Welding part design method and system for welding multi-section target material

Abstract

The invention belongs to the technical field of intelligent welding, and discloses a welding part design method and system for welding a multi-section target material, and the method comprises the steps: scanning the multi-section target material through laser scanning and visible light imaging equipment, and obtaining the assembly three-dimensional shape of the multi-section target material; identifying a welding seam area based on the assembly three-dimensional shape, and extracting geometric deviation characteristics of the welding seam area; on the basis of the geometric deviation characteristics of the weld joint area and the thermal expansion characteristics of the welding material, according to a preset groove design rule, dynamically-matched groove design parameters are generated; the method comprises the steps that thermal infrared image data and strain field data in the welding process are collected, a thermal-mechanical coupling welding process simulation model is constructed, strain concentration and residual stress distribution of a heat affected zone in the welding process are analyzed, the strain concentration area distribution characteristics of the heat affected zone are obtained, and then a welding seam path with a fractal structure is constructed; and the overall quality and performance of the welding part of the multi-section target material are improved.

Description

Technical Field

[0001] The present invention relates to the field of intelligent welding technology. More specifically, the present invention relates to a welding part design method and system for multi-segment target welding. Background Art

[0002] With the rapid development of high-tech industries such as semiconductors, flat panel displays, and solar photovoltaics, multi-segment targets are usually spliced and welded by target segments of different materials and functions, and have been widely used due to their flexible material combinations and high deposition performance. In the manufacturing process of multi-segment targets, the welding process is a key link to ensure the performance of the target. The design of the welding part directly affects the overall structural strength, electrical conductivity, thermal stability, and film deposition uniformity of the target.

[0003] The traditional welding part design methods and systems for multi-segment targets have the following main problems:

[0004] Traditional welding part design methods often rely on experience and simple mechanical analysis, lacking systematicness and accuracy. This design method is difficult to fully consider the complex stress distribution, heat conduction characteristics, and physical and chemical compatibility between different materials during the use of the target, and is prone to problems such as stress concentration, insufficient interface bonding strength, and mismatched thermal expansion coefficients at the welding part, which may lead to target cracking and peeling, affecting the film deposition quality and the normal operation of the equipment, and increasing production and maintenance costs.

[0005] In addition, with the continuous increase in the size and the increasing complexity of the structure of the target, the traditional design methods can no longer meet the manufacturing requirements of high-precision and high-performance targets. At the same time, the existing welding part design lacks effective digital simulation and optimization means, and it is difficult to accurately predict the performance of the welding part at the design stage, resulting in a long design cycle and high test costs, and unable to quickly respond to the market demand for new targets.

[0006] In view of this, the present invention proposes a welding part design method and system for multi-segment target welding to solve the above problems. Summary of the Invention

[0007] To overcome the above defects of the prior art and to achieve the above object, the present invention provides the following technical solution: A welding part design method for multi-segment target welding, comprising:

[0008] S1. Scanning the multi-segment target through a laser scanning and visible light imaging device to obtain the assembled three-dimensional topography of the multi-segment target; identifying the weld area based on the assembled three-dimensional topography, and extracting the geometric deviation features of the weld area;

[0009] S2. Based on the geometric deviation characteristics of the weld area and the thermal expansion characteristics of the welding material, generate dynamically adapted groove design parameters according to the preset groove design rules;

[0010] S3. Collect the thermal infrared image data and strain field data during the welding process, construct a thermo-mechanical coupled welding process simulation model, analyze the strain concentration and residual stress distribution in the heat-affected zone during the welding process, obtain the distribution characteristics of the strain concentration area in the heat-affected zone, and then construct a weld path with a fractal structure;

[0011] S4. Based on scanning electron microscopy and electron backscatter diffraction, and combined with a cross-scale image fusion method, analyze the microstructure and element diffusion characteristics of the welding joint interface area, and obtain the pore distribution, ripple amplitude spectrum and element diffusion curve of the joint interface area;

[0012] S5. Design a gradient transition layer structure for the welding interface according to the pore distribution, ripple amplitude spectrum and element diffusion curve of the joint interface area, and perform continuous transition of the welding interface performance;

[0013] S6. Generate a welding part design scheme for multi-segment target welding according to the dynamically adapted groove design parameters, the weld path with a fractal structure and the gradient transition layer structure of the welding interface.

[0014] Preferably, the method for obtaining the assembled three-dimensional morphology of the multi-segment target includes:

[0015] Adopt the principle of line laser triangulation, select a laser scanning device, and equip it with a visible light imaging device; install the multi-segment target on a clamping platform with stable support and multi-axis motion control, and use the laser scanning device and the visible light imaging device to scan the multi-segment target;

[0016] Preset the scanning path according to the geometric shape of the multi-segment target, control the laser scanning device to emit a line laser beam along the preset scanning path, perform point-by-point scanning on the surface of the target, and obtain the point cloud data of the complete shape of the target by receiving the reflected light; while laser scanning, use the visible light imaging device to synchronously capture the surface texture image of the target, and each frame of the image is attached with a timestamp and a spatial coordinate label consistent with the laser scanning device;

[0017] Through the iterative closest point ICP algorithm, splice and align the point cloud data in each direction to the camera coordinate system; map the RGB values of the target surface texture image to the corresponding point cloud data through nearest neighbor interpolation, and then generate the assembled three-dimensional morphology of the multi-segment target.

[0018] Preferably, the method for extracting the geometric deviation characteristics of the weld area includes:

[0019] By solving the local neighborhood covariance matrix, the normal vectors of all points in the point cloud data of the complete shape of the target are obtained; the regions with abrupt changes in the normal vectors are extracted, and the candidate weld regions are located by combining a preset point cloud height difference threshold;

[0020] Perform Canny edge detection on the surface texture map of the target collected synchronously, extract the contour lines with abrupt changes in gray-scale gradient composed of two-dimensional edge points, and perform image-point cloud coordinate mapping on the contour lines through the time stamps and spatial coordinate tags attached to each frame of the image, and back-project the two-dimensional edge points into the three-dimensional point cloud space, so as to obtain the three-dimensional candidate weld edge point set;

[0021] Region growing and morphological filtering: Combine the points in the candidate weld region and the three-dimensional candidate weld edge point set to form a seed point set; Perform region clustering growth based on the spatial proximity and normal vector angle between point clouds, gradually expand the weld region, and at the same time use morphological opening operation to remove noise points and close small gaps, and finally form the weld region point cloud set;

[0022] Analyze the main direction of the weld in the weld region point cloud set, preset an ideal welding path based on the standard process specifications, calculate the deviation amount between the main direction of the weld in the weld region point cloud set and the preset ideal welding path point by point, and then obtain the geometric deviation characteristics of the weld region.

