the time interval between sampling time 1 and sampling time 39. The number of shading data in the region between sampling time 1 and sampling time 39 in the fitted curve 051 (the detection time is within the third time interval) is 37. 37 is added to 2 to obtain the second interval as 39.

[0154] Based on the ratio of the first spacing and the second spacing, width direction detection is performed. If the ratio is less than a preset ratio threshold, the tab width is determined to be abnormal; and if the ratio is greater than or equal to the ratio threshold, the tab width is determined to be normal. For example, if the ratio threshold is 0.65, and the ratio of the first spacing 29 to the second spacing 39 is 0.74, then 0.74 is greater than 0.65, and the tab width is determined to be normal.

[0155] Based on a preset ratio threshold for width direction detection, the system allows setting ratio threshold and other electrode detection parameters. Different detection parameters can be used for electrodes of different shapes and types, adapting to the width direction detection of various electrodes, reducing parameter tuning costs and improving detection efficiency.

[0156] In some embodiments, such as Figure 8B As shown, fitting curve 053 is the contour fitting curve for an irregularly shaped electrode tab. This irregularity is missing a corner on the left, which is usually the last electrode tab of each roll of electrodes. The solid points in fitting curve 053 represent the shading amount data of each region in the regional shading dataset. The vertical axis represents the shading amount, and the horizontal axis values ​​from 1 to 56 represent the sampling time. The horizontal axis values ​​from 1 to 56 can characterize the detection time corresponding to the shading amount. The time interval between adjacent sampling times can be 20, 30 milliseconds, etc.

[0157] The difference between the shading amount of each region's shading data (each solid point in the fitted curve 053) and the shading amount of the adjacent region's shading data that was detected earlier is calculated as the shading change value, which is equivalent to taking the derivative of the shading amount of the region's shading data.

[0158] For example, such as Figure 8BAs shown, the shading change value corresponding to sampling time 1 is 0 by default; the shading change value corresponding to sampling time 2 = the shading amount of the area shading data corresponding to sampling time 2 - the shading amount of the area shading data corresponding to sampling time 1; the shading change value corresponding to sampling time 3 = the shading amount of the area shading data corresponding to sampling time 3 - the shading amount of the area shading data corresponding to sampling time 2.

[0159] By analogy, the changes in shading amount corresponding to sampling times 4-56 can be calculated. Based on the changes in shading amount corresponding to all sampling times, a shading amount change fitting curve 054 is generated. The hollow points in the shading amount change fitting curve 054 represent the changes in shading amount corresponding to each sampling time.

[0160] like Figure 8B As shown, since the left side of the irregularly shaped tab is missing a corner, when determining the two waist shading data, the two waist shading data can be determined based on the maximum value of the two shading change values ​​and the minimum value of one shading change value. During the detection, it can be determined whether the tab is the last tab. When determining to perform width direction detection on the last tab, in the shading change value fitting curve 054 of this tab, the maximum value of the two shading change values ​​and the minimum value of one shading change value are selected. The shading data of the area corresponding to the maximum value of the shading change value closest to sampling time 1 (this area shading data corresponds to sampling time 7) is taken as one waist shading data; the area shading data corresponding to the minimum value of the shading change value is taken as the other waist shading data. If the right side of the last tab of the electrode is missing a corner, the two waist shading data can be determined using a similar method, based on the maximum value of one shading change value and the minimum value of the two shading change values.

[0161] Based on the maximum value of two shading amount changes and the minimum value of one shading amount change, two hollow points of triangles were selected in the shading amount change fitting curve 054. The sampling times corresponding to these two hollow points of triangles are sampling time 7 and sampling time 50. In the fitting curve 053, the shading amount data of two regions corresponding to sampling time 7 and sampling time 50 were selected as two waist shading amount data (the two regions of shading amount data circled in the fitting curve 054).

[0162] The shading data of the two circularly enclosed regions in the fitted curve 053 are identified as two waist-level shading data. Based on the sampling time 7 and sampling time 50 corresponding to the two waist-level shading data, the time interval between the detection times of the two waist-level shading data is determined as the time interval between sampling time 7 and sampling time 50. The number of shading data in the fitted curve 053 located between sampling time 7 and sampling time 50 (the detection time is within the second time interval) is 42. Adding 2 to 42 gives the first spacing as 44.

[0163] Two shading data points corresponding to sampling time 1 and sampling time 56 are selected from the fitted curve 053 as two boundary shading data points. The boundary shading data points in the fitted curve 053 are determined to correspond to sampling time 1 and sampling time 56. The time interval between the detection times of the two boundary shading data points is determined to be the time interval between sampling time 1 and sampling time 56. The number of shading data points in the region of the fitted curve 053 located between sampling time 1 and sampling time 56 (the detection time is within the third time interval) is 56, and the second spacing is 56. For example, if the ratio threshold is 0.65, the ratio of the first spacing 44 to the second spacing 56 is 0.78. If 0.78 is greater than 0.65, the tab width is determined to be normal.

[0164] Figure 9 This is a schematic flowchart illustrating the height-direction detection process in some embodiments of the electrode detection method of this disclosure, such as... Figure 9 As shown:

[0165] In step S601, the theoretical shading amount and shading threshold of the electrode are determined.

[0166] In some embodiments, experimental data on the height and shading amount of various electrodes are obtained, and the experimental data on the height and shading amount are fitted to obtain a shading fitting formula.

