A friction stir welding control method and system based on welding analysis model

Abstract

The present application provides a stir friction welding control method and system based on a welding analysis model, which relates to the technical field of stir friction welding. The technical solution provided by the present application is based on a regional division method based on crack morphological characteristics and structural characteristics, so that the repair process can adopt differentiated treatment strategies according to the crack characteristics of different regions. By preferentially implementing the first repair solution for key areas, and evaluating the crack extension information and welding quality information in combination with the welding analysis model, the risk of crack propagation during the repair process can be effectively controlled. When the repair effect of the key area meets the preset requirements, the second repair solution is implemented for the general area. This zoned and step-by-step repair strategy is based on real-time monitoring and analysis of multimodal images and welding information, which enables the repair process to have adaptive adjustment capabilities, can promptly discover and solve problems in the repair process, and significantly improve the welding effect of stir friction welding.

Description

Technical Field

[0001] The present application relates to the technical field of friction stir welding, and in particular to a friction stir welding control method and system based on a welding analysis model. Background Art

[0002] Friction stir welding (FSW) is a solid-state joining technology that utilizes frictional heat and plastic deformation generated between a high-speed rotating stirrer and the workpiece to soften and thoroughly mix the materials in the joint area, thereby achieving a metal-to-metal connection. This welding method offers advantages such as minimal deformation, low residual stress, and the absence of filler material. It is particularly suitable for materials such as aluminum alloys that are difficult to weld using traditional fusion welding. Because the material remains in a solid state during FSW, the weld microstructure is fine and uniform, with excellent mechanical properties. Therefore, it holds great promise for crack repair applications.

[0003] When using friction stir welding for crack repair, conventional methods typically employ uniform welding parameters across the entire cracked area. This method not only easily leads to crack propagation, but also, due to the lack of effective monitoring of welding quality during the crack repair process, can easily lead to problems such as inadequate welding and insufficient joint strength. Consequently, conventional friction stir welding control methods suffer from the drawback of poor welding performance. Summary of the Invention

[0004] The present application provides a stir friction welding control method and system based on a welding analysis model, which can improve the welding repair effect.

[0005] In a first aspect, the present application provides a friction stir welding control method based on a welding analysis model, the method comprising:

[0006] Acquire a multimodal image of the crack area, and extract crack morphological features and crack structural features from the multimodal image;

[0007] Dividing the crack area into a key area and a general area according to the crack morphological characteristics and crack structural characteristics;

[0008] generating a first repair plan for the friction stir welding method of the key area, and controlling the stirring head to execute the first repair plan;

[0009] Respectively acquiring image information of the crack region and welding information of the key region, and inputting the image information and welding information into a welding analysis model to obtain crack extension information and welding quality information;

[0010] When both the crack extension information and the welding quality information meet the preset welding requirements, a second repair scheme of the friction stir welding method for the general area is generated, and the stirring head is controlled to execute the second repair scheme.

[0011] By adopting the above-mentioned technical solution and the regional division method based on the crack morphological characteristics and structural characteristics, the repair process can adopt differentiated treatment strategies based on the crack characteristics of different regions. By prioritizing the implementation of the first repair solution in key areas and evaluating the crack extension information and welding quality information in combination with the welding analysis model, the risk of crack propagation during the repair process can be effectively controlled. When the repair effect of the key area meets the preset requirements, the second repair solution is implemented in the general area. This zoned and step-by-step repair strategy is based on real-time monitoring and analysis of multimodal images and welding information, giving the repair process adaptive adjustment capabilities, enabling timely detection and resolution of problems in the repair process, and significantly improving the welding effect of stir friction welding.

[0012] Optionally, the crack morphological characteristics include crack shape characteristics and crack width characteristics, the crack structural characteristics include crack depth characteristics and crack surface characteristics, and the crack area is divided into a key area and a general area according to the crack morphological characteristics and crack structural characteristics, including:

[0013] Based on the crack morphological characteristics, identifying the main path and branch paths of the crack area;

[0014] Calculating the product of the crack width and the crack depth of the trunk path according to the crack width feature and the crack depth feature, and determining the trunk path where the product is greater than a preset first threshold as a first key area;

[0015] Determining a surface curvature of the crack region based on the crack surface features, and determining a second key region where the crack surface is in an arched state or a concave state according to the surface curvature;

[0016] The first key area and the second key area are determined as key areas, and areas other than the key areas in the crack area are divided into general areas.

[0017] By employing this technical solution, the crack's main and branch paths are identified. Combined with the product of crack width and depth, the severity of the crack can be accurately determined. Furthermore, curvature analysis of the crack's surface features can identify arched or depressed areas where stress concentrations exist. By classifying high-risk main path areas and surface deformation regions with high stress concentrations as key areas, targeted repair measures can be implemented, thereby improving the subsequent friction stir welding process.

[0018] Optionally, generating a first repair solution for the friction stir welding method of the key area and controlling the stirring head to execute the first repair solution includes:

[0019] Obtaining material properties of the key area and determining model parameters of a stirring head for friction stir welding;

[0020] Determining welding parameters of the stirring head according to the crack morphology and crack structure characteristics of the key area, wherein the welding parameters include rotation speed, travel speed, pressing depth and tilt angle;

[0021] Obtaining the crack direction of the key area, and planning the welding path of the key area according to the crack direction;

[0022] A first repair scheme for the friction stir welding method of the key area is generated according to the model parameters of the stirring head, the welding parameters and the welding path, and the stirring head is controlled to execute the first repair scheme.

[0023] By adopting the above technical solution, the material properties of the key areas can be obtained, and the most suitable stirring head model can be selected to ensure that the geometric characteristics of the stirring tool match the material properties. Based on the morphological and structural characteristics of the crack, the welding parameters such as rotation speed, travel speed, pressing depth and tilt angle are determined to achieve precise control of heat input and plastic deformation during welding. The welding path is planned in combination with the direction of the crack to ensure that the spatial position relationship between the stirring head and the crack is always in the optimal state. This method of unified planning of the stirring head model parameters, welding parameters and welding path establishes the correlation between material properties, crack characteristics and welding process, so that the repair plan can fully adapt to the actual conditions of the key areas. By controlling the stirring head to strictly implement the generated first repair plan, it can be ensured that the key areas obtain stable and reliable repair effects, and significantly improve the quality level of stir friction welding repairs.

[0024] Optionally, before generating a first repair solution of the friction stir welding method for the key area and controlling the stirring head to execute the first repair solution, the method further includes:

[0025] When there are multiple key areas, obtaining the physical structure of the workpiece in the crack area;

[0026] The stress distribution of the crack area is analyzed according to the physical structure of the workpiece, and the priority order of each key area is determined according to the order of the stress distribution from large to small.

[0027] By employing this technical solution, the physical structure of the workpiece in the cracked area is captured and, combined with stress distribution analysis, the stress levels in different key areas can be accurately identified. Prioritizing these key areas in descending order of stress distribution allows for prioritization of repairs in areas subject to greater stress. This stress-based repair sequence effectively reduces the risk of secondary damage in high-stress areas.

[0028] Optionally, the welding analysis model includes a crack analysis sub-model and a welding quality inspection sub-model, and the steps of respectively acquiring image information of the crack area and welding information of the key area, and inputting the image information and welding information into the welding analysis model to obtain crack extension information and welding quality information include:

[0029] Acquiring image information of the crack area after executing the first repair solution;

[0030] Inputting the multimodal image and the image information before welding into the crack analysis sub-model, detecting whether new cracks are induced or existing cracks extend during the welding process by image comparison, and generating crack extension information;

[0031] Real-time collection of welding information of key areas during welding;

[0032] The welding information is input into the welding quality inspection sub-model, and the welding quality information of the key area is generated through process parameter matching analysis.