[0023] Preferably, the method for obtaining the groove design parameters includes:

[0024] Based on the material of the target welding material, query and obtain the corresponding thermal expansion coefficient and thermal conductivity, combine the welding heat input and process parameters, conduct thermal-structural response analysis and modeling, and predict the post-welding shrinkage deformation, residual stress and structural warping trend; According to the preset groove design rules, combine the post-welding shrinkage deformation, residual stress and structural warping trend, and form a joint feature vector with the geometric deviation characteristics based on the weld region, and match it in the preset groove design rules to dynamically generate the adapted groove design parameters.

[0025] Preferably, the method for constructing the thermal-mechanical coupling welding process simulation model includes: Based on the heat conduction theory and the elastic-plastic mechanics theory, construct the heat conduction equation and the mechanical equation, and then obtain the thermal-mechanical coupling model; Use the thermal-mechanical coupling model to simulate the temperature field and strain field during the welding process.

[0026] Preferably, the method for constructing the weld path with a fractal structure includes:

[0027] Real-time obtain a sequence of temperature distribution maps of the heat-affected zone during the welding process through a thermal infrared camera to obtain thermal infrared image data; through a distributed optical fiber strain sensing system, arrange monitoring points in the weld area of the point cloud set in the weld area to dynamically capture the three-dimensional strain distribution during the welding process, form a strain tensor field, and obtain strain field data;

[0028] Perform geometric modeling and mesh division on the assembled three-dimensional topography, and use the finite element method based on the thermo-mechanical coupling model to perform thermo-mechanical coupling simulation of the welding process; obtain the temperature field by solving the heat conduction equation, input the temperature field as a load into the mechanical equation to solve the stress field, and obtain the distribution characteristics of the strain concentration area in the heat-affected zone by analyzing the strain concentration and residual stress distribution under the temperature field;

[0029] Extract the maximum principal strain distribution in the distribution characteristics of the strain concentration area in the heat-affected zone, use the threshold segmentation method to identify the strain concentration area, and generate a continuous high-strain area; use the SIMP method to perform topology optimization modeling, take minimizing the strain energy density per unit volume of the structure as the objective function, and construct the fractal structure of the weld path; discretize the fractal structure of the weld path into the gun movement path points, and then obtain the weld path with a fractal structure.

[0030] Preferably, the method for obtaining the pore distribution, ripple amplitude spectrum, and element diffusion curve of the joint interface area includes:

[0031] Intercept and perform surface preparation on the joint interface area of the multi-segment target weld, and the surface preparation includes grinding, polishing, and ion beam removal of the surface deformation layer; use a scanning electron microscope to obtain secondary electron images and backscattered electron images at different scales of the joint interface area of the weld; equip an EBSD probe on the scanning electron microscope platform to perform crystallographic orientation analysis on the joint interface area of the weld to obtain the grain orientation distribution map of this area;

[0032] Adopt an image stitching and multi-scale enhancement algorithm to construct a panoramic view of the joint interface of the weld including micro-scale and nano-scale structure information, and identify the pore area of the panoramic view of the joint interface of the weld to obtain the pore distribution of the joint interface area;

[0033] Perform boundary tracking and extraction on the ripple contour in the panoramic view of the joint interface of the weld, and obtain the ripple amplitude spectrum through Fourier transform analysis; use spectral analysis technology to set cross-sectional scanning paths and surface scanning areas on both sides of the multi-segment target weld interface to obtain the spatial distribution data of different metal elements in the joint interface area of the weld, and generate an element diffusion curve of the element concentration changing with the spatial position based on the spatial distribution data.

[0034] Preferably, the method for designing the gradient transition layer structure of the welding interface includes:

[0035] Based on the pore distribution data identified in the joint interface region, identify the distribution density and size of the pores, design buffer beads, and improve the filling density of the pore distribution region through material remelting and interlayer interleaving to obtain a pore density field; arrange micro-concave / gently sloping corrugated structures in the region of sudden change in the fluctuation frequency of the corrugation amplitude spectrum to release the thermal stress along the direction of the structural morphology and obtain a corrugated morphology field; design the M-layer alloy combination according to the slope of the element diffusion curve, with the material composition of each layer changing gradually to obtain a composition concentration field; adopt a parameter field driving model based on neural network to fuse the pore density field, corrugated morphology field, and composition concentration field to generate a three-dimensional gradient transition structure map and obtain the welded interface gradient transition layer structure.

[0036] Preferably, the method for generating a welding part design scheme for multi-segment target welding includes:

[0037] Generate a welding part design scheme for multi-segment target welding according to the dynamically adapted groove design parameters, the weld path with a fractal structure, and the welded interface gradient transition layer structure;

[0038] Based on the dynamically adapted groove design parameters, the weld path with a fractal structure, and the welded interface gradient transition layer structure, establish a structured welding part model through 3D CAD software; use the numerical control programming interface to convert the structured welding part model into an instruction set recognizable by the welding robot, thereby forming a digital design scheme for the welding part used in multi-segment target welding.

[0039] A welding part design system for multi-segment target welding includes:

[0040] A three-dimensional morphology acquisition module scans the multi-segment target through a laser scanning and visible light imaging device to obtain the assembled three-dimensional morphology of the multi-segment target; identify the weld region based on the assembled three-dimensional morphology and extract the geometric deviation characteristics of the weld region;

[0041] A groove parameter generation module generates dynamically adapted groove design parameters based on the geometric deviation characteristics of the weld region and the thermal expansion characteristics of the welding material according to the preset groove design rules;

[0042] A weld path generation module collects the thermal infrared image data and strain field data during the welding process, constructs a thermal-mechanical coupling welding process simulation model, obtains the distribution characteristics of the strain concentration region in the heat-affected zone by analyzing the strain concentration and residual stress distribution in the heat-affected zone during the welding process, and then constructs a weld path with a fractal structure;

[0043] A microstructure analysis module analyzes the microstructure and element diffusion characteristics of the welding joint interface region based on a scanning electron microscope and electron backscatter diffraction, and in combination with a cross-scale image fusion method, to obtain the pore distribution, corrugation amplitude spectrum, and element diffusion curve in the joint interface region;

[0044] The interface structure design module designs the gradient transition layer structure of the welding interface according to the pore distribution, ripple amplitude spectrum and element diffusion curve in the joint interface area, and conducts continuous transition of the welding interface performance; the welding scheme integration module generates a welding part design scheme for multi-segment target welding according to the dynamically adapted groove design parameters, the weld path of the fractal structure and the gradient transition layer structure of the welding interface.

