WO2023039800A1 - Procédé et appareil de production de texture de surface de modèle, et dispositif informatique et support de stockage - Google Patents

Procédé et appareil de production de texture de surface de modèle, et dispositif informatique et support de stockage Download PDF

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Publication number
WO2023039800A1
WO2023039800A1 PCT/CN2021/118824 CN2021118824W WO2023039800A1 WO 2023039800 A1 WO2023039800 A1 WO 2023039800A1 CN 2021118824 W CN2021118824 W CN 2021118824W WO 2023039800 A1 WO2023039800 A1 WO 2023039800A1
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Prior art keywords
partition
texture
corner
model
wall
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PCT/CN2021/118824
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English (en)
Chinese (zh)
Inventor
贾琇
亓欣波
李长鹏
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西门子股份公司
西门子（中国）有限公司
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Application filed by 西门子股份公司, 西门子（中国）有限公司 filed Critical 西门子股份公司
Priority to CN202180100930.2A priority Critical patent/CN117836811A/zh
Priority to PCT/CN2021/118824 priority patent/WO2023039800A1/fr
Publication of WO2023039800A1 publication Critical patent/WO2023039800A1/fr

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    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B33—ADDITIVE MANUFACTURING TECHNOLOGY
    • B33Y—ADDITIVE MANUFACTURING, i.e. MANUFACTURING OF THREE-DIMENSIONAL [3-D] OBJECTS BY ADDITIVE DEPOSITION, ADDITIVE AGGLOMERATION OR ADDITIVE LAYERING, e.g. BY 3-D PRINTING, STEREOLITHOGRAPHY OR SELECTIVE LASER SINTERING
    • B33Y50/00—Data acquisition or data processing for additive manufacturing
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T15/00—3D [Three Dimensional] image rendering
    • G06T15/04—Texture mapping

Definitions

  • the present application relates to the field of manufacturing technology, and in particular to a method, device, computing device and storage medium for generating model surface textures.
  • AM additive Manufacturing
  • 3D printing is a manufacturing technique that creates three-dimensional objects by depositing materials layer by layer.
  • AM overcomes the technical limitations of traditional manufacturing methods in producing complex structures and provides greater freedom in structural design.
  • Parts manufactured by AM technology have rough surface textures.
  • Flat outer surfaces on parts can be polished to a target finish during post-processing.
  • polishing is not always feasible for the interior or complex exterior surfaces of AM-manufactured parts, and rough surface textures cannot always be eliminated.
  • Rough surface structure affects the mechanical behavior of parts such as wear, sealing and hydrodynamics, and is critical to the long-term performance of parts such as crack initiation and fatigue life.
  • design verification is usually carried out on an ideal computer-aided design (Computer Aided Design, abbreviated as CAD) model.
  • CAD Computer Aided Design
  • the embodiment of the present application provides a solution for generating a surface texture of a model, which can enable a model with a surface texture to more accurately represent a molded part to be manufactured, so that the model can be used for design verification more accurately.
  • a method for generating a surface texture of a model is provided, which is applied to a computing device, and the method includes:
  • the wall angle of each partition is the angle between the normal vector of the partition and the construction direction of the target additive manufacturing method, and the wall angle
  • the corresponding texture data is used to characterize: the texture feature of the surface with the wall corner manufactured by the target additive manufacturing method
  • the surface texture of each partition is generated to obtain a model with surface texture.
  • the method for generating the surface texture of the model described above generates the surface texture of each partition according to the wall angle of each partition, so that the model with the surface texture can more accurately represent the molded part to be manufactured, so that the model can be used for design verification more accurately.
  • an apparatus for generating a surface texture of a model which is applied to a computing device, and the apparatus includes:
  • the original model acquisition unit acquires the original model of the surface texture to be generated
  • the partition unit partitions the surface of the original model to obtain a partition result, wherein the angle between the normal vectors of any two adjacent partitions in the partition result is greater than the angle threshold, and any two in each partition The angle between the normal vectors at the position does not exceed the angle threshold;
  • a texture data acquisition unit which acquires texture data corresponding to the wall corner of each partition in the partition result, where the wall angle of each partition is the angle between the normal vector of the partition and the construction direction of the target additive manufacturing method , the texture data corresponding to the wall corner is used to characterize: the texture feature of the surface with the wall corner manufactured by the target additive manufacturing method;
  • the texture generation unit generates the surface texture of each partition according to the texture data of the wall corners of each partition to obtain a model with surface texture.
  • the above-mentioned device for generating the surface texture of the model can generate the surface texture of each partition according to the wall angle of each partition, so that the model with the surface texture can more accurately represent the molded part to be manufactured, so that the model can be used for design verification more accurately.
