Motor iron core stamping die assembly surface high-fidelity rapid modeling method and system

Abstract

The invention discloses a high-fidelity rapid modeling method and system for a motor iron core stamping die assembly surface. The method comprises the following steps: 1, establishing a simulation ideal model of a concave template and an insert, and generating a grid; and collecting point cloud data of the female template and the insert assembly surface. And 2, respectively fitting and establishing curved surfaces according to the point cloud data of the female template and the insert assembly surface. And 3, shifting grid nodes on the surfaces of the simulation ideal models of the concave template and the insert to the corresponding curved surfaces established in the step 2, and correspondingly shifting grid nodes in the models to obtain an actual assembly model. According to the method, the grid nodes on the surface of the simulation model are shifted to the NURBS accurate contact surface generated by the point cloud data, geometric errors of the assembly surface are fully considered, simulation is closer to the actual situation, hole center deformation after mold assembly can be accurately predicted, and effective guidance is provided for mold assembly.

Description

Technical Field

[0001] The present invention belongs to the technical field of digital twin modeling, and specifically relates to a high-fidelity rapid modeling method and system for the assembly surface of a motor core stamping die. Technical Background

[0002] In the field of motor core stamping die assembly, the geometric error of the assembly surface has a universal impact on assembly accuracy. Even if the dimensional tolerance and matching requirements are considered in the processing design stage, the contact surface of the mold insert and the template will present an irregular geometric shape due to various factors such as machine tool accuracy, tool wear, process system geometric error, and force and heat deformation. This surface irregularity has a significant impact on the assembly accuracy of the mold. Traditional simulation methods rely on ideal geometric surface modeling and ignore processing errors, resulting in significant deviations between simulation predictions and actual assembly. In the traditional forward modeling process, data processing and precise modeling, virtual assembly, and then importing the complex path of finite element simulation platform for multi-physics field analysis across platforms lead to low model reconstruction efficiency and easy distortion of multi-software data conversion. Due to the limitations of geometric model format conversion between different software, especially the differences in the discretization expression of complex surfaces, it is difficult to fit the actual geometric features when generating meshes.

[0003] In order to overcome the above problems, the present invention proposes a method for high-fidelity rapid modeling based on the geometric error of the motor core stamping die assembly surface using an innovative node offset method. Through the geometry-simulation integrated modeling architecture, the full-chain closed loop of error characterization, mesh optimization and contact analysis is realized in a single CAE environment.

[0004] This method uses a three-coordinate measuring machine to scan the mold surface and obtain point cloud data. In the finite element simulation platform, a three-dimensional model is established from the two-dimensional model according to the drawings of the concave template and the insert. Then, the point cloud data is subjected to error elimination and data filtering. Based on these surveying and mapping data, a NURBS surface model (non-uniform rational B-spline) is constructed to find the mapping of the nodes on the assembly surface on the NURBS surface, and the holes in the template and the mesh nodes of the outer ring of the insert are offset to the corresponding NURBS surface. Through the flexible adjustment of control points and weights, NURBS can accurately fit surfaces with irregular features such as local protrusions and depressions. In addition, NURBS surfaces allow geometric errors to be analyzed at different scales, taking into account global shapes and local details. Through the construction of geometric error surfaces and node offsets, accurate surface modeling is achieved directly in the simulation software, reducing errors in actual assembly, improving the overall accuracy of the mold, and thus improving assembly quality. This method can also be extended to precision scenes such as gear pair meshing and bearing raceway assembly, but this patent focuses on the assembly surface modeling of motor core stamping dies. Compared with the traditional forward modeling method, this solution reduces 80% of data interface redundancy and shortens the modeling cycle by 60%. Summary of the invention

[0005] The purpose of the present invention is to provide a method and system for high-fidelity rapid modeling of the assembly surface of a motor core stamping die, aiming at the influence of geometric errors formed by the processing of assembly parts on the assembly accuracy during the mechanical assembly process of the motor core stamping die. The traditional forward modeling method uses multiple software to establish accurate surface simulation, and the data format conversion between different software is difficult, and there are errors in model integration. The present invention is based on a new node offset technology, and directly constructs an accurate surface model in a finite element simulation platform. Through specific steps such as constructing a NURBS surface model, node offset, etc., the geometric errors between assembly parts are accurately simulated, thereby improving the assembly accuracy of the mold. This method provides theoretical support for the mechanical design and assembly of precision molds, and can accurately predict the assembly results. It is a general and efficient accurate modeling and simulation technology.

