Multi-AOI equipment joint detection method and device, equipment and storage medium

Abstract

The invention relates to a multi-AOI equipment joint detection method and device, equipment and a storage medium, and the method comprises the steps: obtaining an initial detection result of each piece of AOI equipment after the initial detection of each piece of AOI equipment is completed; extracting initial defect information of a target detection object according to the initial detection result of each piece of AOI equipment; generating a backtracking detection parameter in combination with the detection parameter of each AOI device and the initial defect information; performing backtracking detection based on the backtracking detection parameter to obtain a backtracking detection result; and synthesizing the initial detection result and the backtracking detection result to obtain a detection result. The method has the effects of reducing the misjudgment probability when a plurality of AOI devices are used for joint detection and improving the detection precision.

Description

Technical Field

[0001] The present invention relates to the technical field of AOI equipment, and in particular to a method, device, equipment and storage medium for joint detection of multiple AOI equipment. Background Art

[0002] AOI (Automatic Optical Inspection) is a technology that uses optical principles to inspect electronic products such as PCB boards and semiconductor devices. AOI equipment is usually composed of light sources, optical systems, image processing systems, mechanical systems, etc., and can quickly and accurately detect various defects in electronic products.

[0003] At present, AOI equipment has been widely used in the field of electronic manufacturing, especially in the production of electronic products with high precision and high reliability requirements. The application of AOI technology can greatly improve the quality and reliability of products and reduce production costs and human error rates.

[0004] With the rapid development of the electronics manufacturing industry, AOI technology has become a key link in ensuring product quality. However, existing AOI equipment often has viewing angle limitations during the inspection process, causing certain areas to become "blind spots" for inspection, thus affecting the accuracy and comprehensiveness of the inspection results. To solve the viewing angle limitation problem, a common practice is to increase the number of AOI devices or perform multiple inspections from different angles, but this method is inefficient. In addition, due to the increase in the number of AOI devices, the inspection results of multiple AOI devices are independent, and the inspection results of multiple AOI devices need to be integrated. If the inspection results of multiple AOI devices cannot be well integrated, the accuracy of the inspection results will decrease and the probability of misjudgment will increase. Summary of the invention

[0005] In order to reduce the probability of misjudgment when using multiple AOI devices for joint detection and improve detection accuracy, the present application provides a multi-AOI device joint detection method, apparatus, device and storage medium.

[0006] In the first aspect, the above-mentioned invention objective of the present application is achieved through the following technical solutions: A multi-AOI equipment joint detection method, the multi-AOI equipment joint detection method comprising: After the initial inspection of each of the AOI devices is completed, obtaining the initial inspection result of each of the AOI devices; Extracting initial defect information of the target inspection object according to the initial inspection result of each of the AOI devices; Combining the detection parameters of each of the AOI devices and the initial defect information, generating a retrospective detection parameter; Performing a backtracking test based on the backtracking test parameters to obtain a backtracking test result; The initial detection result and the back-testing detection result are combined to obtain a detection result.

[0007] By adopting the above technical solution and combining multiple AOI devices for inspection, the inspection advantages and characteristics of each device can be fully utilized to cover a wider inspection range and angle. Different devices may use different light sources, cameras and algorithms to capture the characteristic information of the inspected object under different conditions. The initial inspection is combined with the retrospective inspection. After the initial inspection is completed, the initial defect information is extracted according to the initial inspection results of each device, and the retrospective inspection parameters are generated to identify defects that may be missed or misjudged. The defects are further confirmed and corrected through retrospective inspection, thereby improving the accuracy of the inspection. The entire inspection process is highly automated, from initial inspection to retrospective inspection, and then to the output of the final results, all rely on the control of computers and algorithms, reducing the need for manual intervention and improving the inspection efficiency and consistency. Through the retrospective inspection mechanism, targeted re-inspections can be carried out on suspected defects instead of comprehensive re-inspections of the entire inspected object. The inspection parameters of each AOI device (such as light angle, light intensity, camera angle, etc.) are usually adjustable. For inspected objects with complex structures and multiple defect types, the joint inspection of multiple AOI devices can provide a more comprehensive inspection perspective and more accurate inspection results.

[0008] In a preferred example, the present application may be further configured as follows: combining the detection parameters of each of the AOI devices and the initial defect information to generate a retrospective detection parameter includes: Based on the detection parameters of each of the AOI devices, generate symmetric detection parameters of each of the AOI devices; According to the symmetric detection parameters of each of the AOI devices, it is determined whether the initial defect information can be detected, and according to the determination result, a retrospective detection parameter is generated.

[0009] By adopting the above technical solution and generating symmetrical detection parameters for each AOI device, the detection effect under opposite or symmetrical conditions can be simulated or predicted, which is convenient for discovering those tiny defects or hidden problems that are difficult to detect under conventional detection conditions, thereby improving the accuracy and sensitivity of detection. By using symmetrical detection parameters, it is possible to ensure a comprehensive evaluation of the initial defect information from different angles and conditions, reduce missed detections due to detection blind spots or angle limitations, and improve the comprehensiveness of detection. According to the matching degree between the symmetrical detection parameters and the initial defect information, the subsequent retrospective detection parameters can also be dynamically adjusted. By continuously accumulating and analyzing the data of the symmetrical detection parameters and the retrospective detection results, the existing detection algorithm can be optimized and improved, and the algorithm's adaptability and robustness can be improved to make it more suitable for complex and changeable detection tasks.

