Product parameterized model generation method, device, equipment, system and medium

Abstract

The embodiment of the invention discloses a method, a device, equipment and a system for generating a parameterized model of a product and a medium. The method comprises the following steps: determining optimization parameters of a product and a three-dimensional model for simulating and verifying the product; determining a to-be-parameterized part of the minimum volume in the three-dimensional model, wherein the to-be-parameterized part needs to be divided into grids repeatedly in the process of optimizing the product based on the optimization parameters; segmenting the part to be parameterized from the three-dimensional model; and parameterizing the part to be parameterized. And a parameterized model is generated for the part needing to be divided into the grids repeatedly, so that design optimization of a product is facilitated. In addition, the whole product model does not need to be re-gridded, so that the time consumption is reduced, and the optimization efficiency is improved.

Description

Method, device, equipment, system and medium for generating parametric model of product Technical Field

[0001] The present invention relates to the technical field of product design, and in particular to a method, device, equipment, system and medium for generating a parametric model of a product. Background Art

[0002] Optimization design for products (e.g., mechanical equipment) is a design method based on simulation analysis, applying optimization principles to the design scope. Design optimization is often applied during the detailed design phase of complex products, using automated iterations to simulate within the design space to find the optimal design parameters. When tackling complex product design problems, designers use optimization design methods to identify the appropriate design solution from a range of options, thereby improving design efficiency and quality. The design optimization process relies on a parametric simulation model of the product, which allows for input of design parameters and evaluation of the corresponding performance.

[0003] Meshing during the pre-processing steps of complex product simulations is often time-consuming. As product parameters (typically geometric parameters) change during the iterative design optimization process, the entire product model must be meshed again with each iteration, resulting in significant time consumption. This is especially true when optimizing a large number of product parameters, requiring multiple iterations to achieve an acceptable optimization solution, further increasing the time consumption.

[0004] Summary of the Invention

[0005] The embodiments of the present invention provide a method, device, equipment, system and medium for generating a parametric model of a product.

[0006] First, a method for generating a parametric model of a product is proposed. The method includes:

[0007] Determine the optimized parameters of the product and the three-dimensional model for simulation verification of the product;

[0008] Determining a minimum volume of a to-be-parameterized portion in the three-dimensional model, wherein the to-be-parameterized portion needs to be repeatedly meshed during the process of optimizing the product based on the optimization parameters;

[0009] Segmenting the portion to be parameterized from the three-dimensional model;

[0010] Parameterize the part to be parameterized.

[0011] In a second aspect, a device for generating a parametric model of a product is provided. The device includes:

[0012] A first determination module is used to determine the optimization parameters of the product and to simulate and verify the three-dimensional model of the product;

[0013] a second determining module, configured to determine a minimum volume of a to-be-parameterized portion in the three-dimensional model, wherein the to-be-parameterized portion needs to be repeatedly meshed during the process of optimizing the product based on the optimization parameters;

[0014] A segmentation module, configured to segment the portion to be parameterized from the three-dimensional model;

[0015] The parameterization module is used to parameterize the part to be parameterized.

[0016] In a third aspect, an electronic device is provided. The electronic device includes:

[0017] processor;

[0018] a memory for storing executable instructions of the processor;

[0019] The processor is configured to read the executable instructions from the memory and execute the executable instructions to implement the above method for generating a parameterized model of a product.

[0020] In a fourth aspect, a computer-readable storage medium is provided, on which computer instructions are stored. When the computer instructions are executed by a processor, the method for generating a parametric model of a product as described above is implemented.

[0021] In a fifth aspect, a computer program product is provided, comprising a computer program, which, when executed by a processor, implements the method for generating a parameterized model of the above product.

[0022] As can be seen from the above technical solution, in the embodiments of the present invention, the optimization parameters of the product and a three-dimensional model for simulating and verifying the product are determined; the minimum volume of the parameterized portion to be parameterized in the three-dimensional model is determined, wherein the parameterized portion requires repeated meshing during the product optimization process based on the optimization parameters; the parameterized portion to be parameterized is segmented from the three-dimensional model; and the parameterized portion to be parameterized is parameterized. Therefore, a parameterized model is generated for the portion that requires repeated meshing, facilitating product design optimization. Furthermore, there is no need to re-mesh the entire product model, reducing time consumption and improving optimization efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] The preferred embodiments of the present invention will be described in detail below with reference to the accompanying drawings, so that those skilled in the art will understand the above and other features and advantages of the present invention more clearly. In the accompanying drawings:

[0024] FIG1 is a flow chart of a method for generating a parametric model of a product according to an embodiment of the present invention.

