Punching monitoring method and monitoring system applied to flexible circuit board and medium

Abstract

The invention relates to the technical field of punching monitoring, in particular to a punching monitoring method and monitoring system applied to a flexible circuit board and a medium, and the method comprises the steps: determining a real-time material hardness change parameter of a to-be-monitored flexible circuit board according to first real-time sensing data; when the real-time material hardness change parameter is not higher than a preset change parameter threshold value, generating a first punching parameter based on the first real-time sensing data; if so, determining a data matching value between the first real-time sensing data and the second real-time sensing data; when the data matching value is higher than a preset matching threshold value, generating a second punching parameter based on the first real-time sensing data and the second real-time sensing data; if not, generating a third punching parameter based on the first real-time sensing data, the second real-time sensing data and the third real-time sensing data; and punching operation is carried out based on the first punching parameter, the second punching parameter or the third punching parameter. According to the invention, the accuracy of punching the flexible circuit board can be improved.

Description

Technical Field

[0001] This application relates to the field of hole detection technology, and in particular to a hole detection method, monitoring system and medium for flexible printed circuit boards. Background Technology

[0002] As a key component in modern electronic devices, flexible circuit boards (PCBs) place extremely high demands on drilling processes due to their high-density wiring, multi-layered structure, and complex material systems. With the development of electronic products towards miniaturization, high frequency, and functional integration, drilling accuracy, hole alignment, and hole wall quality have become core factors affecting the reliability and electrical performance of PCBs.

[0003] Traditional drilling processes mainly rely on pre-set drilling parameters for drilling operations. However, due to the non-homogeneity of flexible circuit board materials, if fixed drilling parameters are used to drill flexible circuit boards of different materials or with different hardness, it may be that the drilling parameters are not compatible with the drilling position, which may lead to hole position displacement or unstable quality. Summary of the Invention

[0004] To improve the accuracy of drilling holes in flexible printed circuit boards, this application provides a drilling monitoring method, monitoring system, and medium for use in flexible printed circuit boards.

[0005] Firstly, this application provides a method for detecting holes in flexible printed circuit boards, employing the following technical solution: A method for detecting perforations in flexible printed circuit boards, comprising: Acquire first real-time sensing data and determine the real-time material hardness change parameter of the flexible circuit board to be monitored based on the first real-time sensing data. The first real-time sensing data is collected by the first sensing network element. When the real-time material hardness change parameter is not higher than the preset change parameter threshold, the first drilling parameter is generated based on the first real-time sensing data. When the real-time material hardness change parameter is higher than the preset change parameter threshold, the second sensing element to be activated is determined based on the first real-time sensing data, the second real-time sensing data is acquired, and the data matching value between the first real-time sensing data and the second real-time sensing data is determined. The second real-time sensing data is collected by the second sensing element to be activated. When the data matching value is higher than the preset matching threshold, a second punching parameter is generated based on the first real-time sensing data and the second real-time sensing data. When the data matching value is not higher than the preset matching threshold, the third sensing network element to be activated is determined based on the first real-time sensing data and the second real-time sensing data, the third real-time sensing data is obtained, and the third punching parameters are generated based on the first real-time sensing data, the second real-time sensing data and the third real-time sensing data. The third real-time sensing data is collected by the third sensing network element to be activated. Based on the first drilling parameters, or the second drilling parameters, or the third drilling parameters, a drilling operation is performed on the flexible circuit board to be monitored.

[0006] By adopting the above technical solution, the material hardness variation parameters of the flexible circuit board are acquired and analyzed in real time, which facilitates the dynamic adjustment of drilling parameters to adapt to the changes in the hardness of different materials. When the real-time material hardness variation parameters exceed the preset threshold, additional second or third sensing network elements are activated to collect more sensing data, so as to ensure accurate drilling decisions can be made even in complex or uncertain situations. That is, it is convenient to flexibly adjust the drilling strategy according to the real-time situation. This multi-level data acquisition and analysis mechanism helps to ensure the adaptability between drilling parameters and the drilling position, thereby improving the accuracy and reliability of the drilling process.

[0007] In one possible implementation, determining the second sensing network element to be activated based on the first real-time sensing data includes: The image of the monitored area containing the flexible circuit board to be monitored is acquired, and abnormal hardness areas are identified from the monitored area image based on the first real-time sensing data. The material hardness change parameter corresponding to the abnormal hardness area is higher than the preset change parameter threshold, and the material hardness change parameter corresponding to different abnormal hardness areas is different. Each abnormal hardness region is identified in the image of the area to be monitored, resulting in an image of identified abnormal regions. Obtain at least one drilling interest area corresponding to the abnormal hardness area, and each drilling interest area corresponds to a drilling position. By overlaying all the punching concern areas onto the identified abnormal area image, an integrated abnormal area image is obtained; At least one overlapping region of interest is determined from the integrated abnormal region image, and the second sensing element corresponding to each overlapping region of interest is determined as the second sensing element to be activated.

[0008] By adopting the above technical solution, a corresponding drilling interest area is set for each drilling position, which facilitates comprehensive consideration of the material hardness of the drilling position and its surrounding area, thereby improving the accuracy and efficiency of drilling. By superimposing the drilling interest area onto the image of the identified abnormal area, an integrated abnormal area image is obtained, and overlapping interest areas are determined from it, which facilitates the accurate location of areas that need further sensing data collection. Finally, based on the overlapping interest areas, the corresponding second sensing network element is selected for second sensing data collection, instead of activating all second sensing network elements for second sensing data collection. This facilitates meeting the needs of further sensing data collection while avoiding resource waste caused by activating too many second sensing network elements.

