Display panel detection method and device, point screen detection system and electronic equipment

Abstract

The invention relates to a display panel detection method and device, a point screen detection system and electronic equipment, and the method comprises the steps: obtaining a current work station type of a line body where a to-be-detected panel is located and a target defect grade corresponding to the to-be-detected panel, and adjusting the detection configuration information corresponding to the current work station type according to the target defect grade; and according to the adjusted detection configuration information, controlling a detection device associated with the current work station type to detect the to-be-detected panel. By the adoption of the panel defect detection method and device, differential detection can be achieved on the basis of different defect levels of the panel at the current work station, the data processing amount of equipment is effectively reduced, the equipment load is reduced, unnecessary manpower and test time waste is effectively reduced, and the productivity efficiency is improved.

Description

[0001] This application is a divisional application of the invention patent application filed on November 20, 2025, with application number 202511711582.9, entitled "Display Panel Detection Method, Apparatus, Dot Screen Detection System and Electronic Equipment". Technical Field

[0002] This application relates to the field of display panel testing technology, and in particular to a display panel testing method, apparatus, dot detection system and electronic equipment. Background Technology

[0003] In the manufacturing process of display panels (also known as displays or screens), screen testing is a critical quality control step. Before leaving the factory, qualified panels undergo screen testing on semi-finished products. This test observes whether the panel can be lit up, whether there is screen flickering, light leakage, or defective or dead pixels. Panels with quality problems are then graded. Based on the grading level, after secondary repair processing, the panels need to undergo screen testing again.

[0004] In existing technologies, all display panels use the same testing scheme, whether it is the initial screen detection or the re-inspection after repair. This undifferentiated screen detection scheme leads to unnecessary waste of testing resources and limited efficiency. Summary of the Invention

[0005] In view of the above, this application provides a display panel detection method, apparatus, dot detection system, and electronic device to solve at least one problem existing in the background art.

[0006] In a first aspect, embodiments of this application provide a display panel detection method, the method comprising: Obtain the current workstation type of the online body to which the panel under test is located, and the target defect level corresponding to the panel under test; Adjust the detection configuration information corresponding to the current workstation type according to the target defect level; Based on the adjusted detection configuration information, the detection device associated with the current workstation type is controlled to perform detection on the panel to be tested.

[0007] In some embodiments, the detection configuration information includes at least one of the following: the type of test image, the display order of the test images, the detection duration of each test image, and the drive signal parameters, wherein the drive signal parameters are used to control the drive signal applied by the detection device to the panel under test.

[0008] In some embodiments, when the panel under test is a display panel that has been repaired and assigned to the production line for re-inspection according to the target defect level, the target defect level is the defect level determined by the panel under test in the first inspection.

[0009] In some embodiments, adjusting the detection configuration information corresponding to the current workstation type according to the target defect level includes: Based on the panel model of the panel under test and the target defect level, a target yield file is obtained from the server, wherein the target yield file is generated by the server based on the panel model of the panel under test and the first inspection data of the panels in the batch on multiple production lines, according to the defect level; Adjust the detection configuration information corresponding to the current workstation type based on the target yield file.

[0010] In some embodiments, the target yield file includes at least one defect type and the occurrence rate of each defect type; adjusting the detection configuration information corresponding to the current workstation type according to the target yield file includes: Determine the minimum test image combination, wherein the minimum test image combination includes multiple types of test images that can cover all defect types under the current workstation type in the target yield file; The detection time of each test image in the minimum test image combination is adjusted according to the occurrence rate of each defect type in the target yield file.

[0011] In some embodiments, adjusting the detection time of each test image in the minimum test image combination based on the occurrence rate of each defect type in the target yield file includes: For each test image in the minimum test image combination, the preset detection time of the test image is adjusted to the detection time corresponding to the target interval according to the target interval to which the occurrence rate of the defect type belongs among multiple preset intervals; wherein, different preset intervals correspond to different detection times.

[0012] In some embodiments, the method further includes: The re-inspection data obtained from the re-inspection of the panel under test is uploaded to the server, so that the server can generate the latest yield file according to the defect level based on the panel model and the re-inspection data of the panels in the batch under test on multiple production lines. The system periodically retrieves the latest yield file corresponding to the target defect level from the server, and readjusts the detection configuration information based on the difference between the latest yield file and the historically obtained yield files, in order to detect the display panel to be re-inspected.

[0013] In some embodiments, adjusting the detection configuration information corresponding to the current workstation type according to the target defect level includes: Based on the panel model of the panel under test and the target defect level, a test configuration file is obtained from the server. The test configuration file is generated by the server based on the target yield file. The target yield file is generated by the server based on the panel model of the panel under test and the first test data of the panels in the batch on multiple production lines, according to the defect level. Adjust the detection configuration information corresponding to the current workstation type to be consistent with the detection configuration information in the detection configuration file.

[0014] In some embodiments, when the panel under test is a display panel awaiting its first inspection, the target defect level is a defect level determined based on the panel model of the panel under test and the overall yield value of the tested panels in the same batch.

[0015] In some embodiments, adjusting the detection configuration information corresponding to the current workstation type according to the target defect level includes: Based on the target defect level, a target adjustment strategy is matched from multiple preset adjustment strategies, wherein the target defect level is positively correlated with the detection intensity, and different preset adjustment strategies correspond to different detection intensities; Adjust the detection configuration information corresponding to the current workstation type according to the target adjustment strategy.

[0016] In some embodiments, adjusting the detection configuration information corresponding to the current workstation type according to the target defect level includes: The server obtains the panel model and overall yield file of the panel under test and its batch, wherein the overall yield file is generated by the server based on the panel model and the first inspection data of the panels in the batch on multiple production lines, according to the defect type. Based on the occurrence rate of each defect type under the current workstation type contained in the overall yield file, determine the defect level corresponding to each defect type; Based on the target defect level and the defect level corresponding to each defect type, the target adjustment strategy corresponding to the current workstation type is matched from the predefined strategy library; Adjust the detection configuration information corresponding to the current workstation type according to the target adjustment strategy.

[0017] In some embodiments, the method further includes: For the display panels that pass the simplified testing configuration in the current workstation, random inspection is carried out using the standard testing configuration corresponding to the current workstation to obtain the inspection results. When the sampling inspection results contain defect types, the detection configuration corresponding to the previous workstation of the current workstation is restored to the standard detection configuration corresponding to the previous workstation.

[0018] Secondly, embodiments of this application provide a display panel detection device, the device comprising: The first acquisition module is used to acquire the current workstation type of the online body to which the panel under test is located and the target defect level corresponding to the panel under test. The adjustment module is used to adjust the detection configuration information corresponding to the current workstation type according to the target defect level; The control module is used to control the detection equipment associated with the current workstation type to perform detection on the panel to be tested according to the adjusted detection configuration information.

[0019] Thirdly, embodiments of this application provide a dot detection system, the system comprising: The host computer is configured to perform the display panel detection method as described in any of the first aspects; The testing equipment is configured to perform screen detection on the panel to be tested under the control of the host computer.

[0020] Fourthly, embodiments of this application provide an electronic device including a processor, the processor being configured to invoke instructions to cause the electronic device to execute the display panel detection method as described in any of the first aspects.

[0021] Fifthly, embodiments of this application provide a storage medium having an executable program stored thereon, wherein the executable program, when executed by a processor, implements the display panel detection method as described in any of the first aspects.