[0033] By employing this technical solution, pre- and post-weld image information is captured and fed into the crack analysis sub-model, enabling timely detection of new crack formation or expansion of existing cracks during the welding process, providing a reliable means for monitoring crack evolution. Furthermore, by collecting welding information in real time and feeding it into the welding quality inspection sub-model, dynamic assessment of the compatibility of welding process parameters is achieved, ensuring that the welding process remains optimal. This twin-model-based analysis method organically combines crack monitoring with quality inspection, enabling comprehensive assessment of repair outcomes and timely identification of potential quality issues.

[0034] Optionally, the welding information includes axial stress, transverse shear stress, plastic strain distribution, and temperature field data. Inputting the welding information into the welding quality inspection sub-model and generating welding quality information through process parameter matching analysis includes:

[0035] Inputting the axial stress, the transverse shear stress, the plastic strain distribution and the temperature field data into a welding quality inspection sub-model;

[0036] Calculating a deviation between the axial stress and a preset axial stress threshold to generate an axial stress matching index;

[0037] Calculating the ratio of the transverse shear stress to the critical shear stress based on the material mechanical property parameters to generate a shear stress safety factor;

[0038] Analyzing the spatial gradient characteristics of the plastic strain distribution and calculating the strain uniformity index, wherein the strain uniformity index is used to characterize the plastic deformation consistency of the key area;

[0039] Matching the temperature field data with a standard welding temperature field distribution and calculating a temperature field similarity coefficient;

[0040] The welding quality information of the key area is generated based on the axial stress matching index, the shear stress safety factor, the strain uniformity index and the temperature field similarity coefficient.

[0041] By adopting the above technical solution, the rationality of the welding stress can be evaluated by calculating the deviation between the axial stress and the preset threshold; by calculating the ratio of the transverse shear stress to the critical shear stress, the shear safety state of the material can be determined; by analyzing the spatial gradient characteristics of the plastic strain distribution, the uniformity of the plastic deformation can be evaluated; and by matching the temperature field data with the standard distribution, the rationality of the heat input can be evaluated. This multi-index collaborative evaluation method takes into account key factors such as stress state, plastic deformation, and temperature distribution, forming a complete evaluation system that includes the axial stress matching index, shear stress safety factor, strain uniformity index, and temperature field similarity coefficient. Generating welding quality information through comprehensive analysis of these indicators can not only comprehensively reflect the performance status of the welded joint, but also provide a reliable basis for the optimization of welding process parameters, significantly improving the accuracy and reliability of welding quality evaluation.

[0042] Optionally, the preset welding requirements include a first welding requirement and a second welding requirement, and when the crack extension information and the welding quality information both meet the preset welding requirements, generating a second repair scheme of the friction stir welding method for the general area, and controlling the stirring head to execute the second repair scheme, including:

[0043] Verifying whether the welding of the key area suppresses crack extension based on the crack extension information, and determining that the first welding requirement is met when the crack extension length is less than a preset second threshold;

[0044] Comparing the welding quality information with a corresponding preset third threshold to determine whether the welding quality information meets a second welding requirement;

[0045] When the first welding requirement and the second welding requirement are simultaneously met, extracting crack morphological characteristics and crack structural characteristics of the general area;

[0046] adjusting the welding parameters of the stirring head according to the crack characteristics of the general area to generate a second repair solution that is at least one strength grade lower than the first repair solution;

[0047] According to the second repair scheme, the stirring head is controlled to perform repair welding on the general area, and the welding quality information of the connection between the general area and the adjacent key area is monitored in real time during the welding process.

[0048] By employing this technical solution, dual verification of crack extension and welding quality information ensures that repairs in key areas achieve the desired results. Crack suppression effectiveness is verified by comparing crack extension length with a preset second threshold, and welding quality information is matched and analyzed with a preset third threshold, enabling a comprehensive assessment of repair quality. After confirming that the repair in the key area meets both requirements, welding parameters are adjusted based on the crack characteristics of the general area. By reducing the repair intensity level, this ensures both repair effectiveness and efficiency.

[0049] In a second aspect, the present application provides a friction stir welding control system based on a welding analysis model, the system comprising:

[0050] A feature extraction module, configured to obtain a multimodal image of the crack region and extract crack morphological features and crack structural features from the multimodal image;

[0051] A region division module, configured to divide the crack region into a key region and a general region according to the crack morphological characteristics and crack structural characteristics;

[0052] A first execution module is used to generate a first repair plan of the friction stir welding method for the key area and control the stirring head to execute the first repair plan;

[0053] An analysis module is used to respectively obtain image information of the crack area and welding information of the key area, and input the image information and welding information into a welding analysis model to obtain crack extension information and welding quality information;

[0054] The second execution module is used to generate a second repair plan of the stir friction welding method for the general area when the crack extension information and the welding quality information both meet the preset welding requirements, and control the stirring head to execute the second repair plan.

[0055] In a third aspect, the present application provides a computer storage medium, which stores a plurality of instructions, and the instructions are suitable for being loaded by a processor and executing any one of the above methods.

[0056] In a fourth aspect, the present application provides an electronic device comprising a processor, a memory and a transceiver, wherein the memory is used to store instructions, the transceiver is used to communicate with other devices, and the processor is used to execute the instructions stored in the memory so that the electronic device performs any one of the above methods.

[0057] In summary, the beneficial effects brought about by the technical solution of this application include:

[0058] By adopting the above-mentioned technical solution and the regional division method based on the crack morphological characteristics and structural characteristics, the repair process can adopt differentiated treatment strategies based on the crack characteristics of different regions. By prioritizing the implementation of the first repair solution in key areas and evaluating the crack extension information and welding quality information in combination with the welding analysis model, the risk of crack propagation during the repair process can be effectively controlled. When the repair effect of the key area meets the preset requirements, the second repair solution is implemented in the general area. This zoned and step-by-step repair strategy is based on real-time monitoring and analysis of multimodal images and welding information, giving the repair process adaptive adjustment capabilities, enabling timely detection and resolution of problems in the repair process, and significantly improving the welding effect of stir friction welding. BRIEF DESCRIPTION OF THE DRAWINGS

[0059] Figure 1 1 is a flow chart of a friction stir welding control method based on a welding analysis model according to an embodiment of the present application;

[0060] Figure 2 1 is a structural diagram of a friction stir welding control system based on a welding analysis model according to an embodiment of the present application;

[0061] Figure 3 This is a structural diagram of an electronic device provided in an embodiment of the present application.

[0062] Description of reference numerals: 300, electronic device; 301, processor; 302, communication bus; 303, user interface; 304, network interface; 305, memory. DETAILED DESCRIPTION

[0063] In order to enable people skilled in the art to better understand the technical solutions in this specification, the technical solutions in the embodiments of this specification will be clearly and completely described below in conjunction with the drawings in the embodiments of this specification. Obviously, the described embodiments are only part of the embodiments of this application, not all of the embodiments.

[0064] In the description of the embodiments of this application, words such as "exemplary," "for example," or "for example" are used to indicate examples, illustrations, or descriptions. Any embodiment or design described as "exemplary," "for example," or "for example" in the embodiments of this application should not be construed as being preferred or advantageous over other embodiments or designs. Rather, the use of words such as "exemplary," "for example," or "for example" is intended to present the relevant concepts in a concrete manner.

[0065] In the description of the embodiments of the present application, the term "multiple" means two or more. For example, multiple systems refer to two or more systems, and multiple screen terminals refer to two or more screen terminals. In addition, the terms "first" and "second" are used for descriptive purposes only and are not to be understood as indicating or implying relative importance or implicitly indicating the indicated technical features. Thus, the features defined as "first" and "second" may explicitly or implicitly include one or more of the features. The terms "including", "comprising", "having" and their variations all mean "including but not limited to", unless otherwise specifically emphasized.

