A method and system for stamping die trial fitting control

Abstract

The present invention discloses a control method and system for stamping die trial fitting and adjustment. The method includes scanning the actual surface of the stamping die to generate actual three-dimensional point cloud data; determining the difference value according to the actual three-dimensional point cloud data and the virtual three-dimensional point cloud data; determining the first area to be repaired according to the difference value and the preset tolerance range; predicting the contact area and pressure distribution between the stamping die and the stamping part during the actual stamping process based on the preset virtual fitting simulation model to simulate the deformation of the stamping part under different pressures; determining the second area to be repaired according to the contact area and pressure distribution; determining the area to be polished according to the first area to be repaired and the second area to be repaired; generating a polishing path according to the area to be polished by using a path planning algorithm; and controlling a polishing device to perform a polishing action on the stamping die according to the polishing path. To improve the efficiency of the entire trial fitting and adjustment process.

Description

Technical Field

[0001] The present invention relates to the technical field of mold processing control, and particularly to a control method and system for trial fitting of stamping molds. Background Art

[0002] During the processing and assembly of molds, due to processing errors and assembly errors, there are often certain deviations between the actual formed surface of the mold and the ideal surface designed. Especially when there are large curvature changes on the mold surface, the deviation may be more obvious. To ensure that the mold can process stamping parts meeting the design requirements, the mold usually needs to go through the trial fitting process.

[0003] However, in the analysis process of the existing trial fitting methods, it is mostly carried out by engineering personnel based on experience, with strong subjectivity, being greatly affected by human factors, and due to the need for multiple mold closings, grindings, and re - mold closings for repeated confirmation, the trial fitting process takes a long time and has low efficiency. Summary of the Invention

[0004] To solve at least one of the above - mentioned technical problems, the present invention provides a control method and system for trial fitting of stamping molds.

[0005] In a first aspect, the present invention provides a control method for trial fitting of stamping molds, the method comprising:

[0006] Obtain the 3D geometric data of the ideal surface of the stamping mold, perform meshing processing on the 3D geometric data, and discretize the continuous surface into virtual three - dimensional point cloud data;

[0007] Use a three - dimensional scanning device to scan the actual surface of the stamping mold to generate actual three - dimensional point cloud data;

[0008] Determine the difference value according to the actual three - dimensional point cloud data and the virtual three - dimensional point cloud data;

[0009] Determine the first area to be repaired according to the difference value and the preset tolerance range;

[0010] Based on a preset virtual mold - closing simulation model, simulate the deformation of the stamping part under different pressures, and predict the contact area and pressure distribution between the stamping mold and the stamping part during the actual stamping process;

[0011] Determine the second area to be repaired according to the contact area and the pressure distribution;

[0012] Determine the area to be polished according to the first area to be repaired and the second area to be repaired;

[0013] Adopt a path planning algorithm to generate a polishing path according to the area to be polished;

[0014] Control the grinding equipment to perform a grinding action on the stamping die according to the grinding path.

[0015] Preferably, scan the actual surface of the stamping die to generate actual three-dimensional point cloud data, including:

[0016] Calculate the curvature value of each sampling point based on the 3D geometric data;

[0017] Divide the area to be scanned into a high-curvature area and a low-curvature area according to the curvature value;

[0018] Scan the high-curvature area and the low-curvature area along a preset scanning path multiple times;

[0019] Perform registration and fusion processing on the multiple scanning results to obtain actual three-dimensional point cloud data.

[0020] Preferably, it further includes:

[0021] Calculate the surface normal vector of the stamping die in real time according to the current scanning point;

[0022] Determine the scanning angle of the three-dimensional scanning device according to the surface normal vector; wherein, the three-dimensional scanning device is perpendicular to the surface normal vector;

[0023] Determine the distance between the three-dimensional scanning device and the surface of the stamping die according to the surface concavity and convexity of the stamping die.

[0024] Preferably, determine the difference value according to the actual three-dimensional point cloud data and the virtual three-dimensional point cloud data, including:

[0025] Use a point cloud feature extraction algorithm to perform a preliminary alignment on the actual three-dimensional point cloud data and the virtual three-dimensional point cloud data to obtain a preliminary alignment result;

[0026] According to the preliminary alignment result, perform a secondary point cloud alignment operation using the iterative closest point algorithm to obtain a final alignment result;

[0027] According to the final alignment result, calculate the normal vector difference and geometric distance difference of each point in the actual three-dimensional point cloud data after the secondary point cloud alignment operation;

[0028] Determine the difference value according to the normal vector difference and the geometric distance difference.

[0029] Preferably, determine the first area to be repaired according to the difference value and a preset tolerance range, including:

[0030] Use a color mapping algorithm to convert the difference value into a color map;

[0031] On the point cloud surface, the Gaussian curvature and mean curvature of each point are calculated by locally fitting the quadratic surface;

[0032] Determining a first profile deviation region according to the color map, the Gaussian curvature and the average curvature;

[0033] Based on the preset tolerance range, a first area to be repaired is determined from the first profile deviation area.

[0034] Preferably, determining the second area to be repaired according to the contact area and the pressure distribution includes:

[0035] Determining a second profile deviation area according to the contact area and the pressure distribution;

[0036] An actual mold closing result of the stamping die is obtained, and the second molding surface deviation area is corrected according to the actual mold closing result to determine the second area to be repaired.

[0037] Preferably, before the step of simulating the deformation of the stamping part under different pressures based on the preset virtual joint simulation model and predicting the contact area and pressure distribution between the stamping die and the stamping part during the actual stamping process, the method further includes:

[0038] The preset virtual mold simulation model is constructed using the actual three-dimensional point cloud data and stamping process parameters of the stamping die.

[0039] Preferably, simulating the deformation of the stamping part under different pressures based on a preset virtual joint simulation model and predicting the contact area and pressure distribution between the stamping die and the stamping part during the actual stamping process include:

[0040] Finite element meshing of dies and stampings;

[0041] Defining boundary conditions during the stamping process; wherein the boundary conditions include the magnitude of the stamping force and the contact conditions between the stamping die and the stamping part;

[0042] The deformation process of the stamping part is simulated by static nonlinear analysis to obtain the pressure distribution and contact conditions between the stamping die and the stamping part;

[0043] A virtual mold closing result is generated according to the pressure distribution and the contact condition, and a high-pressure contact area between the stamping die surface and the stamping part and a non-contact area with a large deviation are identified.

