Abnormality detection method and adjustable light source detection device

Abstract

The embodiments of this specification provide an abnormality detection method and an adjustable light source detection device, wherein the abnormality detection method comprises: acquiring a target image through a camera unit of the adjustable light source detection device, and determining an image processing rule for the target image; inputting the target image into a processing unit of the adjustable light source detection device, and performing a mark line recognition on the target image according to the image processing rule by the processing unit, and determining a recognition result; wherein the processing unit comprises a ZYNQ chip; and determining an abnormality according to the recognition result. Acquiring a target image through a camera unit of the adjustable light source detection device, and determining an image processing rule for the target image; inputting the target image into a processing unit of the adjustable light source detection device with a ZYNQ chip, and performing a mark line recognition on the target image according to the image processing rule by the processing unit, and determining a recognition result; and determining an abnormality according to the recognition result, thereby improving the precision and accuracy of detection.

Description

Technical Field

[0001] The embodiments of this specification relate to the field of image detection technology, and in particular to anomaly detection methods. Background Art

[0002] In the prior art, the detection device is supplemented with light by an external adjustable light source, or by a built-in non-adjustable light source (similar to the light source of the camera on a mobile phone, which is built-in but the brightness is not adjustable). This method of using an external light source will make the device more complicated, which is not conducive to on-site installation and debugging. The built-in non-adjustable light source will cause instability in image recognition or even inaccurate recognition. Summary of the invention

[0003] In view of this, the embodiments of this specification provide an anomaly detection method. One or more embodiments of this specification also relate to an anomaly detection device, a computing device, a computer-readable storage medium and a computer program to solve the technical defects existing in the prior art.

[0004] According to a first aspect of an embodiment of this specification, there is provided an anomaly detection method, comprising:

[0005] Acquire a target image through a camera unit of the adjustable light source detection device, and determine an image processing rule for the target image;

[0006] Input the target image into the processing unit of the adjustable light source detection device, and perform marker line recognition on the target image according to the image processing rule by the processing unit to determine the recognition result; wherein the processing unit includes a ZYNQ chip;

[0007] Determine the abnormal situation based on the recognition results.

[0008] In a possible implementation, the image processing rules include yellow glue image processing rules, V-angle processing rules and tab processing rules.

[0009] According to a second aspect of the embodiments of this specification, there is provided an adjustable light source detection device, characterized in that it includes a ZYNQ chip, a camera unit and an output interface;

[0010] The camera unit is connected to the ZYNQ chip for communication;

[0011] The output interface is communicatively connected with the output interface;

[0012] The camera unit is used to obtain a target image;

[0013] The ZYNQ chip is used to perform marker line recognition on the target image, determine the recognition result, and send the recognition result to the controller through the output interface.

[0014] In a possible implementation, the camera unit includes a driven area array CCD unit or a CMOS unit.

[0015] In a possible implementation, it also includes an indicator light, a setting panel, an Ethernet interface, a storage unit, and a display interface.

[0016] In a possible implementation, the setting panel includes a light source channel unit and a brightness selection unit.

[0017] In a possible implementation, the display interface is at least one of an HDMI interface, a Type-C interface, and a DP interface.

[0018] According to a third aspect of an embodiment of this specification, there is provided an abnormality detection device, including:

[0019] An image acquisition module is configured to acquire a target image through a camera unit of the adjustable light source detection device and determine an image processing rule for the target image;

[0020] The image recognition module is configured to input the target image into the processing unit of the adjustable light source detection device, and perform marker line recognition on the target image according to the image processing rule through the processing unit to determine the recognition result; wherein the processing unit includes a ZYNQ chip;

[0021] The abnormality determination module is configured to determine the abnormal situation according to the recognition result.

[0022] According to a fourth aspect of an embodiment of this specification, a computing device is provided, including:

[0023] Memory and processor;

[0024] The memory is used to store computer executable instructions, and the processor is used to execute the computer executable instructions. When the computer executable instructions are executed by the processor, the steps of the above-mentioned abnormality detection method are implemented.

[0025] According to a fifth aspect of the embodiments of this specification, a computer-readable storage medium is provided, which stores computer-executable instructions, and when the instructions are executed by a processor, the steps of the above-mentioned abnormality detection method are implemented.

[0026] According to a sixth aspect of the embodiments of this specification, a computer program is provided, wherein when the computer program is executed in a computer, the computer is caused to execute the steps of the above-mentioned anomaly detection method.