[0045] The technical effects and advantages of a welding part design method and system for multi-segment targets of the present invention:

[0046] By means of two methods, namely, the preliminary screening of the weld candidate area and the edge enhancement of the texture image, the weld is located from two dimensions of point cloud data and texture image. These two methods complement each other, improving the accuracy and reliability of weld positioning;

[0047] Based on the heat conduction theory and the elastic-plastic mechanics theory, a thermal-mechanical coupling model is constructed. By solving the heat conduction equation and the mechanical equation, the temperature field and stress field distributions in the heat affected zone during the welding process can be accurately simulated, which helps to predict in advance the magnitude and distribution of the residual stress and the deformation condition of the structure after welding, providing a theoretical basis for the optimization of the welding process;

[0048] By simulating the welding process under different parameters through the thermal-mechanical coupling model and analyzing the changes in the temperature field and stress field, the optimal welding process parameters can be found, reducing the occurrence probability of welding defects, improving the process stability and the qualified rate of finished products; this model has good simulation efficiency and engineering adaptability, can support the simulation analysis of working conditions such as multi-pass welding and multi-layer welding of complex components, provide an online prediction and feedback control basis for the intelligent welding system, enhance the automation and intelligence capabilities of the system, and improve the welding quality and efficiency;

[0049] Adopting a weld path design method based on actual welding process data and simulation analysis can optimize the weld path, reduce stress concentration during welding, and improve welding quality; by reasonably designing the gradient transition layer structure of the welding interface, the stress concentration at the welding joint interface is effectively alleviated, interface defects are reduced, and the strength, toughness, corrosion resistance and other properties of the welding joint are improved, extending the service life of the welded structure;

[0050] The gradient transition layer structure can make the combination between different materials closer, reduce problems such as uneven element diffusion at the interface, thereby improving welding quality and ensuring the reliability of the welded structure under complex working conditions; it can quickly and accurately generate a digital design scheme for the welding part that meets the actual requirements, reducing the time and error of manual design, and improving the design efficiency and quality. Description of the Drawings

[0051] Figure 1Schematic flow chart of a welding part design method for a multi - segment target material welding of the present invention;

[0052] Figure 2 Schematic structural diagram of a welding part design system for a multi - segment target material welding of the present invention;

[0053] Figure 3 Schematic flow chart of a method for obtaining groove design parameters provided by the present invention. Specific implementation manners

[0054] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0055] Embodiment 1

[0056] Please refer to Figure 1 and Figure 3 As shown, this Embodiment 1 further illustrates a welding part design method for a multi - segment target material welding proposed by the present invention. This design can be applied to the modular design of converting large / heavy metal target materials that are difficult to transport into segment - transportable ones: Due to limitations in size, weight, or special shape, large or heavy metal target materials are often difficult to transport as a whole. Therefore, they need to be disassembled into multiple metal components (multi - segment target materials) and then welded and assembled after arriving at the destination. A welding part design method for a multi - segment target material welding proposed by the present invention can effectively solve the welding problems in such scenarios and ensure that the performance of the spliced target material can meet the standards of an integral target material.

[0057] In the context of the semiconductor chip manufacturing process accuracy moving towards more advanced nodes, flat panel displays developing towards ultra - high - definition resolutions, and solar photovoltaics pursuing higher photoelectric conversion efficiencies, multi - segment target materials have become key basic materials in high - tech industries due to their flexible material combinations and high - efficiency thin - film deposition performance. This special structure composed of spliced and welded target material segments of different materials and functions has greatly improved the industrial production efficiency and reduced production costs.

[0058] However, in the manufacturing process of multi-segment target materials, the welding process has become the core bottleneck restricting their performance. The design quality of the welded part directly determines the overall structural strength, electrical and thermal conductivity, and film deposition uniformity of the target material, and plays a decisive role in the yield of downstream products and the operation stability of equipment. Traditional welded part design relies on experience accumulation and simple mechanical calculations, lacking systematic theoretical support and accurate quantitative analysis models. This extensive design mode is difficult to cope with the complex working conditions during the service of the target material, such as the high-frequency alternating electric field in semiconductor sputtering and the high-temperature and high-vacuum environment in flat panel display coating, resulting in the inability to comprehensively consider key factors such as stress distribution, heat conduction characteristics, and physical and chemical compatibility between materials.

[0059] This has given rise to a series of serious problems: stress concentration in the welded part causes microcracks in the target material under cyclic thermal stress, eventually leading to structural cracking; insufficient interface bonding strength causes the target material to fall off under high-speed ion bombardment, contaminating the coating equipment and reducing the film quality; mismatched thermal expansion coefficients cause permanent deformation at the weld, damaging the flatness of the target material. These problems not only significantly increase production and maintenance costs, but also severely restrict production capacity improvement due to frequent shutdowns for maintenance.

[0060] At the same time, the development of the industry has promoted the evolution of target materials towards larger sizes and more complex structures, and the limitations of traditional design methods in terms of accuracy and efficiency have become increasingly prominent. Due to the lack of effective support from digital means such as finite element analysis and molecular dynamics simulation, it is difficult to accurately predict the mechanical, thermal, and chemical properties of the welded part during the design stage, resulting in repeated trial and correction, a long design cycle, and high R & D costs, and being unable to quickly respond to the urgent market demand for new high-performance target materials. Therefore, constructing a scientific and systematic design method and supporting system for the welded part of multi-segment target materials has become a key task to break through the technical bottleneck of industrial development and ensure the performance reliability of target materials.

