CN116401904A - CAD digital-analog optimization method and visualization method - Google Patents
CAD digital-analog optimization method and visualization method Download PDFInfo
- Publication number
- CN116401904A CN116401904A CN202310122960.4A CN202310122960A CN116401904A CN 116401904 A CN116401904 A CN 116401904A CN 202310122960 A CN202310122960 A CN 202310122960A CN 116401904 A CN116401904 A CN 116401904A
- Authority
- CN
- China
- Prior art keywords
- cad
- data
- vertex
- grid
- cae
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000000034 method Methods 0.000 title claims abstract description 45
- 238000005457 optimization Methods 0.000 title claims abstract description 24
- 238000007794 visualization technique Methods 0.000 title abstract description 12
- 238000004088 simulation Methods 0.000 claims abstract description 47
- 238000013461 design Methods 0.000 claims abstract description 44
- 238000012545 processing Methods 0.000 claims abstract description 26
- 238000013079 data visualisation Methods 0.000 claims abstract description 24
- 238000009877 rendering Methods 0.000 claims abstract description 16
- 230000008569 process Effects 0.000 claims abstract description 9
- 230000006835 compression Effects 0.000 claims abstract description 4
- 238000007906 compression Methods 0.000 claims abstract description 4
- 238000004364 calculation method Methods 0.000 claims description 17
- 230000000007 visual effect Effects 0.000 claims description 11
- 238000013499 data model Methods 0.000 claims description 7
- 239000000463 material Substances 0.000 claims description 7
- 238000013507 mapping Methods 0.000 claims description 6
- 239000003086 colorant Substances 0.000 claims description 5
- 239000013585 weight reducing agent Substances 0.000 claims description 5
- 230000002829 reductive effect Effects 0.000 claims description 4
- 230000036961 partial effect Effects 0.000 claims description 3
- 230000000694 effects Effects 0.000 claims description 2
- 238000012800 visualization Methods 0.000 abstract description 21
- 230000004927 fusion Effects 0.000 abstract description 17
- 238000011960 computer-aided design Methods 0.000 description 130
- 238000004422 calculation algorithm Methods 0.000 description 8
- 238000010586 diagram Methods 0.000 description 7
- 239000011159 matrix material Substances 0.000 description 7
- 230000008602 contraction Effects 0.000 description 5
- 238000011156 evaluation Methods 0.000 description 5
- 230000008859 change Effects 0.000 description 4
- 238000004458 analytical method Methods 0.000 description 3
- 230000002452 interceptive effect Effects 0.000 description 3
- 230000009286 beneficial effect Effects 0.000 description 2
- 239000012530 fluid Substances 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 238000003672 processing method Methods 0.000 description 2
- 238000012827 research and development Methods 0.000 description 2
- 238000004891 communication Methods 0.000 description 1
- 238000010276 construction Methods 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 238000012938 design process Methods 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 238000000605 extraction Methods 0.000 description 1
- 230000003993 interaction Effects 0.000 description 1
- 238000012482 interaction analysis Methods 0.000 description 1
- 230000002427 irreversible effect Effects 0.000 description 1
- 230000000670 limiting effect Effects 0.000 description 1
- 230000002441 reversible effect Effects 0.000 description 1
- 238000004904 shortening Methods 0.000 description 1
- 238000012549 training Methods 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F30/00—Computer-aided design [CAD]
- G06F30/20—Design optimisation, verification or simulation
- G06F30/23—Design optimisation, verification or simulation using finite element methods [FEM] or finite difference methods [FDM]
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F30/00—Computer-aided design [CAD]
- G06F30/10—Geometric CAD
- G06F30/12—Geometric CAD characterised by design entry means specially adapted for CAD, e.g. graphical user interfaces [GUI] specially adapted for CAD
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F30/00—Computer-aided design [CAD]
- G06F30/10—Geometric CAD
- G06F30/15—Vehicle, aircraft or watercraft design
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T15/00—3D [Three Dimensional] image rendering
- G06T15/005—General purpose rendering architectures
-
- 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
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T17/00—Three dimensional [3D] modelling, e.g. data description of 3D objects
- G06T17/20—Finite element generation, e.g. wire-frame surface description, tesselation
- G06T17/205—Re-meshing
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F2111/00—Details relating to CAD techniques
- G06F2111/04—Constraint-based CAD
Landscapes
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Geometry (AREA)
- General Physics & Mathematics (AREA)
- Computer Hardware Design (AREA)
- Evolutionary Computation (AREA)
- General Engineering & Computer Science (AREA)
- Computer Graphics (AREA)
