Anti-re-pasting and anti-missing pasting monitoring method based on gray scale matching template

Abstract

The invention discloses an anti-re-pasting and anti-missing pasting monitoring method based on a gray scale matching template, and relates to the technical field of anti-re-pasting and anti-missing pasting monitoring, and the method comprises the steps: feeding an FPC product into production line equipment, and carrying out the three-code-in-one comparison; an industrial camera is used for continuously shooting images of a monitoring station area, the preprocessed images are compared with a gray scale matching template, the similarity is calculated through a gray scale matching algorithm, and whether the station coordinates are missed or not is determined; the collected image is matched with a preset template through a gray matching algorithm, the similarity between the image and the gray matching template is calculated, whether repasting exists or not is judged according to the similarity, and station coordinates, time and the image are automatically output so that follow-up processing and tracing can be facilitated; according to the method, the gray value difference between the template image and the FPC product image is compared through a gray matching algorithm, so that the area defects of missing and repeated attachment can be accurately identified, the production efficiency and the product quality are improved, and the labor cost is reduced.

Description

Technical Field

[0001] The invention belongs to the technical field of monitoring the prevention of repeated pasting and missing stickers, and specifically relates to a monitoring method for preventing repeated pasting and missing stickers based on a grayscale matching template. Background Art

[0002] With the continuous upgrading of electronic products, customers have higher and higher requirements for FPC products. They not only pay attention to the performance and price of the products, but also pay great attention to the quality and reliability of the products. As a key component in electronic products, the quality and reliability of FPC directly affect the performance and stability of the entire product. During the production process, if FPC is re-pasted or missed, it often needs to be reworked or re-produced, which will not only increase production costs, but also reduce production efficiency. By implementing anti-re-pasting and anti-missing monitoring, problems can be discovered in the early stages of production, and timely measures can be taken to solve them to avoid the expansion of problems, thereby improving production efficiency and reducing costs.

[0003] Due to the complex structure, small size and high precision of FPC products, the monitoring technology for preventing repeated pasting and missing stickers is highly complex. In addition, a large amount of data will be generated during the monitoring process. These data need to be processed and analyzed in a timely and accurate manner in order to find and solve problems in a timely manner. However, due to the huge amount of data, various types and different formats, data processing and analysis are difficult, and traditional manual detection methods can no longer meet the needs of modern production.

[0004] Therefore, we propose a monitoring method to prevent repeated pasting and missed pasting based on grayscale matching template. Summary of the invention

[0005] The purpose of the present invention is to improve production efficiency and product quality and reduce labor costs. This application provides a monitoring method for preventing repeated pasting and missing pasting based on a grayscale matching template.

[0006] The technical solution adopted by the present invention is as follows:

[0007] The anti-re-sticking and anti-missing sticking monitoring method based on grayscale matching template comprises the following steps:

[0008] S1: Send FPC products into the production line equipment, arrange and convey the FPC products on the production line according to the established production plan and sequence, and equip the production equipment with an automatic identification and positioning system to accurately capture and locate each FPC product entering the equipment;

[0009] S2: When the FPC product enters the equipment, the high-precision camera or scanner on the equipment will quickly capture the QR code on the product. The camera or scanner will sequentially shoot the QR code of the product, the QR code of the fixture, and the QR code of the steel sheet of the pressed product for subsequent comparison and confirmation;

[0010] S3: The three QR codes captured will be transmitted to the control system of the production equipment, which will decode and compare the three QR codes to ensure that the products, fixtures and steel sheets they represent are consistent;

[0011] S4: During the comparison process, the control system will check whether the information in the QR code matches. If all the information is consistent, the control system will confirm that the three elements are matched, that is, "three codes in one", and can enter the monitoring process of leak-proof stickers. If the information is inconsistent or any error occurs, the control system will immediately issue an alarm and stop the production line to prevent unqualified products from entering the monitoring process of leak-proof stickers;

[0012] S5: Use a high-resolution, low-distortion industrial camera equipped with a stable flying platform to continuously capture images of the monitoring workstation area and transmit image data to the control system in real time. The control system will grayscale the collected images to eliminate the interference of color information on the matching results, and apply filtering algorithms to remove image noise to achieve image preprocessing;

[0013] S6: Compare the preprocessed image with the grayscale matching template, calculate the similarity using the grayscale matching algorithm, and determine whether the workstation coordinates are missed based on the matching results;