[0061] In order to effectively solve the above problems, the present invention proposes a design method for the welded part of multi-segment target materials, including:

[0062] S1. Scanning the multi-segment target material through a laser scanning and visible light imaging device to obtain the assembled three-dimensional topography of the multi-segment target material; identifying the weld area based on the assembled three-dimensional topography and extracting the geometric deviation characteristics of the weld area;

[0063] S2. Based on the geometric deviation characteristics of the weld area and the thermal expansion characteristics of the welding material, generating dynamically adapted groove design parameters according to the preset groove design rules;

[0064] S3. Collect the thermal infrared image data and strain field data during the welding process, construct a simulation model of the thermo-mechanical coupling welding process, analyze the strain concentration and residual stress distribution in the heat-affected zone during the welding process, obtain the distribution characteristics of the strain concentration area in the heat-affected zone, and then construct a weld path with a fractal structure;

[0065] S4. Based on the scanning electron microscope and electron backscatter diffraction, and combined with the cross-scale image fusion method, analyze the microstructure and element diffusion characteristics in the interface area of the welded joint, and obtain the pore distribution, ripple amplitude spectrum and element diffusion curve in the joint interface area;

[0066] S5. According to the pore distribution, ripple amplitude spectrum and element diffusion curve in the joint interface area, design the structure of the welding interface gradient transition layer to achieve continuous transition of the welding interface performance;

[0067] S6. According to the dynamically adapted groove design parameters, the weld path with a fractal structure and the welding interface gradient transition layer structure, generate a welding part design scheme for multi-segment target welding.

[0068] The method for obtaining the three-dimensional assembly topography of the multi-segment target includes:

[0069] Adopt the principle of line laser triangulation, select a laser scanning device (such as laser triangulation or structured light), and be equipped with a visible light imaging device (such as an industrial camera); install the multi-segment target on a clamping platform with stable support and multi-axis motion control to ensure the stability and repeat positioning accuracy of the target during scanning, and use the laser scanning device and the visible light imaging device to scan the multi-segment target;

[0070] Preset a spiral or grid scanning path according to the geometric shape (cylindrical / irregular) of the multi-segment target to ensure that the overlap rate of adjacent scanning areas is ≥30%, control the laser scanning device to emit a line laser beam along the preset scanning path, scan the target surface point by point, and obtain the point cloud data of the complete target shape by receiving the reflected light; while laser scanning, use the visible light imaging device to synchronously capture the surface texture image of the target, and each frame of the image is attached with a timestamp and a spatial coordinate label consistent with the laser scanning device to assist in identifying surface detail features such as weld edges, contour lines, positioning holes and assembly errors;

[0071] Through the iterative closest point ICP algorithm, splice and align the point cloud data in each direction to the camera coordinate system; map the RGB values of the target surface texture image to the corresponding point cloud data through nearest neighbor interpolation, and then generate the three-dimensional assembly topography of the multi-segment target.

[0072] The method for extracting the geometric deviation characteristics of the weld area includes:

[0073] Initial screening of weld candidate regions: By solving the local neighborhood covariance matrix, the normal vectors of all points in the point cloud data of the complete shape of the target material are obtained; a covariance matrix is constructed for the k-neighborhood point cloud of each point, and the eigenvector corresponding to the minimum eigenvalue is the normal vector; the region with abrupt change of normal vectors is extracted (there is usually a sharp change in normal vectors at the weld edge), and the weld candidate region is located in combination with a preset point cloud height difference threshold (such as the height difference between adjacent point clouds > 0.5 mm);

[0074] Since the weld edge is the joint of segmented target materials, there is usually an abrupt change in the surface topography (such as protrusion, depression or dislocation), resulting in a sharp change in the direction of the normal vector (the included angle of the normal vectors > 30°). At the same time, the height difference between the weld region and the target materials on both sides is significant (the height difference between adjacent point clouds > 0.5 mm, and the height difference direction is perpendicular to the reference plane of the target material). Combining these two features, the weld candidate region can be initially located, that is, the continuous region in the point cloud where the normal vector changes abruptly and the height difference exceeds the threshold, which is manifested as an "abnormal band" in the point cloud.

[0075] Edge enhancement of texture image: Perform Canny edge detection on the texture map of the target material surface collected synchronously, and extract the contour line with abrupt change of gray gradient composed of two-dimensional edge points. The weld edge appears as a clear step edge in the visual image, such as the bright-dark boundary or the oxidation color boundary of the metal target material. Through the timestamp and spatial coordinate tags attached to each frame of the image, the contour line is mapped from image coordinates to point cloud coordinates, and the two-dimensional edge points are back-projected into the three-dimensional point cloud space, so as to obtain the three-dimensional candidate weld edge point set, which accurately corresponds to the physical edge of the weld in the three-dimensional space, such as the boundary line between the weld and the base material;

[0076] Region growing and morphological filtering: The points in the weld candidate region and the three-dimensional candidate weld edge point set are merged to form a seed point set. These seed points cover both the macroscopic abnormal region at the point cloud level and the microscopic edge features at the image level, ensuring the comprehensiveness and accuracy of the seed points; Based on the spatial proximity and the included angle of the normal vectors between the point clouds, region clustering growth is carried out to gradually expand the weld region. At the same time, morphological opening operation (such as a spherical structuring element with a radius of 2 mm) is used to remove noise points and close small gaps, and finally a closed and coherent weld region point cloud set is formed;

[0077] Analyze the main trend of the weld in the weld region point cloud set, preset an ideal welding path based on the standard process specifications, calculate the deviation between the main trend of the weld in the weld region point cloud set and the preset ideal welding path point by point, and then obtain the geometric deviation characteristics of the weld region.

[0078] The deviation amount includes the normal deviation (the distance perpendicular to the preset ideal welding path) and the tangential deviation (the offset along the weld seam direction). After calculating the deviation amount, further statistics are carried out and the extreme value of the deviation amount, the average deviation amount of all deviation points and the standard deviation amount are output, and they are integrated with the deviation amount of each point to obtain the final geometric deviation characteristics.