[0066] See Figure 1 The following is a flow chart of a friction stir welding control method based on a welding analysis model, provided in an embodiment of the present application. This method can be implemented using a computer program, a single-chip microcomputer, or run on a von Neumann-based friction stir welding control system based on a welding analysis model. The computer program can be integrated into an application or run as a standalone tool application. The specific steps of the friction stir welding control method based on a welding analysis model are described in detail below.

[0067] S101: Acquire a multimodal image of the crack area and extract crack morphological features and crack structural features from the multimodal image;

[0068] Among them, the crack area refers to the crack location and its surrounding area caused by fatigue, stress concentration, material defects and other factors on the surface of metal workpieces such as aluminum alloys and magnesium alloys that are suitable for repair by stir friction welding process. This area includes not only the morphological characteristics of the crack itself, but also the affected material structure around the crack.

[0069] Among them, crack morphological characteristics refer to the appearance characteristics of the crack on the surface of the workpiece, mainly including the planar characteristics such as the crack's external contour, direction, length, surface width and crack expansion path.

[0070] Crack structural characteristics refer to the three-dimensional spatial features of the crack region, including three-dimensional geometric features such as crack depth distribution, surface curvature, crack cross-sectional shape, and crack propagation direction. By analyzing the three-dimensional model constructed from multimodal images, spatial information such as the specific depth value and surface flatness of the crack region can be obtained.

[0071] In this embodiment, due to the complexity of crack information, a single image acquisition method is unable to fully reflect all crack characteristics. Therefore, multiple imaging devices are used to capture images of the crack area, obtaining multimodal images including visible light images, infrared thermal images, and ultrasonic images. These different modal images can reflect crack characteristics from different angles. Visible light images are primarily used to observe the surface characteristics of the crack, infrared thermal images can reflect the temperature distribution of the crack area and the internal state of the material, and ultrasonic images can detect crack depth information. The acquired multimodal images are input into an image recognition system, and an edge detection algorithm is used to extract morphological features such as the crack's shape, direction, and length. Combined with depth information analysis, structural features such as the crack's depth distribution and surface curvature are obtained.

[0072] S102: Divide the crack area into key areas and general areas based on crack morphological characteristics and crack structural characteristics;

[0073] Among them, the key area refers to a specific part in the crack area with a higher welding repair priority. It can be understood as: based on the quantitative analysis of the crack morphological characteristics and structural characteristics, it is identified as an area that requires priority treatment and adopts enhanced welding parameters. The division standard is that the crack characteristics of this area indicate that if it is not given priority treatment, the risk of crack propagation during welding will increase significantly or the repair quality will not meet the standards.

[0074] Among them, the general area refers to the rest of the crack area except the key area, which can be understood as: based on the collaborative analysis of crack morphological characteristics and structural characteristics, it is identified as an area with relatively low welding repair priority. Its crack characteristics indicate that the repair of this area can be completed in the key area and verified by the welding analysis model, and then safely implemented using standard or degraded welding parameters.

[0075] In the embodiment of the present application, the division of the crack area is based on the collaborative analysis of the crack morphological characteristics and crack structural characteristics. By quantitatively evaluating the geometric characteristics and mechanical effects of the crack, the repair area is differentiated to achieve precise control. In the specific implementation, the topological structure data of the crack is first extracted by a multimodal imaging system, including but not limited to the distribution of the crack width along the path, the depth profile characteristics and the surface morphology curvature. For the section where the product of the crack width and depth exceeds the material-related threshold, the significantly increased cross-sectional characteristic quantity indicates that the area has a high risk of stress concentration. If it is not treated as a priority, it may induce secondary crack expansion under the action of the welding thermal cycle, so it is delineated as the first key area. At the same time, the arched or concave morphology areas identified based on the surface curvature analysis are listed as the second key areas because they will cause poor contact between the stirring head and the substrate and produce unwelded defects. The remaining crack sections not covered by the above standards, whose geometric characteristics indicate that the mechanical response caused by the heat input is relatively controllable, are classified as general areas.

[0076] Based on the above embodiment, as an optional implementation method, the division of key areas and general areas can be specifically implemented through the following steps S201-S204.

[0077] S201: Based on the crack morphology characteristics, identify the main path and branch paths of the crack area;

[0078] In practice, crack regions typically exhibit a complex network structure, encompassing primary extension directions and secondary branching paths. To accurately identify the main and branching paths within a crack region, a multimodal image acquisition device is first used to acquire image information of the crack region. Multimodal images include visible light images, infrared thermal images, and ultrasonic scanning images. Image preprocessing techniques are used to reduce noise and enhance the multimodal images, extracting the edge contours of the cracks. Subsequently, a skeleton extraction algorithm is used to refine the processed image, simplifying the crack network into single-pixel-width skeleton lines to facilitate subsequent path identification.

[0079] Based on the crack skeleton, a minimum spanning tree algorithm was used to construct a crack propagation network. The crack's starting point was set as the root node, and the primary direction of crack propagation was determined by calculating the connectivity weights between each node. Morphological analysis was then used to extract the crack's shape characteristics, including its extension length, curvature variation, and bifurcation characteristics. Paths with long extension lengths and gentle curvature variations were identified as main paths, while paths with bifurcated connections to the main path and relatively short extension lengths were identified as branch paths.

[0080] S202: Calculating the product of the crack width and crack depth of the trunk path according to the crack width characteristics and the crack depth characteristics, and determining the trunk path whose product is greater than a preset first threshold as a first key area;

[0081] Testing points are set at regular intervals along the trunk path, and crack width and depth data are collected at each testing point using a detection device. Based on the collected data, the product of the crack width and crack depth at each testing point is calculated to form crack damage distribution data, which characterizes the damage variation along the trunk path. The crack damage distribution data is compared with a preset first threshold. When the product values ​​of multiple consecutive testing points are greater than the preset first threshold, the trunk path section and the surrounding affected area are designated as the first priority area.

[0082] S203: determining a surface curvature of the crack region based on the crack surface characteristics, and determining a second key region where the crack surface is in an arched state or a concave state according to the surface curvature;

[0083] Among them, the crack surface characteristics refer to the geometric characteristics of the crack area surface, including surface height distribution, local concavity and convexity, and surface deformation state.

[0084] Surface curvature refers to the degree to which the crack surface deviates from a flat state. It is quantified by calculating the surface curvature, which mainly includes two indicators: Gaussian curvature and mean curvature. Gaussian curvature is the product of the principal curvatures, and mean curvature is the arithmetic mean of the principal curvatures.

[0085] Among them, the arched state refers to the deformation state in which the crack surface bulges upward relative to the reference plane, which is usually caused by local plastic deformation of the material due to internal stress; the concave state refers to the deformation state in which the crack surface is concave relative to the reference plane, which is often related to internal crack expansion and material damage.

[0086] A variety of detection methods are used to analyze the surface characteristics of the crack, obtaining multi-dimensional measurement data including laser 3D scanning data, digital speckle images, and surface strain cloud maps. These different types of measurement data can reflect the deformation characteristics of the crack surface from different angles. Laser 3D scanning is mainly used to obtain point cloud data of the surface contour, digital speckle images can analyze the surface strain distribution state, and surface strain cloud maps can display the gradient distribution of deformation. The acquired measurement data is input into the surface analysis system, and the local surface curvature is calculated using the least squares surface fitting algorithm. Combined with the principal curvature analysis, it is determined whether the surface has abnormal deformation. For areas with abnormal curvature, the strain distribution is further combined to determine their arching or concave state, thereby identifying the second key area that requires special attention.

[0087] S204: Determine the first key area and the second key area as key areas, and divide the area other than the key area in the crack area into a general area.

