A method for detecting the welding quality of a connector

Abstract

The present invention discloses a method for detecting the welding quality of a connector, which relates to the technical field of quality detection. The method includes: using a 3D scanner to collect the connector to be inspected to obtain point cloud information and extract depth features to obtain solder joint features, training a deep learning model embedded with template matching technology based on this to identify defects, constructing a database containing defect type, morphology, and size information based on historical instances, respectively setting three sub-loops for welding quality detection associated with preset quality standards based on this, and connecting the three sub-loops to perform welding quality detection. It solves the technical problems in the prior art that the detection of the welding quality of the connector is not comprehensive and accurate enough, resulting in inaccurate and unreliable detection results, affecting the product quality and reliability, and achieves the technical effects of reducing the defective rate and use risk, and improving the quality and reliability of the connector product.

Description

Technical Field

[0001] This application relates to the technical field of quality inspection, and particularly to a method for inspecting the welding quality of connectors. Background Art

[0002] In the scenario of inspecting the welding quality of connectors, the issues of ensuring the reliability and stability of the welding quality of connectors are particularly prominent. The contradiction in the demand for high-quality inspection technology is relatively more prominent. Since the welding quality of connectors is directly related to the stability and reliability of equipment, developing an efficient and accurate inspection method to better meet the precise identification of various welding defects has become a crucial link in solving the inspection of the welding quality of connectors. Traditional methods for inspecting the welding quality of connectors are often relatively simple and localized, relying only on manual visual inspection or simple measuring tools, lacking a comprehensive grasp of the characteristics of solder joints, and lacking in-depth analysis and utilization of the complex structure and potential defects of solder joints. It is difficult to comprehensively and accurately detect various welding defects. In terms of the inspection effect, there are inaccurate situations, resulting in the omission of some subtle and critical defects, while some non-critical problems are over-concerned. The formulation of inspection standards is relatively vague and inconsistent, and it cannot well meet the increasing quality requirements of connectors.

[0003] In the current related technologies, there are technical problems such as incomplete and inaccurate inspection of the welding quality of connectors, resulting in inaccurate and unreliable inspection results, affecting product quality and reliability. Summary of the Invention

[0004] This application provides a method for inspecting the welding quality of connectors. By using a 3D scanner to collect the connector to be inspected to obtain point cloud information and extract depth features to obtain solder joint features, a deep learning model embedded with template matching technology is trained to identify defects based on this. A database containing information on defect types, shapes, and sizes is constructed based on historical instances. Based on this, three sub-loops for inspecting the welding quality associated with preset quality standards are respectively set up, and the three sub-loops are connected to perform the inspection of the welding quality, achieving precise and efficient inspection and evaluation of the welding quality of connectors, comprehensively considering various information such as defect types, shapes, and sizes, and achieving the technical effects of reducing the defective rate and usage risk, and improving the quality and reliability of connector products.

[0005] This application provides a method for inspecting the welding quality of connectors, including:

[0006] Using a 3D scanner, collect the connector to be inspected to obtain point cloud information, and perform depth feature extraction to obtain solder joint feature information; based on the solder joint feature information, train a deep learning model for defect classification and recognition. The deep learning model embeds a template matching technique, and the template matching technique is used to quickly identify known defect patterns; according to historical welding quality examples, statistically analyze the distribution law and bind it to the known defect patterns to construct a defect database. The defect database contains type information, morphological information, and size information of various welding defects; based on the type information of various welding defects in the defect database, set a first welding quality detection sub-loop, where the termination condition corresponding to the first welding quality detection sub-loop is associated with a first preset quality standard. The first preset quality standard is determined by taking industry standard specifications and connector product design requirements as constraints, including types of welding defects that are not allowed to appear; based on the morphological information of various welding defects in the defect database, set a second welding quality detection sub-loop. The termination condition corresponding to the second welding quality detection sub-loop is associated with a second preset quality standard. The second preset quality standard is determined by taking industry standard specifications and welding process conditions as constraints. Based on the size information of various welding defects in the defect database, set a third welding quality detection sub-loop. The termination condition corresponding to the third welding quality detection sub-loop is associated with a third preset quality standard. The third preset quality standard is determined by taking industry standard specifications and welding material characteristics as constraints; connect the first welding quality detection sub-loop, the second welding quality detection sub-loop, and the third welding quality detection sub-loop to perform welding quality detection on the connector to be inspected.

[0007] It is intended to propose a welding quality detection method for a connector through this application. First, use a 3D scanner to collect the connector to be inspected to obtain point cloud information and extract depth features to obtain solder joint features. Based on this, train a deep learning model embedded with a template matching technique to identify defects. Construct a database containing defect type, morphology, and size information based on historical examples. Based on this, set three welding quality detection sub-loops associated with preset quality standards respectively, and connect the three sub-loops to perform welding quality detection, achieving the technical effects of accurately and efficiently detecting and evaluating the welding quality of the connector, comprehensively considering various information such as defect type, morphology, and size, reducing the defective rate and usage risk, and improving the quality and reliability of the connector product. Description of the Drawings

[0008] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings of the embodiments of the present invention will be briefly introduced below. Flowcharts are used in this application to illustrate the operations performed by the systems according to the embodiments of the present application. It should be understood that the operations described above or below do not necessarily need to be performed precisely in order. On the contrary, various steps can be performed in reverse order or simultaneously as needed. At the same time, other operations can also be added to these processes, or one or more steps can be removed from these processes.