[0167] The height information of the tab can be the height of the tab after the electrode has been die-cut, which can be obtained by querying the parameters of the die-cutting process. Various light-blocking experiments can be performed on the tab. For example, the light emitting device and the light receiving device are the transmitter and receiver of a through-beam photoelectric sensor, respectively. In the light-blocking experiment, various electrodes pass between the light emitting device and the light receiving device. The light emitting device emits detection light, and the tab of the electrode can block or not block the detection light. The light receiving device samples the detection light and detects the light intensity value of the sampled detection light. The maximum light intensity value is subtracted from the detected light intensity value to obtain the light-blocking amount, and the height of the tab is recorded. Through experiments, experimental data on the height and light-blocking amount of the tab can be obtained, including the height value of the tab and the light-blocking amount.

[0168] The height shading fitting formula is a formula that fits the mapping relationship between the tab height value and the tab shading amount. There are various formulas for height shading fitting. For example, the least squares method can be used to fit the mapping relationship between the tab height value and the tab shading amount. Assuming the tab height value is represented by X and the tab shading amount by Y, the height shading fitting formula is: Y = kX + b, where k is the slope of the parameter to be fitted, and b is the bias of the parameter to be fitted. If the goodness of fit R... 2 If the value is less than 0.99, return to b, repeat the experiment, and perform a fitting.

[0169] like Figure 10 As shown, through experimental data and fitting using the least squares method, the high shading fitting formula is obtained as Y = 42.639X - 0.3048, where X represents the die-cutting height value, which is the tab height, and Y represents the maximum value of the tab shading amount, i.e., the shading threshold.

[0170] The theoretical shading amount is determined using a height-based shading fitting formula and based on the electrode height information. A shading threshold is then determined based on the theoretical shading amount and a preset shading deviation threshold. For example, using the height-based shading fitting formula Y = 42.639X - 0.3048, where X is the electrode height information, the resulting Y value is the shading threshold. A shading deviation threshold is set according to the electrode type and shape, and the difference between the theoretical shading amount and the shading deviation threshold is calculated as the shading threshold. By using the height-based shading fitting formula to determine the theoretical shading amount, it is possible to determine the theoretical shading amount for various electrodes, adapting to the detection of various electrode height directions, reducing parameter tuning costs, and improving detection efficiency.

[0171] In step S602, the top shading dataset is determined based on two boundary shading data and two waist shading data in the regional shading dataset.

[0172] In some embodiments, within the regional shading dataset, two regional shading data points are determined based on two boundary shading data points and two waist shading data points, serving as two top shading boundary data points. Regional shading data points whose detection time falls within a fourth time interval are used as top shading data points. This fourth time interval includes the time interval between the acquisition data of the two top shading boundary data points. A top shading dataset is generated, comprising top shading data points and top shading boundary data points.

[0173] The fifth time interval includes the interval between the detection time of the top shading boundary data and the detection time of the adjacent waist shading data; the sixth time interval includes the interval between the detection time of this waist shading data and the detection time of the adjacent boundary shading data; the number of shading data in the first region is the number of shading data in the region whose detection time falls within the fifth time interval, and the number of shading data in the second region is the number of shading data in the region whose detection time falls within the sixth time interval. The ratio between the number of shading data in the first region and the number of shading data in the second region is a preset ratio, which can be determined according to the shape of the tab, such as 1 or 2.

[0174] By determining the top shading dataset based on boundary shading data and waist shading data, the top width region of the electrode can be identified and height direction detection can be performed, which can improve the accuracy of height direction detection. By setting a preset ratio, the corresponding top shading dataset can be determined for various electrodes, which can be applied to various electrodes, reducing parameter tuning costs and improving detection efficiency.

[0175] For example, such as Figure 8A As shown, all solid points in the fitted curve 051 represent all data in the area shading dataset of the electrode. The two boundary shading data points correspond to sampling times 1 and 39 in the fitted curve 051, i.e., the two data points enclosed by the two boxes. The two area shading data points enclosed by circles in the fitted curve 051 are identified as the two waist shading data points, corresponding to sampling times 6 and 34.

[0176] Set the preset ratio to 1, and determine two top shading boundary data in the fitted curve 051, so that the number of regional shading data between sampling time 1 and sampling time 6 is equal to the number of regional shading data between sampling time 6 and the sampling time corresponding to one top shading boundary data, and the number of regional shading data between sampling time 34 and sampling time 39 is equal to the number of regional shading data between sampling time 34 and the sampling time corresponding to another top shading boundary data.

[0177] In the fitted curve 051, two regions with shading data corresponding to sampling times 11 and 29 are identified as two top shading boundary data points, each enclosed by two diamond-shaped frames. In the fitted curve 051, a waist shading data point corresponding to sampling time 6 is adjacent to an adjacent boundary shading data point corresponding to sampling time 1, and a waist shading data point corresponding to sampling time 6 is adjacent to a top shading data point corresponding to sampling time 11.

[0178] In the fitting curve 051, the number of regional shading data points in the interval between sampling time 6 (corresponding to a waist shading data point) and sampling time 1 (corresponding to an adjacent boundary shading data point) (the sixth time interval interval) is 4, that is, the number of second regional shading data points is 4; the number of regional shading data points in the interval between sampling time 6 (corresponding to a waist shading data point) and sampling time 11 (corresponding to an adjacent top shading data point) (the fifth time interval interval) is also 4, that is, the number of first regional shading data points is 4, and the preset ratio between the number of first regional shading data points and the number of second regional shading data points is 1.

