Defect detection method, device and equipment for die cutting product and storage medium

Abstract

The invention discloses a defect detection method, device and equipment for a die-cutting product and a storage medium. The method comprises the following steps: acquiring a first die-cutting material image and a second die-cutting material image; comparing the first die cutting material image with the second die cutting material image to obtain defect information; performing feature extraction on the defect information to obtain defect features, and judging whether the defect features are stored in a memory or not; when it is judged that the defect features are stored in the memory, a first correction instruction corresponding to the defect information is called to conduct correction operation, so that the die cutting equipment produces the target die cutting material; when it is judged that the defect features are not stored in the memory, a second correction instruction is generated according to the defect information, the second correction instruction and the defect information are stored in the memory, and the second correction instruction is called to conduct correction operation so that the die cutting equipment can produce the target die cutting material. The method can improve the speed and smoothness of the production line, and further improve the production efficiency.

Description

Technical Field

[0001] The present invention relates to the technical field of die-cut products, and in particular to a method, device, electronic equipment and storage medium for defect detection of die-cut products. Background Art

[0002] Die-cutting is a material processing technology that is mainly used to cut various materials (such as paper, cardboard, rubber, plastic, metal foil, cloth, leather, etc.) into predetermined shapes and sizes. Die-cutting is widely used in packaging printing, electronics, medical devices, automobile manufacturing, clothing, printed circuit boards (PCBs) and other fields. However, during the die-cutting process, the die-cut products may have some defects, such as dimensional deviation, shape defects and surface defects at specific locations, scratches, dents, impurities and uneven colors at specific locations. Due to the large number of die-cut products to be produced, the number of errors in the die-cutting process will also increase. At this time, it is necessary to use specific defect detection technology to detect and optimize the entire die-cutting process to improve production efficiency.

[0003] In the existing die-cutting defect detection technology, the commonly used method is to perform defect detection during the die-cutting process, and if a defect is detected, the system will automatically correct it. However, as people's material needs are getting higher and higher, the number of die-cut products to be produced is also increasing, and the number of errors in the die-cutting process will also increase, which brings challenges to the speed and smoothness of the die-cutting production line.

[0004] During the die-cutting production process, once an error occurs, the die-cutting production line needs to stop working immediately and perform automatic system correction. If the number of errors increases, it will seriously affect the speed and smoothness of the die-cutting production line, thereby affecting production efficiency. Summary of the invention

[0005] The present invention provides a method, device, equipment and storage medium for defect detection of die-cut products, which can efficiently utilize historical defects for rapid correction, so as to achieve smooth and rapid die-cutting production line and improve production efficiency.

[0006] In a first aspect, in order to solve the above technical problems, the present invention provides a defect detection method for die-cut products, comprising: Acquire a first die-cutting material image and a second die-cutting material image; wherein the first die-cutting material image is a target die-cutting material image, and the second die-cutting material image is an image of a die-cutting material to be detected for defects; Comparing the first die-cut material image with the second die-cut material image to obtain defect information; Extracting features from the defect information to obtain defect features, and determining whether the defect features are stored in the memory; When it is determined that the defect feature is stored in the memory, calling the first correction instruction corresponding to the defect information to perform a correction operation so that the die-cutting device produces the target die-cutting material; When it is determined that the defect feature is not stored in the memory, a second correction instruction is generated according to the defect information, the second correction instruction and the defect information are stored in the memory, and the second correction instruction is called to perform a correction operation so that the die-cutting equipment produces the target die-cutting material.

[0007] The first correction instruction is an instruction pre-generated according to historical defect information and stored in the memory.

[0008] Preferably, the comparing the first die-cutting material image with the second die-cutting material image to obtain defect information includes: Performing image comparison based on the first die-cut material image and the second die-cut material image to obtain image difference information; The image difference information is analyzed to obtain defect information.