[0009] In one possible implementation, determining overlapping regions of interest from the integrated anomaly regions includes: The actual overlapping area is determined from the integrated abnormal area, which is the area where the area of ​​concern for drilling and the area of ​​abnormal hardness overlap. Identify the distance between the center point of the actual overlapping area and the corresponding punching position, and determine the first score corresponding to the distance based on the mapping relationship between the distance and the first preset score. Identify the hardness change difference between the material hardness change parameter corresponding to the actual overlapping area and the preset change parameter threshold, and determine the second score corresponding to the hardness change difference based on the mapping relationship between the hardness change difference and the second preset score. Identify the overlapping area corresponding to the actual overlapping region, and determine the third score corresponding to the overlapping area based on the mapping relationship between the overlapping area and the third preset score; The overlap score is determined based on the first score, the second score, and the third score, and the expansion area corresponding to the overlap score is determined based on the overlap score and the preset expansion mapping relationship. The overlapping region of interest is obtained by adjusting the actual overlapping region based on the expanded area.

[0010] By adopting the above technical solution, and by analyzing and quantifying the distance between the center of the actual overlapping area and the drilling position, the change in material hardness, and the overlapping area of ​​the actual overlapping area, it is convenient to comprehensively analyze the importance of the actual overlapping area. Finally, based on the overlap score and the preset edge expansion mapping relationship, the edge expansion area corresponding to the overlap score of the actual overlapping area is determined, and the actual overlapping area is adjusted accordingly to obtain the overlapping area of ​​interest, rather than simply using the actual overlapping area to represent the final overlapping area of ​​interest. This moderate edge expansion adjustment method facilitates the improvement of the fit between the overlapping area of ​​interest and the actual situation. By monitoring the overlapping area of ​​interest more accurately and effectively, it is convenient to discover and deal with potential problems in a timely manner, thereby improving the reliability and quality of the flexible circuit board to be monitored.

[0011] In one possible implementation, determining the actual overlapping region from the integration anomaly region includes: Identify the punching interest area from the integrated anomaly area, and at least one anomalous hardness area that overlaps with the punching interest area; When the area of ​​interest for drilling corresponds to at least two abnormal hardness areas, identify the overlap area between each abnormal hardness area and the area of ​​interest for drilling, and the material hardness change parameters of each abnormal hardness area. Based on each overlapping area, the material hardness change parameter corresponding to each overlapping area, and the preset overlapping parameter mapping relationship, the adjustment score corresponding to the perforation focus area is determined. Based on the adjustment score, a target adjustment strategy corresponding to the punching attention area is determined, and based on the target adjustment strategy and the punching attention area, the corresponding actual overlapping area is determined.

[0012] By adopting the above technical solution, the drilling interest area and the abnormal hardness area that overlaps with the drilling interest area can be identified from the integrated abnormal area. This facilitates the understanding of the overlap between the drilling interest area and the abnormal hardness area. When the same drilling interest area overlaps with at least two abnormal hardness areas, the overlap can be quantified based on data such as the overlap area and material hardness change parameters to obtain an adjustment score. Finally, the drilling interest area is expanded and adjusted based on the overlap score. The obtained actual overlap area facilitates a more comprehensive and objective assessment of the importance of the drilling position. This helps to improve drilling accuracy and efficiency while reducing problems such as drilling deviation and drill bit wear caused by uneven material hardness, thereby improving the accuracy and efficiency of the drilling process.

[0013] In one possible implementation, determining the target adjustment strategy corresponding to the punching attention area based on the adjustment score includes: When the adjustment score is within the first preset score range, the corresponding target adjustment strategy is to determine the actual overlapping area between the perforation concern area and the corresponding abnormal hardness area as the actual overlapping area. When the adjustment score is within the range of the second preset score, the corresponding target adjustment strategy is to determine the punching attention area as the actual overlapping area; When the adjustment score is within the range of the third preset score, the corresponding target adjustment strategy is to expand the edge of the punching attention area to obtain the expanded punching attention area, and determine the expanded punching attention area as the actual overlapping area.

[0014] By adopting the above technical solution, different preset score ranges are set, and different adjustment scores are processed in a hierarchical manner. This hierarchical processing method makes it easier to take corresponding adjustment strategies according to different degrees of overlap, thereby improving the accuracy of determining the actual overlapping area.

[0015] In one possible implementation, when the first real-time sensing data or the second real-time sensing data contains preset material features, the method further includes: A virtual punch image is generated based on the first real-time sensing data and the second real-time sensing data, and the virtual punch image is fed back to the terminal device of the relevant remote personnel. Upon receiving a drilling suggestion from a relevant remote person, the remote drilling information in the drilling suggestion is identified, including the remote drilling location and remote drilling parameters. Based on the remote punching location, the corresponding remote punching parameters are superimposed onto the virtual punching image to obtain a remote AR punching image; The remote AR punching image is fed back to the AR device worn by the punching personnel to guide them in the punching operation.

[0016] By adopting the above technical solution, the virtual punching image is fed back to the terminal device of the remote personnel, and their punching suggestions are received. This facilitates real-time communication between the punching site and the remote location. This collaborative method breaks down geographical limitations, allowing relevant experts or technicians to participate in the punching process remotely, thereby improving collaboration efficiency and response speed. In addition, by identifying the remote punching location and parameters in the remote punching suggestions and overlaying them onto the virtual punching image to generate a remote AR punching image, it is convenient to provide accurate punching guidance and parameter settings for relevant on-site punching personnel, thereby reducing human error in the punching process and improving punching accuracy.

[0017] Secondly, this application provides a monitoring system, which adopts the following technical solution: A monitoring system comprising: At least one processor; Memory; At least one application, wherein the at least one application is stored in memory and configured to be executed by at least one processor, the at least one application being configured to: perform the above-described hole detection method applied to flexible circuit boards.

[0018] Thirdly, this application provides a computer-readable storage medium, which adopts the following technical solution: A computer-readable storage medium includes: a computer program stored thereon that can be loaded by a processor and executed by the above-described perforation detection method applied to flexible printed circuit boards.

[0019] Fourthly, this application provides a computer program product, which adopts the following technical solution: A computer program product includes a computer program that, when executed by a processor, implements the above-described hole detection method applied to flexible circuit boards.