[0179] In the fitted curve 051, another waist shading data corresponding to sampling time 34 is adjacent to another boundary shading data corresponding to sampling time 39, and another waist shading data corresponding to sampling time 34 is adjacent to another top shading data corresponding to sampling time 29.

[0180] In the fitted curve 051, the number of regional shading data points within the interval (sixth time interval) between sampling time 34 (corresponding to another waist shading data point) and sampling time 39 (corresponding to another boundary shading data point) is 4, meaning the number of shading data points in the second region is 4; the number of regional shading data points within the interval (fifth time interval) between sampling time 34 (corresponding to another waist shading data point) and sampling time 29 (corresponding to another top shading data point) is 4, meaning the number of shading data points in the first region is 4, and the ratio between the number of shading data points in the first region and the number of shading data points in the second region is 1.

[0181] like Figure 8B As shown, all solid points in the fitted curve 053 represent all data points in the area shading dataset of the electrode. The two boundary shading data points correspond to sampling times 1 and 56 in the fitted curve 053, i.e., the two data points enclosed by the two boxes. The two area shading data points enclosed by circles in the fitted curve 053 are identified as the two waist shading data points, corresponding to sampling times 7 and 50.

[0182] When determining that the tab corresponding to the fitted curve 053 is the last tab, two top shading boundary data are determined in the fitted curve 053, with a preset multiplier of 2, such that twice the number of shading data in the region between sampling time 1 and sampling time 7 equals the number of shading data in the region between sampling time 7 and the sampling time corresponding to one top shading boundary data; with a preset multiplier of 1, the number of shading data in the region between sampling time 50 and sampling time 56 equals the number of shading data in the region between sampling time 50 and the sampling time corresponding to another top shading boundary data.

[0183] In the fitted curve 053, two regions with shading data corresponding to sampling times 19 and 44 are identified as two top shading boundary data points, each enclosed by a diamond-shaped frame. The number of shading data points between sampling time 1 (corresponding to a boundary shading data point) and sampling time 7 (corresponding to a waist shading data point) in the fitted curve 053 is 5, meaning the number of shading data points in the second region is 5. The number of shading data points between sampling time 7 (corresponding to a waist shading data point) and sampling time 19 (corresponding to a top shading data point) is 10, meaning the number of shading data points in the first region is 10. The ratio between the number of shading data points in the first region and the second region is 2.

[0184] In the fitted curve 053, the number of shading data points between sampling time 56 (corresponding to another boundary shading data point) and sampling time 50 (corresponding to another waist shading data point) is 5, that is, the number of shading data points in the second region is 5; the number of shading data points between sampling time 50 (corresponding to another waist shading data point) and sampling time 44 (corresponding to another top shading data point) is 5, that is, the number of shading data points in the first region is 5, and the ratio between the number of shading data points in the first region and the number of shading data points in the second region is 1.

[0185] like Figure 8A As shown, the shading data of the two diamond-enclosed regions in the fitted curve 051 are identified as the two top shading boundary data points, corresponding to sampling times 11 and 29. The time interval between the acquisition data of the two top shading boundary data points is the time interval between sampling times 11 and 29. The shading data of the regions in the fitted curve 051 located between sampling times 11 and 29 (the detection time is within the fourth time interval) are obtained as the top shading data, generating a top shading dataset, including the top shading data and the two top shading boundary data points (the shading data of the regions corresponding to sampling times 11 and 29).

[0186] like Figure 8BAs shown, the shading data of the two diamond-enclosed regions in the fitted curve 053 are identified as the two top shading boundary data points, corresponding to sampling times 19 and 44. The time interval between the acquisition data of the two top shading boundary data points is the time interval between sampling times 19 and 44. The shading data of the region in the fitted curve 053 located between sampling times 19 and 44 (the detection time is within the fourth time interval) is obtained as the top shading data, generating a top shading dataset, including the top shading data and the two top shading boundary data points (the shading data of the regions corresponding to sampling times 19 and 44).

[0187] In step S603, height direction detection is performed based on the theoretical shading amount and shading amount threshold, and based on the top shading dataset.

[0188] By using theoretical shading amount, shading amount threshold, and top shading dataset for height direction detection, height direction detection can be performed based on the shape contour information of the electrode, which can improve the accuracy of height direction detection and reduce the occurrence of missed detections and over-detection.

[0189] In some embodiments, the maximum shading amount is determined from the shading amounts of all data in the top shading dataset. If the difference between the theoretical shading amount and the maximum shading amount is greater than a preset difference threshold, the height shading fitting formula is determined to be abnormal. The difference threshold can be set, for example, to 10% of the theoretical shading amount.

[0190] A shading threshold is determined based on the theoretical shading amount and a preset shading difference threshold. For example, the shading difference threshold can be set to 2%, 3%, 5%, etc., of the theoretical shading amount, and the difference between the theoretical shading amount and the shading difference threshold is used as the shading threshold. If the shading amount of one or more data points in the top shading dataset is less than the shading threshold, an abnormal electrode height is determined, and an electrode fold is determined.

[0191] For example, such as Figure 8A As shown, the data in the top shading dataset includes the shading data of the region located between sampling time 11 and sampling time 29 in the fitted curve 051 (top shading data) and two top shading boundary data (regional shading data corresponding to sampling time 11 and sampling time 29).