[0009] Preferably, extracting features from defect information to obtain defect features includes: From the time when the die-cutting material is loaded, the timer starts timing and generates the die-cutting start time; when it is determined that the die-cutting material has defects, the timer stops timing and generates the die-cutting error time; Obtaining die-cutting duration according to the die-cutting start time and the die-cutting error time; generating a time defect feature according to the die-cutting duration; Wherein, the defect characteristics include time defect characteristics.

[0010] Preferably, extracting features from defect information to obtain defect features includes: generating position comparison information according to the first die-cut material image and the second die-cut material image; generating position defect features according to the position comparison information; Wherein, the defect characteristics include position defect characteristics. Preferably, it is determined whether the die-cutting duration has been recorded in the memory; if so, it is determined that the defect feature has been stored in the memory; if not, it is determined that the defect feature has not been stored in the memory.

[0011] Preferably, it is determined whether the position comparison information has been recorded in the memory; if so, it is determined that the defect feature has been stored in the memory; if not, it is determined that the defect feature has not been stored in the memory.

[0012] Preferably, after storing the second correction instruction and the defect information in the memory, the method further comprises: When the next defect information determination comes, the defect information and the second correction instruction stored in the memory will be used as the stored defect information and the corresponding first correction instruction.

[0013] In a second aspect, the present invention provides a defect detection device for die-cut products, comprising: An image acquisition module, used to acquire a first die-cutting material image and a second die-cutting material image; wherein the first die-cutting material image is a target die-cutting material image, and the second die-cutting material image is an image of a die-cutting material to be detected for defects; A defect detection module, used for comparing the first die-cutting material image with the second die-cutting material image to obtain defect information; A feature extraction module is used to extract features from defect information, obtain defect features, and determine whether the defect features are stored in the memory; A first correction module, for invoking a first correction instruction corresponding to the defect information to perform a correction operation when it is determined that the defect feature is stored in the memory, so that the die-cutting device produces a target die-cutting material; A second correction module is used to generate a second correction instruction according to the defect information when it is determined that the defect feature is not stored in the memory, store the second correction instruction and the defect information in the memory, and call the second correction instruction to perform a correction operation so that the die-cutting device produces a target die-cutting material; In a third aspect, the present invention further provides an electronic device comprising a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, wherein the processor implements any one of the above-mentioned methods for detecting defects in die-cut products when executing the computer program.

[0014] In a fourth aspect, the present invention further provides a computer-readable storage medium, wherein the computer-readable storage medium includes a stored computer program, wherein when the computer program is running, the device where the computer-readable storage medium is located is controlled to execute any one of the above-mentioned die-cut product defect detection methods.

[0015] Compared with the prior art, the present invention has the following beneficial effects: an embodiment of the present invention provides a method, apparatus, device and storage medium for defect detection of die-cutting products, the method comprising acquiring a first die-cutting material image and a second die-cutting material image; comparing the first die-cutting material image and the second die-cutting material image to obtain defect information; extracting features from the defect information to obtain defect features, and determining whether the defect features are stored in a memory; when it is determined that the defect features are stored in the memory, the defect information is then calling a first correction instruction corresponding to the defect information to perform a correction operation so that the die-cutting device produces a target die-cutting material; when it is determined that the defect features are not stored in the memory, generating a second correction instruction according to the defect information, storing the second correction instruction and the defect information in the memory, and calling the second correction instruction to perform a correction operation so that the die-cutting device produces the target die-cutting material.