[0006] In a first aspect, the present invention provides a high-fidelity rapid modeling method for an assembly surface of a motor core stamping die, which comprises the following steps:

[0007] Step 1: Establish an ideal simulation model of the concave template and the insert, and generate a mesh. The mesh nodes on the assembly surface use an adaptive mesh; collect point cloud data of the actual concave template and the insert assembly surface.

[0008] Step 2: Build curved surfaces by fitting based on the point cloud data of the concave template and the insert assembly surface.

[0009] Step 3: offset the mesh nodes on the surface of the ideal simulation model of the concave template and the insert to the corresponding surface established in step 2, and offset the internal mesh nodes of the model accordingly to obtain the actual assembly model.

[0010] As a preferred method, the process of establishing the surface is as follows: using the point cloud data as the shape value point Q of the surface k,l ; Obtain the node parameters corresponding to the measured data points in the point cloud data through the cumulative chord length method, and establish the curve node vector; Construct the NURBS surface; According to the type value point Q k,l Generate interpolation points on NURBS surfaces; extract extreme point sets on NURBS surfaces.

[0011] Preferably, the process of offsetting the nodes on the model surface in step 3 is as follows:

[0012] (1) For each adaptive mesh node on the surface of the simulated ideal model , both look for the closest interpolation point Q on the surface k,l,t , as a candidate target point .

[0013] (2) Calculate the candidate target points corresponding to each adaptive grid node The distance between the extreme point closest to itself. Determine each candidate target point separately Whether the corresponding distance is less than the target point moving threshold; if it is satisfied, the candidate target point The closest extreme point is taken as the final target point Otherwise, the candidate target point Directly as the final destination .

[0014] (3) Each mesh node on the surface of the simulated ideal model Transfer to the corresponding final destination point respectively .

[0015] As an example, the target point moving threshold is set to 1×10 -5 ~3×10 -5 .

[0016] Preferably, the offset vector of the internal grid node of the simulation ideal model is The expression is as follows:

[0017]

[0018]

[0019] in, , are the offset vectors of surface mesh node i and internal mesh node j respectively; is the weight coefficient of surface mesh node i to internal mesh node j; To control the coefficient of distance attenuation; , are the coordinates of the surface grid node i and the internal grid node j before migration; L ref is the average unit side length; J j is the Jacobian determinant of the unit to which the internal grid node j belongs; J ref is the Jacobian reference value; AR j is the aspect ratio of the unit to which the internal grid node j belongs, AR ref is the reference value of the aspect ratio; α and β are the exponents controlling the Jacobian and aspect ratio weights, respectively.

[0020] Preferably, the interference fit simulation is performed using the actual assembly model, and the offset distance of the die is extracted from the simulation results as the assembly deformation between the hole of the die plate and the insert.

[0021] Preferably, the sampling point spacing of the point cloud data in step 1 is 1 mm to 2 m; the point cloud data is filtered and error separated. Further preferably, the preset tolerance range in the error separation is 5% to 7%.

[0022] Preferably, the ideal simulation models of the concave template and the insert are both set to elastic deformation, and a surface-to-surface contact relationship is established, and the actual friction force is simulated by a contact friction penalty model.

[0023] In a second aspect, the present invention provides a high-fidelity rapid modeling system for the assembly surface of a motor core stamping die, which is used to execute the aforementioned high-fidelity rapid modeling method for the assembly surface of a motor core stamping die; the modeling system includes a three-coordinate measuring instrument, a NURBS surface generation module, and a finite element simulation module. The three-coordinate measuring instrument is used to collect point cloud data; the NURBS surface generation module is used to generate a surface according to the point cloud data; the finite element simulation module is used to establish a simulation model, and offset the mesh nodes of the simulation model according to the surface generated by the point cloud data.

[0024] In a third aspect, the present invention provides a method for assembling a motor core stamping die, which comprises the following steps:

[0025] Step 1: Execute the aforementioned high-fidelity rapid modeling method for the assembly surface of the motor core stamping die to model the assembled die holes and inserts.