[0022] This application provides a display panel inspection method, apparatus, dot-mapping inspection system, and electronic device. By acquiring the current workstation type of the online body where the panel under test is located and the target defect level corresponding to the panel, and adjusting the inspection configuration information corresponding to the current workstation type based on the target defect level, the system controls the inspection equipment associated with the current workstation type to perform inspection on the panel according to the adjusted inspection configuration information. Therefore, the current workstation can achieve differentiated inspection based on different defect levels of the panel, effectively reducing the data processing volume and equipment load, and also effectively reducing unnecessary waste of manpower and testing time, thereby improving production efficiency. Attached Figure Description

[0023] Figure 1 This is an application environment diagram illustrating a display panel detection method according to an embodiment of this application.

[0024] Figure 2This is a schematic diagram of a portion of the data in a yield file, as shown in an embodiment of this application.

[0025] Figure 3 A flowchart illustrating a display panel testing method according to an embodiment of this application. Figure 1 .

[0026] Figure 4 A flowchart illustrating a display panel testing method according to an embodiment of this application. Figure 2 .

[0027] Figure 5 This is a schematic diagram illustrating some of the defect types involved in the yield file, as shown in an embodiment of this application.

[0028] Figure 6 A flowchart illustrating a display panel testing method according to an embodiment of this application. Figure 3 .

[0029] Figure 7 A flowchart illustrating a display panel testing method according to an embodiment of this application. Figure 4 .

[0030] Figure 8 A flowchart illustrating a display panel testing method according to an embodiment of this application. Figure 5 .

[0031] Figure 9 A flowchart illustrating a display panel testing method according to an embodiment of this application. Figure 6 .

[0032] Figure 10 This is a schematic diagram of the structure of a display panel detection device according to an embodiment of this application. Detailed Implementation

[0033] To make the technical solution and beneficial effects of this application more apparent and understandable, a detailed description is provided below by listing specific embodiments. The accompanying drawings are not necessarily drawn to scale, and local features may be enlarged or reduced to more clearly show the details of the local features; unless otherwise defined, the technical and scientific terms used herein have the same meanings as those in the technical field to which this application pertains.

[0034] The embodiments in this application are not exhaustive, but merely illustrative of some embodiments, and are not intended to limit the scope of protection of this disclosure. Unless otherwise specified, each step in a particular embodiment can be implemented as an independent embodiment, and the steps can be arbitrarily combined. For example, a solution after removing some steps in a particular embodiment can also be implemented as an independent embodiment, and the order of the steps in a particular embodiment can be arbitrarily interchanged. Furthermore, the optional implementation methods in a particular embodiment can be arbitrarily combined; moreover, the embodiments can be arbitrarily combined, for example, some or all steps of different embodiments can be arbitrarily combined, and a particular embodiment can be arbitrarily combined with the optional implementation methods of other embodiments.

[0035] In each embodiment of this application, unless otherwise specified or in case of logical conflict, the terminology and / or descriptions of the embodiments are consistent and can be referenced by each other. Technical features in different embodiments can be combined to form new embodiments based on their inherent logical relationships.

[0036] In the description of the embodiments of this application, it should be understood that the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Therefore, features defined with "first" and "second" may explicitly or implicitly include one or more of the stated features. In the description of the embodiments of this application, "multiple" means two or more, unless otherwise explicitly specified.

[0037] In related technologies, all display panels undergo the same testing process, whether for initial screen inspection or post-repair screen re-inspection. This leads to unnecessary waste of testing resources and limited efficiency. For example, if the yield rate of a batch of products is 99.8%, it means that the yield rate of each screen in this batch is above 99.8%. For such high-yield screens, there is no need to perform multi-screen, long-term screen inspection on each screen during the second re-inspection. However, for batches with lower yield rates, such as only 70%, a more detailed inspection of each screen is required during the second re-inspection.

[0038] Figure 1 This diagram illustrates the application environment of a display panel detection method according to an embodiment of this application. Figure 1As shown, the host computer 110 communicates with the server 120 and controls the testing device 130 to perform screen detection on the display panel 140 under test. The server 120 communicates with the host computers 110 of all production lines (hereinafter referred to as "lines"), supports data upload and download by the host computers 110 of each line, and receives and stores the test data uploaded by the host computers 110 of each line. The testing device 130 includes an image generator 131 and an optical testing device 132. The image generator 131 is connected to the display panel 140. During the screen detection process, the host computer 110 sends the image data and image cropping instructions required for screen detection to the image generator 131. According to the received instructions, the image generator 131 controls the display panel 140 to switch and display different test images (e.g., pure red, pure green, pure blue, red and white horizontal stripes, red and white vertical stripes, etc.) sequentially according to a preset time sequence through its built-in application. During each frame display, the optical testing equipment 132 performs real-time automated optical inspection (AOI) on the screen display content of the display panel 140 and reports the inspection data to the host computer 110. The host computer 110 then uploads the inspection data to the server 120. The host computer can connect to the inspection equipment of multiple workstations on the same production line, or the inspection equipment of different workstations can be connected to different host computers.

[0039] Understandable, Figure 1 The application environment shown is merely exemplary, and this application is not limited thereto. In practical applications, the display panel detection method can be applied to other similar environments or scenarios according to specific needs.

[0040] In the embodiments of this application, the terms "display panel", "panel", "screen" and "display screen" can be used interchangeably, and the terms "panel model" and "screen model" can be used interchangeably.

[0041] In some examples, taking the inspection of screen model M by line A as an example, in line A, using a host computer and inspection equipment, the screen model M undergoes its first spot inspection, obtaining the first inspection data. This data includes defect information and the defect level determined for each screen. Defect information includes, for example, bright spots, green bright spots, double bright spots, triple bright spots, clusters of bright spots, vertical faint lines, horizontal faint lines, etc. After each screen is inspected, the host computer processes the inspection data of that screen according to a unified format and uploads it to the server.

[0042] In some examples, the server categorizes all received inspection data from different panel models on different production lines according to panel model, production batch, and production line type. The categorization follows these priority principles: First priority is screen model, meaning data is collected separately for each screen model; second priority is production line type (i.e., workstation type), as different workstations use different inspection and processing procedures for the same screen. For example, workstation A only needs to verify basic display functions (e.g., using only pure red, pure green, and pure blue test images for screen detection), while workstation B needs to add a pure white screen test on top of the three test images; third priority is screen grade: screens of the same model and from the same batch with different defect grades need to be counted separately. Based on this multi-level categorization, the server generates yield files categorized by screen model, production line type, and defect grade, and displays them in the software interface for the host computer of each production line to download as needed.

[0043] For example, the server generates multiple yield files based on defect levels for the same screen model's inspection data. Different yield files correspond to different defect levels, and each yield file contains yield data corresponding to that defect level. Figure 2 The image shows a portion of the yield data in the yield file that includes defect level 1 (optimal). The specific fields included are: Type (workstation type), Line ID (line ID), Product ID (screen model), Defect type (e.g., bright spots, broken bright spots, dark spots, and horizontal lines), Defect QT (number of defects of that type), Output (total number of screens of that model detected on the line within the statistical period), Quality grade description (Pnl grade), indicating the quality grade of screens of a certain defect type on the line. Quality grades can include NG (scrap), Y1 (brightness unevenness defect, reflowable), etc., and Defect rate (percentage of screens of that defect type out of the total number of screens detected, i.e., the occurrence rate of the defect type).

[0044] In some examples, the server categorizes all received inspection data from different panel models on different production lines according to panel model, production batch, and production line type. For instance, based on the initial inspection data of panels of the same model and batch on multiple production lines, an overall yield file is generated according to defect type to record the overall yield and the occurrence rate and distribution of various defects.