- Mathematical Optimization (AREA)
- Computational Mathematics (AREA)
- Mathematical Analysis (AREA)
- Pure & Applied Mathematics (AREA)
- Human Computer Interaction (AREA)
- Automation & Control Theory (AREA)
- Aviation & Aerospace Engineering (AREA)
- Architecture (AREA)
- Software Systems (AREA)
- Processing Or Creating Images (AREA)
Abstract
The invention relates to a CAD digital-analog optimizing method and a visualization method, which comprises the following steps: reading CAD design data and CAE simulation data; constructing a multidisciplinary data format parser to convert the read data; discretizing CAD digital and analog into CAD grids; inserting the CAE grid vertices serving as characteristic points into CAD grids, and carrying out local grid subdivision on the CAD grids; processing the CAD grid according to the automatic light weight criterion of the grid model, and reserving characteristic points; the automatic light-weight criterion of the grid model is any one of the following: maximum error weight criteria, compression percentage weight criteria. According to the invention, the simulation body data visualization engine is taken as a basic platform, the existing CAE grid data is utilized to guide the optimization process of the CAD digital and analog, the CAD digital and analog is automatically compressed on the premise of ensuring the display quality of the CAD digital and analog, the rendering efficiency is improved, and a feasible technical path is provided for multi-disciplinary fusion visualization of civil aircraft complex products.
Description
Technical Field
The invention relates to the technical field of CAD design data and CAE simulation data fusion, in particular to an optimization method and a visualization method of CAD digital and analog.
Background
Multidisciplinary collaborative evaluation is an important means for shortening the research and development period of complex products and improving the research and development quality. The complex product refers to a modern industrial complex product system, including aircraft, spacecraft, high-speed trains, large ships, and the like. The multidisciplinary collaborative evaluation refers to that the calculation results of multiple disciplines are displayed in the same application by using the current advanced visualization means (VR/AR/MR visualization). In the aircraft design process, CAD and CAE designs can be mutually influenced, CAD and CAE design tools are completely different, and in order to facilitate communication and collaborative evaluation among different departments, it is very important to visualize CAD and CAE design results in the same application.
Currently, designers use CAD systems (Computer Aided Design ) to design three-dimensional models of products, and simulators use CAE systems (Computer Aided Engineering ) to perform simulation calculations on products in the field of finite element, fluid mechanics professionals. CAD design data generated by a CAD system is surface data and CAE simulation data generated by a CAE system is volume data, both of which are typically displayed by different visualization systems. In general, CAD design data may also be referred to as CAD models or CAD models.
In order to realize the fusion visualization of CAD design data and CAE simulation data, the current common mode is: the CAE simulation data is first preprocessed to convert the volume data into surface data, and then imported into a general-purpose surface data rendering engine (e.g., unity3D, unrealEngine, etc.). Whether the process is realized by manual operation or through automatic and semi-automatic software tools which are custom-developed, the efficiency is low, more importantly, the general surface data rendering engine is difficult to be compatible with the processing of support data, visual interaction analysis can not be carried out on CAE simulation data, and the actual requirement of complex product multidisciplinary collaborative evaluation can not be met.
In practical engineering application, the proportion of CAE simulation data (volume data) is often larger, and a more reasonable solution should be: CAD design data (face data) is fused based on a simulation volume data visualization engine (e.g., VTK, etc.). However, the burden of the interactive visualization processing of the volume data is heavy, in order to realize the fusion visualization of CAE/CAD multidisciplinary data, the real-time performance of the interactive visualization analysis is ensured, the original CAD digital model is not suitable to be directly adopted for rendering, and the CAD digital model can be processed by the simulated volume data visualization engine after being read into the simulated volume data visualization engine and discretized (tessellated) into a triangular patch model; the discretization of the CAD digital model is mature, but the discretized triangular surface patch model is often broken, so that the data size is large and the triangle surface patch model is not smooth, and therefore, the problems of large data size and difficult visual quality guarantee exist.