[0044] Preferably, a path planning algorithm is used to generate a grinding path according to the area to be polished, including:

[0045] Calculating the surface curvature and roughness of each point on the surface of the area to be polished of the stamping die;

[0046] Partition the area to be polished according to the difference value, the surface curvature, and the roughness;

[0047] Construct a density field of the area to be polished in three-dimensional space according to the difference value, the surface curvature, and the roughness, and map the deviation and curvature features to density values; wherein, the larger the density value, the denser the path required for the area;

[0048] Generate a corresponding polishing path according to the density field.

[0049] In a second aspect, the present invention further provides a stamping die trial assembly control system, and the system includes:

[0050] An acquisition module, configured to acquire 3D geometric data of the ideal surface of the stamping die, perform grid processing on the 3D geometric data, and discretize the continuous surface into virtual three-dimensional point cloud data;

[0051] A first generation module, configured to use a three-dimensional scanning device to scan the actual surface of the stamping die to generate actual three-dimensional point cloud data;

[0052] A first determination module, configured to determine a difference value according to the actual three-dimensional point cloud data and the virtual three-dimensional point cloud data;

[0053] A second determination module, configured to determine a first area to be repaired according to the difference value and a preset tolerance range;

[0054] A prediction module, configured to simulate the deformation of the stamping part under different pressures based on a preset virtual simulation model, and predict the contact area and pressure distribution between the stamping die and the stamping part during the actual stamping process;

[0055] A third determination module, configured to determine a second area to be repaired according to the contact area and the pressure distribution;

[0056] A fourth determination module, configured to determine an area to be polished according to the first area to be repaired and the second area to be repaired;

[0057] A second production module, configured to use a path planning algorithm to generate a polishing path according to the area to be polished;

[0058] A control module, configured to control a polishing device to perform a polishing action on the stamping die according to the polishing path.

[0059] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0060] 1) The stamping die trial fitting control method provided by the present invention first calculates based on the actual three-dimensional point cloud data and virtual three-dimensional point cloud data of the stamping die, so as to specifically compare and analyze the actual surface and ideal surface of the stamping die to determine the first area to be repaired. Since the parameters in die design are based on the ideal state, and there will be certain errors in actual production and processing, the present invention takes into account the difference between the actual surface data after actual forming and the ideal surface data, thereby accurately determining the first area to be repaired, reducing the dependence on the experience of engineering personnel, reducing the influence of human subjective factors on the trial fitting process, and improving the accuracy of data and the accuracy of subsequent grinding operations.

[0061] 2) The present invention simulates the deformation of the stamping part under different pressures according to a preset virtual closing simulation model, predicts the contact area and pressure distribution between the stamping die and the stamping part during the actual stamping process, and determines the second area to be repaired according to the contact area and the pressure distribution; since performing the actual closing operation requires a large amount of manpower, material resources and time costs, the present invention conducts actual closing simulation by constructing a preset virtual closing simulation model, thereby determining the second area to be repaired, which can effectively improve the working efficiency of trial fitting and reduce the manpower, material resources and time costs of trial fitting operations.

[0062] 3) After determining the first area to be repaired and the second area to be repaired, the present invention determines the area to be ground according to the first area to be repaired and the second area to be repaired; uses a path planning algorithm to generate a grinding path according to the area to be ground; controls a grinding device to perform a grinding action on the stamping die according to the grinding path. The present invention combines the first area to be repaired and the second area to be repaired, thereby accurately identifying the area to be ground of the stamping die, generating a grinding path according to the area to be ground, improving the grinding efficiency and grinding accuracy, realizing the refined control of grinding parameters during the grinding process, ensuring the accuracy of the die grinding process, especially for areas with large curvature changes, the surface modification amount can be more accurately controlled, improving the correction success rate of this die, greatly shortening the time of repeated grinding and verification, thereby further improving the efficiency of the entire trial fitting process, achieving an efficient and accurate die correction effect, significantly reducing manual intervention, and improving the accuracy and efficiency of die trial fitting.

[0063] It should be understood that the above general description and the following detailed description are only exemplary and explanatory, and do not limit the present disclosure. Brief Description of the Drawings

[0064] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the background art, the following will describe the drawings required to be used in the embodiments of the present invention or the background art.

[0065] The accompanying drawings here are incorporated into the specification and form a part of this specification. These drawings illustrate embodiments consistent with the present disclosure and, together with the specification, are used to explain the technical solutions of the present disclosure.

[0066] Figure 1 It is a schematic flowchart of a method for controlling the trial fitting of a stamping die provided by an embodiment of the present invention. Detailed implementation manners

[0067] To enable those skilled in the art to better understand the solution of the present invention, the following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to 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 making creative efforts fall within the scope of protection of the present invention.

[0068] The terms "first", "second", etc. in the specification and claims of the present invention and the above accompanying drawings are used to distinguish different objects, rather than to describe a specific order. In addition, the terms "comprising" and "having" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or device that includes a series of steps or units is not limited to the listed steps or units, but optionally further includes steps or units not listed, or optionally further includes other steps or units inherent to these processes, methods, products, or devices.

[0069] Referring to "embodiment" herein means that a specific feature, structure, or characteristic described in connection with the embodiment can be included in at least one embodiment of the present invention. The phrase appears in various places in the specification and does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment mutually exclusive with other embodiments. Those skilled in the art will explicitly and implicitly understand that the embodiments described herein can be combined with other embodiments.

[0070] In addition, to better illustrate the present invention, numerous specific details are given in the following detailed implementation manners. Those skilled in the art should understand that the present invention can still be implemented without some specific details. In some instances, methods, means, elements, and circuits well-known to those skilled in the art are not described in detail to highlight the gist of the present invention.

[0071] Please refer to Figure 1 , Figure 1 It is a schematic flowchart of a method for controlling the trial fitting of a stamping die provided by an embodiment of the present invention. As Figure 1 shown, a method for controlling the trial fitting of a stamping die includes the following steps:

[0072] S10. Obtain the 3D geometric data of the ideal surface of the stamping die, perform meshing on the 3D geometric data, and discretize the continuous surface into virtual three-dimensional point cloud data;

[0073] In this embodiment, obtain the 3D geometric data of the ideal surface from the die design stage, perform meshing on the data of the ideal surface, and discretize the continuous surface into three-dimensional point cloud data to ensure that it can be compared with the actually scanned surface data. Specifically, import common 3D format files (such as STEP, IGES), and generate three-dimensional point cloud data from the continuous geometric model through a discretization algorithm for comparison with the actual scanned data; among them, for the ideal surface, a more refined adaptive mesh division technology can also be used, especially in areas with complex curvature, dividing more dense meshes to ensure that the accuracy can match the actually scanned data during subsequent comparison.

