Stamping die test lapping-in control method and system

Abstract

The invention discloses a method and a system for controlling test lapping of a stamping die. The method comprises the following steps: scanning an actual molded surface of the stamping die to generate actual three-dimensional point cloud data; determining a difference value according to the actual three-dimensional point cloud data and the virtual three-dimensional point cloud data; determining a first to-be-repaired area according to the difference value and a preset tolerance range; simulating deformation conditions of the stamping part under different pressures based on a preset virtual combined simulation model, and predicting a contact area and pressure distribution of the stamping die and the stamping part in an actual stamping process; determining a second to-be-repaired area according to the contact area and the pressure distribution; determining a to-be-polished area according to the first to-be-repaired area and the second to-be-repaired area; a polishing path is generated according to the to-be-polished area through a path planning algorithm; and grinding equipment is controlled to grind the stamping die according to the grinding path. Therefore, the efficiency of the whole test lapping process is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of die processing control, and in particular to a stamping die test control method and system. Background Art

[0002] During the processing and assembly of the mold, due to processing errors and assembly errors, there is often a certain deviation between the actual molded surface and the ideal designed surface. Especially when the mold surface has a large curvature change, the deviation may be more obvious. In order to ensure that the mold can process stamping parts that meet the design requirements, the mold usually needs to go through a trial and test process.

[0003] However, the analysis process of the existing trial and development methods is mostly conducted by engineering personnel based on experience, which is highly subjective and greatly affected by human factors. In addition, since it requires multiple mold closing, grinding, and re-mold closing for repeated confirmation, the trial and development process is time-consuming and inefficient. Summary of the invention

[0004] In order to solve at least one of the technical problems mentioned above, the present invention provides a stamping die trial and development control method and system.

[0005] In a first aspect, the present invention provides a stamping die test control method, the method comprising:

[0006] 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;

[0007] Use 3D scanning equipment to scan the actual surface of the stamping die and generate actual 3D point cloud data;

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

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

[0010] 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;

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

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

[0013] Using a path planning algorithm to generate a grinding path according to the area to be polished;

[0014] According to the grinding path, the grinding equipment is controlled to perform a grinding action on the stamping die.

[0015] Preferably, the actual surface of the stamping die is scanned 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] According to the curvature value, the area to be scanned is divided into a high curvature area and a low curvature area;

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

[0019] The multiple scanning results are registered and fused to obtain the actual three-dimensional point cloud data.

[0020] Preferably, it also includes:

[0021] Calculating 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] 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.

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

[0025] 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;

[0026] 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;

[0027] 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;

[0028] A difference value is determined according to the normal vector difference and the geometric distance difference.

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

[0030] Converting the difference values ​​into a color map using a color mapping algorithm;

[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 by using the actual three-dimensional point cloud data of the stamping die and the stamping process parameters.

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

[0047] 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;

[0048] A corresponding grinding path is generated according to the density field.

[0049] In a second aspect, the present invention further provides a stamping die test and research control system, the system comprising:

[0050] 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;

[0051] 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;

[0052] A first determining 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, used to simulate the deformation of the stamping part 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;

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

[0056] 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;

[0057] A second production module is used to generate a grinding path according to the area to be polished by using a path planning algorithm;

[0058] The control module is used to control the grinding equipment to perform grinding action on the stamping die according to the grinding path.

[0059] Compared with the prior art, the present invention has the following beneficial effects:

[0060] 1) The present invention provides a stamping die trial and fitting control method. First, the present invention performs calculations based on the actual three-dimensional point cloud data and virtual three-dimensional point cloud data of the stamping die, thereby realizing a specific comparison and analysis of the actual surface and the ideal surface of the stamping die to determine the first area to be repaired. Since the parameters during mold design are designed based on ideal conditions, 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 molding and the ideal surface data, thereby accurately determining the first area to be repaired, reducing the reliance on the experience of engineering personnel, reducing the influence of human subjective factors on the trial and fitting process, and improving the accuracy of data and the accuracy of subsequent polishing operations.