[0020] In summary, this application includes at least one of the following beneficial technical effects: By acquiring and analyzing the material hardness variation parameters of flexible circuit boards in real time, it is easy to dynamically adjust the drilling parameters to adapt to the changes in the hardness of different materials. When the real-time material hardness variation parameters exceed the preset threshold, additional second or third sensing network elements are activated to collect more sensing data to ensure accurate drilling decisions can be made even in complex or uncertain situations. In other words, it is easy to flexibly adjust the drilling strategy according to the real-time situation. This multi-level data acquisition and analysis mechanism helps to ensure the adaptability between the drilling parameters and the drilling position, thereby improving the accuracy and reliability of the drilling process.

[0021] By feeding back the virtual punching image to the terminal device of a remote operator and receiving their punching suggestions, real-time communication between the punching site and the remote location is facilitated. This collaborative approach breaks down geographical limitations, enabling relevant experts or technicians to participate in the punching process remotely, thereby improving collaboration efficiency and response speed. Furthermore, by identifying the remote punching location and parameters in the remote punching suggestions and overlaying them onto the virtual punching image to generate a remote AR punching image, precise punching guidance and parameter settings can be provided to relevant on-site punching personnel, thus reducing human error during the punching process and improving punching accuracy. Attached Figure Description

[0022] Figure 1 This is a flowchart illustrating a perforation detection method for flexible printed circuit boards according to an embodiment of this application. Figure 2 This is an example of an image used to identify abnormal regions in this application. Figure 3 This is an embodiment of integrating abnormal region images in this application; Figure 4 This is a schematic diagram of the structure of a monitoring system according to an embodiment of this application. Detailed Implementation

[0023] The following is in conjunction with the appendix Figures 1 to 4 This application will be described in further detail.

[0024] After reading this specification, those skilled in the art may make modifications to this embodiment without contributing any inventive step, but such modifications are protected by patent law as long as they fall within the scope of the claims of this application.

[0025] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0026] It should be noted that, in the optional embodiments of this application, the data related to object information, when applied to specific products or technologies, requires the permission or consent of the object. Furthermore, the collection, use, and processing of this data must comply with the relevant laws, regulations, and standards of the relevant countries and regions. In other words, if the embodiments of this application involve data related to an object, it must be obtained with the object's authorization and consent, the authorization and consent of relevant departments, and in accordance with the relevant laws, regulations, and standards of the country and region. If the embodiments involve personal information, the acquisition of all personal information requires the individual's consent. If sensitive information is involved, the separate consent of the information subject is required. The embodiments also need to be implemented with the object's authorization and consent.

[0027] Specifically, this application provides a method for detecting hole punching on flexible printed circuit boards, executed by a monitoring system. This monitoring system can be a server or a terminal device. The server can be a standalone physical server, a server cluster or distributed system composed of multiple physical servers, or a cloud server providing cloud computing services. The terminal device can be a smartphone, tablet, laptop, desktop computer, etc., but is not limited to these. The terminal device and the server can be directly or indirectly connected via wired or wireless communication, and this application does not impose any limitations on this.

[0028] refer to Figure 1 , Figure 1 This is a flowchart illustrating a hole detection method for flexible printed circuit boards according to an embodiment of this application. The method includes steps S110-S160, wherein: Step S110: Acquire the first real-time sensing data and determine the real-time material hardness change parameters of the flexible circuit board to be monitored based on the first real-time sensing data. The first real-time sensing data is collected by the first sensing network element.

[0029] Specifically, multiple first sensing network elements are set up on the production line of the flexible circuit board to be monitored. The first sensing network element can be a sensor array. Each first sensing network element covers a different area of ​​the production line. By collecting the first real-time sensing data corresponding to the flexible circuit board to be monitored in real time and uploading it to the monitoring system in a timely manner, it is convenient to grasp the actual drilling operation process of the flexible circuit board to be monitored in a timely manner. Since pressure is one of the key factors causing material deformation, in addition to pressure data, the degree of deformation can also reflect the material's resistance to pressure. Hardness values ​​directly reflect the material's current hardness state. Therefore, the first real-time sensing data includes, but is not limited to, pressure data, deformation data, and hardness values. The collected first real-time sensing data can be imported into a pre-trained mathematical model for calculation, yielding the real-time material hardness change parameters corresponding to the first real-time sensing data. The pre-trained mathematical model can be a linear regression model, a multinomial regression model, a neural network model, etc. Specific pre-trained mathematical models are not specifically limited in this embodiment. When training the pre-trained mathematical model, training sensing data under different pressures, deformations, and hardnesses can be collected. The collected training sensing data is used to train the pre-trained mathematical model, adjusting the parameters to minimize prediction errors. The specific training method for the pre-trained mathematical model is not specifically limited in this embodiment, as long as the first real-time sensing data can be processed and analyzed to obtain the real-time material hardness corresponding to the first real-time sensing data. Comparing the real-time material hardness with the pre-trained material hardness yields the corresponding real-time material hardness change parameters. The pre-trained material hardness can be uploaded to the monitoring system by relevant personnel according to the actual drilling plan. The larger the hardness variation parameter, the higher the hardness value characterizing the flexible circuit board under monitoring.

[0030] Step S120: When the real-time material hardness change parameter is not higher than the preset change parameter threshold, the first drilling parameter is generated based on the first real-time sensing data.

[0031] Specifically, if the real-time material hardness change parameter is not higher than the preset change parameter threshold, representing the area where the flexible circuit board to be monitored does not show abnormal hardness, then the first drilling parameter can be generated based on the collected first real-time sensing data. The first drilling parameter includes, but is not limited to, drill bit rotation speed, feed speed, retraction speed, and drilling depth. The generation of the first drilling parameter based on the first real-time sensing data includes three steps: feature processing, establishing a prediction model, and generating the first drilling parameter. In the feature processing step, the first real-time sensing data needs to be preprocessed by cleaning, denoising, and normalizing. In the establishing the prediction model step, a suitable prediction model needs to be selected based on the sensing characteristics of the first real-time sensing data. Alternatively, relevant personnel can specify the prediction model based on historical experimental data. The prediction model can be a linear regression model, a multinomial regression model, etc. The specific prediction model is not specifically limited in this embodiment. Then, the selected prediction model is trained using the historically known drilling parameters and the corresponding historical sensing data to obtain a trained prediction model. In the generating the first drilling parameter step, the first real-time sensing data can be input into the trained prediction model, and the prediction model will directly output the corresponding first drilling parameter.