[0192] The difference threshold can be set according to the shape and specifications of the electrode tabs. The maximum shading amount is determined from all shading amounts in the top shading dataset. If the difference between the theoretical shading amount and the maximum shading amount exceeds the preset difference threshold, the height shading fitting formula is deemed abnormal, and a relevant alarm message is issued. If the shading amount of one or more data points in the top shading dataset is less than the shading amount threshold, the electrode tab height is deemed abnormal, and the electrode tab is determined to have folded over.

[0193] In some embodiments, the light intensity detection data undergoes data quality testing to ensure it meets data quality requirements. Before performing tab quality testing, the light intensity detection data can be analyzed according to data quality requirements to obtain quality analysis results. If the quality analysis results meet the data quality requirements, tab quality testing is then performed based on the light intensity detection data to obtain quality testing results.

[0194] For example, data features such as the data length, range (data range error), and standard deviation (arithmetic square root of data variance) of the light intensity detection data are extracted. The data quality requirement is that these data features, such as length, range, and standard deviation, are less than their corresponding feature thresholds. The system then determines whether the data features exceed the corresponding feature thresholds, and based on the determination result, whether the light intensity detection data meets the data quality requirements.

[0195] If one or more data features exceed the corresponding data feature threshold, the light intensity detection data is determined to be non-compliant with data quality requirements, and an alarm is triggered or an investigation is conducted. If none of the data features exceed the corresponding feature threshold, the light intensity detection data is determined to be compliant with data quality requirements, and electrode quality testing can proceed.

[0196] By extracting data features such as length, range, and standard deviation from light intensity detection data and performing threshold judgment, it is possible to determine whether the data quality is normal, eliminate cases of missed detection or over-detection caused by abnormal data, improve the accuracy of light intensity detection data, and increase the accuracy of electrode quality detection.

[0197] In some embodiments, such as Figure 11 As shown, the electrode 750 can be a cathode electrode, an anode electrode, etc. During the process of the electrode 750 passing between the light emitting device 740 and the light receiving device 710, the tab 730 can block or not block the detection light 720 emitted by the light emitting device 740. The light receiving device 710 samples the detection light 720 and detects the light intensity value of the sampled detection light 720 to generate light detection data. The light detection data includes multiple light intensity detection data.

[0198] The data acquisition device 760 receives optical detection data sent by the optical receiving device 710. The message server 770 obtains the optical detection data from the data acquisition device 760 and sends it to the tab detection device 780. The tab detection device 780 can be a host computer, etc. The tab detection method disclosed herein is applied to the tab detection device 780.

[0199] The data acquisition device 760 can be an edge data acquisition box, etc., and the target device 790 can be a winding machine, etc., to wind the electrode sheet 750. The PLC (Programmable Logic Controller) of the target device 790 can send start and stop signals to the data acquisition device 760. Based on the start and stop signals, the data acquisition device 760 sends control signals to the light receiving device 710. The light receiving device 710 starts or stops sampling the detection light beam 720 according to the control signals and detects the light intensity value of the sampled detection light beam 720.

[0200] The optical receiving device 710 sends the light intensity detection data to the data acquisition device 760, which can then forward the light intensity detection data through intermediate devices such as the message server 770. The electrode detection device 780 can parse the network address of the message server 770 from the locally stored configuration information and send a data request to the message server 770 to obtain the light intensity timing data based on the network address.

[0201] The message server 770 can be a server such as MQTT (Message Queuing Telemetry Transport). The electrode detection device 780 uses protocols such as MQTT to send data requests to the network address of the message server 770 to obtain light intensity time-series data. Through the data acquisition device 760 and the message server 770, the flexibility of acquiring light intensity detection data can be effectively improved.

[0202] The tab detection device 780 can subscribe to the MQTT server's "CATHODE" and "ANODE" topics in real time to obtain photodetector data of the cathode and anode electrodes during the winding process, and perform tab quality inspection based on this data. The tab detection device 780 receives photointensity detection data from the message server 770, performs tab quality inspection, and sends abnormal detection results to the target device 790. The target device 790 can display the abnormal detection results, and staff can trigger alarms and remove defective products based on these results. By sending abnormal prompts and alarms to the target device 790 when abnormalities occur, staff can take timely and effective measures to prevent production accidents.

[0203] The tab detection device 780 can simultaneously perform tab quality detection based on the light intensity detection data corresponding to the anode and cathode electrodes. The tab detection device 780 can generate light intensity fitting curves for the anode and cathode electrodes based on the light intensity values ​​and detection time in the light intensity detection data, such as... Figure 12 As shown, the outline information of the electrode can be determined based on the light intensity fitting curve, and the light intensity fitting curve can be approximately regarded as the outline information of the electrode.

[0204] In some embodiments, the detection result display process is performed based on the quality inspection results. For example, when the quality inspection result is abnormal, abnormality warning color information and abnormality warning information are determined, and warning processing is performed based on the abnormality warning color information and / or abnormality warning information. Abnormalities include abnormality in the number of tabs, abnormality in tab width, abnormality in tab height, abnormality in the fitting formula, etc., and abnormality warning information includes abnormality detection category information, or abnormality detection category information and information on the abnormal tabs. When an abnormality occurs, operations such as pausing the quality inspection process can also be performed.