[0045] See Figure 3 As shown in the figure, this application provides a display panel detection method, including the following steps: S301: Obtain the current workstation type of the online body to which the panel under test is located and the target defect level corresponding to the panel under test; S302: Adjust the detection configuration information corresponding to the current workstation type according to the target defect level; S303: Based on the adjusted detection configuration information, control the detection equipment associated with the current workstation type to perform detection on the panel to be tested.

[0046] In this embodiment, the execution entity of the display panel detection method is a host computer, which is a client running on a terminal device. Terminal devices include, but are not limited to, personal computers (PCs), industrial control computers (IPCs), or mobile terminals.

[0047] In some examples, when the panel under test is a display panel that has been repaired and assigned to the line for re-inspection according to the target defect level, the target defect level is the defect level that the panel under test was determined to be in the first inspection.

[0048] Defect levels can be classified based on the number of defects in the panel during the initial inspection. For example, they can be divided into multiple levels based on the number of detected defects, from fewest to most: fewer defects result in a lower defect level (e.g., "Best" or "Level 1"), representing higher quality; more defects result in a higher level (e.g., "Defective" or "Level 3"), representing lower quality. The number of defects in a panel refers to the sum of the number of defects of all defect types detected in a single inspection. The number of defects of a specific defect type refers to the number of defects detected for that specific defect type (e.g., bright spots, green bright spots, or horizontal faint lines) in the same inspection.

[0049] After a panel identified as defective in the initial screen inspection (i.e., the first inspection) has been repaired, it needs to undergo a second screen inspection (i.e., a re-inspection). Since the panels were categorized according to their defect level after the initial inspection, during the re-inspection, panels from the same batch are assigned to different inspection lines based on their defect level determined in the initial inspection. For example, if a batch of 5000 panels is inspected and classified into three defect levels after the initial screen inspection—2000 in level 1, 2000 in level 2, and 1000 in level 3—then the panels of each level will be placed on three separate inspection lines for re-inspection; that is, each line independently re-inspects the panels of its corresponding level.

[0050] In this embodiment, the repaired panels are assigned to corresponding re-inspection lines according to the defect level determined in their initial inspection. Since each line is dedicated to processing panels with a specific defect level, for each line's current workstation type, panels with the same defect level can be re-inspected in batches by adjusting the inspection configuration information corresponding to that workstation type each time. This not only reduces the complexity of frequently switching configurations but also improves the stability and efficiency of the inspection.

[0051] In step S301, for cases where the panel under test is a repaired display panel awaiting re-inspection, the target defect level of the panel under test, as determined in the initial inspection, can be obtained based on information input by the user (e.g., an operator). For example, the target defect level can be determined based on allocation information input by the user, where the allocation information characterizes the defect level to which the repaired panel under test is assigned in the line. Alternatively, the host computer can automatically query the target defect level of the panel under test, determined in the initial inspection, based on the unique identifier of the panel under test obtained through scanning. Furthermore, the host computer can automatically match all panels of that panel model that were determined to have that defect level in the initial inspection, based on the panel model (e.g., panel model M) and target defect level (e.g., level 1) input by the user.

[0052] In other examples, when the panel under test is a display panel awaiting its first inspection, the target defect level is a defect level determined based on the panel model of the panel under test and the overall yield value of the tested panels in the same batch.

[0053] For example, the target defect level of the panel under test can be determined by the server based on the panel model of the panel under test and the overall yield value of the tested panels in the same batch. The host computer of the panel under test can obtain the target defect level of the panel under test from the server. This target defect level can be determined based on the overall yield value of the tested panels and a pre-set mapping relationship between yield ranges and defect levels. For example, the target defect level of the panel under test can be determined based on the panel model of the panel under test and the yield range to which the overall yield value of the tested panels in the same batch belongs.

[0054] The overall yield value of the tested panels in the same batch can be determined based on the ratio between the number of qualified tested panels and the total number of tested panels. The higher the overall yield value of the panels in the same batch, the better the overall quality of the panels in that batch, and the lower the defect risk of the corresponding panels (such as "optimal" or "level 1"), thus assigning them a lower defect level; conversely, the lower the overall yield value of the panels in the same batch, the higher the corresponding defect level (such as "defective" or "level 3").

[0055] The current workstation type of the panel under test can be manually selected by the operator, or it can be identified by the host computer based on the real-time flow information of the panel under test in the production line (such as barcode scanning records).

[0056] It is understandable that a production line includes multiple workstations, and different types of workstations take different tests and procedures for the same screen. Therefore, the test configuration information (which can be referred to as "standard configuration information") of different types of workstations under normal screen testing (i.e. standard screen testing) conditions also differs.

[0057] In some examples, the detection configuration information corresponding to the current workstation type includes: configuration parameters for controlling the detection device associated with the current workstation type to perform screen detection, such as test image information and / or drive signal parameters.

[0058] The test image information may include at least one of the following: the type of test image, the display order of the test images, and the detection duration of each test image. Drive signal parameters are used to control the drive signals applied to the panel under test, such as drive voltage signals and / or drive current signals.

[0059] The type of test image refers to the image format used to detect defects in the display panel, such as pure red, pure green, pure blue, red and white horizontal stripes, red and white vertical stripes, etc. The display order of the test images refers to the order in which the test images are presented in the detection process. The detection time for a single test image refers to the time a single test image remains on the display panel (i.e., screen lock time or lock-in seconds).

[0060] In some examples, in step S302 above, the host computer can obtain a combination of detection parameters that has a preset correspondence with the target defect level and the current workstation type, and adjust the detection configuration information corresponding to the current workstation type according to the combination of detection parameters. For example, when the target defect level is low (i.e., the number of defects is small), a simplified combination of detection parameters can be matched for the workstation type, using fewer test image types (e.g., only including red, green, and blue basic images), and shortening the detection time of a single image to improve detection efficiency; while when the target defect level is high (i.e., the number of defects is large), an enhanced combination of detection parameters is matched, using more types of test images (e.g., adding pure white, grayscale, high-contrast stripes, etc.), and extending the detection time of a single image to improve the defect detection rate.

[0061] In some examples, in step S303 above, the detection device includes an image generator and an optical testing device. According to the adjusted detection configuration information, the host computer can send corresponding test image data and image cropping instructions to the image generator to drive the panel under test to display test images in a preset order. Based on the detection duration of each image in the adjusted detection configuration information, the dwell time of each image is controlled. During the image display, the optical testing device is triggered to perform automated optical detection on the panel under test, obtain detection data, and upload it to the server.

[0062] In existing technologies, all display panels on the same testing station use the same testing scheme, whether for initial screen inspection or post-repair screen re-inspection. For example, each panel requires 18 test images for initial inspection, and the same 18 images are used for re-inspection. Furthermore, all display panels in the initial screen inspection use the same testing configuration. This "undifferentiated" testing method is significantly redundant for high-yield panels with few defects, resulting in wasted testing resources. In contrast, this application obtains the current station type of the line where the panel under test is located and the target defect level of the panel. Based on the target defect level, it adjusts the testing configuration information corresponding to the current station type, and then controls the testing equipment associated with the current station type to perform testing on the panel according to the adjusted testing configuration information. Therefore, the current station can achieve differentiated testing based on different defect levels of the panel, effectively reducing the data processing volume and equipment load, as well as unnecessary waste of manpower and testing time, thus improving production efficiency.

[0063] In some embodiments, such as Figure 4 As shown, step S302 above, which adjusts the detection configuration information corresponding to the current workstation type according to the target defect level, may include the following steps: S401: Based on the panel model and target defect level of the panel under test, obtain the target yield file from the server. The target yield file is generated by the server based on the panel model of the panel under test and the first inspection data of the panels in the batch on multiple production lines, according to the defect level. S402: Adjust the detection configuration information corresponding to the current workstation type according to the target yield file.