[0016] In the present invention, the method extracts features from defect information to obtain defect features. If the obtained defect features have been stored in a storage device, the next time a defect of the same type occurs, the system can immediately call up the previously generated correction measures to perform correction operations, without the need to generate the corresponding correction measures again, especially in the context of an increasing number of die-cut products to be produced leading to an increasing number of die-cut defects, which can greatly improve the speed and fluency of the production line, thereby improving production efficiency. In addition, since the defects that occur will increase with the increase in the number of die-cut products to be produced, the system will store too much defect information, which is not conducive to calling the corresponding correction instructions. The present invention also filters and saves repeated defect occurrence times and repeated defect locations, solving the problem of storing too many repeated defects, thereby improving the efficiency of correction operations and production efficiency. In addition, the defect features stored in the memory can also help technicians further improve and optimize the parameters of the die-cutting equipment to avoid waste of materials. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 It is a flow chart of a defect detection method for die-cut products provided by the first embodiment of the present invention; Figure 2 It is a schematic structural diagram of a defect detection device for die-cut products provided in the second embodiment of the present invention. DETAILED DESCRIPTION

[0018] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0019] Reference Figure 1 The first embodiment of the present invention provides a method for defect detection of die-cut products, comprising the following steps: S11, acquiring a first die-cutting material image and a second die-cutting material image; wherein the first die-cutting material image is a target die-cutting material image, and the second die-cutting material image is an image of a die-cutting material to be detected for defects; S12, comparing the first die-cut material image with the second die-cut material image to obtain defect information; S13, extracting features from the defect information to obtain defect features, and determining whether the defect features are stored in the memory; S14, when it is determined that the defect feature is stored in the memory, calling the first correction instruction corresponding to the defect information to perform a correction operation so that the die-cutting device produces the target die-cutting material; S15, when it is determined that the defect feature is not stored in the memory, a second correction instruction is generated according to the defect information, the second correction instruction and the defect information are stored in the memory, and the second correction instruction is called to perform a correction operation so that the die-cutting device produces the target die-cutting material.

[0020] It should be noted that die-cutting is a material processing technology, which is mainly used to cut various materials (such as paper, cardboard, rubber, plastic, metal foil, cloth, leather, etc.) according to predetermined shapes and sizes. Die-cutting is widely used in packaging printing, electronics, medical devices, automobile manufacturing, clothing, printed circuit boards (PCBs) and other fields. However, during the die-cutting process, the die-cut products may have some defects, such as dimensional deviation, shape defects and surface defects at specific locations, scratches, dents, impurities and uneven colors at specific locations. At this time, it is necessary to use specific defect detection technology to detect and optimize the entire die-cutting process to improve production efficiency.

[0021] In order to facilitate the understanding of the present invention, some preferred embodiments of the present invention are further described below.

[0022] In step S11, the first die-cutting material image, i.e., the target die-cutting material image, is the desired perfect die-cutting product image, which can be obtained from the original design file pre-stored in the system, or by photographing the perfect die-cutting sample using a high-precision camera or scanning device. The second die-cutting material image, i.e., the die-cutting material image waiting for defect detection on the production line, can be obtained by installing an image acquisition module on the die-cutting production line to photograph the die-cutting product being produced in real time, wherein the image acquisition module can include a high-resolution industrial camera, an optical lens system, and machine vision technology.

[0023] In step S12, defect information is obtained by comparing the first die-cutting material image and the second die-cutting material image, including: Performing image comparison based on the first die-cut material image and the second die-cut material image to obtain image difference information; The image difference information is analyzed to obtain defect information.

[0024] Specifically, defect information can be obtained through image comparison technology, which involves image matching algorithms, such as feature matching algorithms, including scale-invariant feature transform (Scale-Invariant Feature Transform) and SURF algorithm (Speeded-Up Robust Features); template matching algorithms, including standard template matching; and edge detection and matching, including Canny edge detection and Sobel operator.

[0025] Specifically, features such as shape features, texture features, and color features can be extracted from image differences through feature extraction technology. The algorithms involved include: edge detection, such as Canny edge detection and Sobel operator; corner detection, such as Harris corner detection and Shi-Tomasi corner detection.

[0026] Among them, the defects that may appear in the second die-cutting material image include: size deviation, shape defect, surface defect, color defect, impurity defect, position defect, and edge defect of the die-cutting material.

[0027] After image comparison, if no defect information is obtained, it means that the die-cut product produced has no defects, the product is qualified, and the die-cutting work can continue.