  • a computing device including: a processor and a memory; computer-readable instructions are stored in the memory, enabling the processor to: execute a method for generating a surface texture of a model.
  • a non-volatile storage medium storing one or more programs, the one or more programs including instructions, and the instructions, when executed by a computing device, cause the computing device to execute Instructions for the method of generating model surface textures according to the present application.
  • Figure 1 shows a schematic diagram of an ideal model and a molded part according to an embodiment of the application
  • FIG. 2 shows a flowchart of a method 200 for generating model surface textures according to an embodiment of the present application
  • FIG. 3 shows a flow chart of a method 300 for acquiring texture data of a wall corner according to an embodiment of the present application
  • Fig. 4A shows the construction direction of the target additive manufacturing method of the embodiment of the present application
  • Fig. 4B shows a schematic diagram of normal vectors of multiple surfaces in the embodiment of the present application.
  • FIG. 5 shows a flow chart of a method 500 for acquiring texture data of a wall corner according to an embodiment of the present application
  • FIG. 6 shows a flowchart of a method 600 for training a texture generation model according to an embodiment of the present application
  • Fig. 7A and Fig. 7B respectively show the schematic diagram of the test piece according to the embodiment of the present application.
  • FIG. 8 shows a flowchart of a method 800 for acquiring texture data of a test piece according to an embodiment of the present application
  • Fig. 9A shows a schematic diagram of separating original texture data into waviness texture and roughness texture according to the embodiment of the present application
  • FIG. 9B shows a schematic diagram of filtering processing on original texture data according to an embodiment of the present application.
  • FIG. 9C shows a schematic diagram of converting filtered texture data into a grayscale height map according to an embodiment of the present application.
  • Fig. 10 shows a schematic diagram of the conditional generation confrontation network of the embodiment of the present application.
  • FIG. 11 shows a flowchart of a method 1100 for partitioning the surface of an original model according to an embodiment of the present application
  • FIG. 12A shows a flowchart of a method 1200 for partitioning triangular faces in a mesh model according to an embodiment of the present application
  • FIG. 12B shows a schematic diagram of a triangular face in an embodiment of the present application.
  • Fig. 12C shows a schematic diagram of the partition result of the embodiment of the present application.
  • FIG. 13 shows a flowchart of a method 1300 for obtaining a model with surface texture according to an embodiment of the present application
  • FIG. 14 shows a flowchart of a method 1400 for obtaining a model with surface texture according to an embodiment of the present application
  • Fig. 15 shows a schematic diagram of generating a model with surface texture according to an embodiment of the present application
  • FIG. 16 shows a flowchart of a method 1600 for generating a model surface texture according to an embodiment of the present application
  • FIG. 17 shows a schematic diagram of an apparatus 1700 for generating model surface texture according to an embodiment of the present application
  • FIG. 18 shows a schematic diagram of a computing device according to an embodiment of the present application.
  • the targeted additive manufacturing method can manufacture solid parts with rough surface structure, which can also be called molded parts.
  • Figure 1 shows a schematic diagram of an idealized model and a molded part.
  • the surface of the ideal model 101 and the surface of the molded part 102 in Fig. 1 that is, the surface of the molded part has a rough surface structure
  • the ideal model 101 has an ideal smooth surface without a rough surface structure.
  • the rough surface structure will affect the mechanical behavior of the molded parts such as wear, sealing and hydrodynamics, and has a great influence on the long-term performance of the molded parts such as crack initiation and fatigue life.
  • the performance of the ideal model cannot truly represent the performance of the molded part structure to be manufactured.
  • simulating the surface texture on the idealized model 101 and using the model with the surface texture for design verification helps to more accurately understand the performance of the molded part to be manufactured.
  • the roughness of the surface of the formed part can be quantified by wire measurement or surface measurement.
  • the roughness of the surface of the molded part is, for example, average roughness, root mean square roughness, maximum height range, skewness, and kurtosis. value.
  • some embodiments may generate a deterministic surface or a random surface on the surface of the ideal model according to the roughness.
  • the deterministic curved surface has a predetermined shape, such as a triangle, a rectangle, or a sinusoid.
  • Stochastic surfaces are generated by one or more stochastic processes based on indicators of roughness.
  • the embodiment of the present application also proposes other schemes for generating the surface texture of the model, so that the surface texture of the model can more accurately represent the molded part to be manufactured, so that the model can be used for design verification more accurately.
  • FIG. 2 shows a flowchart of a method 200 for generating model surface textures according to an embodiment of the present application.
  • Method 200 may be applied, for example, in a computing device.
  • the computing device may be, for example, a personal computer, a server, and the like.
  • step S201 the original model of the surface texture to be generated is acquired.