[0064] The panel model number of the panel under test can be obtained by user input or automatically by scanning the panel identification information.

[0065] Different yield files correspond to different defect levels, and each yield file reflects the actual yield of the panel model under a specific defect level. The target yield file can be generated by the server based on the first inspection data of panels of the same panel model belonging to the batch of the panel under test on multiple production lines, and statistically analyzed by defect level.

[0066] Initial inspection data includes defect information for each panel acquired during the initial inspection process, and the defect level determined for each panel based on that information.

[0067] In step S401, the host computer can send a data request to the server based on the panel model and target defect level of the panel under test, so as to request the server to return the target yield file corresponding to the target defect level to the host computer based on the panel model and target defect level of the panel under test.

[0068] After receiving the target yield file corresponding to the target defect level returned by the server, the host computer reads all the defect type information involved in the file and adjusts the detection configuration information corresponding to the current workstation type.

[0069] In some examples, the target yield file includes at least one defect type and the occurrence rate of each defect type. The occurrence rate of a defect type quantifies the severity of that defect type. For example, the occurrence rate of a defect type could be the ratio of the number of defective pixels in that defect type to the total number of pixels in the entire display panel, specifically obtained by pixel counting of the defective area using an image acquisition device. Alternatively, the occurrence rate of a defect type could also be the ratio between the number of panels containing that defect type and the total number of display panels included in the statistics.

[0070] In step S402, the host computer can determine the test image combination, detection duration, and / or the drive signal parameters applied to the display panel by the detection equipment during re-inspection based on the defect type information contained in the target yield file, thereby adjusting the detection configuration information corresponding to the current workstation type. For example, regarding drive signal parameters, the host computer can match and call the corresponding drive signal parameters in the preset drive parameter configuration table based on the defect type information contained in the target yield file to enhance the visibility of bright spots in the dark. For example, if bright spot defects (such as bright spots, green bright spots, and clusters of bright spots) account for the largest proportion of defect types in the target yield file, the drive voltage or timing can be adjusted to enhance the visibility of bright spots in the dark. This helps to detect potential defects more effectively during the re-inspection stage and improves detection accuracy.

[0071] Compared to the approach of using the same indiscriminate testing method for all panel re-inspections as the initial inspection, this embodiment integrates the initial inspection data of all panels of the same model from multiple production lines and within the batch to which the panel under test belongs through a server. It generates yield files according to defect levels. The host computer adjusts the inspection configuration information corresponding to the current workstation type based on the target yield file. In this way, the re-inspection is dynamically optimized according to the actual yield of each batch of panels, rather than indiscriminate re-inspection. Low-yield batches are given priority inspection (e.g., more inspection images and time lock), while the inspection content is simplified for high-yield batches (e.g., fewer inspection images and time lock). This achieves rapid re-inspection, effectively reduces the data processing volume of the equipment, and greatly improves the production and testing efficiency of display modules. In addition, since the target yield file is generated by the server based on the panel model of the panel under test and the first inspection data of the panels in the batch on multiple production lines according to the defect level, the yield file integrates the real inspection results of the same batch of panels of the same model from different production lines. This allows the yield file to more accurately reflect the actual defect distribution of the panels under the corresponding defect level. Thus, adjusting the inspection configuration information corresponding to the current workstation type based on the target yield file can improve the accuracy of the inspection configuration information adjustment.

[0072] In some embodiments, the target yield file includes at least one defect type and the occurrence rate of each defect type; in step S402 above, adjusting the detection configuration information corresponding to the current workstation type according to the target yield file may include: Step S4021: Determine the minimum test image combination, wherein the minimum test image combination contains multiple types of test images that can cover all defect types under the current workstation type in the target yield file; Step S4022: Adjust the detection time of each test image in the minimum test image combination according to the occurrence rate of each defect type in the target yield file.

[0073] In some embodiments, in step S4021 above, based on the various defect types under the current workstation type in the target yield file, the preset test image type library corresponding to the current workstation type can be filtered to match multiple test images that can cover all defect types under the current workstation type in the target yield file, so as to form the minimum test image set, thereby reducing redundant test images.

[0074] In some embodiments, the display order of each test image can be adjusted according to the order of occurrence of at least one defect type from high to low. For example, test images corresponding to defect types with higher occurrence rates are displayed earlier, and test images corresponding to defect types with lower occurrence rates are displayed later.

[0075] In some embodiments, step S4022 above, adjusting the detection time of each test image in the minimum test image combination according to the occurrence rate of each defect type in the target yield file, may include: For each test image in the minimum test image combination, the preset detection time of the test image is adjusted to the detection time corresponding to the target interval according to the target interval to which the occurrence rate of the defect type belongs among multiple preset intervals; wherein, different preset intervals correspond to different detection times.

[0076] The preset intervals are multiple consecutive incidence intervals pre-divided based on the incidence rate of each adverse disease type.

[0077] Compared to using a fixed detection time for all test images, this embodiment achieves differentiated control of the detection time for test images by mapping the occurrence rate of defect types to a preset threshold range and matching the corresponding detection time to adjust the preset detection time for each test image, which can effectively improve the efficiency of re-inspection.

[0078] For example, when the incidence rate is below the first threshold (e.g., 0.2%), the detection time for the corresponding test image is shortened from the normal detection time (e.g., 4 seconds) to the first detection time (e.g., 2 seconds); when the incidence rate is between the first threshold and the second threshold (e.g., 0.2%–0.4%), the detection time is shortened from the normal detection time to the second detection time (the second detection time is longer than the first detection time, e.g., the second detection time is 3 seconds); when the incidence rate is above the second threshold (e.g., 0.4%), the normal detection time is maintained to ensure the reliability of defect detection.

[0079] In some embodiments, step S4022 is an optional step, meaning that it is not necessary to adjust the detection duration of each test image. For example, the detection duration can be the normal detection duration (i.e., the same as the detection duration of the test images in the first detection).

[0080] It should be understood that, for the sake of simplicity of the illustrations, steps S4021 and S4022 are not shown in the accompanying drawings, but they belong to the preferred embodiments of this application. Their specific implementation has been described in detail in the specification and does not affect the understanding and implementation of this application by those skilled in the art.

[0081] Figure 5 This is a schematic diagram illustrating some of the defect types involved in the yield file provided for embodiments of this application. For example... Figure 5As shown, assuming the host computer obtains the first-level yield file of line A and panel model M from the server, the defect types involved in the yield file include: bright spots, green bright spots, double bright spots, triple bright spots, more than 3 consecutive bright spots, cluster bright spots, missing BM (Black Matrix), missing color resist, broken bright spots, and clustered broken bright spots. These defect types can all be detected by L0 (all-black screen) and RGB (red, green, blue) screens. Therefore, when re-inspecting this batch of panels, in addition to retaining 6 fixed mandatory inspection screens, the remaining images in the original 18 screens can be simplified to L0 (all-black screen) plus RGB screens, thereby reducing the total number of inspection screens from 18 to 8. Based on the occurrence rate of each defect type in the yield rate file, set the display time for each frame, i.e., increase or decrease the lock second (i.e., the detection duration of the test image). If the occurrence rate is low, for example, the occurrence rate of all involved defect types is less than or equal to 0.2, then decrease the lock second, that is, shorten the normal display time of a frame (e.g., 4 seconds) to the first detection duration (e.g., reduced to 2 seconds). If the occurrence rate is between 0.2 and 0.4, then shorten the normal display time of a frame to the second detection duration (the second detection duration is longer than the first detection duration, for example, reduced to 3 seconds). If it is greater than 0.4, then display according to the detection duration required to normally display a frame.