[0028] In step S13, feature extraction is performed on the defect information to obtain defect features, and it is determined whether the defect features are stored in the memory. The defect features include time defect features and position defect features; In one embodiment, the extracted defect features include time defect features. The steps of extracting the time defect features are as follows: starting from the feeding of the die-cutting material, the timer starts timing and generates the die-cutting start time; when it is determined that the die-cutting material has defects, the timer stops timing and generates the die-cutting error time; according to the die-cutting start time and the die-cutting error time, the die-cutting duration is obtained; according to the die-cutting duration, the time defect feature is generated.

[0029] In order to achieve the effect of timing from the time the die-cutting material is fed, a proximity sensor or a position sensor can be installed on the die-cutting equipment. When the die-cutting material reaches the specified position, the sensor is triggered and sends a signal to the system to start the timer. In order to achieve the effect of stopping the timer when it is determined that the die-cutting material has defects, the timer can be stopped by sending a timer stop timing instruction to the timer when the defect information is generated. According to the generated die-cutting start time and die-cutting error time, the duration of the die-cutting process is calculated to generate a time defect feature. It is worth noting that the time defect feature is generated based on the die-cutting start time and die-cutting error time. It represents the duration of the die-cutting process and is a time interval from the start of die-cutting to the detection of the defect.

[0030] In this embodiment, it is determined whether the die-cutting duration has been recorded in the memory; if so, it is determined that the defect feature has been stored in the memory; if not, it is determined that the defect feature has not been stored in the memory.

[0031] Specifically, in order to determine whether the generated time defect feature is stored in the memory, the newly generated time defect feature needs to be matched with the historical time defect feature stored in the memory to determine whether the same type of defect has occurred. If the match with the historical time defect feature is successful, it means that the same defect has occurred in history. In the process of die-cutting, die-cutting work often makes mistakes at a certain time. The system can make immediate corrections based on the correction instructions generated historically to ensure the orderly progress of die-cutting work. The saved time defect features can also help technicians further improve and optimize the parameters of die-cutting equipment to avoid waste of materials.

[0032] In another embodiment, the step of extracting the position defect feature is specifically: generating position comparison information according to the first die-cut material image and the second die-cut material image; generating the position defect feature according to the position comparison information; It is worth noting that the position defect characteristics obtained in this step can also be directly obtained from step S12. When the defect information is generated in step S12, the position defect characteristics of the specific defect position are generated for step S13 to determine whether to store repeatedly. It is worth noting that the position defect characteristics include the size deviation, shape defect, surface defect, color defect, impurity defect, position defect, and edge defect of the die-cut material.

[0033] In this embodiment, the determination of whether the defect feature is stored in the memory is specifically as follows: determining whether the position comparison information has been recorded in the memory; if so, determining that the defect feature has been stored in the memory; if not, determining that the defect feature has not been stored in the memory.

[0034] Specifically, in order to determine whether the generated position defect feature is stored in the memory, the newly generated position defect feature needs to be matched with the historical position defect feature stored in the memory to determine whether the same type of defect has occurred. If the match with the historical position defect feature is successful, it means that the same defect has occurred in the past. In the process of die-cutting, die-cutting work often makes mistakes at a certain position of the die-cutting material. The system can make immediate corrections based on the correction instructions generated historically to ensure the orderly progress of the die-cutting work. The saved position defect features can also help technicians further improve and optimize the parameters of the die-cutting equipment to avoid waste of materials.

[0035] In another optional embodiment, it is also possible to determine whether the defect feature is stored in the memory based on the generated time defect feature and position defect feature. Specifically, it is determined whether the die-cutting duration is stored in the memory. If so, it is further determined whether the position comparison information is stored in the memory; if not, it is determined that the defect information is not stored in the memory. Next, it is determined whether the position comparison information is stored in the memory. If so, it is determined that the defect feature has been stored in the memory; if not, it is determined that the defect feature is not stored in the memory.

