Forklift gantry welding deformation control and correction method

Abstract

The invention discloses a forklift gantry welding deformation control and correction method, particularly relates to the technical field of electron beam welding in the intelligent manufacturing equipment industry, and is used for solving the problems of low correction precision and insufficient effect stability caused by interference of a welding residual stress field and a thermal tension field in the existing electron beam correction technology. A correction area is determined by obtaining a portal frame component three-dimensional model and deformation data, the mapping relation between electron beam focus drifting characteristics and the welding residual stress state is established, a macroscopic plastic flow channel formed in the mode that the stress gradient direction is consistent with the thermal tension vector direction is recognized, an electron beam scanning path is planned according to the macroscopic plastic flow channel, and technological parameters are optimized. And finally, the electron beam welding equipment is controlled to execute precise scanning heating. The welding deformation correction is converted from experience judgment to quantitative control, and the correction precision and the process stability are remarkably improved.

Description

Technical Field

[0001] This invention relates to the field of electron beam welding technology in the intelligent manufacturing equipment industry, and more specifically, to a method for controlling and correcting welding deformation of forklift masts. Background Technology

[0002] As a core load-bearing component of logistics handling equipment, the manufacturing precision of the forklift mast directly affects the safety and reliability of the entire vehicle. Electron beam welding technology, with its high energy density, low heat input, and excellent protective characteristics under vacuum conditions, demonstrates unique advantages in welding high-strength steel structures such as forklift masts, and is one of the key processes for achieving high-quality connections in the intelligent manufacturing equipment industry. After welding, for any deformation that occurs, the industry generally uses thermal correction technology for repair, which utilizes an electron beam as a controllable heat source to perform non-melting scanning heating on the deformed area.

[0003] However, existing technologies face problems when using electron beams for welding deformation correction: there is an inherent residual stress field inside the welded portal frame components. When the electron beam acts as a correction heat source on a local area, the thermal tension field it introduces will have a complex interference effect with the unknown original stress field. This interaction of stress fields is difficult to predict and control, resulting in uncertainty in the plastic flow behavior of materials during the correction process. This leads to low correction accuracy, insufficient stability of the effect, and may even induce microscopic damage in extreme cases, thus restricting its large-scale reliable application in high-end intelligent manufacturing. Summary of the Invention

[0004] In order to overcome the above-mentioned defects of the prior art, the present invention provides a method for controlling and correcting welding deformation of forklift masts to solve the problems mentioned in the background art.

[0005] To achieve the above objectives, the present invention provides the following technical solution: A method for controlling and correcting welding deformation of a forklift mast, comprising: S1. Obtain the 3D model and actual deformation measurement data of the forklift mast component to be corrected; S2. Determine the electron beam correction area and initial electron beam process parameters based on the three-dimensional model and actual deformation measurement data; S3. Within the electron beam correction region, the electron beam focusing current is changed systematically and the drift characteristics of the corresponding focal position are monitored to establish a mapping relationship between the focal drift characteristics and the welding residual stress state, so as to characterize the welding residual stress gradient distribution in the electron beam correction region. S4. Analyze the spatial correspondence between the stress gradient direction and the electron beam thermal tension vector direction in the distribution of welding residual stress gradient, and identify the macroscopic plastic flow channels formed due to the tendency of the stress gradient direction and the thermal tension vector direction to be consistent. S5. Based on the distribution characteristics of the macroscopic plastic flow channels, plan the scanning path of the electron beam in the electron beam correction region and optimize the initial electron beam process parameters. S6. Control the electron beam welding equipment to perform scanning heating operations on the electron beam correction area according to the scanning path and optimized initial electron beam process parameters.

[0006] Furthermore, the three-dimensional model and actual deformation measurement data of the forklift mast component to be corrected are obtained, including: The surface point cloud data of the gantry components is collected by a 3D scanning device, and the surface point cloud data is compared and analyzed with the original design model. Actual deformation measurement data are generated based on the deviation data obtained from the comparative analysis. The actual deformation measurement data and the original design model are combined to form an integrated three-dimensional model.

[0007] Furthermore, based on the 3D model and actual deformation measurement data, the electron beam correction region and initial electron beam process parameters are determined, including: Analyze the strain concentration regions in the actual deformation measurement data, and mark the regions in the strain concentration regions that exceed a preset threshold as electron beam correction regions; Simultaneously, based on the material thickness and material properties corresponding to the electron beam correction area in the 3D model, the corresponding electron beam power range and scanning speed range are matched from the pre-established process parameter database as the initial electron beam process parameters.

[0008] Furthermore, within the electron beam correction region, the electron beam focusing current is systematically changed and the drift characteristics of the corresponding focal position are monitored to establish a mapping relationship between the focal drift characteristics and the welding residual stress state, thereby characterizing the welding residual stress gradient distribution in the electron beam correction region, including: Within the electron beam correction area, the electron beam focusing current is continuously adjusted according to a preset step size, and the electron beam focal point position coordinates corresponding to each focusing current value are recorded. The maximum offset of the electron beam focal position coordinates within the range of focusing current variation is used as the focal drift characteristic parameter; By comparing the correspondence between the focus drift characteristic parameters and the pre-calibrated stress parameters, a quantitative mapping relationship between the focus drift characteristic parameters and the welding residual stress state is established. Based on the quantization mapping relationship, the focus drift characteristic parameters of each measurement point in the electron beam correction area are converted into welding residual stress gradient distribution data.

[0009] Furthermore, by comparing the correspondence between the focus drift characteristic parameters and the pre-calibrated stress parameters, a quantitative mapping relationship between the focus drift characteristic parameters and the welding residual stress state is established. This includes: measuring the focus drift characteristic parameters on a calibration sample with a known welding residual stress state to obtain the pre-calibrated stress parameters; and using a data fitting method to correlate the focus drift characteristic parameters with the pre-calibrated stress parameters to establish a linear or nonlinear quantitative mapping relationship between the focus drift characteristic parameters and the welding residual stress state.

[0010] Furthermore, the spatial correspondence between the stress gradient direction and the electron beam thermal tension vector direction in the weld residual stress gradient distribution was analyzed, and macroscopic plastic flow channels formed due to the convergence of the stress gradient direction and the thermal tension vector direction were identified, including: The stress gradient direction vector of each grid node is calculated based on the welding residual stress gradient distribution data, and the direction of the electron beam thermal tension vector is determined according to the electron beam scanning direction. Calculate the spatial angle between the stress gradient direction vector and the electron beam thermal tension vector at each grid node; Continuous grid node regions with spatial angles less than a preset critical angle are identified as macroscopic plastic flow channels, and the spatial orientation and distribution range of the macroscopic plastic flow channels are recorded.

[0011] Furthermore, calculating the spatial angle between the stress gradient direction vector and the electron beam thermal tension vector at each grid node includes: extracting the stress gradient direction vector coordinates of each grid node based on the welding residual stress gradient distribution data; determining the electron beam thermal tension vector direction coordinates according to the electron beam scanning direction; and calculating the spatial angle between the stress gradient direction vector and the electron beam thermal tension vector direction through vector dot product operation.

[0012] Furthermore, based on the distribution characteristics of the macroscopic plastic flow channels, the scanning path of the electron beam within the electron beam correction region is planned and the initial electron beam process parameters are optimized, including: Based on the spatial orientation of the macroscopic plastic flow channel, the electron beam scanning path is planned so that its main direction forms a preset angle with the spatial orientation of the macroscopic plastic flow channel; Adjust the electron beam power value in the initial electron beam process parameters according to the distribution range and density of the macroscopic plastic flow channels; Simultaneously, the electron beam scanning speed parameter value is adjusted accordingly based on the number of macroscopic plastic flow channels identified.