[0082] In this embodiment, by determining the minimum combination of test images that can cover all defect types under the current workstation type in the target yield file, and combining the occurrence rate of each defect type in the target yield file, the display order and / or detection time of each image are dynamically adjusted. In this way, while ensuring the panel defect detection capability, redundant images and invalid detection time are effectively reduced, and the re-inspection efficiency and resource utilization under the current workstation type are improved.

[0083] In some embodiments, such as Figure 6 As shown, the method may further include the following steps: S601: Upload the re-inspection data obtained from the re-inspection of the panel under test to the server, so that the server can generate the latest yield file according to the defect level based on the panel model and the re-inspection data of the panels in the batch under test on multiple production lines; S602: Periodically retrieves the latest yield file corresponding to the target defect level from the server, and readjusts the inspection configuration information based on the difference between the latest yield file and the historically retrieved yield files, in order to inspect the display panel to be re-inspected.

[0084] Here, the re-inspection data includes defect information for each panel obtained during this re-inspection process, as well as the defect level determined for each panel based on this information.

[0085] After the re-inspection begins, the host computer uploads the re-inspection data obtained from this re-inspection to the server. The server then generates a new yield file based on the re-inspection data of panels of the same model from multiple production lines, categorized by defect level. For example, when the number of re-inspection data belonging to the same defect level and panel model received by the server reaches a preset quantity, a new yield file is generated. This preset quantity can be set according to actual needs, such as 200 panels. It is understandable that the re-inspection yield of a panel after repair will be higher than the yield of the first inspection.

[0086] When the server generates yield files corresponding to different defect levels based on the re-inspection data, the host computer can periodically read the yield files generated by the server to obtain the defect types and their occurrence rates of the panels after this batch of re-inspection, and optimize the detection of the panels that have not yet been re-inspected. For example, every preset time interval, the detection configuration optimization process is performed once for the panels to be re-inspected on the current line.

[0087] The acquisition period for the latest yield file can be determined based on a user-defined time period, such as 2 hours or other suitable durations. This embodiment does not impose specific limitations on this.

[0088] For example, the host computer reads yield file 2 again, which is the yield file for the current production line A and panel model M. The defect types it involves include: broken bright spots and clustered broken bright spots. These defects can all be detected by the L0 screen. Therefore, when re-inspecting this batch of panels, in addition to retaining 6 fixed mandatory inspection screens, the previously set L0 (all-black screen) and RGB screens can be simplified to the L0 screen, resulting in a total of 7 screens to be inspected. Based on the occurrence rate of the defect types in yield file 2, the display time for each screen is set, i.e., increasing or decreasing the lock time. If the occurrence rate is low, for example, the occurrence rate of all involved defect types is less than or equal to 0.2, the lock time is reduced, that is, the normal display time for one screen (e.g., 4 seconds) is shortened to the first inspection time (e.g., reduced to 2 seconds). If the occurrence rate is between 0.2 and 0.4, the normal display time for one screen is shortened to the second inspection time (the second inspection time is longer than the first inspection time, for example, reduced to 3 seconds). If it is greater than 0.4, the normal display time for one screen is used.

[0089] When the host computer periodically reads the latest yield file, if the latest yield file contains a recurring or newly added defect type compared to the previously acquired yield file, such as including but not limited to missing BM, missing color resist, broken bright spots, or clustered broken bright spots, then a test image matching the defect type is added to the minimum test image combination accordingly, and the corresponding lock time is dynamically increased according to the occurrence rate of the recurring or newly added defect type.

[0090] In this embodiment, considering that the module detection parameters issued by the host computer are generated by the server based on the re-inspection results of panels that have recently reached a preset number (e.g., 200 pieces), there may be a risk that certain types of defects may be missed due to the test screen being too simplified; therefore, by periodically reading the latest yield file in the server and then dynamically optimizing the detection configuration, the re-inspection coverage and accuracy can be effectively improved.

[0091] In some embodiments, the method may further include the following steps: For display panels that have passed the re-inspection using a simplified testing configuration in the current workstation, a random inspection is conducted using the standard testing configuration corresponding to the current workstation to obtain the inspection results; if the inspection results include defective types, the testing configuration corresponding to the previous workstation is restored to the standard testing configuration corresponding to the previous workstation.

[0092] In the standard detection configuration, there are more types of test images than in the simplified detection configuration; and / or, the detection duration of at least one test image in the standard detection configuration is longer than the detection duration of at least one test image in the simplified detection configuration.

[0093] The panels that have undergone re-inspection need to be randomly sampled. If defects or yield exceeding the standard are still found (for example, the defect rate of bright spots exceeds the threshold, such as the threshold of 0.1%, which means that the batch is considered to be unqualified by the previous station), then at least one of the following operations shall be performed: restore the detection configuration of all panels to be re-inspected in the previous station to the standard configuration (that is, change the detection configuration information of the front-end dot screen station to a full inspection screen and add a lock time to prevent missed detection), and the host computer generates an OQC (Outgoing Quality Control) alarm file for the line and uploads it to the server so that the server can display the OQC pass rate of the line on the electronic Kanban interface.

[0094] In this way, while ensuring efficient re-inspection, the risk of missed inspection can be detected in a timely manner through random sampling; once a defect is detected by random sampling, the standard testing configuration of the upstream workstation is immediately restored, thereby effectively improving the reliability of re-inspection and product yield.

[0095] In some embodiments, such as Figure 7 As shown, in step S302 above, adjusting the detection configuration information corresponding to the current workstation type according to the target defect level may include the following steps: S701: Obtain the detection configuration file from the server based on the panel model and target defect level of the panel to be tested; S702: Adjust the detection configuration information corresponding to the current workstation type to be consistent with the detection configuration information in the detection configuration file.

[0096] The test configuration file is generated by the server based on the target yield file, which is generated by the server based on the panel model of the panel to be tested and the first test data of the panels in the batch on multiple production lines, according to the defect level.

[0097] In some examples, the server generating a detection configuration file based on a target yield file may include: determining a minimum combination of test images for each workstation type, the minimum combination of test images covering all defect types under that workstation type in the target yield file, wherein the minimum combination of test images contains multiple types of test images; determining the detection duration of each test image in the minimum combination of test images based on the occurrence rate of each defect type in the target yield file; and generating the detection configuration file based on the multiple types of test images in the minimum combination of test images and the detection duration of each test image.

[0098] Here, the process of determining the minimum test image combination and the process of determining the detection time of each test image can refer to steps S4021 and S4022 and their optional implementations in the aforementioned embodiments, and will not be repeated here.

[0099] In other examples, the detection configuration file can be dynamically generated by the server based on the defect types and their occurrence rates in the yield file, combined with multiple preset detection modes (such as normal mode, simplified A mode, simplified B mode, etc.). The detection configuration file contains specific detection configuration information, such as the test image combination, the lock-in time for each image, and the display order. Different detection modes correspond to different detection configurations. For example, the normal mode contains a complete set of test images, with a normal lock-in time (usually 4 seconds), which is suitable for panel re-inspection with low yield and high defect level; the simplified A mode can appropriately reduce the number of test images and shorten the lock-in time to 2 seconds; the simplified B mode further simplifies the image set and compresses the lock-in time to 1 second, which is suitable for panel re-inspection with high yield and low defect level.