  • the original model can be, for example, a three-dimensional model generated by various CAD applications.
  • step S202 the surface of the original model is partitioned to obtain a partition result.
  • the angle between the normal vectors of any two adjacent partitions in the partition result is greater than the angle threshold, and the angle between the normal vectors at any two positions in each partition does not exceed the angle threshold.
  • the included angle threshold can be set, for example, 5 degrees or 10 degrees.
  • step S203 the texture data corresponding to the wall corner of each partition in the partition result is acquired.
  • the wall angle of each partition is the angle between the normal vector of the partition and the construction direction of the target additive manufacturing method.
  • the texture data corresponding to each wall corner is used to characterize: the texture feature of the surface with the wall corner manufactured by the target additive manufacturing method.
  • step S204 according to the texture data of the wall corners of each partition, the surface texture of each partition is generated to obtain a model with surface texture.
  • the model with surface texture can also be called a virtual molded part model (Virtual As-Built Model).
  • the texture features of each surface (region) in the molded part are strongly related to the wall angle of each surface.
  • the texture features of the two surfaces are also close.
  • the texture characteristics of the two surfaces may be very different.
  • the method 200 of the embodiment of the present application partitions the surface of the original model through step S202, so that the normal directions of different positions in the same partition are close to each other, while the normal directions of different partitions are quite different.
  • step S202 can make the wall angles at different positions in the same partition close, while the wall angles of different partitions are quite different.
  • the method 200 can divide the surface areas with the same or close texture features into the same partition, while the surface areas with relatively different texture features can be divided into different partitions.
  • the method 200 obtains the texture data corresponding to the wall corners of each partition through step S203, and generates the surface texture of each partition according to the texture data corresponding to the wall corners in step S204. Since the texture characteristics of the surface are strongly related to the wall angle, the method 200 can make the model with the surface texture more accurately represent the molded part to be manufactured by generating the surface texture of each partition according to the wall angle of each partition, so as to more accurately Use models for design validation.
  • step S203 can be implemented as the method 300 in order to obtain the texture data of the wall corner.
  • step S301 the corner type to which the corner of each partition belongs is determined, wherein different corner types are used to identify different corner ranges.
  • FIG. 4A shows a build direction d0 of a target additive manufacturing approach.
  • Figure 4B shows a schematic view of the corners of the various surfaces in the molding.
  • the angle ⁇ 1 between the normal vector d1 of the upward plane 401 and the construction direction d0 is 0°, that is, the wall angle is 0°.
  • the included angle ⁇ 2 between the normal vector d2 of the downward plane 402 and the construction direction d0 is 180°, that is, the wall angle is 180°.
  • the included angle ⁇ 3 between the normal vector d3 of the obliquely downward plane 403 and the construction direction d0 is 135°, that is, the wall angle is 135°.
  • the angle ⁇ 4 between the normal vector d4 of the vertical plane 404 and the construction direction d0 is 90°, that is, the wall angle is 90°.
  • the included angle ⁇ 5 between the normal vector d5 of the obliquely upward plane 405 and the construction direction d0 is 45°, that is, the wall angle is 45°.
  • type 2 wall angle range satisfies: 0° ⁇ 90°
  • type 4 the wall angle range satisfies: 90° ⁇ 180°
  • the wall angle value range [0°, 180°] can be divided into n intervals, that is, the wall angle types can include n types.
  • n is a positive integer.
  • the wall angle type is, for example, type 1 (the wall angle range satisfies: 0° ⁇ 5°), type 2 (the wall angle range satisfies: 5° ⁇ 30°), type 3 (the wall angle range satisfies: 30° ⁇ ⁇ 60°) and so on.
  • step S302 for each partition, input the corner type to which the partition's corner belongs to the texture generation model to obtain texture data corresponding to the corner type, and use the texture data as the texture data of the partition's corner.
  • the texture data corresponding to the corner type is used to characterize: the common texture features of the surfaces of different corners within the range of the corner identified by the corner type. Surfaces with different corners are manufactured by targeted additive manufacturing.
  • the method 300 can generate texture data corresponding to the corner type through the texture generation model after determining the corner type to which the corner belongs. Since the texture data corresponding to the corner type can represent the common features of the surfaces of the corners within the range corresponding to the corner type, method 300 can use the texture data corresponding to the corner type as any corner within the range corresponding to the corner type. Texture data for the corners. In short, the method 300 can infer the texture data of any corner by analyzing the corner type of the corner. It is particularly emphasized that since the difference of the wall corners within the range of the wall angle corresponding to the wall angle type is relatively small, the texture characteristics of the surfaces of the wall corners within the range of the wall angle corresponding to the wall angle type are relatively close. The method 300 can accurately represent the surface texture features of any corner belonging to the corner type by using the corner data corresponding to the corner type.
