Tab inspection method, device and system

Abstract

A tab inspection method, a device and a system, relating to the technical field of battery generation. The method comprises: acquiring optical inspection data of an inspection object, wherein the inspection object has at least one tab, and during the process of the inspection object passes between a light emitting device and a light receiving device, the light receiving device samples inspection light emitted by the light generation device and measures the light intensity value of the sampled inspection light, the optical inspection data comprising a plurality of pieces of light intensity measurement data, and the light intensity measurement data comprising light intensity values and measurement times for the light intensity values; and performing tab quality inspection on the basis of the optical inspection data to obtain a tab quality inspection result.

Description

Tab detection method, device and system

[0001] CROSS-REFERENCE TO RELATED APPLICATIONS

[0002] This disclosure claims priority to Chinese patent application number 2023114342535, filed on October 31, 2023, entitled “Tab Detection Method, Device and System,” the entire contents of which are incorporated by reference into this disclosure. Technical Field

[0003] The present disclosure relates to the field of battery generation technology, and in particular to a tab detection method, device, and system. Background Art

[0004] Tabs are metal conductors that lead to the positive and negative electrodes in battery cells. Because they are made of a relatively soft material, they are prone to missing or folding during handling and production. Missing or folding tabs can affect the safety of the battery cell, for example, reducing the charge and discharge performance of the battery cell, causing a short circuit, or even catching fire. Therefore, it is very important to inspect the tabs before winding the electrode sheet. Currently, image detection technology is commonly used to inspect tabs. By capturing tab images, the number of missing tabs, folding tabs, and other such detections are detected based on the tab images. Because the captured tab images may contain significant noise, missed detections and over-detection are common during inspection, resulting in low detection accuracy.

[0005] Summary of the Invention

[0006] In view of the above problems, the present disclosure provides a tab detection method, device and system to improve the detection accuracy of tab detection.

[0007] According to a first aspect of the present disclosure, a tab detection method is provided, comprising: acquiring optical inspection data of a detection target; wherein the detection target has at least one tab; in a process in which the detection target passes between a light emitting device and a light receiving device, the light receiving device samples the detection light emitted by the light generating device, and detects the light intensity value of the sampled detection light; the optical inspection data comprises: a plurality of light intensity detection data; the light intensity detection data comprises: the light intensity value and the detection time; and performing tab quality inspection based on the optical inspection data to obtain a quality inspection result for the tab.

[0008] In this embodiment, the tab is detected by collecting time-series light intensity detection data. The data noise of the light intensity detection data is smaller than the noise of the tab image data, which can improve the accuracy of tab detection, reduce the occurrence of missed detection, over-detection, etc., improve the detection accuracy of tab detection, ensure product quality and reduce production costs.

[0009] In some embodiments, the tab quality detection includes: tab quantity detection; the light intensity value includes: the light intensity value of the detection light blocked or not blocked by the tab; the tab quality detection based on the light detection data includes: performing the tab quantity detection based on the light detection data to obtain the tab detection quantity; obtaining the preset number of tabs of the detection target; and determining whether the tab quantity is correct based on the tab detection quantity and the tab preset quantity.

[0010] In this embodiment, by collecting time-series light intensity detection data for pole lug quantity detection, the contour information of the pole lug can be obtained based on the light intensity detection data, which can improve the accuracy of pole lug quantity detection and reduce the occurrence of missed detection, over-detection, etc.; by setting a preset number of pole lugs, it can adapt to the quantity detection of multiple pole lugs, reduce the parameter adjustment cost, and improve the detection efficiency.

[0011] In some embodiments, the detection of the number of tabs is performed based on the optical inspection data to obtain the number of tabs detected, including: determining a regional light intensity threshold based on the light intensity value of the light intensity detection data in the optical inspection data; and determining the number of tabs detected based on the optical inspection data and the regional light intensity threshold.

[0012] In this embodiment, the regional light intensity threshold of the tab is determined by the light intensity value of the light intensity detection data. The accurate number of tabs detected can be obtained based on the light detection data and the regional light intensity threshold, which can improve the accuracy of the tab number detection.

[0013] In some embodiments, determining the number of pole lug 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 pole lug in the light intensity fitting curve based on 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 pole lug detections based on the total number of regional discrimination points of all pole lugs.

[0014] In this embodiment, two regional discrimination points of the tab are determined based on the light intensity fitting curve and using the regional light intensity threshold, and the number of tab detections is determined based on the total number of regional discrimination points of all tabs; based on the light intensity fitting curve, the outer contour of the tab can be displayed graphically, which can improve the accuracy of the tab number detection and reduce the occurrence of missed detection, over-detection, etc.

[0015] In some embodiments, determining the regional light intensity threshold based on the light intensity value of the light intensity detection data in the light detection data includes: obtaining all light intensity detection data in the light detection data; calculating the light intensity average of the light intensity values ​​of all the light intensity detection data; and using the light intensity average as the regional light intensity threshold.

[0016] In this embodiment, by taking the average light intensity value of all light intensity detection data as the regional light intensity threshold, the tab area can be determined more accurately based on the light intensity fitting curve, thereby improving the accuracy of the tab quantity detection.

[0017] In some embodiments, determining whether the number of tabs is correct based on the detected number of tabs and the preset number of tabs includes: determining that the number of tabs is correct when the detected number of tabs is equal to the preset number of tabs; and determining that the number of tabs is abnormal when the detected number of tabs is not equal to the preset number of tabs.

[0018] In this embodiment, whether the number of tabs is correct is determined based on the detected number of tabs and the preset number of tabs. Different preset numbers of tabs can be used for different models of tabs, which can adapt to the number detection of tabs of various models, reduce the parameter adjustment cost, and improve the detection efficiency.

[0019] In some embodiments, the tab quality detection includes: fold detection; the tab quality detection based on the optical inspection data includes: obtaining the area detection data set of the tab in the optical inspection data based on the two area discrimination points of the tab and the light intensity fitting curve; and performing the fold detection according to the area detection data set.

[0020] In this embodiment, a regional detection data set of the tab is obtained based on two regional discrimination points and a light intensity fitting curve. The contour information of the tab can be obtained based on the regional detection data set, and folding detection can be performed based on the external contour information of each tab, which can improve the accuracy of folding detection and reduce the occurrence of missed detection, excessive detection, etc.

[0021] In some embodiments, the method of obtaining the regional detection data set of the pole lug in the optical detection data based on the two regional discrimination points of the pole lug and the light intensity fitting curve includes: taking the two regional discrimination points as starting points and respectively along the rising direction of the light intensity fitting curve, performing search processing on the light intensity fitting curve to obtain the two regional boundary points of the pole lug; wherein, during the search processing, when it is determined for the first time that 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, the light intensity detection data is used as the regional boundary point; in the optical detection data, the light intensity detection data whose detection time is within the first time interval is used as the regional light intensity detection data; wherein, the first time interval includes: the time interval between the detection times of the two regional boundary points; generating the regional detection data set, wherein the regional detection data set includes: the regional light intensity detection data and the two regional boundary points.

[0022] In this embodiment, by searching and processing the light intensity fitting curve based on the regional discrimination point, a regional detection data set is obtained, and the light intensity detection data corresponding to the tab area can be obtained for folding detection, which can improve the accuracy of folding detection.

[0023] In some embodiments, performing the fold detection based on the area detection data set includes: generating a corresponding area shading data set based on the area detection data set; wherein the area shading data set includes: area shading amount data corresponding to each data in the area detection data set; the area shading amount data includes: shading amount, and the detection time corresponding to the shading amount; performing the fold detection based on the area shading data set.

[0024] In this embodiment, light shielding data is obtained through light intensity detection data, and the shape profile information of each tab can be determined based on the light shielding data for folding detection, which can improve the accuracy of folding detection.

[0025] In some embodiments, a regional light intensity maximum value is determined among the light intensity values ​​of all data in the regional detection data set; and the shading amount is determined based on the light intensity values ​​of the data in the regional detection data set and the regional light intensity maximum value.

[0026] In this embodiment, the light shielding amount is obtained according to the maximum light intensity value of the area and the light intensity values ​​of all data in the area detection data set, and the outer contour of the tab can be determined more accurately according to the light shielding amount data.

[0027] In some embodiments, the folding detection includes: width direction detection; the folding detection based on the regional shading data set includes: determining the shading amount change information of each regional shading amount data in the regional shading data set; based on the shading amount change information, determining the two waist shading amount data of the pole ear in the regional shading data set; determining the two shading amount data corresponding to the two regional boundary points in the regional shading data set as two boundary shading amount data; performing the width direction detection based on the two waist shading amount data and the two boundary shading amount data.

[0028] In this embodiment, by using waist shading amount data and boundary shading amount data to perform width direction detection, width direction detection can be performed based on the external contour information of the tab, which can improve the accuracy of detection and reduce the occurrence of missed detection, excessive detection, etc.

[0029] In some embodiments, the shading amount change information includes: a shading amount change value; the shading amount change information of determining the shading amount data of each area includes: calculating the shading amount difference between the shading amount of each area shading amount data and the shading amount of the adjacent area shading amount data and the area whose detection time is earlier, as the shading amount change value.

[0030] In this embodiment, the light shielding amount difference can be used to accurately determine the waist light shielding amount data according to the outer contour information of the tab, thereby improving the accuracy of the width direction detection.

[0031] In some embodiments, determining the two waist shading amount data of the pole ear in the regional shading data set based on the shading amount change information includes: in the regional shading data set, determining two regional shading amount data based on the maximum and minimum values ​​of the shading amount change values ​​as two waist shading amount data.

[0032] In this embodiment, the extreme value of the light shielding amount difference is used to determine the light shielding amount data of the waist, which can make the determination of the light shielding amount data of the waist more accurate.

[0033] In some embodiments, the width direction detection based on the two waist shading amount data and the two boundary shading amount data includes: determining a first spacing based on the two waist shading amount data; determining a second spacing based on the two boundary shading amount data; and performing the width direction detection based on the ratio of the first spacing to the second spacing.

[0034] In this embodiment, the first spacing and the second spacing determined according to the two waist shading amount data and the two boundary shading amount data can correspond to the waist width and the bottom width of the tab, and can perform width direction detection according to the outer contour information of the tab, which can improve the accuracy of detection.

[0035] In some embodiments, the width direction detection based on the ratio of the first spacing and the second spacing includes: when the ratio is less than a preset ratio threshold, determining that the tab width is abnormal; and when the ratio is greater than or equal to the ratio threshold, determining that the tab width is normal.