[0009] Figure 1 It is a schematic flowchart of a method for detecting the welding quality of a connector provided by an embodiment of the present application;

[0010] Figure 2 It is a schematic flowchart of determining the best scanning perspective of a method for detecting the welding quality of a connector provided by an embodiment of the present application. Detailed implementation manners

[0011] The above description is only an overview of the technical solutions of the present application. In order to be able to understand the technical means of the present application more clearly, it can be implemented according to the content of the specification. And in order to make the above and other purposes, features and advantages of the present application more obvious and understandable, the following specifically gives the detailed implementation manners of the present application.

[0012] In order to make the purpose, technical solutions and advantages of the present application clearer, the present application will be further described in detail below with reference to the accompanying drawings. The described embodiments should not be regarded as limitations of the present application. All other embodiments obtained by those of ordinary skill in the art without creative efforts fall within the scope of protection of the present application.

[0013] In the following description, reference is made to "some embodiments", which describe subsets of all possible embodiments. However, it can be understood that "some embodiments" can be the same subset or different subsets of all possible embodiments, and can be combined with each other without conflict. The terms "first\second" involved are only used to distinguish similar objects and do not represent a specific order for the objects. The terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, product or server that includes a series of steps or units does not necessarily have to be limited to those steps or units clearly listed, but may include other steps or modules that are not clearly listed or are inherent to these processes, methods, products or devices. Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the technical field to which this application belongs. The terms used herein are only for the purpose of describing the embodiments of the present application.

[0014] An embodiment of the present application provides a method for detecting the welding quality of a connector, as Figure 1 shown, the method includes:

[0015] Step S100: Use a 3D scanner to collect the connector to be inspected, obtain point cloud information, and perform depth feature extraction to obtain solder joint feature information. Specifically, in the inspection of the welding quality of the connector, start a high-precision 3D scanner, place the connector to be inspected within the working area of the scanner, ensure its position is accurate and stable. The 3D scanner emits a dense light or laser beam towards the connector to be inspected. The light or laser beam interacts with the surface of the connector and is reflected from various angles. The sensor of the scanner receives these reflected light or laser beams and converts them into a large number of data points. The set of data points constitutes the point cloud information. The point cloud information contains detailed information such as the three-dimensional geometric shape and position of the connector surface. Perform depth feature extraction on the obtained point cloud information. Use the Gaussian filtering algorithm to remove noise. The Gaussian filtering effectively smooths the data and reduces the influence of random noise by performing weighted averaging on the point cloud data within the neighborhood. Use the bilateral filtering technique to keep important features such as the solder joint edges clear while removing noise. The bilateral filtering not only considers the spatial distance but also the difference in pixel values, thus better retaining details while smoothing the noise. Use the principal component analysis technique to reduce the data dimension and extract the main features. By calculating the covariance matrix of the data, find the main direction of the data, project the high-dimensional data into a low-dimensional space while retaining most of the information. Through data processing and analysis operations, effectively remove possible noise and interference factors. After removing the noise, further extract the feature information directly related to the solder joint. The feature information includes key parameters such as the position, shape, size, and height of the solder joint, as well as related features such as the surface roughness and flatness around the solder joint. After depth feature extraction, finally obtain the feature information that can accurately reflect the characteristics of the solder joint, providing an important data basis for subsequent welding quality assessment and defect detection.

[0016] In a possible implementation, a 3D scanner is used to collect the connector to be inspected, obtain point cloud information, and perform depth feature extraction to obtain solder joint feature information. Step S100 further includes step S110 of configuring the 3D scanner parameters, which are the resolution and scanning speed of the 3D scanner. Specifically, the key parameters of the 3D scanner are configured. The resolution determines the detail accuracy that the scanner can capture when scanning the connector to be inspected. If the resolution is set relatively high, the obtained point cloud information will be very fine, and it can clearly present the tiny features on the surface of the connector. However, a high resolution also means a significant increase in the amount of data generated, and the time and computing resources required for subsequent data processing and analysis will also increase accordingly. The scanning speed is a key parameter. A faster scanning speed can significantly improve the detection efficiency and complete the scanning of the connector in a short time. However, if the scanning speed is too fast, the scanner may not capture information accurately and comprehensively, thus affecting the final detection quality. It is necessary to weigh the pros and cons and reasonably set the resolution and scanning speed according to the specific characteristics of the connector to be inspected, the requirements for detection accuracy, and the actual work efficiency requirements.