[0013] Furthermore, adjusting the electron beam power value in the initial electron beam process parameters based on the distribution range density of the macroscopic plastic flow channel includes: calculating the distribution range density of the macroscopic plastic flow channel within the electron beam correction region; increasing the electron beam power value when the distribution range density is higher than a preset density threshold; and decreasing the electron beam power value when the distribution range density is lower than a preset density threshold.

[0014] Furthermore, the electron beam welding equipment is controlled to perform scanning heating operations on the electron beam correction area according to the scanning path and optimized initial electron beam process parameters, including: The planned scanning path is converted into a sequence of control commands that can be recognized by the electron beam welding equipment; Set the power output unit and scanning control unit of the electron beam welding equipment according to the optimized initial electron beam process parameters; Segmented progressive scanning heating is performed along the scanning path within the electron beam correction area. After completing the current segment of scanning heating, the process pauses for a preset interval before continuing with the next segment of scanning heating, until the scanning heating operation of the entire electron beam correction area is completed.

[0015] Compared with the prior art, the present invention has the following beneficial effects: 1. By establishing a quantitative mapping relationship between electron beam focus drift characteristics and welding residual stress state, the original stress field inside the component is accurately characterized, effectively solving the uncertainty of material plastic flow caused by stress field interference effect in traditional correction process. By identifying the macroscopic plastic flow channel formed when the stress gradient direction and thermal tension vector direction tend to be consistent, the material flow trend caused by electron beam thermal input can be accurately predicted, thereby actively avoiding unfavorable stress superposition areas when planning the scanning path, significantly improving the control accuracy and effect stability of the correction process; 2. In the intelligent manufacturing equipment industry, through systematic stress field identification and plastic flow channel analysis, the electron beam correction process has been transformed from experience-based to scientifically controlled. It can adaptively plan the optimal scanning path and process parameters according to the actual stress state of the component, which not only avoids the generation of micro-damage during the correction process, but also ensures the consistency and reliability of deformation correction effect in mass production, providing technical support for the precision manufacturing of core components of high-end intelligent equipment. Attached Figure Description

[0016] Figure 1 This is a flowchart of a method for controlling and correcting welding deformation of a forklift mast according to the present invention. Detailed Implementation

[0017] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0018] Example: Figure 1 This invention provides a method for controlling and correcting welding deformation of a forklift mast, comprising: S1. Obtain the 3D model and actual deformation measurement data of the forklift mast component to be corrected; S2. Determine the electron beam correction area and initial electron beam process parameters based on the three-dimensional model and actual deformation measurement data; S3. Within the electron beam correction region, the electron beam focusing current is changed systematically and the drift characteristics of the corresponding focal position are monitored to establish a mapping relationship between the focal drift characteristics and the welding residual stress state, so as to characterize the welding residual stress gradient distribution in the electron beam correction region. S4. Analyze the spatial correspondence between the stress gradient direction and the electron beam thermal tension vector direction in the distribution of welding residual stress gradient, and identify the macroscopic plastic flow channels formed due to the tendency of the stress gradient direction and the thermal tension vector direction to be consistent. S5. Based on the distribution characteristics of the macroscopic plastic flow channels, plan the scanning path of the electron beam in the electron beam correction region and optimize the initial electron beam process parameters. S6. Control the electron beam welding equipment to perform scanning heating operations on the electron beam correction area according to the scanning path and optimized initial electron beam process parameters.

[0019] S1. Obtain the 3D model and actual deformation measurement data of the forklift mast component to be corrected. The specific implementation is as follows: In acquiring the 3D model and actual deformation measurement data of the forklift mast component to be corrected, a laser 3D scanning device is first used to collect circumferential data on the surface of the mast component. The measurement accuracy of this laser 3D scanning device needs to be within 0.05 mm, and the scanning point spacing is set to 1 mm. Complete surface point cloud data is obtained through multi-view scanning. Before scanning, a positioning reference needs to be established for the mast component, using the center line of the mast pin hole as the reference coordinate system to ensure that the scanned data and the original design model are in the same coordinate reference system.

[0020] The acquired surface point cloud data is imported into 3D data processing software, where it is automatically aligned and matched with the original design model using an iterative nearest-point algorithm. A preset matching tolerance of 0.1 mm is set during the matching process. This preset tolerance value is determined by analyzing the mast assembly accuracy requirements, for example, derived from the required clearance between the mast and the forks. When the matching deviation between the surface point cloud data and the original design model exceeds this preset tolerance, the coordinate transformation parameters need to be readjusted until the matching requirements are met. After coordinate alignment is completed, the system automatically calculates the Euclidean distance between each measurement point in the surface point cloud data and the corresponding point in the original design model, generating an initial deviation dataset containing positional deviation information.

[0021] Data filtering was performed on the initial deviation dataset, using a Gaussian filtering algorithm to eliminate measurement noise, with the filtering window size set to a 3×3 neighborhood. The filtered deviation data was then spatially interpolated using the Kriging interpolation method to generate continuously distributed deviation field data. Regions in the deviation field data exceeding a preset deformation threshold were marked as significant deformation regions. This preset deformation threshold was set to 1.5 mm according to the gantry design tolerance standard. A region growing algorithm was then applied to these significant deformation regions to extract the boundaries of connected regions, generating actual deformation measurement data.

[0022] The actual deformation measurement data includes information such as the location coordinates of the deformation area, the value of the deformation, and the direction of the deformation gradient. The actual deformation measurement data is fused with the original design model, and the material thickness attribute of each deformation area is marked in the actual deformation measurement data. This material thickness attribute is extracted from the feature tree of the original design model. Using a non-uniform rational B-spline surface reconstruction method, the discrete measurement points in the actual deformation measurement data are reconstructed into a continuous surface. This continuous surface, together with the original design model, constitutes an integrated three-dimensional model.

[0023] The integrated 3D model employs a hierarchical data structure. The bottom layer contains the geometric and topological information of the original design model, the middle layer is a meshed representation of the actual deformation measurement data, and the top layer is a parametric description of the deformation characteristics. In the integrated 3D model, each mesh node stores four types of attribute data: position coordinates, normal vector, deformation amount, and material thickness. The mesh size is determined based on the deformation characteristic scale, using a fine mesh of 0.5 mm in areas with large deformation gradients and a standard mesh of 2 mm in areas with gentle deformation.

[0024] The integrated 3D model reduces data volume through lightweight processing and simplifies the mesh using an edge-folding algorithm, keeping the number of mesh faces below 500,000 while preserving geometric features. The simplified integrated 3D model is stored in a standard triangular facet format while retaining complete metadata information, including coordinate system definition, unit system, creation time, and version number. The final integrated 3D model can be directly used in subsequent electron beam correction region determination processes, providing a complete digital foundation for deformation correction.

[0025] In the processing of surface point cloud data, missing data needs to be compensated. When holes caused by occlusion exist in the point cloud data, the moving least squares method is used for surface fitting and completion. During the completion process, the curvature of the surface is kept continuous to ensure a smooth transition between the completed area and the surrounding data. Outliers in the point cloud data are identified and removed using statistical analysis methods. The criteria for outliers are data points whose average distance from their neighbors exceeds three standard deviations.

[0026] The generation of actual deformation measurement data also includes the extraction of deformation characteristic parameters. Principal component analysis is used to determine the main deformation directions of each deformation region, and geometric features such as the area, perimeter, and centroid position of the deformation region are calculated. These characteristic parameters, together with the deformation values, constitute a complete deformation description index system, providing a quantitative basis for subsequent calibration process planning.