[0032] The preset threshold for the variable parameter can be determined by relevant personnel based on historical experimental data and then uploaded to the monitoring system. The specific preset threshold is not limited in this embodiment. When the real-time material hardness change parameter is not higher than the preset threshold, the drilling operation can be guided based on the first drilling parameter.

[0033] Step S130: When the real-time material hardness change parameter is higher than the preset change parameter threshold, the second sensing element to be activated is determined based on the first real-time sensing data, the second real-time sensing data is acquired, and the data matching value between the first real-time sensing data and the second real-time sensing data is determined. The second real-time sensing data is collected by the second sensing element to be activated.

[0034] Step S140: When the data matching value is higher than the preset matching threshold, a second punching parameter is generated based on the first real-time sensing data and the second real-time sensing data.

[0035] Specifically, if the real-time material hardness change parameter is higher than the preset change parameter threshold, it indicates that the flexible circuit board under monitoring may contain areas with abnormal hardness. In this case, the drilling operation cannot be directly guided according to the first drilling parameter corresponding to the first real-time sensing data. Instead, a second sensing network element with higher sensing accuracy can be activated to collect second real-time sensing data of the flexible circuit board under monitoring. After determining the second drilling parameter based on the first and second real-time sensing data, the drilling operation can be guided according to the second drilling parameter. Multiple second sensing network elements are also set on the production line of the flexible circuit board under monitoring. The second sensing network element can also be a sensor array, and each second sensing network element covers a different area of ​​the production line. The second sensing network element can be an optical sensor with high resolution. The specific second sensing network element is not specifically limited in this embodiment, as long as its sensing accuracy is higher than that of the first sensing network element. The second sensing network element is not always active; it is only activated when the real-time material hardness change parameter is higher than the preset change parameter threshold.

[0036] The first real-time sensing data and the second real-time sensing data are sensing data with different sensing accuracies. Since the second real-time sensing data is measured by a sensor with higher sensing accuracy, the sensing accuracy of the second real-time sensing data is higher than that of the first real-time sensing data. In the actual drilling operation environment, due to various factors such as equipment calibration and environmental interference, the sensing data collected by different sensing network elements may have certain differences. If the first real-time sensing data and the second real-time sensing data are directly combined, it may lead to unstable or unreliable second drilling parameters. Therefore, after determining the first real-time sensing data and the second real-time sensing data, the two data can be matched first, and the matching result can be quantified in the form of data matching value to facilitate the verification of the reliability of the sensing data.

[0037] If the data matching value is higher than a preset matching threshold, a second drilling parameter can be generated based on both the first and second real-time sensing data. The preset matching threshold can be determined by relevant personnel based on historical experimental data and then uploaded to the monitoring system. The steps for generating the first drilling parameter based on the first real-time sensing data in the above embodiment can be referred to, and will not be repeated here. The generated second drilling parameter is used to guide the drilling operation when the real-time material hardness change parameter is higher than a preset change parameter threshold.

[0038] Step S150: When the data matching value is not higher than the preset matching threshold, the third sensing network element to be activated is determined based on the first real-time sensing data and the second real-time sensing data, the third real-time sensing data is obtained, and the third punching parameters are generated based on the first real-time sensing data, the second real-time sensing data and the third real-time sensing data. The third real-time sensing data is collected by the third sensing network element to be activated.

[0039] Specifically, when the data matching value is not higher than the preset matching threshold, it indicates that there is a large difference between the first real-time sensing data and the second real-time sensing data. If the first real-time sensing data and the second real-time sensing data with large differences are directly combined to determine the second punching parameter, it may cause the second punching parameter to be unstable or unreliable. Therefore, it is necessary to activate the third sensing network element and use the third real-time sensing data collected by the third sensing network element together with the first real-time sensing data and the second real-time sensing data to guide the punching operation.

[0040] The third sensing element is activated only when the data matching value is not higher than a preset matching threshold; it is not always active. The third sensing element can be a sensing device with advanced sensing capabilities, such as an ultrasonic detector. The specific third sensing element is not specifically limited in this embodiment, as long as its sensing accuracy is higher than that of the second sensing element. The third sensing elements are arranged in an array on the production line of the flexible circuit board to be monitored, with different third sensing elements corresponding to different monitoring areas. The method for determining the third drilling parameters based on the first real-time sensing data, the second real-time sensing data, and the third real-time sensing data can refer to the steps for determining the first drilling parameters based on the first real-time sensing data in the above embodiments, and will not be elaborated here.

[0041] Step S160: Perform a drilling operation on the flexible circuit board to be monitored based on the first drilling parameter, or the second drilling parameter, or the third drilling parameter.

[0042] Specifically, when the real-time material hardness change parameter is not higher than the preset change parameter threshold, the drilling operation is guided by the first drilling parameter; when the real-time material hardness change parameter is higher than the preset change parameter threshold, and the data matching value is higher than the preset matching value, the drilling operation is guided by the second drilling parameter; when the real-time material hardness change parameter is higher than the preset change parameter threshold, and the data matching value is not higher than the preset matching value, the drilling operation is guided by the third drilling parameter. The flexible circuit board to be monitored is drilled based on the first, second, or third drilling parameter; that is, the equipment parameters of the drilling equipment are adjusted according to the first, second, or third drilling parameter to control the drilling equipment to perform the drilling operation according to the first, second, or third drilling parameter.

[0043] In this embodiment of the application, by acquiring and analyzing the material hardness change parameters of the flexible circuit board in real time, it is convenient to dynamically adjust the drilling parameters to adapt to the changes in the hardness of different materials. When the real-time material hardness change parameters exceed the preset threshold, additional second or third sensing network elements are activated to collect more sensing data to ensure that accurate drilling decisions can be made even in complex or uncertain situations. That is, it is convenient to flexibly adjust the drilling strategy according to the real-time situation. This multi-level data acquisition and analysis mechanism helps to ensure the adaptability between the drilling parameters and the drilling position, thereby improving the accuracy and reliability of the drilling process.