[0025] FIG. 2A is a first schematic diagram of a product according to an embodiment of the present invention.

[0026] FIG. 2B is a first schematic diagram of meshing a product according to the prior art.

[0027] FIG. 2C is a second schematic diagram of meshing a product according to an embodiment of the present invention.

[0028] 3A is a second schematic diagram of a product according to an embodiment of the present invention.

[0029] FIG3B is a schematic diagram of determining associated local features according to an embodiment of the present invention.

[0030] FIG3C is a schematic diagram of meshing a product according to an embodiment of the present invention.

[0031] FIG4 is an exemplary flow chart of a method for generating a parametric model of a product according to an embodiment of the present invention.

[0032] FIG5 is an exemplary structural diagram of an apparatus for generating a parameterized model of a product according to an embodiment of the present invention.

[0033] FIG6 is an exemplary structural diagram of an electronic device according to an embodiment of the present invention.

[0034] The accompanying drawings are numerals as follows: DETAILED DESCRIPTION

[0035] In order to make the purpose, technical solutions and advantages of the present invention more clear, the present invention is further described in detail with reference to the following examples.

[0036] For the sake of brevity and intuitiveness in description, the solution of the present invention is explained below by describing several representative implementations. A large number of details in the implementations are only used to help understand the solution of the present invention. However, it is obvious that the technical solution of the present invention may not be limited to these details when implemented. In order to avoid unnecessarily obscuring the solution of the present invention, some implementations are not described in detail, but only a framework is given. Hereinafter, "including" means "including but not limited to", and "according to..." means "at least according to..., but not limited to only according to...". Due to the language habits of Chinese, when the number of a component is not specifically specified below, it means that the component can be one or more, or can be understood as at least one.

[0037] Recognizing the drawbacks of meshing the entire product model at each iteration of the product design optimization process, the present invention proposes a solution for generating a parametric model of the product. This generates a parametric model only for the product portions that require repeated meshing, facilitating product design optimization. Furthermore, this solution eliminates the need to re-mesh the entire product model, reducing time consumption and improving optimization efficiency.

[0038] FIG1 is a flow chart of a method for generating a parameterized model of a product according to an embodiment of the present invention. As shown in FIG1 , the method includes:

[0039] Step 101: Determine the optimized parameters of the product and the three-dimensional model for simulation verification of the product.

[0040] Here, the three-dimensional model used for simulation and verification of the product is a three-dimensional model for product simulation and verification. The three-dimensional model used for simulation and verification of the product can be a three-dimensional model of the product itself, or it can be a three-dimensional model associated with the product. The three-dimensional model can be the entire area or a partial area of ​​the verification object that needs to be verified by three-dimensional simulation (for example, three-dimensional structure simulation or fluid simulation) during the design process. For example, when it is necessary to verify the overall effect of the product, the three-dimensional model can be a three-dimensional model of the product itself. When it is necessary to verify the heat dissipation effect of the product, the three-dimensional model can be a three-dimensional model of the gas area in the product used for thermal simulation. The product can be implemented as a mechanical equipment product or an electronic product with a geometric shape.

[0041] A 3D model used for product simulation and verification is a digital representation based on points, lines, surfaces, volumes, and various geometric features, typically displayed on a computer or other video device. The product represented by the 3D model can be a real-world entity or a fictional product. This can be done using 3D modeling tools, by measuring the product using instruments, or by using images or videos. Examples of 3D modeling tools include Softimage, Maya, UG, and AutoCAD.

[0042] Product optimization parameters are parameters related to a product that need to be optimized. For example, these can be product attribute parameters, preferably geometric dimension parameters. When these parameters change, product performance typically changes. Therefore, by performing iterative simulations for each specific value of the optimization parameter within its range, the optimal value of the optimization parameter can be found.

[0043] The above exemplary descriptions are typical examples of products, optimization parameters and three-dimensional models. Those skilled in the art will appreciate that such descriptions are merely exemplary and are not intended to limit the scope of protection of the embodiments of the present invention.

[0044] Step 102: Determine a minimum volume of a to-be-parameterized portion in the three-dimensional model, wherein the to-be-parameterized portion needs to be repeatedly meshed during the process of optimizing the product based on the optimization parameters.