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

[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 polished according to the first area to be repaired and the second area to be repaired; generates a polishing path according to the area to be polished by using a path planning algorithm; and controls the polishing equipment to perform polishing on the stamping die according to the polishing path. The present invention combines the first area to be repaired and the second area to be repaired to accurately identify the area to be polished of the stamping die, and generates a polishing path according to the area to be polished, thereby improving the polishing efficiency and polishing accuracy, achieving refined control of the polishing parameters during the polishing process, and ensuring the accuracy of the mold polishing process, especially for areas with large curvature changes, the surface correction amount can be more accurately controlled, the success rate of the correction of this mold is improved, and the time for repeated polishing and verification is greatly shortened, thereby further improving the efficiency of the entire trial and testing process, achieving efficient and accurate mold correction effects, greatly reducing manual intervention, and improving the accuracy and efficiency of mold trial and testing.

[0063] It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the 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 technology, the drawings required for use in the embodiments of the present invention or the background technology will be described below.

[0065] The drawings herein are incorporated into the specification and constitute a part of the specification. These drawings illustrate embodiments consistent with the present disclosure and are used to illustrate the technical solutions of the present disclosure together with the specification.

[0066] Figure 1 A schematic flow chart of a stamping die trial and development control method provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0067] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are 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-mentioned drawings are used to distinguish different objects, rather than to describe a specific order. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions. 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 may optionally include steps or units that are not listed, or may optionally include other steps or units that are inherent to these processes, methods, products or devices.

[0069] Reference to "embodiments" herein means that a particular feature, structure, or characteristic described in conjunction with the embodiments may be included in at least one embodiment of the present invention. The appearance of the phrase in various places in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0070] In addition, in order to better illustrate the present invention, numerous specific details are provided in the following specific embodiments. It should be understood by those skilled in the art that the present invention can be implemented without certain specific details. In some examples, methods, means, components and circuits well known to those skilled in the art are not described in detail in order to highlight the subject matter of the present invention.

[0071] See also Figure 1 , Figure 1 The present invention provides a flow chart of a stamping die test control method. Figure 1 As shown, a stamping die test and control method comprises the following steps:

[0072] S10, acquiring 3D geometric data of the ideal surface of the stamping die, meshing the 3D geometric data, and discretizing the continuous curved surface into virtual three-dimensional point cloud data;

[0073] In this embodiment, the 3D geometric data of the ideal surface is obtained from the mold design stage, the data of the ideal surface is meshed, and the continuous curved surface is discretized into three-dimensional point cloud data to ensure that it can be compared with the actual scanned surface data. Specifically, commonly used 3D format files (such as STEP, IGES) are imported, and the continuous geometric model is used to generate three-dimensional point cloud data through a discretization algorithm to compare with the actual scanned data; among them, for the ideal surface, a more sophisticated adaptive meshing technology can also be used, especially in areas with complex curvatures, to divide more dense grids to ensure that in the subsequent comparison process, the accuracy can match the actual scanned data.

[0074] S20, using 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 mold processing and assembly are completed, the mold surface is scanned using a three-dimensional scanning device to generate high-precision three-dimensional point cloud data, and the scanned point cloud is pre-processed to obtain three-dimensional data of the actual mold surface to ensure the integrity and accuracy of the data.

[0076] It should be noted that preprocessing includes denoising, point cloud resampling, hole repairing, etc. Specifically, outliers (i.e., points with large errors that deviate from the surface) generated during the scanning process are removed through a statistical noise filtering algorithm (such as a distance-based noise removal algorithm). In order to reduce the computational burden, voxel downsampling is performed while maintaining surface details. A uniform voxel grid sampling algorithm is used to define the voxel size, and points falling within the same voxel are compressed into a central point. For areas that cannot be scanned directly, a surface reconstruction algorithm (such as the Poisson reconstruction algorithm) is applied to complete the local surface and generate complete three-dimensional point cloud data. Preprocessing the scanned point cloud can greatly ensure the integrity and accuracy of the data.