[0026] Step 2: Obtain the die hole model and the insert model in step 1, perform interference fit simulation at different relative angles, and obtain the die offset distances at different relative angles; take the relative angle with the smallest die offset distance as the installation angle.

[0027] Step 3: Perform interference fit between the actual mold hole and the insert to be assembled according to the installation angle determined in step 2.

[0028] The beneficial effects of the present invention are:

[0029] 1. The present invention provides a novel node offset method, which offsets the mesh nodes on the surface of the simulation model to the NURBS precise contact surface generated by the point cloud data, fully considering the geometric error of the assembly surface, making the simulation closer to the actual situation, and being able to accurately predict the hole center deformation after the mold is assembled, providing effective guidance for the mold assembly.

[0030] 2. The present invention adopts the strategy of "discretizing the basic grid first and then offsetting it to the NURBS precise surface", which significantly simplifies the grid discretization process while retaining the original geometric accuracy. It not only avoids the compatibility problem of cross-platform grid division, but also discretizes the grid nodes to the extreme points of the surface, fully ensuring the high fidelity of the geometric error of the simulation model.

[0031] 3. The present invention realizes an accurate digital twin model including processing errors that can be directly used for simulation analysis. Through the geometry-simulation integrated modeling architecture, a full-chain closed loop of error characterization, mesh optimization and contact analysis is realized in a single CAE environment, which reduces the data interaction links between software, reduces the risks of data loss and error introduction, improves modeling efficiency and simulation accuracy, and simplifies the simulation process. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] Figure 1 It is a flow chart of the present invention.

[0033] Figure 2 This is a simulation ideal model diagram of the concave template and the insert obtained in step S200 of the present invention.

[0034] Figure 3 This is the actual assembly model diagram of the concave mold plate and the insert obtained in step S400 of the present invention.

[0035] Figure 4 This is a contact pressure distribution diagram of the concave mold plate and the insert after interference fit in the mold obtained in step S500 of the present invention. DETAILED DESCRIPTION

[0036] The following describes the embodiments of the present invention by specific examples, and those skilled in the art can easily understand other advantages and effects of the present invention from the contents disclosed in this specification. The present invention can also be implemented or applied through other different specific embodiments, and the details in this specification can also be modified or changed in various ways based on different viewpoints and applications without departing from the spirit of the present invention. It should be noted that the following embodiments and features in the embodiments can be combined with each other without conflict.

[0037] Example 1

[0038] like Figure 1 As shown, a high-fidelity rapid modeling method for the assembly surface of a motor core stamping die comprises the following steps:

[0039] Step S100 determines the processing drawing information and process requirements, and measures the point cloud data of the contact surface:

[0040] First, according to the actual processing requirements of the motor core mold, obtain and confirm the mold drawing information and corresponding process requirements. The drawing information includes but is not limited to: the nominal diameter of the concave mold plate and the insert, tolerance range, shape error, position error, interference fit size, etc. This information provides basic data for subsequent measurement and simulation modeling.

[0041] Before assembly, use a three-dimensional coordinate measuring machine (CMM) to measure the finished concave plate and insert assembly surface with high precision. Before using the three-dimensional coordinate measuring machine, it is necessary to calibrate the measuring machine with a standard ball according to the instrument operating procedures to ensure that the measurement error is within the allowable range. During the calibration process, the standard ball is measured multiple times, the measurement data is obtained and compared with the standard value, and the measurement deviation is calculated. If the deviation exceeds the specified range, the measuring machine needs to be adjusted or repaired until the accuracy requirements are met.

[0042] Before S110 measurement, clean the concave template and insert to ensure that there are no interference factors such as oil, impurities, etc. on the surface.

[0043] The S120 coordinate measuring machine uses a sub-micron-level stylus to ensure that the measurement accuracy can meet the design requirements. The length of the stylus is adapted according to the depth of the concave template and the insert measurement part to ensure that the stylus can accurately contact the measurement surface during the measurement process without excessive deformation or interference. At the same time, check the installation firmness and verticality of the stylus. After installation, use a standard gauge block to perform simulated measurement to verify the measurement repeatability of the stylus.

[0044] S130 uses a multi-point sampling method to measure the inner surface of the concave template, and densifies the sampling points in key matching areas (such as the hole wall and positioning surface that match the insert); in this embodiment, the sampling point spacing is set to 1mm; in some embodiments, the sampling spacing in other areas is appropriately adjusted according to the surface curvature and size, but the minimum is not less than 2mm. For the outer surface of the insert, the key parts in contact with the concave template are also measured to ensure that the geometric morphology information of the assembly surface can be fully and accurately obtained.