[0100] In this embodiment, after the host computer obtains the corresponding inspection configuration file from the server based on the panel model and defect level of the panel to be tested, it can directly update the inspection configuration information of the current workstation to be consistent with the configuration file and send it to the inspection equipment of the workstation to perform screen detection. This method realizes centralized generation and unified distribution of inspection configurations, eliminating the need for host computers on each production line to occupy local computing resources to adjust inspection configurations using yield files. This not only reduces the equipment burden on the host computer but also enables overall control of the production efficiency of the entire factory and real-time response to the quality status of different batches of panels, allowing for flexible optimization of inspection efficiency.

[0101] In some embodiments, when the panel to be tested is a display panel awaiting its first inspection, step S302 above, adjusting the inspection configuration information corresponding to the current workstation type according to the target defect level, may include the following steps: Based on the target defect level, the target adjustment strategy is matched from multiple preset adjustment strategies; the detection configuration information corresponding to the current workstation type is adjusted according to the target adjustment strategy.

[0102] Among them, the target adjustment strategy is used to indicate the detection intensity related to the target defect level. The target defect level is positively correlated with the detection intensity, and different preset adjustment strategies indicate different detection intensities.

[0103] When the panel under test is a display panel waiting for its first inspection, the target defect level is determined based on the panel model of the panel under test and the overall yield value of the tested panels in the same batch.

[0104] The host computer can obtain multiple preset adjustment strategies from the local machine or the server. For example, there are at least two preset adjustment strategies, namely a simplified detection strategy and a standard detection strategy, with the corresponding detection intensities increasing sequentially.

[0105] For example, when the target defect level corresponding to the panel under test is a first defect level, the target adjustment strategy is a preset adjustment strategy indicating a first detection intensity; when the target defect level corresponding to the panel under test is a second defect level, the target adjustment strategy is a preset adjustment strategy indicating a second detection intensity. Wherein, the overall yield value corresponding to the second defect level is lower than the overall yield value corresponding to the first defect level, and the first detection intensity is lower than the second detection intensity. For example, the preset adjustment strategy indicating the first detection intensity is a simplified detection strategy, and the preset adjustment strategy indicating the second detection intensity is a standard detection strategy.

[0106] Compared to using the same indiscriminate testing scheme for all panels in the same batch, this embodiment determines the target defect level of the panel under test based on the panel model and the overall yield value of the tested panels in the same batch. Based on the target defect level, the testing configuration information corresponding to the current workstation type is adjusted. In this way, the untested display panels are dynamically optimized according to the actual yield data of the tested panels in the same batch, rather than indiscriminate testing. For example, untested display panels in low-yield batches are tested according to the standard testing method (i.e., using a complete combination of test images and the normal lock-in time), while untested display panels in high-yield batches are tested with simplified testing content (e.g., reducing test images and lock-in time) to achieve rapid testing. This can greatly reduce the data processing volume of the equipment and effectively improve the testing efficiency of the display module.

[0107] In other embodiments, such as Figure 8As shown, in step S302 above, adjusting the detection configuration information corresponding to the current workstation type according to the target defect level may include the following steps: S801: Obtain the panel model and overall yield file of the panel under test from the server. The overall yield file is generated by the server based on the panel model and the first test data of the panels in the batch on multiple production lines, according to the defect type. S802: Determine the defect level corresponding to each defect type based on the occurrence rate of each defect type under the current workstation type contained in the overall yield file; S803: Based on the target defect level and the defect level corresponding to each defect type, match the target adjustment strategy corresponding to the current workstation type in the predefined strategy library; S804: Adjust the detection configuration information corresponding to the current workstation type according to the target adjustment strategy.

[0108] In some examples, the occurrence rate of each type of defect can be determined within multiple consecutive occurrence rate intervals to determine its corresponding defect level, with each occurrence rate interval corresponding to a defect level.

[0109] In some examples, defect types with a defect level exceeding a preset threshold can be identified as critical defect types. Based on the target defect level and the defect level of the critical defect type, a target adjustment strategy corresponding to the current workstation type is matched against a predefined strategy library. For instance, the target defect level and the defect level of the critical defect type can be combined into a composite query condition. This composite query condition is then compared with a preset mapping table between strategies and conditions in the strategy library to retrieve the target adjustment strategy corresponding to the current workstation type.

[0110] In some examples, different detection adjustment strategies in the strategy library correspond to different detection configurations. For example, the detection configuration corresponding to the standard detection strategy includes a complete set of test images and a lock-in time of the normal lock-in time (usually 4 seconds), which is suitable for panel detection with low yield and high defect level. Compared with the standard detection strategy, the detection configuration corresponding to the first simplified detection strategy reduces the number of test images and shortens the lock-in time to 2 seconds. Compared with the first simplified detection strategy, the detection configuration corresponding to the second simplified detection strategy further simplifies the image set and compresses the lock-in time to 1 second, which is suitable for panel detection with high yield and low defect level.

[0111] In this embodiment, the overall yield file is generated by the server based on the panel model of the panel under test and the first inspection data of the panels in the batch on multiple production lines, according to the defect type. That is, the overall yield file integrates the real inspection results of the same batch of panels of the same model from different production lines, so that the overall yield file can more accurately reflect the actual defect distribution of the batch to which the panel under test belongs. In this way, by combining the target defect level and the defect level corresponding to each defect type in the overall yield file, the detection configuration information corresponding to the current workstation type can be adjusted, which can improve the accuracy of the detection configuration information adjustment.

[0112] It is worth noting that in the display panel testing method provided in this application embodiment, the adjustment of the testing configuration information corresponding to the current workstation type can be dynamic and reversible. For example, in the initial testing, the server can periodically count the overall yield value of the tested panels in the same batch, and adjust the testing configuration information corresponding to the current workstation type from simplified testing to standard testing configuration based on the target defect level determined by the overall yield value. After completing this adjustment, the server will continuously monitor the testing results of subsequent panels. If the monitoring data indicates that the overall yield value of the batch under simplified testing fluctuates or triggers the preset defect level upgrade condition, the testing configuration information corresponding to the current workstation type will be restored to the standard testing configuration, thereby realizing the optimization and adaptive adjustment of testing resource configuration.

[0113] Next, combined Figure 9 Taking the re-inspection of the display panel as an example, the display panel testing method provided in this application embodiment will be further explained.

[0114] See Figure 9 As shown in the embodiment of this application, a display panel detection method may include the following steps: S901: First screen detection data is uploaded to the server.

[0115] Taking the inspection of screen model M by line A as an example, in line A, the host computer and inspection equipment perform the first screen inspection on screen model M, obtaining the first inspection data. This data includes defect information and the defect level determined for each screen. Defect information includes, for example, bright spots, green bright spots, double bright spots, triple bright spots, clusters of bright spots, vertical faint lines, horizontal faint lines, etc. The host computer processes the first inspection data according to a unified format and uploads it to the server.

[0116] S902: The server processes the data to obtain a yield file, ready for the next use.

[0117] The server categorizes all received inspection data from different production lines and different panel models according to panel model and production line type. For inspection data of the same screen model, multiple yield files are generated based on defect level. Different yield files correspond to different defect levels.

[0118] S903: During the second screen test, the yield file is retrieved from the server and parsed. The module configuration information is then displayed in a simplified manner, and the second screen test data is uploaded to the server.

[0119] After a panel that was initially identified as defective has been repaired, it needs to undergo a re-inspection. Since the screens were categorized and placed according to their defect levels after the initial inspection, during the re-inspection, panels from the same batch will be assigned to different production lines based on the defect levels determined in the initial inspection.

[0120] After the host computer on each production line obtains the panel model, defect level, and workstation type to be re-inspected, it establishes communication with the server and downloads the yield files corresponding to each defect level of the panel model from the server.