[0077] In one embodiment, the actual surface of the stamping die is scanned to generate actual three-dimensional point cloud data, including:

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

[0079] In this embodiment, for each mesh vertex or each point in the point cloud, the curvature of the point is calculated. The curvature can be calculated using a variety of methods, 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, k1 and k2 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 based on the size or complexity of the model;

[0084] S22, dividing the area to be scanned into a high curvature area and a low curvature area according to the curvature value;

[0085] In this embodiment, the scanning area is divided according to the curvature value to form different scanning priority areas, including:

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

[0087] Label each curvature region to facilitate adjustment of scanning parameters in subsequent steps.

[0088] According to the needs, it also includes: before each scanning frame starts, the average curvature value of the local area is calculated in real time, and the step length is dynamically adjusted to set the dynamic scanning step length for the high curvature area and the low curvature area:

[0089]

[0090] Where C is a constant and K is the curvature value; it ensures that a smaller scanning step size (stepstep) is set for areas with larger curvature, and a larger step size is set for areas with smaller curvature.

[0091] S23, scanning the high curvature area and the low curvature area multiple times along a preset scanning path; specifically, comprising:

[0092] S231. For each partition, two or more scanning paths are planned to obtain a preset scanning path; specifically: a space filling algorithm (such as serpentine scanning or spiral scanning) is used to generate a first scanning path; based on the first scanning path, a second scanning path is generated in a relatively vertical direction or a relatively parallel direction; wherein the number of scans of each partition can be set as required, for example: the number of scans of the high curvature area is greater than or equal to the number of scans of the low curvature area;

[0093] S232, collecting data on the stamping die along a preset scanning path;

[0094] S233, using a weighted filter, assigning weights to each point in the collected data according to the actual curvature value; wherein each point p in the point cloudi Neighborhood N(p i ) is the curvature estimate K(p i ) determines whether the point is a noise point, using a curvature-based weighted filter including: In the formula, w(p i ) is the weight and γ is the control parameter.

[0095] S234: Remove or modify points whose weights are lower than the threshold value to complete the noise reduction process.

[0096] In this embodiment, in terms of noise removal, curvature information is combined for processing, that is, more points are retained for areas with larger curvature, while points in smooth areas can be appropriately simplified. Local statistical filtering based on curvature changes is adopted, and weighted analysis is performed on the neighborhood curvature of each point to determine whether it is a noise point. In the data processing process, hierarchical reconstruction technology is introduced, and low-precision reconstruction is first used to quickly generate contours, and then high-precision supplementation is performed on local areas with complex curvatures, thereby ensuring efficiency while improving detail accuracy.

[0097] In one embodiment, it also includes:

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

[0099] S2322. Determine a 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;

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

[0101] In this embodiment, the angle of the three-dimensional scanning device is adjusted to make it perpendicular to the normal vector of the point to minimize the projection error, and the distance between the scanning head and the surface is adjusted in real time according to the concavity of the surface of the stamping die to keep the focal length consistent. The projection error is reduced by adjusting the angle and distance in real time to ensure that the scanning device can adapt to complex surfaces.

[0102] According to the needs, it also includes: calculating the moving speed and sampling interval of the three-dimensional scanning device based on the curvature value; specifically: for the scanning path optimization of complex surfaces, the curvature K can be used as a control variable: Where n is the normal vector and V is the surface velocity. The moving speed v of the scanning head of the 3D scanning device s Adjust according to the curvature K: In the formula, α is the adjustment factor, which controls the degree to which the moving speed of the scanning head changes with the curvature. The point cloud data acquisition is planned by different plane perspectives, the sampling interval is set, and the point cloud data acquired by multiple planes are fused. In it, 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 sampling points (i.e., sampling spacing d i ) is determined by the curvature K: Where, d i is the sampling interval, β is the control parameter, 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 to ensure that the details of the complex area are fully captured, and data is collected layer by layer through layer slicing. 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, and the spacing of more complex areas is smaller to improve accuracy.

[0104] It should be noted that by introducing more accurate three-dimensional scanning equipment (such as scanners based on white light interferometry), it is possible to achieve sub-micron accuracy to ensure accurate scanning of stamping molds with complex curvatures. At the same time, by adopting multi-angle scanning technology, increasing the scanning path and angle, and reducing occluded areas and scanning blind spots, it is possible to further improve the data collection for molds with complex curvatures, and improve the accuracy of the data.