[0045] Here, a portion of the 3D model with the smallest volume to be parameterized is determined. This portion is then repeatedly meshed during the product optimization process based on the optimized parameters. The remaining portion of the 3D model, excluding this portion, does not need to be repeatedly meshed during the product optimization process based on the optimized parameters. (The mesh of the remaining portion is only meshed in the first iteration, and the mesh from the first iteration is reused in subsequent iterations.)

[0046] It can be seen that the embodiment of the present invention generates a parameterized model only for the product portion that needs to be repeatedly meshed, which facilitates product design optimization.

[0047] Step 103: Segment the part to be parameterized from the 3D model.

[0048] Step 104: Parameterize the part to be parameterized.

[0049] Here, parameterizing the part to be parameterized means expressing its characteristic dimensions with variables, and then driving the parameterization of the part through changes in the variables. For example, you can input design parameters into the parameterized part, and the parameterized part can output the corresponding 3D model.

[0050] In one embodiment, the optimization parameters include the dimensional parameters of a single local feature of the product. Determining the minimum volume portion to be parameterized in the three-dimensional model in step 102 includes determining a value range for the dimensional parameter; and determining the minimum volume portion in the three-dimensional model that contains the single local feature within the value range and satisfies a first constraint as the portion to be parameterized. The first constraint includes at least one of the following: a constraint on the shape of the minimum volume portion; or a constraint on the size of the minimum volume portion. For example, the single local feature may be a hole or a key area in the product.

[0051] Preferably, the constraints on the shape of the minimum volume portion include: constraining the minimum volume portion to have a standard shape (e.g., a cylinder or a cube) or an irregular specific shape. The constraints on the size of the minimum volume portion may include: constraining the diameter, length, thickness, width, etc. of the minimum volume portion.

[0052] Here, the part to be parameterized with the minimum volume is determined based on the dimensional parameters of a single local feature. The dimensional parameters of a single local feature can be one or more geometric dimensions of the local feature (e.g., length, thickness, width, diameter). A minimum volume is created in the 3D model to encompass the single local feature within the entire design parameter range (i.e., value range) of the dimensional parameter.

[0053] Figure 2A is a first schematic diagram of a product according to an embodiment of the present invention. In Figure 2A , hexagonal nut 10 is the product to be optimized. The three-dimensional model of hexagonal nut 10 includes a hole 11. The diameter of hole 11 is an optimization parameter. The range of values ​​for the hole 11 is [1 mm, 10 mm]. When the diameter of hole 11 changes, the performance of hexagonal nut 10 (such as deformation, strength, etc.) changes accordingly.

[0054] In the optimization design of the hexagonal nut 10 based on the aperture, it is necessary to perform simulations in the aperture design space in an iterative manner to find the optimal value of the aperture. Moreover, the hexagonal nut 10 needs to be meshed in the simulation preprocessing step for each iteration.

[0055] Figure 2B is a first schematic diagram of meshing a product according to prior art techniques. In Figure 2 , in each iteration (corresponding to different values ​​of the aperture), all components of the hexagonal nut 10 are meshed. Furthermore, the optimal aperture value is determined based on the meshed 3D simulation model of the hexagonal nut 10 corresponding to each iteration.

[0056] For example, assume that 10 iterations are performed, each corresponding to a 1 mm increase in aperture. In the first iteration, the aperture of the hexagonal nut 10 is specifically 1 mm, and a first meshing is performed on all components of the hexagonal nut 10 (excluding the aperture). Then, the performance of the hexagonal nut 10 for the first iteration is determined based on the first meshed hexagonal nut 10. In the second iteration, the aperture of the hexagonal nut 10 is specifically 2 mm, and a second meshing is performed on all components of the hexagonal nut 10 (excluding the aperture). Then, the performance of the hexagonal nut 10 for the second iteration is determined based on the second meshed hexagonal nut 10. In the third iteration, the aperture of the hexagonal nut 10 is specifically 3 mm, and a third meshing is performed on all components of the hexagonal nut 10 (excluding the aperture). Then, the performance of the hexagonal nut 10 for the third iteration is determined based on the third meshed hexagonal nut 10. Multiple iterations are performed in this manner until, in the tenth iteration, the aperture of the hexagonal nut 10 is specifically set to 10 mm. All components of the hexagonal nut 10 (excluding the aperture) are meshed for the tenth time. The performance of the hexagonal nut 10 for the tenth iteration is then determined based on the tenth meshed hexagonal nut 10. Finally, the optimal performance of the hexagonal nut 10 from these ten iterations is selected, and the aperture corresponding to the optimal performance is determined as the optimized aperture value.