[0121] The host computer performs the first simplification and optimization process based on the downloaded yield file. That is, it reads all the defect types involved in the file and simplifies the detection configuration information (i.e., display module configuration information) issued in this batch. After that, the host computer will send the detection data (i.e. re-inspection data) obtained from the second screen detection back to the server. The server generates the yield file again based on the returned data.

[0122] A second round of streamlining is performed on the production line at regular intervals. After the server generates a set of yield files based on the re-inspection data, the host computer can read the server's files at regular intervals to obtain the latest yield values ​​of this batch of re-inspected panels, and then optimize and test the panels that have not yet been re-inspected.

[0123] S904: The sampling inspection station performs screen testing again. If there are still defects, the screen testing data is uploaded to the server.

[0124] The screens that have undergone re-inspection still need to be sampled for inspection. If any defects or yield exceeding the standard are found (for example, if the defect rate of bright spots exceeds 0.1%, the batch is deemed to have failed the inspection of the previous station), the host computer will generate an OQC alarm file for the line and upload it to the server.

[0125] S905: After the server processes the data, the host computer of this production line displays the module configuration information again in a simplified manner.

[0126] After the server processes the OQC alarm file uploaded by the host computer, it displays the OQC pass rate of the line on the electronic Kanban interface. The host computer changes the detection configuration information of the front-end screen station of the line to a full inspection screen and adds a lock-second function to prevent missed detections.

[0127] In summary, this application uses host computer software in conjunction with server software to intelligently simplify the configuration information of the display module, which greatly reduces the amount of data processing on the machine, reduces the waste of detection resources, and effectively improves the detection efficiency of the display module.

[0128] The various embodiments or implementation methods described in this specification are presented in a progressive manner. Each embodiment focuses on the differences from other embodiments, and the same or similar parts between the embodiments can be referred to each other.

[0129] In the various embodiments of the specification, some or all of the steps and their optional implementations can be arbitrarily combined with some or all of the steps in other embodiments, or arbitrarily combined with the optional implementations in other embodiments.

[0130] This application also provides a display panel detection device, such as... Figure 10 As shown, the display panel detection device 100 includes: The first acquisition module 101 is used to acquire the current workstation type of the online body to which the panel under test is located and the target defect level corresponding to the panel under test; The adjustment module 102 is used to adjust the detection configuration information corresponding to the current workstation type according to the target defect level; The control module 103 is used to control the detection equipment associated with the current workstation type to perform detection on the panel to be tested according to the adjusted detection configuration information.

[0131] In some embodiments, the detection configuration information includes at least one of the following: the type of test image, the display order of the test images, the detection duration of each test image, and the drive signal parameters, wherein the drive signal parameters are used to control the drive signal applied by the detection device to the panel under test.

[0132] In some embodiments, when the panel under test is a display panel that has been repaired and assigned to the production line for re-inspection according to the target defect level, the target defect level is the defect level determined by the panel under test in the first inspection.

[0133] In some embodiments, the adjustment module 102 is used to: Based on the panel model of the panel under test and the target defect level, a target yield file is obtained from the server, wherein the target yield file is generated by the server based on the panel model of the panel under test and the first inspection data of the panels in the batch on multiple production lines, according to the defect level; Adjust the detection configuration information corresponding to the current workstation type based on the target yield file.

[0134] In some embodiments, the target yield file includes at least one defect type and the occurrence rate of each defect type; the adjustment module 102 is used to: Determine the minimum test image combination, wherein the minimum test image combination includes multiple types of test images that can cover all defect types under the current workstation type in the target yield file; The detection time of each test image in the minimum test image combination is adjusted according to the occurrence rate of each defect type in the target yield file.

[0135] In some embodiments, the adjustment module 102 is used to: For each test image in the minimum test image combination, the preset detection time of the test image is adjusted to the detection time corresponding to the target interval according to the target interval to which the occurrence rate of the defect type belongs among multiple preset intervals; wherein, different preset intervals correspond to different detection times.

[0136] In some embodiments, the apparatus further includes: The upload module is used to upload the re-inspection data obtained from the re-inspection of the panel under test to the server, so that the server can generate the latest yield file according to the defect level based on the panel model and the re-inspection data of the panels in the batch to which the panel under test belongs in multiple production lines; The second acquisition module is used to periodically acquire the latest yield file corresponding to the target defect level from the server; The adjustment module 102 is also used to readjust the detection configuration information based on the difference between the latest yield file and the historically acquired yield file, so as to detect the display panel to be re-inspected.

[0137] In some embodiments, the adjustment module 102 is used to: Based on the panel model of the panel under test and the target defect level, a test configuration file is obtained from the server. The test configuration file is generated by the server based on the target yield file. The target yield file is generated by the server based on the panel model of the panel under test and the first test data of the panels in the batch on multiple production lines, according to the defect level. Adjust the detection configuration information corresponding to the current workstation type to be consistent with the detection configuration information in the detection configuration file.

[0138] In some embodiments, when the panel under test is a display panel awaiting its first inspection, the target defect level is a defect level determined based on the panel model of the panel under test and the overall yield value of the tested panels in the same batch.

[0139] In some embodiments, the adjustment module 102 is used to: Based on the target defect level, a target adjustment strategy is matched from multiple preset adjustment strategies, wherein the target defect level is positively correlated with the detection intensity, and different preset adjustment strategies correspond to different detection intensities; Adjust the detection configuration information corresponding to the current workstation type according to the target adjustment strategy.

[0140] In some embodiments, the adjustment module 102 is used to: The server obtains the panel model and overall yield file of the panel under test and its batch, wherein the overall yield file is generated by the server based on the panel model and the first inspection data of the panels in the batch on multiple production lines, according to the defect type. Based on the occurrence rate of each defect type under the current workstation type contained in the overall yield file, determine the defect level corresponding to each defect type; Based on the target defect level and the defect level corresponding to each defect type, the target adjustment strategy corresponding to the current workstation type is matched from the predefined strategy library; Adjust the detection configuration information corresponding to the current workstation type according to the target adjustment strategy.

[0141] In some embodiments, the apparatus further includes: The sampling inspection module is used to conduct random inspections on display panels that have passed the simplified inspection configuration in the current workstation using the standard inspection configuration corresponding to the current workstation, and obtain the sampling inspection results. The adjustment module 102 is also used to restore the detection configuration corresponding to the previous workstation of the current workstation to the standard detection configuration corresponding to the previous workstation when the sampling result contains a defect type.

[0142] This application embodiment also provides a screen dot detection system, the system comprising: The host computer is configured to execute the display panel detection method described in any embodiment applied to the host computer side; The testing equipment is configured to perform screen detection on the display panel under the control of the host computer.

[0143] This application also provides an electronic device, including a processor, which calls instructions to cause the electronic device to perform the steps of the display panel detection method provided in any of the foregoing embodiments.

[0144] This application also provides a storage medium, including an executable program stored thereon, which, when executed by a processor, implements the steps of the display panel detection method provided in any of the foregoing embodiments.

[0145] For ease of understanding, the following focuses on explaining the terminology used in this embodiment: In this application embodiment, the processor is a circuit with signal processing capabilities. In one implementation, the processor can be a circuit with instruction read and execute capabilities, such as a Central Processing Unit (CPU), a microprocessor, a Graphics Processing Unit (GPU) (which can be understood as a type of microprocessor), or a Digital Signal Processor (DSP). In another implementation, the processor can implement certain functions through the logical relationships of hardware circuits. The logical relationships of the aforementioned hardware circuits are fixed or reconstructable. For example, the processor is a hardware circuit implemented using an Application-Specific Integrated Circuit (ASIC) or a Programmable Logic Device (PLD), such as an FPGA. In a reconstructable hardware circuit, the processor loads a configuration document, implementing a cyclical process of hardware circuit configuration. This can be understood as the processor loading instructions to implement the functions of some or all of the above units or modules in a cyclical process. In addition, it can also be a hardware circuit designed for artificial intelligence, which can be understood as an ASIC, such as a Neural Network Processing Unit (NPU), a Tensor Processing Unit (TPU), a Deep Learning Processing Unit (DPU), etc.