[0088] In this example, due to significant differences in damage severity and repair difficulty across different areas, a zoning strategy is employed for welding repair. Specifically, the first key area, determined by crack size calculation, and the second key area, determined by surface curvature analysis, are spatially marked. A dedicated marking pen is used to delineate the boundaries of the key areas on the workpiece surface. Furthermore, the remaining portions of the cracked area not marked as key areas are designated as general areas, forming a complete regional classification map.

[0089] S103: generating a first repair plan of the friction stir welding method for the key area, and controlling the stirring head to execute the first repair plan;

[0090] During the specific implementation, the analysis results of the key area in the previous step are first used. Based on the material properties of the key area that have been obtained, the system will select the model parameters of the stirring head to ensure that the selected stirring head can adapt to the welding requirements of the specific material and can effectively handle the crack characteristics of the key area. Next, the welding parameters of the stirring head will be carefully determined according to the crack morphology and crack structure characteristics of the key area, including but not limited to rotation speed, travel speed, pressing depth and tilt angle. The setting of these parameters is intended to optimize the heat input, material flow and plastic deformation behavior during the welding process, in order to obtain the best crack closure effect and joint structure. At the same time, the crack direction of the key area is obtained, and the welding path of the key area is planned according to this crack direction to ensure that the stirring head can accurately cover and repair the entire key crack area. Finally, the system will integrate the determined stirring head model parameters, calculated welding parameters and planned welding path to generate a complete first repair plan for the stir friction welding method for the key area. Subsequently, the first repair plan is transmitted to the control system of the friction stir welding equipment, and the control system accurately drives the stirring head to perform repair welding operations on key areas according to the parameters and paths set in the plan.

[0091] On the basis of the above embodiment, as an optional implementation manner, the manner of controlling the stirring head to execute the first repair solution can be specifically implemented through the following steps S301-S304.

[0092] S301: Obtaining material properties of a key area and determining model parameters of a stirring head for friction stir welding;

[0093] During implementation, the material type of the workpiece in the key area is determined, and the relevant material parameters, such as yield strength, tensile strength, melting point, and thermal conductivity, are accurately obtained. Next, based on these material parameters and the requirements of the friction stir welding process for the stir head model, a comprehensive analysis is conducted to determine the optimal stir head model parameters, primarily including geometric parameters such as the stir head shoulder diameter, taper angle, and probe length and diameter.

[0094] S302: Determine welding parameters of the stirring head based on the crack morphology and structural characteristics of the key area. The welding parameters include rotation speed, travel speed, pressing depth, and tilt angle.

[0095] During implementation, the system analyzes the crack morphology characteristics of key areas. For example, the width and overall profile of the crack will influence the setting of the rotation speed and travel speed. Wider or more complex cracks may require a specific combination of rotation speeds to generate sufficient heat and plastic material flow to ensure adequate filling; at the same time, the travel speed must also be matched to ensure sufficient stirring time and material transport per unit length. The crack depth characteristic within the crack structure is the key basis for determining the pressing depth. The pressing depth must be set to enable the stirring head to effectively act at the crack root to ensure that the original crack interface is completely eliminated. In addition, the crack surface characteristics, such as the presence of oxidation or contaminants, will in turn affect the selection of rotation speed to ensure sufficient cleaning and activation. The determination of the tilt angle will take into account the crack morphology characteristics and the desired material flow method. A suitable tilt angle helps control the migration path of the plastic metal and promotes dense filling and good surface formation of the weld.

[0096] S303: Obtain the crack direction of the key area and plan the welding path of the key area according to the crack direction;

[0097] During specific implementation, the welding path of stir friction welding is systematically planned based on the crack direction information, combined with the crack width characteristics and crack depth characteristics. The planning of the welding path needs to consider the following technical points: First, the welding path should maintain a certain angle with the crack direction, so as to ensure that the stirring area of ​​the stirring head can fully cover the crack area and achieve effective material plasticization and mixing. Secondly, when planning the path, it is necessary to consider the changes in the surface characteristics of the crack in the key area. When the crack surface is in an arched or concave state, the welding path should be adjusted accordingly to adapt to the changes in the surface morphology. Thirdly, the planning of the welding path also needs to consider the model parameters of the stirring head to ensure that the path planning meets the motion characteristics requirements of the stirring head.

[0098] S304: generating a first repair plan for the friction stir welding method of the key area according to the model parameters, welding parameters and welding path of the stirring head, and controlling the stirring head to execute the first repair plan.

[0099] The stirring head model parameters include the geometric size characteristics of the stirring head, which directly affects the material flow state during welding; the rotation speed, travel speed, pressing depth and tilt angle in the welding parameters determine the heat input and the degree of plastic deformation; and the welding path ensures complete coverage of the repair area.

[0100] When generating the first repair plan, it is necessary to comprehensively consider the crack morphology and crack structure characteristics of the key areas and systematically match the stirring head model parameters with the welding parameters. First, the downward pressure depth is determined based on the crack depth characteristics to ensure that the stirring action of the stirring head can fully reach the bottom of the crack. Secondly, the inclination angle of the stirring head is adjusted based on the crack width characteristics to obtain the appropriate advance angle and working angle to enhance the plasticization effect of the material. At the same time, it is also necessary to optimize the ratio of rotation speed and travel speed according to the crack surface characteristics to ensure sufficient heat input while avoiding overheating.

[0101] Optionally, when there are multiple key areas, obtaining the physical structure of the workpiece in the crack area;

[0102] The stress distribution in the crack area is analyzed according to the physical structure of the workpiece, and the priority order of each key area is determined in descending order of stress distribution.

[0103] During specific implementation, it is first necessary to obtain the physical structure information of the workpiece in the crack area, including basic information such as the workpiece's geometric characteristics, structural characteristics, and material properties. This information is the basis for stress distribution analysis. By analyzing the physical structure of the workpiece, combined with the crack morphological characteristics and crack structural characteristics, the stress state of each key area during the service life of the workpiece can be determined. Stress distribution analysis needs to take into account the force characteristics of the workpiece, and also the impact of the geometric discontinuity of the workpiece structure on the stress distribution. On this basis, the stress level of each key area is calculated, and these areas are sorted in order from large to small according to the stress distribution, so as to determine the priority order of repair.

[0104] S104: acquiring image information of the crack area and welding information of the key area respectively, and inputting the image information and welding information into a welding analysis model to obtain crack extension information and welding quality information;

[0105] Image information of the crack region refers to information obtained by imaging the entire crack region using multimodal imaging equipment. This information includes visually identifiable features such as the crack's appearance, surface topography, and regional distribution. By comparing image information before and after welding, changes in the crack state can be intuitively observed. Welding information of key areas refers to data reflecting the welding status collected in real time by various sensors during the welding process. This information can demonstrate the stability and reliability of the welding process.

[0106] Inputting these two types of information into the welding analysis model generates crack extension information and weld quality information, respectively. Crack extension information indicates whether the welding process has caused the expansion of existing cracks or the creation of new cracks, which is important for evaluating the effectiveness of repairs. Weld quality information comprehensively reflects the performance of the weld joint, including evaluation results of multiple aspects such as joint integrity and strength.

[0107] Based on the above embodiment, as an optional implementation method, the welding analysis model includes a crack analysis sub-model and a welding quality inspection sub-model, and a specific evaluation is performed on the stirring head after executing the first repair plan, which can be specifically achieved through the following steps S401-S404.