[0027] The integrated 3D model also needs to undergo data integrity verification. The model's watertightness is calculated to ensure the mesh is free of cracks and self-intersections. Element quality checks are performed, removing malformed elements with an aspect ratio greater than 10 to ensure numerical stability in subsequent finite element analyses. After all checks are completed, the integrated 3D model is ready for the next stage.

[0028] S2. Based on the 3D model and actual deformation measurement data, determine the electron beam correction region and initial electron beam process parameters, specifically as follows: In determining the electron beam correction region and initial electron beam process parameters, the strain concentration regions in the actual deformation measurement data are first analyzed. These regions are identified by calculating the equivalent strain values ​​of each grid node in the actual deformation measurement data. The equivalent strain values ​​are calculated using the Mises strain formula, and the required displacement gradient tensor is obtained by dividing the displacement difference between adjacent grid nodes in the actual deformation measurement data by the node spacing. Grid nodes whose equivalent strain values ​​exceed a preset strain threshold are marked as candidate strain concentration nodes. This preset strain threshold is determined by multiplying the ratio of the material's yield strength to its elastic modulus by a safety factor. The safety factor is determined based on the importance of the gantry structure; for example, the safety factor for the main load-bearing structure is 1.5, and the safety factor for the secondary structure is 1.2.

[0029] Cluster analysis was performed on candidate strain concentration nodes. A density-based spatial clustering algorithm was used to group adjacent nodes with a spatial distance of less than 3 mm into the same strain concentration region. The average equivalent strain value and the maximum equivalent strain value of each strain concentration region were calculated. Strain concentration regions with an average equivalent strain value exceeding a preset strain threshold were marked as electron beam correction regions. This preset strain threshold was determined based on the safety factor of the gantry structure and material properties. For example, the threshold was set to 0.005 for primary load-bearing components and 0.008 for secondary components. The geometric center coordinates, area, average strain value, and maximum strain value of each electron beam correction region were recorded.

[0030] Material thickness and properties of the electron beam correction region are extracted from the 3D model. Material thickness is obtained by calculating the normal projection distance of the electron beam correction region onto the 3D model; for curved regions, a piecewise linear approximation method is used to calculate the average thickness. Material properties are read from the material property library of the 3D model, including parameters such as material density, elastic modulus, Poisson's ratio, thermal conductivity, and specific heat capacity. For composite material regions, equivalent material parameters are calculated according to the area proportion of each material.

[0031] The pre-established process parameter database contains electron beam power and scanning speed ranges corresponding to different material thicknesses and material combinations. This database was established through extensive process experiments, covering material thicknesses from 1 mm to 50 mm, and materials including commonly used gantry materials such as low-carbon steel, low-alloy steel, and high-strength steel. The electron beam power range in the database is determined based on the material's heat of fusion and heat-affected zone width requirements, while the scanning speed range is determined based on heat input control and deformation correction effect requirements.

[0032] Based on the material thickness and properties of the electron beam correction region, the corresponding electron beam power range and scanning speed range are matched in a pre-established process parameter database. The matching process uses a nearest neighbor algorithm to find records in the database that have a material thickness difference of less than 0.5 mm and are of the same material. When multiple matching records exist, the intersection of the electron beam power ranges in each record is taken as the final electron beam power range, and the intersection of the scanning speed ranges is taken as the final scanning speed range.

[0033] For materials with thicknesses falling within the middle range of the database records, a linear interpolation method is used to calculate the electron beam power range and scanning speed range. For example, when the material thickness is 8 mm and the database contains records for 6 mm and 10 mm, the electron beam power range is obtained by linear interpolation of the power values ​​corresponding to 6 mm and 10 mm. The interpolation calculation considers the influence of material properties; for materials with higher thermal conductivity, the upper limit of the power range is appropriately increased.

[0034] The initial electron beam process parameters also include parameters such as the electron beam focusing current and the scanning path mode. The electron beam focusing current is determined based on a combination of material thickness and electron beam power; for every 1 mm increase in material thickness, the electron beam focusing current is adjusted by 5 mA. The scanning path mode is selected based on the shape characteristics of the electron beam correction area: a linear scanning mode is used for elongated areas, a spiral scanning mode is used for circular areas, and a grid scanning mode is used for irregular areas.

[0035] The final determined initial electron beam process parameters include four main parameters: electron beam power range, scanning speed range, electron beam focusing current, and scanning path mode. These parameters are output in the form of process cards for subsequent process optimization. Each electron beam correction region corresponds to an independent set of initial electron beam process parameters, ensuring that the process parameters match the characteristics of the correction region.

[0036] During the process parameter matching, the influence of the strain level in the electron beam correction region on parameter selection also needs to be considered. For high-strain regions with an average equivalent strain value exceeding 0.01, the upper limit of the electron beam power range is increased by 10% and the lower limit of the scanning speed range is decreased by 15% based on the database matching results. This adjustment is to ensure that the high-strain region receives sufficient heat input to achieve effective stress release and deformation correction.

[0037] The pre-established process parameter database is regularly updated and optimized based on actual calibration results. After each electron beam calibration, the actual process parameters used and the calibration results are recorded. When the calibration accuracy meets the requirements, the corresponding parameter combination is added to the database. When the calibration effect is unsatisfactory, the corresponding parameters in the database are marked and prioritized for exclusion in subsequent use. This self-learning mechanism continuously improves the accuracy of process parameter matching.

[0038] After determining all electron beam correction regions and initial electron beam process parameters, a process planning report is generated. This report details the location, geometric features, material properties, and corresponding initial electron beam process parameters for each electron beam correction region. This process planning report serves as the technical basis for subsequent electron beam correction operations, ensuring the standardization and consistency of the correction process.

[0039] S3. Within the electron beam correction region, the electron beam focusing current is systematically changed, and the drift characteristics of the corresponding focal position are monitored. A mapping relationship between the focal drift characteristics and the welding residual stress state is established to characterize the welding residual stress gradient distribution within the electron beam correction region. Specifically, this is implemented as follows: When monitoring the drift characteristics of the corresponding focal position by systematically changing the electron beam focusing current within the electron beam correction region, it is first necessary to set the adjustment range and step size of the electron beam focusing current. The adjustment range of the electron beam focusing current is determined according to the performance parameters of the electron beam welding equipment. For example, for commonly used electron beam welding equipment, the adjustment range is set to 200 mA to 800 mA. The preset step size is determined according to the measurement accuracy requirements. For example, when higher measurement accuracy is required, the preset step size is set to 10 mA; when measurement efficiency is prioritized, the preset step size is set to 20 mA. During the adjustment of the electron beam focusing current, it is necessary to keep the electron beam power and accelerating voltage constant to ensure that the change in focal position is only affected by the focusing current.

[0040] While continuously adjusting the electron beam focusing current, the electron beam focus position coordinates corresponding to each focusing current value are recorded by an electron beam focus position monitoring system. This system employs a dual-view high-speed camera with a shooting frequency of 1000 frames per second and a spatial resolution of 0.01 mm. The electron beam focus position coordinates are extracted using an image processing algorithm. This algorithm first performs Gaussian filtering to denoise the acquired image, then uses an edge detection algorithm to identify the electron beam focus contour, and finally calculates the centroid coordinates of the contour as the electron beam focus position coordinates.

[0041] The maximum offset of the electron beam focal point position coordinates within the range of focusing current variation is used as the focal drift characteristic parameter. The maximum offset is obtained by calculating the maximum Euclidean distance between any two points in all electron beam focal point position coordinates. During the calculation, outliers caused by measurement noise need to be excluded; outliers are defined as data points whose distance from adjacent points exceeds three times the average distance. The focal drift characteristic parameter also needs to be normalized to convert it into a dimensionless parameter to facilitate the subsequent establishment of mapping relationships.