[0074] S20. Use a three-dimensional scanning device to scan the actual surface of the stamping die to generate actual three-dimensional point cloud data;

[0075] In this embodiment, after the die is processed and assembled, use a three-dimensional scanning device to scan the die surface to generate high-precision three-dimensional point cloud data, and preprocess the scanned point cloud to obtain the three-dimensional data of the actual die surface to ensure the integrity and accuracy of the data.

[0076] It should be noted that the preprocessing includes denoising, point cloud resampling, hole repair, etc. Specifically, through a statistical noise point filtering algorithm (such as a distance-based noise point deletion algorithm), remove the outlier points (i.e., large error points deviating from the surface) generated during the scanning process. To reduce the computational burden, perform voxel downsampling while maintaining surface details. Use a uniform voxel grid sampling algorithm to define the voxel size and compress the points falling within the same voxel into a central point. For areas that cannot be directly scanned, apply a surface reconstruction algorithm (such as the Poisson reconstruction algorithm) to perform local surface completion and generate complete three-dimensional point cloud data. By preprocessing the scanned point cloud, the integrity and accuracy of the data can be greatly ensured.

[0077] In one of the embodiments, scanning the actual surface of the stamping die to generate actual three-dimensional point cloud data includes:

[0078] S21. Calculate the curvature value of each sampling point based on the 3D geometric data;

[0079] In this embodiment, for each grid vertex or each point in the point cloud, calculate the curvature of this point. Multiple methods can be used to calculate the curvature, such as Gaussian curvature or mean curvature:

[0080] For each vertex, calculate the normal vector of the neighborhood of that point;

[0081] Gaussian curvature: In the formula, k 1 and k 2 are the principal curvatures, and A is the area of the local region;

[0082] Mean curvature:

[0083] Among them, the size of the neighborhood can be dynamically selected according to the size or complexity of the model;

[0084] S22. According to the curvature values, divide the area to be scanned into a high-curvature area and a low-curvature area;

[0085] In this embodiment, according to the magnitudes of the curvature values, divide the scanning area to form different scanning priority areas, including:

[0086] According to a preset curvature threshold, divide the scanning area into a high-curvature area and a low-curvature area;

[0087] Label each curvature area so as to adjust the scanning parameters in subsequent steps.

[0088] According to requirements, it also includes: before the start of each scanning frame, calculate the mean curvature value of the local region in real time and dynamically adjust the step size to set dynamic scanning step sizes for the high-curvature area and the low-curvature area:

[0089]

[0090] In the formula, C is a constant and K is the curvature value; ensure that for regions with larger curvatures, set smaller scanning step sizes (stepstep), and for regions with smaller curvatures, increase the step size.

[0091] S23. Scan the high-curvature area and the low-curvature area multiple times along a preset scanning path; specifically, it includes:

[0092] S231. For each partition, plan two or more scanning paths to obtain a preset scanning path; specifically: use a space-filling algorithm (such as serpentine scanning or spiral scanning) to generate the first scanning path; according to the first scanning path, generate the second scanning path in a relatively perpendicular direction or a relatively parallel direction; among them, the number of scanning times for each partition can be set according to requirements, for example: the number of scanning times for the high-curvature area is more than or equal to the number of scanning times for the low-curvature area;

[0093] S232. Collect data of the stamping die along the preset scanning path;

[0094] S233. Assign weights to each point in the acquired data according to the actual curvature value through a weighted filter; among them, for each point p in the point cloud i the curvature estimate K(p i ) of the neighborhood N(p i ) determines whether the point is a noise point. Using a curvature-based weighted filter includes: where w(p i ) is the weight and γ is the control parameter.

[0095] S234. Remove or correct the points with weights below the threshold to complete the noise reduction process.

[0096] In this embodiment, in terms of noise point removal, the curvature information is combined for processing, that is, more points are retained for regions with larger curvatures, while the points in smooth regions can be appropriately simplified. A local statistical filter based on curvature change is adopted. By performing weighted analysis on the neighborhood curvature of each point to determine whether it is a noise point. During the data processing process, a hierarchical reconstruction technology is introduced. First, a low-precision reconstruction is used to generate a quick contour, and then a high-precision supplement is performed on the local regions with complex curvatures, so as to improve the detail accuracy while ensuring efficiency.

[0097] In one of the embodiments, it further includes:

[0098] S2321. Calculate the surface normal vector of the stamping die in real time according to the current scanning point;

[0099] S2322. Determine the scanning angle of the 3D scanning device according to the surface normal vector; among them, the 3D scanning device is perpendicular to the surface normal vector;

[0100] S2323. Determine the distance between the 3D scanning device and the surface of the stamping die according to the surface concavity and convexity of the stamping die.

[0101] In this embodiment, the angle of the 3D scanning device is adjusted to be perpendicular to the normal vector of the point to minimize the projection error, and according to the concavity and convexity of the curved surface of the stamping die, the distance between the scanning head and the curved surface is adjusted in real time to keep the focal length consistent. By adjusting the angle and distance in real time to reduce the projection error, it is ensured that the scanning device can adapt to complex surfaces.

[0102] As needed, it further includes: calculating the moving speed and sampling interval of the 3D scanning device based on the curvature value; specifically: for the scanning path optimization of complex curved surfaces, the curvature K can be used as a control variable: where n is the normal vector and V is the surface speed. The moving speed v of the scanning head of the 3D scanning device s is adjusted according to the curvature K: Where α is an adjustment factor that controls the degree to which the moving speed of the scanning head changes with curvature. The point cloud data acquisition is planned through different planar perspectives, the sampling interval is set, and the point cloud data obtained from multiple planes is fused. Among them, it is assumed that the mold surface is discretized into a series of point clouds P on multiple planes, and each plane z = x i , the spacing of the sampling points (i.e., the sampling interval d i ) is determined by the curvature K: Where d i is the sampling interval, β is a control parameter, and d i is the sampling interval.