[0079] Region clustering growth: First, create an empty weld region point cloud set to store the final weld region point cloud; select an unvisited seed point from the seed point set, mark the selected seed point as visited, and add it to the weld region point cloud set; search for neighborhood points in the point cloud data of the complete outer shape of the entire target material whose neighborhood radius with the marked seed point is less than 1 mm (to ensure the compactness of the weld region), and calculate the normal vector angle between each neighborhood point and the marked seed point; retain the neighborhood points with a normal vector angle less than fifteen degrees, mark them as visited, and add them to the seed point set and the weld region point cloud set. Repeat the above steps until all seed points in the seed point set have been visited. At this time, the expanded weld region point cloud set is obtained, which includes the weld body and its adjacent transition region;

[0080] Example illustration:

[0081] Suppose there are 100 seed points in the seed point set S. At the initial stage of region growth, select the first unvisited seed point p1, mark it as visited and add it to the weld region point cloud set W. Then, based on p1, search for its neighborhood points in the point cloud data of the complete outer shape of the entire target material. If there are points that meet the two constraint conditions of spatial proximity and normal vector angle among the neighborhood points, add these neighborhood points to the sets S and W; if the neighborhood points do not meet the conditions, do not include them. In subsequent iterations, continue to select unvisited seed points from the set S and repeat the above operations until all points in the set S have been visited; the finally obtained set W is the weld region point cloud set determined after screening and expansion.

[0082] The method for obtaining the groove design parameters includes:

[0083] Based on the material of the target welding material, query and obtain the corresponding coefficient of thermal expansion and thermal conductivity, combine the welding heat input and process parameters, conduct thermal-structural response analysis and modeling, and predict the shrinkage deformation, residual stress and structural warping trend after welding; according to the preset groove design rules, combine the shrinkage deformation, residual stress and structural warping trend after welding with the geometric deviation characteristics based on the weld region to form a joint feature vector, and match it in the preset groove design rules to dynamically generate the adapted groove design parameters.

[0084] The combined feature vectors are analyzed using a generator network to output samples of groove design parameters. The discriminator network matches and discriminates the samples of groove design parameters against the preset groove design rules. Through cyclic generation and adversarial training, the samples of groove design parameters are continuously updated until suitable groove design parameters are obtained. The groove design parameters include groove angle, root face width, gap compensation value, symmetry factor, and estimated penetration parameters.

[0085] The coefficient of thermal expansion reflects the degree of expansion or contraction of a material when the temperature changes, and the thermal conductivity affects the heat transfer during the welding process. Different welding materials have different thermal expansion characteristics, which have an important impact on groove design. According to the welding process requirements, the characteristics of the target material, the welding quality standards, and past welding experience, preset groove design rules are formulated. The rules usually specify the value ranges and adjustment methods of parameters such as groove angle, groove depth, root face size, and root gap under different conditions.

[0086] The construction method of the thermo-mechanical coupled welding process simulation model includes: based on the heat conduction theory and the elastoplastic mechanics theory, constructing the heat conduction equation and the mechanical equation, and then obtaining the thermo-mechanical coupled model; using the thermo-mechanical coupled model to simulate the temperature field and strain field during the welding process.

[0087] Heat conduction equation: Among them, ρ is the density of the multi-segment target material; c is the specific heat capacity of the multi-segment target material; is the partial derivative of temperature with respect to time, the rate of change of temperature with time; T is the temperature; t is the time; is the Nabla operator, representing the vector differential operator; k is the thermal conductivity of the multi-segment target material; is the temperature gradient, the rate of change of temperature in space; Q is the welding heat input;

[0088] represents the net heat outflow rate due to heat conduction per unit volume, which describes the process of heat diffusion in space through conduction and is the core term of the heat conduction equation, determining the way the temperature field evolves over time; represents the heat flowing out of this point, resulting in a local temperature decrease; represents the heat flowing into this point, resulting in a local temperature increase;

[0089] The mechanical equation is: Among them, is the divergence of the stress tensor, describing the non-uniform distribution of stress in space; σ is the stress tensor; F is the body force, the external force acting on the unit volume (such as gravity, inertial force); D ep is the elastoplastic constitutive matrix, describing the stress-strain relationship of the material in the elastoplastic deformation stage; ε is the strain tensor, a measure of the degree of material deformation; Dep : ε is the product of the elastoplastic constitutive matrix and the strain tensor.

[0090] Through the thermo-mechanical coupling model, the temperature field and stress field distributions in the heat-affected zone during the welding process can be accurately simulated, which helps to predict in advance the magnitude and distribution of the residual stress and the deformation of the structure after welding, facilitating early compensation. At the same time, the thermo-mechanical coupling model can be used to optimize the design of welding process parameters, reduce the occurrence probability of welding defects, improve process stability and the qualified rate of finished products. In addition, the thermo-mechanical coupling model has good simulation efficiency and engineering adaptability, can support the simulation analysis of working conditions such as multi-pass welding and multi-layer welding of complex components, provide the basis for online prediction and feedback control for intelligent welding systems, and enhance the automation and intelligent capabilities of the system.

[0091] The methods for constructing a weld path with a fractal structure include:

[0092] Real-time obtain the sequence of temperature distribution maps in the heat-affected zone during the welding process through a thermal infrared camera to obtain thermal infrared image data; through a distributed fiber optic strain sensing system, arrange monitoring points in the weld zone of the point cloud set in the weld zone to dynamically capture the three-dimensional strain distribution during the welding process, form a strain tensor field, and obtain strain field data;

[0093] Perform geometric modeling and mesh generation on the assembled three-dimensional topography, and use the finite element method based on the thermo-mechanical coupling model for thermo-mechanical coupling simulation of the welding process; obtain the temperature field by solving the heat conduction equation, input the temperature field as a load into the mechanical equation to solve the stress field, and obtain the distribution characteristics of the strain concentration region in the heat-affected zone by analyzing the strain concentration and residual stress distribution under the temperature field;

[0094] It should be noted that: the heat conduction equation and the mechanical equation are discretized in space and time. The spatial discretization uses the finite element method to discretize the assembled three-dimensional topography into a finite number of elements and nodes, and represents the temperature and displacement of the nodes as the temperature and displacement of any point within the element through the interpolation function of the element; the time discretization uses the difference method to divide the time domain into several time steps and gradually solve the temperature and stress fields of each time step; the solution result (temperature field) of the heat conduction equation is used as the input of the mechanical model, affecting the mechanical properties of the material; the solution result (stress field) of the mechanical equation will affect the heat generation and heat transfer in the heat conduction process;

[0095] Extract the maximum principal strain distribution in the distribution characteristics of the strain concentration region in the heat-affected zone, use the threshold segmentation method to identify the strain concentration region, and generate a continuous high-strain zone; adopt the SIMP method for topological optimization modeling, with minimizing the strain energy density per unit volume of the structure as the objective function to construct the fractal structure of the weld path; discretize the fractal structure of the weld path into the points of the torch movement path, and then obtain the weld path with a fractal structure.