[0036] Specifically, first match the newly generated time defect feature with the historical time defect feature stored in the memory to determine whether the same type of defect has occurred before. If the match with the historical time defect feature is successful, it means that the same error may have occurred when the die-cutting work reaches a certain position. At this time, the final judgment is further made through the position comparison information. Match the newly generated position defect feature with the historical time defect feature stored in the memory to determine whether the same type of defect has occurred before. If the match with the historical position defect feature is successful, it means that the same defect has occurred in history. At this time, the system can make immediate corrections based on the correction instructions generated historically to ensure the orderly progress of the die-cutting work.

[0037] After step S13, when it is determined that the defect feature is stored in the memory, step S14 is executed.

[0038] In step S14, the first correction instruction is an instruction pre-generated and stored in the memory according to the historical defect information. The system can perform correction operations according to the first correction instruction, including automatically adjusting the relevant parameters of the die-cutting equipment, such as pressure, speed, die position, material tension, and equipment temperature. This process can save the time of generating correction instructions according to defect information and ensure the smoothness of the production line.

[0039] After step S13, when it is determined that the defect feature is not stored in the memory, step S15 is executed.

[0040] In step S15, it is determined that the defect feature is not stored in the memory, indicating that a new defect has occurred. At this time, the system needs to accurately identify the defect feature to generate corresponding correction instructions. Defect information includes size deviation, shape defect, and surface defect. Correction instructions are generated according to the defect information, including pressure and speed adjustment of the die-cutting equipment, adjustment of the mold position, adjustment of the material tension, and adjustment of the equipment temperature.

[0041] In one embodiment, after storing the second correction instruction and the defect information in the memory, the method further includes: When the next defect information determination comes, the defect information and the second correction instruction stored in the memory will be used as the stored defect information and the corresponding first correction instruction.

[0042] In this embodiment, after the second correction instruction is generated, the second correction instruction and the defect information are stored in the memory together, and the defect information and the corresponding second correction instruction stored in the memory are used as the stored defect information and the corresponding first correction instruction when the next defect feature determination comes. This step forms a closed loop with step S14, and the new defect feature obtained is used as the defect feature stored in the memory when the same defect appears again in the subsequent die-cutting work; the newly generated second correction instruction can be used as the first correction instruction when the same defect appears again in the subsequent die-cutting work; the first correction instruction, as a correction instruction that has been generated before, can be immediately called and executed, saving the time of generating the correction instruction again.

[0043] The following describes the working process of the present invention by taking a relatively common scenario as an example. The working process is as follows: On the die-cutting production line, an image acquisition module of a high-resolution industrial camera is installed, and the industrial camera takes real-time photos of the die-cutting material after die-cutting, that is, the second die-cutting material image. At the same time, the system stores the target die-cutting material image, that is, the first die-cutting material image, which is obtained from the design file.

[0044] The system compares the first die-cut material image with the second die-cut material image through image comparison technology to identify the difference. After analyzing the image difference, the system obtains defect information.

[0045] The system extracts features from defect information to obtain defect features.

[0046] In order to obtain defect characteristics, two implementation methods are provided below: In one embodiment, a timer starts timing from the time when the die-cutting material is loaded, and a die-cutting start time is generated. When it is determined that the die-cutting material has defects, the timer stops timing, and a die-cutting error time is generated. Based on the die-cutting start time and the die-cutting error time, a die-cutting duration is obtained. Based on the die-cutting duration, a time defect feature is generated.

[0047] In another embodiment, the system generates position comparison information through image comparison technology, obtains position defects of the die-cut material according to the position comparison information, and generates position defect features.

[0048] After obtaining the time defect feature and the position defect feature, the system queries whether the same defect feature has been stored in the memory.

[0049] If the defect feature has been stored in the memory, the system will call the first correction instruction related to the defect feature to adjust the parameters of the die-cutting equipment, such as pressure and speed, so that the die-cutting equipment can produce the target die-cutting material.