[0017] Step S120, based on the 3D scanner parameters, perform a comprehensive coverage scan of the solder joints of the connector to be inspected. The coverage positions corresponding to the point cloud information include M solder joints and M perimeter regions. The perimeter region refers to the surrounding area that closely surrounds each solder joint and has slight welding differences. Specifically, according to the previously set 3D scanner parameters, the connector to be inspected is scanned. The goal of the scan is to achieve comprehensive coverage of the solder joints to ensure that no solder joint is missed. During the scan, the coverage positions corresponding to the obtained point cloud information clearly cover M solder joints, including M perimeter regions closely connected to each solder joint. Although the perimeter region is not large, due to the slight welding differences, it is crucial for accurately evaluating the welding quality. By comprehensively scanning the M solder joints and M perimeter regions, rich and comprehensive information can be collected, providing sufficient data support for subsequent quality analysis.

[0018] Step S130: Combine the M solder joints and the M perimeter regions for synchronous adjustment during the scanning process of the 3D scanner. Specifically, during the scanning process, consider the M solder joints and the M perimeter regions as a whole for analysis. According to the actual situation during the scanning process, perform synchronous adjustment on the 3D scanner. The adjustment mainly focuses on two aspects: scanning angle and distance. In terms of the scanning angle, based on the distribution and shape characteristics of the solder joints and the perimeter regions, the angle of the scanner is changed in real time to ensure that the light or laser beam can irradiate the target area at the best angle, thereby obtaining more accurate and complete point cloud information. In terms of the scanning distance, according to the size and shape of the connector to be inspected, as well as the positions of the solder joints and the perimeter regions, dynamically adjust the distance between the scanner and the connector. If the distance is too far, it may lead to incomplete information collection or reduced accuracy; if the distance is too close, it may cause scanning dead angles or unnecessary interference to the connector. Through precise synchronous adjustment of the scanning angle and distance, the quality and efficiency of scanning can be maximally improved, ensuring high-quality point cloud information is obtained, laying a solid foundation for subsequent welding quality inspection and analysis.

[0019] In a possible implementation manner, combine the M solder joints and the M perimeter regions for synchronous adjustment during the scanning process of the 3D scanner. Step S130 further includes step S131: Add P position states according to the shape structure of the connector to be inspected. The P position states correspond to the relative positions of the connector to be inspected and the 3D scanner. Specifically, analyze the shape structure of the connector to be inspected. Since the shapes of connectors are different and there are complex geometric shapes and structural features, in order to comprehensively and accurately obtain its point cloud data, set P different position states according to the specific shape and structure of the connector. Each position state clearly corresponds to a specific relative position relationship between the connector to be inspected and the 3D scanner. For example, if the connector is a curved tubular structure, multiple position states may be set, including horizontal placement, vertical placement, and inclined placements at different angles, etc.

[0020] Step S132: Based on the P position states, issue a position adjustment instruction for the occluded area. Specifically, after determining the P position states, perform a preliminary scan of the connector by the 3D scanner. During the scanning process, compare the actually scanned information with the preset position states, and pay special attention to those areas that may be occluded due to improper position. Once an occluded area is found, the system will intelligently issue a corresponding position adjustment instruction according to the current position state and the situation of the occluded area. For example, if it is found that a certain part is occluded by other parts of the connector due to improper position of the connector, the system will issue an adjustment instruction to change the position of the connector.

[0021] Step S133: After the connector under test receives the position adjustment instruction, synchronously execute the rotation action, tilt action, and translation action corresponding to the position adjustment instruction. Specifically, when the connector under test receives the position adjustment instruction issued by the system, it will immediately respond. The connector will synchronously execute the corresponding actions according to the requirements of the instruction. The actions include the rotation action, that is, rotating around a certain axis to change the angle; the tilt action, which causes the connector to tilt in a plane; and the translation action, moving linearly along a specific direction. Through precise action adjustment, it is ensured that the 3D scanner can obtain complete and accurate point cloud data for complex structural parts, thereby providing a reliable basis for subsequent quality inspection and analysis. Especially for parts with complex structures, only through such precise position adjustment can data loss be avoided and the accuracy and comprehensiveness of the detection results be guaranteed.

[0022] In a possible implementation manner, according to the shape and structure of the connector under test, P position states are added. The P position states correspond to the relative positions of the connector under test and the 3D scanner. Step S131 further includes step S1311: In the first position state, q scanning perspectives are added. The first position state is any one of the P position states. Specifically, select any one of the P position states as the first position state. On the basis of the first position state, q different scanning perspectives are added. The setting of the scanning perspectives is to scan the connector under test from multiple angles to obtain more comprehensive and accurate information. For example, if the first position state is to place the connector horizontally, then the q scanning perspectives added may include vertically downward from above, horizontally from left to right, horizontally from right to left, and other different directions.

[0023] Step S1312: Based on the q scanning perspectives, arrange them in descending order according to the number of solder joints in each scanning perspective to obtain the first scanning perspective sequence. Specifically, after determining the q scanning perspectives, calculate the number of solder joints that each scanning perspective can cover respectively, and sort the q scanning perspectives in descending order of the number of solder joints. The purpose is to preferentially select the scanning perspectives that can capture more solder joints because the number of solder joints reflects to a certain extent the ability of this perspective to obtain key information. For example, if a scanning perspective can cover 20 solder joints while another can only cover 10, then the former will be ranked higher in the sorting.