[0044] Furthermore, to avoid resource waste caused by activating too many second sensing network elements, this embodiment of the application determines the second sensing network elements to be activated based on the first real-time sensing data, which may specifically include: An image of the monitored area containing the flexible circuit board to be monitored is acquired, and abnormal hardness regions are identified from the monitored area image based on the first real-time sensing data. The material hardness change parameter corresponding to the abnormal hardness region is higher than a preset change parameter threshold, and the material hardness change parameter corresponding to different abnormal hardness regions is different. Each abnormal hardness region is marked in the monitored area image to obtain an image of marked abnormal areas. At least one perforation interest region corresponding to the abnormal hardness region is acquired, and each perforation interest region corresponds to a perforation position. All perforation interest regions are superimposed on the image of marked abnormal areas to obtain an integrated abnormal area image. At least one overlapping interest region is determined from the integrated abnormal area image, and the second sensing element corresponding to each overlapping interest region is determined as the second sensing element to be activated.

[0045] Specifically, an image acquisition device installed at the production line of the flexible printed circuit board to be monitored can be used to acquire images of the area to be monitored, as long as the acquired images of the area to be monitored contain the flexible printed circuit board to be monitored. The first real-time sensing data includes not only the sensing data itself but also the corresponding sensing element number. Based on the sensing element number, the corresponding sensing element can be accurately located. Since each sensing element has its own coverage area, abnormal hardness areas can be determined from the image of the area to be monitored based on the first real-time sensing data. The hardness change parameters corresponding to the abnormal hardness areas are all higher than a preset change parameter threshold. The specific preset change parameter threshold is not specifically limited in this embodiment. The image of the area to be monitored may contain one or more abnormal hardness areas; the specific number is not specifically limited in this embodiment.

[0046] The material hardness variation parameters corresponding to the same abnormal hardness region are consistent; that is, the material hardness is consistent at different locations within the same abnormal hardness region, but the material hardness variation parameters differ between different abnormal hardness regions. To facilitate the differentiation of abnormal hardness regions with different material hardness variation parameters, the abnormal hardness value corresponding to each abnormal hardness region can be determined first based on the material hardness variation parameters. Then, a hardness identifier corresponding to each abnormal hardness region can be determined based on a preset hardness identifier mapping relationship. This preset hardness identifier mapping relationship is the correspondence between abnormal hardness values ​​and hardness identifiers; the higher the abnormal hardness value, the denser the corresponding hardness identifiers. Based on the hardness identifiers corresponding to each abnormal hardness region, each abnormal hardness region is identified in the image of the area to be monitored, resulting in an image of identified abnormal regions, such as... Figure 2 As shown.

[0047] The area of ​​interest for punching holes is a region centered on the punching location with a preset radius. The punching location can be uploaded to the monitoring system in advance by relevant personnel based on the punching task. The specific preset distance is not specifically limited in this embodiment and can be determined by relevant personnel based on historical experimental data before being uploaded to the monitoring system. The punching edge information of each area of ​​interest is identified. Based on the punching edge information of each area, all areas of interest are superimposed onto the image of the identified abnormal areas to obtain an integrated abnormal area image, such as... Figure 3 As shown, the circular area is the area of ​​interest for drilling. The area where the area of ​​interest for drilling overlaps with the area of ​​abnormal hardness is called the overlapping area of ​​interest. Since the overlapping area of ​​interest is the intersection of the area of ​​interest for drilling and the area of ​​abnormal hardness, it needs to be closely monitored during the drilling process. If the drilling parameters do not match the actual situation in the overlapping area of ​​interest, it will likely affect the drilling quality of the corresponding area of ​​interest for drilling.

[0048] When determining the overlapping region of interest, a preset feature recognition algorithm can be used to identify whether each pixel in the integrated abnormal region image is simultaneously located within the perforation region of interest and the abnormal hardness region. If a pixel satisfies both conditions, it is considered a pixel of interest within the overlapping region of interest. The overlapping region of interest is then determined based on these pixels. The preset feature recognition algorithm is not specifically limited in this embodiment and can be set by relevant personnel based on historical experimental data. Based on the overlapping region of interest and the coverage area corresponding to each second sensing element, a second sensing element to be activated is selected from all second sensing elements for second real-time sensing data acquisition, rather than activating all second sensing elements. This facilitates meeting further sensing data acquisition needs while avoiding resource waste caused by activating too many second real-time sensing elements.

[0049] Furthermore, to improve the reliability and quality of the flexible circuit board to be monitored, the technical method provided in this application, when determining the overlapping region of interest from the integrated anomaly region, may specifically include: The actual overlapping region is determined from the integrated abnormal region. The actual overlapping region is the area where the area of ​​interest for drilling and the abnormal hardness region overlap. The distance between the center point of the actual overlapping region and the corresponding drilling position is identified, and the first score corresponding to the distance is determined based on the mapping relationship between the distance and the first preset score. The hardness change difference between the material hardness change parameter corresponding to the actual overlapping region and the preset change parameter threshold is identified, and the second score corresponding to the hardness change difference is determined based on the mapping relationship between the hardness change difference and the second preset score. The overlapping area corresponding to the actual overlapping region is identified, and the third score corresponding to the overlapping area is determined based on the mapping relationship between the overlapping area and the third preset score. The overlap score is determined based on the first, second, and third scores, and the expansion area corresponding to the overlap score is determined based on the overlap score and the preset expansion mapping relationship. The actual overlapping region is adjusted based on the expansion area to obtain the overlapping area of ​​interest.

[0050] Specifically, when determining the overlapping region of interest, the region where the perforation region of interest and the corresponding abnormal hardness region actually overlap can be determined from the integrated abnormal region according to the preset edge detection algorithm. The region where there is actual overlap is called the actual overlapping region. The actual overlapping region may be the final overlapping region of interest, or it may not be the final overlapping region of interest, and further analysis and processing are required. The preset edge detection algorithm is not specifically limited in this embodiment of the application.