[0027] The embodiments of this specification provide an abnormality detection method and an adjustable light source detection device, wherein the abnormality detection method comprises: acquiring a target image through a camera unit of an adjustable light source detection device, and determining an image processing rule for the target image; inputting the target image into a processing unit of the adjustable light source detection device, and performing a mark line recognition on the target image according to the image processing rule by the processing unit, and determining a recognition result; wherein the processing unit comprises a ZYNQ chip; and determining an abnormality according to the recognition result. Acquiring a target image through a camera unit of an adjustable light source detection device, and determining an image processing rule for the target image; inputting the target image into a processing unit of an adjustable light source detection device with a ZYNQ chip, and performing a mark line recognition on the target image according to the image processing rule by the processing unit, and determining a recognition result; and determining an abnormality according to the recognition result, thereby improving the precision and accuracy of detection. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] Figure 1 is a flow chart of an anomaly detection method provided by an embodiment of this specification;

[0029] Figure 2 is a flow chart of an anomaly detection method provided by an embodiment of this specification;

[0030] Figure 3 It is a schematic diagram of an adjustable light source detection device of an abnormality detection method provided by an embodiment of this specification;

[0031] Figure 4 is a structural schematic diagram of an abnormality detection device provided by an embodiment of this specification;

[0032] Figure 5 It is a structural block diagram of a computing device provided by an embodiment of this specification. DETAILED DESCRIPTION

[0033] Many specific details are described in the following description to facilitate a full understanding of this specification. However, this specification can be implemented in many other ways than those described herein, and those skilled in the art can make similar generalizations without violating the connotation of this specification, so this specification is not limited to the specific implementation disclosed below.

[0034] The terms used in one or more embodiments of this specification are only for the purpose of describing specific embodiments, and are not intended to limit one or more embodiments of this specification. The singular forms of "a" and "the" used in one or more embodiments of this specification and the appended claims are also intended to include plural forms, unless the context clearly indicates other meanings. It should also be understood that the term "and / or" used in one or more embodiments of this specification refers to and includes any or all possible combinations of one or more associated listed items.

[0035] It should be understood that although the terms first, second, etc. may be used to describe various information in one or more embodiments of this specification, this information should not be limited to these terms. These terms are only used to distinguish the same type of information from each other. For example, without departing from the scope of one or more embodiments of this specification, the first may also be referred to as the second, and similarly, the second may also be referred to as the first. Depending on the context, the word "if" as used herein may be interpreted as "at the time of" or "when" or "in response to determining".

[0036] First, the terms involved in one or more embodiments of this specification are explained.

[0037] ZYNQ is a fully programmable system-on-chip.

[0038] Currently, there are ARM-driven linear array CCD solutions, FPGA-driven linear array CCD, ARM data interaction solutions, and FPGA-driven area array CCD, ARM data interaction solutions.

[0039] Among them, the ARM-driven linear CCD solution has a small size and simple driving. The image provided by the linear CCD is a single-line image, and the pixel data of the single-line image is also relatively small, which is suitable for processing occasions with obvious marking lines. The field of view is less than 10mm, the accuracy is greater than 0.1mm, and the frame rate is ≤500Hz. The FPGA-driven linear CCD and ARM data interaction solution have a relatively large size and relatively complex driving. The image provided by the linear CCD is a single-line image, and the pixel data of the single-line image is rich, which is suitable for processing occasions with obvious marking lines. The field of view is less than 20mm, the accuracy is greater than 0.1mm, and the frame rate is ≤800Hz. The FPGA-driven area CCD and ARM data interaction solution have a relatively large size and relatively complex driving. The image provided by the area CCD is a multi-line image, and the pixel data of the multi-line image is rich, which is suitable for processing occasions with obvious and inconspicuous marking lines. Due to the rich image information, various algorithms such as ear shielding and V-angle shielding can be processed. The field of view is less than 20mm, the accuracy is greater than 0.1mm, and the frame rate is ≤400Hz. However, these solutions cannot achieve high accuracy due to the limited processing capacity due to the small amount of image information collected.

[0040] Based on this, in this specification, an anomaly detection method is provided. This specification also relates to an anomaly detection device, a computing device, and a computer-readable storage medium, which are described in detail one by one in the following embodiments.

[0041] See also Figure 1 , Figure 1 A schematic diagram of a scenario of an anomaly detection method provided according to an embodiment of the present specification is shown.