[0042] By comparing the correspondence between focus drift characteristic parameters and pre-calibrated stress parameters, a quantitative mapping relationship between focus drift characteristic parameters and welding residual stress state is established. The pre-calibrated stress parameters are obtained by measuring on calibration samples with known welding residual stress states. The calibration samples are prepared using the same materials and welding processes as actual portal frame components, and the welding residual stress values ​​of the calibration samples are measured by X-ray diffraction as reference values. The electron beam focusing current adjustment and focus position monitoring process is repeated on the calibration samples to obtain the corresponding focus drift characteristic parameters.

[0043] When establishing a quantitative mapping relationship, a data fitting method is used for correlation. The pre-calibrated stress parameter is used as the dependent variable, and the focus drift characteristic parameter is used as the independent variable. Regression analysis is used to determine the mathematical relationship between the two. For example, when the data shows a linear relationship, a linear function is used for fitting; when the data shows a nonlinear relationship, a quadratic or exponential function is used. Goodness of fit is evaluated using the coefficient of determination, which should be above 0.9; otherwise, the measurement data needs to be re-examined or the form of the fitting function needs to be adjusted.

[0044] Based on the quantization mapping relationship, the focus drift characteristic parameters of each measurement point within the electron beam correction area are converted into welding residual stress gradient distribution data. During the conversion process, the electron beam correction area is first divided into a uniform grid. At each grid node, the electron beam focusing current is adjusted and the focus position is monitored to obtain the focus drift characteristic parameters of that node. Then, the welding residual stress value of that node is calculated using the established quantization mapping relationship. Finally, an interpolation method is used to interpolate the welding residual stress values ​​of discrete nodes into continuous welding residual stress gradient distribution data.

[0045] When establishing quantization mapping relationships, the influence of material thickness on the mapping relationship also needs to be considered. For materials of different thicknesses, corresponding quantization mapping relationships need to be established separately. For example, the material thickness can be grouped into intervals of 5 millimeters, and calibration and fitting can be performed separately within each thickness interval. When the actual material thickness falls between two calibrated thicknesses, a linear interpolation method is used to determine the corresponding quantization mapping relationship parameters.

[0046] The weld residual stress gradient distribution data is represented in tensor form, containing information on stress magnitude and direction. At each grid node, the weld residual stress value is decomposed into three normal stress components and three shear stress components. The stress gradient is calculated using the central difference method, obtained by dividing the stress difference between adjacent grid nodes by the node spacing. The node spacing is determined based on the mesh density; for example, when the mesh size is 1 mm, the node spacing is 1 mm.

[0047] To verify the accuracy of the quantization mapping, cross-validation is required. The calibration sample data is randomly divided into training and validation sets. The training set data is used to establish the quantization mapping, and the validation set data is used to test the prediction accuracy. The prediction accuracy requires a relative error of less than 15% and an absolute error of less than 20 MPa. If the validation results do not meet the accuracy requirements, the number of calibration samples needs to be increased or the form of the fitting function needs to be adjusted.

[0048] The final obtained welding residual stress gradient distribution data is stored in matrix form, with the number of rows and columns consistent with the grid division of the electron beam correction region. Each matrix element contains the welding residual stress value and its gradient information at that location. This data can be used for subsequent analysis of the spatial correspondence between the stress gradient direction and the electron beam thermal tension vector direction in the welding residual stress gradient distribution, providing a basis for identifying macroscopic plastic flow channels.

[0049] Throughout the measurement process, environmental conditions must be kept stable. The ambient temperature should be maintained between 20 and 25 degrees Celsius, and the humidity below 60%. The electron beam welding equipment needs to be preheated for at least 30 minutes to ensure it reaches a stable operating state. Data acquisition at each measurement point should be repeated three times, and the average value should be taken as the final result to reduce the impact of random errors.

[0050] After collecting the welding residual stress gradient distribution data, a data quality assessment is required. Assessment indicators include data completeness, consistency, and accuracy. Completeness requires that the coverage of valid data points within the electron beam calibration area exceeds 95%; consistency requires that stress changes between adjacent measurement points be continuous and smooth; and accuracy requires that the deviation from the baseline value of the calibration sample be within acceptable limits. Only data that passes the quality assessment can be used for subsequent analysis and processing.

[0051] S4. Analyze the spatial correspondence between the stress gradient direction and the electron beam thermal tension vector direction in the welding residual stress gradient distribution, and identify the macroscopic plastic flow channels formed due to the tendency of the stress gradient direction and the thermal tension vector direction to be consistent. The specific implementation is as follows: When analyzing the spatial correspondence between the stress gradient direction and the electron beam thermal tension vector direction in the welding residual stress gradient distribution, it is first necessary to calculate the stress gradient direction vector of each grid node based on the welding residual stress gradient distribution data. The welding residual stress gradient distribution data comes from the output of the previous steps and is stored in the form of a three-dimensional matrix. Each element of the matrix corresponds to the stress state of a grid node, including three normal stress components and three shear stress components. The calculation of the stress gradient direction vector is achieved using the finite difference method. For example, for each grid node, the stress difference between adjacent nodes in the x, y, and z directions is taken, divided by the node spacing to obtain the stress gradient components. Then, the three gradient components are combined into a stress gradient vector, and finally, this vector is normalized to obtain the unit stress gradient direction vector. The node spacing is determined according to the grid density; for example, when the grid size is 1 mm, the node spacing is 1 mm. During the calculation process, it is necessary to ensure the consistency of the stress gradient direction vector's direction; for example, the vector direction is defined to point towards the direction of increasing stress.

[0052] Simultaneously, the direction of the electron beam thermal tension vector is determined based on the electron beam scanning direction. The electron beam scanning direction is read from the process parameter file, which records the trajectory and scanning path information of the electron beam within the electron beam correction area. For a straight scanning path, the direction of the electron beam thermal tension vector is consistent with the scanning path direction; for a curved scanning path, the direction of the electron beam thermal tension vector is determined by calculating the tangent direction at each point on the scanning path. The direction of the electron beam thermal tension vector is also represented as a unit vector, and its coordinate components are calculated using direction cosines. For example, when the scanning direction makes a 30-degree angle with the x-axis, the x-component of the electron beam thermal tension vector is cos30 degrees, the y-component is sin30 degrees, and the z-component is 0. When determining the direction of the electron beam thermal tension vector, the scanning sequence and scanning speed of the electron beam need to be considered to ensure that the vector direction is consistent with the actual electron beam motion state.

[0053] Calculate the spatial angle between the stress gradient direction vector and the electron beam thermal tension vector at each grid node. The spatial angle is calculated using a vector dot product operation. First, calculate the dot product of the stress gradient direction vector and the electron beam thermal tension vector; the dot product is the sum of the products of the corresponding coordinate components of the two vectors. Then, calculate the magnitudes of the two vectors; the magnitude is the square root of the sum of the squares of the coordinate components of each vector. Finally, divide the dot product by the product of the magnitudes of the two vectors to obtain the cosine value, and then calculate the spatial angle using the inverse cosine function. The unit for the spatial angle is degrees, ranging from 0 to 180 degrees. During the calculation, ensure that the vector coordinates are in the same coordinate system, with the origin at the lower left corner of the electron beam correction area, the x-axis horizontal to the right, the y-axis vertically upward, and the z-axis perpendicular to the workpiece surface. After calculating the spatial angle for each grid node, check if the result is within a reasonable range. For example, if the spatial angle is close to 0 or 180 degrees, verify the correctness of the vector direction.