[0036] In this embodiment, a preset ratio threshold is used for width direction detection, and the ratio threshold and other tab detection parameters can be set. Different detection parameters can be used for tabs of different shapes and types. It can adapt to the width direction detection of various tabs, reduce the parameter adjustment cost, and improve the detection efficiency.

[0037] In some embodiments, determining the first spacing based on the two waist shading data includes: adding 2 to the number of regional shading data whose detection time is within the second time interval as the first spacing; wherein the second time interval includes: the time interval between the detection times of the two waist shading data.

[0038] In this embodiment, the first spacing is determined based on the number of regional shading data located between the detection time of the two waist shading data and the two waist shading data, which can accurately determine the waist width information of the tab and improve the accuracy of width direction detection.

[0039] In some embodiments, determining the second spacing based on the two boundary shading data includes: adding 2 to the number of regional shading data whose detection time is within the third time interval as the second spacing; wherein the third time interval includes: the time interval between the detection times of the two boundary shading data.

[0040] In this embodiment, the second spacing is determined based on the amount of regional shading data located between the detection time of the two boundary shading data and the two boundary shading data, which can accurately determine the bottom width information of the tab and improve the accuracy of width direction detection.

[0041] In some embodiments, the folding detection includes: height direction detection; the folding detection based on the regional shading data set includes: determining the theoretical shading amount and shading amount threshold of the tab; in the regional shading data set, determining the top shading data set based on the two boundary shading amount data and the two waist shading amount data; performing the height direction detection based on the theoretical shading amount and the shading amount threshold, and based on the top shading data set.

[0042] In this embodiment, by using the theoretical shading amount, shading amount threshold, and top shading data set to perform height direction detection, height direction detection can be performed based on the external contour information of the tab, which can improve the accuracy of height direction detection and reduce the occurrence of missed detection, excessive detection, etc.

[0043] In some embodiments, determining the theoretical shading amount and shading amount threshold of the tab includes: using a height shading fitting formula and based on the height information of the tab, determining the theoretical shading amount; and determining the shading amount threshold based on the theoretical shading amount and a preset shading deviation threshold.

[0044] In this embodiment, the theoretical shading amount is determined by using a height shading fitting formula, which can determine the theoretical shading amount for a variety of tabs and adapt to the height direction detection of a variety of tabs, thereby reducing the parameter adjustment cost and improving the detection efficiency.

[0045] In some embodiments, experimental data on the heights and light-shielding amounts of various tabs are obtained; the heights and light-shielding amount experimental data are fitted to obtain the light-shielding fitting formula.

[0046] In this embodiment, a fitting process is performed on experimental data to obtain a height shading fitting formula, thereby improving the accuracy of the theoretical shading amount and the accuracy of height direction detection.

[0047] In some embodiments, determining the top shading data set based on the two boundary shading amount data and the two waist shading amount data includes: in the regional shading data set, determining two regional shading amount data based on the two boundary shading amount data and the two waist shading amount data as two top shading boundary data; taking the regional shading amount data whose detection time is within the fourth time interval as the top shading amount data; wherein the fourth time interval includes: the time interval between the collection data of the two top shading boundary data; generating the top shading data set; wherein the top shading data set includes: the top shading amount data and the top shading boundary data.

[0048] In this embodiment, the top shading data set is determined based on the boundary shading amount data and the waist shading amount data, so that the top width area of ​​the tab can be determined and height direction detection can be performed, which can improve the accuracy of height direction detection.

[0049] In some embodiments, the ratio between the number of light shading data in the first area and the number of light shading data in the second area is a preset ratio; wherein, the number of light shading data in the first area is the number of light shading data in the area whose detection time is within the fifth time interval, and the fifth time interval includes: the interval between the detection time of the top light shading boundary data and the adjacent waist light shading data; the number of light shading data in the second area is the number of light shading data in the area whose detection time is within the sixth time interval, and the sixth time interval includes: the interval between the detection time of this waist light shading data and the detection time of the adjacent boundary light shading data.

[0050] In this embodiment, corresponding top shading data sets can be determined for a variety of tabs through a preset ratio, which is applicable to a variety of tabs, reduces parameter adjustment costs, and improves detection efficiency.

[0051] In some embodiments, the height direction detection performed according to the theoretical shading amount and the shading amount threshold and based on the top shading data set includes: determining that the tab height is abnormal when the shading amount of at least one data in the top shading data set is less than the shading amount threshold.

[0052] In this embodiment, whether the tab height is abnormal is determined based on the comparison between the shading amount of the data in the top shading data set and the shading amount threshold, which can improve the accuracy of height direction detection.

[0053] In some embodiments, the maximum shading amount is determined among the shading amounts of all data in the top shading data set; when 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.

[0054] In this embodiment, by detecting the height shading fitting formula, errors in the calculated theoretical shading amount can be avoided, and the accuracy of height direction detection can be improved.

[0055] 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 optical inspection 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 inspection result.

[0056] In this embodiment, a detection control is provided to facilitate the user's control of the quality inspection of the tabs; by displaying the quality inspection results in the second area of ​​the display interface, the user can intuitively know the quality inspection results through the display interface, and the staff can quickly obtain the quality inspection results and take effective measures in time to ensure production safety.

[0057] In some embodiments, the display processing of the test results in the second area according to the quality test result includes: when the quality test result is abnormal, determining the 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 abnormal tab information; displaying the abnormal prompt mark and / or abnormal display area in the second area; controlling the color of the prompt mark located in the second area based on the abnormal prompt color information, and / or displaying the abnormal prompt information in the abnormal display area.

[0058] In this embodiment, abnormal prompt color information and abnormal prompt information can be set for different abnormalities, and prompt processing can be performed, so that staff can quickly obtain abnormal information and take effective measures in time to prevent the occurrence of production accidents.

[0059] In some embodiments, when the quality detection result is abnormal, abnormal prompt information and / or alarm information is sent to the target device; wherein, the target device is used to process the detection target.

[0060] In this embodiment, when an abnormality occurs, abnormal prompt information and alarm information are sent to the target device used to process the detection target, so that the staff can take effective measures in time to prevent the occurrence of production accidents.

[0061] In some embodiments, the detection light includes: linear detection light and strip detection light; and the time intervals between two temporally adjacent detection times are the same.

[0062] In this embodiment, using linear detection light and strip detection light and making the time intervals between detection times the same can make the light intensity detection data correspond more accurately to the outer contour of the tab, thereby improving the accuracy of tab quality detection.

[0063] According to a second aspect of the present disclosure, a tab detection device is provided, comprising: a memory; and a processor coupled to the memory, wherein the processor is configured to execute the tab detection method described above based on instructions stored in the memory.

[0064] According to a third aspect of the present disclosure, a tab detection system is provided, comprising: a light emitting device, a light receiving device, and the tab detection device as described above; wherein, in 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 light detection data; and the tab detection device performs tab quality detection based on the light detection data.

[0065] In this embodiment, the cost of equipment such as the light emitting device and the light receiving device is relatively low, and the storage capacity of the light intensity detection data is smaller than the storage capacity of the image data, which can reduce the detection cost; the data noise of the light intensity detection data is smaller than the noise of the tab image data, which can improve the accuracy of tab detection and reduce the occurrence of missed detection, excessive detection, etc.

[0066] In some embodiments, the detection light includes: linear detection light and strip detection light; when the detection target passes between the light emitting device and the light receiving device, the center line of the tab is parallel to the linear detection light and the strip detection light.

[0067] In this embodiment, linear detection light and strip detection light are used, and the center line of the tab is made parallel to the detection light, so that the light intensity detection data can more accurately correspond to the outer contour of the tab, thereby improving the accuracy of tab quality detection.

[0068] In some embodiments, the system further includes: a data acquisition device and a message server; the data acquisition device receives the optical detection data sent by the light receiving device; the message server obtains the optical detection data from the data acquisition device and sends it to the tab detection device.

[0069] 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.

[0070] In this embodiment, the data acquisition device controls the light receiving device to sample and perform detection according to the start or stop signal sent by the target device, can trigger the light receiving device to sample and perform detection according to the working status of the target device, and can be linked with the target device so that quality detection and the processing of the detection target by the target device are carried out synchronously to ensure product quality.

[0071] The above description is only an overview of the technical solution of the present disclosure. In order to more clearly understand the technical means of the present disclosure, it can be implemented in accordance with the contents of the specification. In order to make the above and other purposes, features and advantages of the present disclosure more obvious and easy to understand, the specific implementation methods of the present disclosure are listed below. BRIEF DESCRIPTION OF THE DRAWINGS

[0072] In order to more clearly illustrate the technical solutions of the embodiments of the present disclosure, the lower wall will briefly introduce the drawings required for use in the embodiments of the present disclosure. Obviously, the drawings described on the lower wall are only some embodiments of the present disclosure. For ordinary technicians in this field, other drawings can be obtained based on the drawings without paying any creative work.

[0073] FIG1 is a schematic flow chart of some embodiments of the tab detection method disclosed herein;

[0074] FIG2 is a schematic diagram of a process for detecting the number of tabs in some embodiments of the tab detection method disclosed herein;

[0075] FIG3 is a schematic diagram of a process for determining the number of tabs to be detected in some embodiments of the tab detection method disclosed herein;

[0076] FIG4A is a schematic diagram of determining the number of tab inspections based on optical inspection data;

[0077] FIG4B is a schematic diagram of a light intensity fitting curve corresponding to a single tab and two regional discrimination points;

[0078] FIG5 is a schematic diagram of a process for performing folding detection in some embodiments of the tab detection method disclosed herein;

[0079] FIG6 is a schematic diagram of a tab profile fitting curve of the tab detection method disclosed herein;

[0080] FIG7 is a schematic diagram of a process for performing width direction detection in some embodiments of the tab detection method disclosed herein;

[0081] FIG8A is a schematic diagram showing the change in the light shielding amount data of a normal tab area;

[0082] FIG8B is a schematic diagram showing the change in the amount of light shielding in the area of ​​the special-shaped tab;

[0083] FIG9 is a schematic diagram of a process for performing height direction detection in some embodiments of the tab detection method disclosed herein;

[0084] FIG10 is a schematic diagram showing the fitting of the tab height and the light shielding amount in the tab detection method disclosed herein;

[0085] FIG11 is a schematic diagram of the detection process of the tab detection method disclosed herein;

[0086] FIG12 is a schematic diagram of the outlines of the cathode tab and the anode tab of the tab detection method disclosed herein;

[0087] FIG13 is a schematic diagram of a display interface in some embodiments of the tab detection method disclosed herein;

[0088] FIG14 is a schematic diagram of modules of other embodiments of the tab detection device disclosed herein;

[0089] FIG15A is a module diagram of some embodiments of the tab detection system disclosed herein;

[0090] FIG15B is a module schematic diagram of other embodiments of the tab detection system disclosed herein. DETAILED DESCRIPTION

[0091] The following embodiments of the technical solution of the present disclosure are described in detail with reference to the accompanying drawings. The following embodiments are only used to more clearly illustrate the technical solution of the present disclosure and are therefore only examples and are not intended to limit the scope of protection of the present disclosure.