[0014] S7: The coordinates of the workstations that are confirmed to have missed stickers and those that have not been missed are recorded in the database for subsequent analysis and tracing, and reports or charts are generated as needed. The coordinates of the workstations are fed back to the production line control system in real time, and the products that have not been missed will enter the anti-re-sticking process;

[0015] S8: The grayscale camera at the inspection station configured on the production line will automatically capture images of the product attachment area and pre-process the captured images, including grayscale conversion, denoising, enhancement, etc., to improve the image quality and matching effect, so as to perform grayscale matching inspection on the attached products;

[0016] S9: Use the grayscale matching algorithm to match the captured image with the preset template, calculate the similarity between the image and the grayscale matching template, and determine whether there is a duplicate paste based on the similarity. If the algorithm determines that there is a duplicate paste, the workstation coordinates, time and image are automatically output for subsequent processing and tracing;

[0017] S10: After the monitoring of anti-duplicate and anti-missing stickers is completed, the control system will record the coordinates, time and image of the missed and duplicate stickers in a folder generated by combining the three codes for easy traceability, and trigger the alarm notification mechanism to notify the relevant personnel on the production line.

[0018] Furthermore, the QR code contains the production date, batch number and specification parameters of the product, fixture and steel sheet.

[0019] Furthermore, after the control system confirms the "three codes in one", it will record the confirmation result and generate corresponding production logs and reports.

[0020] Furthermore, the grayscale matching template is a template formed by graying the standard anti-missing sticker image and extracting key feature areas.

[0021] Furthermore, the industrial camera is equipped with a stable flying platform.

[0022] Furthermore, the calculation method of the grayscale matching algorithm is NCC(x,y)=∑(x_i*y_i) / (√∑(x_i^2)*√∑(y_i^2)), wherein x and y are two signals to be compared, x_i and y_i are sample values ​​at their corresponding positions, and the similarity value can be obtained by calculating the inner product of the two signals and dividing it by their amplitudes, ranging from -1 to 1. When the value of NCC is close to 1, it indicates that the two signals are very similar. When the value of NCC is close to -1, it indicates that the two signals have opposite characteristics. When the value of NCC is close to 0, it indicates that there is no obvious correlation between the two signals.

[0023] Furthermore, the alarm notification mechanism is a display screen notification, SMS notification or email notification set up on the production line to ensure that relevant personnel can respond in time.

[0024] In summary, due to the adoption of the above technical solution, the beneficial effects of the present invention are:

[0025] 1. In the present invention, by comparing the gray value difference between the template image and the FPC product image using a gray matching algorithm, regional defects such as missed attachment and repeated attachment can be accurately identified, thereby reducing human errors and missed detections, improving production efficiency and product reliability, and thus improving product quality.

[0026] 2. In the present invention, by combining automated equipment and intelligent algorithms, grayscale matching template monitoring can achieve efficient production with no human supervision or a small amount of human intervention, thereby reducing labor costs. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] Figure 1 It is a flow chart of the present invention. DETAILED DESCRIPTION

[0028] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in combination with the embodiments of the present invention. Obviously, the described embodiments are 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.

[0029] Example:

[0030] Reference Figure 1 , the anti-re-sticking and anti-missing sticking monitoring method based on grayscale matching template, sends FPC products into the production line equipment, and arranges and transmits the FPC products on the production line according to the established production plan and sequence, and equips the production equipment with an automatic identification and positioning system to accurately capture and locate each FPC product entering the equipment; when the FPC product enters the equipment, the high-precision camera or scanner on the equipment will quickly capture the QR code on the product, and the camera or scanner will sequentially shoot the product QR code, the fixture QR code, and the steel sheet QR code of the pressed product for subsequent comparison and confirmation; the QR code contains the production date, batch number and specification parameters of the product, fixture and steel sheet; the three QR codes captured will be transmitted to the control system of the production equipment, and the control system will decode and compare the three QR codes to ensure that the products, fixtures and steel sheets they represent are consistent. After the control system confirms the "three codes in one", it will record the confirmation result and generate corresponding production logs and reports; specifically, through high-precision cameras or scanners and advanced control systems, we can achieve automation and intelligence, thereby improving production efficiency and quality levels.

[0031] Reference Figure 1 During the comparison process, the control system will check whether the information in the QR code matches. If all the information is consistent, the control system will confirm that the three elements are matched, that is, "three codes in one", and can enter the monitoring process of the anti-leakage sticker. If the information is inconsistent or any error occurs, the control system will immediately sound an alarm and stop the production line to prevent unqualified products from entering the monitoring process of the anti-leakage sticker. Specifically, the three-code integration ensures the accuracy and traceability of the production process and prevents confusion and errors. At the same time, the three-code integration simplifies the production process and reduces the steps of repeated scanning and information entry, thereby improving the overall production efficiency. Through the three-code integration, the production batch, raw material source and other information of FPC products can be traced more conveniently, which is helpful for quality control and after-sales service.