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

[0106] The scan results in different directions are registered using the iterative closest point algorithm (ICP);

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

[0108]

[0109] In the formula, p i is the point in the i-th scan result, w i is the weight value.

[0110] S30, determining a difference value according to the actual three-dimensional point cloud data and the virtual three-dimensional point cloud data;

[0111] In this embodiment, calculations are performed based on the actual three-dimensional point cloud data and virtual three-dimensional point cloud data of the stamping die, thereby achieving specific comparison and analysis of the actual surface and the ideal surface of the stamping die to determine the first area to be repaired. Since the parameters during mold design are designed based on ideal conditions, 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 molding and the ideal surface data, so as to accurately determine the first area to be repaired, reduce dependence on the experience of engineers, reduce the influence of human subjective factors on the trial and development process, and improve the accuracy of data and the accuracy of subsequent polishing operations.

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

[0113] S31, using a point cloud feature extraction algorithm to 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 molds, feature point detection algorithms such as SIFT (Scale Invariant Feature Transform) or SURF (Speeded Up Robust Features) are used to extract local key features from the two sets of point clouds, and feature points are used for preliminary alignment, which greatly reduces the possibility of large-scale misalignment. In areas with complex curvature, Bezier surfaces can also be used to fit local shapes to improve local alignment accuracy.

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

[0116]

[0117] Where M is the rotation matrix and t is the translation vector.

[0118] S33, 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; specifically

[0119] For each point p i , calculate its normal vector difference θ ij ; Among them, 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=λ1||p i -q i ||+λ2(1-cos(θ ij ))

[0123] Where λ1 and λ2 are weight parameters.

[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, converting the difference value into a color map using a color mapping algorithm;

[0129] In this embodiment, according to the calculated difference distance, a color mapping algorithm (such as a gradient color map based on error distribution) is applied to intuitively represent the difference value through color, highlighting the area with a large deviation.

[0130] S42. On the point cloud surface, the Gaussian curvature K and the average curvature H of each point are calculated by locally fitting the quadratic surface. Specifically:

[0131] K=k1*k2

[0132]

[0133] Where k1 and k2 are the principal curvatures. Areas with greater curvature often require more fine grinding, so differential analysis is prioritized in these areas.

[0134] S43, determining a first profile deviation region according to the color map, the Gaussian curvature and the average curvature;

[0135] In this embodiment, the color map, Gaussian curvature and average curvature are combined to achieve rapid and accurate determination of the first profile deviation area, thereby improving subsequent grinding accuracy.

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

[0137] In this embodiment, the first profile deviation area is screened by a preset tolerance range to further determine the first area to be repaired, further improve the subsequent grinding accuracy, and ensure the accuracy of the data.

[0138] S50, 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;

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

[0140] In one embodiment, before 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:

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

[0142] In this embodiment, based on the actual profile of the stamping die, finite element analysis tools (such as Abaqus, ANSYS) are used to model the die and stamping parts. The process parameters such as die material, stamping force, friction coefficient, etc. are input into the model.

[0143] In this embodiment, based on a preset virtual joint simulation model, the deformation of the stamping part under different pressures is simulated, and the contact area and pressure distribution between the stamping die and the stamping part during the actual stamping process are predicted, including:

[0144] S51, performing finite element mesh division on the mold and the stamping part; wherein the division method includes tetrahedral unit division or hexahedral unit division;

[0145] If needed, 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 large local errors 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 areas with complex curvature can be achieved to reduce computational redundancy. Adaptive division based on error estimation is introduced to dynamically adjust the mesh accuracy through an iterative process.

[0146] S52, defining boundary conditions in 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;

[0147] S53, 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; wherein, in the simulation process, using a multi-scale nonlinear solver can speed up the finite element solution speed of complex molds while maintaining high accuracy and shortening the simulation time

[0148] S54, generating a virtual mold closing result according to the pressure distribution and the contact condition, and identifying a high-pressure contact area between the stamping die surface and the stamping part and a non-contact area with a large deviation.