[0054] Continuous grid node regions with spatial angles less than a preset critical angle are identified as macroscopic plastic flow channels. The preset critical angle is determined based on material type and plastic deformation mechanism, derived through statistical analysis of extensive experimental data. For example, for low-carbon steel, the preset critical angle is set to 15 degrees; for aluminum alloys, it is set to 20 degrees. Continuous grid node regions are identified using a region growing algorithm, starting from seed points that meet the spatial angle condition and gradually expanding to adjacent grid nodes. The criterion for adjacent nodes is a spatial distance less than twice the grid size. Boundary continuity is checked during region growing to ensure that the identified regions are connected macroscopic plastic flow channels. After identification, the spatial orientation and distribution range of the macroscopic plastic flow channels are recorded. The spatial orientation is determined using principal component analysis (PCA). The coordinate covariance matrix of all grid nodes within the macroscopic plastic flow channel is calculated, and then the eigenvectors of the covariance matrix are obtained. The eigenvector corresponding to the largest eigenvalue is the main spatial orientation of the macroscopic plastic flow channel. The distribution range is obtained by calculating the boundary points of the macroscopic plastic flow channel. The convex hull algorithm is used to extract the circumscribed polygons of the channel region, and the vertex coordinates of the polygons are recorded. Simultaneously calculate the area and volume of the macroscopic plastic flow channel, where the area is the coverage area of ​​the channel on the two-dimensional projection plane, and the volume is the space occupied by the channel in three-dimensional space.

[0055] When calculating the spatial angle, the consistency of vector directions must also be considered. Since both the stress gradient direction vector and the electron beam thermal tension vector are directional quantities, it is necessary to ensure that the directions of the two vectors are defined consistently before calculating the dot product. For example, the stress gradient direction vector can be defined to point in the direction of increasing stress, and the electron beam thermal tension vector can be defined to point in the forward direction of the electron beam scan. If the vector directions are not defined consistently, one of the vectors needs to be inverted before calculating the dot product and the spatial angle. Furthermore, for boundary mesh nodes, due to the insufficient number of adjacent nodes, special processing methods are required, such as using the one-sided difference method to calculate the stress gradient direction vector, to ensure that all nodes obtain a valid spatial angle value.

[0056] The setting of the preset critical angle needs to be optimized in conjunction with material properties. Statistical analysis of extensive experimental data revealed that materials are more prone to plastic flow when the spatial angle is less than a certain value. For example, after testing various types of steel, it was determined that plastic flow is significant when the spatial angle is less than 15 degrees; therefore, the preset critical angle was set to 15 degrees. For different materials, calibration experiments are required to determine the appropriate preset critical angle value. Calibration experiments involve preparing samples of different materials, applying a known stress state, measuring the corresponding spatial angle values, and determining the optimal preset critical angle through statistical analysis.

[0057] The identification results of macroscopic plastic flow channels need to be verified. Verification methods include comparing with metallographic observations, observing grain deformation in the channel region under a microscope to confirm the presence of plastic flow characteristics, and comparing with hardness test results, measuring Vickers hardness in the channel region to verify whether hardness changes occur. Only when both metallographic and hardness test results indicate the presence of plastic deformation can the identified region be confirmed as a valid macroscopic plastic flow channel. The verification process also requires checking the continuity of the channel to ensure there are no false channels caused by data noise.

[0058] After identifying the macroscopic plastic flow channels, the identification results need to be overlaid and analyzed with the electron beam correction area. The distribution density of the macroscopic plastic flow channels within the electron beam correction area is analyzed, and the number of channels per unit area is calculated. Simultaneously, the positional relationship between the macroscopic plastic flow channels and the electron beam correction area is analyzed to determine whether the channels are completely within the correction area. For channels partially located outside the correction area, the proportion exceeding the range needs to be recorded. These analytical results are used for subsequent process optimization; for example, when the channel distribution density is too high, the electron beam scanning path needs to be adjusted to cover more areas.

[0059] The spatial orientation data of the macroscopic plastic flow channels is used for subsequent electron beam scanning path planning. By analyzing the relative relationship between the channel orientation and the electron beam scanning direction, the scanning path can be optimized to more effectively act on the plastic flow channels. For example, when the channel orientation is perpendicular to the scanning direction, the scanning path needs to be adjusted to form a certain angle with the channel orientation to enhance the correction effect. Distribution range data is used for process parameter optimization. Based on the size of the macroscopic plastic flow channels, the electron beam power and scanning speed are adjusted. For example, for channels with a large distribution range, the electron beam power needs to be increased to ensure sufficient heat input; for channels with a small distribution range, the power can be appropriately reduced to avoid overheating.

[0060] The entire identification process requires quality control. This includes checking whether the number of identified macroscopic plastic flow channels is within a reasonable range; for example, for a 1-square-meter electron beam correction area, the number of identified channels is typically between 5 and 20. The uniformity of channel distribution must be checked to avoid over-concentration of channels. The completeness of the channel data must also be checked to ensure that each channel has its complete spatial orientation and distribution range information recorded. Quality control also includes checking intermediate results during the calculation process, such as whether the magnitude of the stress gradient direction vector is within a reasonable range and whether the spatial angle calculation is accurate.

[0061] The final output of macroscopic plastic flow channel data includes channel number, spatial orientation vector, distribution range polygon, channel area, and channel volume. This data is stored in a structured format for easy subsequent analysis. A channel distribution map is also generated, visually displaying the spatial distribution of macroscopic plastic flow channels within the electron beam correction region, providing a visual reference for process optimization. The output data also needs to include parameter settings from the identification process, such as preset critical angle values ​​and mesh size information, to facilitate traceability and reproduction.

[0062] During the identification process, it is also necessary to pay attention to handling anomalies. When the welding residual stress gradient distribution data is missing, interpolation methods are used to complete the data before calculation. When the electron beam scanning direction is unclear, the direction of the electron beam thermal tension vector is determined by referring to the default scanning path. When anomalies occur in the spatial angle calculation results, the vector coordinates are checked for accuracy, and the calculation is recalculated. These measures ensure the stability and reliability of the identification process. Anomaly handling also includes reviewing the identification results. For example, when the number of identified channels is abnormally high or low, it is necessary to check whether the preset critical angle is set reasonably or whether there are data quality issues.

[0063] The accuracy of identifying macroscopic plastic flow channels is evaluated through repeated calculations. For example, the same set of data is used to perform the identification operation three times, comparing the number and location of channels identified each time to ensure consistency of results. If the results differ significantly, the identification parameters need to be adjusted or the data quality needs to be checked. The identification accuracy is also verified by comparing it with actual deformation measurement data, such as comparing the positional relationship between the channel locations and the actual deformation areas, to ensure that the identification results are consistent with the actual physical phenomena.

[0064] After completing all identification and verification steps, the macroscopic plastic flow channel data can be used for subsequent electron beam scanning path planning and process parameter optimization. This data provides the foundation for precise control of the electron beam correction process, ensuring that the correction effect achieves the expected goals. The entire identification process realizes a complete conversion from weld residual stress gradient distribution data to macroscopic plastic flow channels, providing reliable technical support for weld deformation control.