[0032] Reference Figure 1, using a high-resolution, low-distortion industrial camera equipped with a stable flight platform. The industrial camera is equipped with a stable flight platform; specifically, using software to plan the flight path of the camera to ensure that the path can cover all monitoring areas, and minimize flight time and energy consumption, and set the flight altitude and speed to ensure that the camera can capture clear and stable images; the industrial camera continuously captures images of the monitoring station area and transmits image data to the control system in real time. The control system will grayscale the collected images to eliminate the interference of color information on the matching results, and apply filtering algorithms to remove image noise to achieve image preprocessing; specifically, through grayscale processing, color information interference is eliminated, image matching is more accurate, and the accuracy of defect or anomaly detection is improved; the application of filtering algorithms can effectively remove image noise, reduce misjudgment caused by environmental factors, and enhance the stability and reliability of the system; the image data is simplified through the preprocessing steps, the complexity of subsequent image analysis and processing is reduced, thereby improving the overall processing efficiency.

[0033] Reference Figure 1 , compare the preprocessed image with the grayscale matching template, use the grayscale matching algorithm to calculate the similarity, and determine whether the workstation coordinates are missed based on the matching results; the calculation method of the grayscale matching algorithm is NCC(x,y)=∑(x_i*y_i) / (√∑(x_i^2)*√∑(y_i^2)), where x and y are two signals to be compared, x_i and y_i are sample values ​​at their corresponding positions, and the similarity value can be obtained by calculating the inner product of the two signals and dividing them by their amplitudes. The range is between -1 and 1. When the NCC value is close to 1, it means that the two signals are very similar. When the NCC value is close to -1, it means that the two signals have opposite When the value of NCC is close to 0, it means that there is no obvious correlation between the two signals; the grayscale matching template is a template formed by graying the standard anti-missing pasting image and extracting the key feature area; the coordinates of the workstations confirmed to be missed and not missed are recorded in the database for subsequent analysis and tracing, and reports or charts are generated as needed, and the workstation coordinates are fed back to the production line control system in real time, and the products that are not missed will enter the anti-re-sticking process; specifically, the grayscale matching algorithm is used to compare the grayscale value difference between the template image and the FPC product image, so as to accurately identify the missing pasting defects, reduce human errors and missed inspections, improve production efficiency and product reliability, and thus improve product quality.

[0034] Reference Figure 1The grayscale camera on the inspection station configured on the production line will automatically capture images of the product attachment area and pre-process the captured images, including grayscale, denoising, enhancement, etc., to improve the image quality and matching effect, so as to perform grayscale matching inspection on the attached products; the captured image is matched with the pre-set template using the grayscale matching algorithm, the similarity between the image and the grayscale matching template is calculated, and whether there is a double-sticking is determined based on the similarity. If the algorithm determines that there is a double-sticking, the station coordinates, time and image are automatically output for subsequent processing and tracing; specifically, by using the grayscale matching algorithm to compare the grayscale value difference between the template image and the FPC product image, the defects of the repeated attachment area can be accurately identified, and by reducing human errors and missed inspections, production efficiency and product reliability can be improved, thereby improving product quality; by combining automated equipment and intelligent algorithms, grayscale matching template monitoring can achieve efficient production under unattended or with a small amount of manual intervention, reducing labor costs.

[0035] Reference Figure 1 After the anti-duplicate and anti-missing monitoring is completed, the control system will record the coordinates, time and image of the missed and duplicated workstations into a folder generated by the three-in-one code for easy traceability, and trigger the alarm notification mechanism to notify the relevant personnel on the production line; the alarm notification mechanism is a display screen notification, SMS notification or email notification set up on the production line to ensure that the relevant personnel can respond in time; specifically, through real-time monitoring and recording, the problems of missed and duplicated sticking can be discovered in time, production errors can be reduced, and production efficiency can be improved. The workstation coordinates, time and images can be recorded to facilitate subsequent tracing of the source of the problem, conduct quality analysis and improvement, and trigger the alarm notification mechanism to ensure that the relevant personnel can respond quickly so as to deal with the problem in time and avoid the expansion of the problem.

[0036] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the sentence "comprise a ..." do not exclude the existence of other identical elements in the process, method, article or device including the elements.