[0096] A method for obtaining the pore distribution, ripple amplitude spectrum, and element diffusion curve of the joint interface region includes:

[0097] Sample cutting and surface preparation treatment are performed on the joint interface region of the multi-segment target welded joint. The surface preparation treatment includes grinding, polishing, and ion beam removal of the surface deformation layer; a scanning electron microscope is used to obtain secondary electron images and backscattered electron images of the joint interface region at different scales; an EBSD probe is equipped on the scanning electron microscope platform to perform crystallographic orientation analysis on the joint interface region, and a grain orientation distribution map of this region is obtained;

[0098] An image stitching and multi-scale enhancement algorithm is adopted to construct a panoramic view of the joint interface of the welded joint containing micro-scale and nano-scale structure information, and the pore region of the panoramic view of the joint interface of the welded joint is identified to obtain the pore distribution in the joint interface region;

[0099] Boundary tracing and extraction are performed on the ripple contour in the panoramic view of the joint interface of the welded joint, and the ripple amplitude spectrum is obtained through Fourier transform analysis; using spectral analysis technology, transverse line scan paths and surface scan regions are set on both sides of the multi-segment target weld interface to obtain spatial distribution data of different metal elements in the joint interface region of the welded joint, and an element diffusion curve showing the change of element concentration with spatial position is generated based on the spatial distribution data.

[0100] A method for designing the welding interface gradient transition layer structure includes:

[0101] Based on the pore distribution data identified in the joint interface region, the distribution density and size of the pores are identified, and a buffer weld bead is designed. Through material remelting and interlayer staggering, the filling density of the pore distribution region is improved to obtain a pore density field; a micro-concave / sloping ripple structure is arranged in the region where the fluctuation frequency of the ripple amplitude spectrum changes suddenly, so that the thermal stress is released along the direction of the structure morphology to obtain a ripple morphology field; an M-layer alloy combination is designed according to the slope of the element diffusion curve, and the composition of each layer of material changes gradually to obtain a composition concentration field; a parameter field driving model based on a neural network is used to fuse the pore density field, ripple morphology field, and composition concentration field to generate a three-dimensional gradient transition structure map, and the welding interface gradient transition layer structure is obtained.

[0102] A method for generating a welding part design scheme for multi-segment target welding includes:

[0103] According to the dynamically adapted groove design parameters, the weld path of the fractal structure, and the welding interface gradient transition layer structure, a welding part design scheme for multi-segment target welding is generated.

[0104] Based on the dynamically adapted groove design parameters, the weld path with a fractal structure, and the welding interface gradient transition layer structure in 3D CAD software, a structured welding part model is established to achieve the collaborative expression of geometric structure and thermal-mechanical properties. Using the numerical control programming interface, the structured welding part model is transformed into an instruction set recognizable by the welding robot, including process information such as the welding torch movement trajectory, energy input parameters, and multi-layer welding sequence, thereby forming a digital design solution for the welding part used in multi-segment target welding to ensure the overall coordination of welding accuracy, structural strength, and interface performance.

[0105] The preset point cloud height difference threshold is set by the staff. By collecting different point cloud height differences, the average value of multiple point cloud height differences is taken as the preset point cloud height difference threshold; similarly, the preset error threshold is set.

[0106] In this embodiment, the weld is located from two dimensions of point cloud data and texture image through two methods: preliminary screening of the weld candidate area and edge enhancement of the texture image. These two methods complement each other, improving the accuracy and reliability of weld location.

[0107] Based on the heat conduction theory and elastoplastic mechanics theory, a thermal-mechanical coupling model is constructed. By solving the heat conduction equation and mechanical equation, the temperature field and stress field distributions in the heat-affected zone during the welding process can be accurately simulated, which helps to predict in advance the magnitude and distribution of residual stress and deformation of the structure after welding, providing a theoretical basis for the optimization of welding processes.

[0108] By simulating the welding process under different parameters through the thermal-mechanical coupling model and analyzing the changes in the temperature field and stress field, the optimal welding process parameters can be found, reducing the occurrence probability of welding defects, improving process stability and the qualified rate of finished products. This model has good simulation efficiency and engineering adaptability, can support the simulation analysis of working conditions such as multi-pass welding and multi-layer welding of complex components, provides an online prediction and feedback control basis for the intelligent welding system, enhances the automation and intelligent capabilities of the system, and improves welding quality and efficiency.

[0109] Adopting a weld path design method based on actual welding process data and simulation analysis can optimize the weld path, reduce stress concentration during welding, and improve welding quality. By reasonably designing the welding interface gradient transition layer structure, stress concentration at the welding joint interface is effectively alleviated, interface defects are reduced, and the strength, toughness, corrosion resistance and other properties of the welding joint are improved, extending the service life of the welded structure.

[0110] The gradient transition layer structure can make the bonding between different materials closer, reduce problems such as uneven element diffusion at the interface, thereby improving the welding quality and ensuring the reliability of the welded structure under complex working conditions; it can quickly and accurately generate a digital design scheme for the welding part that meets the actual requirements, reduce the time and error of manual design, and improve the design efficiency and quality.

[0111] Example 2

[0112] Please refer to Figure 2 As shown in the figure, a welding part design system for multi-segment target welding in this embodiment includes:

[0113] A three-dimensional morphology acquisition module scans the multi-segment target through a laser scanning and visible light imaging device to obtain the assembled three-dimensional morphology of the multi-segment target; based on the assembled three-dimensional morphology, the weld area is identified, and the geometric deviation characteristics of the weld area are extracted;

[0114] A groove parameter generation module generates dynamically adapted groove design parameters based on the geometric deviation characteristics of the weld area and the thermal expansion characteristics of the welding material according to the preset groove design rules;

[0115] A weld path generation module collects thermal infrared image data and strain field data during the welding process, constructs a thermal-mechanical coupling welding process simulation model, obtains the distribution characteristics of the strain concentration area in the heat affected zone by analyzing the strain concentration and residual stress distribution in the heat affected zone during the welding process, and then constructs a weld path with a fractal structure;

[0116] A microstructure analysis module analyzes the microstructure and element diffusion characteristics of the welding joint interface area based on scanning electron microscopy and electron backscatter diffraction, and combines cross-scale image fusion methods to obtain the pore distribution, ripple amplitude spectrum and element diffusion curve in the joint interface area;

[0117] An interface structure design module designs a gradient transition layer structure for the welding interface according to the pore distribution, ripple amplitude spectrum and element diffusion curve in the joint interface area to achieve continuous transition of the welding interface performance;

[0118] A welding scheme integration module generates a welding part design scheme for multi-segment target welding according to the dynamically adapted groove design parameters, the weld path with a fractal structure and the gradient transition layer structure of the welding interface.