[0010] In a preferred example, the present application may be further configured as follows: generating symmetrical detection parameters of each AOI device based on the detection parameters of each AOI device, including: Based on the detection parameters of each of the AOI devices, obtaining complementary detection features of each of the AOI devices; Determine whether the complementary detection features of each of the AOI devices can be symmetrically set, symmetrically replace the detection parameters of the AOI devices that can be symmetrically set, and retain the detection parameters of the AOI devices that cannot be symmetrically set; The detection parameters of the AOI device based on symmetric replacement and the detection parameters of the retained AOI device are comprehensively considered to determine whether the symmetry rate is greater than a preset symmetry rate threshold. When the symmetry rate is not greater than the preset symmetry rate threshold, the detection parameters of the retained AOI device are symmetric replaced based on a preset alternative replacement rule, and the symmetric detection parameters of each AOI device are obtained by combining the detection parameters of the AOI device that is symmetric replaced.

[0011] By adopting the above technical solution, the complementary detection features of each AOI device are obtained, which can ensure that when generating symmetrical detection parameters, the detection advantages between different devices can be fully utilized. The detection parameters of the AOI device that can be set symmetrically are symmetrically replaced, which can further expand the detection angle and range, reduce the detection blind area, and thus optimize the overall detection coverage; by calculating the symmetry rate and comparing it with the preset symmetry rate threshold, the detection strategy can be flexibly adjusted. When the symmetry rate does not meet the requirements, the alternative replacement rule can be automatically triggered to seek a better combination of symmetrical detection parameters. The alternative replacement rule provides a variety of possibilities for adjusting the detection parameters, so that it can respond more flexibly when facing complex detection tasks, and improve the adaptability and flexibility of the detection strategy. Therefore, by generating symmetrical detection parameters, it is no longer completely dependent on the detection performance of a specific AOI device. Even if the detection parameters of a device cannot be set completely symmetrically, they can be supplemented and replaced by the detection parameters of other devices, thereby enhancing the replaceability of the entire detection system. In the case of device failure or performance fluctuation, the setting of symmetrical detection parameters can ensure that the detection process is not affected by the state of a single device, and maintain the continuity and stability of detection.

[0012] In a preferred example, the present application may be further configured as follows: combining the detection parameters of each of the AOI devices and the initial defect information to generate a retrospective detection parameter includes: Determine the detection parameter range of each of the AOI devices, and generate an initial defect segmentation range according to the detection parameter range of each of the AOI devices and the initial defect information; Inputting the detection parameter range and the initial defect segmentation range into a preset defect segmentation model to generate initial defect segmentation information and segmentation detection parameters corresponding to each of the AOI devices; The initial defect segmentation information and segmentation detection parameters of each of the AOI devices are associated to obtain a retrospective detection parameter.

[0013] By adopting the above technical solution, judging the detection parameter range of each AOI device, and combining with the initial defect information, the specific position range of the initial defect in the detection space can be accurately determined, the defect can be quickly located, and a fine search area can be provided for subsequent detection. By using the preset defect segmentation model, the initial defect can be further refined and segmented to generate more detailed initial defect segmentation information, which can include the specific shape, size, position, etc. of the defect, providing a finer search area for subsequent precise detection. By generating the initial defect segmentation range, the invalid detection area in the detection process can be significantly reduced, so that the detection resources can be more concentratedly used for the search and confirmation of potential defects, thereby improving the detection efficiency and reducing the detection time. Cost; associate the initial defect segmentation information and segmentation detection parameters of each AOI device to obtain retrospective detection parameters for specific defects. These parameters are more targeted and accurate, and can more accurately reflect the characteristics and status of defects, thereby improving the accuracy of detection; during the detection process, if it is found that the initial defect segmentation range or segmentation detection parameters do not match the actual detection situation, these parameters can be fed back and adjusted in real time. By continuously accumulating and analyzing the detection data, the detection process and parameter settings can be continuously optimized. For example, the parameters of the defect segmentation model can be adjusted according to historical detection data to improve its segmentation accuracy and generalization ability; or according to the characteristics of the current detection task, the priority and weight of the retrospective detection parameters can be adjusted.

[0014] In a preferred example, the present application may be further configured as follows: performing backtracking detection based on the backtracking detection parameter to obtain the backtracking detection result includes: Performing a backtracking test based on the backtracking test parameters to obtain an initial backtracking test result; Combining the initial backtracking detection result and the initial detection result, generating suspected defect information, and generating backtracking recovery detection parameters based on the suspected defect information; Performing a backtracking recovery test based on the backtracking recovery test parameters to obtain a backtracking recovery test result; The backtracking recovery detection result and the initial backtracking detection result are combined to obtain a backtracking detection result.

[0015] By adopting the above technical solution, through the two-stage detection of initial backtracking detection and backtracking recovery detection, double verification of suspected defects is achieved, the accuracy and reliability of defect identification are significantly improved, and false alarms and missed alarms are reduced. On the basis of the initial backtracking detection results, suspected defect information is generated in combination with the initial detection results, and backtracking recovery detection parameters are further generated to perform more refined analysis and description of suspected defects, providing more accurate targets for subsequent detection; in addition, the generation of backtracking recovery detection parameters is based on suspected defect information, and detection resources can be more concentratedly used for in-depth detection and verification of suspected defects. Targeted detection helps to optimize the allocation of detection resources and improve detection efficiency. Through the combination of backtracking detection and backtracking recovery detection, repeated detection of known non-defective areas can be avoided, thereby reducing redundant detection and saving detection time and cost. For complex or difficult-to-identify defects, through the combination of backtracking detection and backtracking recovery detection, the detection range can be gradually narrowed, gradually approaching the real defects, and better responding to the detection challenges of complex defects.

[0016] In the second aspect, the above invention objective of the present application is achieved through the following technical solutions: A multi-AOI equipment joint detection device, the multi-AOI equipment joint detection device comprising: An initial detection module, used for obtaining an initial detection result of each AOI device after the initial detection of each AOI device is completed; An initial defect extraction module, used to extract initial defect information of the target inspection object according to the initial inspection result of each of the AOI devices; A backtracking parameter module, used to generate a backtracking detection parameter by combining the detection parameter of each of the AOI devices and the initial defect information; A backtracking detection module, used to perform backtracking detection based on the backtracking detection parameters to obtain a backtracking detection result; The detection result module is used to integrate the initial detection result and the backtracking detection result to obtain the detection result.