[0024] Step S1313: Based on the q scanning perspectives, arrange them in descending order of the coverage ratio of the perimeter area in each scanning perspective to obtain a second scanning perspective sequence. Specifically, based on the q scanning perspectives, calculate the coverage ratio of each perspective to the perimeter area. The perimeter area is also very important for evaluating the welding quality. The larger the coverage ratio, the more complete the perimeter area information obtained. Reorder the q scanning perspectives in descending order of the perimeter area coverage ratio to obtain a second scanning perspective sequence.

[0025] Step S1314: Determine q' best scanning perspectives in the first position state according to the first scanning perspective sequence and the second scanning perspective sequence. Specifically, comprehensively consider the first scanning perspective sequence (sorted based on the number of solder joints) and the second scanning perspective sequence (sorted based on the perimeter area coverage ratio). Through the analysis and comparison of the two sequences, screen out q' scanning perspectives that perform well in both solder joint coverage and perimeter area coverage, and determine them as the best scanning perspectives in the first position state. The best scanning perspectives can provide the most valuable information for subsequent welding quality detection, ensuring the accuracy and reliability of the detection.

[0026] In a possible implementation, as Figure 2 shown, to determine q' best scanning perspectives in the first position state according to the first scanning perspective sequence and the second scanning perspective sequence, step S1314 further includes step S13141: Compare the first scanning perspective sequence and the second scanning perspective sequence, and screen out N alternative scanning perspectives whose serial numbers in the first scanning perspective sequence and the second scanning perspective sequence are the same. Specifically, compare and analyze the previously obtained first scanning perspective sequence (sorted based on the number of solder joints) and the second scanning perspective sequence (sorted based on the perimeter area coverage ratio). Check the serial numbers of each scanning perspective in the two sequences one by one. If the serial numbers of a certain scanning perspective are the same in these two sequences, it means that its performance in both solder joint coverage and perimeter area coverage is relatively stable and excellent, and the scanning perspective is screened out. A total of N alternative scanning perspectives are obtained.

[0027] Step S13142: Receive a first verification signal, verify the integrity of the solder joint coverage for the N alternative scanning perspectives, and if it passes, send a second verification signal. Specifically, after the system receives the first verification signal, it starts to verify the integrity of the solder joint coverage for these N alternative scanning perspectives. Through calculation and analysis, check whether these perspectives can completely cover all the solder joints. If the verification passes, it indicates that these alternative scanning perspectives meet the requirements in terms of solder joint coverage. At this time, the system will send a second verification signal.

[0028] Step S13143: Use the second verification signal to verify the coverage integrity of the perimeter area for the N alternative scanning perspectives. If the verification is passed, determine q' best scanning perspectives in the first position state. Specifically, after receiving the second verification signal, verify the coverage integrity of the perimeter area for these N alternative scanning perspectives. Through calculation and analysis, determine whether the perspectives can completely cover the perimeter area. If the verification is passed, it means that the alternative scanning perspectives perform well in both solder joint coverage and perimeter area coverage. Then, q' best scanning perspectives in the first position state can be determined from these N alternative scanning perspectives for subsequent detection work to ensure the accuracy and comprehensiveness of the detection results.

[0029] In a possible implementation, receive the first verification signal and verify the solder joint coverage integrity for the N alternative scanning perspectives. If the verification is passed, send the second verification signal. Step S13142 further includes step S131421. If the verification is not passed, based on the N alternative scanning perspectives, determine the solder joints that are not covered. Specifically, if the verification of the solder joint coverage integrity for the N alternative scanning perspectives fails, it means that there are some solder joints not covered by these perspectives. Based on the N alternative scanning perspectives, through detailed comparison and analysis, accurately identify the solder joints that are not covered.

[0030] Step S131422: Denote the multiple scanning perspectives in the first scanning perspective sequence except the N alternative scanning perspectives as the remaining scanning perspectives, and arrange them in descending order according to the number of solder joints of the uncovered solder joints in the remaining scanning perspectives to obtain the first re-arranged scanning perspective sequence. Specifically, define the multiple scanning perspectives other than the N alternative scanning perspectives in the original first scanning perspective sequence as the remaining scanning perspectives, calculate the number of occurrences of the uncovered solder joints in the remaining scanning perspectives, and re-arrange the remaining scanning perspectives in descending order of the number to obtain the first re-arranged scanning perspective sequence.

[0031] Step S131423: Based on the first re-arranged scanning perspective sequence, conduct supplementary verification on the N alternative scanning perspectives until the solder joint coverage integrity verification is passed. Specifically, according to the obtained first re-arranged scanning perspective sequence, conduct supplementary verification on the N alternative scanning perspectives that failed the previous verification. Repeat this supplementary verification process and continuously check the solder joint coverage integrity until the solder joint coverage integrity verification is finally passed. Through repeated supplementation and verification, ensure that sufficient comprehensive and accurate scanning perspectives can be found to provide a reliable basis for subsequent detection work.