[0045] The above steps use a three-coordinate measuring machine to record the point cloud data of the inner wall of the concave template and the outer surface of the insert. These data will be used for subsequent geometric error analysis and simulation modeling.

[0046] Step S200: Finite element simulation modeling

[0047] Based on the drawing information of the motor core mold, the finite element simulation software is used to build an ideal simulation model of the motor core mold assembly.

[0048] Based on the drawing information of the motor core mold, S210 uses drawing software to draw a 2D sketch of the motor core mold and converts its format into the standard file IGES format so that it can be imported into the simulation software to establish a 3D solid model. During the conversion process, the integrity and accuracy of the geometric elements are checked to ensure that there will be no data loss or errors when imported into the simulation software.

[0049] S220 imports the sketch into the simulation software, creates a three-dimensional solid model of the concave mold plate and inserts in the motor core mold, and assembles them.

[0050] S230 sets the material properties. The material of the concave plate in the motor core mold is mold steel DC53, and the material of the insert is cemented carbide ZNF26. Since the contact deformation between the concave plate and the insert is interference contact, their deformation is elastic deformation, so it is necessary to set the material density, elastic modulus and Poisson's ratio. The material parameters of the concave plate and the insert in this embodiment are shown in Table 1

[0051] Table 1 Mould material parameters

[0052] Material <![CDATA[Density / (t / mm 3 )]]> Young's modulus / (MPa) Poisson's ratio DC53 <![CDATA[7.8×10 -9 ]]> <![CDATA[2.31×10 6 ]]> 0.285 ZNF26 <![CDATA[1.4×10 -8 ]]> <![CDATA[5.86×10 6 ]]> 0.235

[0053] S240 establishes a surface-to-surface contact relationship between the concave plate and the insert, and enables the contact friction penalty model to simulate the friction force in the actual contact process. By consulting the relevant friction coefficient manual and actual experience data, combined with the working environment of the mold (such as lubrication conditions, working temperature, etc.), the friction coefficient is determined to be 0.15. The normal contact is set to hard contact to ensure that the contact surfaces do not penetrate each other during the assembly process.

[0054] S250 meshes the mold and the insert, and the mesh size matches the sampling point spacing in step S130; in this embodiment, the mesh size is 1 mm. Based on the actual processing requirements, the corresponding concave plate mesh and insert mesh in the motor core mold are selected as the adaptive mesh area, and the mesh nodes on the inner surface of the concave plate and the mesh nodes on the outer surface of the insert are selected as the adaptive mesh nodes, so as to establish the precise surface of the concave plate and the insert in the subsequent simulation. Establish the analysis step, and set the output variables as stress, strain, displacement field, contact pressure and node coordinates.

[0055] The concave template model and insert model obtained in this step are as follows Figure 2 shown.

[0056] Step S300 processes the point cloud data, removes random errors and extracts valid data.

[0057] In the specific implementation of the present invention, after obtaining the point cloud data collected by the three-dimensional coordinate measuring machine, the data needs to be preprocessed because the point cloud data may contain random errors caused by the measuring equipment or environmental conditions. The specific process is as follows:

[0058] S310 data pre-screening: Based on the least squares filtering algorithm, it identifies obvious outliers in the measured point cloud data and filters out noise points generated during the measurement process by setting a threshold.

[0059] S320 Error Separation: Based on the least squares curve fitting method and residual filtering method, the point cloud data is fitted into a preliminary surface model, and then the deviation of each measured point relative to the fitted surface is calculated to eliminate the points that exceed the preset tolerance range.

[0060] S330 Extract valid data: After eliminating random errors, further analyze the remaining data to extract point cloud data type value points Q suitable for establishing accurate surfaces k ,l (k=0 ,1 ,…,n;l=0 ,1 ,…,m), n+1 and m+1 are the number of layers of point cloud collection and the number of points in each layer respectively. These valid data should cover the entire contact surface and ensure that the point cloud density is high enough to meet the requirements of NURBS surface fitting.

[0061] Through the processing of the above steps, the point cloud data obtained not only removes the random errors in the measurement, but also extracts the precise surface geometry information, ensuring the accuracy of the simulation modeling.