[0017] Optionally, the backtracking parameter module includes: A symmetry analysis submodule, used for generating symmetry detection parameters of each of the AOI devices based on the detection parameters of each of the AOI devices; The backtracking analysis submodule is used to determine whether the initial defect information can be detected according to the symmetric detection parameters of each of the AOI devices, and generate backtracking detection parameters according to the judgment result.

[0018] Optionally, the symmetry analysis submodule includes: A complementary analysis unit, configured to obtain complementary detection features of each of the AOI devices based on detection parameters of each of the AOI devices; A parameter replacement unit, used for judging whether the complementary detection features of each of the AOI devices can be symmetrically set, symmetrically replacing the detection parameters of the AOI devices that can be symmetrically set, and retaining the detection parameters of the AOI devices that cannot be symmetrically set; The symmetry rate analysis unit is used to comprehensively judge whether the symmetry rate is greater than a preset symmetry rate threshold by combining the detection parameters of the AOI device based on symmetric replacement and the detection parameters of the retained AOI device. When the symmetry rate is not greater than the preset symmetry rate threshold, the detection parameters of the retained AOI device are symmetrically replaced based on a preset alternative replacement rule, and the symmetric detection parameters of each of the AOI devices are obtained by combining the detection parameters of the symmetrically replaced AOI device.

[0019] In the third aspect, the above invention objective of the present application is achieved through the following technical solutions: A computer device comprises a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the above-mentioned multi-AOI device joint detection method when executing the computer program.

[0020] In a fourth aspect, the above-mentioned invention objective of the present application is achieved through the following technical solutions: A computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the multi-AOI device joint detection method are implemented.

[0021] In summary, the present application includes at least one of the following beneficial technical effects: 1. Combined inspection with multiple AOI devices can make full use of the inspection advantages and characteristics of each device, covering a wider inspection range and angle. Different devices may use different light sources, cameras and algorithms, which can capture the characteristic information of the inspected object under different conditions. The initial inspection is combined with the retrospective inspection. After the initial inspection is completed, the initial defect information is extracted according to the initial inspection results of each device, and the retrospective inspection parameters are generated to identify defects that may be missed or misjudged. The defects are further confirmed and corrected through retrospective inspection, thereby improving the accuracy of the inspection. The entire inspection process is highly automated, from initial inspection to retrospective inspection, and then to the output of the final results, all rely on the control of computers and algorithms, reducing the need for manual intervention and improving the inspection efficiency and consistency. Through the retrospective inspection mechanism, targeted re-inspections can be carried out on suspected defects instead of comprehensive re-inspection of the entire inspected object. The inspection parameters of each AOI device (such as light angle, light intensity, camera angle, etc.) are usually adjustable. For inspected objects with complex structures and multiple defect types, the joint inspection of multiple AOI devices can provide a more comprehensive inspection perspective and more accurate inspection results. 2. By generating symmetrical detection parameters for each AOI device, the detection effect under opposite or symmetrical conditions can be simulated or predicted, which is convenient for discovering those tiny defects or hidden problems that are difficult to detect under conventional detection conditions, thereby improving the accuracy and sensitivity of detection. The use of symmetrical detection parameters can ensure a comprehensive evaluation of the initial defect information from different angles and conditions, reduce missed detections caused by detection blind spots or angle limitations, and improve the comprehensiveness of detection; according to the matching degree between the symmetrical detection parameters and the initial defect information, the subsequent retrospective detection parameters can also be dynamically adjusted. By continuously accumulating and analyzing the data of symmetrical detection parameters and retrospective detection results, the existing detection algorithm can be optimized and improved, and the algorithm's adaptability and robustness can be improved, making it more suitable for complex and changeable detection tasks; 3. Obtaining the complementary detection features of each AOI device can ensure that when generating symmetrical detection parameters, the detection advantages between different devices can be fully utilized. Symmetrical replacement of the detection parameters of AOI devices that can be set symmetrically can further expand the detection angle and range, reduce the detection blind area, and thus optimize the overall detection coverage; by calculating the symmetry rate and comparing it with the preset symmetry rate threshold, the detection strategy can be flexibly adjusted. When the symmetry rate does not meet the requirements, the alternative replacement rule can be automatically triggered to seek a better combination of symmetrical detection parameters. The alternative replacement rule provides a variety of possibilities for adjusting the detection parameters, so that it can respond more flexibly when facing complex detection tasks, and improve the adaptability and flexibility of the detection strategy. Therefore, by generating symmetrical detection parameters, it is no longer completely dependent on the detection performance of a specific AOI device. Even if the detection parameters of a device cannot be set completely symmetrically, they can be supplemented and replaced by the detection parameters of other devices, thereby enhancing the replaceability of the entire detection system. In the case of equipment failure or performance fluctuations, the setting of symmetrical detection parameters can ensure that the detection process is not affected by the state of a single device, and maintain the continuity and stability of detection. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] Figure 1 This is a flowchart of a method for joint detection of multiple AOI devices in an embodiment of the present application; Figure 2 This is a first implementation flow chart of S30 of the multi-AOI equipment joint detection method in an embodiment of the present application; Figure 3 It is a flowchart for implementing S031 of the multi-AOI equipment joint detection method in an embodiment of the present application; Figure 4 This is a second implementation flow chart of S30 of the multi-AOI equipment joint detection method in an embodiment of the present application; Figure 5 is a flowchart for implementing S40 of the multi-AOI equipment joint detection method in an embodiment of the present application; Figure 6 This is a principle block diagram of a multi-AOI equipment joint detection device in an embodiment of the present application; Figure 7 It is a diagram of the internal structure of a computer device in an embodiment of the present application. DETAILED DESCRIPTION

[0023] The following is combined with Figure 1-7 This application is described in further detail.