[0050] If it is a new defect feature, the system will generate a new second correction instruction accordingly, store it together with the defect information into the memory, and execute the second correction instruction to enable the die-cutting device to produce the target die-cutting material.

[0051] In summary, the defect detection method for die-cut products provided by the embodiment of the present invention includes obtaining a first die-cutting material image and a second die-cutting material image; comparing the first die-cutting material image and the second die-cutting material image to obtain defect information; extracting features from the defect information to obtain defect features, and determining whether the defect features are stored in the memory; when it is determined that the defect features are stored in the memory, the defect information is then calling the first correction instruction corresponding to the defect information to perform a correction operation, so that the die-cutting device produces the target die-cutting material; when it is determined that the defect features are not stored in the memory, generating a second correction instruction according to the defect information, storing the second correction instruction and the defect information in the memory, and calling the second correction instruction to perform a correction operation, so that the die-cutting device produces the target die-cutting material. The method stores the defect information and the corresponding correction instructions that have appeared, so that they can be quickly retrieved and used when the same defect features are brought next time, eliminating the process of repeatedly generating correction instructions, improving the speed and fluency of the production line, and thus improving production efficiency. In addition, since the defects will increase with the increase in the number of die-cut products to be produced, the system will store too much defect information, which is not conducive to calling the corresponding correction instructions. The present invention also filters and saves the repeated defect occurrence time and repeated defect location, solving the problem of storing too many repeated defects, thereby improving production efficiency. In addition, the defect characteristics stored in the memory can also help technicians further improve and optimize the parameters of the die-cutting equipment to avoid waste of materials.

[0052] Reference Figure 2 A second embodiment of the present invention provides a defect detection device for die-cut products, the device being configured in a mobile terminal and comprising: An image acquisition module, used to acquire a first die-cutting material image and a second die-cutting material image; wherein the first die-cutting material image is a target die-cutting material image, and the second die-cutting material image is an image of a die-cutting material to be detected for defects; A defect detection module, used for comparing the first die-cutting material image with the second die-cutting material image to obtain defect information; A feature extraction module is used to extract features from defect information, obtain defect features, and determine whether the defect features are stored in the memory; A first correction module, for invoking a first correction instruction corresponding to the defect information to perform a correction operation when it is determined that the defect feature is stored in the memory, so that the die-cutting device produces a target die-cutting material; The second correction module is used to generate a second correction instruction according to the defect information when it is determined that the defect feature is not stored in the memory, store the second correction instruction and the defect information in the memory, and call the second correction instruction to perform a correction operation so that the die-cutting equipment can produce the target die-cutting material.

[0053] In an optional implementation, the defect detection module is specifically used to: Performing image comparison based on the first die-cut material image and the second die-cut material image to obtain image difference information; The image difference information is analyzed to obtain defect information.

[0054] In an optional implementation, the feature extraction module is specifically used to: From the time when the die-cutting material is loaded, the timer starts timing and generates the die-cutting start time; when it is determined that the die-cutting material has defects, the timer stops timing and generates the die-cutting error time; Obtaining die-cutting duration according to the die-cutting start time and the die-cutting error time; generating a time defect feature according to the die-cutting duration; In another optional implementation, the feature extraction module is specifically used to: generating position comparison information according to the first die-cut material image and the second die-cut material image; generating position defect features according to the position comparison information; In an optional implementation, the feature extraction module is specifically used to: Determine whether the die-cutting duration has been recorded in the memory; if so, determine that the defect feature has been stored in the memory; if not, determine that the defect feature has not been stored in the memory.

[0055] In another optional implementation, the feature extraction module is specifically used to: Determine whether the position comparison information has been recorded in the memory; if so, determine that the defect feature has been stored in the memory; if not, determine that the defect feature has not been stored in the memory.

[0056] In an optional implementation, the second correction module is specifically used to: When the next defect information determination comes, the defect information and the second correction instruction stored in the memory will be used as the stored defect information and the corresponding first correction instruction.