[0057] It can be seen that in each iteration, all components of the hexagonal nut 10 need to be meshed, which results in a large amount of time consumption.

[0058] Fig. 2C is a second schematic diagram of meshing a product according to an embodiment of the present invention. In Fig. 2C , the smallest volume portion is a cylinder for exemplary illustration.

[0059] The composition range of the cylinder 12 is determined in the three-dimensional model of the hexagonal nut 10. The cylinder 12 contains the hole 11. Therefore, the diameter of the cylinder 12 is greater than the maximum value of the hole diameter (i.e., 10 mm). The diameter of the cylinder 12 that satisfies the maximum value of the hole diameter can be multiple values, and the minimum value that meets the constraint conditions of the shape of the cylinder 12 is determined from these multiple values. The cylinder 12 corresponding to the minimum value is the minimum volume part that needs to be repeatedly divided into grids in the process of optimizing the nut 10 based on the hole diameter. Specifically, the constraint conditions of the shape of the cylinder 12 may include: (1) the minimum value of the diameter of the cylinder 12; (2) the maximum value of the diameter of the cylinder 12; (2) the restriction constraints on the diameter of the cylinder during the meshing process, etc.

[0060] Based on the cylinder 12 identified in FIG2C , in the first iteration (corresponding to different aperture values), meshing is performed on all components of the hexagonal nut 10 (excluding the aperture). Furthermore, in subsequent iterations after the first iteration, meshing is performed only on the cylinder 12. The remaining components of the hexagonal nut 10, excluding the cylinder 12, no longer require meshing, and the mesh used in the first iteration can be reused. Furthermore, the optimal aperture value is determined based on the meshed 3D simulation model of the hexagonal nut 10 for each iteration.

[0061] For example, assume 10 iterations are performed, each corresponding to a 1 mm increase in aperture. In the first iteration, the aperture of the hexagonal nut 10 is specifically set to 1 mm, and a first meshing is performed on all components of the hexagonal nut 10 (excluding the aperture). The performance of the hexagonal nut 10 for the first iteration is then determined based on the first meshed hexagonal nut 10. In the second iteration, the aperture of the hexagonal nut 10 is specifically set to 2 mm, and a second meshing is performed on the cylinder 12. The remaining portion of the hexagonal nut 10 retains the mesh from the first iteration. The performance of the hexagonal nut 10 for the second iteration is then determined based on the second meshing of the hexagonal nut 10 (including the mesh of the remaining portion of the hexagonal nut 10 and the mesh of the cylinder 12 after the second meshing). In the third iteration, the aperture of the hexagonal nut 10 is specifically set to 3 mm, and a third meshing is performed on the cylinder 12. The remaining portion of the hexagonal nut 10 retains the mesh from the first iteration. The performance of the hexagonal nut 10 for the third iteration is then determined based on the third meshing of the hexagonal nut 10 (including the mesh of the remaining portion of the hexagonal nut 10 and the mesh of the cylinder 12 after the third meshing). This process is repeated until the tenth iteration, in which the aperture of the hexagonal nut 10 is specifically set to 10 mm, and a tenth meshing is performed on the cylinder 12 after the tenth meshing. The performance of the hexagonal nut 10 for the tenth iteration is then determined based on the tenth meshing of the hexagonal nut 10 (including the mesh of the remaining portion of the hexagonal nut 10 and the mesh of the cylinder 12 after the tenth meshing). Finally, the optimal performance of the hexagonal nut 10 for these ten iterations is selected, and the specific aperture value corresponding to this optimal performance is determined as the optimized aperture value.

[0062] In one embodiment, the optimization parameters include dimensional parameters (such as distance or angle) between multiple local features of the product; determining the minimum volume part to be parameterized in the three-dimensional model in step 102 includes: determining associated local features associated with multiple local features; determining the value range of the dimensional parameter; determining the minimum volume part among the associated local features in the three-dimensional model that meets the second constraint as the part to be parameterized, wherein the value range of the associated local features is associated with the value range of the dimensional parameter; wherein the second constraint includes at least one of the following: a constraint on the shape of the minimum volume part; a constraint on the size of the minimum volume part.

[0063] Figure 3A is a second schematic diagram of a product according to an embodiment of the present invention. In Figure 3A , the product is a connecting rod. The connecting rod includes a first hole 21 and a second hole 22. The distance between the centers of the first and second holes 21, 22 is the optimization parameter D. The value range of the optimization parameter D is [190 mm, 210 mm]. As can be seen, the optimization parameter includes the dimensional parameters between multiple local features of the product (the first and second holes 21, 22).