[0024] In one embodiment, if Figure 1 As shown, the present application discloses a multi-AOI equipment joint detection method, which specifically includes the following steps: S10: After the initial inspection of each AOI device is completed, the initial inspection result of each AOI device is obtained.

[0025] In this embodiment, the multi-AOI device joint detection method is applied to a central control system, and the central control system is used to control a joint detection system composed of multiple AOI devices deployed at different positions or stages in a production process. The multiple AOI devices are distributed at different positions of the detection line or at different angles around the detection object to ensure that image data is obtained from multiple perspectives. Each AOI device has independent image acquisition, processing and analysis capabilities, and can identify and report detected defects. Different AOI devices may use different detection principles or technologies (such as white light, color light, infrared, ultraviolet, etc.), which can cover a wider range of defect types. A network connection can be established between multiple AOI devices to achieve real-time sharing and collaborative processing of detection data, and further improve detection efficiency and accuracy; the central control system is the core of the entire joint detection system, responsible for coordinating the work of each AOI device, the central control system receives the detection data from each AOI device, summarizes, analyzes and processes it, and finally generates a comprehensive detection report. The central control system also has functions such as remote monitoring, fault diagnosis and automatic parameter adjustment to improve detection efficiency and accuracy; For example, the basic working principle of the joint detection system can be: Each AOI device uses its built-in camera and lighting system to collect images of the target inspection object. The image data captured by the camera is transmitted to the respective image processing unit for preliminary processing. The image processing unit pre-processes the received image, such as denoising, contrast enhancement, etc., to improve the image quality. Subsequently, the image processing algorithm is used to extract features and compare templates on the image to identify defects that do not conform to the standard template. Each AOI device sends the detected defect data to the central control system, which summarizes, analyzes and processes the received data and generates a report containing all the inspection results. The report can list in detail the defect location, type, size and other information of each inspection object for subsequent processing reference. The central control system also has a remote monitoring function, which can view the working status and inspection results of each AOI device in real time. When a certain AOI device is found to be faulty or the inspection effect is poor, the central control system can be used to perform fault diagnosis and parameter adjustment to ensure the stable operation and efficient operation of the entire inspection system. An illustration of a joint detection system may be: On a circular or U-shaped assembly line, multiple AOI devices are installed in different positions, rotating or moving around the target inspection object (such as lead frame or circuit board). Each AOI device is equipped with a camera and lighting system, which can shoot the target inspection object from different angles and distances. The central control system is located in the center or one side of the assembly line, connected to each AOI device by wired or wireless means, and is responsible for receiving and processing inspection data.

[0026] Specifically, when the joint inspection system is running, the inspected object will pass through each AOI device in turn and be inspected for defects by each AOI device, that is, the image of the target object will be compared with the standard template to identify defects that do not conform to the standard template. Therefore, after the initial inspection of each AOI device is completed, that is, after the first inspection of the target object by each AOI device in the current generation process is completed, the initial inspection results of each AOI device on the target object are obtained.

[0027] S20: Extracting initial defect information of the target inspection object according to the initial inspection result of each AOI device.

[0028] Specifically, the initial inspection result of each AOI device will display the defects of the target inspection object exposed in the initial inspection. Therefore, according to the initial inspection result of each AOI device, the initial defect information of the target inspection object corresponding to each AOI device is extracted.

[0029] S30: Generate retrospective inspection parameters by combining the inspection parameters of each AOI device and the initial defect information.

[0030] Specifically, in a joint detection system, a common detection method is that each AOI device sequentially detects the target detection object and then completes a round of detection. For example, when multiple AOI devices in a joint detection system are sequentially arranged on an assembly line, a round of detection of the target detection object is completed after the target detection object has passed through the assembly line. However, due to reasons such as equipment accuracy, algorithm differences, equipment layout, detection angle or algorithm limitations, there may be certain misjudgments, which will cause the detection accuracy of the joint detection system to decrease, affecting the overall production process. Therefore, it is necessary to improve the detection accuracy of the target detection object; Based on this, according to the initial defect information corresponding to each AOI device, the positions of all initially detected defects on the target inspection object are determined, and then according to the detection parameters of each AOI device, the key detection area of ​​each AOI device is determined. Because there are multiple AOI devices in the joint detection system, each AOI device in the joint detection system has a focused detection area, that is, not every AOI device performs a full range of detection on the target inspection object, but each AOI device is responsible for detecting a part of the target inspection object. Therefore, combined with the positions of all initially detected defects on the target inspection object and the key detection area of ​​each AOI device, it is determined whether the positions of all initially detected defects can be detected during retrospective detection. When it is determined that all the positions of the initially detected defects can be detected, there is no need to adjust the parameters of each AOI device; when it is determined that all the positions of the initially detected defects cannot be detected, it means that some AOI devices can detect the initial defects during the retrospective inspection, while some AOI devices cannot detect the initial defects during the retrospective inspection. Therefore, according to the positions of the defects that cannot be retrospectively detected, combined with some AOI devices that cannot detect the initial defects during the retrospective inspection, the inspection parameters of these AOI devices that cannot detect the initial defects during the retrospective inspection are adjusted, so that these AOI devices can detect the corresponding defect positions, so that all the initially detected defects can be detected; Alternatively, when it is determined that it is not possible to detect the positions of all initially detected defects, the detection parameters of each AOI device are adjusted so that each AOI device can detect the corresponding defect position. At this time, the detection position corresponding to each AOI device may be different from the position detected during the initial detection.