  • step S203 can be implemented as the method 500 in order to obtain the texture data of the wall corner.
  • step S501 the type of the corner to which the corner of each partition belongs is determined.
  • the different wall corner types are used to identify different wall corner ranges.
  • step S502 for each partition, the texture data corresponding to the corner type to which the corner of the partition belongs is obtained as the texture data of the corner of the partition.
  • the texture data corresponding to the corner type is generated by the texture generation model.
  • the texture data corresponding to each corner type may be generated by the texture generation model before performing the method 500 .
  • the texture data corresponding to the corner type is used to characterize: the common texture characteristics of the surfaces of different corners within the range of the corner identified by the corner type. Surfaces with different corners are manufactured by targeted additive manufacturing.
  • the texture data corresponding to the wall corner type may be obtained by querying.
  • the method 500 can obtain the texture data corresponding to the corner type after determining the corner type of the wall corner, and use it as the texture data of the wall corner.
  • the texture data corresponding to the wall corner type can be generated before the method 500 is executed, the method 500 can determine the texture data of the wall corner more quickly.
  • the above texture generation model can be obtained through training.
  • the training method of the texture generation model can be implemented as method 600 .
  • step S601 texture data of multiple corners of the test piece are acquired.
  • the test piece is a sample structure manufactured by the target additive manufacturing method for collecting texture data, and the sample structure may include surfaces with multiple corners.
  • the sample structure can be a single molded part or a plurality of molded parts.
  • FIG. 7A and FIG. 7B respectively show a schematic view of a test strip according to an embodiment of the present application. Both the coupon in Figure 7A and the coupon in Figure 7B have surfaces with multiple corners.
  • the texture data of each corner is used to characterize the texture feature of the surface of the corner in the test piece manufactured by the target additive manufacturing method.
  • the texture data may be, for example, a texture image or texture features extracted based on the texture image.
  • Each corner of the test piece is the angle between the normal vector of the surface of the corner and the construction direction of the target additive manufacturing method.
  • step S602 the corner type of each corner of the test piece is determined.
  • step S603 the texture generation model is trained according to the texture data of multiple wall corners and the corner type of each wall corner to obtain a trained texture generation model.
  • the texture generation model may be various machine learning models capable of generating texture data according to wall corner types.
  • the corner type can be used as an input of the trained texture generation model, and the trained texture generation model can output texture data corresponding to the corner type.
  • the method 600 can use the test piece manufactured by the target additive manufacturing method to obtain the texture data of multiple corners, so as to use the texture data of multiple corners and the corner type of each corner to train the texture generation model .
  • the trained texture generation model can accurately output the texture features of surfaces with various corner types.
  • step S601 in order to obtain the texture data of the test piece, step S601 can be implemented as the method 800.
  • step S801 the original texture data of surfaces of multiple wall corners in the test piece are acquired by means of three-dimensional measurement.
  • step S801 may use a non-contact three-dimensional area measurement system to acquire original texture data.
  • Non-contact three-dimensional area measurement systems are, for example, confocal microscopes, coherent scanning interference devices, zoom microscopes, and the like.
  • the prepared test pieces will first undergo preliminary treatment, such as surface cleaning and bracket removal. Then, surface measurement is carried out at multiple surface positions on the test piece to obtain the original texture data of the surface at multiple wall corners.
  • step S801 may scan a millimeter-level (eg 2.5mm*2.5mm) square area at each surface position.
  • step S802 the original texture data of the surface of each wall corner is filtered, and the filtered texture data of the surface of each wall corner is used as the texture data of each wall corner.
  • the original texture data obtained directly from the measurement is complex, including the inherent waviness texture and roughness texture of the surface.
  • the roughness texture includes the detail texture in the original texture data and the noise related to the measurement equipment.
  • the waviness texture and the roughness texture can be divided by wavelength, for example.
  • the texture data larger than the wavelength A can be regarded as the waviness texture, and the texture data not exceeding the wavelength A can be regarded as the roughness texture.
  • the wavelength A can be set as required, for example, it is 2.5mm.
  • FIG. 9A shows a schematic diagram of separating original texture data into a waviness texture and a roughness texture.
  • the original texture data 901 in FIG. 9A can be represented separately as a waviness texture 902 and a roughness texture 903 .
  • step S802 for example, Gaussian filtering or fast Fourier transform may be used to filter out at least a part of the roughness texture 903 . That is, part or all of the roughness texture 903 may be removed by filtering in step S802. In this way, the filtering process in step S802 helps to remove noise in the original texture data. In addition, through filtering, step S802 may also filter out at least a part of detail features in the original texture data, so as to improve data processing efficiency.