[0064] Figure 3B is a schematic diagram illustrating the determination of associated local features according to an embodiment of the present invention. It can be seen that the length of the connecting rod's middle portion 23 is related to the first hole 21 and the second hole 22. For example, when the optimization parameter D between the first hole 21 and the second hole 2 is longer, the middle portion 23 is longer; when the optimization parameter D between the first hole 21 and the second hole 2 is shorter, the middle portion 23 is shorter. Therefore, the middle portion 23 is determined to be an associated local feature. Furthermore, the difference between the maximum and minimum values ​​of the middle portion 23 corresponds to the difference between the maximum and minimum values ​​of the value range of the optimization parameter D. The difference between the maximum and minimum values ​​of the value range of the optimization parameter D is 210 mm minus 190 mm, which equals 20 mm. Therefore, the difference between the maximum and minimum values ​​of the middle portion 23 is also 20 mm. The middle portion 23 also needs to satisfy shape constraints and size constraints. For example, assume that the shape constraint specifies that the middle portion 23 is a rectangular parallelepiped, and the size constraint stipulates that the minimum length E of the middle portion 23 is 17 mm. Then, it can be determined that the length E of the middle portion 23 with the smallest volume ranges from [17 mm, 37 mm]. The size constraint can come from the aspect ratio constraint for the mesh object in meshing, etc.

[0065] Figure 3C is a schematic diagram of meshing a product according to an embodiment of the present invention. In Figure 3C , the minimum volume portion is a rectangular parallelepiped for exemplary illustration. The composition range of the middle portion 23 is determined within the three-dimensional model of the connecting rod. Middle portion 23 is the minimum volume portion that needs to be repeatedly meshed during the connecting rod optimization process based on the optimization parameter D.

[0066] Based on the middle portion 23 determined in FIG3C , all components of the connecting rod are meshed in the first iteration (corresponding to different values ​​of the optimization parameter D). Furthermore, in the subsequent iterations after the first iteration, only the middle portion 23 needs to be meshed. The remaining components of the connecting rod, excluding the middle portion 23, do not need to be meshed, and the mesh used in the first iteration for the remaining components can be reused. Furthermore, the optimal value of the optimization parameter D is determined based on the meshed 3D simulation model of the connecting rod corresponding to each iteration.

[0067] For example, assume that 20 iterations are performed, each corresponding to a 1 mm increase in aperture. In the first iteration, the optimization parameter D is specifically 190 mm, the length E of the middle portion 23 is 17 mm, and a first meshing is performed on all components of the connecting rod. The performance of the connecting rod for the first iteration is then determined based on the first meshed connecting rod. In the second iteration, the optimization parameter D is specifically 191 mm, the length E of the middle portion 23 is 18 mm, and a second meshing is performed on the middle portion 23. The mesh of the remaining portion of the connecting rod is retained in the first iteration. The performance of the connecting rod for the second iteration is then determined based on the second meshing of the connecting rod (including the mesh of the remaining portion and the mesh of the second meshed middle portion 23). Repeat this process until, at the 20th iteration, the optimization parameter D is set to 210 mm, the length E of the middle portion 23 is set to 37 mm, and the middle portion 23 is meshed for the 20th time. The remaining portion of the connecting rod retains the mesh from the first iteration. The performance of the connecting rod at the 20th iteration is then determined based on the 20th meshed connecting rod (including the mesh of the remaining portion and the mesh of the middle portion 23 after the 20th meshing). Finally, the optimal performance of the connecting rod at these 20 iterations is selected, and the specific value of the optimization parameter D corresponding to this optimal performance is determined as the optimized value of the optimization parameter D.

[0068] In the above description, the specific method for determining the minimum volume of the parameterized portion is achieved by analyzing the specific properties of the optimization parameters (the size parameters of a single local feature or the size parameters between local features). In practice, it is also possible to directly determine the minimum volume of the parameterized portion based on multiple instances of the 3D model without analyzing the specific properties of the optimization parameters.

[0069] In one embodiment, determining the minimum volume of the portion to be parameterized in the three-dimensional model in step 102 includes: creating multiple instances of the three-dimensional model based on the value range of the optimization parameter; determining the overlapping portion of the multiple instances; and determining the minimum volume of the portion to be parameterized based on the overlapping portion. When determining the overlapping portion of the multiple instances, a center alignment method, a left alignment method, a right alignment method, or the like can be used for the multiple instances.