[0062] Step S400 NURBS surface equation development and node offset

[0063] S410 writes a NURBS surface equation subroutine through secondary development to build a NURBS surface model of the contact surface between the concave template and the insert. The specific steps are as follows:

[0064] Determine the degree of the NURBS surface as p and q, the value point Q k,l The weight factor is w k,l =1, for the point cloud data type value point Q after error separation k ,l (k=0,1,…,n;l=0,1,…,m); n+1 and m+1 are the number of layers of point cloud collection and the number of points in each layer respectively; the cumulative chord length method is used for parameterized calculation to obtain the node parameters corresponding to all measured data points in the same layer , and further calculate the curve node vector U as follows:

[0065] (1)

[0066] (2)

[0067] (3)

[0068] (4)

[0069] (5)

[0070] in, are the coordinates of two adjacent measurement data points; k and l are the measurement data type value points The serial number in the point cloud data, d is the sum of the distances between two adjacent measurement data points.

[0071] Similarly, calculate the node parameters And the curve node vector V is as follows:

[0072] (6)

[0073] (7)

[0074] (8)

[0075] (9)

[0076] (10)

[0077] Using NURBS surface reconstruction technology, based on the NURBS surface equation, the NURBS surface is constructed. The surface must pass through the value point, and the control point P is calculated by the following formula k,l as follows:

[0078]

[0079] in, represents the rational basis function of the p-order NURBS curve determined by the i-th data point; represents the rational basis function of the q-order NURBS curve determined by the j-th data point; P k,l Represents the NURBS surface control mesh vertex. Calculate the control point to get the value interpolation point Q k,l,t , and get the extreme point set (TOTAL in total) of the distance to the axis in the NURBS surface POINT_MAX_MIN=(x t ,y t ,z t ), (t=1,2,…,TOTAL).

[0080] In this embodiment, a high-precision numerical calculation method (such as Gaussian elimination method or LU decomposition method) is used to ensure the accuracy of control point calculation, and the calculation results are verified and analyzed, for example, to check whether the control points meet the geometric continuity and smoothness requirements of the curve.

[0081] In the process of constructing the surface, this embodiment analyzes and verifies the shape and characteristics of the surface, for example, checks whether the curvature change of the surface conforms to the geometric characteristics of the actual assembly surface, and ensures that the surface equation can accurately describe the geometric shape of the assembly surface through comparison and visualization with the original point cloud data.

[0082] S420 finds the mapping of the nearest point or extreme point of the node on the ideal simulation model on the NURBS surface, and offsets the mesh nodes of the holes in the template and the outer ring of the insert to the corresponding NURBS surface. The specific steps are as follows:

[0083] S421 For each grid node on the simulation ideal model , using the optimization method to obtain the nearest interpolation point on the NURBS surface .

[0084] S422 After step S421, each adaptive mesh node on the surface of each simulation ideal model Find the nearest interpolation point Q on the NURBS surface k,l,t , as a candidate target point ;

[0085] S423 For each candidate target point corresponding to the adaptive grid node , calculate each candidate target point again The distance to the closest extreme point is calculated as follows:

[0086]

[0087] Determine the distance deter_min is less than 10 -5 Whether the condition is met, if so, the candidate target point The closest extreme point is taken as the final target point Otherwise, the candidate target point Directly as the final destination ; Finally, each adaptive mesh node on the surface of the ideal model will be simulated Transfer to the corresponding final target points on the NURBS surface respectively ; Its corresponding displacement vector .

[0088] S424 will each adaptive grid node According to the displacement vector corresponding to itself Move; each adaptive mesh node After the movement, the controlled motion of the internal mesh nodes of the simulation ideal model is realized through the arbitrary Lagrangian-Euler (ALE) method. The internal mesh nodes (total_inter) are represented by the set Under the condition of minimizing mesh distortion, the Jacobian and aspect ratio of the original mesh will change. To ensure high mesh quality, a weight coefficient w is proposed in this embodiment. ij , give the remaining mesh nodes an offset correction to ensure that the quality of the mesh meets the requirements. The remaining mesh nodes (total_other) refer to the nodes inside the model, that is, .