[0065] S5. Based on the distribution characteristics of the macroscopic plastic flow channels, plan the scanning path of the electron beam within the electron beam correction region and optimize the initial electron beam process parameters. Specifically, the implementation is as follows: In planning the electron beam scanning path and optimizing the initial electron beam process parameters based on the distribution characteristics of macroscopic plastic flow channels, the electron beam scanning path is first planned based on the spatial orientation of the macroscopic plastic flow channels. The spatial orientation data of the macroscopic plastic flow channels comes from the output of the previous steps and is stored in vector form, with each vector representing the main extension direction of a macroscopic plastic flow channel. The electron beam scanning path planning adopts a path generation algorithm, which uses the spatial orientation vector of the macroscopic plastic flow channels as input parameters to calculate the main direction of the electron beam scanning path, so that the main direction of the electron beam scanning path forms a preset angle with the spatial orientation of the macroscopic plastic flow channels. The preset angle is determined based on material properties and deformation correction requirements. For example, through experimental statistical analysis of the stress release effect of different materials under electron beam heating, it was found that for low-carbon steel, the correction effect is best when the preset angle is set to 45 degrees; for high-strength steel, a preset angle of 60 degrees can effectively avoid crack generation. During the planning process, it is necessary to ensure that the electron beam scanning path covers all areas where macroscopic plastic flow channels are located, while avoiding path overlap or omission. The electron beam scanning path consists of a series of continuous point coordinates. The spacing between adjacent points is determined by the electron beam spot diameter. For example, when the electron beam spot diameter is 0.5 mm, the point spacing is set to 0.3 mm. The generation of the electron beam scanning path also includes path smoothing processing, using a Bezier curve algorithm to smooth the path and ensure smooth speed changes during electron beam movement.

[0066] The electron beam power value in the initial electron beam process parameters is adjusted based on the distribution range density of the macroscopic plastic flow channels. The distribution range density of the macroscopic plastic flow channels is obtained by calculating the ratio of the total area of ​​the macroscopic plastic flow channels to the total area of ​​the electron beam correction region. During calculation, the distribution range polygon of each channel is first extracted from the macroscopic plastic flow channel data, the area of ​​the polygon is calculated, and then summed to obtain the total area of ​​the macroscopic plastic flow channels. The total area of ​​the electron beam correction region is obtained from the electron beam correction region data. The distribution range density value is obtained by dividing the total area of ​​the macroscopic plastic flow channels by the total area of ​​the electron beam correction region. The preset density threshold is determined based on the material's heat input requirements and deformation correction effect. For example, experimental statistics show that when the distribution range density is higher than 0.6, the electron beam power value needs to be increased; when the distribution range density is lower than 0.4, the electron beam power value needs to be decreased. The adjustment of the electron beam power value uses a linear interpolation method. For example, when the distribution range density is 0.7, the electron beam power value is increased by 15% from the initial value; when the distribution range density is 0.3, the electron beam power value is decreased by 10%. The adjustment of electron beam power also needs to take into account the influence of material thickness. The material thickness data is obtained from the three-dimensional model. For areas with a thickness greater than 10 mm, an additional 5% electron beam power value is added on top of the adjustment based on the distribution range density.

[0067] Simultaneously, the electron beam scanning speed parameter value is adjusted according to the number of macroscopic plastic flow channels identified. The number of identified macroscopic plastic flow channels is directly read from the macroscopic plastic flow channel data, representing the total number of macroscopic plastic flow channels identified within the electron beam correction area. The adjustment of the electron beam scanning speed parameter value is based on the comparison between the number of identified channels and a preset threshold. The preset threshold is set according to the size and material properties of the electron beam correction area; for example, for an electron beam correction area of ​​1 square meter, the preset threshold is set to 10 channels. When the number of identified macroscopic plastic flow channels is higher than the preset threshold, the electron beam scanning speed parameter value is reduced to ensure sufficient heat input; when the number of identified macroscopic plastic flow channels is lower than the preset threshold, the electron beam scanning speed parameter value is increased to avoid overheating. The adjustment range of the electron beam scanning speed parameter value is determined by a lookup table method; for example, when the number of identified channels is 15, the electron beam scanning speed parameter value is reduced by 20%; when the number of identified channels is 5, the electron beam scanning speed parameter value is increased by 15%. The adjustment of the electron beam scanning speed parameter also needs to take into account the size characteristics of the macroscopic plastic flow channel. For macroscopic plastic flow channels with an area of ​​more than 100 square millimeters, the electron beam scanning speed parameter should be reduced by 10% on the basis of the adjustment based on the number of recognitions.

[0068] During electron beam scanning path planning, the uniformity of the distribution of macroscopic plastic flow channels also needs to be considered. Distribution uniformity is evaluated by calculating the density variance of macroscopic plastic flow channels in each sub-region within the electron beam correction area. First, the electron beam correction area is divided into multiple sub-regions, each 10 cm by 10 cm in size. Then, the distribution density of macroscopic plastic flow channels within each sub-region is calculated, and finally, the variance of the distribution density across all sub-regions is calculated. When the variance exceeds a preset uniformity threshold, the distribution of the electron beam scanning path needs to be adjusted, for example, by increasing the density of the scanning path in higher-density sub-regions. The preset uniformity threshold is set according to the required correction effect, for example, 0.05. Adjustment of the electron beam scanning path also includes path direction optimization, ensuring that the direction of the electron beam scanning path intersects the channel orientation at multiple different angles in areas with dense macroscopic plastic flow channels to enhance stress release.

[0069] Adjusting the electron beam power also requires optimization based on the material's thermophysical properties. These properties include thermal conductivity and specific heat capacity, parameters retrieved from a material property database. For materials with high thermal conductivity, the increase in electron beam power is appropriately increased based on density adjustments within the distribution range; for materials with high specific heat capacity, the decrease in electron beam power is appropriately decreased. For example, when the material's thermal conductivity exceeds 50 W / m Kelvin, the increase in electron beam power is increased by 5%; when the material's specific heat capacity exceeds 500 J / kg Kelvin, the decrease in electron beam power is decreased by 5%.

[0070] The adjustment of the electron beam scanning speed parameter also needs to consider the geometry of the electron beam correction area. For irregularly shaped electron beam correction areas, the electron beam scanning speed parameter needs to be adjusted according to the area boundary, reducing the electron beam scanning speed parameter near the boundary to ensure that the edge area is sufficiently heated. The adjustment of the electron beam scanning speed parameter is achieved through a piecewise function. For example, in areas less than 5 mm from the boundary, the electron beam scanning speed parameter is reduced by 10%; in the central area, the electron beam scanning speed parameter remains unchanged.

[0071] After completing the electron beam scanning path planning and process parameter optimization, the results need to be converted into an instruction format executable by the electron beam welding equipment. The electron beam scanning path is converted into a series of continuous coordinate points, and the movement speed between these points is set according to the electron beam scanning speed parameter value. The electron beam power value and electron beam scanning speed parameter value are written into the process parameter file in a standard text format, including the parameter name, value, and unit. All optimized parameters need to be verified to ensure they are within the equipment's allowable range; for example, the electron beam power value does not exceed the equipment's maximum power, and the electron beam scanning speed parameter value is not lower than the equipment's minimum speed. The verification process includes parameter range checks and logical consistency checks to ensure that the combination of electron beam power value and electron beam scanning speed parameter value will not cause equipment overload or calibration failure.

[0072] Simulation verification is also required during the planning process. A thermodynamic simulation model is used to simulate the electron beam scanning process and predict temperature distribution and stress changes. The simulation model takes the electron beam scanning path and optimized initial electron beam process parameters as input to calculate the temperature and stress fields within the electron beam correction region. The simulation results are used to verify the rationality of the electron beam scanning path and process parameters, such as ensuring that the peak temperature does not exceed the material's melting point and that the cooling rate is within a reasonable range. If the simulation results do not meet the requirements, the electron beam scanning path or process parameters need to be readjusted until the expected correction effect is achieved. Simulation verification also includes heat-affected zone assessment to ensure that electron beam heating does not cause adverse changes in the material microstructure.