The CAE/CAD multidisciplinary data fusion visualization method disclosed by the invention comprises the following steps of:
multidisciplinary fusion refers to CAD (three-dimensional digital-analog design) fusion and CAE (simulation calculation in the field of finite element and fluid mechanics profession) fusion in civil aircraft design and visual presentation;
data fusion visualization refers to subject data fusion, and the final presentation form can be understood as the visualization and superposition fusion display of CAD (computer aided design) and CAE (computer aided engineering) models in one visualization system (such as a computer desktop, a VR helmet, a CAVE system and the like) in the same visualization application. For example: the fuselage visualization is based on CAD design data and the wing visualization is based on CAE simulation data.
Through the fusion, the spatial states of the CAD design data and the CAE simulation data in the three-dimensional scene of the volume data visualization platform are coordinated and consistent, so that the interaction behavior can be applied as a whole, the data states can be synchronously updated, and the analysis operation can be independently selected from the internal data structure.
The existing technical path still depends on manual visual optimization processing of CAD digital and analog, and the manual processing is time-consuming and labor-consuming, has high technical level requirements on personnel, and becomes one of bottleneck technical problems for preventing multi-disciplinary fusion visualization of complex products.
Typically, CAD system (e.g., catia) designs produce CAD number molds with accurate mathematical representations, such as non-uniform rational B-splines (NURBS), that need to be discretized into mesh models (mesh models made up of triangular patches) to be processed by a simulation volume data visualization engine. Because the grid model directly and discretely generated by CAD digital and analog is often not optimized, the triangular patches are broken, and the method is directly used for rendering, so that the rendering burden is heavy, and the display quality is poor. The existing grid optimization algorithm can improve the light smoothness of the grid model, but is difficult to effectively reduce the number of triangular patches, so that the light weight of the grid model cannot be realized, the light weight of CAD (computer aided design) digital and analog still needs a large amount of manual participation, time is wasted, and the technical level requirement on personnel is high.
The information disclosed in this background section is only for enhancement of understanding of the general background of the invention and should not be taken as an acknowledgement or any form of suggestion that this information forms the prior art already known to a person skilled in the art.
Disclosure of Invention
Aiming at the defects existing in the prior art, the invention aims to provide the optimization method and the visualization method of the CAD digital model, which take a simulation body data visualization engine as a basic platform, utilize the existing CAE grid data to guide the optimization process of the CAD digital model, automatically compress the CAD digital model on the premise of ensuring the display quality of the CAD digital model, improve the rendering efficiency and provide a feasible technical path for multi-disciplinary fusion visualization of complex products of civil machines.
In order to achieve the above purpose, the invention adopts the following technical scheme:
the CAD digital-analog optimization method is characterized by comprising the following steps:
step 1, reading in CAD design data from a CAD system in a volume data visualization platform; reading in CAE simulation data from a CAE system in a volume data visualization platform;
step 2, constructing a multidisciplinary data format analyzer, reading CAD design data and CAE simulation data through the multidisciplinary data format analyzer, and converting the read data into a data structure which can be processed by a pipeline and a rendering engine of a body data visualization platform;
step 3, discretizing the CAD digital model to obtain a discretized CAD grid;
step 4, taking CAE grid data as an optimization template for CAD digital-analog light weight, taking CAE grid vertices in the CAE grid data as characteristic points to be inserted into discretized CAD grids, and carrying out partial grid subdivision on the CAD grids;
step 5, processing the CAD grid according to the automatic lightweight criterion of the grid model, and reserving the characteristic points obtained in the step 4 in the lightweight processing process so as to achieve the aim of optimizing the CAD grid;
the automatic light-weight criterion of the grid model is any one of the following: maximum error weight criteria, compression percentage weight criteria.
Based on the above technical solution, in step 1, the CAD design data includes: geometric information and texture information; the CAD design data is CAD design data for complex products;
the CAE simulation data includes: the grid model and the calculation result are tensor calculation result or vector calculation result.
On the basis of the technical scheme, in the STEP 1, the CAD design data and the CAE simulation data can be read in by constructing a data interface, and the CAD design data and the CAE simulation data can be read in and converted by using open data file formats such as STEP, 3dxml and the like.