[0119] Since the electronic device introduced in this embodiment is the electronic device adopted in the method and system for designing welding parts for a multi-segment target welding in the embodiments of the present application, based on the method and system for designing welding parts for a multi-segment target welding introduced in the embodiments of the present application, those skilled in the art can understand the specific implementation manners and various variations of the electronic device in this embodiment. Therefore, the specific implementation of how this electronic device implements the method in the embodiments of the present application will not be described in detail here. As long as those skilled in the art implement the electronic device adopted in the method and system for designing welding parts for a multi-segment target welding in the embodiments of the present application, it falls within the scope of protection of the present application.

[0120] The above formulas are all dimensionless and take their numerical values for calculation. The formulas are obtained by collecting a large amount of data and performing software simulation to obtain a formula that is closest to the actual situation. The preset parameters and threshold selection in the formulas are set by those skilled in the art according to the actual situation.

[0121] The above is only the preferred implementation manner of the present invention. The protection scope of the present invention is not limited to the above embodiments. All technical solutions falling within the idea of the present invention belong to the protection scope of the present invention. It should be noted that for ordinary technical users in the technical field, several improvements and refinements made without departing from the principle of the present invention should also be regarded as within the protection scope of the present invention.

Claims

1. A welding part design method for multi-segment target welding, characterized in that, Including: S1. Scanning a multi-segment target by a laser scanning and visible light imaging device to obtain the assembled three-dimensional topography of the multi-segment target; Identifying the weld area based on the assembled three-dimensional topography and extracting the geometric deviation characteristics of the weld area; S2. Generating dynamically adapted groove design parameters according to the geometric deviation characteristics of the weld area and the thermal expansion characteristics of the welding material according to the preset groove design rules; S3. Collecting thermal infrared image data and strain field data during the welding process, constructing a thermal-mechanical coupling welding process simulation model, obtaining the distribution characteristics of the strain concentration area in the heat affected zone by analyzing the strain concentration and residual stress distribution in the heat affected zone during the welding process, and then constructing a weld path with a fractal structure; S4. Analyzing the microstructure and element diffusion characteristics of the welding joint interface area based on scanning electron microscopy and electron backscatter diffraction, and combining cross-scale image fusion methods to obtain the pore distribution, ripple amplitude spectrum and element diffusion curve in the joint interface area; S5. Designing a gradient transition layer structure for the welding interface according to the pore distribution, ripple amplitude spectrum and element diffusion curve in the joint interface area to achieve continuous transition of the welding interface performance; S6. Generating a welding part design plan for multi-segment target welding according to the dynamically adapted groove design parameters, the weld path with a fractal structure and the gradient transition layer structure of the welding interface.

2. The welding part design method for multi-segment target welding according to claim 1, characterized in that The method for obtaining the assembled three-dimensional topography of the multi-segment target includes: Adopting the principle of line laser triangulation, selecting a laser scanning device and equipping it with a visible light imaging device; installing the multi-segment target on a clamping platform with stable support and multi-axis motion control, and using the laser scanning device and the visible light imaging device to scan the multi-segment target; Presetting a scanning path according to the geometric shape of the multi-segment target, controlling the laser scanning device to emit a line laser beam along the preset scanning path to perform point-by-point scanning of the target surface, and obtaining the point cloud data of the complete shape of the target by receiving the reflected light; while laser scanning, using the visible light imaging device to synchronously capture the surface texture image of the target, and each frame of image is attached with a timestamp and a spatial coordinate label consistent with the laser scanning device; Through the iterative closest point (ICP) algorithm, splicing and aligning the point cloud data in each direction to the camera coordinate system; mapping the RGB values of the target surface texture image to the corresponding point cloud data through nearest neighbor interpolation, and then generating the assembled three-dimensional topography of the multi-segment target.

3. A welding part design method for multi-segment target welding according to claim 2, characterized in that, The method for extracting the geometric deviation characteristics of the weld area includes: Solving the normal vector of all points in the point cloud data of the complete shape of the target through the local neighborhood covariance matrix; extracting the area with sudden change of the normal vector, and combining the preset point cloud height difference threshold to locate the weld candidate area; Performing Canny edge detection on the synchronously collected target surface texture map, extracting the contour line with sudden change of gray level gradient composed of two-dimensional edge points, and performing image-point cloud coordinate mapping on the contour line through the timestamp and spatial coordinate label attached to each frame of image, and back-projecting the two-dimensional edge points into the three-dimensional point cloud space, and then obtaining the three-dimensional candidate weld edge point set. Region growing and morphological filtering: Points in the weld candidate region and the three-dimensional candidate weld edge point set are merged to form a seed point set. Based on the spatial proximity and normal vector angle between point clouds, region clustering growth is performed to gradually expand the weld region. At the same time, morphological opening operation is used to remove noise points and close small gaps, and finally a point cloud set of the weld region is formed. Analyze the main trend of the weld in the point cloud set of the weld region, preset an ideal welding path based on the standard process specifications, calculate the deviation amount between the main trend of the weld in the point cloud set of the weld region and the preset ideal welding path point by point, and then obtain the geometric deviation characteristics of the weld region.

4. A welding part design method for multi-segment target welding according to claim 3, characterized in that The method for obtaining the groove design parameters includes: Based on the material of the target welding material, query and obtain the corresponding coefficient of thermal expansion and thermal conductivity. Combine the heat input during welding and process parameters to conduct thermal-structural response analysis and modeling, and predict the shrinkage deformation, residual stress, and structural warping trend after welding. According to the preset groove design rules, combine the shrinkage deformation, residual stress, and structural warping trend after welding with the geometric deviation characteristics based on the weld region to form a joint feature vector, and match it in the preset groove design rules to dynamically generate adapted groove design parameters.