[0103] In this embodiment, a path planning algorithm based on surface curvature is used to adjust the angle and movement speed of the scanning head according to the change of the mold curvature, ensuring that the details of complex areas are fully captured, and the data is collected layer by layer in the form of layered slicing. The multi-plane scanning technology is used to intercept data from different heights. The spacing of each layer is determined by the curvature and local features. The spacing in more complex areas is smaller to improve the accuracy.

[0104] It should be noted that a three-dimensional scanning instrument with higher precision (such as a scanner based on white light interferometry) can be introduced to achieve an accuracy of sub-micron level to ensure that accurate scanning of stamping dies with complex curvature can be realized. At the same time, by adopting multi-angle scanning technology, the scanning path and angle are increased, and the occlusion area and scanning dead angle are reduced, so as to further improve the refined and accurate data acquisition for molds with complex curvature and improve the accuracy of the data.

[0105] S24. Perform registration and fusion processing on the scanning results to obtain the actual three-dimensional point cloud data.

[0106] Use the Iterative Closest Point algorithm (ICP) to register the scanning results in different directions;

[0107] In the neighborhood of each point, the weighted average method is used to fuse the multiple scanning results. The formula is as follows:

[0108]

[0109] Where p i is the point in the i-th scanning result, and w i is the weight value.

[0110] S30. Determine the difference value according to the actual three-dimensional point cloud data and the virtual three-dimensional point cloud data;

[0111] In this embodiment, by calculating based on the actual three-dimensional point cloud data and the virtual three-dimensional point cloud data of the stamping die, the actual surface and the ideal surface of the stamping die are specifically compared and analyzed to determine the first area to be repaired. Since the parameters in die design are based on the ideal state, and there are certain errors in actual production and processing, the present invention takes into account the differences between the actual surface data after actual forming and the ideal surface data, thereby accurately determining the first area to be repaired, reducing the dependence on the experience of engineering personnel, reducing the influence of human subjective factors on the trial fitting process, and improving the accuracy of data and the precision of subsequent grinding operations.

[0112] In one embodiment, according to the actual three-dimensional point cloud data and the virtual three-dimensional point cloud data, determining a difference value includes:

[0113] S31. Using a point cloud feature extraction algorithm, preliminarily align the actual three-dimensional point cloud data and the virtual three-dimensional point cloud data to obtain a preliminary alignment result;

[0114] It should be noted that for the initial alignment of complex dies, in combination with feature point detection algorithms such as SIFT (Scale-Invariant Feature Transform) or SURF (Speeded-Up Robust Features), local key features are extracted from the two groups of point clouds, and the feature points are used for preliminary alignment, greatly reducing the possibility of large-scale misalignment. In complex curvature regions, Bezier surface fitting can also be used to fit the local shape to improve the local alignment accuracy.

[0115] S32. According to the preliminary alignment result, perform a secondary point cloud alignment operation using the iterative closest point algorithm to obtain a final alignment result, including: initializing the rotation matrix and the translation vector, calculating the error function, and using an optimization algorithm (such as the Levenberg-Marquardt algorithm) to iteratively update until the error is minimized; specifically: point cloud alignment can be performed through the matching of feature points. Let the corresponding feature points of two groups of point clouds P and Q be p i and q i , then the goal of alignment is to minimize the following error function:

[0116]

[0117] In the formula, M is the rotation matrix and t is the translation vector.

[0118] S33. According to the final alignment result, calculate the normal vector difference and geometric distance difference of each point in the actual three-dimensional point cloud data after the secondary point cloud alignment operation; specifically

[0119] For each point p i , calculate its normal vector difference θ ij ; where the normal vector n i and nj The angle θ between ij It can be calculated by the following formula:

[0120] Calculate the geometric distance difference||p i -q i ||.

[0121] S34, determining a difference value according to the normal vector difference and the geometric distance difference; specifically:

[0122] d=λ 1 ||p i -q i ||+λ 2 (1-cos(θ ij ))

[0123] In the formula, λ 1 , 2 is the weight parameter.

[0124] In this embodiment, a point cloud feature extraction algorithm is used, such as calculating surface normals and curvatures, to extract key feature points in the point cloud. The actual surface and the ideal surface are preliminarily aligned through a feature-based alignment method (Feature-Based Alignment). The point cloud of the actual surface and the ideal surface data are globally aligned using an iterative closest point (ICP) algorithm to ensure that the two are in the same coordinate system. For each point on the actual surface, its closest point on the ideal surface is found, and the Euclidean distance between the two is calculated to obtain the difference value. Color mapping is used to convert the difference value into an intuitive color map to display the surface deviation area, especially to focus on the analysis of the area with large curvature changes. According to the preset tolerance range, the area that exceeds the tolerance is marked to determine the key area that needs to be corrected.

[0125] It should be noted that for areas with larger curvatures, the impact of normal deviation is greater and should be given a higher weight to prevent local deviations from being ignored overall. The classification of difference areas can be based on machine learning algorithms and trained through sample data. For different curvatures and surface features, it can automatically identify areas that need to be corrected and reduce errors in human subjective judgment.

[0126] S40, determining a first area to be repaired according to the difference value and a preset tolerance range;

[0127] In this embodiment, by marking the area beyond the tolerance according to the difference value and the preset tolerance range, the key area that needs to be corrected is determined to ensure the accuracy of the first area to be corrected. Specifically, it includes:

[0128] S41. Use a color mapping algorithm to convert the difference value into a color map;

[0129] In this embodiment, according to the calculated difference distance, apply a color mapping algorithm (such as a gradient color map based on error distribution) to visually represent the difference value by color, highlighting areas with larger deviations.

[0130] S42. On the surface of the point cloud, calculate the Gaussian curvature K and the mean curvature H of each point by locally fitting a quadratic surface; specifically:

[0131] K = k 1 *k 2

[0132]

[0133] In the formula, k 1 and k 2 are the principal curvatures. Areas with larger curvatures often require more precise polishing, so differential analysis is preferentially performed in these areas.

[0134] S43. Determine the first surface deviation area according to the color map, the Gaussian curvature, and the mean curvature;

[0135] In this embodiment, by comprehensively considering the color map, the Gaussian curvature, and the mean curvature, the first surface deviation area can be quickly and accurately determined, improving the subsequent polishing accuracy.