[0032] In a possible implementation, based on the reordered sequence of the first scanning perspective, supplementary verification is performed on N alternative scanning perspectives until the solder joint coverage integrity verification is passed. Step S131423 further includes step S1314231, which determines U critical solder joints and V normal solder joints among the M solder joints according to the shape structure of the connector to be inspected. Specifically, by analyzing the shape structure characteristics of the connector to be inspected, based on the characteristics as well as the importance and function of the connector in actual applications, U critical solder joints and V normal solder joints are distinguished from a total of M solder joints. Critical solder joints are usually parts that have a greater impact on the performance and safety of the connector, while normal solder joints are relatively less important.

[0033] Step S1314232, set a solder joint coverage integrity verification strategy with reference to the U critical solder joints. The solder joint coverage integrity verification strategy includes the minimum scanning times threshold for the U critical solder joints. Specifically, for the determined U critical solder joints, a special solder joint coverage integrity verification strategy is set. The strategy clearly stipulates the minimum scanning times threshold for each critical solder joint. The threshold is comprehensively determined based on factors such as the importance of the solder joint, welding process requirements, and quality standards.

[0034] Step S1314233, when performing supplementary verification, generate a list of critical solder joints through the solder joint coverage integrity verification strategy and count the scanning times of each critical solder joint. Specifically, when performing the supplementary verification operation, according to the previously set solder joint coverage integrity verification strategy, generate a list containing all critical solder joints. During the verification process, accurately count the number of scans that have been completed for each critical solder joint in order to compare with the set minimum scanning times threshold.

[0035] Step S1314234, if the scanning times of a critical solder joint do not reach the corresponding minimum scanning times threshold, continue to perform supplementary scanning from the reordered sequence of the first scanning perspective. The scanning perspectives in the reordered sequence of the first scanning perspective are allowed to be supplemented and scanned only once. Specifically, if it is found that the scanning times of a certain critical solder joint do not reach the pre-set minimum scanning times threshold, then supplementary scanning needs to be continued. Select a suitable scanning perspective from the reordered sequence of the first scanning perspective for supplementation. However, it should be noted that each scanning perspective can only be allowed to be supplemented and scanned once during this process to ensure the efficiency and rationality of scanning, and at the same time avoid resource waste caused by excessive scanning.

[0036] In a possible implementation manner, according to the shape structure of the connector to be inspected, U key solder joints and V normal solder joints among the M solder joints are determined. Step S1314231 further includes step S13142311. If all the scanning perspectives in the first scanning perspective rearrangement sequence have been subjected to supplementary scanning once, in combination with the V normal solder joints, an auxiliary tool is used for supplementary scanning. The auxiliary tool includes a reflector. Specifically, if all the scanning perspectives in the first scanning perspective rearrangement sequence have been subjected to supplementary scanning once, when all the scanning perspectives in the first scanning perspective rearrangement sequence have completed a supplementary scanning operation, in combination with the V normal solder joints, an auxiliary tool is used for supplementary scanning. The auxiliary tool includes a reflector. In order to further improve the scanning effect, especially for the possible insufficient scanning situation before, the V normal solder joints are also taken into consideration, and the auxiliary tool is used for supplementary scanning. The mentioned auxiliary tool includes a reflector, which changes the propagation path of light, so that information about the solder joints can be obtained from more angles, making up for the possible scanning blind spots or incomplete parts, and improving the comprehensiveness and accuracy of the entire scanning.

[0037] Step S200, based on the solder joint feature information, train a deep learning model for defect classification and recognition. The deep learning model embeds a template matching technique, and the template matching technique is used to quickly identify known defect patterns. Specifically, the obtained solder joint feature information is the basic data for subsequent training of the deep learning model. The feature information includes various attributes and feature descriptions of the solder joints. The solder joint feature information is used to train the deep learning model. During the training process, a large amount of labeled solder joint feature data is input into the model, enabling the model to learn how to judge whether there are defects in the solder joints and the types of defects based on these features. In this deep learning model, a template matching technique is embedded, and the template matching technique can quickly identify those known defect patterns. The known defect patterns are relatively broad and common major defect situations, such as common major patterns like poor soldering and abnormal solder joint shapes.

[0038] Step S300: Based on historical welding quality examples, statistically analyze the distribution patterns and bind them to the known defect patterns to construct a defect database. The defect database contains type information, morphological information, and size information of various welding defects. Specifically, analyze and study the historical examples, and use statistical methods to discover the distribution patterns therein. For example, statistically analyze the frequencies of welding defects under different types and process conditions, or the distribution characteristics of defects in welds of different materials and structures. Closely bind the discovered distribution patterns to the known defect patterns. The known defect patterns are relatively broad categories, and when constructing the defect database, it will be further subdivided into specific sub-category type information. For example, the welding defect types will be subdivided into sub-categories such as cracks, lack of fusion, and lack of penetration. In addition to type information, the database will also include morphological information, which describes the shape, orientation, edge characteristics, etc. of the defects; and size information, which records specific numerical data such as the length, width, and depth of the defects. By integrating and correlating the distribution patterns, known defect patterns (including the subdivided sub-category type information), morphological information, and size information, a comprehensive and detailed defect database is constructed. In subsequent welding quality inspection and evaluation, based on the database for comparison and analysis, more accurately judge whether there are defects in the currently detected solder joints, what kind of defects exist, and the severity of the defects, etc., providing strong support and reference for improving welding quality and optimizing the process.