  • Gaussian filtering or fast Fourier transform may be used to filter out at least a part of the roughness texture 903 . That is, part or all of the roughness texture 903 may be removed by filtering in step S802. In this way, the filtering process in step S802 helps to remove noise in the original texture data. In addition, through filtering, step S802 may also filter out at least a part of detail features in the original texture data, so as to improve data processing efficiency.
  • step S802 uses Gaussian filtering to filter out the data whose wavelength is smaller than the wavelength threshold in the original texture data to obtain the filtered texture of the surface of the wall corner data and use it as the texture data for this corner.
  • the wavelength threshold can be set according to the detail requirement. For example, in scenes with high detail requirements, the wavelength threshold is smaller. Conversely, in scenes with low detail requirements, the wavelength threshold is larger. The smaller the wavelength threshold, the more detail textures are preserved in the filtered texture data. The larger the wavelength threshold, the less detailed texture in the filtered texture data.
  • the weight function of the Gaussian filter is:
  • ⁇ c is a wavelength threshold, which may also be called a cut-off parameter.
  • the roughness texture 905 can be filtered out to obtain the filtered texture data 907 .
  • the roughness texture 906 can be filtered out to obtain the filtered texture data 907 .
  • the filtered texture data for example, 907
  • the more feature quantity ie, detailed texture
  • the smoother the filtered texture data eg, 908
  • the roughness textures 905 and 906 contain the inherent detailed features of the test piece surface and device-related random details.
  • the embodiment of the present application may make the filtered texture data include the texture texture and a part of the roughness texture, or only include the texture texture.
  • the filtered texture data may be converted to a grayscale height map.
  • the intensity of each pixel ranges from 0 (black) to 255 (white) and is linearly related to the local surface height. For example, if white represents the maximum height, black represents the minimum height.
  • FIG. 9C shows a schematic diagram of converting filtered texture data into a grayscale height map.
  • 909 in FIG. 9C is a three-dimensional schematic diagram of the filtered texture data.
  • 910 is a two-dimensional grayscale height map of the filtered texture data 909 .
  • step S802 can filter out the data whose wavelength is smaller than the wavelength threshold in the original texture data by means of fast Fourier transform to obtain the surface texture data of the wall corner. Filtered texture data and use it as the texture data for this corner.
  • the texture generation model is a conditional generation confrontation network (Conditional GAN), and the conditional generation confrontation network includes: a generator and a discriminator.
  • the generator is used to generate image samples
  • the discriminator is used to identify whether the image samples are the texture data of the surface manufactured by the target additive manufacturing method.
  • the texture generation model may also be other models such as generative adversarial networks, which is not limited in this application.
  • step S603 may convert the texture data of multiple wall corners into a grayscale height map.
  • step S603 takes the grayscale height maps of multiple wall corners and the corner type of each wall corner as the input of the generator, and uses the image samples generated by the generator and the grayscale height maps of multiple wall corners as The input of the discriminator is used to train the generator and the discriminator to obtain a trained texture generation model.
  • Figure 10 shows a schematic diagram of a conditional generative adversarial network.
  • the input of the generator 1001 in FIG. 10 includes a first input 1002 and a second input 1003 .
  • the first input 1002 is, for example, a grayscale height map.
  • the second input 1003 is eg a corner type.
  • the corner type can be represented by an encoding generated by one-hot encoding.
  • step S603 may sample the grayscale height map in the form of a Gaussian distribution to obtain a latent vector (equivalent to performing feature transformation on the grayscale height map), and use the latent vector as the first input 1002 .
  • the purpose of sampling in the form of Gaussian distribution is to convert the image features in the original space of the gray height map into the features of the latent space, which are expressed by new latent vectors.
  • the latent vector can be used for automatic feature extraction, and at the same time, it has the effect of compressing the feature quantity to reduce the complexity of the model.
  • FIG. 10 shows examples of corner types a1, a2, and a3.
  • the image sample 1004 generated by the generator in FIG. 10 and the gray height map 1005 of the wall corner are used as the input of the discriminator 1006 .
  • a robust generator 1001 can be generated.
  • step S603 before using the gray-scale height maps of multiple wall corners and the corner type of each wall corner as the input of the generator, step S603 can also perform linear regression on the gray-scale height maps of each wall corner One treatment. In this way, the grayscale height maps of various wall corner types can have a common zero level height, which is standardized to have the same height value range. In other words, step S603 can normalize each group of training grayscale height maps, and the same grayscale value in different grayscale heightmaps corresponds to the same height value.
  • step S202 in order to partition the surface of the original model, can be implemented as method 1100 .