[0070] In one embodiment, determining the portion to be parameterized with the minimum volume based on the overlapping portion may include:

[0071] (1): The remaining area except the overlapping part is determined as the minimum volume to be parameterized;

[0072] (2): Determine the regular shape part inscribed in the overlapping part; determine the remaining area except the regular shape part as the minimum volume part to be parameterized.

[0073] For example, assume that the optimization parameters include the diameter A of the first hole of the connecting rod (ranging from 1 mm to 10 mm) and the diameter B of the second hole (ranging from 20 mm to 30 mm). 100 3D model instances of the connecting rod can be generated, each corresponding to a different value of the diameter A and the diameter B. For example, the 100 instances are: [1,20], [1,21]…[1,31], [2,20], [2,21]…[2,30]…[A, B]…[10,30]. These 100 3D model instances of the connecting rod are then aligned to determine the overlapping portion. The remaining area excluding the overlapping portion can be directly determined as the minimum volume portion to be parameterized. Preferably, to facilitate subsequent meshing operations, a regular shape portion inscribed in the overlapping portion can be determined, and then the remaining area excluding the regular shape portion can be determined as the minimum volume portion to be parameterized.

[0074] In one embodiment, segmenting the portion to be parameterized from the 3D model in step 103 includes segmenting the portion to be parameterized in a 3D model creation tool. Parameterizing the portion to be parameterized in step 104 includes parameterizing the portion to be parameterized based on the 3D model creation tool. Since segmenting the portion to be parameterized in the 3D model creation tool allows for convenient parameterization of the portion to be parameterized based on the 3D model creation tool.

[0075] In one embodiment, segmenting the portion to be parameterized from the 3D model in step 103 includes: converting the 3D model into a universal file format; segmenting the 3D model in the universal file format (e.g., .stp or .igs) using a segmentation tool different from the tool used to create the 3D model; and parameterizing the portion to be parameterized in step 104 includes the following methods:

[0076] Method (1): Create a target topology structure of the part to be parameterized, wherein the target topology structure is parameterized, match the part to be parameterized with the target topology structure; and parameterize the part to be parameterized based on the matching result.

[0077] Here, a target topology structure can be created based on manual input (for example, a parameterized circle is drawn manually), and then the target topology structure is matched with the part to be parameterized. When the similarity between the two is found to be greater than a threshold value, the part to be parameterized is determined to be a circle, and the diameter is determined as the parameter of the part to be parameterized.

[0078] Method (2): Identify the size characteristics of the part to be parameterized; and parameterize the part to be parameterized based on the size characteristics.

[0079] Here, the size features of the part to be parameterized can be determined based on artificial intelligence or other methods (for example, length features, width features, and height features can be identified), and then the part to be parameterized can be parameterized based on the size features, that is, the length, width, and height can be determined as the parameters of the part to be parameterized.

[0080] FIG4 is an exemplary flow chart of a method for generating a parametric model of a product according to an embodiment of the present invention.

[0081] As shown in FIG4 , the method includes:

[0082] Step 401: Obtain a three-dimensional model for simulation verification of a product.

[0083] Step 402: Determine the optimized parameters of the product.

[0084] Step 403: Determine whether rules for optimizing parameters have been set. If yes (corresponding to the "Y" branch), execute step 404 and its subsequent steps. If not (corresponding to the "N" branch), execute step 407 and its subsequent steps.

[0085] Step 404: Analyze the properties of the optimization parameters to obtain a specific method for determining the minimum volume of the part to be parameterized. Here, the method for determining the minimum volume of the part to be parameterized can be determined based on the dimensional parameters of a single local feature of the product or the dimensional parameters between multiple local features.

[0086] Step 405: Based on the specific method for determining the minimum volume of the part to be parameterized, determine the minimum volume of the part to be parameterized from the three-dimensional model.

[0087] Step 406 : Determine the remaining parts of the three-dimensional model except the part to be parameterized, and jump to step 410 .

[0088] Step 408: Create multiple instances of the three-dimensional model of the product based on the value range of the optimization parameter.

[0089] Step 409: Determine the overlapping parts of the multiple instances, and determine the remaining area except the overlapping parts as the minimum volume part to be parameterized.

[0090] Step 410: Segment the part to be parameterized from the three-dimensional model.

[0091] Step 411: Parameterize the part to be parameterized.