[0089] In order to comply with the smoothness principle of the ALE adaptive mesh, this embodiment proposes a mesh-based Jacobian and aspect ratio coefficient for the correction of the remaining mesh nodes.

[0090]

[0091]

[0092] in is the displacement vector of the node in the other node set, To control the distance attenuation coefficient, L ref is the average unit side length, J j For Node The Jacobian of the unit, J ref is the Jacobian reference value, AR j For Node The aspect ratio of the unit, AR ref is the reference value of aspect ratio, is an exponent that controls the Jacobian and aspect ratio weights.

[0093] Through ALE adaptive mesh offset, the adaptive mesh boundary nodes will be offset to the exact surface, and the remaining mesh nodes will be adjusted accordingly based on the smoothness principle and the Jacobian and aspect ratio coefficients of the mesh to ensure the convergence of the mesh quality. All adaptive mesh nodes After all the nodes are moved, the remaining mesh nodes are redrawn after ALE adaptive mesh correction to obtain the actual assembly model of the motor core stamping die.

[0094] The actual assembly model obtained in this step is as follows Figure 3 shown.

[0095] Step S500 performs interference fit simulation, and extracts the die offset distance according to the simulation result, and compares it with the actual measurement result to verify the accuracy of the simulation model.

[0096] S510 submits the constructed actual assembly model and the set parameters to the solver for simulation calculation, and obtains the displacement deformation, mesh stress, mesh strain and contact pressure (such as Figure 4 As shown). According to the displacement deformation at different positions, the center offset of the hole of the concave template is obtained as the concave mold offset distance; the concave mold offset distance is used as the assembly deformation between the template hole and the insert. Before submission, check the integrity of the model and the rationality of the parameters to ensure that the solver can run the simulation calculation correctly. During the simulation calculation process, monitor the calculation progress and resource usage in real time, such as memory usage, CPU usage, etc., and adjust the calculation parameters or hardware resource allocation according to the actual situation to ensure that the simulation calculation can be completed smoothly.

[0097] S520 extracts simulation offset data: based on the simulation results, locates the node coordinates corresponding to the actual measurement position (such as the edge node of the insert), and fits the hole offset of the concave template through the weighted least squares method to ensure the weight distribution of key areas to improve the fitting accuracy.

[0098] S530 obtains actual offset data: uses actual assembly data collected by a three-dimensional coordinate measuring machine, and after error compensation, fits the actual circle center offset based on the least squares method to eliminate the influence of measurement noise on the result.

[0099] S540 Comparative analysis and model optimization: Statistical analysis (such as error percentage, standard deviation, etc.) is performed on the simulated offset data and the actual offset data. If the error is within the allowable range (≤5%), the model is valid and can be directly used for mold design and process optimization; if it is out of tolerance, it is necessary to iteratively correct the contact model parameters (such as friction coefficient, material properties) or re-evaluate the processing error data until the simulation results converge with the actual assembly error.

[0100] In order to verify the superiority of this method, a motor core mold of a certain enterprise is used as an example, and the inner diameter tolerance of the concave mold plate is Φ35.5±0.005mm. The assembly surface point cloud data is obtained by a three-coordinate measuring instrument, and the node offset method is used to construct a NURBS surface model (the control point density is 1 / 3 of the traditional method). The simulation results show that the predicted value of the insert center offset is 15.3μm in the horizontal direction and 13.2μm in the vertical direction. The absolute error of the horizontal offset of 15.5μm with the actual assembly measurement value is 0.2μm, and the relative error is only 1.3%. The actual assembly measurement value is 13.5 in the vertical direction, and the relative error is only 2.2%. The predicted value of the traditional ideal model is 12.5μm in the horizontal direction, with a relative error of 19.4%, and 11.9 in the vertical direction, with a relative error of 11.8%.