[0042] exist Figure 1 In the application scenario, the computing device 101 can obtain the target image 102 through the camera unit of the adjustable light source detection device, and determine the image processing rule 103 for the target image; the target image 102 is input into the processing unit of the adjustable light source detection device, and the processing unit performs marker line recognition on the target image 102 according to the image processing rule 103, and determines the recognition result 104; wherein the processing unit includes a ZYNQ chip; and the abnormal situation is determined according to the recognition result 104, as shown by the figure mark 105.

[0043] It should be noted that the computing device 101 can be hardware or software. When the computing device 101 is hardware, it can be implemented as a distributed cluster consisting of multiple servers or terminal devices, or it can be implemented as a single server or a single terminal device. When the computing device 101 is embodied as software, it can be installed in the hardware devices listed above. It can be implemented as multiple software or software modules for providing distributed services, for example, or it can be implemented as a single software or software module. No specific limitation is made here.

[0044] See also Figure 2 , Figure 2 A flowchart of an abnormality detection method provided according to an embodiment of the present specification is shown, which specifically includes the following steps.

[0045] Step 201: acquiring a target image through a camera unit of an adjustable light source detection device, and determining an image processing rule for the target image.

[0046] Step 202: Input the target image into the processing unit of the adjustable light source detection device, and perform marker line recognition on the target image according to the image processing rule by the processing unit to determine the recognition result; wherein the processing unit includes a ZYNQ chip.

[0047] Step 203: Determine the abnormal situation according to the recognition result.

[0048] In a possible implementation, the image processing rules include yellow glue image processing rules, V-angle processing rules and tab processing rules.

[0049] Specifically, the yellow glue image processing rule can be a yellow glue shielding algorithm: the collected image is separated into red, green and blue colors according to the pixels, and the color of the current pixel is determined for each pixel. For the RGB three-color range of 0-255, when the red value is between 200 and 240, the green value is between 200 and 240, and the red value is greater than the blue value by more than 100, when the above conditions are met, the current pixel color can be considered to be yellow. If more than 10 consecutive pixels are yellow, it can be considered that yellow glue has appeared. The normal image color is black on one side of the coating area, and the other side is the original color of the copper foil or the aluminum foil itself. When yellow glue appears, the yellow glue information is transmitted to the controller through CAN communication, and the controller controls the driver to stop the action, thereby shielding the yellow glue; when the above conditions are not met or exceed a certain time (the duration can be set by software), normal mark line search and position output are performed.

[0050] Furthermore, the V-angle processing rule may be a V-angle shielding algorithm: when the material is normally corrected, the marking line will swing left and right at the target position. When the material has a V-angle, the most obvious feature is that the marking line increases or decreases in one direction. When continuous changes in one direction are detected (the number can be set through software), it is considered that a V-angle has appeared, and the V-angle information is transmitted to the controller through CAN communication. The controller controls the drive to stop the action, thereby shielding the V-angle. When the above conditions are not met or exceed a certain time (the duration can be set through software), normal marking line search and position output are performed.

[0051] Furthermore, the tab processing rule can be a tab shielding algorithm: the normal image color is the black of the coated area on one side, and when there is a tab on the other side, it may be the original color of the copper foil or the aluminum foil itself. When there is no tab, there is no material and it appears gray or slightly brighter black than the coated area in the image. When the tab shielding function is turned on, it is determined whether there is a tab by judging the black of the coated area and the color of the other side. When the tab appears, the standard line position data of the tab position and the non-tab position will be sent to the controller through CAN communication.

[0052] The embodiments of this specification provide an abnormality detection method and an adjustable light source detection device, wherein the abnormality detection method comprises: acquiring a target image through a camera unit of an adjustable light source detection device, and determining an image processing rule for the target image; inputting the target image into a processing unit of the adjustable light source detection device, and performing a mark line recognition on the target image according to the image processing rule by the processing unit, and determining a recognition result; wherein the processing unit comprises a ZYNQ chip; and determining an abnormality according to the recognition result. Acquiring a target image through a camera unit of an adjustable light source detection device, and determining an image processing rule for the target image; inputting the target image into a processing unit of an adjustable light source detection device with a ZYNQ chip, and performing a mark line recognition on the target image according to the image processing rule by the processing unit, and determining a recognition result; and determining an abnormality according to the recognition result, thereby improving the precision and accuracy of detection.

[0053] According to the second aspect of the embodiments of this specification, an adjustable light source detection device is provided, characterized in that it includes a ZYNQ chip, a camera unit and an output interface; the camera unit is communicatively connected to the ZYNQ chip; the output interface is communicatively connected to the output interface; the camera unit is used to acquire a target image; the ZYNQ chip is used to perform marker line recognition on the target image, determine the recognition result, and send the recognition result to a controller through the output interface.