[0205] The display interface of the tab detection device 780 can be used to set prompts and abnormal display areas. When the detection result is abnormal, the abnormal prompt color information is determined. For example, when the abnormality is due to abnormal tab quantity, abnormal tab width, abnormal tab height, abnormal fitting formula, etc., the abnormal prompt color can be set to red, orange, blue, green, etc., respectively. The displayed abnormal prompt color is controlled to provide alarms and prompts.

[0206] When an anomaly occurs, the system sets the detection category and the corresponding electrode information based on the anomaly settings. For example, if the anomaly is an abnormal electrode quantity, the detection category is set to "Electrode Quantity Detection," and the corresponding electrode information is "2 electrodes missing." This information is then displayed in the anomaly display area for alarm and notification purposes. Different anomalies can be assigned different colors and messages for alerting and handling, allowing staff to quickly obtain anomaly information and take timely and effective measures to prevent production accidents.

[0207] When the quality inspection result is abnormal, an abnormality prompt message and / or alarm message are sent to the target device 790; the target device 790 is used to process the inspection target. The target device 790 can be a winding machine, etc., used to wind cathode and anode electrodes. When the quality inspection result is abnormal in the number of tabs, tab width, tab height, fitting formula, etc., corresponding prompt messages and alarm messages are generated based on the abnormality.

[0208] For example, when the anomaly is an abnormality in the number of cathode tabs, the generated alarm message is "Abnormal detection of cathode tab quantity" and the prompt message is "Please check if the cathode electrode is missing tabs." The alarm message and prompt message are sent to the target device 790, alerting the staff and reminding them to investigate. By sending anomaly prompts and alarm messages to the target device 790 used to process the detected target when an anomaly occurs, staff can take timely and effective measures to prevent production accidents.

[0209] In some embodiments, a display interface including a first area is presented to acquire photodetector data of the target object in response to a detection command triggered by a detection control in the first area. Electrode quality detection is performed based on the photodetector data to obtain a quality detection result for the electrode. The display interface can be a GUI interface or the like, and can be displayed in a device such as an electrode detection apparatus. The display interface includes a second area, which is displayed in response to the detection command, and the detection result is displayed in the second area based on the quality detection result.

[0210] like Figure 13 As shown, the display interface includes a first area 071. The detection controls in the first area 071 include multiple buttons, namely a home button, a real-time contour button, a historical data button, a parameter setting button, a model query button, and a permission setting button. The home button is used to statistically analyze historical quality inspection results; the real-time contour button is used to perform electrode quality inspection and display the real-time electrode inspection results; the historical data button is used to trace historical inspection data and display historical electrode contours.

[0211] The parameter setting button is used to query and set threshold parameters, facilitating control over the quality inspection effect. Threshold parameters include ratio thresholds, difference thresholds, etc. Different parameters can be used for different models of tabs, adapting to the inspection of various tab models, reducing parameter tuning costs and improving inspection efficiency. The model query button is used to query and set the die-cutting parameters of the current product; the permission setting button is used to manage user access permissions for each function.

[0212] In response to the detection command triggered by the user clicking the real-time contour button, the system acquires the optical detection data of the target. This data includes multiple light intensity detection data points, each containing the light intensity value and the detection time. Based on this data, the system performs electrode quality detection to obtain the electrode quality results. Also in response to the user clicking the real-time contour button, the system displays a second area 072 on the interface. The detection results are then processed and displayed within this second area 072.

[0213] The connection status of the winding machine and the data acquisition card can be displayed in real time at the top of the display interface. Alarms will be triggered when the winding machine or data acquisition card malfunctions. When the quality inspection result is abnormal, the abnormality prompt color information and abnormality prompt information are determined. The abnormality prompt information includes the abnormality detection category information, or the abnormality detection category information and the abnormal electrode information, etc. An abnormality prompt icon and an abnormality display area are displayed in the second area. The color of the prompt icon in the second area is controlled based on the abnormality prompt color information, and the abnormality prompt information is displayed in the abnormality display area. Anomalies include abnormal electrode quantity, abnormal electrode width, abnormal electrode height, and abnormal fitting formula, etc. Abnormal electrode width and abnormal electrode height both belong to electrode folding anomalies.

[0214] like Figure 13 As shown, warning labels are displayed in the second area 072, including an anode warning label 074 and a cathode warning label 075. An anode anomaly display area 077 and a cathode anomaly display area 078 are also provided in the second area 072. When the quality inspection results indicate anomalies such as abnormal anode or cathode tab quantity, abnormal tab width, abnormal tab height, or abnormal fitting formula, different anomaly warning colors are determined based on the different anomalies. The colors of the anode warning label 074 and the cathode warning label 075 are controlled based on these anomaly warning colors.

[0215] For example, when the test results for both the anode and cathode tabs are normal, the color of the anode indicator 074 and cathode indicator 075 will be controlled as color A. When the quality test result indicates that the anode tab height is abnormal, the abnormality indication color information will be determined as color B, and the color of the anode indicator 074 will be controlled as color B.

[0216] When the quality inspection result indicates an abnormal anode tab height, the abnormality warning information includes the abnormality detection category information and the information of the abnormal tab. The abnormality warning information is displayed in the anode abnormality display area 077, with the abnormality detection category information being "tab folding," and the abnormal tab information including "20th tab" and the tab outline information of the 20th tab. The second area 072 can be set to a cathode abnormality display area 078. If no abnormality is found in the cathode tab detection, no information is displayed in the cathode abnormality display area 078.