[0136] S44. Based on the preset tolerance range, determine the first area to be repaired from the first surface deviation area.

[0137] In this embodiment, the first surface deviation area is screened by the preset tolerance range to further determine the first area to be repaired, further improving the subsequent polishing accuracy and ensuring the accuracy of the data.

[0138] S50. Based on a preset virtual simulation model, simulate the deformation of the stamping part under different pressures, and predict the contact area and pressure distribution between the stamping die and the stamping part during the actual stamping process;

[0139] In this embodiment, perform finite element analysis (FEA) to simulate the deformation of the stamping part under different pressures, and predict the contact area and pressure distribution between the die and the stamping part during the actual stamping process

[0140] In one of the embodiments, before the step of simulating the deformation of the stamping part under different pressures based on a preset virtual simulation model and predicting the contact area and pressure distribution between the stamping die and the stamping part during the actual stamping process, it further includes:

[0141] Construct the preset virtual closed-die simulation model by using the actual three-dimensional point cloud data of the stamping die and stamping process parameters (such as punching force, material properties, etc.).

[0142] In this embodiment, based on the actual surface of the stamping die, use finite element analysis tools (such as Abaqus, ANSYS) to model the die and the stamped part. Input process parameters such as die material, punching force, and friction coefficient into the model

[0143] In this embodiment, based on the preset virtual closed-die simulation model, simulate the deformation of the stamped part under different pressures, and predict the contact area and pressure distribution between the stamping die and the stamped part during the actual stamping process, including:

[0144] S51. Perform finite element mesh division on the die and the stamped part; among them, the division method includes tetrahedral element division or hexahedral element division;

[0145] According to needs, an error estimator can be introduced to monitor the error in each simulation in real time and automatically adjust the mesh division according to the error. Among them, the area with a large local error will automatically increase the mesh density in the next iteration, thereby reducing the overall error. By adopting an adaptive mesh division strategy, local fine division of the area with complex curvature is realized, and calculation redundancy is reduced. Introduce adaptive division based on error estimation, and dynamically adjust the mesh accuracy through the iterative process.

[0146] S52. Define the boundary conditions during the stamping process; among them, the boundary conditions include the magnitude of the punching force and the contact conditions between the stamping die and the stamped part;

[0147] S53. Simulate the deformation process of the stamped part through static nonlinear analysis to obtain the pressure distribution and contact situation between the stamping die and the stamped part; among them, during the simulation, use a multi-scale nonlinear solver, which can accelerate the finite element solution speed of complex dies, maintain high precision at the same time, and shorten the simulation time

[0148] S54. Generate a virtual closed-die result according to the pressure distribution and the contact situation, and mark the high-pressure contact area and the non-contact area with large deviation between the surface of the stamping die and the stamped part.

[0149] In one of the embodiments, it further includes: accurately simulating the nonlinear elastoplastic behavior of the material by introducing a multi-material model. For the actual die material, especially for a die with a composite material or multi-layer structure, ensure that the simulation results are consistent with the actual performance.

[0150] Among them, perform finite element analysis on the stamping die, calculate the stress and strain distribution, and optimize the mesh with an error estimator. Specifically, it includes:

[0151] Define the material properties and boundary conditions of the mold;

[0152] Generate an initial finite element mesh;

[0153] Calculate the stress σ and strain ∈, and apply the constitutive relationship of the material. Among them, in the finite element analysis, the stress σ and strain ∈ of the mold satisfy the following relationship: σ = D∈;

[0154] In the formula, D is the elastic modulus matrix of the material. For composite materials or multi-layer structures, D will be a piecewise function;

[0155] Optimize the mesh using the error estimator η: η = ||σ - σ h ||, where σ h is the finite element solution.

[0156] In one of the embodiments, it further includes: during the simulation, based on various physical quantities such as temperature, friction, stress, and displacement, form a multi-dimensional thermal map.

[0157] In this embodiment, use the thermal map to visually present the pressure distribution in different regions. The red area represents high-pressure contact, and the blue area represents no contact. The size changes of each physical quantity are distinguished by different color levels to help engineers quickly identify the problem areas.

[0158] S60. Determine the second area to be repaired according to the contact area and the pressure distribution; specifically, it includes:

[0159] S61. Determine the second surface deviation area according to the contact area and the pressure distribution;

[0160] S62. Obtain the actual mold closing result of the stamping die, and correct the second surface deviation area according to the actual mold closing result to determine the second area to be repaired. Specifically:

[0161] In this embodiment, correcting the second surface deviation area according to the actual mold closing result of the stamping die can effectively improve the accuracy of the data.

[0162] Among them, obtaining the actual mold closing result of the stamping die includes: determining the actual mold closing result according to the outer contour parameters of the standard stamping part and the outer contour parameters of the stamping part to be measured formed after the stamping die is closed;

[0163] It should be noted that the standard stamping part is a standard reference finished product, and the stamping part to be measured is the stamping part to be measured formed after the stamping die is closed. The shape of the stamping part to be measured is adapted to the stamping die. Therefore, accurate data comparison and analysis can be carried out between the standard stamping part and the stamping part to be measured. And according to the analysis result, the actual die closing result of the stamping die is determined, so as to correct the second surface deviation area obtained by virtual die closing according to the actual die closing result, improve the accuracy of the data, and ensure the trial die closing effect. By comparing the outer contour parameters of the standard stamping part with the outer contour parameters of the stamping part to be measured formed after the stamping die is closed, accurate contour parameter comparison and analysis can be realized, so as to obtain accurate analysis data, and then ensure the accuracy of the second area to be repaired. Since the contour parameter comparison and analysis process can be completed only through data processing and comparison, without manual analysis and repeated confirmation throughout the process, the influence of human factors is effectively reduced and the trial die closing efficiency is effectively improved, thus shortening the trial die closing cycle.

[0164] Or, obtaining the actual die closing result of the stamping die includes: respectively obtaining the images to be measured on the same dyed surface of the standard stamping part before and after the stamping die is closed, and determining the actual die closing result according to the outer contour parameters of the standard stamping part and the outer contour parameters of the stamping part to be measured formed after the stamping die is closed.