[0149] In one embodiment, the method further includes: accurately simulating the nonlinear elastic-plastic behavior of the material by introducing a multi-material model, so as to ensure that the simulation results are consistent with the actual performance for the actual mold material, especially the mold with composite materials or multi-layer structures.

[0150] Among them, the finite element analysis of the stamping die is carried out to calculate the stress and strain distribution, and the error estimator is used to optimize the mesh, including:

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

[0152] Generate initial finite element mesh;

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

[0154] Where D is the elastic modulus matrix of the material. For composite materials or multilayer structures, D will be a piecewise function;

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

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

[0157] In this embodiment, a heat map is used to visually present the pressure distribution in different areas. The red area indicates high-pressure contact, and the blue area indicates no contact. Different color levels are used to distinguish the size changes of various physical quantities, helping engineers to quickly identify problem areas.

[0158] S60, determining a second area to be repaired according to the contact area and the pressure distribution; specifically, comprising:

[0159] S61, determining a second profile deviation area according to the contact area and the pressure distribution;

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

[0161] In this embodiment, the second molding surface deviation area is corrected according to the actual mold closing result of the stamping mold, which can actually and effectively improve the accuracy of the data.

[0162] Wherein, 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 tested formed after the stamping die is closed;

[0163] It should be noted that the standard stamping parts are standard reference finished products, and the stamping parts to be tested are the stamping parts to be measured formed after the stamping die is closed. The shape of the stamping parts to be tested is compatible with the stamping die. Therefore, the standard stamping parts can be used for accurate data comparison and analysis with the stamping parts to be tested. And the actual closing result of the stamping die is determined according to the analysis results, so that the second profile deviation area obtained by the virtual closing is corrected according to the actual closing result, so as to improve the accuracy of the data and ensure the trial and research effect. Accurate contour parameter comparison and analysis can be achieved based on the outer contour parameters of the standard stamping parts and the outer contour parameters of the stamping parts to be tested formed after the stamping die is closed, so as to obtain accurate analysis data, thereby ensuring 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, no manual analysis and repeated confirmation are required throughout the process, so the influence of human factors is effectively reduced and the trial and research efficiency is effectively improved, thereby shortening the trial and research cycle.

[0164] Or, obtaining the actual mold closing result of the stamping die, including: obtaining the images to be tested on the same dyeing surface of the standard stamping part before and after the mold closing of the stamping die, and 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 tested formed after the stamping die is closed.

[0165] It should be noted that the standard stamping parts are standard finished products, and their shapes are compatible with the stamping dies, so they can be smoothly installed in the mold for mold closing. Based on this, by applying paint on each surface of the standard stamping parts that contacts the stamping dies, the grinding and fitting conditions of the upper and lower stamping dies can be judged by comparing the paint adhesion conditions at various positions on the standard stamping parts before and after mold closing. For example, after mold closing, the paint at some positions of the standard stamping parts becomes less, which means that the position is in good fit with the stamping die; for example, after mold closing, the paint at some positions of the standard stamping parts remains unchanged, which means that the position is not in good fit with the stamping die. Since the analysis process of the paint adhesion condition can be completed only through image processing and recognition, and no manual analysis and repeated confirmation are required throughout the process, it effectively reduces the impact of human factors and effectively improves the efficiency of trial and fitting, thereby shortening the trial and fitting cycle.

[0166] In one of the embodiments, the method further includes: using a feature matching algorithm to match the images to be tested on the same dyeing surface before and after the mold closing so that pixels at the same position are aligned with each other.

[0167] In this embodiment, the images to be tested on the same dyeing surface before and after mold closing are images of the standard stamping parts at the same position. In order to reduce the influence of variables, the shooting parameters of the two images to be tested are kept the same, including but not limited to shooting angle, shooting height, resolution, image size, shooting position, etc., so that the pixels at the same position on the two images to be tested correspond to the same position of the standard stamping parts, and then the pixels at the same position on the two images to be tested are aligned to quickly analyze the pigment adhesion at various positions of the standard stamping parts. Among them, the feature matching algorithm is a prior art and will not be repeated here.

[0168] S70, determining an area to be polished according to the first area to be repaired and the second area to be repaired;

[0169] In this embodiment, the final area to be polished is determined based on the first area to be repaired and the second area to be repaired, thereby greatly improving the polishing accuracy and the mold trial grinding effect.