Based on the technical scheme, in the step 2, the pipeline and the rendering engine adopt a simulation body data visualization engine;
the data structure comprises: CAD data corresponding to CAD data; CAE mesh data corresponding to CAE simulation data.
Based on the above technical solution, in step 5, the strategy of lightening the CAD mesh is to reduce the resolution of the mesh, and only remove the geometric details that have no significant effect on the shape, so as to significantly reduce the number of vertices and polygons;
when the strategy of CAD mesh weight reduction adopts the QEM method, constraint conditions are added on the selection of vertexes and edges:
constraint a, the valid edge must be the edge present in the grid;
constraint b, V c ∈{V i }，V c Refers to the lightweight vertex, { V i The vertex set before light weight, namely the new vertex is the original vertex; the constraint condition is that no new vertex is generated after the light weight is limited, so that the problem of large light weight deformation is avoided;
constraint condition c, the inserted CAE grid vertex is marked as a feature point, and is reserved in the light weight processing.
Based on the technical scheme, the specific processing steps of the step 4 are as follows:
in the simulation body data visualization engine, according to the CAE grid vertex list, starting from the first CAE grid vertex, sequentially selecting each vertex P, and after each vertex P is selected, performing the following processing:
traversing triangular patches in the CAD grid, and calculating the distances between the vertexes V1, V2 and V3 of the triangular patches and the vertexes P one by one;
when the distance between the vertex of a certain triangular surface patch and the vertex P is smaller than a preset threshold delta, marking the vertex of the certain triangular surface patch as a characteristic point;
when the distances between the vertexes of the triangular surface patches and the vertexes P are all larger than or equal to a preset threshold delta, the method comprises the following steps:
traversing the triangular patches in the CAD grid, and calculating projection distances from the vertexes P to each side of the triangular patches one by one;
when a certain projection distance is smaller than a preset threshold epsilon, inserting a projection point P 'of a vertex P on the edge into the CAD grid, and marking the projection point P' as a characteristic point;
when the projection distance from the vertex P to each side of the triangular patch is larger than or equal to a preset threshold epsilon, the following steps are:
inserting the vertex P and marking the vertex P as a feature point.
Based on the above technical solution, in step 4, the performing local mesh subdivision on the CAD mesh refers to performing CAD model triangulation by using feature points, forming a new triangle by using a re-topology, and adding the feature points into a vertex chain table of the CAD model.
The visualization method of the CAD data model is characterized in that texture material mapping is carried out based on a vertex linked list of the CAD model obtained by the optimization method of any one of the CAD data models;
the lightweight CAD grid is obtained through texture material mapping processing, and comprises vertex positions, vertex colors and texture information;
and visually presenting the lightweight CAD grid through a simulation body data visual engine.
On the basis of the above technical solution, for the color attribute of the mesh, let the triangle t= (V1, V2, V3), P be the vertex coordinates, S be the color rgb, and the error metric error of the triangle T be expressed as:
wherein the method comprises the steps of
Is the square of the distance from the vertex P to the projection point P'>
S is the distance deviation from S ' and S ' is the color interpolation of the projection point P ';
the distance from the vertex P to the projection point P' is usually very small, and the point P can be approximately considered to be positioned in the triangle T, and the appearance attribute value is obtained by directly interpolating the attribute values at the three vertices, so that the calculation amount is greatly reduced.
The invention relates to a CAD digital-analog optimization method and a visualization method, which have the following steps of
The beneficial effects are that:
1. based on a simulation body data visualization engine as a basic platform, CAD design data (surface data) are fused, a feasible technical path is provided for multi-disciplinary fusion visualization of civil aircraft (refer to civil aircraft) complex products, CAD digital and analog is automatically compressed on the premise of ensuring the CAD digital and analog display quality, and the rendering efficiency is improved.
2. The existing CAE grid data is fully utilized to guide the optimization process of the CAD digital-analog, and the CAD digital-analog is optimized and compressed on the premise of ensuring the display quality of the CAD digital-analog.
3. The number of patches of the CAD digital model (the number of triangular patches of the CAD visual model) is greatly compressed, so that the rendering load of a simulation body data visual engine is reduced, the interactive operation analysis of multi-subject data fusion visualization of a complex product is ensured, and the CAD and the CAE are more seamlessly attached during fusion display.