[0108] S401: Acquire image information of the crack area after executing the first repair solution;

[0109] Specifically, after the stirring head completes the weld repair in the key area, an image acquisition device is used to image the entire crack area. This image acquisition device includes a visible light camera and an infrared camera. The visible light camera acquires surface morphology information of the crack area, and the infrared camera acquires temperature distribution information of the crack area. When acquiring the image, the position and angle of the image acquisition device are first adjusted to ensure that its field of view can completely cover the crack area and maintain the same imaging conditions as before welding. Subsequently, the image acquisition device is controlled to perform synchronous acquisition to obtain multimodal image information of the crack area after welding. This image information not only includes the surface characteristics of the weld repair area, but also reflects the expansion of new cracks or existing cracks that may have occurred during the welding process.

[0110] S402: Inputting the multimodal image and image information before welding into the crack analysis sub-model, detecting whether new cracks are induced or existing cracks extend during the welding process through image comparison, and generating crack extension information;

[0111] In specific implementation, the multimodal images acquired before welding are first registered with the post-weld image information to ensure precise spatial alignment between the two sets of images. Subsequently, image processing techniques are used to extract crack features from both sets of images, including information such as crack location, length, and direction. Based on this feature extraction, an image difference algorithm is used to compare and analyze crack features before and after welding to identify potential crack changes during the welding process. By calculating the offset of the crack tip position, the extent of the original crack can be quantitatively assessed. By detecting the presence of new crack features around the weld area, it is possible to determine whether the welding process has induced new cracks.

[0112] S403: Real-time collection of welding information of key areas during welding;

[0113] Specifically, during the execution of the first repair solution by the stirring head, the welding status of key areas is continuously monitored through the sensor system configured on the welding equipment. The sensor system includes stress sensors, temperature sensors, and strain sensors, which are used to collect axial stress, transverse shear stress, temperature field data, and plastic strain distribution information during the welding process. During the welding process, the sensor system continuously collects data at a preset sampling frequency to ensure that transient changes in the welding process can be captured. These sensors are arranged at key positions around the stirring head to obtain the most representative welding parameter information. Through the real-time data acquisition system, the various types of collected information are synchronously integrated to form a complete welding information data stream.

[0114] S404: Input the welding information into the welding quality inspection sub-model, and generate welding quality information of key areas through process parameter matching analysis.

[0115] During implementation, the collected welding data must first be preprocessed, including signal filtering and data standardization, to eliminate potential interference factors and ensure data reliability. Subsequently, based on process parameter matching analysis, the processed welding data is compared with standard welding process parameters to assess the degree of match between the actual welding parameters and the ideal parameters. This parameter matching analysis allows for a comprehensive assessment of the stability and reliability of the welding process and generates comprehensive information reflecting the welding quality status of key areas.

[0116] Based on the above embodiment, as an optional implementation manner, the welding information includes axial stress, transverse shear stress, plastic strain distribution and temperature field data, and step S404 specifically includes steps S501-S506.

[0117] S501: Inputting axial stress, transverse shear stress, plastic strain distribution and temperature field data into the welding quality inspection sub-model;

[0118] Among them, axial stress refers to the stress generated along the welding direction during the stir friction welding process, which can be understood in the embodiment of the present application as a physical quantity used to characterize the stress state of the material during the welding process; transverse shear stress refers to the shear stress perpendicular to the welding direction, which can be understood in the embodiment of the present application as a physical quantity used to characterize the stress state of the material during the welding process; plastic strain distribution refers to the permanent deformation distribution state of the material during the welding process, which can be understood in the embodiment of the present application as a distribution feature used to characterize the flow and deformation degree of the material; temperature field data refers to the temperature distribution at various positions of the workpiece during the welding process, which can be understood in the embodiment of the present application as temperature information used to reflect the welding heat input and heat conduction characteristics; welding quality inspection sub-model refers to an analysis tool for evaluating welding quality, which can be understood in the embodiment of the present application as a processing unit used to comprehensively analyze welding process parameters and evaluate welding quality.

[0119] In practice, the collected data on axial stress, transverse shear stress, plastic strain distribution, and temperature field are first preprocessed. This preprocessing process includes three steps: data cleaning, standardization, and outlier removal. The data cleaning stage removes noise and redundant data generated during the acquisition process. Standardization converts different physical quantities into dimensionless parameters with a unified dimension, eliminating the impact of dimensional differences on the analysis results. Outlier removal filters out abnormal data points that fall outside the normal process parameter range by setting a reasonable fluctuation range.

[0120] The preprocessed data is fed into the welding quality inspection submodel. The submodel's input layer contains four data channels, one for axial stress, the other for transverse shear stress, the other for plastic strain distribution, and the other for temperature field. The model's training set consists of a large amount of historical welding data, derived from experimental records under various welding conditions and labeled with corresponding weld quality grades. By analyzing the training data, a correspondence between various physical quantities and weld quality is established, forming a welding quality assessment criterion.

[0121] In practical applications, the welding quality inspection sub-model performs a multi-dimensional analysis of input physical quantities: first, it assesses whether each physical quantity is within a reasonable range; then, it analyzes the coupling relationships between physical quantities, including the synergy between stress and temperature fields, and the matching degree between plastic deformation and stress distribution; finally, it comprehensively judges the welding quality status based on established evaluation criteria. This comprehensive analysis method based on multiple physical quantities can comprehensively reflect the welding status from the perspective of material mechanical properties and thermal-mechanical coupling, and effectively identify problems such as stress anomalies and uneven deformation during the welding process.

[0122] S502: Calculate the deviation between the axial stress and a preset axial stress threshold value to generate an axial stress matching index;

[0123] The axial stress matching index refers to an evaluation parameter that reflects the degree of conformity between the actual axial stress and the preset axial stress threshold. In the embodiment of the present application, it can be understood as a technical indicator for quantitatively evaluating the level of axial stress control during welding. The index is obtained by calculating the deviation value between the actual axial stress and the preset axial stress threshold.

[0124] In specific implementation, an axial stress threshold is set based on welding process requirements. This threshold reflects the ideal stress state required to ensure weld quality. Subsequently, the collected actual axial stress data undergoes preprocessing, including data smoothing and noise removal, to improve data reliability. Furthermore, quantitative stress difference information is obtained by calculating the deviation between the actual axial stress and the preset axial stress threshold. Based on this calculated deviation and the allowable range of stress deviation, an axial stress matching index is generated to reflect the stress state during the welding process.

[0125] S503: Calculate the ratio of the transverse shear stress to the critical shear stress based on the mechanical property parameters of the material, and generate a shear stress safety factor;

[0126] The shear stress safety factor refers to the inverse of the ratio of the transverse shear stress to the critical shear stress, which reflects the ability of the material to resist shear failure during welding. In the embodiment of the present application, it can be understood as a quantitative indicator for evaluating the safety degree of the shear stress state of the material during welding. This indicator is obtained by calculating the ratio of the actual transverse shear stress to the critical shear stress of the material, and is used to characterize the shear safety margin of the material during welding.

[0127] During implementation, the critical shear stress value is first determined based on the mechanical properties of the material to be repaired. This value represents the material's ultimate load-bearing capacity under shear. Subsequently, the real-time transverse shear stress data is preprocessed, including signal filtering and data normalization, to improve data quality. Based on this, the ratio of the transverse shear stress to the critical shear stress is calculated based on the material's mechanical properties to generate a shear stress safety factor. This safety factor reflects the material's safety margin under shear during welding and provides a visual representation of the safety status of the welding process.

[0128] S504: Analyze the spatial gradient characteristics of the plastic strain distribution and calculate the strain uniformity index, which is used to characterize the consistency of plastic deformation in key areas;

[0129] In specific implementation, the collected plastic strain distribution data is first spatially discretized to obtain the strain values ​​at each measurement point within the key area. Subsequently, the strain gradient between adjacent measurement points is calculated, and the spatial variation characteristics of the strain distribution are analyzed. After obtaining the strain gradient data, the degree of variation of the strain gradient within the key area is calculated to obtain a quantitative indicator reflecting the uniformity of plastic deformation, namely the strain uniformity index. This index effectively characterizes the degree of consistency of plastic deformation within the key area by evaluating the spatial distribution characteristics of the strain gradient.