[0039] Step S400: Set up the first welding quality inspection sub-loop based on the type information of various welding defects in the defect database. The termination condition corresponding to the first welding quality inspection sub-loop is associated with the first preset quality standard, which is determined by taking industry standard specifications and connector product design requirements as constraints and includes types of welding defects that are not allowed. Specifically, analyze the already constructed defect database, paying particular attention to the type information regarding various welding defects. The type information includes specific types of welding defects such as cracks, lack of fusion, incomplete penetration, etc. Based on the type information of welding defects, set up the first welding quality inspection sub-loop. The sub-loop is an important part of the entire welding quality inspection process. When setting up the first welding quality inspection sub-loop, clarify its corresponding termination condition, which is closely related to the first preset quality standard. The determination of the first preset quality standard is a rigorous process. Based on industry standard specifications and fully considering the specific design requirements of the connector product, under the constraints, it clearly stipulates the specific types of welding defects that are not allowed. For example, the industry standard specifications may stipulate that cracks are not allowed in certain key parts, while the connector product design requirements may further specify that lack of fusion is not allowed at specific positions. During the operation of the first welding quality inspection sub-loop, the welding quality will be continuously inspected and evaluated until the termination condition associated with the first preset quality standard is reached. Only when the standard and conditions are met will the sub-loop end, thus ensuring the accuracy and reliability of the inspection and guaranteeing that the welding quality meets the requirements of industry specifications and product design.

[0040] Step S500: Based on the morphological information of various welding defects in the defect database, set up a second welding quality inspection sub-loop. The termination condition corresponding to the second welding quality inspection sub-loop is associated with a second preset quality standard, which is determined by taking industry standard specifications and welding process conditions as constraints. Based on the size information of various welding defects in the defect database, set up a third welding quality inspection sub-loop. The termination condition corresponding to the third welding quality inspection sub-loop is associated with a third preset quality standard, which is determined by taking industry standard specifications and the characteristics of welding materials as constraints. Specifically, conduct in-depth research on the morphological information of various welding defects in the defect database. The morphological information may include detailed descriptions of aspects such as the shape of the defect (such as long strip-shaped, circular, irregular, etc.), the trend (straight line, curve, bend, etc.), and the edge characteristics (smooth, serrated, etc.). Based on the morphological information, set up a second welding quality inspection sub-loop. When setting up the second welding quality inspection sub-loop, clarify its corresponding termination condition, which is closely related to the second preset quality standard. The determination of the second preset quality standard comprehensively considers industry standard specifications and actual welding process conditions. Industry standard specifications will have certain allowable ranges and restrictive requirements for the morphology of welding defects, and welding process conditions (such as welding methods, welding parameters, etc.) will also affect the acceptance degree of defect morphology. Analyze the size information of various welding defects in the defect database, such as specific values of the length, width, depth, area, etc. of the defects. Based on the size information, set up a third welding quality inspection sub-loop. The termination condition of the third welding quality inspection sub-loop is associated with the third preset quality standard. The formulation of the third preset quality standard is based on industry standard specifications and fully considers the characteristics of welding materials. Different welding materials have different performances and abilities to tolerate defects. Therefore, the characteristics of welding materials will be taken into account when determining the preset quality standard. During the operation of the second and third welding quality inspection sub-loops, continuously detect and evaluate the morphology and size of welding defects until the termination conditions specified by their respective preset quality standards are met. Through meticulous and targeted settings, the welding quality can be comprehensively and accurately evaluated to ensure that the welded products meet the relevant requirements and standards.

[0041] Step S600: Connect the first welding quality inspection sub-loop, the second welding quality inspection sub-loop, and the third welding quality inspection sub-loop to perform welding quality inspection on the connector to be inspected. Specifically, clarify the respective functions and key points of the first welding quality inspection sub-loop, the second welding quality inspection sub-loop, and the third welding quality inspection sub-loop. The first welding quality inspection sub-loop mainly conducts inspections based on the type information of welding defects. The second welding quality inspection sub-loop focuses on the morphological information of welding defects. The third welding quality inspection sub-loop focuses on the size information of welding defects. When connecting these three sub-loops, carefully design the sequence and logical relationship between them. Define the termination condition of the first welding quality inspection sub-loop as the starting condition of the second welding quality inspection sub-loop, which means that only when the first sub-loop completes the inspection of the welding defect type and meets the corresponding standards, the second welding quality inspection sub-loop will be started. Set the termination condition of the second welding quality inspection sub-loop as the starting condition of the third welding quality inspection sub-loop. This connection method forms a coherent and orderly inspection process. When preparing to perform welding quality inspection on the connector to be inspected, first start the first welding quality inspection sub-loop. In the sub-loop, comprehensively and meticulously inspect and evaluate the type of welding defects of the connector according to the first preset quality standard. Once the first welding quality inspection sub-loop meets the termination condition, automatically trigger the second welding quality inspection sub-loop, and deeply analyze and judge the morphology of the welding defects according to the second preset quality standard. When the second welding quality inspection sub-loop reaches the termination condition, immediately start the third welding quality inspection sub-loop, and accurately measure and evaluate the size of the welding defects according to the third preset quality standard. By sequentially connecting and running the three sub-loops, it is possible to comprehensively and systematically perform comprehensive inspection on the welding quality of the connector to be inspected from multiple dimensions, ensuring the accuracy, integrity, and reliability of the inspection results, and providing sufficient basis for judging whether the welding quality of the connector is qualified.