The CAE grid data is usually optimized, so that the shape of the CAD design is maintained, the number of the patches is small, and if the existing CAE grid data is fully utilized, the number of the patches of the CAD digital model can be greatly compressed on the premise of ensuring the display quality of the CAD digital model.
The optimization method and the visualization method of the CAD digital model can be used in the fields of collaborative design and evaluation, multidisciplinary collaboration, virtual simulation, training and the like of digital prototypes of civil aircrafts (civil aircrafts), can realize real-time rendering of large-scale engineering data, are beneficial to developing staff to find potential technical problems, reduce reworking and improve the development efficiency of the civil aircrafts.
The CAD digital-analog optimization method and the visualization method have the characteristics of universality and basicity, can be applied to multi-disciplinary collaborative visualization of complex products such as ships, engines and automobiles, and have market popularization value.
Drawings
The invention has the following drawings:
the drawings are included to provide a better understanding of the invention and are not to be construed as unduly limiting the invention. Wherein:
FIG. 1 is a flow chart of a CAD data model optimizing method and a visualization method according to the present invention.
FIG. 2 (a) schematic diagram one of the QEM edge contraction algorithm proposed by Garland and Heckbert;
FIG. 2 (b) schematic diagram II of the QEM edge contraction algorithm proposed by Garland and Heckbert;
FIG. 3 (a) schematic diagram of the distance between the apex of a triangular patch and the apex P;
FIG. 3 (b) schematic diagram II of the distance between the apex of the triangular patch and the apex P;
fig. 3. (c) schematic view of the projected point P' of the vertex P on the edge;
fig. 3. (d) triangulation scheme;
(e) vertex P directly serves as a feature point schematic diagram one;
(f) vertex P directly serves as a feature point schematic diagram two;
FIG. 4 is a schematic diagram of a processing method for color and texture in model weight reduction;
Detailed Description
The present invention will be described in further detail with reference to the accompanying drawings. The detailed description, while indicating exemplary embodiments of the invention, includes various details of the embodiments of the invention for the purpose of illustration only, should be considered as exemplary. Accordingly, those skilled in the art will recognize that various changes and modifications of the embodiments described herein can be made without departing from the scope and spirit of the invention. Also, descriptions of well-known functions and constructions are omitted in the following description for clarity and conciseness.
As shown in fig. 1, the invention provides a method for optimizing CAD digital-analog, comprising the following steps:
step 1, reading in CAD design data from a CAD system in a volume data visualization platform; reading in CAE simulation data from a CAE system in a volume data visualization platform;
the CAD design data includes: geometric information and texture information; the CAD design data is CAD design data for complex products;
the CAE simulation data includes: the grid model and the calculation result are tensor calculation result or vector calculation result;
reading in CAD design data and CAE simulation data can be realized by constructing a data interface, taking a commercial CAD system Catia as an example, constructing a 3DK data interface and a CADExChanger data interface, and reading in the CAD design data and the CAE simulation data;
the read CAD design data and CAE simulation data can be converted through STEP, 3dxml and other open data file formats;
step 2, constructing a multidisciplinary data format analyzer, reading CAD design data and CAE simulation data through the multidisciplinary data format analyzer, and converting the read data into a data structure which can be processed by a pipeline and a rendering engine of a body data visualization platform; the pipeline and the rendering engine adopt simulation body data visualization engines (such as any existing simulation body data visualization engines such as VTK and the like);
the data structure comprises: CAD data corresponding to CAD data; CAE mesh data corresponding to CAE simulation data;
the CAE grid data is usually optimized, so that not only the shape of the CAD design is maintained, but also the number of the patches is small, and is about 20% of the number of the patches of the CAD discrete grid in general;
the CAE grid data are obtained discretely on the basis of CAD design digital-analog, in order to ensure the accuracy of subsequent CAE calculation, the grid needs to be optimized, and for complex-shape products, the optimization process often needs to be participated by technicians with abundant engineering experience;
although the optimization criterion of CAE grid data is proposed for subsequent simulation calculation, the optimization criterion is highly consistent with the visualization processing criterion of CAD digital-analog, namely fewer grid vertices are arranged in a gentle region, larger grids are adopted, denser grids are arranged in a region with severe curvature change, and the appearance characteristics of the original CAD product are maintained as much as possible;