[0054] In a possible implementation, the camera unit includes a driven area array CCD unit or a CMOS unit.

[0055] In practical applications, the camera unit may use an area array CMOS or an area array CCD, which is not limited in the embodiments of this specification.

[0056] In one possible implementation, see Figure 3 , also includes indicator lights, setting panel, Ethernet interface, storage unit and display interface.

[0057] Specifically, the indicator light can be an LED indicator light, used to indicate the status of the adjustable light source detection device, the setting panel can be a physical button or a touch screen button, used to set the parameters of the adjustable light source detection device, the Ethernet interface is used for data exchange, and the storage unit is used for file storage, for example, operation logs and other files, and the display interface can display the debugging process.

[0058] In a possible implementation, the setting panel includes a light source channel unit and a brightness selection unit.

[0059] In actual applications, you can choose to set the light source channel and the brightness.

[0060] In a possible implementation, the display interface is at least one of an HDMI interface, a Type-C interface, and a DP interface.

[0061] In practical applications, multiple or one of the connection cables among the HDMI interface, TypeC interface and DP interface can be used to connect the adjustable light source detection device to display the debugging status.

[0062] The embodiment of this specification adopts the solution of ZYNQ driving the area array CCD, which makes the image information richer, the improvement of computing power makes the frame rate higher, and the algorithm richer. In abnormal situations (yellow glue, V angle, and ear), the marking line can be better and more stably identified. In addition, the adjustable light source is integrated internally, and the ZYNQ driving the area array CCD makes it small in size, high in computing power, rich in algorithms, and supports HDMI interface, making debugging easier and interaction easier.

[0063] In practical applications, the above solution solves the problem of better and more stable identification of the marking line in abnormal situations, such as yellow glue, V-angle, and ear. Due to the higher output frame rate, the subsequent correction accuracy is higher, from the original ≤0.2mm to ≤0.1mm.

[0064] Corresponding to the above method embodiment, this specification also provides an abnormality detection device embodiment, Figure 4 FIG. 2 shows a schematic diagram of the structure of an abnormality detection device provided by an embodiment of the present specification. Figure 4 As shown, the device comprises:

[0065] According to a third aspect of an embodiment of this specification, there is provided an abnormality detection device, including:

[0066] The image acquisition module 401 is configured to acquire a target image through a camera unit of the adjustable light source detection device and determine an image processing rule for the target image;

[0067] The image recognition module 402 is configured to input the target image into the processing unit of the adjustable light source detection device, and perform marker line recognition on the target image according to the image processing rule through the processing unit to determine the recognition result; wherein the processing unit includes a ZYNQ chip;

[0068] The abnormality determination module 403 is configured to determine an abnormality according to the recognition result.

[0069] In a possible implementation, module 402 is further configured to:

[0070] Image processing rules include yellow glue image processing rules, V-angle processing rules and tab processing rules.

[0071] The embodiments of this specification provide an abnormality detection method and an adjustable light source detection device, wherein the abnormality detection device comprises: acquiring a target image through a camera unit of the adjustable light source detection device, and determining an image processing rule for the target image; inputting the target image into a processing unit of the adjustable light source detection device, and performing a mark line recognition on the target image according to the image processing rule by the processing unit, and determining a recognition result; wherein the processing unit comprises a ZYNQ chip; and determining an abnormality according to the recognition result. Acquiring a target image through a camera unit of the adjustable light source detection device, and determining an image processing rule for the target image; inputting the target image into a processing unit of the adjustable light source detection device with a ZYNQ chip, and performing a mark line recognition on the target image according to the image processing rule by the processing unit, and determining a recognition result; and determining an abnormality according to the recognition result, thereby improving the precision and accuracy of detection.

[0072] The above is a schematic scheme of an abnormality detection device of this embodiment. It should be noted that the technical scheme of the abnormality detection device and the technical scheme of the abnormality detection method described above are of the same concept, and the details not described in detail in the technical scheme of the abnormality detection device can be referred to the description of the technical scheme of the abnormality detection method described above.

[0073] Figure 5 The structure block diagram of a computing device 500 provided according to an embodiment of the present specification is shown. The components of the computing device 500 include but are not limited to a memory 510 and a processor 520. The processor 520 is connected to the memory 510 via a bus 530, and the database 550 is used to store data.