[0092] FIG5 is an exemplary structural diagram of a device for generating a parametric model of a product according to an embodiment of the present invention. As shown in FIG5 , the device 500 for generating a parametric model of a product includes:

[0093] The first determination module 501 is used to determine the optimization parameters of the product and to simulate and verify the three-dimensional model of the product;

[0094] A second determining module 502 is configured to determine a minimum volume of a to-be-parameterized portion in the three-dimensional model, wherein the to-be-parameterized portion needs to be repeatedly meshed during the process of optimizing the product based on the optimization parameters;

[0095] A segmentation module 503 is used to segment the part to be parameterized from the three-dimensional model;

[0096] The parameterization module 504 is used to parameterize the part to be parameterized.

[0097] In one embodiment, the optimization parameters include the size parameters of a single local feature of the product; the second determination module 502 is used to determine the value range of the size parameters; the minimum volume part in the three-dimensional model that contains a single local feature within the value range and satisfies the first constraint condition is determined as the part to be parameterized; wherein the first constraint condition includes at least one of the following: a constraint condition on the shape of the minimum volume part; a constraint condition on the size of the minimum volume part.

[0098] In one embodiment, the optimization parameters include dimensional parameters between multiple local features of the product; the second determination module 502 is used to determine associated local features associated with multiple local features; determine the value range of the dimensional parameters; determine the minimum volume part of the associated local features in the three-dimensional model that meets the second constraint as the part to be parameterized, wherein the value range of the associated local features is associated with the value range of the dimensional parameters; wherein the second constraint includes at least one of the following: a constraint on the shape of the minimum volume part; a constraint on the size of the minimum volume part.

[0099] In one embodiment, the second determining module 502 is configured to create multiple instances of the three-dimensional model based on the value range of the optimization parameter; determine overlapping portions of the multiple instances; and determine a minimum volume of a portion to be parameterized based on the overlapping portions.

[0100] In one embodiment, based on the overlapping part, determining the minimum volume of the part to be parameterized includes: determining the remaining area except the overlapping part as the minimum volume of the part to be parameterized; or, determining a regular shape part inscribed in the overlapping part; and determining the remaining area except the regular shape part as the minimum volume of the part to be parameterized.

[0101] In one embodiment, the segmentation module 503 is used to segment the part to be parameterized in the three-dimensional model creation tool; the parameterization module 504 is used to parameterize the part to be parameterized based on the three-dimensional model creation tool.

[0102] In one embodiment, a segmentation module 503 is used to convert a three-dimensional model into a universal file format; segment the three-dimensional model in the universal file format in a segmentation tool that is different from the tool used to create the three-dimensional model; a parameterization module 504 is used to create a target topology structure of the part to be parameterized, wherein the target topology structure is parameterized; match the part to be parameterized with the target topology structure; parameterize the part to be parameterized based on the matching result; or, identify the size characteristics of the part to be parameterized; and parameterize the part to be parameterized based on the size characteristics.

[0103] The embodiment of the present invention also proposes an electronic device with a processor-memory architecture. Figure 6 is an exemplary structural diagram of an electronic device according to an embodiment of the present invention. As shown in Figure 7, the electronic device 600 includes a processor 601, a memory 602, and a computer program stored on the memory 602 and run on the processor 601. When the computer program is executed by the processor 601, a method for generating a parameterized model of any of the above products is implemented. Among them, the memory 602 can be specifically implemented as a variety of storage media such as an electrically erasable programmable read-only memory (EEPROM), a flash memory (Flash memory), and a programmable program read-only memory (PROM). The processor 601 can be implemented to include one or more central processing units or one or more field programmable gate arrays, wherein the field programmable gate array integrates one or more central processing unit cores. Specifically, the central processing unit or the central processing unit core can be implemented as a CPU, an MCU or a DSP, and so on.

[0104] It should be noted that not all steps and modules in the above processes and structure diagrams are required, and certain steps or modules can be omitted based on actual needs. The execution order of the steps is not fixed and can be adjusted as needed. The division of the modules is merely for the convenience of describing the functional division adopted. In actual implementation, a module can be implemented by multiple modules, and the functions of multiple modules can be implemented by the same module. These modules can be located in the same device or in different devices.

[0105] The hardware modules in each embodiment can be implemented mechanically or electronically. For example, a hardware module may include a specially designed permanent circuit or logic device (such as a dedicated processor, such as an FPGA or ASIC) for performing a specific operation. The hardware module may also include a programmable logic device or circuit (such as a general-purpose processor or other programmable processor) temporarily configured by software to perform a specific operation. As for whether to implement the hardware module mechanically, or using a dedicated permanent circuit, or using a temporarily configured circuit (such as configured by software), it can be decided based on cost and time considerations.