[0092] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the art to which the present disclosure belongs; the terms used herein are only for the purpose of describing specific embodiments and are not intended to limit the present disclosure; the terms "including" and "having" and any variations thereof in the specification and claims of the present disclosure and the above-mentioned figure descriptions are intended to cover non-exclusive inclusions.

[0093] In the description of the embodiments of the present disclosure, technical terms such as "first" and "second" are used solely to distinguish between different objects and should not be understood to indicate or imply relative importance or to implicitly specify the quantity, specific order, or primary and secondary relationship of the technical features indicated. In the description of the embodiments of the present disclosure, "plurality" means more than two, unless otherwise specifically defined.

[0094] References herein to "embodiments" mean that a particular feature, structure, or characteristic described in connection with the embodiments may be included in at least one embodiment of the present disclosure. The appearance of this phrase in various places in the specification does not necessarily refer to the same embodiment, nor does it constitute an independent or alternative embodiment that is mutually exclusive of other embodiments. It is understood, both explicitly and implicitly, by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0095] In the description of the embodiments of the present disclosure, the term "and / or" is simply a description of the association relationship between associated objects, indicating that three relationships can exist. For example, A and / or B can represent three situations: A exists alone, A and B exist simultaneously, and B exists alone. In addition, the character " / " in this document generally indicates that the associated objects are in an "or" relationship.

[0096] In the description of the embodiments of the present disclosure, the term "multiple" refers to more than two (including two). Similarly, "multiple groups" refers to more than two groups (including two groups), and "multiple pieces" refers to more than two pieces (including two pieces).

[0097] In the description of the embodiments of the present disclosure, the technical terms "center", "longitudinal", "lateral", "length", "width", "thickness", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside", "clockwise", "counterclockwise", "axial", "radial", "circumferential", etc., indicating the orientation or position relationship, are based on the orientation or position relationship shown in the accompanying drawings, and are only for the convenience of describing the embodiments of the present disclosure and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operate in a specific orientation, and therefore should not be understood as limiting the embodiments of the present disclosure.

[0098] In the description of the embodiments of the present disclosure, unless otherwise expressly specified or limited, technical terms such as "installed," "connected," "connected," and "fixed" should be understood in a broad sense. For example, they can refer to fixed connections, detachable connections, or integration; mechanical connections or electrical connections; direct connections or indirect connections through an intermediate medium; and they can refer to internal connectivity between two components or interaction between two components. Those skilled in the art can understand the specific meanings of the above terms in the embodiments of the present disclosure based on specific circumstances.

[0099] According to the inventors' knowledge of related technologies, the winding process involves winding the cathode and anode electrodes and separator together using a winding machine to form a bare cell. This process is a key step in the assembly phase of lithium battery production. Because tabs are prone to missing or folding during handling and production, inspecting the tabs for missing and folding issues before winding can improve the yield rate of finished cells and reduce assembly and rework costs.

[0100] Currently, tab inspection typically uses image detection technology, which captures tab images and performs folding and other tests. However, because the captured tab images may contain significant noise, this can lead to missed detections and over-detection (for example, misclassifying a qualified tab as unqualified), resulting in low detection accuracy. Furthermore, image detection is costly. In light of this, the present disclosure provides a technical solution for tab inspection to address the aforementioned technical issues.

[0101] FIG1 is a flow chart of some embodiments of the tab detection method disclosed herein, as shown in FIG1 :

[0102] In step S101 , optical detection data of a detection target is acquired.

[0103] In some embodiments, the detection target may be a cathode electrode piece, an anode electrode piece, or the like, each of which has at least one electrode tab disposed on its edge. As the detection target passes between the light emitting device and the light receiving device, the light emitting device emits detection light. The detection target may block the detection light during movement, and the light receiving device samples and detects the detection light to obtain the light intensity value and detection time of the sampled detection light.

[0104] The light emitting device and the light receiving device can be a variety of devices. For example, a through-beam photoelectric sensor is a non-contact sensor based on the principle of photoelectric conversion. It consists of a transmitter and a receiver. The light emitting device and the light receiving device are the transmitter and receiver of the through-beam photoelectric sensor, respectively. Through-beam photoelectric sensors can be of various types.

[0105] When inspecting the tabs, the cathode and anode pieces pass between a light-emitting device and a light-receiving device (which can be the emitter and receiver of a through-beam photoelectric sensor). During this process, the light-generating device emits a detection light beam, which is blocked by the cathode and anode pieces.

[0106] Tabs are provided on the sides of the cathode and anode electrodes, with gaps between the tabs. During the passage of the cathode and anode electrodes between the light emitting device and the light receiving device, the tabs may or may not block the detection light. The light receiving device samples the received detection light and detects the light intensity of the sampled detection light. 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 or the like. When the tabs block the detection light, the light intensity value sampled and detected by the light receiving device decreases.

[0107] Light detection data is generated based on the detection results of the light receiving device. The light detection data includes multiple light intensity detection data, including light intensity values ​​and detection times (sampling times) of the light intensity values. The time intervals between two temporally adjacent detection times can be the same, partially the same, or completely different.

[0108] The detection light can be linear or strip-shaped, and can be laser-like. To achieve accurate detection, the centerline of the tab should be parallel to the linear or strip-shaped detection light when the cathode and anode pieces pass between the light-emitting and light-receiving devices. Using linear or strip-shaped detection light, and aligning the tab centerline with the detection light, allows the light intensity detection data to more accurately correspond to the tab's external contours, thereby improving the accuracy of tab quality inspection.

[0109] In step S102, the tab quality inspection is performed based on the optical inspection data to obtain the tab quality inspection results. The tab quality inspection may include multiple inspections such as tab quantity inspection, tab fold inspection, and tab edge defect inspection.

[0110] The tab detection method in the above embodiment detects the tab by collecting time-series light intensity detection data, and the contour information of the tab can be obtained based on the light intensity detection data; the data noise of the light intensity detection data is smaller than the noise of the tab image data, which can improve the accuracy of tab detection, reduce the occurrence of missed detection, over-detection, etc., improve the detection accuracy of tab 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, and the storage capacity of light intensity detection data is smaller than the storage capacity of image data. The cost of equipment such as light emitting devices and light receiving devices is low, which can reduce detection costs.

[0111] In some embodiments, during the winding process, the tab quality inspection can be performed simultaneously on both the cathode and anode tabs, which can reduce assembly and rework costs. The tab inspection method disclosed herein can be applied to a tab inspection device, which can be a variety of electronic devices. The electronic device is a device terminal capable of executing a computer program or the aforementioned server. The device terminal can be a personal computer, tablet computer, mobile internet device, etc. A server refers to a device that provides computing services over a network, and can be an x86 server or a non-x86 server.

[0112] Tab quality inspection can include multiple inspections, such as tab quantity inspection and folding inspection, and folding inspection includes height direction inspection and width direction inspection. FIG2 is a schematic diagram of the process of performing tab quantity inspection in some embodiments of the tab inspection method disclosed herein. The light intensity value in the optical inspection data includes the light intensity value of the inspection light blocked or not blocked by the tab, as shown in FIG2:

[0113] In step S201 , the number of tabs is detected based on the optical inspection data to obtain the number of tabs detected.

[0114] In step S202 , a preset number of tabs of the detection target is obtained.

[0115] In some embodiments, the preset number of tabs can be set based on the tab data of the cathode and anode plates being tested, which are found to be qualified. For example, the number of die-cut tabs of the cathode and anode plates after the die-cutting process can be queried as the preset number of tabs. For each model and batch of cathode and anode plates, the preset number of tabs only needs to be queried once before performing the tab quality inspection.

[0116] In step S203 , it is determined whether the number of tabs is correct based on the detected number of tabs and the preset number of tabs.

[0117] By collecting time-series light intensity detection data for lug quantity detection, the accuracy of lug quantity detection can be improved, and the occurrence of missed detection, over-detection, etc. can be reduced; by setting parameters such as the preset number of lugs, it can adapt to the number detection of various lugs, reducing the parameter adjustment cost and improving the detection efficiency.

[0118] In some embodiments, if the detected number of tabs is equal to the preset number of tabs, the number of tabs is determined to be correct; if the detected number of tabs is not equal to the preset number of tabs, the number of tabs is determined to be abnormal. For example, the difference between the preset number of tabs and the detected number of tabs is calculated. If the difference is 0, the number of tabs is determined to be correct; if the difference is not 0, the number of tabs is determined to be abnormal, and the number of abnormal tabs is the absolute value of the difference.

[0119] FIG3 is a schematic diagram of a process for determining the number of tabs to be detected in some embodiments of the tab detection method disclosed herein, as shown in FIG3 :

[0120] In step S301 , a regional light intensity threshold is determined based on the light intensity value of the light intensity detection data in the light detection data.

[0121] In step S302 , the number of tabs to be detected is determined based on the light detection data and the regional light intensity threshold.

[0122] The regional light intensity threshold of the tab is determined by the light intensity value of the light intensity detection data. The accurate number of tabs detected can be obtained based on the light detection data and the regional light intensity threshold, which can improve the accuracy of the tab number detection.

[0123] In some embodiments, a variety of methods can be used to determine the regional light intensity threshold: obtaining all light intensity detection data in the light detection data, calculating the light intensity average of the light intensity values ​​of all the light intensity detection data, and using the light intensity average as the regional light intensity threshold.

[0124] Based on the light intensity detection data from the optical inspection data, a light intensity fitting curve is generated. Based on the regional light intensity threshold, two regional discrimination points of the tab are determined in the light intensity fitting curve. The light intensity values ​​of the regional discrimination points are equal to the regional light intensity threshold. The number of tabs to be detected is determined based on the total number of regional discrimination points for all tabs. The light intensity fitting curve can be used to visualize the tab's outline, improving the accuracy of tab quantity detection and reducing the occurrence of missed detections and over-detection.