therefore, CAE grid data can be regarded as a high-quality simplified version of the CAD discrete model, so as to guide the light weight processing of the CAD original discrete grid model;
step 3, discretizing the CAD digital model to obtain a discretized CAD grid;
step 4, taking CAE grid data as an optimization template for CAD digital-analog light weight, taking CAE grid vertices in the CAE grid data as characteristic points to be inserted into discretized CAD grids, and carrying out partial grid subdivision on the CAD grids;
step 5, processing the CAD grid according to the automatic lightweight criterion of the grid model, and reserving the characteristic points obtained in the step 4 in the lightweight processing process so as to achieve the aim of optimizing the CAD grid;
the automatic light-weight criterion of the grid model is any one of the following: a maximum error weight criterion and a compression percentage weight criterion; the above light weight criteria are all conventional light weight criteria, and the present invention will not be described in detail;
the strategy of CAD mesh weight reduction is to reduce the resolution of the mesh, and only remove geometric details that have no significant impact on shape, thereby significantly reducing the number of vertices and polygons;
in the strategy of CAD mesh weight reduction, the selection of the difference measure is important, and theoretically, the difference measure should reflect the visual change degree of the model, however, in practice, the difference measure is difficult to measure; thus, researchers have proposed a number of specific difference metrics, such as geometric distance in object space (e.g., hausdorff distance), pixel distance in screen space, or differences in attribute space (e.g., normal, color, or texture), applying a broad-ranging edge-contraction algorithm based on quadratic errors as metric costs (Quadric Error Matrix, QEM) proposed by Garland and Heckbert, as shown in fig. 2 (a), 2 (b), which is fast in computation speed and of higher simplified quality, the QEM edge-contraction algorithm defines a variable Δ describing the edge-contraction cost when selecting an appropriate edge for iterative contraction, as follows:
for each of the gridsA 4×4 symmetric error matrix Q is predefined for each vertex V, then vertex v= [ Vx Vy Vz 1] T The error is its quadratic form delta (V) =v T QV；
Assume that for a contracted edge (V1, V2), its vertex becomes Vc after contraction, and its error matrix Qc is qc=q1+q2;
there are two strategies for conventionally calculating the location of the vertex Vc: one simple strategy is to choose one of V1, V2 and (v1+v2)/2 that minimizes the contraction cost delta (Vc), another strategy is to numerically calculate the vertex Vc position that minimizes delta (Vc), since the expression of delta is a quadratic form, let the first derivative be 0, i.e. the expression is equivalent to solving:
wherein q is ij Corresponding elements in the matrix Qc;
if the coefficient matrix is reversible, the position of the new vertex Vc can be obtained by solving the equation, and if the coefficient matrix is irreversible, the position of the new vertex Vc is obtained by a first strategy;
according to the above description, the QEM algorithm steps are as follows ([ 1]Garland M,Heckbert P S.Simplifying surfaces with color and texture using quadric error metrics[C ]// visualization.ieee, 1998.):
(1) Calculating a Q matrix for all initial vertices;
(2) Selecting all valid edges (here, the edges are communicated, and edges with a distance smaller than a threshold value can be classified as valid edges);
(3) For each valid edge (V1, V2), an optimal extraction target is calculated
Error->
(Q1+Q2)/>
Is the cost of extracting this edge (cost);
(4) Placing all edges into a heap according to the weight of the cost;
(5) The edge with the smallest cost (cost) is removed each time, and the cost of all valid edges containing V1 is updated;
however, the conventional QEM method can change the topology of the original grid, and there is a risk of changing edges, holes and concave shapes in the original grid, and vertices in the original grid are directly generated in a CAD design model in a discrete manner, that is, the vertices are interpolation points with accurate spatial positions, so that the positions of the vertices are not easy to change;
the invention reforms the conventional QEM method, and when the CAD grid light strategy adopts the QEM method, constraint conditions are added on the selection of vertexes and edges:
constraint a, the valid edge must be the edge present in the grid;
constraint b, V c ∈{V i }，V c Refers to the lightweight vertex, { V i The vertex set before light weight, namely the new vertex is the original vertex; the constraint condition is that no new vertex is generated after the light weight is limited, so that the problem of large light weight deformation is avoided;
constraint condition c, namely marking the inserted CAE grid vertexes as characteristic points, and reserving the characteristic points in light weight treatment;
after constraint conditions are added, the topology of the CAD grid can be effectively maintained, and the calculation speed can be greatly improved; the grid after the above processing can be optimized as a whole in order to ensure the fairing of the final grid.