[0217] Different anomalies can be identified by setting different error codes and message information. This allows staff to quickly obtain information about anomalies and take timely and effective measures to prevent production accidents.

[0218] In the second area 072, an anode detection display area 073 is set up to display the anode detection result information. After the number of tabs is detected, the anode detection display area 073 displays "Total number of anode tabs: 31, Total number of measured tabs: 30, Number of normal tabs: 29". If it is determined that the number of anode tabs is incorrect, the anode detection display area 073 displays the information "Number of missing tabs: 1" to indicate that the number of tabs is incorrect.

[0219] Based on the light intensity detection data in the optical detection data, a light intensity fitting curve is generated and displayed in the second area. For example, a data display area 076 can be set in the second area 072, where the contour curve of the anode tab and the light intensity fitting curve can be displayed. For example, after generating the light intensity fitting curve and contour fitting curve of the anode tab, the light intensity fitting curve and contour fitting curve of the anode tab can be displayed in the data display area 076.

[0220] Figure 14 This is a schematic diagram of some embodiments of the tab detection device according to the present disclosure. Figure 14 As shown, the electrode detection device may include a memory 801, a processor 802, a communication interface 803, and a bus 804. The memory 801 is used to store instructions, and the processor 802 is coupled to the memory 801. The processor 802 is configured to execute the above-described electrode detection method based on the instructions stored in the memory 801.

[0221] The memory 801 can be a high-speed RAM, non-volatile memory, or a memory array. The memory 801 may also be divided into blocks, and these blocks can be combined into virtual volumes according to certain rules. The processor 802 can be a central processing unit (CPU), an application-specific integrated circuit (ASIC), or one or more integrated circuits configured to implement the tab detection method of this disclosure.

[0222] In some embodiments, this disclosure provides a tab detection system, including the tab detection device as described in any of the above embodiments, wherein the tab detection device can perform the tab detection method in any of the embodiments. The tab detection system may also include other devices, such as a light emitting device, a light receiving device, etc.

[0223] like Figure 15AAs shown, this disclosure provides a tab detection system, including a light emitting device 910, a light receiving device 920, and a tab detection device 930. During the passage of a detection target, such as a tab, between the light emitting device 910 and the light receiving device 920, the light emitting device 910 emits detection light rays that illuminate the detection target; the light receiving device 920 samples and detects the received detection light rays, obtaining the light intensity value and detection time of the sampled detection light rays and generating photodetection data; the tab detection device 930 acquires the photodetection data and performs tab quality detection based on the photodetection data. The tab detection device 930 can acquire photodetection data in various ways; for example, the tab detection device 930 can receive photodetection data sent by the light receiving device 920, or it can receive photodetection data sent by other devices.

[0224] In some embodiments, such as Figure 15B As shown, the electrode detection system also includes a data acquisition device 940 and a message server 950; the data acquisition device 940 receives optical detection data sent by the optical receiving device; the message server 950 obtains the optical detection data from the data acquisition device 940 and sends it to the electrode detection device 930.

[0225] The data acquisition device 940 controls the light receiving device to start or stop sampling the detection light beam and detect the light intensity value of the sampled detection light beam based on the start or stop signal sent by the target device. The target device is used to process the detection target, and the target device can be a winding machine, etc.

[0226] The data acquisition device 940 controls the light receiving device 920 to start or stop sampling the detection light beam and detect the light intensity value of the sampled detection light beam based on the start or stop signal sent by the target device. The data acquisition device can be linked with the target device to ensure that quality inspection and the processing of the target by the target device are synchronized, thus guaranteeing product quality.

[0227] In some embodiments, this disclosure provides a computer-readable storage medium storing computer instructions that are executed by a processor according to the methods described in any of the above embodiments.

[0228] Computer-readable storage media may take the form of any combination of one or more readable media. A readable medium may be a readable signal medium or a readable storage medium. A readable storage medium may, for example, include, but is not limited to, electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatuses, or devices, or any combination thereof. More specific examples (not an exhaustive list) of readable storage media may include: electrical connections having one or more wires, portable disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof.

[0229] This disclosure is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this disclosure. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create a machine for implementing the flowchart illustrations. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0230] The methods and systems of this disclosure may be implemented in many ways. For example, they may be implemented by software, hardware, firmware, or any combination of software, hardware, and firmware. The above-described order of steps for the methods is for illustrative purposes only, and the steps of the methods of this disclosure are not limited to the order specifically described above unless otherwise specifically stated. Furthermore, in some embodiments, this disclosure may also be implemented as a program recorded on a recording medium, the program including machine-readable instructions for implementing the methods according to this disclosure. Thus, this disclosure also covers recording media storing programs for performing the methods according to this disclosure.

[0231] Although this application has been described with reference to preferred embodiments, various modifications can be made thereto and components can be replaced with equivalents without departing from the scope of this application. In particular, the technical features mentioned in the various embodiments can be combined in any manner, provided there is no structural conflict. This application is not limited to the specific embodiments disclosed herein, but includes all technical solutions falling within the scope of the claims.