[0031] In this embodiment, when the joint detection system performs retrospective detection, it can be performed in the reverse order of the initial detection, or in a specific order. For example, it is set to call only some AOI devices when performing detection in the reverse order of the initial detection, or call only some AOI devices to perform multiple rounds of detection with different detection parameters, etc. Therefore, in addition to the detection parameters of each AOI device, the retrospective detection parameters can also include the order when the joint detection system performs retrospective detection and the detection time point of each AOI device.

[0032] S40: Perform a backtracking test based on the backtracking test parameters to obtain a backtracking test result.

[0033] Specifically, after the backtracking detection parameters are obtained, the backtracking detection is performed based on the backtracking detection parameters to obtain the backtracking detection results.

[0034] S50: The initial test result and the back-test result are combined to obtain a test result.

[0035] Specifically, since the retrospective detection is performed on the defects detected initially, the retrospective detection results are also performed on the defects detected initially. The initial detection results and the retrospective detection results are combined to determine the same defects that appear in both the initial detection results and the retrospective detection results, and mark them as measurement defects accordingly. Defects that only appear in the initial detection results or defects that only appear in the retrospective detection results can be marked as test defects to obtain the detection results.

[0036] In one embodiment, if Figure 2 As shown, in step S30, the detection parameters of each AOI device and the initial defect information are combined to generate the retrospective detection parameters, including: S031: Based on the detection parameters of each AOI device, generate symmetric detection parameters of each AOI device.

[0037] Specifically, when performing initial detection, each AOI device targets a specific area on the target detection object, that is, the initial area. Therefore, according to the initial area on the target detection object targeted by the detection parameters of each AOI device during initial detection, the area on the target detection object that is symmetrical to the initial area corresponding to each AOI device, that is, the symmetrical area, can be determined, and then the detection parameters when each AOI device needs to detect the symmetrical area can be determined to obtain the symmetrical detection parameters. It should be noted that if the detection parameters of the AOI device cannot detect the symmetrical area by adjusting the detection parameters, it is not necessary to adjust them; Alternatively, based on the preset order of backtracking detection of the joint detection system, the detection area of ​​each AOI device is determined when the detection parameters of each current AOI device are not changed during the backtracking detection, and then it is determined whether the detection area of ​​each AOI device is symmetrical with the initial area when the detection parameters of each current AOI device are not changed, and then the detection parameters of the AOI device determined to be asymmetric are adjusted.

[0038] S032: judging whether the initial defect information can be detected according to the symmetric detection parameters of each AOI device, and generating a retrospective detection parameter according to the judgment result.

[0039] Specifically, according to the symmetric detection parameters of each AOI device, it is determined whether all the initial defect information can be detected when performing retrospective detection based on the symmetric detection parameters of each AOI device, and a judgment result is obtained. According to the judgment result, for the initial defect information that is determined to be undetectable, the symmetric detection parameters of one or more AOI devices are adjusted, that is, the symmetric detection parameters of each AOI device can be adjusted to the detection parameters during the initial detection, or can remain unchanged, or be set to empty. In this way, different combinations of detection parameters of all AOI devices are judged by simulation, and it is determined under which combination all the initial defect information can be detected during retrospective detection, so as to generate retrospective detection parameters that can detect all the initial defect information during retrospective detection.

[0040] In one embodiment, if Figure 3 As shown, in step S031, based on the detection parameters of each AOI device, symmetric detection parameters of each AOI device are generated, including: S0311: Based on the detection parameters of each AOI device, obtain complementary detection features of each AOI device.

[0041] Specifically, according to the detection parameters of each AOI device, the detection characteristics of each AOI device based on the current detection parameters of each AOI device are determined, that is, the detection area of ​​each AOI device for the target detection object and the detection parameter type of each AOI device. Because for different types of target detection objects, the multi-dimensional detection requirements for the target detection objects are also correspondingly different. For example, for the lead frame, it is necessary to check whether the surface of the lead frame is flat, whether there are scratches, dents, deformations, stains and other defects, and it is necessary to verify whether the size of the lead frame meets the design requirements, including length, width, height, and the diameter, position, spacing, etc. of the lead hole. The detection parameter type is also the detection requirement. Therefore, it is necessary to Generate the inspection parameters of each AOI device according to these inspection requirements, so that each AOI device corresponds to one or more types of inspection parameters. After determining the inspection parameters of each AOI device, analyze the inspection features of each AOI device according to the inspection parameters of each AOI device, such as the inspection area, inspection angle and inspection dimension (two-dimensional or three-dimensional) of each AOI device. The inspection features correspond to the inspection requirements. For other items such as PBC boards, more attention may be paid to the installation quality, welding quality and electrical performance of components. Therefore, for different target inspection objects or for the same target inspection object but different batches of target inspection objects, the inspection features of each AOI device may be different. In addition, complementary detection features refer to features that correspond to the current detection requirements of the target object but not to the current detection features. That is, in addition to the current detection features, each AOI device can obtain other detection features that correspond to the current detection requirements of the target object by changing the detection parameters.

[0042] S0312: Determine whether the complementary detection features of each AOI device can be symmetrically set, symmetrically replace the detection parameters of the AOI devices that can be symmetrically set, and retain the detection parameters of the AOI devices that cannot be symmetrically set.

[0043] Specifically, since the complementary detection features of an AOI device may include one or more, and the corresponding detection parameters are one or more sets, when setting the symmetrical detection parameters, it is necessary to meet the current detection requirements and the symmetrical conditions of the smallest adjustment of the detection parameters of each AOI device as a whole, so that the complementary detection feature corresponding to an AOI device is one and no excessive parameter adjustment is performed to ensure the stability of the system. Therefore, it is determined whether the complementary detection features of each AOI device can be set symmetrically, that is, when the symmetrical conditions are met, it is determined whether each AOI device can replace the detection features with complementary detection features by changing the parameters. For those that can replace the detection features with complementary detection features by changing the parameters, the parameters are changed and replaced. For those that cannot replace the detection features with complementary detection features by changing the parameters, the parameters are retained. At this time, the detection parameters of each AOI device can meet the symmetrical conditions, that is, the current detection requirements are met and the symmetrical conditions of the smallest adjustment of the detection parameters of each AOI device as a whole.