[0165] It should be noted that the standard stamping part is a standard finished product, and its shape is adapted to the stamping die. Therefore, it can be smoothly installed into the die for die closing. Based on this, by coating pigments on each surface where the standard stamping part contacts the stamping die, the die closing condition of the upper and lower stamping dies can be judged by comparing the pigment adhesion conditions at each position on the standard stamping part before and after die closing. For example, if the pigment becomes less at some positions on the standard stamping part after die closing, it means that this position fits with the stamping die; another example is that if the pigment remains unchanged at some positions on the standard stamping part after die closing, it means that this position does not fit with the stamping die. Since the analysis process of the pigment adhesion condition can be completed only through image processing and recognition, without manual analysis and repeated confirmation throughout the process, the influence of human factors is effectively reduced and the trial die closing efficiency is effectively improved, thus shortening the trial die closing cycle.

[0166] In one of the embodiments, it further includes: using a feature matching algorithm to match the images to be measured on the same dyed surface before and after die closing, so that the pixel points at the same positions are aligned with each other.

[0167] In this embodiment, the images to be measured on the same dyed surface before and after mold clamping are images of a standard stamping part at the same position. To reduce the influence of variables, the shooting parameters of the two images to be measured are kept the same. The shooting parameters include but are not limited to shooting angle, shooting height, resolution, image size, shooting position, etc. Thus, the pixel points at the same position on the two images to be measured correspond to the same position of the standard stamping part. Furthermore, after aligning the pixel points at the same position on the two images to be measured, the pigment adhesion situation at each position of the standard stamping part can be quickly analyzed. Among them, the feature matching algorithm is a prior art and will not be elaborated here.

[0168] S70. Determine the area to be polished according to the first area to be repaired and the second area to be repaired;

[0169] In this embodiment, by determining the final area to be polished according to the first area to be repaired and the second area to be repaired, the accuracy of polishing and the mold trial fitting effect are greatly improved.

[0170] S80. Adopt a path planning algorithm to generate a polishing path according to the area to be polished; specifically, it includes:

[0171] S81. Calculate the surface curvature and roughness of each point on the surface of the area to be polished of the stamping die;

[0172] S82. Divide the area to be polished according to the difference value, the surface curvature and the roughness; to optimize the complexity of the path planning algorithm; specifically:

[0173] Region R high : The area where the difference value is greater than the set threshold (for example, |d|>0.1|d|>0.1 mm) needs to be finely polished.

[0174] Region R medium : The area where the difference value is within the set threshold (0.05 mm ≤ |d| ≤ 0.1) adopts a relatively sparse path planning strategy.

[0175] Region R low : The area where the difference value is less than the lowest threshold (|d|<0.05), skip polishing or perform simple path planning. d is the difference value.

[0176] Using the principal curvature k 1 and k 2 Analyze the surface curvature characteristics and divide the surface into different curvature regions:

[0177] High curvature region: |k 1 | or |k 2 | is relatively large (for example, |k|>0.2), and a dense spiral path needs to be adopted to reduce tool wear.

[0178] Low-curvature region: |k 1 and |k 2 are small (e.g., |k| < 0.05), and parallel paths or sparser spiral paths can be adopted.

[0179] The surface is divided into different roughness regions according to the roughness R; the greater the difference between the roughness and the target roughness, the denser the paths required.

[0180] S83. Construct a density field of the area to be polished in three-dimensional space according to the difference value, the surface curvature, and the roughness, and map the deviation and curvature features to a density value D(x, y, z). The greater the density value, the denser the paths required in this area; specifically:

[0181] Construct a density field of the area to be polished in three-dimensional space, and map the difference value, the surface curvature, and the roughness features to a density value D(x, y, z). The greater the density value, the denser the paths required in this area.

[0182] Construction of the density field:

[0183]

[0184] where and ψ are weighting factors that can be adjusted according to specific polishing requirements, and R is the roughness.

[0185] S84. Generate corresponding polishing paths according to the density field; specifically:

[0186] For low-curvature regions, equidistant parallel lines are used to generate polishing paths, and the path spacing d parallel is adjusted according to the regional density value:

[0187]

[0188] Among them, when generating parallel paths, the angle between the polishing direction and the normal direction of the mold is given priority to ensure that the paths are parallel to the surface to be polished and improve the surface finish.

[0189] For high-curvature regions, spiral paths are used for path planning. The starting point P of the path o is the centroid of this surface area, and spiral lines are generated layer by layer outward:

[0190] The spiral radius r of each layer n is jointly determined by the upper-layer radius r n-1 and the density value D(x, y, z):

[0191]

[0192] During the generation of each layer, maintain the normal consistency of the path to ensure path smoothness.

[0193] S90. Control the grinding equipment to perform a grinding action on the stamping die according to the grinding path.

[0194] In one embodiment, it further includes: real-time collecting the surface data after grinding; calculating the current error and adjusting the grinding depth, applying PID control, and iteratively adjusting according to the feedback.

[0195] The present invention ensures high-precision alignment and correction in areas with complex curvature through high-precision equipment and multi-angle scanning, combined with curvature-sensitive adaptive sampling, alignment, and difference analysis. Through adaptive finite element analysis and intelligent grinding path planning, redundant calculations and the time for repeated grinding are reduced, significantly reducing the time for trial fitting. The real-time feedback grinding system combines multi-dimensional difference analysis and compensation mechanisms to ensure that the final die meets high-precision requirements and improves the overall quality of stamping parts. It can provide a fine grinding path for dies with complex curved surfaces, reduce the trial-and-error time, and improve the final precision of the die and the product at the same time.

[0196] In summary, the stamping die trial fitting control method provided by the present invention can at least achieve the following effects:

[0197] 1) For the stamping die trial fitting control method provided by the present invention, first, the present invention calculates based on the actual three-dimensional point cloud data and virtual three-dimensional point cloud data of the stamping die, so as to specifically compare and analyze the actual surface and ideal surface of the stamping die to determine the first area to be repaired. Since the parameters in die design are based on the ideal state, and there will be certain errors in actual production and processing, the present invention considers the difference between the actual surface data after actual forming and the ideal surface data, thereby accurately determining the first area to be repaired, reducing the dependence on the experience of engineering personnel, reducing the influence of subjective human factors on the trial fitting process, and improving the accuracy of data and the precision of subsequent grinding operations.

[0198] However, in the analysis process of existing trial fitting methods, it is mostly carried out by engineering personnel based on experience, with strong subjectivity, being greatly affected by human factors, and due to the need for multiple mold closings, grindings, and re-mold closings for repeated confirmation, the trial fitting process takes a long time and has low efficiency.