[0042] In a possible implementation, connect the first welding quality detection sub-loop, the second welding quality detection sub-loop, and the third welding quality detection sub-loop to perform welding quality detection on the connector to be inspected. Step S600 further includes step S610, defining the termination condition corresponding to the first welding quality detection sub-loop as the starting condition corresponding to the second welding quality detection sub-loop, defining the termination condition corresponding to the second welding quality detection sub-loop as the starting condition corresponding to the third welding quality detection sub-loop, and connecting the first welding quality detection sub-loop, the second welding quality detection sub-loop, and the third welding quality detection sub-loop. Specifically, determine the termination condition of the first welding quality detection sub-loop. The termination condition is set based on the detection and evaluation of welding defect types. When a specific detection standard is reached or the predetermined detection steps and requirements are completed, it is determined that the first welding quality detection sub-loop ends. Defining the termination condition directly as the starting condition of the second welding quality detection sub-loop means that only when the first welding quality detection sub-loop is successfully completed and meets its termination condition, the second welding quality detection sub-loop will be triggered to start. Define the termination condition of the second welding quality detection sub-loop. The condition is set based on the detection and judgment of the welding defect morphology. When the second welding quality detection sub-loop completes the relevant detection and evaluation of the welding defect morphology and meets the set termination standard, it is declared that the second welding quality detection sub-loop ends. Set the termination condition of the second welding quality detection sub-loop as the starting condition of the third welding quality detection sub-loop. Only after the second welding quality detection sub-loop is successfully completed, the third welding quality detection sub-loop will start to run. By the above method, the first, second, and third welding quality detection sub-loops are connected in sequence. In actual operation, when the first welding quality detection sub-loop completes the detection of welding defect types according to the predetermined standards and requirements, its termination condition is met, and then the second welding quality detection sub-loop is triggered to start detecting the welding defect morphology. When the second welding quality detection sub-loop also completes the task and meets the termination condition, the third welding quality detection sub-loop is started to detect the size of the welding defect. The connection method forms a logically tight and orderly detection process, ensuring a comprehensive, in-depth, and gradually refined detection of welding quality, thereby improving the accuracy and reliability of the detection and being able to more comprehensively and accurately evaluate whether the welding quality meets the requirements.

[0043] In the embodiments of the present application, a 3D scanner is used to collect the connector to be inspected to obtain point cloud information and extract depth features to obtain solder joint features. Based on this, a deep learning model integrating template matching technology is trained to identify defects. A database containing defect type, morphology, and size information is constructed based on historical instances. Based on this, three welding quality inspection sub-loops associated with preset quality standards are respectively set, and the three sub-loops are connected to perform welding quality inspection, achieving the technical effects of accurately and efficiently detecting and evaluating the welding quality of the connector, comprehensively considering various information such as defect type, morphology, and size, reducing the defective rate and usage risk, and improving the quality and reliability of the connector product.

[0044] The above specific embodiments do not constitute a limitation to the protection scope of the present application. Those skilled in the art should understand that various modifications, combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principle of the present application shall be included within the protection scope of the present application. In some cases, the actions or steps recorded in the present application can be executed in a different order from that in the embodiments and still achieve the desired results. Additionally, the processes depicted in the drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In certain embodiments, multi-task processing and parallel processing are also possible or may be advantageous.

Claims

1. A method for detecting the welding quality of a connector, characterized in that: The method comprises: Use a 3D scanner to collect the connector to be inspected, obtain point cloud information, and perform deep feature extraction to obtain solder joint feature information; Based on the solder joint feature information, a deep learning model is trained to classify and identify defects, wherein the deep learning model is embedded with a template matching technology, and the template matching technology is used to quickly identify known defect patterns; According to historical welding quality examples, statistical distribution rules are obtained and bound with the known defect patterns to construct a defect database, which contains type information, morphology information, and size information of various welding defects; Based on the type information of various welding defects in the defect database, a first welding quality detection sub-cycle is set, wherein the termination condition corresponding to the first welding quality detection sub-cycle is associated with a first preset quality standard, and the first preset quality standard is determined by industry specifications and connector product design requirements as constraints, including welding defect types that are not allowed to occur; Based on the morphological information of various welding defects in the defect database, a second welding quality detection sub-cycle is set, and the termination condition corresponding to the second welding quality detection sub-cycle is associated with a second preset quality standard, and the second preset quality standard is determined by industry specification standards and welding process conditions as constraints; based on the size information of various welding defects in the defect database, a third welding quality detection sub-cycle is set, and the termination condition corresponding to the third welding quality detection sub-cycle is associated with a third preset quality standard, and the third preset quality standard is determined by industry specification standards and welding material characteristics as constraints; Connecting the first welding quality detection sub-cycle, the second welding quality detection sub-cycle, and the third welding quality detection sub-cycle to perform welding quality detection on the connector to be inspected; Connecting the first welding quality detection sub-cycle, the second welding quality detection sub-cycle, and the third welding quality detection sub-cycle includes: Define the termination condition corresponding to the first welding quality detection sub-cycle as the starting condition corresponding to the second welding quality detection sub-cycle, define the termination condition corresponding to the second welding quality detection sub-cycle as the starting condition corresponding to the third welding quality detection sub-cycle, and connect the first welding quality detection sub-cycle, the second welding quality detection sub-cycle, and the third welding quality detection sub-cycle.