[0044] S0313: Comprehensively judging whether the symmetry rate is greater than the preset symmetry rate threshold by combining the detection parameters of the AOI device based on symmetric replacement and the detection parameters of the retained AOI device; when the symmetry rate is not greater than the preset symmetry rate threshold, symmetrically replacing the detection parameters of the retained AOI device based on the preset alternative replacement rule, and obtaining the symmetrical detection parameters of each AOI device by combining the detection parameters of the symmetrically replaced AOI device.

[0045] Specifically, the detection parameters of the AOI device based on symmetric replacement and the detection parameters of the retained AOI device are comprehensively considered to determine whether the symmetry rate is greater than the preset symmetry rate threshold, that is, to determine whether the amount of detection parameters for parameter change and replacement is greater than the preset symmetry rate threshold. When the symmetry rate is not greater than the preset symmetry rate threshold, that is, the amount of detection parameters for parameter change and replacement is small, it indicates that the current amount of detection parameters for parameter change and replacement is small and cannot meet the preset symmetry requirements. Therefore, based on the preset alternative replacement rules, the detection parameters of the retained AOI device are symmetrically replaced, that is, when the symmetry conditions are met, different complementary detection features that can replace the detection features with complementary detection features through parameter change are reselected from multiple complementary detection features of some AOI devices, and then parameter change and replacement are performed according to the reselected complementary detection features. Combined with the detection parameters of the AOI device that has been symmetrically replaced, the symmetrical detection parameters of each AOI device are obtained.

[0046] In one embodiment, if Figure 4 As shown, in step S30, the detection parameters of each AOI device and the initial defect information are combined to generate the retrospective detection parameters, including: S131: Determine the detection parameter range of each AOI device, and generate an initial defect segmentation range according to the detection parameter range of each AOI device and the initial defect information.

[0047] Specifically, the detection parameter range of each AOI device is determined, that is, the adjustable range of each detection parameter type of each AOI device, for example, the angle at which the light source irradiates the target detection object, the camera angle, and the light source intensity. In addition, the defects on the target detection object represented by the initial defect information usually have a certain area. Therefore, the defects on the target detection object represented by the initial defect information can be segmented, and the characteristics of multiple AOI devices for joint detection of multiple AOI devices can be used to perform more refined detection on the defects on the segmented target detection object; Based on this, according to the current detection parameters of each AOI device and the corresponding detection parameter range, it is determined that when the detection parameters of each AOI device are adjusted within the detection parameter range, the area size of the defect area on the target detection object corresponding to the initial defect information that can be detected can be obtained to obtain the initial defect segmentation range.

[0048] S132: Input the detection parameter range and the initial defect segmentation range into a preset defect segmentation model to generate initial defect segmentation information and segmentation detection parameters corresponding to each AOI device.

[0049] Specifically, the detection parameter range and the initial defect segmentation range are input into a preset defect segmentation model. Through the defect segmentation model, the most suitable area size of the initial defect area is found in the initial defect segmentation range of each AOI device, that is, through the defect segmentation model, the detection amount of the AOI device when each AOI device corresponds to the area size of different initial defect areas is judged, and the corresponding defect segmentation range of each AOI device when the detection amount of all AOI devices is the smallest is found. Because after the defects on the target detection object are segmented, one defect becomes multiple defects, and the number of inspections required at this time will increase. Therefore, in order to save inspection resources, the corresponding defect segmentation range of each AOI device when the detection amount of all AOI devices is the smallest is found through a defect segmentation model with an optimal solution algorithm, as the initial defect segmentation information corresponding to each AOI device, that is, the area detected by each AOI device during retrospective inspection, and then according to the area detected by each AOI device during retrospective inspection, a detection parameter suitable for detecting the area, that is, a segmentation detection parameter, is generated.

[0050] S133: Associating the initial defect segmentation information and segmentation detection parameters of each AOI device to obtain a retrospective detection parameter.

[0051] Specifically, the initial defect segmentation information corresponding to each AOI device is associated with the segmentation detection parameter to obtain the backtracking detection parameter corresponding to each AOI device.

[0052] In one embodiment, if Figure 5 As shown, in step S40, a backtracking detection is performed based on the backtracking detection parameters to obtain a backtracking detection result, including: S41: Perform backtracking detection based on the backtracking detection parameters to obtain an initial backtracking detection result.

[0053] Specifically, a backtracking detection is performed based on the backtracking detection parameters to obtain a detection result obtained by performing the detection using the backtracking detection parameters, that is, an initial backtracking detection result.

[0054] S42: generating suspected defect information by combining the initial backtracking detection result and the initial detection result, and generating backtracking recovery detection parameters based on the suspected defect information.

[0055] Specifically, based on the initial backtracking test results and the initial test results, defects that appear in both the initial backtracking test results and the initial test results can be considered as defects, while defects that only appear in the initial backtracking test results or only appear in the initial test results can be considered as suspected defect information; in addition, because when performing backtracking testing, the position of the target test object returns to the vicinity of the position of the AOI device that is ranked first in the joint detection system, that is, close to the feed port of the joint detection system, if it is necessary to complete the detection of the AOI device at this time, the target test object needs to be transmitted for a distance, and the target test object will pass through multiple subsequent AOI devices. Therefore, at this time, the target test object can be tested again during the transmission process of the target test object for the suspected defect information. Therefore, based on the suspected defect information, backtracking recovery detection parameters suitable for detecting defects corresponding to the suspected defect information are generated for multiple subsequent AOI devices.

[0056] S43: Perform a backtracking recovery test based on the backtracking recovery test parameters to obtain a backtracking recovery test result.