[0101] Table 2 Comparison between the ideal model method and the method of the present invention

[0102] index Traditional ideal model Method of the present invention Improvement effect Horizontal error of hole center deviation prediction (μm) 3.0 (error 19.4%) 0.2 (error 1.3%) Accuracy improved by 74.4% Vertical error predicts horizontal error (μm) 1.6 (error 11.8%) 0.3 (error 2.2%) Accuracy improved by 81.3% Surface detail loss 18% <2% Detail restoration increased by 88%

[0103] To illustrate the simplicity of this method, a motor core mold of a certain enterprise is used as an example, and the inner diameter tolerance of the concave mold plate is Φ35.5±0.005mm. The assembly surface point cloud data is obtained by a three-coordinate measuring instrument. Compared with the traditional forward modeling process in the existing precise modeling technology, which requires cross-platform data processing and parametric modeling, reverse engineering modeling, virtual assembly, and then importing the finite element simulation platform for multi-physical field analysis, the method of the present invention uses the node offset method to construct a NURBS surface model in the finite element simulation platform to directly establish an accurate surface model. The simulation results show that the center offset of the insert of the present invention is 15.3μm in the horizontal direction and 13.2μm in the vertical direction. The absolute error of the horizontal offset of 15.5μm with the actual assembly measurement value is 0.2μm, and the relative error is only 1.3%. The actual assembly measurement value is 13.5 in the vertical direction, and the relative error is only 2.2%. The predicted value of the traditional forward modeling technology is 15.2μm in the horizontal direction, with a relative error of 1.4%, and 13.1 microns in the vertical direction, with a relative error of only 2.9%. This method shortens the modeling cycle from 4 hours to 1.6 hours, improving efficiency by 60%.

[0104] Table 3 Comparison between traditional forward modeling method and the method of the present invention

[0105] index Traditional forward modeling method Method of the present invention Improvement effect Data interaction steps 5 times 1 time 80% reduction Modeling time (hours) 4.0 1.6 60% shorter Meshing time (hours) 1.0 0.5 50% shorter Offset prediction horizontal error (μm) 0.3 (error 1.4%) 0.2 (error 1.3%) Almost no difference in accuracy Offset prediction vertical error (μm) 0.3 (error 2.2%) 0.4 (error 2.9%) Almost no difference in accuracy Model correction iterations 5 times 2 times 60% reduction

[0106] The above data show that this method greatly simplifies the modeling process while ensuring sub-micron accuracy, providing technical support for enterprises to achieve "one-time modeling, accurate prediction".

[0107] This embodiment also provides a high-fidelity rapid modeling system for the assembly surface of a motor core stamping die; the modeling system includes a three-coordinate measuring machine, a NURBS surface generation module, and a finite element simulation module. The three-coordinate measuring machine is used to collect point cloud data; the NURBS surface generation module is used to generate a surface based on the point cloud data; the finite element simulation module is used to establish a simulation model and offset the mesh nodes of the simulation model based on the surface generated by the point cloud data.

[0108] Example 2

[0109] A method for assembling a motor core stamping die comprises the following steps:

[0110] Step 1: Model the assembled mold hole and insert. The modeling process is the same as that in Example 1.

[0111] Step 2: Obtain the die hole model and the insert model in step 1, perform interference fit simulation at different relative angles, and obtain the die offset distances at different relative angles; take the relative angle with the smallest die offset distance as the installation angle.

[0112] In this embodiment, interference fit simulations are performed for three different relative angles; the three relative angles are increased by 45° in sequence, and the obtained horizontal and vertical die offset distances are shown in the following table:

[0113] Table 1 Offset distances at different relative angles

[0114] Rotation Angle Horizontal die offset distance Vertical die offset distance 0° 14.9μm 12.8μm 45° 15.1μm 13.6μm 90° 15.6μm 12.8μm

[0115] The relative angle of 45 degrees with the smallest die offset distance is taken as the installation angle.

[0116] Step 3: The actual mold hole to be assembled is connected with the insert according to the installation angle determined in step 2. After actual measurement, the horizontal offset of the insert center is 15.1μm, and the vertical offset is 12.9. Compared with the simulation of 45 degrees counterclockwise rotation, the horizontal error is only 0.2μm, and the vertical error is only 0.1μm.

[0117] As described above, although the present invention has been shown and described with reference to specific preferred embodiments, it should not be construed as limiting the present invention itself. Various changes in form and details may be made without departing from the spirit and scope of the present invention as defined in the appended claims.

Claims

1. A high-fidelity rapid modeling method for the assembly surface of a motor core stamping die, characterized in that: The following steps are involved: Step 1: Establish an ideal simulation model of the concave plate and the insert, and generate a mesh. The mesh nodes on the assembly surface use an adaptive mesh. And collect point cloud data of the concave template and the insert assembly surface; Step 2: Fit and establish curved surfaces according to the point cloud data of the concave template and the insert assembly surface; Step 3: offset the mesh nodes on the surface of the ideal simulation model of the concave template and the insert to the corresponding surface established in step 2, and offset the internal mesh nodes of the model accordingly to obtain the actual assembly model.