[0051] After determining the actual overlapping area, the center point of the actual overlapping area can be determined first using a preset feature recognition algorithm. Then, the distance between the center point of the actual overlapping area and the corresponding drilling position can be determined using a preset distance calculation formula. The specific preset feature recognition algorithm and preset distance calculation formula are not specifically limited in this embodiment. After determining the distance, a first score corresponding to the distance is determined based on a first preset score mapping relationship. The first preset score mapping relationship is the correspondence between the distance and the first score; the smaller the distance, the higher the first score. The difference in hardness change between the material hardness change parameter corresponding to the actual overlapping area and a preset change parameter threshold is calculated. Then, a second score corresponding to the hardness change difference is determined based on a second preset score mapping relationship. The second preset score mapping relationship is the correspondence between the hardness change difference and the second score; the larger the hardness change difference, the higher the second score. Based on a preset edge detection algorithm, the overlapping area of ​​the actual overlapping area is determined. Then, a third score corresponding to the overlapping area is determined based on a third preset score mapping relationship. The third preset score mapping relationship is the correspondence between the overlapping area and the third score; the larger the overlapping area, the higher the third score. In this embodiment of the application, the specific contents of the preset edge detection algorithm, the first preset score mapping relationship, the second preset score mapping relationship, and the third preset score mapping relationship are not specifically limited, and can be determined by relevant personnel based on historical experimental data and then uploaded to the monitoring system.

[0052] After determining the first, second, and third scores corresponding to the actual overlapping area, the sum of these three scores is calculated to obtain the overlap score. Finally, based on a preset edge-expansion mapping relationship, the expansion area corresponding to the overlap score is determined. The preset edge-expansion mapping relationship is the correspondence between the overlap score and the expansion area; the higher the overlap score, the larger the corresponding expansion area. The specific content of the preset edge-expansion mapping relationship is not specifically limited in this embodiment of the application and can be determined by relevant personnel based on historical experimental data and then uploaded to the monitoring system. After determining the expansion area, the overlapping area of ​​interest can be obtained by expanding the edge outward based on the actual overlapping area, rather than simply using the actual overlapping area to represent the final overlapping area of ​​interest. This moderate edge-expansion adjustment method facilitates the improvement of the fit between the overlapping area of ​​interest and the actual situation. By monitoring the overlapping area of ​​interest more accurately and effectively, it is easier to discover and handle potential problems in a timely manner, thereby improving the reliability and quality of the flexible circuit board under monitoring.

[0053] Furthermore, to improve the accuracy of determining the actual overlapping region, the technical method provided in this application, when determining the actual overlapping region from the integration anomaly region, may specifically include: Identify the area of ​​interest for drilling from the integrated abnormal areas, and at least one abnormal hardness area that overlaps with the area of ​​interest for drilling; when the area of ​​interest for drilling corresponds to at least two abnormal hardness areas, identify the overlap area between each abnormal hardness area and the area of ​​interest for drilling, and the material hardness variation parameter of each abnormal hardness area; based on each overlap area, the material hardness variation parameter corresponding to each overlap area, and the preset overlap parameter mapping relationship, determine the overlap score corresponding to the area of ​​interest for drilling; determine the target adjustment strategy corresponding to the area of ​​interest for drilling based on the overlap score, and determine the corresponding actual overlap area based on the target adjustment strategy and the area of ​​interest for drilling.

[0054] Specifically, under normal circumstances, when the area of ​​interest for drilling overlaps with only one abnormal hardness area, the area of ​​interest for drilling is determined as the actual overlapping area. However, when the same area of ​​interest for drilling overlaps with at least two abnormal hardness areas, it is necessary to further analyze the overlap between different abnormal hardness areas and the corresponding area of ​​interest for drilling. The final actual overlapping area is determined based on the analysis results. The final actual overlapping area may be smaller than, equal to, or larger than the area of ​​interest for drilling.

[0055] When there are at least two abnormal hardness regions corresponding to the area of ​​interest for drilling, the overlapping area between each abnormal hardness region and the area of ​​interest for drilling can be identified first according to a preset edge recognition algorithm. The specific preset edge recognition algorithm is not specifically limited in this embodiment. Then, the adjustment score corresponding to the area of ​​interest for drilling is determined according to each overlapping area, the material hardness change parameter corresponding to each overlapping area, and the preset overlapping parameter mapping relationship. The preset overlapping parameter mapping relationship is the correspondence between the parameter combination of overlapping area and material hardness change parameter and the adjustment score. The adjustment score corresponding to any parameter combination can be determined based on the preset overlapping parameter mapping relationship. The specific content of the preset overlapping parameter mapping relationship is not specifically limited in this embodiment. It can be determined by relevant personnel based on historical experimental data and then uploaded to the monitoring system.

[0056] Finally, after selecting different target adjustment strategies based on different adjustment scores, the area of ​​interest for punching is expanded based on the target adjustment strategies. Specifically: When the adjustment score is within the first preset score range, the corresponding target adjustment strategy is to determine the actual overlapping area between the drilling interest area and the corresponding abnormal hardness area as the actual overlapping area; when the adjustment score is within the second preset score range, the corresponding target adjustment strategy is to determine the drilling interest area as the actual overlapping area; when the adjustment score is within the third preset score range, the corresponding target adjustment strategy is to expand the edge of the drilling interest area to obtain an expanded drilling interest area, and determine the expanded drilling interest area as the actual overlapping area.

[0057] By setting different preset score ranges, different adjustment scores are processed in a hierarchical manner. This hierarchical processing method facilitates more precise adjustment strategies based on different degrees of overlap, thereby improving the accuracy of determining the actual overlapping area. Specifically, the first preset score range is lower than the second preset score range, and the second preset score range is lower than the third preset score range. For example, the first preset score range is 0-5, the second preset score range is 6-10, and the third preset score range is 11-15. The specific preset score ranges are not specifically limited in this embodiment and can be determined and uploaded by relevant personnel based on historical experimental data.