[0057] Specifically, a backtracking recovery detection is performed based on the backtracking recovery detection parameter to obtain a detection result obtained by performing the detection using the backtracking recovery detection parameter, that is, a backtracking recovery detection result.

[0058] S44: Combining the backtracking recovery detection result and the initial backtracking detection result to obtain the backtracking detection result.

[0059] Specifically, since the detection direction of the backtracking recovery detection result and the initial backtracking detection result is the same, that is, the movement direction of the target detection object is the same, therefore, combining the backtracking recovery detection result and the initial backtracking detection result, the defects that appear in both the backtracking recovery detection result and the initial backtracking detection result can be considered as defects, thereby obtaining the backtracking detection result.

[0060] It should be understood that the size of the serial numbers of the steps in the above embodiments does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0061] In one embodiment, a multi-AOI device joint detection device is provided, and the multi-AOI device joint detection device corresponds to the multi-AOI device joint detection method in the above embodiment. Figure 6 As shown, the multi-AOI equipment joint detection device includes an initial detection module, an initial defect extraction module, a backtracking parameter module, a backtracking detection module and a detection result module. The detailed description of each functional module is as follows: An initial inspection module, used to obtain the initial inspection result of each AOI device after the initial inspection of each AOI device is completed; The initial defect extraction module is used to extract the initial defect information of the target inspection object according to the initial inspection results of each AOI device; The backtracking parameter module is used to generate the backtracking detection parameters by combining the detection parameters of each AOI device and the initial defect information; A backtracking detection module, used to perform backtracking detection based on the backtracking detection parameters and obtain the backtracking detection result; The test result module is used to integrate the initial test results and the back-test results to obtain the test results.

[0062] Optionally, the traceback parameter module includes: A symmetry analysis submodule, for generating symmetry detection parameters of each AOI device based on the detection parameters of each AOI device; The backtracking analysis submodule is used to determine whether the initial defect information can be detected based on the symmetrical detection parameters of each AOI device, and generate backtracking detection parameters based on the judgment result.

[0063] Optionally, the symmetry analysis submodule includes: A complementary analysis unit, used for obtaining complementary detection features of each AOI device based on the detection parameters of each AOI device; A parameter replacement unit, used to determine whether the complementary detection features of each AOI device can be symmetrically set, symmetrically replace the detection parameters of the AOI devices that can be symmetrically set, and retain the detection parameters of the AOI devices that cannot be symmetrically set; The symmetry rate analysis unit is used to comprehensively judge whether the symmetry rate is greater than a preset symmetry rate threshold by combining the detection parameters of the AOI device based on symmetric replacement and the detection parameters of the retained AOI device. When the symmetry rate is not greater than the preset symmetry rate threshold, the detection parameters of the retained AOI device are symmetrically replaced based on a preset alternative replacement rule, and the symmetric detection parameters of each AOI device are obtained by combining the detection parameters of the symmetrically replaced AOI device.

[0064] Optionally, the traceback parameter module includes: The segmentation range submodule is used to determine the detection parameter range of each AOI device and generate the initial defect segmentation range according to the detection parameter range of each AOI device and the initial defect information; The segmentation determination submodule is used to input the detection parameter range and the initial defect segmentation range into a preset defect segmentation model to generate initial defect segmentation information and segmentation detection parameters corresponding to each AOI device; The association submodule is used to associate the initial defect segmentation information and segmentation detection parameters of each AOI device to obtain the backtracking detection parameters.

[0065] Optionally, the backtracking detection module includes: The initial backtracking result submodule is used to perform backtracking detection based on the backtracking detection parameters to obtain the initial backtracking detection result; The suspected defect submodule is used to synthesize the initial backtracking detection result and the initial detection result to generate suspected defect information, and generate backtracking recovery detection parameters based on the suspected defect information; The backtracking recovery detection submodule is used to perform backtracking recovery detection based on the backtracking recovery detection parameters to obtain the backtracking recovery detection result; The comprehensive backtracking submodule is used to combine the backtracking recovery detection result and the initial backtracking detection result to obtain the backtracking detection result.

[0066] For the specific definition of the multi-AOI device joint detection device, please refer to the definition of the multi-AOI device joint detection method above, which will not be repeated here. Each module in the above-mentioned multi-AOI device joint detection device can be implemented in whole or in part by software, hardware and their combination. The above-mentioned modules can be embedded in or independent of the processor in the computer device in the form of hardware, or can be stored in the memory of the computer device in the form of software, so that the processor can call and execute the operations corresponding to the above modules.

[0067] In one embodiment, a computer device is provided. The computer device may be a server, and its internal structure diagram may be as follows: Figure 7 As shown. The computer device includes a processor, a memory, a network interface and a database connected through a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store initial detection results, initial defect information, retrospective detection parameters, retrospective detection results and detection results, etc. The network interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, a multi-AOI device joint detection method is implemented.

[0068] In one embodiment, a computer device is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the following steps when executing the computer program: After the initial inspection of each AOI device is completed, the initial inspection result of each AOI device is obtained; Extract the initial defect information of the target inspection object based on the initial inspection results of each AOI device; Combine the inspection parameters of each AOI device with the initial defect information to generate retrospective inspection parameters; Perform backtracking detection based on the backtracking detection parameters to obtain the backtracking detection results; The test results are obtained by combining the initial test results and the retrospective test results.

[0069] In one embodiment, a computer readable storage medium is provided, on which a computer program is stored, and when the computer program is executed by a processor, the following steps are implemented: After the initial inspection of each AOI device is completed, the initial inspection result of each AOI device is obtained; Extract the initial defect information of the target inspection object based on the initial inspection results of each AOI device; Combine the inspection parameters of each AOI device with the initial defect information to generate retrospective inspection parameters; Perform backtracking detection based on the backtracking detection parameters to obtain the backtracking detection results; The test results are obtained by combining the initial test results and the retrospective test results.