  • step S1101 model segmentation is performed on the surface of the original model to obtain a mesh model composed of triangular faces.
  • step S1102 the triangular faces in the mesh model are partitioned to obtain partition results.
  • the angle between the normal vectors of any two adjacent partitions is greater than the angle threshold, and the angle between the normal vectors of any two adjacent triangular faces in each partition does not exceed the angle threshold.
  • the method 1100 can divide the triangular faces with the same or close texture features into the same partition, and the triangular faces with relatively different texture features into different partitions.
  • step S1102 can be implemented as the method 1200 in order to partition the triangular faces in the mesh model.
  • step S1201 for each pair of adjacent triangular faces in the mesh model, when the angle between the normal vectors of the group of adjacent triangular faces does not exceed the angle threshold value, the group The adjacent triangular faces are divided into the same partition, resulting in multiple partitions in the mesh model.
  • FIG. 12B shows a schematic diagram of a part of a triangular surface.
  • the angle between the normal vectors of the triangular faces 1210 and 1211 exceeds the angle threshold and is divided into different partitions, while the angle between the normal vectors of the triangular faces 1211 and 1212 does not exceed the angle threshold and is divided into the same partition. partition.
  • step 1202 for a plurality of partitions, iteratively execute the partition merging operation until the angle between the normal vectors of any two adjacent partitions is greater than the angle threshold, so as to obtain the partition result.
  • the partition merging operation performed each time includes: for each pair of adjacent two partitions in the grid model, merging the two partitions when the angle between the normal vectors of the two partitions does not exceed the angle threshold.
  • FIG. 12C shows a schematic diagram of partitioning results.
  • Figure 12C shows the numbers of some partitions, such as 1213, 1214 and 1215.
  • method 1200 can continue to iteratively merge partitions after triangular faces are initially partitioned, so that triangular faces with the same or close to texture features can be divided into the same partition, and triangular faces with relatively different texture features can be divided into different partitions. partition.
  • the texture data corresponding to the corners of each partition is a grayscale height map.
  • the surface of the original model is divided into a mesh model composed of triangular faces.
  • step S204 can be implemented as method 1300 .
  • step S1301 the vertices of the triangular faces in each partition are associated with the pixels in the gray height map of the wall corners of the partition.
  • step S1301 may map the vertices of the triangle surface to the pixel points.
  • step S1302 for each vertex in each partition, adjust the position of the vertex along the normal direction of the vertex according to the height value corresponding to the gray value of the pixel associated with the vertex to obtain a surface texture Model.
  • the manner of adjusting the position of the vertex along the normal direction at the vertex may be referred to as displacement mapping.
  • the method 1300 can simulate the surface texture of the molded part to be manufactured by adjusting the position of the apex of the triangular surface, so as to accurately use the model for design verification.
  • step S204 in order to obtain a model with surface texture, can be implemented as method 1400 .
  • step S1401 the triangular faces in the mesh model are divided into smaller triangular faces.
  • step S1402 the vertices of the triangular faces in each partition are associated with the pixel points in the gray height map of the wall corners of the partition.
  • step S1403 for each vertex in each partition, the position of the vertex is adjusted along the normal direction at the vertex according to the height value corresponding to the gray value of the pixel associated with the vertex.
  • the model with surface texture can be obtained according to the execution result of S1403.
  • the method 1400 may execute step S1404.
  • step S1404 after adjusting the positions of vertices in the model, the gaps existing between the triangular faces in the mesh model are closed to obtain a model with surface texture.
  • the operation of closing the gaps between the triangular faces in the mesh model is, for example, merging the same vertices, and updating the connecting edges between the vertices in the deformed mesh (that is, regenerating the triangular faces).
  • FIG. 15 shows a schematic diagram of generating a model with surface texture.
  • Step S1401 may divide the triangular faces in the mesh model 1501 into smaller triangular faces to obtain the mesh model 1502 .
  • Step S1402 associates the vertices of the triangular faces in each partition in the mesh model 1501 with the pixels in the gray height map (for example, 1503 ) of the wall corners of the partition.
  • step S1403 adjusts the position of the vertex along the normal direction of the vertex according to the height value corresponding to the gray value of the pixel associated with the vertex.
  • the embodiment of the present application can obtain a model 1504 with surface texture.
  • step S1404 after adjusting the positions of vertices in the model, the gaps existing between the triangular faces in the mesh model are closed to obtain a model 1504 with surface texture.
  • FIG. 16 shows a flowchart of a method 1600 for generating model surface textures according to an embodiment of the present application.
  • Method 200 may be applied, for example, in a computing device.
  • step S1601 the original model of the surface texture to be generated is acquired.
  • the original model can be, for example, a three-dimensional model generated by various CAD applications.