[0037] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features may be replaced by equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A monitoring method for preventing repeated pasting and missing pasting based on a grayscale matching template, characterized in that: The steps include: S1: Send the FPC products into the production line equipment, arrange and convey the FPC products on the production line according to the established production plan and sequence, and equip the production equipment with an automatic identification and positioning system to accurately capture and locate each FPC product entering the equipment; S2: When the FPC product enters the equipment, the high-precision camera or scanner on the equipment will quickly capture the QR code on the product. The camera or scanner will sequentially shoot the QR code of the product, the QR code of the fixture, and the QR code of the steel sheet of the pressed product for subsequent comparison and confirmation; S3: The three QR codes captured will be transmitted to the control system of the production equipment, which will decode and compare the three QR codes to ensure that the products, fixtures and steel sheets they represent are consistent; S4: During the comparison process, the control system will check whether the information in the QR code matches. If all the information is consistent, the control system will confirm that the three elements are matched, that is, "three codes in one", and can enter the monitoring process of leak-proof stickers. If the information is inconsistent or any error occurs, the control system will immediately sound an alarm and stop the production line to prevent unqualified products from entering the monitoring process of leak-proof stickers; S5: Use a high-resolution, low-distortion industrial camera equipped with a stable flying platform to continuously capture images of the monitoring workstation area and transmit image data to the control system in real time. The control system will grayscale the collected images to eliminate the interference of color information on the matching results, and apply filtering algorithms to remove image noise to achieve image preprocessing; S6: Compare the preprocessed image with the grayscale matching template, calculate the similarity using the grayscale matching algorithm, and determine whether the workstation coordinates are missed based on the matching results; S7: The coordinates of the workstations that are confirmed to have missed stickers and those that have not been missed are recorded in the database for subsequent analysis and tracing, and reports or charts are generated as needed. The coordinates of the workstations are fed back to the production line control system in real time, and the products that have not been missed will enter the anti-re-sticking process; S8: The grayscale camera at the inspection station configured on the production line will automatically capture images of the product attachment area and pre-process the captured images, including grayscale conversion, denoising, enhancement, etc., to improve the image quality and matching effect, so as to perform grayscale matching inspection on the attached products; S9: Use the grayscale matching algorithm to match the captured image with the preset template, calculate the similarity between the image and the grayscale matching template, and determine whether there is a duplicate paste based on the similarity. If the algorithm determines that there is a duplicate paste, the workstation coordinates, time and image are automatically output for subsequent processing and tracing; S10: After the monitoring of anti-duplicate and anti-missing stickers is completed, the control system will record the coordinates, time and image of the missed and duplicate stickers in a folder generated by combining the three codes for easy traceability, and trigger the alarm notification mechanism to notify the relevant personnel on the production line.

2. The grayscale matching template-based anti-re-sticking and anti-missing monitoring method according to claim 1, characterized in that: The QR code contains the production date, batch number and specification parameters of the product, fixture and steel sheet.

3. The grayscale matching template-based anti-re-sticking and anti-missing monitoring method according to claim 1, characterized in that: After the control system confirms the "three codes in one", it will record the confirmation result and generate corresponding production logs and reports.

4. The grayscale matching template-based anti-re-sticking and anti-missing monitoring method according to claim 1, characterized in that: The grayscale matching template is a template formed by graying the standard anti-leaking sticker image and extracting the key feature area.

5. The grayscale matching template-based anti-re-sticking and anti-missing monitoring method according to claim 1, characterized in that: The industrial camera is equipped with a stable flying platform.

6. The grayscale matching template-based anti-re-sticking and anti-missing monitoring method according to claim 1, characterized in that: The calculation method of the grayscale matching algorithm is NCC(x,y)=∑(x_i*y_i) / (√∑(x_i^2)*√∑(y_i^2)), where x and y are two signals to be compared, x_i and y_i are sample values ​​at their corresponding positions, and the similarity value can be obtained by calculating the inner product of the two signals and dividing it by their amplitudes. The range is between -1 and 1. When the value of NCC is close to 1, it means that the two signals are very similar. When the value of NCC is close to -1, it means that the two signals have opposite characteristics. When the value of NCC is close to 0, it means that there is no obvious correlation between the two signals.

7. The grayscale matching template-based anti-re-sticking and anti-missing monitoring method according to claim 1, characterized in that: The alarm notification mechanism is a display screen notification, SMS notification or email notification set up on the production line to ensure that relevant personnel can respond in time.

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