[0073] The final output electron beam scanning path and optimized initial electron beam process parameters include the electron beam scanning path coordinate sequence, electron beam power value, electron beam scanning speed parameter value, and other relevant parameters. This data is stored in a structured format and transmitted to the electron beam welding control system for controlling the actual electron beam correction operation. Simultaneously, a process report is generated, recording all parameters and adjustment logic used during the planning process, facilitating subsequent traceability and analysis. The process report includes an analysis of the distribution characteristics of the macroscopic plastic flow channel, the basis for electron beam scanning path planning, the process parameter optimization process, and simulation verification results, ensuring the transparency and repeatability of the entire process.

[0074] S6. Control the electron beam welding equipment to perform scanning heating operations on the electron beam correction area according to the scanning path and optimized initial electron beam process parameters. The specific implementation is as follows: In the process of controlling the electron beam welding equipment to perform scanning and heating operations on the electron beam correction area according to the scanning path and optimized initial electron beam process parameters, the planned scanning path must first be converted into a sequence of control commands that the electron beam welding equipment can recognize. The planned scanning path, derived from the output of previous steps, consists of a series of continuous three-dimensional coordinate points. The spacing between these points is determined based on the electron beam spot diameter and scanning accuracy requirements; for example, when the electron beam spot diameter is 0.5 mm, the spacing between coordinate points is set to 0.3 mm. The generation of the control command sequence employs a code conversion algorithm, which converts each coordinate point into a movement command executable by the electron beam welding equipment. The movement command format follows the international standard G-code specification, including coordinate position, movement speed, and acceleration parameters. For example, for a straight scanning path, a G01 command is generated specifying the target coordinates and feed rate; for a curved scanning path, a G02 or G03 command is generated specifying the center coordinates and arc radius. The control command sequence also includes equipment start / stop commands and parameter setting commands to ensure that the electron beam welding equipment completes initialization before scanning and executes a safety shutdown procedure after scanning. The control command sequence is stored in text file format and transmitted to the CNC system of the electron beam welding equipment via a communication interface. During the conversion process, it is necessary to verify the completeness and correctness of the control command sequence, such as checking whether the coordinate points are continuous and whether the command format meets the equipment requirements. If errors or omissions are found, the control command sequence is regenerated.

[0075] Configure the power output unit and scanning control unit of the electron beam welding equipment according to the optimized initial electron beam process parameters. These optimized initial electron beam process parameters are derived from the outputs of previous steps, including electron beam power, electron beam scanning speed, and electron beam focusing current. The power output unit is configured by adjusting the cathode voltage and beam current intensity of the electron beam generator. For example, when the electron beam power is 3000 watts, the cathode voltage is set to 60 kV and the beam current intensity to 50 mA. The scanning control unit is configured by setting the scanning coil current and deflection sensitivity. For instance, the driving current of the scanning coil is calculated based on the electron beam scanning speed parameter; when the electron beam scanning speed parameter is 10 mm / s, the driving current of the scanning coil is set to 100 mA. After all parameters are set, their correctness must be verified through the equipment's self-test program to ensure that the electron beam power is within the equipment's rated range, the electron beam scanning speed parameter does not exceed the equipment's maximum scanning speed, and the electron beam focusing current matches the electron beam power. If the self-test detects abnormal parameters, such as the electron beam power value exceeding the maximum allowable value of the equipment, the parameters will be automatically adjusted to a safe range and the adjustment log will be recorded.

[0076] Segmented progressive scanning heating is performed along the scanning path within the electron beam correction area. After completing the current segment's scanning heating, a preset interval is paused before continuing with the next segment's scanning heating, until the entire electron beam correction area is scanned and heated. The segmented progressive scanning heating is achieved by first dividing the scanning path into multiple continuous segments. The segment length is determined based on the material's thermal conductivity and electron beam energy density; for example, for steel, the segment length is set to 5 mm; for aluminum alloy, the segment length is set to 3 mm. The preset interval time is set based on the material's cooling rate and heat accumulation effect. For example, through thermal simulation analysis, the preset interval time is set to 2 seconds when the material thickness is 5 mm, and 5 seconds when the material thickness is 10 mm. Each segment's scanning heating operation includes three steps: electron beam positioning, energy output, and movement control. Electron beam positioning ensures the beam spot accurately reaches the segment's starting point; energy output releases heat energy according to the set electron beam power value; and movement control moves along the segment path at a constant electron beam scanning speed parameter value. During pauses between segments, the electron beam remains in standby mode, with power output reduced to a maintenance level, such as 10% of the rated power, to avoid unnecessary heat input. The entire scanning and heating process is tracked in real-time by a monitoring system to ensure each segment is completed as planned. If any abnormalities are detected, such as excessive temperature or positional deviation, operation is immediately interrupted and corrective measures are implemented. After all segments have been scanned and heated, the electron beam welding equipment automatically executes a cooling program, gradually reducing power output until it is completely shut down. Simultaneously, an operation report is generated recording the actual parameters used and the execution results.

[0077] During the segmented, progressive scanning heating process, the impact of environmental factors on the heating effect must also be considered. Ambient temperature and humidity are monitored in real time by sensors. When the ambient temperature exceeds a preset temperature threshold or the ambient humidity exceeds a preset humidity threshold, the electron beam power or preset interval time is adjusted to compensate for the environmental impact. The preset temperature threshold is set according to the equipment's operating environment requirements, for example, 35 degrees Celsius; the preset humidity threshold is set according to the equipment's moisture-proof requirements, for example, 70%. The adjustment method is based on a pre-established compensation model. For example, when the ambient temperature increases by 5 degrees Celsius, the electron beam power is reduced by 3%; when the ambient humidity increases by 10%, the preset interval time is extended by 5%.

[0078] The real-time monitoring system of the electron beam welding equipment includes temperature sensors, position sensors, and energy sensors to collect key data during the scanning heating process. The temperature sensor measures the temperature distribution on the surface of the electron beam correction area, the position sensor detects the actual position of the electron beam focal point, and the energy sensor monitors the stability of the electron beam energy output. The monitoring data is compared with preset parameters. If the deviation exceeds the allowable range, such as a temperature deviation exceeding 50 degrees Celsius or a position deviation exceeding 0.1 millimeters, an alarm is triggered, and operation is paused, awaiting manual intervention or automatic adjustment.

[0079] After completing the scanning and heating operation, an effect evaluation is required. This evaluation is achieved by comparing deformation data before and after the scanning and heating process. A 3D scanning device is used to re-acquire surface point cloud data of the electron beam correction area, which is then compared with the original design model to calculate the residual deformation. If the residual deformation exceeds the allowable value, for example, more than 0.5 mm, it is marked as insufficient correction, requiring replanning of the scanning path and process parameters for supplementary correction. The effect evaluation report includes a comparison of deformation before and after correction, statistics on residual deformation, and a correction efficiency analysis, providing a reference for subsequent process optimization.

[0080] Throughout the entire control process, all operational steps and parameter adjustments are recorded in a log file, including timestamps, operation types, parameter values, monitoring data, and abnormal events. The log file is used for traceability and analysis, ensuring the repeatability and auditability of the process. Simultaneously, the electron beam welding equipment undergoes regular maintenance and calibration, such as monthly accuracy checks of the power output unit and scanning control unit, ensuring long-term stable operation of the equipment.

[0081] All calculations involved in the embodiments are dimensionless numerical calculations, and the preset parameters and thresholds in the calculations are set by those skilled in the art according to the actual situation.

[0082] It should be noted that this invention can be deployed on the device itself to realize embedded applications, or it can run on a PC or other terminal with a user interface, thereby meeting various hardware environments and usage requirements.