  • step S1602 the surface of the original model is partitioned to obtain a partition result.
  • the angle between the normal vectors of any two adjacent partitions in the partition result is greater than the angle threshold, and the angle between the normal vectors at any two positions in each partition does not exceed the angle threshold.
  • the included angle threshold can be set, for example, 5 degrees or 10 degrees.
  • step S1603 the boundary of the partition in the partition result is smoothed to obtain the partition result with boundary noise eliminated.
  • step 1603 can make the boundaries of the partitions smoother and help reduce the jaggedness of the boundaries of each partition, thereby reducing the gap between the boundaries of each partition and reducing the computational complexity when the surface texture of each partition is subsequently generated.
  • step 1603 can prevent boundary noise from affecting the texture generation of the model surface, thereby reducing computational complexity, and enabling the generated surface texture to more accurately represent the surface texture of the finished molded part to be manufactured.
  • step S1604 the texture data corresponding to the wall corner of each partition in the partition result is obtained.
  • the wall angle of each partition is the angle between the normal vector of the partition and the construction direction of the target additive manufacturing method.
  • the texture data corresponding to each wall corner is used to characterize: the texture feature of the surface with the wall corner manufactured by the target additive manufacturing method.
  • step S1605 according to the texture data of the wall corners of each partition, the surface texture of each partition is generated to obtain a model with surface texture.
  • step S1606 design verification is performed on the model with surface texture.
  • the design verification is, for example, analyzing the mechanical behavior of the molded part to be manufactured such as wear, sealing and hydrodynamics, and testing the long-term performance of the molded part such as crack initiation and fatigue life.
  • the method 1600 generates the surface texture of each partition according to the wall angle of each partition, so that the model with the surface texture can more accurately represent the molded part to be manufactured, so that the model can be used for design verification more accurately.
  • Fig. 17 shows a schematic diagram of an apparatus 1700 for generating model surface textures according to some embodiments of the present application.
  • the apparatus 1700 is, for example, applied in a computing device.
  • Apparatus 1700 may be a stand-alone application or a plug-in to CAD software.
  • an apparatus 1700 includes an original model acquisition unit 1701 , a partition unit 1702 and a texture data acquisition unit 1703 .
  • the original model obtaining unit 1701 obtains the original model of the surface texture to be generated.
  • the partition unit 1702 partitions the surface of the original model to obtain partition results. Wherein, the angle between the normal vectors of any two adjacent partitions in the partition result is larger than the angle threshold, and the angle between the normal vectors at any two positions in each partition does not exceed the angle threshold.
  • the texture data obtaining unit 1703 obtains the texture data corresponding to the corner of each partition in the partition result.
  • the wall angle of each partition is the angle between the normal vector of the partition and the construction direction of the target additive manufacturing method.
  • the texture data corresponding to the wall corner is used to characterize: the texture feature of the surface with the wall corner manufactured by the target additive manufacturing method.
  • the device 1700 generates the surface texture of each partition according to the wall angle of each partition, so that the model with the surface texture can more accurately represent the molded part to be manufactured, so that the model can be used for design verification more accurately.
  • Figure 18 shows a schematic diagram of a computing device according to some embodiments of the application.
  • the computing device includes one or more processors (CPUs) 1802, a communications module 1804, memory 1806, a user interface 1810, and a communications bus 1808 for interconnecting these components.
  • processors CPUs
  • communications module 1804
  • memory 1806
  • user interface 1810 the computing device includes one or more processors (CPUs) 1802
  • communications bus 1808 for interconnecting these components.
  • the processor 1802 can receive and send data through the communication module 1804 to realize network communication and/or local communication.
  • User interface 1810 includes one or more output devices 1812 including one or more speakers and/or one or more visual displays. User interface 1810 also includes one or more input devices 1814 . The user interface 1810 may, for example, receive instructions from a remote controller, but is not limited thereto.
  • Memory 1806 may be a high-speed random access memory, such as DRAM, SRAM, DDR RAM, or other random access solid-state storage devices; or a non-volatile memory, such as one or more magnetic disk storage devices, optical disk storage devices, flash memory devices, or other non-volatile solid-state storage devices.
  • DRAM dynamic random access memory
  • SRAM static random access memory
  • DDR RAM dynamic random access memory
  • non-volatile memory such as one or more magnetic disk storage devices, optical disk storage devices, flash memory devices, or other non-volatile solid-state storage devices.
  • the memory 1806 stores a set of instructions executable by the processor 1802, including:
  • Operating system 1816 including programs for processing various basic system services and for performing hardware-related tasks;
  • Application 1818 includes various programs for realizing the above-mentioned generating model surface texture.