[0125] As shown in FIG4A , all light intensity detection data from the light detection data is obtained, and based on the light intensity values ​​of all the light intensity detection data and the detection times of the light intensity values, a light intensity fitting curve 040 is generated. Light intensity fitting curve 040 includes the contour lines of multiple tabs. In FIG4A , the abscissa represents the detection time point (in milliseconds), and the ordinate represents the light intensity value. Various methods can be used to fit and generate light intensity fitting curve 040 based on all the light intensity detection data, such as using an analytical expression to approximate discrete data, a least squares method, and the like.

[0126] Calculate the average light intensity of all light intensity detection data as the regional light intensity threshold. Based on the regional light intensity threshold, generate a regional light intensity threshold dividing line 041. The light intensity value (ordinate) 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, determine the two regional discrimination points of the tab in the light intensity fitting curve 040. The light intensity value of the regional discrimination point is the same as the regional light intensity threshold.

[0127] For example, the shape of the light intensity fitting curve of a pole lug corresponding to the dotted box in Figure 4A can be the shape of the light intensity fitting curve 042 in Figure 4B. In Figure 4B, the light intensity fitting curve 042 corresponding to a pole lug has two intersections with the light intensity threshold dividing line 041. These two intersections are two area discrimination points, and these two area discrimination points can determine the area where the pole lug is located. Each pole lug area in the light intensity threshold dividing line 041 and the light intensity fitting curve 040 has two intersections (area discrimination points). The total number of intersections between the light intensity threshold dividing line 041 and the light intensity fitting curve 040 is obtained, that is, the total number of area discrimination points of all pole lugs is obtained, and the total number of area discrimination points is divided by 2 to obtain the number of pole lug detections. Based on the number of pole lug detections and the preset number of pole lugs, determine whether the number of pole lugs is correct.

[0128] A light intensity fitting curve is generated through light intensity detection data, and two regional discrimination points of the pole lug are determined in the light intensity fitting curve according to the regional light intensity threshold. This can determine the area where the pole lug is located and the number of pole lugs to be detected. The detection efficiency is high, the number of pole lugs to be detected can be accurately determined, and the accuracy of pole lug number detection is improved.

[0129] FIG5 is a schematic diagram of a process for performing folding detection in some embodiments of the tab detection method disclosed herein, as shown in FIG5 :

[0130] In step S401 , based on two region discrimination points of the tab and a light intensity fitting curve, a region detection data set of the tab is obtained from the optical detection data.

[0131] In step S402, fold detection is performed based on the region detection dataset.

[0132] Based on the two regional discrimination points and the light intensity fitting curve, the regional detection data set of the tab is obtained, and folding detection is performed. Folding detection can be performed according to the shape contour information of each tab, which can improve the accuracy of folding detection and reduce the occurrence of missed detection, excessive detection, etc.

[0133] In some embodiments, a variety of methods can be used to obtain a region detection dataset for the tab. A search process is performed on the light intensity fitting curve, starting from the two region discrimination points of the tab and along the ascending 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 and a preset light intensity maximum value is determined to be less than a preset light intensity difference threshold, the light intensity detection data is used as a region boundary point, thereby obtaining the two region boundary points of the tab. The preset light intensity maximum value and the preset light intensity difference threshold can be set according to the shape and type of the tab, etc.

[0134] For example, as shown in FIG4B , the light intensity fitting curve 042 corresponding to a pole lug and the light intensity threshold dividing line 041 have two intersection points, and these two intersection points are two regional discrimination points. With these two regional discrimination points as starting points, and along the rising direction of the light intensity fitting curve 042, respectively, a search process is performed on the light intensity fitting curve. A preset light intensity maximum value and a preset light intensity difference threshold value can be set in advance. During the search process, when it is determined for the first time that 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, this light intensity detection data is used as a regional boundary point, that is, two regional boundary points of the pole lug are obtained. The two regional boundary points are points 043 and 044 in FIG4B (points 043 and 044 correspond to two light intensity detection data). For each pole lug, the same search method can be used for search processing to obtain two regional boundary points corresponding to each pole lug.

[0135] In the light detection data, light intensity detection data with detection times within a first time interval is used as regional light intensity detection data. The first time interval includes the time interval between detection times of two regional boundary points. A regional detection dataset is generated, comprising the regional light intensity detection data and the two regional boundary points. The regional detection dataset is obtained by searching the light intensity fitting curve based on the regional discrimination points. Light intensity detection data corresponding to the tab region can be obtained for use in fold detection, thereby improving fold detection accuracy.

[0136] For example, as shown in Figure 4B, the detection times corresponding to point 043 and point 044 are T1 and T2 respectively, and the first time interval includes: the time interval between T1 and T2; in the light detection data, the light intensity detection data with the detection time within the first time interval is used as the regional light intensity detection data, and the regional detection data set includes: regional light intensity detection data and two regional boundary points (point 043 and point 044), that is, the regional detection data set can be regarded as a complete light intensity light detection data of a pole ear, and the regional detection data set includes point 043 and point 044, as well as the light intensity detection data with the detection time between point 043 and point 044.

[0137] In some embodiments, a corresponding regional light shielding dataset is generated based on the regional detection dataset. The regional light shielding dataset includes regional light shielding amount data corresponding to each data point in the regional detection dataset. The regional light shielding amount data includes light shielding amount, detection time corresponding to the light shielding amount, and other information. Folding detection is performed based on the regional light shielding dataset. The light shielding amount data is obtained from the light intensity detection data, and the outer contour information of each tab can be determined based on the light shielding amount data for use in folding detection, thereby improving the accuracy of folding detection.

[0138] The maximum value among the light intensity values ​​of all data in the regional detection dataset can be determined as the regional light intensity maximum value; the light shielding amount can be determined based on the light intensity values ​​of the data in the regional detection dataset and the regional light intensity maximum value. The difference between the regional light intensity maximum value and the light intensity values ​​of each data in the regional detection dataset can be calculated, and the light shielding amount of each data in the regional detection dataset can be determined based on the difference. The light shielding amount is obtained based on the regional light intensity maximum value and the light intensity values ​​of all data in the regional detection dataset, and the outer contour of the tab can be more accurately determined based on the light shielding amount data.

[0139] In one embodiment, a regional detection data set corresponding to each pole ear is obtained, and the maximum regional light intensity value is determined among the light intensity values ​​of all data in the regional detection data set; the light intensity value of each data in the regional detection data set is subtracted from the maximum regional light intensity value, and then the sign is inverted (the absolute value is taken) to obtain the shading amount, and based on the detection time of each data in the regional detection data set, the detection time corresponding to the shading amount is determined.

[0140] Generate regional shading data, including the shading amount and the detection time corresponding to the shading amount. Generate a corresponding regional shading dataset based on the regional detection dataset, including regional shading data corresponding to each data point in the regional detection dataset. Fitting the regional shading data points in the regional detection dataset can generate a tab fitting contour line, as shown in Figure 6. Tab fitting contour line 45 in Figure 6 includes 31 tab contours. The tab fitting contour line can be generated using methods such as analytical expression approximation of discrete data and the least squares method.

[0141] FIG7 is a schematic diagram of a process for performing width direction detection in some embodiments of the tab detection method disclosed herein, as shown in FIG7 :

[0142] In step S501 , the shading amount change information of each regional shading amount data is determined in the regional shading data set.

[0143] In some embodiments, the shading amount change information can be a shading amount change value, and the shading amount difference between the shading amount of each area shading amount data and the shading amount of the adjacent area shading amount data with an earlier detection time is calculated as the shading amount change value.

[0144] As shown in Figure 8A, the fitting curve 051 is the contour fitting curve corresponding to a pole ear, and the solid points in the fitting curve 051 are the regional shading amount data in the regional shading data set, where the vertical axis is the shading amount, and the horizontal axis values ​​1 to 39 are all sampling moments (points). The horizontal axis values ​​1 to 39 can represent the detection time corresponding to the shading amount, and the time interval between adjacent sampling moments can be 20, 30 milliseconds, etc.

[0145] Calculate the difference in shading amount between the shading amount data of each area (each solid point in the fitting curve 051) and the shading amount of the adjacent area shading amount data with an earlier detection time as the shading amount change value, which is equivalent to taking the derivative of the shading amount of the area shading amount data.

[0146] For example, the shading amount change value corresponding to sampling moment 1 is 0; the shading amount change value corresponding to sampling moment 2 = the shading amount of the regional shading amount data corresponding to sampling moment 2 - the shading amount of the regional shading amount data corresponding to sampling moment 1; the shading amount change value corresponding to sampling moment 3 = the shading amount of the regional shading amount data corresponding to sampling moment 3 - the shading amount of the regional shading amount data corresponding to sampling moment 2; and so on, the shading amount change value corresponding to sampling moment 3-39 can be calculated.

[0147] Based on the shading amount change values ​​corresponding to all sampling moments 1-39, a fitting curve 052 of shading amount change values ​​is generated. The hollow points in the fitting curve 052 represent the shading amount change values ​​corresponding to each sampling moment. Fitting curve 052 can be generated using methods such as approximating discrete data using analytical expressions or the least squares method.

[0148] In step S502 , based on the shading amount change information, the shading amount data of two waist portions of the tab are determined in the regional shading data set.

[0149] In some embodiments, in the regional shading dataset, two regional shading amount data are determined based on the maximum and minimum values ​​of the shading amount change values, serving as two waist shading amount data. The tab shape can be normal or irregular. Normal shapes can include trapezoids, quasi-trapezoidal shapes, semicircles, triangles, etc., while irregular shapes can include missing upper left corners or upper right corners. For different tabs, two regional shading amount data can be determined based on the maximum value of one or more shading amount change values ​​and the minimum value of one or more shading amount change values ​​in the regional shading dataset.

[0150] The most common tab shapes are trapezoidal and quasi-trapezoidal. As shown in Figure 8A , in the light shielding amount variation fitting curve 052, the light shielding amount data for the two regions with the largest and smallest light shielding amount variations are selected. These are the hollow points of the two triangles selected in the light shielding amount variation 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 light shielding amount data for the two regions corresponding to sampling time 6 and sampling time 34 are selected as the two waist light shielding amount data (the light shielding amount data for the two regions encircled by circles in the fitting curve 051).

[0151] In step S503 , two pieces of light shielding amount data corresponding to two area boundary points are determined in the area light shielding data set as two pieces of boundary light shielding amount data.

[0152] In some embodiments, as shown in FIG8A , two light shielding amount data corresponding to sampling time 1 and sampling time 39 are selected in the fitting curve 051 as two boundary light shielding amount data.

[0153] In step S504, width direction detection is performed based on two pieces of waist light shielding amount data and two pieces of boundary light shielding amount data.

[0154] By using waist shading data and boundary shading data for width direction detection, width direction detection can be performed based on the external contour information of the tab, which can improve the accuracy of detection and reduce the occurrence of missed detection, excessive detection, etc.