2. A high-fidelity rapid modeling method for the assembly surface of a motor core stamping die according to claim 1, characterized in that: The process of establishing a surface is as follows: using point cloud data as the model point Q of the surface k,l ; Obtain the node parameters corresponding to the measured data points in the point cloud data through the cumulative chord length method, and establish the curve node vector; Construct the NURBS surface; According to the type value point Q k,l Generate interpolation points on the NURBS surface; extract extreme point sets on the NURBS surface.

3. A high-fidelity rapid modeling method for the assembly surface of a motor core stamping die according to claim 2, characterized in that: The process of offsetting the nodes on the model surface in step 3 is as follows: (1) For each adaptive mesh node on the surface of the simulated ideal model , both look for the closest interpolation point Q on the surface k,l,t , as a candidate target point ; (2) Calculate the candidate target points corresponding to each adaptive grid node The distance between the extreme point closest to itself; judge each candidate target point separately Whether the corresponding distance is less than the target point moving threshold; if it is satisfied, the candidate target point The closest extreme point is taken as the final target point Otherwise, the candidate target point Directly as the final destination ; (3) Each mesh node on the surface of the simulated ideal model Transfer to the corresponding final destination point respectively .

4. A high-fidelity rapid modeling method for the assembly surface of a motor core stamping die according to claim 3, characterized in that: The target point moving threshold is set to 1×10 -5 ~3×10 -5 .

5. The high-fidelity rapid modeling method for the assembly surface of a motor core stamping die according to claim 1, characterized in that: The offset vectors of the internal mesh nodes of the simulation ideal model are The expression is as follows: ； ； in, , are the offset vectors of surface mesh node i and internal mesh node j respectively; is the weight coefficient of surface mesh node i to internal mesh node j; To control the coefficient of distance attenuation; , are the coordinates of the surface grid node i and the internal grid node j before migration; L ref is the average unit side length; J j is the Jacobian determinant of the unit to which the internal grid node j belongs; J ref is the Jacobian reference value; AR j is the aspect ratio of the unit to which the internal grid node j belongs, AR ref is the reference value of the aspect ratio; α and β are the exponents controlling the Jacobian and aspect ratio weights, respectively.

6. The high-fidelity rapid modeling method for the assembly surface of a motor core stamping die according to claim 1, characterized in that: The actual assembly model is used to perform interference fit simulation, and the die offset distance is extracted from the simulation results as the assembly deformation between the hole of the die plate and the insert.

7. The high-fidelity rapid modeling method for the assembly surface of a motor core stamping die according to claim 1, characterized in that: The sampling point spacing of the point cloud data in step 1 is 1 mm to 2 m; the point cloud data is filtered and error separated.

8. The high-fidelity rapid modeling method for the assembly surface of a motor core stamping die according to claim 1, characterized in that: The ideal simulation models of the concave template and the insert are both set to elastic deformation, and a surface-to-surface contact relationship is established, and the actual friction force is simulated by a contact friction penalty model.

9. A high-fidelity rapid modeling system for the assembly surface of a motor core stamping die, characterized in that: Used to execute a high-fidelity rapid modeling method for the assembly surface of a motor core stamping die as described in claim 1; the modeling system includes a three-coordinate measuring machine, a NURBS surface generation module and a finite element simulation module; the three-coordinate measuring machine is used to collect point cloud data; the NURBS surface generation module is used to generate a surface based on the point cloud data; the finite element simulation module is used to establish a simulation model and offset the mesh nodes of the simulation model based on the surface generated by the point cloud data.

10. A method for assembling a stamping die for a motor core, characterized in that: The following steps are involved: Step 1: Execute the high-fidelity rapid modeling method for the assembly surface of the motor core stamping die as described in claim 1 to model the assembled die holes and inserts. Step 2: Obtain the die hole model and the insert model in step 1, perform interference fit simulation at different relative angles, and obtain the die offset distances at different relative angles; take the relative angle with the smallest die offset distance as the installation angle; Step 3: Perform interference fit between the actual mold hole and the insert to be assembled according to the installation angle determined in step 2.

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