[0106] The above are only preferred embodiments of the present invention and are not intended to limit the scope of protection of the present invention. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A method for generating a parametric model of a product, characterized in that: The method comprises: Determining (101) optimization parameters of a product and a three-dimensional model for simulating and verifying the product; Determining (102) a minimum volume of a to-be-parameterized portion in the three-dimensional model, wherein the to-be-parameterized portion needs to be repeatedly meshed during the process of optimizing the product based on the optimization parameters; Segmenting (103) the portion to be parameterized from the three-dimensional model; The part to be parameterized is parameterized (104).

2. The method according to claim 1, characterized in that The optimization parameters include size parameters of a single local feature of the product; The determining (102) of the minimum volume of the part to be parameterized in the three-dimensional model comprises: Determining a value range of the size parameter; Determine, in the three-dimensional model, a minimum volume portion that contains the single local feature within the value range and satisfies the first constraint condition as the portion to be parameterized; The first constraint condition includes at least one of the following: Constraints on the shape of the minimum volume portion; constraints on the size of the minimum volume portion.

3. The method according to claim 1, characterized in that: The optimization parameters include size parameters between a plurality of local features of the product; The determining (102) of the minimum volume of the part to be parameterized in the three-dimensional model comprises: determining associated local features associated with the plurality of local features; Determining a value range of the size parameter; Determining, in the three-dimensional model, a minimum volume portion of the associated local feature that satisfies the second constraint condition as the portion to be parameterized, wherein a value range of the associated local feature is associated with a value range of the size parameter; The second constraint condition includes at least one of the following: Constraints on the shape of the minimum volume portion; constraints on the size of the minimum volume portion.

4. The method according to claim 1, characterized in that: The determining (102) of the minimum volume of the part to be parameterized in the three-dimensional model comprises: Creating multiple instances of the three-dimensional model based on the value range of the optimization parameter; determining an overlap of the plurality of instances; Based on the overlapping portion, a portion of the minimum volume to be parameterized is determined.

5. The method according to claim 4, characterized in that The determining, based on the overlapping portion, the portion to be parameterized of the minimum volume comprises: Determine the remaining part except the overlapping part as the part to be parameterized of the minimum volume; or A regular shape portion inscribed in the overlapping portion is determined; and a remaining portion except the regular shape portion is determined as a portion of the minimum volume to be parameterized.

6. The method according to claim 4, characterized in that The segmenting (103) of the part to be parameterized from the three-dimensional model comprises: segmenting the part to be parameterized in a creation tool of the three-dimensional model; The parameterizing (104) the part to be parameterized includes: parameterizing the part to be parameterized based on a creation tool of the three-dimensional model.

7. The method according to claim 4, characterized in that The segmenting (103) of the part to be parameterized from the three-dimensional model comprises: converting the three-dimensional model into a universal file format; segmenting the three-dimensional model in the universal file format in a segmentation tool different from a creation tool of the three-dimensional model; The parameterization (104) of the part to be parameterized includes: Creating a target topology structure of the part to be parameterized, wherein the target topology structure is parameterized; matching the part to be parameterized with the target topology structure; and parameterizing the part to be parameterized based on the matching result; or Identify the size feature of the part to be parameterized; and parameterize the part to be parameterized based on the size feature.

8. A device for generating a parametric model of a product, characterized in that: include: A first determination module (501), used to determine the optimization parameters of a product and to simulate and verify a three-dimensional model of the product; A second determination module (502) is used to determine a minimum volume of a to-be-parameterized portion in the three-dimensional model, wherein the to-be-parameterized portion needs to be repeatedly meshed during the process of optimizing the product based on the optimization parameters; A segmentation module (503), used for segmenting the part to be parameterized from the three-dimensional model; The parameterization module (504) is used to parameterize the part to be parameterized.

9. An electronic device, characterized in that: include: Processor (601); A memory (602), configured to store executable instructions of the processor (601); The processor (601) is used to read the executable instructions from the memory (602), and execute the executable instructions to implement the method for generating a parameterized model of a product according to any one of claims 1 to 7.

10. A computer-readable storage medium having computer instructions stored thereon, characterized in that: When the computer instructions are executed by a processor, the method for generating a parametric model of a product according to any one of claims 1 to 7 is implemented.

11. A computer program product, characterized in that The invention comprises a computer program, which, when executed by a processor, implements the method for generating a parameterized model of a product according to any one of claims 1 to 7.

Images