[0130] S505: Matching the temperature field data with the standard welding temperature field distribution and calculating the temperature field similarity coefficient;

[0131] In specific implementation, a standard welding temperature field distribution is first established based on the welding process requirements. This distribution reflects the temperature distribution characteristics under ideal welding conditions. Subsequently, the collected actual temperature field data undergoes preprocessing, including spatial alignment and data smoothing, to ensure comparability with the standard temperature field. Furthermore, the temperature field similarity coefficient is calculated by calculating the spatial distribution difference between the actual and standard temperature fields. This coefficient reflects the degree of closeness of the temperature field distribution during the actual welding process to the ideal state and can intuitively demonstrate the accuracy of temperature field control.

[0132] S506: Generate welding quality information of key areas based on the axial stress matching index, shear stress safety factor, strain uniformity index and temperature field similarity coefficient.

[0133] During the friction stir welding repair process, in order to comprehensively evaluate the welding quality status of key areas, a comprehensive analysis of various quality indicators is required. The axial stress matching index reflects the stress control level, the shear stress safety factor characterizes the shear safety margin of the material, the strain uniformity index reflects the consistency of plastic deformation, and the temperature field similarity coefficient reflects the rationality of the temperature field distribution. These indicators describe the quality characteristics of the welding process from different angles. In the specific implementation, these four indicators are first weighted, and the corresponding weight coefficient is determined according to the degree of influence of each indicator on the welding quality. Subsequently, each indicator and its weight are substituted into the quality evaluation function, and the evaluation results reflecting the comprehensive quality of the welding are obtained by calculation. Based on the evaluation results, welding quality information containing welding quality grade, quality characteristic description, etc. is generated.

[0134] S105: When the crack extension information and the welding quality information both meet the preset welding requirements, a second repair scheme of the friction stir welding method for the general area is generated, and the stirring head is controlled to execute the second repair scheme.

[0135] When the crack extension information shows that the welding process did not induce new cracks or the original cracks expanded, and the welding quality information shows that the performance of the welded joint meets the preset welding requirements, it indicates that the execution effect of the first repair plan is good and the repair work of the general area can continue. At this time, it is necessary to generate a second repair plan based on the repair experience of the key area and the characteristics of the general area. In the specific implementation, first analyze the crack characteristics and material state of the general area, and combine the welding parameter optimization experience obtained in the repair of the key area to determine the stir friction welding process parameters suitable for the general area. Subsequently, according to the geometric characteristics and spatial position of the general area, plan the motion trajectory and posture of the stirring head to generate a complete second repair plan. After the plan is generated, the stirring head is driven by the control system to perform the repair task according to the planned path and parameters.

[0136] Based on the above embodiment, as an optional implementation manner, the preset welding requirement includes a first welding requirement and a second welding requirement, and step S105 specifically includes steps S601-S605.

[0137] S601: Verify whether welding of the key area suppresses crack propagation based on the crack extension information, and determine that the first welding requirement is met when the crack propagation length is less than a preset second threshold;

[0138] Among them, the first welding requirement refers to the crack suppression standard for evaluating the welding repair effect of key areas. In the embodiment of the present application, it can be understood as a technical indicator for determining whether the crack propagation control is effective during the stir friction welding repair process. This requirement determines whether the welding process effectively suppresses crack propagation by comparing the crack propagation length with the preset second threshold.

[0139] In specific implementation, the crack extension information is first analyzed and processed. Image processing techniques are used to extract data on the change in the crack end position before and after welding, and the crack extension length during the welding process is calculated. The calculated crack extension length is then compared with a pre-set second threshold, which represents the maximum acceptable crack extension. If the crack extension length is less than the pre-set second threshold, the welding process effectively suppresses crack extension, and the first welding requirement is determined to be met.

[0140] S602: Compare the welding quality information with a corresponding preset third threshold to determine whether the welding quality information meets the second welding requirement;

[0141] In specific implementation, the generated welding quality information, including the axial stress matching index, shear stress safety factor, strain uniformity index, and temperature field similarity coefficient, is first compared with corresponding preset third thresholds. These preset third thresholds represent the minimum standards required for each welding quality indicator. Through comparative analysis, it is determined whether the welding quality information meets the second welding requirement.

[0142] S603: When the first welding requirement and the second welding requirement are simultaneously met, extracting crack morphological characteristics and crack structural characteristics of the general area;

[0143] During implementation, the first step is to confirm that both the first and second welding requirements are met, indicating that the repair work in the key area has achieved the desired results. Subsequently, an image acquisition device is used to capture crack image information from the general area, from which the morphological and structural characteristics of the cracks are extracted. Crack morphological characteristics include external features such as the crack's geometry, orientation, and distribution density, while crack structural characteristics include internal features such as the crack's depth, width, and bifurcation.

[0144] S604: adjusting welding parameters of the stirring head according to crack characteristics of the general area, generating a second repair solution that is at least one strength level lower than the first repair solution;

[0145] In practice, the crack characteristics of the general area are first analyzed, including crack depth, length, and distribution. Based on these characteristics, the required weld strength level is determined. Subsequently, based on the welding parameters of the first repair solution, the welding process intensity is adjusted by reducing parameters such as the stirrer rotation speed, feed rate, and axial pressure, reducing the welding process intensity by at least one strength level. This generates a second repair solution suitable for the general area. This parameter adjustment method based on crack characteristics ensures repair quality while improving welding efficiency.

[0146] S605: Control the stirring head to perform repair welding on the general area according to the second repair plan, and monitor the welding quality information of the connection between the general area and the adjacent key area in real time during the welding process.

[0147] During implementation, the welding process begins by controlling the stirrer to weld the general area according to the planned path and parameters based on the generated second repair plan. During the welding process, a sensor system collects real-time weld quality information, focusing on the connection between the general area and adjacent key areas. Real-time monitoring includes axial stress, transverse shear stress, plastic strain distribution, and temperature field data at the connection. The changing trends of these parameters are used to determine the weld condition of the connection.

[0148] On this basis, if the first welding requirement and / or the second welding requirement are not met, steps S102 to S105 are re-executed until the welding requirements are met.

[0149] The following are system embodiments of the present application, which can be used to implement the method embodiments of the present application. For details not disclosed in the system embodiments of the present application, please refer to the method embodiments of the present application.

[0150] See Figure 2, which shows a schematic diagram of the structure of a friction stir welding control system based on a welding analysis model provided by an exemplary embodiment of the present application. The system can be implemented as all or part of the system through software, hardware, or a combination of both. The friction stir welding control system based on the welding analysis model includes:

[0151] A feature extraction module is used to obtain a multimodal image of the crack area and extract the crack morphological features and crack structural features in the multimodal image;

[0152] The area division module is used to divide the crack area into key areas and general areas according to the crack morphological characteristics and crack structural characteristics;

[0153] A first execution module is used to generate a first repair plan of the friction stir welding method for the key area and control the stirring head to execute the first repair plan;

[0154] An analysis module is used to obtain image information of the crack area and welding information of the key area respectively, and input the image information and welding information into the welding analysis model to obtain crack extension information and welding quality information;

[0155] The second execution module is used to generate a second repair plan for the general area using the stir friction welding method when the crack extension information and the welding quality information both meet the preset welding requirements, and control the stirring head to execute the second repair plan.

[0156] On the basis of the above embodiments, as an optional embodiment, the area division module is also used to identify the main path and branch paths of the crack area based on the crack morphological characteristics; calculate the product of the crack width and crack depth of the main path according to the crack width characteristics and the crack depth characteristics, and determine the main path whose product is greater than a preset first threshold as the first key area; determine the surface curvature of the crack area based on the crack surface characteristics, and determine the second key area where the crack surface is in an arched state or a concave state according to the surface curvature; determine the first key area and the second key area as key areas, and divide the area in the crack area other than the key area into general areas.