[0070] Those of ordinary skill in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be implemented by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application may include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0071] Those skilled in the art can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional units and modules is used as an example. In actual applications, the above-mentioned functions can be distributed and completed by different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above.

[0072] The embodiments described above are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, a person skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features may be replaced by equivalents. Such modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application, and should all be included in the protection scope of the present application.

Claims

1. A multi-AOI equipment joint detection method, characterized in that: The multi-AOI equipment joint detection method comprises: After the initial inspection of each of the AOI devices is completed, obtaining the initial inspection result of each of the AOI devices; Extracting initial defect information of the target inspection object according to the initial inspection result of each of the AOI devices; Combining the detection parameters of each of the AOI devices and the initial defect information, generating a retrospective detection parameter; Performing a backtracking test based on the backtracking test parameters to obtain a backtracking test result; The initial detection result and the back-testing detection result are combined to obtain a detection result.

2. The multi-AOI equipment joint detection method according to claim 1, characterized in that: The step of combining the detection parameters of each of the AOI devices and the initial defect information to generate a retrospective detection parameter includes: Based on the detection parameters of each of the AOI devices, generate symmetric detection parameters of each of the AOI devices; According to the symmetric detection parameters of each of the AOI devices, it is determined whether the initial defect information can be detected, and according to the determination result, a retrospective detection parameter is generated.

3. The multi-AOI equipment joint detection method according to claim 2, characterized in that: The step of generating symmetrical detection parameters of each AOI device based on the detection parameters of each AOI device comprises: Based on the detection parameters of each of the AOI devices, obtaining complementary detection features of each of the AOI devices; Determine whether the complementary detection features of each of the AOI devices can be symmetrically set, symmetrically replace the detection parameters of the AOI devices that can be symmetrically set, and retain the detection parameters of the AOI devices that cannot be symmetrically set; The detection parameters of the AOI device based on symmetric replacement and the detection parameters of the retained AOI device are comprehensively considered to determine whether the symmetry rate is greater than a preset symmetry rate threshold. When the symmetry rate is not greater than the preset symmetry rate threshold, the detection parameters of the retained AOI device are symmetric replaced based on a preset alternative replacement rule, and the symmetric detection parameters of each AOI device are obtained by combining the detection parameters of the AOI device that is symmetric replaced.

4. The multi-AOI equipment joint detection method according to claim 1, characterized in that: The step of combining the detection parameters of each of the AOI devices and the initial defect information to generate a retrospective detection parameter includes: Determine the detection parameter range of each of the AOI devices, and generate an initial defect segmentation range according to the detection parameter range of each of the AOI devices and the initial defect information; Inputting the detection parameter range and the initial defect segmentation range into a preset defect segmentation model to generate initial defect segmentation information and segmentation detection parameters corresponding to each of the AOI devices; The initial defect segmentation information and segmentation detection parameters of each of the AOI devices are associated to obtain a retrospective detection parameter.

5. The multi-AOI equipment joint detection method according to claim 1, characterized in that: The performing backtracking detection based on the backtracking detection parameter to obtain the backtracking detection result includes: Performing a backtracking test based on the backtracking test parameters to obtain an initial backtracking test result; Combining the initial backtracking detection result and the initial detection result, generating suspected defect information, and generating backtracking recovery detection parameters based on the suspected defect information; Performing a backtracking recovery test based on the backtracking recovery test parameters to obtain a backtracking recovery test result; The backtracking recovery detection result and the initial backtracking detection result are combined to obtain a backtracking detection result.

6. A multi-AOI equipment joint detection device, characterized in that: The multi-AOI equipment joint detection device comprises: An initial detection module, used for obtaining an initial detection result of each AOI device after the initial detection of each AOI device is completed; An initial defect extraction module, used to extract initial defect information of the target inspection object according to the initial inspection result of each of the AOI devices; A backtracking parameter module, used to generate a backtracking detection parameter by combining the detection parameter of each of the AOI devices and the initial defect information; A backtracking detection module, used to perform backtracking detection based on the backtracking detection parameters to obtain a backtracking detection result; The detection result module is used to integrate the initial detection result and the backtracking detection result to obtain the detection result.

7. The multi-AOI equipment joint detection device according to claim 6, characterized in that: The backtracking parameter module includes: A symmetry analysis submodule, used for generating symmetry detection parameters of each of the AOI devices based on the detection parameters of each of the AOI devices; The backtracking analysis submodule is used to determine whether the initial defect information can be detected according to the symmetric detection parameters of each of the AOI devices, and generate backtracking detection parameters according to the judgment result.

8. The multi-AOI equipment joint detection device according to claim 7, characterized in that: The symmetry analysis submodule includes: A complementary analysis unit, configured to obtain complementary detection features of each of the AOI devices based on detection parameters of each of the AOI devices; A parameter replacement unit, used for judging whether the complementary detection features of each of the AOI devices can be symmetrically set, symmetrically replacing the detection parameters of the AOI devices that can be symmetrically set, and retaining the detection parameters of the AOI devices that cannot be symmetrically set; The symmetry rate analysis unit is used to comprehensively judge whether the symmetry rate is greater than a preset symmetry rate threshold by combining the detection parameters of the AOI device based on symmetric replacement and the detection parameters of the retained AOI device. When the symmetry rate is not greater than the preset symmetry rate threshold, the detection parameters of the retained AOI device are symmetrically replaced based on a preset alternative replacement rule, and the symmetric detection parameters of each of the AOI devices are obtained by combining the detection parameters of the symmetrically replaced AOI device.

9. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the steps of the multi-AOI equipment joint detection method according to any one of claims 1 to 5 are implemented.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the steps of the multi-AOI equipment joint inspection method according to any one of claims 1 to 5 are implemented.

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