[0155] In some embodiments, a first spacing is determined based on two waist light shielding data points. The first spacing corresponds to the tab waist width. Various methods can be used to determine the first spacing. For example, the second time interval includes the time interval between the detection times of the two waist light shielding data points. The first spacing is determined by adding 2 to the number of light shielding data points whose detection times fall within the second time interval.

[0156] As shown in Figure 8A, the two area shading data enclosed by circles in the fitting curve 051 are determined to be two waist shading data. Based on the sampling time 6 and the sampling time 34 corresponding to the two waist shading data, the time interval between the detection times of the two waist shading data is determined to be the time interval between the sampling time 6 and the sampling time 34. The number of area shading data in the fitting curve 051 located between the sampling time 6 and the sampling time 34 (the detection time is within the second time interval) is 27. Add 27 to 2 to obtain the first spacing of 29.

[0157] The second spacing is determined based on the two boundary light shielding data. The second spacing is equivalent to the tab width. Various methods can be used to determine the second spacing. For example, the third time interval includes the time interval between the detection times of the two boundary light shielding data. The second spacing is calculated by adding 2 to the number of light shielding data points whose detection times fall within the third time interval.

[0158] As shown in Figure 8A, the boundary shading amount data in the fitting curve 051 are determined to correspond to the sampling time 1 and the sampling time 39, and the time interval between the detection times of the two boundary shading amount data is determined to be the time interval between the sampling time 1 and the sampling time 39; the number of regional shading amount data in the fitting curve 051, which is located between the sampling time 1 and the sampling time 39 (the detection time is within the third time interval), is obtained as 37, and 37 is added by 2 to obtain the second spacing of 39.

[0159] Based on the ratio of the first spacing to the second spacing, a width-wise detection is performed. If the ratio is less than a preset ratio threshold, the tab width is determined to be abnormal. 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 the tab width is determined to be normal if 0.74 is greater than 0.65.

[0160] Based on the preset ratio threshold for width direction detection, the ratio threshold and other tab detection parameters can be set. Different detection parameters can be used for tabs of different shapes and types. It can adapt to the width direction detection of various tabs, reducing the parameter adjustment cost and improving the detection efficiency.

[0161] In some embodiments, as shown in FIG8B , fitting curve 053 is a contour fitting curve for a non-uniform tab, with a corner missing on the left side of this non-uniform tab, typically the last tab in each electrode roll. The solid points in fitting curve 053 represent the regional shading data in the regional shading dataset, where the ordinate represents the shading amount, and the abscissa values ​​1 to 56 represent the sampling times. The abscissa values ​​1 to 56 represent the detection time corresponding to the shading amount, and the time interval between adjacent sampling times can be 20 or 30 milliseconds, for example.

[0162] The shading amount difference between the shading amount of each regional shading amount data (each solid point in the fitting curve 053) and the shading amount of the adjacent regional shading amount data with an earlier detection time is calculated as the shading amount change value, which is equivalent to taking the derivative of the shading amount of the regional shading amount data.

[0163] For example, as shown in Figure 8B, the shading amount change value corresponding to sampling moment 1 defaults to 0; the shading amount change value corresponding to sampling moment 2 = the shading amount of the regional shading amount data corresponding to sampling moment 2 - the shading amount of the regional shading amount data corresponding to sampling moment 1; the shading amount change value corresponding to sampling moment 3 = the shading amount of the regional shading amount data corresponding to sampling moment 3 - the shading amount of the regional shading amount data corresponding to sampling moment 2.

[0164] By analogy, the shading amount change values ​​corresponding to sampling moments 4 to 56 can be calculated. A shading amount change value fitting curve 054 is generated based on the shading amount change values ​​corresponding to all sampling moments. The hollow points in the shading amount change value fitting curve 054 are the shading amount change values ​​corresponding to each sampling moment.

[0165] As shown in Figure 8B, since the left side of the irregular tab is missing a corner, when determining the two waist shading data, the two waist shading data can be determined based on the maximum of the two shading change values ​​and the minimum of the one shading change value. During the inspection, it can be determined whether the tab is the last tab. When determining to perform width-wise inspection on the last tab, the maximum of the two shading change values ​​and the minimum of the one shading change value are selected from the shading change value fitting curve 054 for this tab. The regional shading data corresponding to the maximum shading change value closest to sampling time 1 (this regional shading data corresponds to sampling time 7) is used as one waist shading data; the regional shading data corresponding to the minimum shading change value is used as the other waist shading data. If the right side of the last tab of the pole piece is missing a corner, the two waist shading data can be determined based on the maximum of the one shading change value and the minimum of the two shading change values ​​using a similar method.

[0166] Based on the maximum value of the two shading amount change values ​​and the minimum value of the shading amount change value, two hollow points of the triangle are selected in the shading amount change value fitting curve 054. The sampling times corresponding to the two hollow points of the triangle are sampling time 7 and sampling time 50. In the fitting curve 053, two regional shading amount data corresponding to sampling time 7 and sampling time 50 are selected as the two waist shading amount data (the two regional shading amount data encircled by circles in the fitting curve 054).

[0167] Determine that the two area shading data enclosed by circles in the fitting curve 053 are two waist shading data. Based on the sampling time 7 and the sampling time 50 corresponding to the two waist shading data, determine that the time interval between the detection times of the two waist shading data is the time interval between the sampling time 7 and the sampling time 50. The number of area shading data in the fitting curve 053 located between the sampling time 7 and the sampling time 50 (the detection time is within the second time interval) is 42. Add 2 to 42 to obtain the first spacing of 44.

[0168] The two light shielding data corresponding to sampling time 1 and sampling time 56 are selected from the fitting curve 053 as the two boundary light shielding data. The boundary light shielding data in the fitting 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 light shielding data is determined to be the time interval between sampling time 1 and sampling time 56. The number of light shielding data in the region between sampling time 1 and sampling time 56 (detection times within the third time interval) in the fitting curve 053 is obtained as 56, and the second spacing is 56. For example, if the ratio threshold is 0.65 and the ratio of the first spacing 44 to the second spacing 56 is 0.78, and 0.78 is greater than 0.65, it is determined that the tab width is normal.

[0169] FIG9 is a schematic diagram of a process for performing height direction detection in some embodiments of the tab detection method disclosed herein, as shown in FIG9 :

[0170] In step S601 , the theoretical light shielding amount and the light shielding amount threshold of the tab are determined.

[0171] In some embodiments, experimental data on the heights and light-shielding amounts of various tabs are obtained, and the experimental data on the heights and light-shielding amounts are fitted to obtain a height-shielding fitting formula.

[0172] The height information of the tab can be the height of the tab after the pole piece is die-cut, which can be obtained by querying the parameters of the die-cutting process. Various light-shielding experiments can be performed on the tab. For example, the light emitting device and the light receiving device are respectively the emitter and the receiver of the through-beam photoelectric sensor. During the light-shielding experiment, various pole pieces pass between the light emitting device and the light receiving device. The light generating device emits detection light. The tab of the pole piece may or may 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 set maximum light intensity value is subtracted from the detected light intensity value to obtain the light-shielding amount, and the height of the tab is recorded. Through the experiment, experimental data on the height light-shielding amount of the tab can be obtained, including the height value of the tab and the light-shielding amount.

[0173] The height shading fitting formula is a formula for fitting the mapping relationship between the tab height value and the tab shading amount. The height shading fitting formula can be a variety of formulas. For example, the least square method can be used to fit the mapping relationship between the tab height value and the tab shading amount. Assuming that the tab height value is represented by X and the tab shading amount is represented 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 offset of the parameter to be fitted. If the goodness of fit R 2 <0.99, return to b, repeat the experiment and perform the fitting.

[0174] As shown in Figure 10, through the experimental data and the least squares method of fitting, the height shading fitting formula is obtained as Y = 42.639X-0.3048, where X represents the die-cutting height value, the die-cutting height is the tab height, and Y represents the maximum value of the tab shading amount, that is, the shading amount threshold.

[0175] The theoretical shading amount is determined using the height shading fitting formula based on the tab height information; the shading amount threshold is determined based on the theoretical shading amount and the preset shading deviation threshold. For example, the height shading fitting formula is Y = 42.639X - 0.3048, with X set to the tab height information, and the resulting Y value is the shading amount threshold. The shading deviation threshold is set according to the type and shape of the tab, and the difference between the theoretical shading amount and the shading deviation threshold is calculated as the shading amount threshold. By using the height shading fitting formula to determine the theoretical shading amount, the theoretical shading amount can be determined for a variety of tabs, and it can adapt to the height direction detection of a variety of tabs, reducing the parameter adjustment cost and improving the detection efficiency.

[0176] In step S602 , in the regional shading data set, a top shading data set is determined based on two boundary shading amount data and two waist shading amount data.

[0177] In some embodiments, in a regional light shielding dataset, two regional light shielding amount data are determined based on two boundary light shielding amount data and two waist light shielding amount data, serving as two top light shielding boundary data. Regional light shielding amount data detected within a fourth time interval is used as the top light shielding amount data. The fourth time interval includes the time interval between the acquisition of data of the two top light shielding boundary data. A top light shielding dataset is generated, comprising the top light shielding amount data and the top light shielding boundary data.

[0178] The fifth time interval includes the interval between the detection time of the top shading boundary data and the adjacent waist shading amount data. The sixth time interval includes the interval between the detection time of the waist shading amount data and the detection time of the adjacent boundary shading amount data. The number of first-region shading amount data is the number of region shading amount data detected within the fifth time interval, and the number of second-region shading amount data is the number of region shading amount data detected within the sixth time interval. The ratio between the number of first-region shading amount data and the number of second-region shading amount data is a preset ratio, which can be determined as 1, 2, etc. based on the shape of the tab.

[0179] The top shading data set is determined based on the boundary shading data and the waist shading data, which can determine the top width area of ​​the tab and perform height direction detection, thereby improving the accuracy of height direction detection; the corresponding top shading data sets can be determined for a variety of tabs through preset ratios, which can be applicable to a variety of tabs, reducing parameter adjustment costs and improving detection efficiency.

[0180] For example, as shown in Figure 8A, all solid points in the fitting curve 051 represent the entire data set for the tab area shading dataset. The two boundary shading data sets correspond to the two data points in the fitting curve 051 at sampling time 1 and sampling time 39, i.e., the two data points enclosed by two boxes. The two circled area shading data sets in the fitting curve 051 are determined to be the two waist shading data sets, i.e., the two waist shading data sets corresponding to sampling time 6 and sampling time 34.