[0058] Furthermore, to improve collaboration efficiency and response speed, when the first real-time sensing data or the second real-time sensing data contains preset material features, the technical solution provided in this application embodiment further includes: A virtual punching image is generated based on the first and second real-time sensing data, and then fed back to the terminal device of the relevant remote personnel. After receiving the punching suggestion from the relevant remote personnel, the remote punching information in the punching suggestion is identified. The remote punching information includes the remote punching location and remote punching parameters. Based on the remote punching location, the corresponding remote punching parameters are superimposed onto the virtual punching image to obtain a remote AR punching image. The remote AR punching image is then fed back to the AR device worn by the relevant punching personnel to guide them in performing the punching operation.

[0059] Specifically, a preset feature recognition algorithm can be used to identify and determine whether the first or second real-time sensing data contains preset material features. The specific preset feature recognition algorithm is not limited in this embodiment. The preset material features can be complex or special materials, determined by relevant personnel based on historical drilling experience. When the flexible circuit board to be monitored is made of complex or special materials, the probability of anomalies occurring during drilling is relatively high. In this case, relevant remote personnel can be invited to access the on-site data stream through a shared channel, i.e., receive the virtual drilling image generated by the first and second real-time sensing data, and provide professional suggestions after comprehensive analysis, i.e., drilling suggestions, to guide relevant drilling personnel to adjust the drill bit type or modify drilling parameters until the most suitable drilling solution is found.

[0060] In this embodiment, preset computer vision and image processing technologies can be used to fuse the first and second real-time sensing data to generate a virtual punched image. The specific preset computer vision and image processing technologies are not limited in this application embodiment, as long as the generated virtual punched image accurately reflects the structure, material, and other information of the flexible circuit board to be monitored. The generated virtual punched image can be transmitted in real-time to the mobile phones, tablets, computers, and other terminal devices of relevant remote personnel via Wi-Fi, 4G, 5G, and other network communication technologies. The punching suggestions provided by the relevant remote personnel include parameters such as remote punching location, hole diameter, hole depth, and hole spacing; the specific content is not limited in this application embodiment. Augmented reality (AR) technology is then used to overlay the remote punching location and corresponding remote punching parameters from the punching suggestions onto the virtual punched image to generate a remote AR punched image. The remote AR punched image can be fed back to the AR glasses, AR helmets, and other AR devices of the relevant punching personnel, allowing them to perform manual punching operations based on the guidance information in the remote AR punched image, thereby reducing human error during the punching process and improving punching accuracy.

[0061] This application provides a monitoring system, such as Figure 4 As shown, Figure 4 The monitoring system 400 shown includes a processor 401 and a memory 403. The processor 401 and the memory 403 are connected, for example, via a bus 402. Optionally, the monitoring system 400 may also include a transceiver 404. It should be noted that in practical applications, the transceiver 404 is not limited to one type, and the structure of this monitoring system 400 does not constitute a limitation on the embodiments of this application.

[0062] Processor 401 may be a CPU (Central Processing Unit), a general-purpose processor, a DSP (Digital Signal Processor), an ASIC (Application Specific Integrated Circuit), an FPGA (Field Programmable Gate Array), or other programmable logic devices, transistor logic devices, hardware components, or any combination thereof. It can implement or execute the various exemplary logic blocks, modules, and circuits described in conjunction with the disclosure of this application. Processor 401 may also be a combination that implements computational functions, such as including one or more microprocessor combinations, a combination of a DSP and a microprocessor, etc.

[0063] Bus 402 may include a pathway for transmitting information between the aforementioned components. Bus 402 may be a PCI (Peripheral Component Interconnect) bus or an EISA (Extended Industry Standard Architecture) bus, etc. Bus 402 can be divided into address bus, data bus, control bus, etc. For ease of representation, Figure 4 The symbol is represented by only one line, but this does not mean that there is only one bus or one type of bus.

[0064] The memory 403 may be a ROM (Read Only Memory) or other type of static storage device capable of storing static information and instructions, RAM (Random Access Memory) or other type of dynamic storage device capable of storing information and instructions, or an EEPROM (Electrically Erasable Programmable Read Only Memory), CD-ROM (Compact Disc Read Only Memory) or other optical disc storage, optical disc storage (including compressed optical discs, laser discs, optical discs, digital universal optical discs, Blu-ray discs, etc.), magnetic disk storage media or other magnetic storage devices, or any other medium capable of carrying or storing desired program code in the form of instructions or data structures and accessible by a computer, but not limited thereto.

[0065] The memory 403 is used to store application code that executes the solution of this application, and its execution is controlled by the processor 401. The processor 401 is used to execute the application code stored in the memory 403 to implement the content shown in the foregoing method embodiments.

[0066] The monitoring system includes, but is not limited to, mobile terminals such as mobile phones, laptops, digital radio receivers, PDAs (personal digital assistants), PADs (tablet computers), PMPs (portable multimedia players), and in-vehicle terminals (such as in-vehicle navigation terminals), as well as fixed terminals such as digital TVs and desktop computers. It can also include servers. Figure 4 The monitoring system shown is merely an example and should not impose any limitations on the functionality and scope of use of the embodiments of this application.

[0067] This application provides a computer-readable storage medium storing a computer program that, when run on a computer, enables the computer to execute the corresponding content in the aforementioned method embodiments.

[0068] This application provides a computer program product including a computer program that, when executed by a processor, implements the methods described in any of the above embodiments.

[0069] It should be understood that although the steps in the flowcharts of the accompanying figures are shown sequentially as indicated by the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the accompanying figures may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily completed at the same time, but can be executed at different times, and their execution order is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the sub-steps or stages of other steps.

[0070] The above description is only a partial embodiment of this application. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the principle of this application, and these improvements and modifications should also be considered within the scope of protection of this application.