[0157] Based on the above embodiments, as an optional embodiment, the first execution module is also used to obtain the material properties of the key area and determine the model parameters of the stirring head for welding using stir friction welding; determine the welding parameters of the stirring head according to the crack morphology characteristics and crack structure characteristics of the key area, and the welding parameters include rotation speed, travel speed, downward pressure depth and inclination angle; obtain the crack direction of the key area, and plan the welding path of the key area according to the crack direction; generate a first repair plan for the stir friction welding method of the key area according to the model parameters, welding parameters and welding path of the stirring head, and control the stirring head to execute the first repair plan.

[0158] Based on the above embodiment, as an optional embodiment, the first execution module is also used to obtain the physical structure of the workpiece in the crack area when there are multiple key areas; analyze the stress distribution in the crack area according to the physical structure of the workpiece, and determine the priority order of each key area in order of stress distribution from large to small.

[0159] Based on the above embodiment, as an optional embodiment, the analysis module is also used to obtain image information of the crack area after executing the first repair scheme; input the multimodal image and image information before welding into the crack analysis sub-model, detect whether new cracks are caused or the original cracks are extended during the welding process through image comparison, and generate crack extension information; collect welding information of key areas during the welding process in real time; input the welding information into the welding quality inspection sub-model, and generate welding quality information of key areas through process parameter matching analysis.

[0160] Based on the above embodiments, as an optional embodiment, the analysis module is also used to input axial stress, transverse shear stress, plastic strain distribution and temperature field data into the welding quality inspection sub-model; calculate the deviation value between the axial stress and the preset axial stress threshold value to generate an axial stress matching index; calculate the ratio of the transverse shear stress to the critical shear stress based on the material mechanical property parameters to generate a shear stress safety factor; analyze the spatial gradient characteristics of the plastic strain distribution and calculate the strain uniformity index, which is used to characterize the plastic deformation consistency of key areas; match the temperature field data with the standard welding temperature field distribution and calculate the temperature field similarity coefficient; and generate welding quality information of key areas based on the axial stress matching index, shear stress safety factor, strain uniformity index and temperature field similarity coefficient.

[0161] On the basis of the above embodiments, as an optional embodiment, the second execution module is also used to verify whether the welding of the key area suppresses crack extension based on the crack extension information, and when the crack extension length is less than the preset second threshold, it is determined that the first welding requirement is met; the welding quality information is compared with the corresponding preset third threshold to determine whether the welding quality information meets the second welding requirement; when the first welding requirement and the second welding requirement are met at the same time, the crack morphological characteristics and crack structural characteristics of the general area are extracted; the welding parameters of the stirring head are adjusted according to the crack characteristics of the general area to generate a second repair plan that is at least one strength level lower than the first repair plan; the stirring head is controlled to perform repair welding on the general area according to the second repair plan, and the welding quality information at the connection between the general area and the adjacent key area is monitored in real time during the welding process.

[0162] An embodiment of the present application also provides a computer storage medium, which can store multiple instructions. The instructions are suitable for being loaded and executed by a processor as the stir friction welding control method based on the welding analysis model in the above embodiment. The specific execution process can be found in the specific description of the embodiment and will not be repeated here.

[0163] See Figure 3 , is a schematic diagram of the structure of an electronic device provided in an embodiment of the present application. Figure 3 As shown, the electronic device 300 may include: at least one processor 301 , at least one network interface 304 , a user interface 303 , a memory 305 , and at least one communication bus 302 .

[0164] The communication bus 302 is used to implement the connection and communication between these components.

[0165] The user interface 303 may include a display screen (Display) and a camera (Camera).

[0166] The network interface 304 may optionally include a standard wired interface or a wireless interface (such as a WI-FI interface).

[0167] The processor 301 may include one or more processing cores. Using various interfaces and circuits, the processor 301 connects to various components within the server. It executes instructions, programs, code sets, or instruction sets stored in the memory 305, as well as accesses data stored in the memory 305, to perform various server functions and process data. Optionally, the processor 301 may be implemented using at least one of the following hardware forms: a digital signal processing (DSP), a field-programmable gate array (FPGA), or a programmable logic array (PLA). The processor 301 may integrate one or a combination of a central processing unit (CPU), a graphics processing unit (GPU), and a modem. The CPU primarily processes the operating system, user interface, and application programs; the GPU is responsible for rendering and drawing content displayed on the display screen; and the modem handles wireless communications. It is understood that the modem may not be integrated into the processor 301 but implemented as a separate chip.

[0168] Among them, the memory 305 may include a random access memory (RAM) or a read-only memory (Read-Only Memory). Optionally, the memory 305 includes a non-transitory computer-readable storage medium. The memory 305 can be used to store instructions, programs, codes, code sets or instruction sets. The memory 305 may include a program storage area and a data storage area, wherein the program storage area may store instructions for implementing an operating system, instructions for at least one function (such as a touch function, a sound playback function, an image playback function, etc.), instructions for implementing the above-mentioned various method embodiments, etc.; the data storage area may store data involved in the above-mentioned various method embodiments, etc. The memory 305 may also be optionally at least one storage device located away from the aforementioned processor 301. As Figure 3 As shown, the memory 305 as a computer storage medium may include an operating system, a network communication module, a user interface module, and an application program for a friction stir welding control method based on a welding analysis model.

[0169] exist Figure 3 In the electronic device 300 shown, the user interface 303 is mainly used to provide an input interface for the user and obtain data input by the user; and the processor 301 can be used to call an application program stored in the memory 305 for a stir friction welding control method based on a welding analysis model. When executed by one or more processors, the electronic device executes one or more methods in the above-mentioned embodiments.

[0170] An electronic device readable storage medium stores instructions, which, when executed by one or more processors, enable the electronic device to execute one or more methods in the above embodiments.

[0171] It should be noted that for the aforementioned method embodiments, for simplicity of description, they are all expressed as a series of action combinations, but those skilled in the art should be aware that this application is not limited by the order of the actions described, because according to this application, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also be aware that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily required for this application.

[0172] In the above embodiments, the description of each embodiment has its own focus. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0173] In the several embodiments provided in this application, it should be understood that the disclosed devices can be implemented in other ways. For example, the device embodiments described above are merely schematic, such as the division of units, which is only a logical function division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some service interface, and the indirect coupling or communication connection of devices or units can be electrical or other forms.

[0174] Units described as separate components may or may not be physically separate, and components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of these units may be selected to achieve the purpose of this embodiment according to actual needs.

[0175] In addition, the functional units in the various embodiments of the present application may be integrated into a single processing unit, or each unit may exist physically separately, or two or more units may be integrated into a single unit. The aforementioned integrated units may be implemented in the form of hardware or software functional units.

[0176] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable memory. Based on this understanding, the technical solution of this application, or the portion that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a memory and includes several instructions for causing a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the various embodiments of the method of this application. The aforementioned memory includes various media that can store program code, such as USB flash drives, mobile hard drives, magnetic disks, or optical disks.

[0177] The above are merely exemplary embodiments of the present disclosure and are not intended to limit the scope of the present disclosure. That is, any equivalent changes and modifications made in accordance with the teachings of the present disclosure are still within the scope of the present disclosure. After considering the disclosure of the specification and the truth of practice, those skilled in the art will easily think of other embodiments of the present disclosure. This application is intended to cover any variations, uses or adaptive changes of the present disclosure, which follow the general principles of the present disclosure and include common knowledge or customary technical means in the field of the present disclosure that are not recorded in the present disclosure.