[0181] Set the preset ratio to 1, and determine two top shading boundary data in the fitting curve 051, so that the number of regional shading amount data between sampling time 1 and sampling time 6 = the number of regional shading amount data between sampling time 6 and the sampling time corresponding to one top shading boundary data, and the number of regional shading amount data between sampling time 34 and sampling time 39 = the number of regional shading amount data between sampling time 34 and the sampling time corresponding to another top shading boundary data.

[0182] In fitting curve 051, two regional shading data points corresponding to sampling times 11 and 29 are identified as the two top shading boundary data points. Each of these top shading boundary data points is framed by two diamond-shaped boxes. In fitting 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. Furthermore, a waist shading data point corresponding to sampling time 6 is adjacent to a top shading data point corresponding to sampling time 11.

[0183] The number of regional shading data in the interval (sixth time interval) between the sampling moment 6 (corresponding to a waist shading data) and the sampling moment 1 (corresponding to an adjacent boundary shading data) in the fitting curve 051 is 4, that is, the number of second regional shading data is 4; the number of regional shading data in the interval (fifth time interval) between the sampling moment 6 (corresponding to a waist shading data) and the sampling moment 11 (corresponding to an adjacent top shading data) is also 4, that is, the number of first regional shading data is 4, and the preset ratio between the number of first regional shading data and the number of second regional shading data is 1.

[0184] In the fitting curve 051, another waist shading amount data corresponding to the sampling time 34 is adjacent to another boundary shading amount data corresponding to the sampling time 39, and another waist shading amount data corresponding to the sampling time 34 is adjacent to another top shading amount data corresponding to the sampling time 29.

[0185] The number of regional shading data in the interval (sixth time interval) between the sampling moment 34 (corresponding to another waist shading data) and the sampling moment 39 (corresponding to another boundary shading data) in the fitting curve 051 is 4, that is, the number of second regional shading data is 4; the number of regional shading data in the interval (fifth time interval) between the sampling moment 34 (corresponding to another waist shading data) and the sampling moment 29 (corresponding to another top shading data) is 4, that is, the number of first regional shading data is 4, and the ratio between the number of first regional shading data and the number of second regional shading data is 1.

[0186] As shown in Figure 8B, all solid points in the fitting curve 053 represent the entire data set for the tab area shading dataset. The two boundary shading data sets, i.e., the two data points enclosed by two boxes, correspond to the two data points in the fitting curve 053 at sampling time 1 and sampling time 56, respectively. The two circled area shading data sets in the fitting curve 053 are determined to be the two waist shading data sets, corresponding to sampling time 7 and sampling time 50.

[0187] When it is determined that the pole ear corresponding to the fitting curve 053 is the last pole ear, two top shading boundary data are determined in the fitting curve 053, and the preset multiple is 2, so that twice the number of regional shading amount data between the sampling time 1 and the sampling time 7 = the number of regional shading amount data between the sampling time 7 and the sampling time corresponding to one top shading boundary data; the preset multiple is 1, and the number of regional shading amount data between the sampling time 50 and the sampling time 56 = the number of regional shading amount data between the sampling time 50 and the sampling time corresponding to the other top shading boundary data.

[0188] In fitting curve 053, two regional shading data points corresponding to sampling time 19 and sampling time 44 are determined as two top shading boundary data points. The two top shading boundary data points are respectively framed by two diamond-shaped boxes. In fitting curve 053, the number of regional shading data points between sampling time 1 (corresponding to one boundary shading data point) and sampling time 7 (corresponding to one waist shading data point) is 5, i.e., the number of second regional shading data points is 5. The number of regional shading data points between sampling time 7 (corresponding to one waist shading data point) and sampling time 19 (corresponding to one top shading data point) is 10, i.e., the number of first regional shading data points is 10. The ratio between the number of first regional shading data points and the number of second regional shading data points is 2.

[0189] The number of regional shading data between the sampling moment 56 (corresponding to another boundary shading data) and the sampling moment 50 (corresponding to another waist shading data) in the fitting curve 053 is 5, that is, the number of second regional shading data is 5; the number of regional shading data between the sampling moment 50 (corresponding to another waist shading data) and the sampling moment 44 (corresponding to another top shading data) is 5, that is, the number of first regional shading data is 5, and the ratio between the number of first regional shading data and the number of second regional shading data is 1.

[0190] As shown in FIG8A , the light shielding amount data in the two areas enclosed by diamonds in the fitting curve 051 are determined to be the two top light shielding boundary data, and the two top light shielding boundary data correspond to sampling time 11 and sampling time 29. The time interval between the acquisition data of the two top light shielding boundary data is the time interval between sampling time 11 and sampling time 29. The light shielding amount data of the area between sampling time 11 and sampling time 29 in the fitting curve 051 (the detection time is within the fourth time interval) is obtained as the top light shielding amount data, and a top light shielding data set is generated, including the top light shielding amount data and the two top light shielding boundary data (the light shielding amount data of the area corresponding to sampling time 11 and sampling time 29).

[0191] As shown in FIG8B , the two regional shading amount data enclosed by diamonds in the fitting curve 053 are determined to be the two top shading boundary data, and the two top shading boundary data correspond to sampling time 19 and sampling time 44. The time interval between the acquisition data of the two top shading boundary data is the time interval between sampling time 19 and sampling time 44. The regional shading amount data between the sampling time 19 and sampling time 44 in the fitting curve 053 (the detection time is within the fourth time interval) is obtained as the top shading amount data, and a top shading data set is generated, including the top shading amount data and the two top shading boundary data (the regional shading amount data corresponding to sampling time 19 and sampling time 44).

[0192] In step S603 , height direction detection is performed according to the theoretical shading amount and the shading amount threshold and based on the top shading data set.

[0193] By using the theoretical shading amount, shading amount threshold, and top shading data set to perform height direction detection, height direction detection can be performed based on the outer contour information of the tab, which can improve the accuracy of height direction detection and reduce the occurrence of missed detection, excessive detection, etc.

[0194] In some embodiments, a 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, an abnormality in the height shading fitting formula is determined. The difference threshold can be set, for example, to 10% of the theoretical shading amount.

[0195] A light shielding threshold is determined based on the theoretical light shielding amount and a preset light shielding difference threshold. For example, the light shielding difference threshold can be set to 2%, 3%, 5%, etc. of the theoretical light shielding amount, and the difference between the theoretical light shielding amount and the light shielding difference threshold is used as the light shielding threshold. If the light shielding amount of one or more data in the top light shielding data set is less than the light shielding threshold, it is determined that the tab height is abnormal and the tab is folded.

[0196] For example, as shown in Figure 8A, the data in the top shading data set include the regional shading amount data (top shading amount data) located in the fitting curve 051, located between the sampling time 11 and the sampling time 29, and two top shading boundary data (regional shading amount data corresponding to the sampling time 11 and the sampling time 29).

[0197] The difference threshold can be set according to the shape and specifications of the tab. The maximum shading amount is determined among the shading amounts of all the data in the top shading data set. When the difference between the theoretical shading amount and the maximum shading amount is greater than the preset difference threshold, it is determined that the height shading fitting formula is abnormal and a related alarm message is issued. When the shading amount of one or more data in the top shading data set is less than the shading amount threshold, it is determined that the tab height is abnormal and the tab is folded.

[0198] In some embodiments, data quality testing is performed on the light intensity detection data to ensure that the light intensity detection data meets data quality requirements. Before performing the tab quality test, a quality analysis can be performed on the light intensity detection data according to the data quality requirements to obtain a quality analysis result. If the quality analysis result meets the data quality requirements, a tab quality test is performed based on the light detection data to obtain a quality test result.

[0199] For example, data features such as the length of the light intensity detection data, the data range error (data range error) of the light intensity detection data, and the data standard deviation (arithmetic square root of the data variance) of the light intensity detection data are extracted. The data quality requirement is that the length, range, standard deviation, and other data features are less than the corresponding feature thresholds. A determination is made as to 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.

[0200] If one or more data features exceed the corresponding data feature threshold, it is determined that the light intensity detection data does not meet the data quality requirements, and an alarm is issued or an investigation is carried out; if all data features do not exceed the corresponding feature threshold, it is determined that the light intensity detection data meets the data quality requirements, and the tab quality test can be carried out.

[0201] By extracting data features such as length, range, standard deviation, etc. of light intensity detection data and performing threshold judgment, it is possible to determine whether the data quality is normal, eliminate missed detection, over-detection, etc. caused by abnormal data, improve the accuracy of light intensity detection data, and improve the accuracy of lug quality detection.

[0202] In some embodiments, as shown in Figure 11, the electrode piece 750 can be a cathode electrode piece, an anode electrode piece, etc. In the process of the electrode piece 750 passing between the light emitting device 740 and the light receiving device 710, the electrode ear 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, which includes multiple light intensity detection data.

[0203] The data acquisition device 760 receives the optical detection data sent by the optical receiving device 710, and 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 in this disclosure is applied to the tab detection device 780.

[0204] The data acquisition device 760 can be an edge data acquisition box, etc., and the target device 790 can be a winding machine, etc., which performs winding processing on the electrode 750. The PLC (Programmable Logic Controller) of the target device 790 can send start and stop signals to the data acquisition device 760. The data acquisition device 760 sends a control signal to the light receiving device 710 based on the start and stop signals. The light receiving device 710 starts or stops sampling the detection light 720 according to the control signal and detects the light intensity value of the sampled detection light 720.

[0205] Light receiving device 710 transmits the light intensity detection data to data acquisition device 760, which can forward the light intensity detection data via an intermediate device such as a message server 770. Tab detection device 780 can parse the network address of message server 770 from locally stored configuration information and, based on the network address, send a data request to message server 770 to obtain light intensity time series data.

[0206] Message server 770 can be a server such as MQTT (Message Queuing Telemetry Transport). Tab detection device 780 uses a protocol such as MQTT to send a data request for obtaining light intensity time series data to the network address of message server 770. By using data acquisition device 760 and message server 770, the flexibility of obtaining light intensity detection data can be effectively improved.

[0207] The tab detection device 780 can subscribe to the two topics of the MQTT server "CATHODE (cathode)" and "ANODE (anode)" in real time to obtain the optical inspection data of the cathode and anode pole pieces during the winding process, and perform tab quality inspection based on the optical inspection data. The tab detection device 780 performs tab quality inspection after receiving the light intensity detection data sent by the message server 770, and sends the abnormal detection results to the target device 790. The target device 790 can display the abnormal detection results, and the staff can issue an alarm and discharge waste based on the abnormal detection results displayed by the target device 790. By sending abnormal prompt information and alarm information to the target device 790 when a detection abnormality occurs, the staff can take effective measures in a timely manner to prevent the occurrence of production accidents.