[0199] 2) The present invention simulates the deformation of a stamping part under different pressures according to a preset virtual die closing simulation model, predicts the contact area and pressure distribution between the stamping die and the stamping part during the actual stamping process, and determines a second area to be repaired according to the contact area and the pressure distribution. Since performing the actual die closing operation requires a large amount of manpower, material resources, and time costs, the present invention conducts actual die closing simulation by constructing a preset virtual die closing simulation model to determine the second area to be repaired, which can effectively improve the work efficiency of trial die closing and reduce the manpower, material resources, and time costs of the trial die closing operation.

[0200] 3) After determining the first area to be repaired and the second area to be repaired, the present invention determines the area to be polished according to the first area to be repaired and the second area to be repaired; uses a path planning algorithm to generate a polishing path according to the area to be polished; and controls a polishing device to perform a polishing action on the stamping die according to the polishing path. By combining the first area to be repaired and the second area to be repaired, the present invention accurately identifies the area to be polished on the stamping die, generates a polishing path according to the area to be polished, improves the polishing efficiency and accuracy, realizes the fine control of the polishing parameters during the polishing process, ensures the accuracy of the die polishing process, especially for areas with large curvature changes, can more accurately control the surface modification amount, improves the correction success rate of this die, greatly shortens the time of repeated polishing and verification, thereby further improving the efficiency of the entire trial die closing process, achieving an efficient and accurate die correction effect, significantly reducing manual intervention, and improving the accuracy and efficiency of die trial die closing.

[0201] In some embodiments, the present invention also provides a stamping die trial die closing control system, and the system includes:

[0202] An acquisition module, configured to acquire 3D geometric data of the ideal surface of the stamping die, perform meshing processing on the 3D geometric data, and discretize the continuous surface into virtual three-dimensional point cloud data;

[0203] A first generation module, configured to use a three-dimensional scanning device to scan the actual surface of the stamping die to generate actual three-dimensional point cloud data;

[0204] A first determination module, configured to determine a difference value according to the actual three-dimensional point cloud data and the virtual three-dimensional point cloud data;

[0205] A second determination module, configured to determine a first area to be repaired according to the difference value and a preset tolerance range;

[0206] A prediction module, configured to simulate the deformation of a stamping part under different pressures based on a preset virtual die closing simulation model, and predict the contact area and pressure distribution between the stamping die and the stamping part during the actual stamping process;

[0207] A third determination module, configured to determine a second area to be repaired according to the contact area and the pressure distribution;

[0208] A fourth determination module, configured to determine an area to be polished according to the first area to be repaired and the second area to be repaired;

[0209] A second production module, configured to generate a polishing path according to the area to be polished by using a path planning algorithm;

[0210] A control module, configured to control a polishing device to perform a polishing action on the stamping die according to the polishing path.

[0211] It can be understood that the functions or modules included in the system provided in this embodiment can be used to execute the methods described in the foregoing method embodiments. The specific implementation can refer to the description of the foregoing method embodiments. For the sake of brevity, it will not be elaborated here.

[0212] The present invention also provides an electronic device, including a processor and a memory. The memory is used to store computer program code, and the computer program code includes computer instructions. When the processor executes the computer instructions, the electronic device executes the method in any of the foregoing possible implementation manners.

[0213] The present invention also provides a computer-readable storage medium, in which a computer program is stored. The computer program includes program instructions. When the program instructions are executed by a processor of an electronic device, the processor is caused to execute the method in any of the foregoing possible implementation manners.

[0214] Those of ordinary skill in the art can realize that the units and algorithm steps of the examples described in combination with the embodiments disclosed herein can be implemented by electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are executed in a hardware or software manner depends on the specific application and design constraints of the technical solution. Professional technicians can use different methods to implement the described functions for each specific application, but such implementation should not be considered to exceed the scope of the present invention.

[0215] Those skilled in the art can clearly understand that for the convenience and brevity of description, the specific working processes of the systems, devices, and units described above can refer to the corresponding processes in the foregoing method embodiments, and will not be elaborated here. Those skilled in the art can also clearly understand that each embodiment of the present invention has different emphases. For the convenience and brevity of description, the same or similar parts may not be elaborated in different embodiments. Therefore, the parts not described or not elaborated in a certain embodiment can be referred to the records of other embodiments.

[0216] In several embodiments provided by the present invention, it should be understood that the disclosed systems, devices, and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For example, the division of the units is only a logical function division. In actual implementation, there may be other division methods. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the displayed or discussed couplings or direct couplings or communication connections to each other can be through some interfaces. The indirect couplings or communication connections of the devices or units can be in electrical, mechanical, or other forms.

[0217] The units described as separate components may or may not be physically separated. The components shown as units may or may not be physical units, that is, they can be located in one place or distributed to multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0218] In the above embodiments, it can be implemented in whole or in part by software, hardware, firmware, or any combination thereof. When implemented using software, it can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, the processes or functions described in the embodiments of the present invention are generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. The computer instructions can be stored in a computer-readable storage medium or transmitted through the computer-readable storage medium. The computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center in a wired (such as coaxial cable, optical fiber, digital subscriber line (DSL)) or wireless (such as infrared, wireless, microwave, etc.) manner. The computer-readable storage medium can be any available medium that the computer can access or a data storage device such as a server, data center, etc. that contains one or more integrated available media. The available medium can be a magnetic medium (such as a floppy disk, hard disk, magnetic tape), an optical medium (such as a digital versatile disc (DVD)), or a semiconductor medium (such as a solid state disk (SSD)), etc.

[0219] Those of ordinary skill in the art can understand that all or part of the processes in the methods of the above embodiments can be completed by relevant hardware instructed by a computer program. This program can be stored in a computer-readable storage medium. When the program is executed, it can include the processes of the above method embodiments. The aforementioned storage medium includes various media that can store program codes, such as read-only memory (ROM), random access memory (RAM), magnetic disks, or optical discs.