Claims

1. A friction stir welding control method based on a welding analysis model, characterized in that: The method comprises: Acquire a multimodal image of the crack area, and extract crack morphological features and crack structural features from the multimodal image; Dividing the crack area into a key area and a general area according to the crack morphological characteristics and crack structural characteristics; generating a first repair plan for the friction stir welding method of the key area, and controlling the stirring head to execute the first repair plan; Respectively acquiring image information of the crack region and welding information of the key region, and inputting the image information and welding information into a welding analysis model to obtain crack extension information and welding quality information; The welding analysis model includes a crack analysis sub-model and a welding quality inspection sub-model. The image information of the crack area and the welding information of the key area are respectively obtained, and the image information and the welding information are input into the welding analysis model to obtain crack extension information and welding quality information, including: Obtaining image information of the crack area after executing the first repair solution; inputting the multimodal image before welding and the image information into the crack analysis sub-model, detecting whether new cracks are induced or existing cracks extend during the welding process through image comparison, and generating crack extension information; collecting welding information of the key area during the welding process in real time; inputting the welding information into the welding quality inspection sub-model, and generating welding quality information of the key area through process parameter matching analysis; The welding information includes axial stress, transverse shear stress, plastic strain distribution and temperature field data. The welding information is input into the welding quality inspection sub-model, and welding quality information is generated through process parameter matching analysis, including: The axial stress, the transverse shear stress, the plastic strain distribution and the temperature field data are input into the welding quality inspection sub-model; the deviation value between the axial stress and the preset axial stress threshold is calculated to generate an axial stress matching index; the ratio of the transverse shear stress to the critical shear stress is calculated based on the material mechanical property parameters to generate a shear stress safety factor; the spatial gradient characteristics of the plastic strain distribution are analyzed to calculate the strain uniformity index, which is used to characterize the plastic deformation consistency of the key area; the temperature field data is matched with the standard welding temperature field distribution to calculate the temperature field similarity coefficient; based on the axial stress matching index, the shear stress safety factor, the strain uniformity index and the temperature field similarity coefficient, the welding quality information of the key area is generated; When both the crack extension information and the welding quality information meet the preset welding requirements, a second repair scheme of the friction stir welding method for the general area is generated, and the stirring head is controlled to execute the second repair scheme.

2. The method according to claim 1, characterized in that The crack morphological characteristics include crack shape characteristics and crack width characteristics, and the crack structural characteristics include crack depth characteristics and crack surface characteristics. The crack area is divided into key areas and general areas according to the crack morphological characteristics and crack structural characteristics, including: Based on the crack morphological characteristics, identifying the main path and branch paths of the crack area; Calculating the product of the crack width and the crack depth of the trunk path according to the crack width feature and the crack depth feature, and determining the trunk path where the product is greater than a preset first threshold as a first key area; Determining a surface curvature of the crack region based on the crack surface features, and determining a second key region where the crack surface is in an arched state or a concave state according to the surface curvature; The first key area and the second key area are determined as key areas, and areas other than the key areas in the crack area are divided into general areas.

3. The method according to claim 1, characterized in that Generating a first repair scheme of the friction stir welding method for the key area and controlling the stirring head to execute the first repair scheme includes: Obtaining material properties of the key area and determining model parameters of a stirring head for friction stir welding; Determining welding parameters of the stirring head according to the crack morphology and crack structure characteristics of the key area, wherein the welding parameters include rotation speed, travel speed, pressing depth and tilt angle; Obtaining the crack direction of the key area, and planning the welding path of the key area according to the crack direction; A first repair scheme for the friction stir welding method of the key area is generated according to the model parameters of the stirring head, the welding parameters and the welding path, and the stirring head is controlled to execute the first repair scheme.

4. The method according to claim 1 or 3, characterized in that Before generating a first repair scheme of the friction stir welding method for the key area and controlling the stirring head to execute the first repair scheme, the method further includes: When there are multiple key areas, obtaining the physical structure of the workpiece in the crack area; The stress distribution of the crack area is analyzed according to the physical structure of the workpiece, and the priority order of each key area is determined according to the order of the stress distribution from large to small.

5. The method according to claim 1, wherein The preset welding requirements include a first welding requirement and a second welding requirement. When the crack extension information and the welding quality information both meet the preset welding requirements, a second repair scheme of the friction stir welding method for the general area is generated, and the stirring head is controlled to execute the second repair scheme, including: Verifying whether the welding of the key area suppresses crack extension based on the crack extension information, and determining that the first welding requirement is met when the crack extension length is less than a preset second threshold; Comparing the welding quality information with a corresponding preset third threshold to determine whether the welding quality information meets a second welding requirement; When the first welding requirement and the second welding requirement are simultaneously met, extracting crack morphological characteristics and crack structural characteristics of the general area; adjusting the welding parameters of the stirring head according to the crack characteristics of the general area to generate a second repair solution that is at least one strength grade lower than the first repair solution; According to the second repair scheme, the stirring head is controlled to perform repair welding on the general area, and the welding quality information of the connection between the general area and the adjacent key area is monitored in real time during the welding process.

6. A friction stir welding control system based on a welding analysis model, characterized in that: The system comprises: A feature extraction module, configured to obtain a multimodal image of the crack region and extract crack morphological features and crack structural features from the multimodal image; A region division module, configured to divide the crack region into a key region and a general region according to the crack morphological characteristics and crack structural characteristics; A first execution module is used to generate a first repair plan of the friction stir welding method for the key area and control the stirring head to execute the first repair plan; An analysis module is used to respectively obtain the image information of the crack area and the welding information of the key area, and input the image information and the welding information into a welding analysis model to obtain crack extension information and welding quality information; the welding analysis model includes a crack analysis sub-model and a welding quality inspection sub-model, and the image information of the crack area and the welding information of the key area are respectively obtained, and the image information and the welding information are input into the welding analysis model to obtain crack extension information and welding quality information, including: obtaining the image information of the crack area after executing the first repair scheme; inputting the multimodal image before welding and the image information into the crack analysis sub-model, detecting whether new cracks are caused or the original cracks are extended during the welding process by image comparison, and generating crack extension information; real-time acquisition of the welding information of the key area during the welding process; inputting the welding information into the welding quality inspection sub-model, and generating the welding quality information of the key area by process parameter matching analysis; the welding The information includes axial stress, transverse shear stress, plastic strain distribution and temperature field data. The welding information is input into the welding quality inspection sub-model, and welding quality information is generated through process parameter matching analysis, including: inputting the axial stress, the transverse shear stress, the plastic strain distribution and the temperature field data into the welding quality inspection sub-model; calculating the deviation value between the axial stress and the preset axial stress threshold value to generate an axial stress matching index; calculating the ratio of the transverse shear stress to the critical shear stress based on the material mechanical property parameters to generate a shear stress safety factor; analyzing the spatial gradient characteristics of the plastic strain distribution and calculating the strain uniformity index, which is used to characterize the plastic deformation consistency of the key area; matching the temperature field data with the standard welding temperature field distribution to calculate the temperature field similarity coefficient; generating the welding quality information of the key area based on the axial stress matching index, the shear stress safety factor, the strain uniformity index and the temperature field similarity coefficient; The second execution module is used to generate a second repair plan of the stir friction welding method for the general area when the crack extension information and the welding quality information both meet the preset welding requirements, and control the stirring head to execute the second repair plan.

7. A computer storage medium, characterized in that The computer storage medium stores a plurality of instructions, and the instructions are suitable for being loaded by a processor and executing the method according to any one of claims 1 to 5.

8. An electronic device, characterized in that: The electronic device comprises a processor, a memory and a transceiver, wherein the memory is used to store instructions, the transceiver is used to communicate with other devices, and the processor is used to execute the instructions stored in the memory so that the electronic device executes the method according to any one of claims 1 to 5.

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