[0170] S80, using a path planning algorithm to generate a polishing path according to the area to be polished; specifically, including:

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

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

[0173] Region R high : Areas where the difference value is greater than the set threshold (for example, |d|>0.1|d|>0.1mm) require fine grinding.

[0174] Region R medium : In areas where the difference value is within the set threshold (0.05mm≤|d|≤0.1), a sparser path planning strategy is adopted.

[0175] Region R low :For areas where the difference value is less than the minimum threshold (|d|<0.05), polishing is skipped or simple path planning is performed. d is the difference value.

[0176] The main curvatures k1 and k2 are used to analyze the surface curvature characteristics and divide the surface into different curvature areas:

[0177] High curvature area: |k1| or |k2| is large (for example, |k|>0.2), and a dense spiral path is required to reduce tool wear.

[0178] Low curvature region: |k1| and |k2| are small (for example, |k| < 0.05), and a parallel path or a sparse spiral path can be used.

[0179] The surface is divided into different roughness regions according to the roughness R; if the roughness differs more from the target roughness, more dense paths are required.

[0180] S83, constructing a density field of the area to be polished in three-dimensional space according to the difference value, the surface curvature and the roughness, mapping the deviation and curvature characteristics into a density value D(x, y, z), wherein a larger density value indicates that the area requires a denser path; specifically:

[0181] A density field of the area to be polished is constructed in three-dimensional space, and the difference value, the surface curvature and the roughness feature are mapped into a density value D(x, y, z). A larger density value indicates that the area requires a denser path.

[0182] Construction of density field:

[0183]

[0184] in, and ψ are weight factors, which can be adjusted according to specific grinding requirements, and R is the roughness.

[0185] S84, generating a corresponding grinding path according to the density field; specifically:

[0186] For low curvature areas, equidistant parallel lines are used to generate the grinding path, with a path spacing of d parallel Adjust based on area density value:

[0187]

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

[0189] For high curvature areas, a spiral path is used for path planning. The path starting point P o As the center of gravity of the surface area, spiral lines are generated outward layer by layer:

[0190] The spiral radius of each layer r n By the upper radius r n-1 And the density value D(x,y,z) determines:

[0191]

[0192] During each layer generation process, the normal consistency of the path is maintained to ensure a smooth path.

[0193] S90: Controlling a grinding device to perform a grinding action on the stamping die according to the grinding path.

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

[0195] The present invention uses high-precision equipment and multi-angle scanning, combined with curvature-sensitive adaptive sampling, alignment and difference analysis, to ensure high-precision alignment and correction in areas with complex curvature. Adaptive finite element analysis and intelligent grinding path planning can reduce the time for redundant calculations and repeated grinding, and significantly reduce the time for trial and development. The real-time feedback grinding system combines multi-dimensional difference analysis and compensation mechanisms to ensure that the final mold meets high-precision requirements and improves the overall quality of stampings. It can provide a fine grinding path for molds with complex surfaces, reduce trial and error time, and improve the final accuracy of the mold and product.

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

[0197] 1) The present invention provides a stamping die trial and fitting control method. First, the present invention performs calculations based on the actual three-dimensional point cloud data and virtual three-dimensional point cloud data of the stamping die, thereby realizing a specific comparison and analysis of the actual surface and the ideal surface of the stamping die to determine the first area to be repaired. Since the parameters during mold design are designed based on ideal conditions, 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 molding and the ideal surface data, thereby accurately determining the first area to be repaired, reducing the reliance on the experience of engineering personnel, reducing the influence of human subjective factors on the trial and fitting process, and improving the accuracy of data and the accuracy of subsequent polishing operations.

[0198] However, the analysis process of the existing trial and development methods is mostly conducted by engineering personnel based on experience, which is highly subjective and greatly affected by human factors. In addition, since it requires multiple mold closing, grinding, and re-mold closing for repeated confirmation, the trial and development process is time-consuming and inefficient.