Claims

1. A method for detecting perforations in flexible printed circuit boards, characterized in that, include: Acquire first real-time sensing data and determine the real-time material hardness change parameter of the flexible circuit board to be monitored based on the first real-time sensing data. The first real-time sensing data is collected by the first sensing network element. When the real-time material hardness change parameter is not higher than the preset change parameter threshold, the first drilling parameter is generated based on the first real-time sensing data. When the real-time material hardness change parameter is higher than the preset change parameter threshold, the second sensing element to be activated is determined based on the first real-time sensing data, the second real-time sensing data is acquired, and the data matching value between the first real-time sensing data and the second real-time sensing data is determined. The second real-time sensing data is collected by the second sensing element to be activated. When the data matching value is higher than the preset matching threshold, a second punching parameter is generated based on the first real-time sensing data and the second real-time sensing data. When the data matching value is not higher than the preset matching threshold, the third sensing network element to be activated is determined based on the first real-time sensing data and the second real-time sensing data, the third real-time sensing data is obtained, and the third punching parameters are generated based on the first real-time sensing data, the second real-time sensing data and the third real-time sensing data. The third real-time sensing data is collected by the third sensing network element to be activated. Based on the first drilling parameters, or the second drilling parameters, or the third drilling parameters, a drilling operation is performed on the flexible circuit board to be monitored.

2. The method for detecting perforations in flexible printed circuit boards according to claim 1, characterized in that, The step of determining the second sensing network element to be activated based on the first real-time sensing data includes: The image of the monitored area containing the flexible circuit board to be monitored is acquired, and abnormal hardness areas are identified from the monitored area image based on the first real-time sensing data. The material hardness change parameter corresponding to the abnormal hardness area is higher than the preset change parameter threshold, and the material hardness change parameter corresponding to different abnormal hardness areas is different. Each abnormal hardness region is identified in the image of the area to be monitored, resulting in an image of identified abnormal regions. Obtain at least one drilling interest area corresponding to the abnormal hardness area, and each drilling interest area corresponds to a drilling position. By overlaying all the punching concern areas onto the identified abnormal area image, an integrated abnormal area image is obtained; At least one overlapping region of interest is determined from the integrated abnormal region image, and the second sensing element corresponding to each overlapping region of interest is determined as the second sensing element to be activated.

3. The method for detecting perforations in flexible printed circuit boards according to claim 2, characterized in that, Determining overlapping regions of interest from the integrated anomaly regions includes: The actual overlapping area is determined from the integrated abnormal area, which is the area where the area of ​​concern for drilling and the area of ​​abnormal hardness overlap. Identify the distance between the center point of the actual overlapping area and the corresponding punching position, and determine the first score corresponding to the distance based on the mapping relationship between the distance and the first preset score. Identify the hardness change difference between the material hardness change parameter corresponding to the actual overlapping area and the preset change parameter threshold, and determine the second score corresponding to the hardness change difference based on the mapping relationship between the hardness change difference and the second preset score. Identify the overlapping area corresponding to the actual overlapping region, and determine the third score corresponding to the overlapping area based on the mapping relationship between the overlapping area and the third preset score; The overlap score is determined based on the first score, the second score, and the third score, and the expansion area corresponding to the overlap score is determined based on the overlap score and the preset expansion mapping relationship. The overlapping region of interest is obtained by adjusting the actual overlapping region based on the expanded area.

4. The method for detecting perforations in flexible printed circuit boards according to claim 3, characterized in that, Determining the actual overlapping region from the integrated anomaly region includes: Identify the punching interest area from the integrated anomaly area, and at least one anomalous hardness area that overlaps with the punching interest area; When the area of ​​interest for drilling corresponds to at least two abnormal hardness areas, identify the overlap area between each abnormal hardness area and the area of ​​interest for drilling, and the material hardness change parameters of each abnormal hardness area. Based on each overlapping area, the material hardness change parameter corresponding to each overlapping area, and the preset overlapping parameter mapping relationship, the adjustment score corresponding to the perforation focus area is determined. Based on the adjustment score, a target adjustment strategy corresponding to the punching attention area is determined, and based on the target adjustment strategy and the punching attention area, the corresponding actual overlapping area is determined.

5. The method for detecting perforations in flexible printed circuit boards according to claim 4, characterized in that, The step of determining the target adjustment strategy corresponding to the punching attention area based on the adjustment score includes: When the adjustment score is within the first preset score range, the corresponding target adjustment strategy is to determine the actual overlapping area between the perforation concern area and the corresponding abnormal hardness area as the actual overlapping area. When the adjustment score is within the range of the second preset score, the corresponding target adjustment strategy is to determine the punching attention area as the actual overlapping area; When the adjustment score is within the range of the third preset score, the corresponding target adjustment strategy is to expand the edge of the punching attention area to obtain the expanded punching attention area, and determine the expanded punching attention area as the actual overlapping area.

6. The method for detecting perforations in flexible printed circuit boards according to claim 1, characterized in that, When the first real-time sensing data or the second real-time sensing data contains preset material features, it further includes: A virtual punch image is generated based on the first real-time sensing data and the second real-time sensing data, and the virtual punch image is fed back to the terminal device of the relevant remote personnel. Upon receiving a drilling suggestion from a relevant remote person, the remote drilling information in the drilling suggestion is identified, including the remote drilling location and remote drilling parameters. Based on the remote punching location, the corresponding remote punching parameters are superimposed onto the virtual punching image to obtain a remote AR punching image; The remote AR punching image is fed back to the AR device worn by the punching personnel to guide them in the punching operation.

7. A monitoring system, characterized in that, The monitoring system includes: At least one processor; Memory; At least one application, wherein the at least one application is stored in memory and configured to be executed by at least one processor, the at least one application being configured to: perform a hole detection method for flexible circuit boards according to any one of claims 1-6.

8. A computer-readable storage medium, characterized in that, include: The computer program is stored and can be loaded by a processor and executed as described in any one of claims 1-6, which is a method for detecting holes in flexible printed circuit boards.

9. A computer program product, characterized in that, The method includes a computer program that, when executed by a processor, implements the steps of a hole detection method for flexible circuit boards according to any one of claims 1-6.

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