[0146] The computer-readable storage medium provided in this embodiment can execute the display panel detection method of the above embodiment. Its implementation principle and technical effect are similar to those of the above embodiment, and will not be repeated here.

[0147] The aforementioned computer-readable storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk. The readable storage medium can be any available medium accessible to a general-purpose or special-purpose computer.

[0148] An exemplary readable storage medium is coupled to a processor, enabling the processor to read information from and write information to the readable storage medium. Of course, the readable storage medium can also be a component of the processor. The processor and the readable storage medium can reside in an Application Specific Integrated Circuit (ASIC). Alternatively, the processor and the readable storage medium can exist as discrete components in an electronic device or a host device.

[0149] Those skilled in the art will understand that all or part of the steps of the above-described method embodiments can be implemented by hardware related to program instructions. The aforementioned program can be stored in a computer-readable storage medium. When executed, the program performs the steps of the above-described method embodiments; and the aforementioned storage medium includes various media capable of storing program code, such as ROM, RAM, magnetic disks, or optical disks.

[0150] The various embodiments or implementation methods described in this specification are presented in a progressive manner. Each embodiment focuses on the differences from other embodiments, and the same or similar parts between the embodiments can be referred to each other.

[0151] In the description of this specification, references to "one embodiment," "some embodiments," "illustrative embodiment," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with an embodiment or example is included in at least one embodiment or example of this application. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0152] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features therein. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of this application.

Claims

1. A method for detecting a display panel, characterized in that, The method includes: Obtain the current workstation type of the online body to which the panel under test is located and the target defect level of the panel under test in the first inspection. The panel under test is a display panel that has been repaired and is to be re-inspected. Based on the panel model of the panel to be tested and the target defect level, the target yield file is obtained from the server. Different yield files correspond to different defect levels. Based on the defect type information contained in the target yield file, determine the test image combination, detection duration, and / or the drive signal parameters applied to the display panel by the detection equipment during re-inspection, so as to adjust the detection configuration information corresponding to the current workstation type. Based on the adjusted detection configuration information, the detection device associated with the current workstation type is controlled to perform detection on the panel to be tested.

2. The display panel detection method according to claim 1, characterized in that, The detection configuration information includes at least one of the following: the type of test image, the display order of the test images, the detection duration of each test image, and the driving signal parameters. The driving signal parameters are used to control the driving signal applied by the detection device to the panel under test. And / or, the panel to be tested is a display panel that has been repaired and assigned to the production line for re-inspection according to the target defect level.

3. The display panel detection method according to claim 1, characterized in that, The target yield file includes at least one defect type; the test image combination is a minimum test image combination, which contains multiple types of test images and can cover all defect types under the current workstation type in the target yield file.

4. The display panel detection method according to claim 3, characterized in that, The target yield file also includes the occurrence rate of each of the defect types; the detection time of each test image in the minimum test image combination is adjusted based on the occurrence rate of each of the defect types in the target yield file.

5. The display panel detection method according to claim 4, characterized in that, For each test image in the minimum test image combination, the preset detection time of the test image is adjusted to the detection time corresponding to the target interval according to the target interval to which the occurrence rate of the defect type belongs among multiple preset intervals; wherein, different preset intervals correspond to different detection times.

6. The display panel detection method according to claim 1, characterized in that, The method further includes: The re-inspection data obtained from the re-inspection of the panel under test is uploaded to the server, so that the server can generate the latest yield file according to the defect level based on the panel model and the re-inspection data of the panels in the batch under test on multiple production lines. The system periodically retrieves the latest yield file corresponding to the target defect level from the server, and readjusts the detection configuration information based on the difference between the latest yield file and the historically obtained yield files, in order to detect the display panel to be re-inspected.

7. The display panel testing method according to any one of claims 1 to 6, characterized in that, The method further includes: For the display panels that pass the simplified testing configuration in the current workstation, random inspection is carried out using the standard testing configuration corresponding to the current workstation to obtain the inspection results. When the sampling inspection results contain defect types, the detection configuration corresponding to the previous workstation of the current workstation is restored to the standard detection configuration corresponding to the previous workstation.

8. A method for detecting a display panel, characterized in that, The method includes: Obtain the current workstation type of the online body to which the panel under test is located and the target defect level of the panel under test in the first inspection. The panel under test is a display panel that has been repaired and is to be re-inspected. Based on the panel model and target defect level of the panel under test, a test configuration file is obtained from the server; the test configuration file is generated by the server based on the target yield file corresponding to the target defect level. Adjust the detection configuration information corresponding to the current workstation type to be consistent with the detection configuration information in the detection configuration file, and send it to the detection device of the workstation corresponding to the current workstation type to perform screen detection.

9. The display panel detection method according to claim 8, characterized in that, The detection configuration information includes at least one of the following: the type of test image, the display order of the test images, the detection duration of each test image, and the driving signal parameters. The driving signal parameters are used to control the driving signal applied by the detection device to the panel under test. And / or, the panel to be tested is a display panel that has been repaired and assigned to the production line for re-inspection according to the target defect level.

10. The display panel detection method according to claim 8, characterized in that, The process of generating the detection configuration file includes: For each workstation type, the server determines a minimum combination of test images. This minimum combination of test images can cover all defect types under that workstation type in the target yield file. The minimum combination of test images includes multiple types of test images. The detection configuration file is generated based on the various types of test images in the minimum test image combination.

11. The display panel detection method according to claim 10, characterized in that, The process of generating the detection configuration file by the server also includes: Based on the occurrence rate of each defect type in the target yield file, determine the detection time for each test image in the minimum test image combination; The detection configuration file is generated based on the various types of test images in the minimum test image combination and the detection duration of each test image.

12. The display panel detection method according to claim 8, characterized in that, The detection configuration file is dynamically generated by the server based on the defect types and their occurrence rates in the target yield file, combined with multiple preset detection modes; different detection modes correspond to different detection intensities.

13. The display panel testing method according to any one of claims 8 to 12, characterized in that, The method further includes: For the display panels that pass the simplified testing configuration in the current workstation, random inspection is carried out using the standard testing configuration corresponding to the current workstation to obtain the inspection results. When the sampling inspection results contain defect types, the detection configuration corresponding to the previous workstation of the current workstation is restored to the standard detection configuration corresponding to the previous workstation.

14. A display panel detection device, characterized in that, The apparatus for performing the display panel detection method as described in any one of claims 1 to 13, the apparatus comprising: The first acquisition module is used to acquire the current workstation type of the online body to which the panel under test is located and the target defect level corresponding to the panel under test. The adjustment module is used to adjust the detection configuration information corresponding to the current workstation type according to the target defect level; The control module is used to control the detection equipment associated with the current workstation type to perform detection on the panel to be tested according to the adjusted detection configuration information.

15. A screen dot detection system, characterized in that, The system includes: The host computer is configured to perform the display panel detection method as described in any one of claims 1 to 13; The testing equipment is configured to perform screen detection on the panel to be tested under the control of the host computer.

16. An electronic device, characterized in that, Includes a processor, the processor being configured to invoke instructions to cause the electronic device to execute the display panel detection method as described in any one of claims 1 to 13.

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