[0199] 2) The present invention simulates the deformation of the stamping parts under different pressures according to a preset virtual mold closing simulation model, predicts the contact area and pressure distribution between the stamping die and the stamping parts during the actual stamping process, and determines the second area to be repaired according to the contact area and the pressure distribution; since performing actual mold closing operations requires a lot of manpower, material resources and time costs, the present invention constructs a preset virtual mold closing simulation model to perform actual mold closing simulation, thereby determining the second area to be repaired, which can effectively improve the work efficiency of trial and research and reduce the manpower, material resources and time costs of trial and research and 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; generates a polishing path according to the area to be polished by using a path planning algorithm; and controls the polishing equipment to perform polishing on the stamping die according to the polishing path. The present invention combines the first area to be repaired and the second area to be repaired to accurately identify the area to be polished of the stamping die, and generates a polishing path according to the area to be polished, thereby improving the polishing efficiency and polishing accuracy, achieving refined control of the polishing parameters during the polishing process, and ensuring the accuracy of the mold polishing process, especially for areas with large curvature changes, the surface correction amount can be more accurately controlled, the success rate of the correction of this mold is improved, and the time for repeated polishing and verification is greatly shortened, thereby further improving the efficiency of the entire trial and testing process, achieving efficient and accurate mold correction effects, greatly reducing manual intervention, and improving the accuracy and efficiency of mold trial and testing.

[0201] In some embodiments, the present invention further provides a stamping die test and research control system, the system comprising:

[0202] 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;

[0203] 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;

[0204] A first determining 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, used to simulate the deformation of the stamping part 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;

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

[0208] 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;

[0209] A second production module is used to generate a grinding path according to the area to be polished by using a path planning algorithm;

[0210] The control module is used to control the grinding equipment to perform grinding action on the stamping die according to the grinding 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 method described in the above method embodiment. Its specific implementation can refer to the description of the above method embodiment. For the sake of brevity, it will not be repeated here.

[0212] The present invention also provides an electronic device, including a processor and a memory, wherein 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 a method as described in any possible implementation manner.

[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 executes a method as described in any possible implementation manner.

[0214] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond 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 aforementioned method embodiments, and will not be repeated here. Those skilled in the art can also clearly understand that the descriptions of the various embodiments of the present invention have different focuses. For the convenience and brevity of description, the same or similar parts may not be repeated in different embodiments. Therefore, for parts not described or not described in detail in a certain embodiment, refer to the records of other embodiments.

[0216] In the 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 only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0217] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may 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 by 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 process or function described in the embodiment of the present invention is generated in whole or in part. 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 through the computer-readable storage medium. The computer instructions can be transmitted from a website site, computer, server or data center to another website site, computer, server or data center by wired (e.g., coaxial cable, optical fiber, digital subscriber line (digital subscriber line, DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) mode. The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device such as a server or data center that includes one or more available media integrated. The available medium may be a magnetic medium (eg, a floppy disk, a hard disk, a magnetic tape), an optical medium (eg, a digital versatile disc (DVD)), or a semiconductor medium (eg, a solid state disk (SSD)).

[0219] A person skilled in the art can understand that to implement all or part of the processes in the above-mentioned embodiments, the processes can be completed by a computer program to instruct the relevant hardware, and the program can be stored in a computer-readable storage medium. When the program is executed, it can include the processes of the above-mentioned method embodiments. The aforementioned storage medium includes: a read-only memory (ROM) or a random access memory (RAM), a magnetic disk or an optical disk, and other media that can store program codes.

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; Determining a first area to be repaired according to the difference value and a preset tolerance range; 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; 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: 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: The preset virtual mold simulation model is constructed using the actual three-dimensional point cloud data and stamping process parameters of the stamping die.

8. The stamping die test control method according to claim 1, characterized in that: The method simulates the deformation of the stamping part under different pressures based on the preset virtual joint simulation model, and predicts the contact area and pressure distribution between the stamping die and the stamping part during the actual stamping process, including: Finite element meshing of dies and stampings; 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; 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; 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.

9. 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.

10. 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 determining module, configured to determine a difference value according to the actual three-dimensional point cloud data and the virtual three-dimensional point cloud data; 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, used to simulate the deformation of the stamping part 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; 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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