[0208] The tab detection device 780 can simultaneously perform tab quality inspection based on the light intensity detection data corresponding to the anode and cathode pole pieces. The tab detection device 780 can generate light intensity fitting curves for the anode and cathode pole pieces based on the light intensity values ​​and detection times in the light intensity detection data, as shown in Figure 12. Based on the light intensity fitting curves, the tab profile information can be determined, and the light intensity fitting curves can be approximately considered as the tab profile information.

[0209] In some embodiments, the test result display process is performed based on the quality inspection results. For example, when the quality inspection result is abnormal, abnormal prompt color information and abnormal prompt information are determined, and prompt processing is performed based on the abnormal prompt color information and / or abnormal prompt information. Abnormalities include abnormal number of tabs, abnormal tab width, abnormal tab height, abnormal fitting formula, etc. The abnormal prompt information includes abnormal detection category information, or abnormal detection category information and information about the tab where the abnormality occurs. When an abnormality occurs, operations such as pausing the quality inspection process can also be performed.

[0210] A prompt mark and an abnormality display area can be set in the display interface displayed by the tab detection device 780. When the detection result is abnormal, the abnormality prompt color information is determined. For example, when the abnormality is an abnormal number of tabs, an abnormal tab width, an abnormal tab height, an abnormal fitting formula, etc., the abnormality prompt color can be set to red, orange, blue, green, etc., and the prompt mark is controlled to display the set abnormality prompt color for alarm and prompt.

[0211] When an abnormality occurs, the detection category and tab information of the abnormality are set based on the abnormality. For example, if the abnormality is an abnormal number of tabs, the detection category information is set to "Tab Quantity Detection" and the abnormal tab information is set to "Two Tabs Missing". The set detection category information and abnormal tab information are displayed in the abnormality display area for alarm and prompt. The abnormality prompt color information and abnormality prompt information can be set for different abnormalities, and prompt processing can be carried out. This allows staff to quickly obtain abnormal information and take effective measures in a timely manner to prevent production accidents.

[0212] If the quality inspection result is abnormal, an abnormality prompt message and / or alarm message is 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. If the quality inspection result is abnormal in the number of tabs, the width of the tabs, the height of the tabs, or the fitting formula, corresponding prompt messages and alarm messages are generated based on the abnormality.

[0213] For example, when the abnormality is an abnormal number of tabs, the generated alarm message is "Cathode tab number detection abnormality" and the prompt message is "Please check whether the cathode electrode is missing a tab." The alarm message and prompt message are sent to the target device 790, alerting the staff and prompting them to investigate. By sending the abnormality prompt message and alarm message to the target device 790 used to process the detection target when an abnormality occurs, the staff can take effective measures in a timely manner to prevent the occurrence of production accidents.

[0214] In some embodiments, a display interface including a first area is presented in response to a detection instruction triggered by a detection control in the first area, acquiring optical inspection data of the detection target. Tab quality inspection is performed based on the optical inspection data to obtain a quality inspection result for the tab. The display interface may be a GUI interface, etc., and may be displayed in a device such as a tab inspection apparatus. The display interface includes a second area, and in response to the detection instruction, the second area is displayed on the display interface, and the detection result display processing is performed in the second area based on the quality inspection result.

[0215] As shown in Figure 13, the display interface includes a first area 071. The inspection controls in this area include multiple buttons, including a home button, a real-time profile button, a historical data button, a parameter setting button, a model query button, and a permission setting button. The home button is used to compile historical quality inspection results; the real-time profile button is used to perform tab quality inspections and display real-time tab inspection results. The historical data button is used to trace historical inspection data and display historical tab profiles.

[0216] The parameter setting button is used to query and set threshold parameters to facilitate quality control. Threshold parameters include ratio thresholds, difference thresholds, and more. Different parameters can be used for different types of tabs, adapting to the detection of multiple tab models, reducing parameter adjustment costs and improving detection 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 control user access to various functions.

[0217] In response to a detection command triggered by a user clicking the Real-Time Contour button, optical inspection data of the detection target is acquired. The optical inspection data includes multiple light intensity detection data, including light intensity values ​​and the time of detection of the light intensity values. Based on the optical inspection data, a tab quality inspection is performed to obtain a quality inspection result for the tab. In response to a detection command triggered by a user clicking the Real-Time Contour button, a second area 072 is displayed on the display interface, and the inspection result is displayed in the second area 072 based on the quality inspection result.

[0218] The connection status of the winding machine and the acquisition card can be displayed in real time at the top of the display interface. When an abnormality occurs in the winding machine or the acquisition card, an alarm will be triggered. When the quality inspection result is abnormal, the abnormal prompt color information and abnormal prompt information are determined. The abnormal prompt information includes abnormal detection category information, or abnormal detection category information and abnormal tab information, etc. The abnormal prompt mark and abnormal display area are displayed in the second area. The color of the prompt mark in the second area is controlled based on the abnormal prompt color information, and the abnormal prompt information is displayed in the abnormal display area. Abnormalities include abnormal number of tabs, abnormal width of tabs, abnormal height of tabs, abnormal fitting formula, etc. Abnormal width of tabs and abnormal height of tabs are both tab folding abnormalities.

[0219] As shown in FIG13 , prompt marks are displayed in second region 072, including an anode prompt mark 074 and a cathode prompt mark 075. Also provided in second region 072 are an anode abnormality display region 077 and a cathode abnormality display region 078. When the quality inspection result indicates an abnormality in the anode or cathode tab, such as an abnormal number of tabs, an abnormal tab width, an abnormal tab height, or an abnormal fitting formula, different abnormality prompt colors are determined based on the abnormality, and the colors of anode prompt mark 074 and cathode prompt mark 075 are controlled based on the abnormality prompt colors.

[0220] For example, when the inspection results of the anode tab and cathode tab are both normal, the colors of the anode prompt mark 074 and the cathode prompt mark 075 are controlled to color A. When the quality inspection result shows that the anode tab height is abnormal, the abnormal prompt color information is determined to be color B, and the color of the anode prompt mark 074 is controlled to color B.

[0221] If the quality inspection result indicates an abnormal anode tab height, the abnormality prompt information is determined to include the abnormality detection category information and information about the tab where the abnormality occurred. The abnormality prompt information is displayed in the anode abnormality display area 077. The abnormality detection category information is "tab folded." The abnormal tab information includes "20th tab" and the tab outline information of the 20th tab. A cathode abnormality display area 078 can be set in the second area 072. If the cathode tab detection does not indicate an abnormality, no information is displayed in the cathode abnormality display area 078.

[0222] For different abnormalities, abnormal prompt color information and abnormal prompt information can be set to perform prompt processing, which can enable staff to quickly obtain abnormal information and take effective measures in time to prevent the occurrence of production accidents.

[0223] An anode detection display area 073 is provided in the second area 072 to display 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, Normal number of tabs: 29". If the number of anode tabs is determined to be incorrect, the anode detection display area 073 displays the incorrect information "Number of missing tabs: 1".

[0224] 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 provided in the second area 072, and a contour curve and a light intensity fitting curve of the anode tab can be displayed in the data display area 076. For example, after the light intensity fitting curve and the contour fitting curve of the anode tab are generated, the light intensity fitting curve and the contour fitting curve of the anode tab can be displayed in the data display area 076.

[0225] Figure 14 is a block diagram of some embodiments of a tab detection device according to the present disclosure. As shown in Figure 14 , the tab detection device may include a memory 801, a processor 802, a communication interface 803, and a bus 804. Memory 801 is used to store instructions, and processor 802 is coupled to memory 801. Processor 802 is configured to execute the aforementioned tab detection method based on the instructions stored in memory 801.

[0226] Memory 801 can be a high-speed RAM memory, non-volatile memory, etc. Memory 801 can also be a memory array. Memory 51 can also be divided into blocks, and the blocks can be combined into virtual volumes according to certain rules. 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 the present disclosure.

[0227] In some embodiments, the present disclosure provides a tab detection system, including the tab detection device of any of the above embodiments, which can perform the tab detection method of any of the above embodiments. The tab detection system can also include other devices, such as a light emitting device, a light receiving device, etc.

[0228] As shown in FIG15A , the present disclosure provides a tab detection system, comprising a light emitting device 910, a light receiving device 920, and a tab detection device 930. When a detection target, such as a pole piece, passes between the light emitting device 910 and the light receiving device 920, the light generating device 910 emits detection light that is irradiated on the detection target; the light receiving device 920 samples and detects the received detection light, obtains the light intensity value and detection time of the sampled detection light, and generates light detection data; the tab detection device 930 obtains the light detection data and performs tab quality detection based on the light detection data. The tab detection device 930 can obtain the light detection data in a variety of ways. For example, the tab detection device 930 can receive light detection data sent by the light receiving device 920, or it can receive light detection data sent by other devices.

[0229] In some embodiments, as shown in Figure 15B, the tab detection system also includes a data acquisition device 940 and a message server 950; the data acquisition device 940 receives the 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 tab detection device 930.

[0230] The data acquisition device 940 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. The target device is used to process the detection target, and the target device can be a winding machine, etc.

[0231] Based on the start or stop signals sent by the target device, the data acquisition device 940 controls the light receiving device 920 to start or stop sampling the test light and detect the intensity of the sampled test light. The data acquisition device can be linked with the target device to synchronize quality inspection with the target device's processing of the test target, ensuring product quality.

[0232] In some embodiments, the present disclosure provides a computer-readable storage medium storing computer instructions, and the instructions are executed by a processor to execute the method in any of the above embodiments.

[0233] Computer readable storage media can adopt any combination of one or more readable media. The readable medium can be a readable signal medium or a readable storage medium. The readable storage medium can, for example, include but is not limited to a system, device or component of electricity, magnetism, light, electromagnetic, infrared, or semiconductor, or any combination thereof. More specific examples (non-exhaustive enumeration) of readable storage media can include: an electrical connection with one or more wires, a portable disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof.

[0234] The present disclosure is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems) and computer program products according to the embodiments of the present disclosure. It should be understood that each process and / or box in the flowchart and / or block diagram and the combination of the processes and / or boxes in the flowchart and / or block diagram can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate a device for implementing the functions specified in one or more processes in the flowchart and / or one or more boxes in the block diagram.