Claims

1. A tab detection method, comprising: obtaining light detection data of a detection target; wherein the detection target has at least one tab; during the detection target passing between a light emitting device and a light receiving device, the light receiving device samples detection light emitted by the light emitting device and detects light intensity values of the sampled detection light; the light detection data comprises a plurality of light intensity detection data; the light intensity detection data comprises the light intensity values and detection times of the light intensity values; performing tab quality detection based on the light detection data to obtain a quality detection result of the tab; wherein the tab quality detection comprises tab number detection; the light intensity values comprise light intensity values of detection light blocked or not blocked by the tab; the tab quality detection based on the light detection data comprises: performing the tab number detection based on the light detection data to obtain a tab detection number; obtaining a preset number of tabs of the detection target; determining whether the number of tabs is correct according to the tab detection number and the preset number of tabs. 2.The method of claim 1, wherein the tab number detection based on the light detection data to obtain a tab detection number comprises: determining a region light intensity threshold value based on light intensity values of light intensity detection data in the light detection data; determining the tab detection number according to the light detection data and the region light intensity threshold value. 3.The method of claim 2, wherein the determination of the tab detection number according to the light detection data and the region light intensity threshold value comprises: generating a light intensity fitting curve based on light intensity detection data in the light detection data; determining two region discrimination points of the tab in the light intensity fitting curve according to the region light intensity threshold value; wherein the light intensity values of the region discrimination points are the same as the region light intensity threshold value; determining the tab detection number according to a total number of region discrimination points of all tabs. 4.The method of claim 2, wherein the determination of a region light intensity threshold value based on light intensity values of light intensity detection data in the light detection data comprises: obtaining all light intensity detection data in the light detection data; calculating a light intensity average value of the light intensity values of the all light intensity detection data; taking the light intensity average value as the region light intensity threshold value. 5.The method of claim 1, wherein the determination of whether the number of tabs is correct according to the tab detection number and the preset number of tabs comprises: in a case where the tab detection number is equal to the preset number of tabs, determining that the number of tabs is correct; and in a case where the tab detection number is not equal to the preset number of tabs, determining that the number of tabs is abnormal. folding detection; 6. The method of claim 3, the tab quality detection comprising: the tab quality detection based on the light detection data comprises: obtaining a region detection data set of the tab in the light detection data based on the two region discrimination points of the tab and the light intensity fitting curve; performing the folding detection according to the region detection data set. 7.The method of claim 6, wherein the obtaining of a region detection data set of the tab in the light detection data based on the two region discrimination points of the tab and the light intensity fitting curve comprises: ​ respectively taking the two region discrimination points as starting points and respectively searching along the rising direction of the light intensity fitting curve to obtain two region boundary points of the tab; wherein, in the searching process, when the difference between the light intensity value of a light intensity detection data and the preset light intensity maximum value is less than the preset light intensity difference threshold value for the first time, the light intensity detection data is determined as the region boundary point; in the light detection data, light intensity detection data with a detection time in a first time interval is taken as region light intensity detection data; wherein, the first time interval includes a time interval between the detection times of the two region boundary points; generating the region detection data set, wherein the region detection data set includes the region light intensity detection data and the two region boundary points.

8. The method of claim 7, wherein the folding detection based on the region detection data set comprises: generating a corresponding region shading data set based on the region detection data set; wherein the region shading data set includes region shading amount data corresponding to each data in the region detection data set; the region shading amount data includes a shading amount and a detection time corresponding to the shading amount; performing the folding detection based on the region shading data set.

9. The method of claim 8, wherein, determining a region light intensity maximum value among the light intensity values of all data in the region detection data set; determining the shading amount based on the light intensity values of the data in the region detection data set and the region light intensity maximum value.

10. The method of claim 8, the foldover detection comprising: width direction detection; wherein the folding detection based on the region shading data set comprises: determining shading amount change information of each region shading amount data in the region shading data set; determining two waist region shading amount data of the tab in the region shading data set based on the shading amount change information; determining two region boundary shading amount data corresponding to the two region boundary points in the region shading data set as two boundary shading amount data; performing the width direction detection based on the two waist region shading amount data and the two boundary shading amount data.

11. The method of claim 10, the light blocking amount change information comprising: shading amount change value; wherein the determination of the shading amount change information of each region shading amount data comprises: calculating a shading amount difference value between the shading amount of each region shading amount data and the shading amount of an adjacent region shading amount data with a detection time earlier than that of the former as the shading amount change value.

12. The method of claim 11, wherein the determination of the two waist region shading amount data of the tab in the region shading data set based on the shading amount change information comprises: determining two region shading amount data as two waist region shading amount data in the region shading data set based on the maximum and minimum values of the shading amount change values.

13. The method of claim 10, wherein the performance of the width direction detection based on the two waist region shading amount data and the two boundary shading amount data comprises: determining a first interval based on the two waist region shading amount data. determining a second interval according to the two boundary light-shielding amount data; performing the width direction detection based on a ratio of the first interval and the second interval.

14. The method of claim 13, wherein the performing the width direction detection based on the ratio of the first interval and the second interval comprises: in a case that the ratio is less than a preset ratio threshold, determining that the tab width is abnormal; and in a case that the ratio is greater than or equal to the ratio threshold, determining that the tab width is normal.

15. The method of claim 13, wherein the determining a first interval according to the two waist light-shielding amount data comprises: adding 2 to a number of region light-shielding amount data whose detection time is in a second time interval interval, as the first interval; wherein the second time interval interval comprises a time interval interval between detection times of the two waist light-shielding amount data.