[0083] The above embodiments can be implemented, in whole or in part, by software, hardware, firmware, or any other combination thereof. When implemented using software, the above embodiments can be implemented, in whole or in part, as a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, all or part of the processes or functions described in the embodiments of this application are generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wireless or wired transmission; wired transmission methods include optical fiber, twisted pair, coaxial cable, etc.; wireless transmission includes infrared, microwave, etc. The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center containing one or more sets of available media. The available medium can be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium. A semiconductor medium can be a solid-state drive.

[0084] Those skilled in the art will understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and modules described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0085] In the several embodiments provided in this application, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of modules is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple modules or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between apparatuses or modules may be electrical, mechanical, or other forms.

[0086] The modules described as separate components may or may not be physically separate. The components shown as modules may or may not be physical modules; they may be located in one place or distributed across multiple network modules. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs.

[0087] In addition, the functional modules in the various embodiments of this application can be integrated into one processing module, or each module can exist physically separately, or two or more modules can be integrated into one module.

[0088] If the aforementioned functions are implemented as software functional modules and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0089] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

[0090] In conclusion, the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for controlling and correcting welding deformation of a forklift mast, characterized in that, include: S1. Obtain the 3D model and actual deformation measurement data of the forklift mast component to be corrected; S2. Determine the electron beam correction area and initial electron beam process parameters based on the three-dimensional model and actual deformation measurement data; S3. Within the electron beam correction region, the electron beam focusing current is changed systematically and the drift characteristics of the corresponding focal position are monitored to establish a mapping relationship between the focal drift characteristics and the welding residual stress state, so as to characterize the welding residual stress gradient distribution in the electron beam correction region. S4. Analyze the spatial correspondence between the stress gradient direction and the electron beam thermal tension vector direction in the distribution of welding residual stress gradient, and identify the macroscopic plastic flow channels formed due to the tendency of the stress gradient direction and the thermal tension vector direction to be consistent. S5. Based on the distribution characteristics of the macroscopic plastic flow channels, plan the scanning path of the electron beam in the electron beam correction region and optimize the initial electron beam process parameters. S6. Control the electron beam welding equipment to perform scanning heating operations on the electron beam correction area according to the scanning path and optimized initial electron beam process parameters.

2. The method for controlling and correcting welding deformation of a forklift mast according to claim 1, characterized in that, Obtain the 3D model and actual deformation measurement data of the forklift mast component to be corrected, including: The surface point cloud data of the gantry components is collected by a 3D scanning device, and the surface point cloud data is compared and analyzed with the original design model. Actual deformation measurement data are generated based on the deviation data obtained from the comparative analysis. The actual deformation measurement data and the original design model are combined to form an integrated three-dimensional model.

3. The method for controlling and correcting welding deformation of a forklift mast according to claim 1, characterized in that, The electron beam correction region and initial electron beam process parameters were determined based on the 3D model and actual deformation measurement data, including: Analyze the strain concentration regions in the actual deformation measurement data, and mark the regions in the strain concentration regions that exceed a preset threshold as electron beam correction regions; Simultaneously, based on the material thickness and material properties corresponding to the electron beam correction area in the 3D model, the corresponding electron beam power range and scanning speed range are matched from the pre-established process parameter database as the initial electron beam process parameters.

4. The method for controlling and correcting welding deformation of a forklift mast according to claim 1, characterized in that, Within the electron beam correction region, the electron beam focusing current is systematically changed, and the drift characteristics of the corresponding focal position are monitored. A mapping relationship between the focal drift characteristics and the welding residual stress state is established to characterize the welding residual stress gradient distribution within the electron beam correction region, including: Within the electron beam correction area, the electron beam focusing current is continuously adjusted according to a preset step size, and the electron beam focal point position coordinates corresponding to each focusing current value are recorded. The maximum offset of the electron beam focal position coordinates within the range of focusing current variation is used as the focal drift characteristic parameter; By comparing the correspondence between the focus drift characteristic parameters and the pre-calibrated stress parameters, a quantitative mapping relationship between the focus drift characteristic parameters and the welding residual stress state is established. Based on the quantization mapping relationship, the focus drift characteristic parameters of each measurement point in the electron beam correction area are converted into welding residual stress gradient distribution data.

5. The method for controlling and correcting welding deformation of a forklift mast according to claim 4, characterized in that, By comparing the correspondence between the focus drift characteristic parameters and the pre-calibrated stress parameters, a quantitative mapping relationship between the focus drift characteristic parameters and the welding residual stress state is established. This includes: measuring the focus drift characteristic parameters on a calibration sample with a known welding residual stress state to obtain the pre-calibrated stress parameters; and using data fitting methods to correlate the focus drift characteristic parameters with the pre-calibrated stress parameters to establish a linear or nonlinear quantitative mapping relationship between the focus drift characteristic parameters and the welding residual stress state.

6. The method for controlling and correcting welding deformation of a forklift mast according to claim 1, characterized in that, Analyze the spatial correspondence between the stress gradient direction and the electron beam thermal tension vector direction in the residual welding stress gradient distribution, and identify the macroscopic plastic flow channels formed due to the convergence of the stress gradient direction and the thermal tension vector direction, including: The stress gradient direction vector of each grid node is calculated based on the welding residual stress gradient distribution data, and the direction of the electron beam thermal tension vector is determined according to the electron beam scanning direction. Calculate the spatial angle between the stress gradient direction vector and the electron beam thermal tension vector at each grid node; Continuous grid node regions with spatial angles less than a preset critical angle are identified as macroscopic plastic flow channels, and the spatial orientation and distribution range of the macroscopic plastic flow channels are recorded.

7. The method for controlling and correcting welding deformation of a forklift mast according to claim 6, characterized in that, The calculation of the spatial angle between the stress gradient direction vector and the electron beam thermal tension vector at each grid node includes: extracting the stress gradient direction vector coordinates of each grid node based on the welding residual stress gradient distribution data; determining the electron beam thermal tension vector direction coordinates according to the electron beam scanning direction; and calculating the spatial angle between the stress gradient direction vector and the electron beam thermal tension vector direction through vector dot product operation.

8. The method for controlling and correcting welding deformation of a forklift mast according to claim 1, characterized in that, Based on the distribution characteristics of the macroscopic plastic flow channels, the scanning path of the electron beam within the electron beam correction region is planned and the initial electron beam process parameters are optimized, including: Based on the spatial orientation of the macroscopic plastic flow channel, the electron beam scanning path is planned so that its main direction forms a preset angle with the spatial orientation of the macroscopic plastic flow channel; Adjust the electron beam power value in the initial electron beam process parameters according to the distribution range and density of the macroscopic plastic flow channels; Simultaneously, the electron beam scanning speed parameter value is adjusted accordingly based on the number of macroscopic plastic flow channels identified.

9. A method for controlling and correcting welding deformation of a forklift mast according to claim 8, characterized in that, Adjusting the electron beam power value in the initial electron beam process parameters based on the distribution range density of the macroscopic plastic flow channel includes: calculating the distribution range density of the macroscopic plastic flow channel within the electron beam correction region; increasing the electron beam power value when the distribution range density is higher than a preset density threshold; and decreasing the electron beam power value when the distribution range density is lower than a preset density threshold.

10. The method for controlling and correcting welding deformation of a forklift mast according to claim 1, characterized in that, The electron beam welding equipment is controlled to perform scanning heating operations on the electron beam correction area according to the scanning path and optimized initial electron beam process parameters, including: The planned scanning path is converted into a sequence of control commands that can be recognized by the electron beam welding equipment; Set the power output unit and scanning control unit of the electron beam welding equipment according to the optimized initial electron beam process parameters; Segmented progressive scanning heating is performed along the scanning path within the electron beam correction area. After completing the current segment of scanning heating, the process pauses for a preset interval before continuing with the next segment of scanning heating, until the scanning heating operation of the entire electron beam correction area is completed.

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