5. A welding part design method for multi-segment target welding according to claim 4, characterized in that, The method for constructing the thermal-mechanical coupled welding process simulation model includes: Based on the heat conduction theory and elastoplastic mechanics theory, construct the heat conduction equation and the mechanical equation, and then obtain the thermal-mechanical coupled model; Use the thermal-mechanical coupled model to simulate the temperature field and strain field during the welding process.

6. A welding part design method for multi-segment target welding according to claim 5, characterized in that, The method for constructing a weld path with a fractal structure includes: Real-time obtain the sequence of temperature distribution maps of the heat-affected zone during the welding process through a thermal infrared camera to obtain thermal infrared image data; Through a distributed optical fiber strain sensing system, arrange monitoring points in the weld region of the point cloud set of the weld region to dynamically capture the three-dimensional strain distribution during the welding process, form a strain tensor field, and obtain strain field data; Perform geometric modeling and mesh division on the assembled three-dimensional topography, and use the finite element method based on the thermal-mechanical coupled model to perform thermal-mechanical coupled simulation of the welding process; Obtain the temperature field by solving the heat conduction equation, input the temperature field as a load into the mechanical equation to solve the stress field, and obtain the distribution characteristics of the strain concentration region in the heat-affected zone by analyzing the strain concentration and residual stress distribution under the temperature field. Extract the maximum principal strain distribution in the distribution characteristics of the strain concentration region in the heat-affected zone, use the threshold segmentation method to identify the strain concentration region, and generate a continuous high-strain zone; Use the SIMP method to perform topology optimization modeling, with minimizing the strain energy density per unit volume of the structure as the objective function, and construct the fractal structure of the weld path; Discretize the fractal structure of the weld path into the points of the welding torch movement path, and then obtain the weld path with a fractal structure.

7. A welding part design method for multi-segment target welding according to claim 6, characterized in that The method for obtaining the pore distribution, ripple amplitude spectrum, and element diffusion curve in the joint interface region includes: Samples are intercepted and surface preparation treatments are performed on the interface region of the multi-segment target welding joint. The surface preparation treatments include grinding, polishing, and ion beam removal of the surface deformation layer; secondary electron images and backscattered electron images of the welding joint interface region at different scales are obtained using a scanning electron microscope; an EBSD probe is equipped on the scanning electron microscope platform to perform crystallographic orientation analysis on the welding joint interface region, and a grain orientation distribution map of this region is obtained; An image stitching and multi-scale enhancement algorithm is adopted to construct a panoramic view of the welding joint interface containing micro-scale and nano-scale structural information, and the pore regions in the panoramic view of the welding joint interface are identified to obtain the pore distribution in the joint interface region; Boundary tracking and extraction are performed on the ripple contours in the panoramic view of the welding joint interface, and the ripple amplitude spectrum is obtained through Fourier transform analysis; using spectral analysis technology, transverse line scan paths and surface scan regions are set on both sides of the multi-segment target weld interface to obtain the spatial distribution data of different metal elements in the welding joint interface region, and an element diffusion curve showing the change of element concentration with spatial position is generated based on the spatial distribution data.

8. A welding part design method for multi-section target welding according to claim 7, characterized in that, The method for designing the welding interface gradient transition layer structure includes: Based on the pore distribution data identified in the joint interface region, the distribution density and size of the pores are identified, a buffer weld bead is designed, and through material remelting and interlayer staggering, the filling density of the pore distribution region is improved to obtain a pore density field; a micro-concave / slope ripple structure is arranged in the region where the fluctuation frequency of the ripple amplitude spectrum changes suddenly, so that the thermal stress is released along the direction of the structure morphology to obtain a ripple morphology field; an M-layer alloy combination is designed according to the slope of the element diffusion curve, and the material composition of each layer changes gradually to obtain a composition concentration field; a parameter field driving model based on a neural network is used to fuse the pore density field, the ripple morphology field, and the composition concentration field to generate a three-dimensional gradient transition structure map, and the welding interface gradient transition layer structure is obtained.

9. A welding part design method for multi-section target welding according to claim 8, characterized in that, The method for generating a welding part design scheme for multi-segment target welding includes: According to the dynamically adapted groove design parameters, the weld path with a fractal structure, and the welding interface gradient transition layer structure, a welding part design scheme for multi-segment target welding is generated; Based on the dynamically adapted groove design parameters, the weld path with a fractal structure, and the welding interface gradient transition layer structure, a structured welding part model is established through 3D CAD software; the structured welding part model is converted into an instruction set recognizable by a welding robot using a numerical control programming interface, thereby forming a digital design scheme for the welding part for multi-segment target welding.

10. A welding part design system for multi - segment target welding, which is used to implement a welding part design method for multi - segment target welding according to any one of claims 1 to 9, characterized in that, Including: A three-dimensional topography acquisition module scans the multi-segment target through a laser scanning and visible light imaging device to obtain the assembled three-dimensional topography of the multi-segment target; The weld region is identified based on the assembled three-dimensional topography, and the geometric deviation characteristics of the weld region are extracted; A groove parameter generation module generates dynamically adapted groove design parameters according to the preset groove design rules based on the geometric deviation characteristics of the weld region and the thermal expansion characteristics of the welding material; The weld path generation module collects the thermal infrared image data and strain field data during the welding process, constructs a thermal-mechanical coupled welding process simulation model, obtains the distribution characteristics of the strain concentration region in the heat-affected zone by analyzing the strain concentration and residual stress distribution in the heat-affected zone during the welding process, and then constructs a weld path with a fractal structure; The microstructure analysis module analyzes the microstructure and element diffusion characteristics in the interface region of the welded joint based on scanning electron microscopy and electron backscatter diffraction, and combines the cross-scale image fusion method to obtain the pore distribution, ripple amplitude spectrum and element diffusion curve in the joint interface region; The interface structure design module designs the gradient transition layer structure of the welding interface according to the pore distribution, ripple amplitude spectrum and element diffusion curve in the joint interface region to achieve continuous transition of the welding interface performance; The welding scheme integration module generates a welding part design scheme for multi-segment target welding according to the dynamically adapted groove design parameters, the weld path with a fractal structure and the gradient transition layer structure of the welding interface.

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