16. The method of claim 13, wherein the determining a second interval according to the two boundary light-shielding amount data comprises: adding 2 to a number of region light-shielding amount data whose detection time is in a third time interval interval, as the second interval; wherein the third time interval interval comprises a time interval interval between detection times of the two boundary light-shielding amount data. height direction detection; the performing the folding detection according to the region light-shielding data set comprises: determining a theoretical light-shielding amount of the tab and a light-shielding amount threshold; 17. The method of claim 10, the foldover detection comprising: determining a top light-shielding data set based on two of the boundary light-shielding amount data and the two waist light-shielding amount data in the region light-shielding data set; performing the height direction detection according to the theoretical light-shielding amount and the light-shielding amount threshold and based on the top light-shielding data set.

18. The method of claim 17, wherein the determining a theoretical light-shielding amount of the tab and a light-shielding amount threshold comprises: determining the theoretical light-shielding amount using a height light-shielding fitting formula and based on height information of the tab; determining the light-shielding amount threshold based on the theoretical light-shielding amount and a preset light-shielding deviation threshold.

19. The method of claim 18, further comprising: obtaining height and height light-shielding amount experimental data of multiple tabs; performing fitting processing on the height and the height light-shielding amount experimental data to obtain the height light-shielding fitting formula.

20. The method of claim 17, wherein the determining a top light-shielding data set based on two of the boundary light-shielding amount data and the two waist light-shielding amount data comprises: determining two region light-shielding amount data as two top light-shielding demarcation data based on the two boundary light-shielding amount data and the two waist light-shielding amount data in the region light-shielding data set; regional light-shielding amount data whose detection time is in a fourth time interval interval as top light-shielding amount data; wherein the fourth time interval interval comprises a time interval interval between collection data of the two top light-shielding demarcation data; generating the top light-shielding data set; wherein the top light-shielding data set comprises the top light-shielding amount data and the top light-shielding demarcation data.

21. The method of claim 20, wherein ​ ​ ​ ​ ​ A ratio between a number of the first area light blocking amount data and a number of the second area light blocking amount data is a preset ratio; The number of the first area light blocking amount data is a number of area light blocking amount data whose detection time is in a fifth time interval interval, and the fifth time interval interval includes an interval between the detection time of the top light blocking demarcation data and the detection time of the adjacent waist light blocking amount data; The number of the second area light blocking amount data is a number of area light blocking amount data whose detection time is in a sixth time interval interval, and the sixth time interval interval includes an interval between the detection time of the waist light blocking amount data and the detection time of the adjacent boundary light blocking amount data.

22. The method of claim 17, wherein the detecting the height direction based on the theoretical light blocking amount and the light blocking amount threshold and based on the top light blocking data set comprises: in a case where the light blocking amount of at least one data in the top light blocking data set is less than the light blocking amount threshold, determining that the tab height is abnormal and determining that the tab is folded.

23. The method of claim 18, further comprising: determining a maximum light blocking amount among the light blocking amounts of all data in the top light blocking data set; in a case where a difference between the theoretical light blocking amount and the maximum light blocking amount is greater than a preset difference threshold, determining that the height light blocking fitting formula is abnormal.

24. The method of any one of claims 1 to 23, further comprising: presenting a display interface including a first area; in response to a detection instruction triggered based on a detection control in the first area, acquiring the light detection data; in response to the detection instruction, displaying a second area in the display interface and performing detection result display processing in the second area based on the quality detection result.

25. The method of claim 24, wherein the performing detection result display processing in the second area based on the quality detection result comprises: in a case where the quality detection result is abnormal, determining abnormal prompt color information and / or abnormal prompt information; wherein the abnormal prompt information includes abnormal detection category information or abnormal detection category information and tab information in which the abnormality occurs; displaying the abnormal prompt identifier and / or abnormal display area in the second area; controlling the color of the prompt identifier located in the second area based on the abnormal prompt color information, and / or displaying the abnormal prompt information in the abnormal display area.

26. The method of claim 24, further comprising: in a case where the quality detection result is abnormal, sending abnormal prompt information and / or alarm information to a target device; wherein the target device is configured to process the detection target.

27. The method of any one of claims 1 to 23, wherein: the detection light includes linear detection light and strip-shaped detection light; the time intervals between two time intervals adjacent in time are all the same.

28. A tab detection device, comprising: a memory; and a processor coupled to the memory, the processor configured to perform the method of any of claims 1 to 27 based on instructions stored in the memory.

29. A tab detection system, comprising: a light emitting device, a light receiving device, and the tab detection device of claim 28; wherein, in a process of detecting a target passing between the light emitting device and the light receiving device, the light receiving device samples and detects detection light emitted by the light emitting device to generate light detection data; and the tab detection device performs tab quality detection based on the light detection data.

30. The system of claim 29, wherein the detection light comprises linear detection light and strip detection light; and a center line of the tab is parallel to the linear detection light and the strip detection light when the detection target passes between the light emitting device and the light receiving device.

31. The system of claim 29 or 30, further comprising: a data collection device and a message server; the data collection device receives the light detection data sent by the light receiving device; the message server obtains the light detection data from the data collection device and sends it to the tab detection device.

32. The system of claim 31, wherein the data collection device controls the light receiving device to start or stop sampling and detecting received detection light according to start or stop signals sent by a target device, wherein the target device is used to process the detection target.

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