[0074] The computing device 500 also includes an access device 540 that enables the computing device 500 to communicate via one or more networks 560. Examples of these networks include a public switched telephone network (PSTN), a local area network (LAN), a wide area network (WAN), a personal area network (PAN), or a combination of communication networks such as the Internet. The access device 540 may include one or more of any type of network interface (e.g., a network interface card (NIC)) that is wired or wireless, such as an IEEE 802.11 wireless local area network (WLAN) wireless interface, a world-wide interoperability for microwave access (Wi-MAX) interface, an Ethernet interface, a universal serial bus (USB) interface, a cellular network interface, a Bluetooth interface, and a near field communication (NFC).

[0075] In one embodiment of the present specification, the above components of the computing device 500 and Figure 5 Other components not shown in the figure may also be connected to each other, for example, via a bus. It should be understood that Figure 5 The computing device structure block diagram shown is only for the purpose of illustration, and is not intended to limit the scope of this specification. Those skilled in the art can add or replace other components as needed.

[0076] The computing device 500 may be any type of stationary or mobile computing device, including a mobile computer or mobile computing device (e.g., a tablet computer, a personal digital assistant, a laptop computer, a notebook computer, a netbook, etc.), a mobile phone (e.g., a smart phone), a wearable computing device (e.g., a smart watch, smart glasses, etc.), or other types of mobile devices, or a stationary computing device such as a desktop computer or a personal computer (PC). The computing device 500 may also be a mobile or stationary server.

[0077] The processor 520 is used to execute the following computer executable instructions, which implement the steps of the above-mentioned anomaly detection method when executed by the processor. The above is a schematic scheme of a computing device of this embodiment. It should be noted that the technical scheme of the computing device and the technical scheme of the above-mentioned anomaly detection method belong to the same concept, and the details of the technical scheme of the computing device that are not described in detail can be found in the description of the technical scheme of the above-mentioned anomaly detection method.

[0078] An embodiment of the present specification further provides a computer-readable storage medium storing computer-executable instructions, which can implement the steps of the above-mentioned abnormality detection method when executed by a processor.

[0079] The above is a schematic scheme of a computer-readable storage medium of this embodiment. It should be noted that the technical scheme of the storage medium and the technical scheme of the above-mentioned anomaly detection method belong to the same concept, and the details not described in detail in the technical scheme of the storage medium can be referred to the description of the technical scheme of the above-mentioned anomaly detection method.

[0080] An embodiment of the present specification further provides a computer program, wherein when the computer program is executed in a computer, the computer is caused to execute the steps of the above-mentioned abnormality detection method.

[0081] The above is an illustrative solution of a computer program of this embodiment. It should be noted that the technical solution of the computer program and the technical solution of the above-mentioned anomaly detection method belong to the same concept, and the details not described in detail in the technical solution of the computer program can be referred to the description of the technical solution of the above-mentioned anomaly detection method.

[0082] The above is a description of a specific embodiment of the specification. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recorded in the claims can be performed in an order different from that in the embodiments and still achieve the desired results. In addition, the processes depicted in the drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0083] The computer instructions include computer program codes, which may be in source code form, object code form, executable files or some intermediate forms, etc. The computer-readable medium may include: any entity or device capable of carrying the computer program code, recording medium, USB flash drive, mobile hard disk, magnetic disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electric carrier signal, telecommunication signal and software distribution medium, etc. It should be noted that the content contained in the computer-readable medium may be appropriately increased or decreased according to the requirements of legislation and patent practice in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, computer-readable media do not include electric carrier signals and telecommunication signals.

[0084] It should be noted that, for the convenience of description, the aforementioned method embodiments are all described as a series of action combinations, but those skilled in the art should be aware that the embodiments of this specification are not limited by the order of the actions described, because according to the embodiments of this specification, some steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also be aware that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily required by the embodiments of this specification.

[0085] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0086] The preferred embodiments of this specification disclosed above are only used to help explain this specification. The optional embodiments do not describe all the details in detail, nor do they limit the invention to the specific implementation methods described. Obviously, many modifications and changes can be made according to the content of the embodiments of this specification. This specification selects and specifically describes these embodiments in order to better explain the principles and practical applications of the embodiments of this specification, so that technicians in the relevant technical field can understand and use this specification well. This specification is limited only by the claims and their full scope and equivalents.