  • This kind of program can realize the processing flow in each of the above examples, for example, it may include a method of generating the surface texture of the model.
  • each embodiment of the present application can be realized by a data processing program executed by a data processing device such as a computer.
  • the data processing program constitutes the present invention.
  • a data processing program stored in a storage medium is executed by directly reading the program out of the storage medium or by installing or copying the program into a storage device (such as a hard disk and/or memory) of the data processing device. Therefore, such a storage medium also constitutes the present invention.
  • the storage medium can use any type of recording method, such as paper storage medium (such as paper tape, etc.), magnetic storage medium (such as floppy disk, hard disk, flash memory, etc.), optical storage medium (such as CD-ROM, etc.), magneto-optical storage medium ( Such as MO, etc.) etc.
  • the present application also discloses a non-volatile storage medium in which a program is stored.
  • the program includes instructions that, when executed by a processor, cause the computing device to execute the method for generating model surface textures according to the present application.
  • the method steps described in this application can be realized by data processing programs, and can also be realized by hardware, for example, by logic gates, switches, application specific integrated circuits (ASICs), programmable logic controllers, and embedded micro-controllers. device etc. to achieve. Therefore, such hardware capable of implementing the method described in this application may also constitute this application.
  • ASICs application specific integrated circuits
  • programmable logic controllers programmable logic controllers
  • embedded micro-controllers embedded micro-controllers. device etc. to achieve. Therefore, such hardware capable of implementing the method described in this application may also constitute this application.

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  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Theoretical Computer Science (AREA)
  • Chemical & Material Sciences (AREA)
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Abstract

Selon les modes de réalisation, la présente invention concerne un procédé et un appareil de production de texture de surface de modèle, et un dispositif informatique et un support de stockage. Le procédé de production de texture de surface de modèle est appliqué à un dispositif informatique. Le procédé comprend les étapes suivantes : acquérir un modèle initial ayant une texture de surface à produire ; partitionner une surface du modèle initial, de manière à obtenir un résultat de partitionnement, un angle inclus entre des vecteurs normaux de deux partitions quelconques dans le résultat de partitionnement étant supérieur à une valeur seuil d'angle inclus, et un angle inclus entre des vecteurs normaux à deux positions adjacentes quelconques dans chaque partition ne dépassant pas la valeur seuil d'angle inclus ; acquérir des données de texture correspondant à un angle de paroi de chaque partition dans le résultat de partitionnement, l'angle de paroi de chaque partition étant un angle inclus entre le vecteur normal de la partition et la direction de construction d'un processus de fabrication additive cible, et les données de texture correspondant à l'angle de paroi étant utilisées pour représenter une caractéristique de texture d'une surface qui est orientée à l'angle de paroi et est fabriquée dans le processus de fabrication additive cible ; et produire une texture de surface de chaque partition selon les données de texture de l'angle de paroi de chaque partition, de façon à obtenir un modèle ayant la texture de surface.
PCT/CN2021/118824 2021-09-16 2021-09-16 Procédé et appareil de production de texture de surface de modèle, et dispositif informatique et support de stockage WO2023039800A1 (fr)

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CN202180100930.2A CN117836811A (zh) 2021-09-16 2021-09-16 生成模型表面纹理的方法、装置、计算设备及存储介质
PCT/CN2021/118824 WO2023039800A1 (fr) 2021-09-16 2021-09-16 Procédé et appareil de production de texture de surface de modèle, et dispositif informatique et support de stockage

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Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20170255714A1 (en) * 2016-03-03 2017-09-07 Electronics And Telecommunications Research Institute Apparatus and method for generating 3d printing model using multiple textures
CN111340959A (zh) * 2020-02-17 2020-06-26 天目爱视（北京）科技有限公司 一种基于直方图匹配的三维模型无缝纹理贴图方法
CN112132943A (zh) * 2020-08-26 2020-12-25 山东大学 一种面向3d打印的过程纹理合成系统及方法
WO2021061149A1 (fr) * 2019-09-27 2021-04-01 Hewlett-Packard Development Company, L.P. Textures de modèle tridimensionnel

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20170255714A1 (en) * 2016-03-03 2017-09-07 Electronics And Telecommunications Research Institute Apparatus and method for generating 3d printing model using multiple textures
WO2021061149A1 (fr) * 2019-09-27 2021-04-01 Hewlett-Packard Development Company, L.P. Textures de modèle tridimensionnel
CN111340959A (zh) * 2020-02-17 2020-06-26 天目爱视（北京）科技有限公司 一种基于直方图匹配的三维模型无缝纹理贴图方法
CN112132943A (zh) * 2020-08-26 2020-12-25 山东大学 一种面向3d打印的过程纹理合成系统及方法

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