2. A method for detecting the welding quality of a connector according to claim 1, characterized in that: The method comprises: Configuring 3D scanner parameters, wherein the 3D scanner parameters include resolution and scanning speed; Based on the 3D scanner parameters, a comprehensive solder joint coverage scan is performed on the connector to be inspected, and the coverage positions corresponding to the point cloud information include M solder joints and M peripheral areas, where the peripheral area refers to the surrounding area that closely surrounds each solder joint and has slight soldering differences; The M welding points and the M peripheral areas are combined to synchronously adjust the scanning process of the 3D scanner.

3. A method for detecting the welding quality of a connector as claimed in claim 2, characterized in that: The M welding points and the M perimeter areas are combined, and the 3D scanner is synchronously adjusted during the scanning process. The method includes: According to the shape structure of the connector to be inspected, P position states are added, and the P position states correspond to the relative positions of the connector to be inspected and the 3D scanner; Based on the P position states, and in comparison with the blocked area, a position adjustment instruction is issued; After the connector to be inspected receives the position adjustment instruction, the rotation action, tilt action, and translation action corresponding to the position adjustment instruction are synchronously executed.

4. A method for detecting the welding quality of a connector as claimed in claim 3, characterized in that: The P position states correspond to the relative positions of the connector to be inspected and the 3D scanner, and the method further includes: In a first position state, q scanning angles are added, and the first position state is any one of the P position states; Based on the q scanning angles, the numbers of solder joints in each scanning angle are arranged in descending order to obtain a first scanning angle sequence; Based on the q scanning angles, the perimeter area coverage ratio in each scanning angle is arranged in descending order to obtain a second scanning angle sequence; According to the first scanning angle sequence and the second scanning angle sequence, q′ optimal scanning angles in a first position state are determined.

5. A method for detecting the welding quality of a connector as claimed in claim 4, characterized in that: Determining q′ optimal scanning angles in a first position state according to the first scanning angle sequence and the second scanning angle sequence, the method further includes: Comparing the first scanning angle sequence and the second scanning angle sequence, screening out N candidate scanning angles for the same scanning angle whose serial number in the first scanning angle sequence and the serial number in the second scanning angle sequence are consistent; receiving a first verification signal, performing solder joint coverage integrity verification on the N candidate scanning angles, and if the verification passes, issuing a second verification signal; The coverage integrity of the peripheral area of ​​the N candidate scanning angles is verified through the second verification signal. If the verification passes, q′ optimal scanning angles in the first position state are determined.

6. A method for detecting the welding quality of a connector as claimed in claim 5, characterized in that: Receiving a first verification signal, and performing solder joint coverage integrity verification on the N candidate scanning angles, the method further comprising: If it fails, the uncovered solder joints are determined based on N alternative scanning angles; Recording multiple scanning angles except N candidate scanning angles in the first scanning angle sequence as remaining scanning angles, and arranging the uncovered solder joints in descending order according to the number of solder joints in the remaining scanning angles, to obtain a first scanning angle rearrangement sequence; Based on the first scanning angle re-arrangement sequence, N candidate scanning angles are supplementarily verified until the solder joint coverage integrity verification is passed.

7. A method for detecting the welding quality of a connector as claimed in claim 6, characterized in that: Based on the first scanning angle re-arrangement sequence, N candidate scanning angles are supplementarily verified until the solder joint coverage integrity verification is passed, and the method further includes: According to the shape structure of the connector to be inspected, determining U key solder joints and V regular solder joints among the M solder joints; According to the U key solder joints, a solder joint coverage integrity verification strategy is set, wherein the solder joint coverage integrity verification strategy includes a minimum scanning number threshold of the U key solder joints; When performing supplementary verification, a list of key solder joints is generated by the solder joint coverage integrity verification strategy, and the number of scans of each key solder joint is counted; If the scanning times of the key solder joints do not reach the corresponding minimum scanning times threshold, then the supplementary scanning is continued from the first scanning angle rearrangement sequence, and the scanning angles in the first scanning angle rearrangement sequence are only allowed to be supplemented once.

8. A method for detecting the welding quality of a connector as claimed in claim 7, characterized in that: According to the shape structure of the connector to be inspected, U key solder joints and V regular solder joints among the M solder joints are determined, and the method further includes: If all the scanning angles in the first scanning angle rearrangement sequence are supplemented with one scan, an auxiliary tool is used to perform supplementary scanning in combination with the V conventional welding points, and the auxiliary tool includes a reflector.

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