[0057] It should be noted that a defect detection device for die-cut products provided in an embodiment of the present invention is used to execute all process steps of a defect detection method for die-cut products in the above embodiment, and the working principles and beneficial effects of the two correspond one to one, so they will not be repeated here.

[0058] The embodiment of the present invention further provides an electronic device. The electronic device includes: a processor, a memory, and a computer program stored in the memory and executable on the processor, such as a die-cut product defect detection program. When the processor executes the computer program, the steps in the above-mentioned die-cut product defect detection method embodiments are implemented, such as Figure 1 Alternatively, when the processor executes the computer program, the functions of each module / unit in the above-mentioned device embodiments are implemented, such as a defect detection module.

[0059] Exemplarily, the computer program may be divided into one or more modules / units, which are stored in the memory and executed by the processor to implement the present invention. The one or more modules / units may be a series of computer program instruction segments capable of implementing specific functions, which are used to describe the execution process of the computer program in the electronic device.

[0060] The electronic device may be a computing device such as a desktop computer, a notebook, a PDA, and a smart tablet. The electronic device may include, but is not limited to, a processor and a memory. Those skilled in the art will appreciate that the above components are merely examples of electronic devices and do not constitute a limitation on the electronic device. The electronic device may include more or fewer components than the above components, or may combine certain components, or different components. For example, the electronic device may also include input and output devices, network access devices, buses, etc.

[0061] The processor may be a central processing unit (CPU), other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor, etc. The processor is the control center of the electronic device, and uses various interfaces and lines to connect various parts of the entire electronic device.

[0062] The memory can be used to store the computer program and / or module, and the processor realizes various functions of the electronic device by running or executing the computer program and / or module stored in the memory, and calling the data stored in the memory. The memory can mainly include a program storage area and a data storage area, wherein the program storage area can store an operating system, an application required for at least one function (such as a sound playback function, an image playback function, etc.), etc.; the data storage area can store data created according to the use of the mobile phone (such as audio data, a phone book, etc.), etc. In addition, the memory can include a high-speed random access memory, and can also include a non-volatile memory, such as a hard disk, a memory, a plug-in hard disk, a smart memory card (Smart Media Card, SMC), a secure digital (Secure Digital, SD) card, a flash card (Flash Card), at least one disk storage device, a flash memory device, or other volatile solid-state storage devices.

[0063] Wherein, if the module / unit integrated in the electronic device is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on such an understanding, the present invention implements all or part of the processes in the above-mentioned embodiment method, and can also be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium, and the computer program can implement the steps of the above-mentioned various method embodiments when executed by the processor. Wherein, the computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or some intermediate form. The computer-readable medium may include: any entity or device capable of carrying the computer program code, recording medium, U disk, mobile hard disk, disk, optical disk, computer memory, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), electric carrier signal, telecommunication signal and software distribution medium. It should be noted that the content contained in the computer-readable medium can be appropriately increased or decreased according to the requirements of legislation and patent practice in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, computer-readable media do not include electric carrier signals and telecommunication signals.

[0064] It should be noted that the device embodiments described above are merely schematic, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. In addition, in the accompanying drawings of the device embodiments provided by the present invention, the connection relationship between the modules indicates that there is a communication connection between them, which may be specifically implemented as one or more communication buses or signal lines. A person of ordinary skill in the art may understand and implement it without paying any creative effort.

[0065] The specific embodiments described above further illustrate the purpose, technical solutions and beneficial effects of the present invention. It should be understood that the above description is only a specific embodiment of the present invention and is not intended to limit the scope of protection of the present invention. It is particularly pointed out that for those skilled in the art, any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention should be included in the scope of protection of the present invention.