[0235] The methods and systems of the present disclosure may be implemented in many ways. For example, the methods and systems of the present disclosure may be implemented by software, hardware, firmware, or any combination of software, hardware, and firmware. The above order of steps for the method is for illustration only, and the steps of the method of the present disclosure are not limited to the order specifically described above unless otherwise specified. In addition, in some embodiments, the present disclosure may also be implemented as programs recorded in a recording medium, which include machine-readable instructions for implementing the methods according to the present disclosure. Therefore, the present disclosure also covers recording media that store programs for executing the methods according to the present disclosure.

[0236] While the present disclosure has been described with reference to preferred embodiments, various modifications may be made thereto and equivalent components may be substituted without departing from the scope of the present disclosure. In particular, the various technical features described in the various embodiments may be combined in any manner, provided no structural conflicts exist. The present disclosure is not limited to the specific embodiments disclosed herein, but encompasses all technical solutions within the scope of the claims.

Claims

1. A method for detecting a tab, comprising: Acquire optical inspection data of the inspection target; Wherein, the detection target has at least one pole ear; when the detection target passes between the light emitting device and the light receiving device, the light receiving device samples the detection light emitted by the light generating device and detects the light intensity value of the sampled detection light; the light detection data includes: a plurality of light intensity detection data; the light intensity detection data includes: the light intensity value and the detection time of the light intensity value; The quality inspection of the tab is performed based on the optical inspection data to obtain a quality inspection result of the tab.

2. The method according to claim 1, wherein the tab quality detection comprises: Tab quantity detection; The light intensity value includes: the light intensity value of the detection light blocked or not blocked by the tab; the tab quality detection based on the light detection data includes: Performing the pole lug quantity detection based on the optical inspection data to obtain the pole lug detection quantity; Obtaining a preset number of tabs of the detection target; Whether the number of the tabs is correct is determined based on the detected number of tabs and the preset number of tabs.

3. The method according to claim 2, wherein the step of performing the detection of the number of tabs based on the optical detection data to obtain the number of tabs detected comprises: Determining a regional light intensity threshold based on the light intensity value of the light intensity detection data in the light detection data; The number of tab detections is determined according to the light detection data and the regional light intensity threshold.

4. The method according to claim 3, wherein determining the number of tab detections according to the light detection data and the regional light intensity threshold comprises: Based on the light intensity detection data in the light detection data, generating a light intensity fitting curve; According to the regional light intensity threshold, two regional discrimination points of the pole ear are determined in the light intensity fitting curve; wherein the light intensity value of the regional discrimination point is the same as the regional light intensity threshold; The number of tab detections is determined according to the total number of area discrimination points of all tabs.

5. The method according to claim 3, wherein determining the regional light intensity threshold based on the light intensity value of the light intensity detection data in the light detection data comprises: Acquire all light intensity detection data in the light detection data; Calculate the light intensity average value of the light intensity values ​​of all the light intensity detection data; The light intensity average value is used as the regional light intensity threshold.

6. The method according to claim 2, wherein determining whether the number of tabs is correct according to the detected number of tabs and the preset number of tabs comprises: When the detected number of pole tabs is equal to the preset number of pole tabs, determining that the number of pole tabs is correct; and, When the detected number of pole tabs is not equal to the preset number of pole tabs, it is determined that the number of pole tabs is abnormal.

7. The method according to claim 4, wherein the tab quality detection comprises: Folding detection; The lug quality detection based on the optical inspection data comprises: Based on the two regional discrimination points of the pole lug and the light intensity fitting curve, a regional detection data set of the pole lug is obtained in the light detection data; The fold detection is performed according to the area detection data set.

8. The method according to claim 7, wherein obtaining the region detection data set of the tab from the light detection data based on the two region discrimination points of the tab and the light intensity fitting curve comprises: Taking the two region discrimination points as starting points respectively and respectively along the rising direction of the light intensity fitting curve, a search process is performed on the light intensity fitting curve to obtain two region boundary points of the pole ear; Wherein, during the search process, when it is determined for the first time that 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, the light intensity detection data is used as the area boundary point; In the light detection data, the light intensity detection data whose detection time is within the first time interval is used as the regional light intensity detection data; The first time interval includes: the time interval between the detection times of the two area boundary points; Generate the regional detection data set, wherein the regional detection data set includes: the regional light intensity detection data and the two regional Domain boundary point.

9. The method according to claim 8, wherein performing the fold detection according to the area detection data set comprises: Generate a corresponding regional shading dataset based on the regional detection dataset; The regional shading data set includes: regional shading amount data corresponding to each data in the regional detection data set; the regional shading amount data includes: shading amount and the detection time corresponding to the shading amount; The fold detection is performed according to the regional shading data set.

10. The method of claim 9, wherein: Determine the maximum regional light intensity value among the light intensity values ​​of all data in the regional detection data set; The light shielding amount is determined according to the light intensity value of the data in the regional detection data set and the regional light intensity maximum value.

11. The method according to claim 9, wherein the fold detection comprises: Width direction detection; The performing the fold detection according to the regional shading data set comprises: In the regional shading data set, determining the shading amount change information of each of the regional shading amount data; Based on the shading amount change information, determining the shading amount data of two waists of the pole ear in the regional shading data set; In the regional shading data set, two shading amount data corresponding to the two regional boundary points are determined as two boundary shading amount data; The width direction detection is performed based on the two waist light shielding amount data and the two boundary light shielding amount data.

12. The method according to claim 11, wherein the light shielding amount change information comprises: Shading amount change value; The determining of the shading amount change information of the shading amount data of each area includes: The light shielding amount difference between the light shielding amount of each of the regional light shielding amount data and the light shielding amount of the adjacent regional light shielding amount data detected earlier in time is calculated as the light shielding amount change value.

13. The method according to claim 11, wherein determining the shading amount data of two waists of the tab in the regional shading data set based on the shading amount change information comprises: In the regional shading data set, two regional shading amount data are determined based on the maximum value and the minimum value of the shading amount change value as two waist shading amount data.

14. The method according to claim 11, wherein the performing the width direction detection according to the two waist shading amount data and the two boundary shading amount data comprises: Determine a first spacing according to the two waist shading amount data; Determine a second spacing according to the two boundary shading amount data; The width direction detection is performed based on a ratio of the first spacing to the second spacing.

15. The method according to claim 14, wherein the performing the width direction detection based on the ratio of the first spacing to the second spacing comprises: When the ratio is less than a preset ratio threshold, determining that the width of the pole lug is abnormal; and, When the ratio is greater than or equal to the ratio threshold, it is determined that the tab width is normal.

16. The method according to claim 14, wherein determining the first distance according to the two waist shading amount data comprises: The number of regional light shielding data whose detection time is within the second time interval is increased by 2 as the first spacing; The second time interval includes: the time interval between the detection times of the two waist light shielding amount data.

17. The method according to claim 14, wherein determining the second distance according to the two boundary shading amount data comprises: Add 2 to the number of regional light shielding data whose detection time is within the third time interval as the second interval; The third time interval includes: the time interval between the detection times of the two boundary light shielding amount data.

18. The method according to claim 11, wherein the fold detection comprises: Height direction detection; The performing the fold detection according to the regional shading data set comprises: Determining a theoretical shading amount and a shading amount threshold value of the tab; In the regional shading data set, a top shading data set is determined based on the two boundary shading amount data and the two waist shading amount data; The height direction detection is performed according to the theoretical shading amount and the shading amount threshold and based on the top shading data set.

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

20. The method of claim 19, further comprising: Obtain experimental data on the height and shading of various tabs; The height and the height shading amount experimental data are fitted to obtain the height shading fitting formula.

21. The method according to claim 18, wherein determining the top shading data set based on the two boundary shading amount data and the two waist shading amount data comprises: In the regional shading data set, two regional shading amount data are determined based on the two boundary shading amount data and the two waist shading amount data as two top shading boundary data; The area shading amount data where the detection time is within the fourth time interval is used as the top shading amount 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 data set; Wherein, the top shading data set includes: the top shading amount data and the top shading boundary data.

22. The method of claim 21, wherein: The ratio between the amount of light shielding data in the first region and the amount of light shielding data in the second region is a preset ratio; The first area shading amount data quantity is the area shading amount data quantity whose detection time is within the fifth time interval, and the fifth time interval includes: the interval between the detection time of the top shading boundary data and the adjacent waist shading amount data; The amount of second area shading data is the amount of area shading data whose detection time is within the sixth time interval, and 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.

23. The method according to claim 18, wherein the performing the height direction detection according to the theoretical shading amount and the shading amount threshold and based on the top shading data set comprises: When the shading amount of at least one data in the top shading data set is less than the shading amount threshold, it is determined that the height of the pole lug is abnormal and that the pole lug is folded.

24. The method of claim 18, further comprising: Determine a maximum shading amount among the shading amounts of all data in the top shading data set; When the difference between the theoretical shading amount and the maximum shading amount is greater than a preset difference threshold, it is determined that the height shading fitting formula is abnormal.

25. The method according to any one of claims 1 to 24, further comprising: Presenting a display interface including a first area; acquiring the optical inspection data in response to a detection instruction triggered based on a detection control in the first area; 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.

26. The method according to claim 25, wherein the step of displaying the detection result in the second area according to the quality detection result comprises: When the quality inspection 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 abnormal tab information; Displaying the abnormal prompt mark and / or abnormal display area in the second area; Based on the abnormal prompt color information, the color of the prompt mark located in the second area is controlled, and / or the abnormal prompt information is displayed in the abnormal display area.

27. The method of claim 25, further comprising: When the quality detection result is abnormal, sending abnormal prompt information and / or alarm information to the target device; Wherein, the target device is used to process the detection target.

28. The method according to any one of claims 1 to 24, wherein: The detection light includes: linear detection light and strip detection light; The time intervals between two detection times that are adjacent in time are the same.

29. A tab detection device, comprising: Memory; and a processor coupled to the memory, wherein the processor is configured to execute the method according to any one of claims 1 to 28 based on instructions stored in the memory.

30. A tab detection system, comprising: A light emitting device, a light receiving device and a tab detection device as claimed in claim 29; Wherein, in the process of the 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 light detection data; the tab detection device performs tab quality detection based on the light detection data.

31. The system of claim 30, wherein: The detection light includes: linear detection light and strip detection light; when the detection target passes between the light emitting device and the light receiving device, the center line of the pole ear is parallel to the linear detection light and the strip detection light.

32. The system of claim 30 or 31, further comprising: Data collection device and message server; The data acquisition device receives the optical detection data sent by the optical receiving device; The message server obtains the optical inspection data from the data acquisition device and sends it to the tab detection device.

33. The system of claim 32, wherein: The data acquisition device controls the light receiving device to start or stop sampling and detecting the received 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.

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