Claims

1. A stamping die test control method, characterized in that: The method comprises: Acquire 3D geometric data of the ideal surface of the stamping die, perform gridding on the 3D geometric data, and discretize the continuous surface into virtual three-dimensional point cloud data; Use 3D scanning equipment to scan the actual surface of the stamping die and generate actual 3D point cloud data; Determining a difference value according to the actual three-dimensional point cloud data and the virtual three-dimensional point cloud data, including aligning the actual three-dimensional point cloud data and the virtual three-dimensional point cloud data using a point cloud feature extraction algorithm and an iterative closest point algorithm, and calculating the Euclidean distance between the two to obtain a difference value; Determining a first area to be repaired according to the difference value and a preset tolerance range; Using the actual three-dimensional point cloud data and stamping process parameters of the stamping die, a preset virtual mold simulation model is constructed; Based on a preset virtual mold closing simulation model, the deformation of the stamping parts under different pressures is simulated, and the contact area and pressure distribution between the stamping die and the stamping parts in the actual stamping process are predicted, including: finite element meshing of the die and the stamping parts; defining boundary conditions in the stamping process; simulating the deformation process of the stamping parts through static nonlinear analysis to obtain the pressure distribution and contact conditions between the stamping die and the stamping parts; generating a virtual mold closing result according to the pressure distribution and the contact conditions, and identifying the high-pressure contact area between the stamping die surface and the stamping parts and the non-contact area with large deviations; wherein the boundary conditions include the size of the stamping pressure and the contact conditions between the stamping die and the stamping parts; Determining a second area to be repaired according to the contact area and the pressure distribution; Determining an area to be polished according to the first area to be repaired and the second area to be repaired; Using a path planning algorithm to generate a grinding path according to the area to be polished; According to the grinding path, the grinding equipment is controlled to perform a grinding action on the stamping die.

2. The stamping die test control method according to claim 1, characterized in that: Scan the actual surface of the stamping die to generate actual 3D point cloud data, including: Calculate the curvature value of each sampling point based on the 3D geometric data; According to the curvature value, the area to be scanned is divided into a high curvature area and a low curvature area; Scanning the high curvature area and the low curvature area multiple times respectively along a preset scanning path; The multiple scanning results are registered and fused to obtain the actual three-dimensional point cloud data.

3. The stamping die test control method according to claim 2, characterized in that: Also includes: Calculating the surface normal vector of the stamping die in real time according to the current scanning point; Determine the scanning angle of the three-dimensional scanning device according to the surface normal vector; wherein the three-dimensional scanning device is perpendicular to the surface normal vector; The distance between the three-dimensional scanning device and the surface of the stamping die is determined according to the concavo-convexity degree of the surface of the stamping die.

4. The stamping die test control method according to claim 1, characterized in that: Determining a difference value according to the actual three-dimensional point cloud data and the virtual three-dimensional point cloud data includes: Using a point cloud feature extraction algorithm, preliminarily aligning the actual three-dimensional point cloud data and the virtual three-dimensional point cloud data to obtain a preliminary alignment result; According to the preliminary alignment result, a secondary point cloud alignment operation is performed using an iterative closest point algorithm to obtain a final alignment result; According to the final alignment result, calculating the normal vector difference and geometric distance difference of each point in the actual three-dimensional point cloud data after the secondary point cloud alignment operation; A difference value is determined according to the normal vector difference and the geometric distance difference.

5. The stamping die test control method according to claim 1, characterized in that: Determining a first area to be repaired according to the difference value and a preset tolerance range includes: Converting the difference values ​​into a color map using a color mapping algorithm; On the point cloud surface, the Gaussian curvature and mean curvature of each point are calculated by locally fitting the quadratic surface; Determining a first profile deviation region according to the color map, the Gaussian curvature and the average curvature; Based on the preset tolerance range, a first area to be repaired is determined from the first profile deviation area.

6. The stamping die test control method according to claim 1, characterized in that: Determining a second area to be repaired according to the contact area and the pressure distribution includes: Determining a second profile deviation area according to the contact area and the pressure distribution; An actual mold closing result of the stamping die is obtained, and the second molding surface deviation area is corrected according to the actual mold closing result to determine the second area to be repaired.

7. The stamping die test control method according to claim 1, characterized in that: A path planning algorithm is used to generate a grinding path according to the area to be polished, including: Calculating the surface curvature and roughness of each point on the surface of the area to be polished of the stamping die; Partitioning the area to be polished according to the difference value, the surface curvature and the roughness; According to the difference value, the surface curvature and the roughness, a density field of the area to be polished is constructed in a three-dimensional space, and the deviation and curvature characteristics are mapped into density values; wherein a larger density value indicates that a more dense path is required for the area; A corresponding grinding path is generated according to the density field.

8. A stamping die test and research control system, characterized in that: The system comprises: An acquisition module, used for acquiring 3D geometric data of the ideal surface of the stamping die, meshing the 3D geometric data, and discretizing the continuous surface into virtual three-dimensional point cloud data; The first generation module is used to scan the actual surface of the stamping die using a three-dimensional scanning device to generate actual three-dimensional point cloud data; A first determination module is used to determine a difference value according to the actual three-dimensional point cloud data and the virtual three-dimensional point cloud data, including aligning the actual three-dimensional point cloud data and the virtual three-dimensional point cloud data using a point cloud feature extraction algorithm and an iterative closest point algorithm, and calculating the Euclidean distance between the two to obtain a difference value; A second determination module, configured to determine a first area to be repaired according to the difference value and a preset tolerance range; A prediction module is used to simulate the deformation of stamping parts under different pressures based on a preset virtual joint simulation model, and predict the contact area and pressure distribution between the stamping die and the stamping part during the actual stamping process, including: finite element meshing of the die and the stamping part; defining boundary conditions during the stamping process; simulating the deformation process of the stamping part through static nonlinear analysis to obtain the pressure distribution and contact conditions between the stamping die and the stamping part; generating a virtual joint result based on the pressure distribution and the contact conditions, and identifying the high-pressure contact area between the stamping die surface and the stamping part and the non-contact area with large deviation; wherein the boundary conditions include the size of the stamping pressure and the contact conditions between the stamping die and the stamping part; wherein the preset virtual joint simulation model is constructed using the actual three-dimensional point cloud data of the stamping die and the stamping process parameters; A third determining module, configured to determine a second area to be repaired according to the contact area and the pressure distribution; A fourth determining module, configured to determine an area to be polished according to the first area to be repaired and the second area to be repaired; A second production module is used to generate a grinding path according to the area to be polished by using a path planning algorithm; The control module is used to control the grinding equipment to perform grinding action on the stamping die according to the grinding path.

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