Claims

1. An anomaly detection method, characterized in that: include: Acquire a target image through a camera unit of an adjustable light source detection device, and determine an image processing rule for the target image; Input the target image into the processing unit of the adjustable light source detection device, and perform marker line recognition on the target image according to the image processing rule by the processing unit to determine the recognition result; wherein the processing unit includes a ZYNQ chip; determining an abnormal situation according to the recognition result; The image processing rules include yellow glue image processing rules, V-angle processing rules and tab processing rules. The yellow glue image processing rules are yellow glue shielding algorithms, the V-angle processing rules are V-angle shielding algorithms, and the tab processing rules are tab shielding algorithms. The yellow glue shielding algorithm includes: separating the collected image into red, green and blue colors according to pixels, judging the color of the current pixel, and if 10 consecutive pixels are yellow, determining the information of the appearance of yellow glue, transmitting the information of the appearance of yellow glue to the controller through CAN communication, and the controller controls the driver to stop the action, thereby realizing the shielding of yellow glue; wherein, for the RGB three-color range of 0-255, when the red value is between 200 and 240, the green value is between 200 and 240, and the red value is greater than the blue value by more than 100, the current pixel color is yellow; The V-angle shielding algorithm includes: the marking line increases or decreases in one direction, and when a continuous change in one direction is detected, the information of the V-angle appearance is determined, and the information of the V-angle appearance is transmitted to the controller through CAN communication, and the controller controls the driver to stop the action, thereby realizing the shielding of the V-angle; The tab shielding algorithm includes: judging whether a tab appears by judging the black color of the coating area and the color of the other side; if the tab appears, sending the position of the tab to the controller via CAN communication, and the controller controls the driver to stop the action.

2. An adjustable light source detection device, characterized in that: The steps for implementing the abnormality detection method of claim 1 include a ZYNQ chip, a camera unit and an output interface; The camera unit is communicatively connected with the ZYNQ chip; The output interface is communicatively connected with the ZYNQ chip; The camera unit is used to acquire a target image; The ZYNQ chip is used to perform marker line recognition on the target image, determine a recognition result, and send the recognition result to the controller through the output interface.

3. The device according to claim 2, characterized in that The camera unit includes a drive array CCD unit or a CMOS unit.

4. The device according to claim 2, characterized in that It also includes indicator lights, a setting panel, an Ethernet interface, a storage unit and a display interface.

5. The device according to claim 4, characterized in that The setting panel includes a light source channel unit and a brightness selection unit.

6. The device according to claim 4, characterized in that The display interface is at least one of an HDMI interface, a TypeC interface and a DP interface.

7. An abnormality detection device, characterized in that: include: An image acquisition module is configured to acquire a target image through a camera unit of the adjustable light source detection device and determine an image processing rule for the target image; An image recognition module is configured to input the target image into a processing unit of the adjustable light source detection device, and perform marker line recognition on the target image according to the image processing rule through the processing unit to determine a recognition result; wherein the processing unit includes a ZYNQ chip; an abnormality determination module, configured to determine an abnormality according to the recognition result; The image processing rules include yellow glue image processing rules, V-angle processing rules and tab processing rules. The yellow glue image processing rules are yellow glue shielding algorithms, the V-angle processing rules are V-angle shielding algorithms, and the tab processing rules are tab shielding algorithms. The yellow glue shielding algorithm includes: separating the collected image into red, green and blue colors according to pixels, judging the color of the current pixel, and if 10 consecutive pixels are yellow, determining the information of the appearance of yellow glue, transmitting the information of the appearance of yellow glue to the controller through CAN communication, and the controller controls the driver to stop the action, thereby realizing the shielding of yellow glue; wherein, for the RGB three-color range of 0-255, when the red value is between 200 and 240, the green value is between 200 and 240, and the red value is greater than the blue value by more than 100, the current pixel color is yellow; The V-angle shielding algorithm includes: the marking line increases or decreases in one direction, and when a continuous change in one direction is detected, the information of the V-angle appearance is determined, and the information of the V-angle appearance is transmitted to the controller through CAN communication, and the controller controls the driver to stop the action, thereby realizing the shielding of the V-angle; The tab shielding algorithm includes: judging whether a tab appears by judging the black color of the coating area and the color of the other side; if the tab appears, sending the position of the tab to the controller via CAN communication, and the controller controls the driver to stop the action.

8. A computing device, characterized in that include: Memory and processor; The memory is used to store computer executable instructions, and the processor is used to execute the computer executable instructions. When the computer executable instructions are executed by the processor, the steps of the abnormality detection method according to claim 1 are implemented.

9. A computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, implement the steps of the anomaly detection method according to claim 1.

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