Claims

1. A defect detection method for die-cut products, characterized in that: include: Acquire a first die-cutting material image and a second die-cutting material image; wherein the first die-cutting material image is a target die-cutting material image, and the second die-cutting material image is an image of a die-cutting material to be detected for defects; Comparing the first die-cut material image with the second die-cut material image to obtain defect information; Extracting features from the defect information to obtain defect features, and determining whether the defect features are stored in the memory; When it is determined that the defect feature is stored in the memory, a first correction instruction corresponding to the defect information is called to perform a correction operation so that the die-cutting device produces the target die-cutting material; When it is determined that the defect feature is not stored in the memory, a second correction instruction is generated according to the defect information, the second correction instruction and the defect information are stored in the memory, and the second correction instruction is called to perform a correction operation so that the die-cutting device produces the target die-cutting material; The first correction instruction is an instruction pre-generated according to historical defect information and stored in the memory.

2. The defect detection method for die-cut products according to claim 1, characterized in that: The obtaining defect information by comparing the first die-cutting material image with the second die-cutting material image includes: Performing image comparison based on the first die-cut material image and the second die-cut material image to obtain image difference information; The image difference information is analyzed to obtain defect information.

3. The defect detection method for die-cut products according to claim 1, characterized in that: The feature extraction of the defect information to obtain the defect feature includes: From the time when the die-cutting material is loaded, the timer starts timing and generates the die-cutting start time; when it is determined that the die-cutting material has defects, the timer stops timing and generates the die-cutting error time; Obtaining die-cutting duration according to the die-cutting start time and the die-cutting error time; generating a time defect feature according to the die-cutting duration; Wherein, the defect characteristics include time defect characteristics.

4. The defect detection method for die-cut products according to claim 1, characterized in that: The feature extraction of the defect information to obtain the defect feature includes: generating position comparison information according to the first die-cut material image and the second die-cut material image; generating position defect features according to the position comparison information; Wherein, the defect characteristics include position defect characteristics.

5. The defect detection method for die-cut products according to claim 3, characterized in that: The determining whether the defect feature is stored in the memory is specifically as follows: Determine whether the die-cutting duration has been recorded in the memory; if so, determine that the defect feature has been stored in the memory; if not, determine that the defect feature has not been stored in the memory.

6. The defect detection method for die-cut products according to claim 4, characterized in that: The determining whether the defect feature is stored in the memory is specifically as follows: Determine whether the position comparison information has been recorded in the memory; if so, determine that the defect feature has been stored in the memory; if not, determine that the defect feature has not been stored in the memory.

7. The defect detection method for die-cut products according to claim 1, characterized in that: After storing the second correction instruction and the defect information in the memory, the method further includes: When the next defect information determination comes, the defect information and the second correction instruction stored in the memory will be used as the stored defect information and the corresponding first correction instruction.

8. A defect detection device for die-cut products, characterized in that: include: An image acquisition module, used to acquire a first die-cutting material image and a second die-cutting material image; wherein the first die-cutting material image is a target die-cutting material image, and the second die-cutting material image is an image of a die-cutting material to be detected for defects; A defect detection module, used for comparing the first die-cut material image with the second die-cut material image to obtain defect information; A feature extraction module is used to extract features from defect information, obtain defect features, and determine whether the defect features are stored in the memory; A first correction module, for invoking a first correction instruction corresponding to the defect information to perform a correction operation when it is determined that the defect feature is stored in the memory, so that the die-cutting device produces a target die-cutting material; The second correction module is used to generate a second correction instruction according to the defect information when it is determined that the defect feature is not stored in the memory, store the second correction instruction and the defect information in the memory, and call the second correction instruction to perform a correction operation so that the die-cutting equipment can produce the target die-cutting material.

9. An electronic device, characterized in that: The method comprises a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, wherein the processor implements the defect detection method for die-cut products according to any one of claims 1 to 7 when executing the computer program.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium includes a stored computer program, wherein when the computer program is executed, the device where the computer-readable storage medium is located is controlled to execute the defect detection method for die-cut products according to any one of claims 1 to 7.

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