Based on the technical scheme, the specific processing steps of the step 4 are as follows:
in the simulation body data visualization engine, according to the CAE grid vertex list, starting from the first CAE grid vertex, sequentially selecting each vertex P, and after each vertex P is selected, performing the following processing:
traversing triangular patches in the CAD grid, and calculating the distances between the vertexes V1, V2 and V3 of the triangular patches and the vertexes P one by one;
when the distance between the vertex of a certain triangular surface patch and the vertex P is smaller than a preset threshold delta, marking the vertex of the certain triangular surface patch as a characteristic point;
as shown in fig. 3 (a) and 3 (b), if the distance between the triangular patch vertex V1 and the vertex P is smaller than a preset threshold value δ, marking the triangular patch vertex V1 as a feature point, and marking as V1 (P);
when the distances between the vertexes of the triangular surface patches and the vertexes P are all larger than or equal to a preset threshold delta, the method comprises the following steps:
traversing the triangular patches in the CAD grid, and calculating projection distances from the vertexes P to each side of the triangular patches one by one;
when a certain projection distance is smaller than a preset threshold epsilon, inserting a projection point P 'of a vertex P on the edge into the CAD grid, and marking the projection point P' as a characteristic point;
as shown in fig. 3. (c), if the projection distance between the vertex P and the edge formed by the triangular patch vertex V1 and the triangular patch vertex V2 is smaller than a preset threshold epsilon, inserting a projection point P 'of the vertex P on the edge into the CAD grid, and marking the projection point P' as a feature point;
when the projection distance from the vertex P to each side of the triangular patch is larger than or equal to a preset threshold epsilon, the following steps are:
inserting a vertex P and marking the vertex P as a feature point;
the feature points are obtained by the vertexes P, and when the vertexes P are very close to the vertexes of the triangular surface patch, the vertexes of the triangular surface patch are feature points; when the vertex P is very close to one side of the triangular patch, the projection point P' from the vertex P to the side is a characteristic point; when the vertex P is not close to the vertex of the triangular surface patch or one side of the triangular surface patch, the vertex P is directly used as a characteristic point;
performing CAD model triangulation through the feature points, forming a new triangle through the re-topology, and adding the feature points into a vertex chain table of the CAD model; the specific algorithm of triangulation is realized by adopting the prior art, and the invention is not described in detail;
as shown in fig. 3 (d), when the vertex P is very close to one side of the triangular surface patch, the vertices of two triangular surface patches including the side where the projection point P' is located are both projected withThe shadow point P' is connected, and the original two triangles DeltaV 1 V 2 V 3 、△V 1 V 2 V 4 Splitting into four triangles DeltaV 1 P ’ V 3 、△V 2 P ’ V 3 、△V 1 P ’ V 4 、△V 2 P ’ V 4 Updating the CAD grid data structure linked list after triangulation is completed: will add the feature point P ’ Adding the triangle indexes to a vertex chain table, deleting vertex indexes of the original two triangles, and adding the vertex indexes of the four triangles subjected to triangulation to the chain table;
as shown in fig. 3 (e) and 3 (f), when the vertex P is not close to the triangular surface patch vertex nor to one side of the triangular surface patch, the vertex P is respectively connected to the triangular surface patch vertex V 1 、V 2 V 3 Is connected with the original triangle delta V 1 V 2 V 3 Split into three triangles DeltaV 1 PV 2 、△V 2 PV 3 、△V 1 PV 3 Updating the CAD grid data structure linked list after triangulation is completed: adding the newly added feature point P to a vertex chain table, deleting the vertex index of the original triangle, and adding the vertex indexes of the three triangles subjected to triangulation to the chain table.
Based on the optimization method of the CAD data model, the invention also provides a visualization method of the CAD data model, and texture material mapping is carried out based on the vertex linked list of the CAD model obtained by the optimization method of the CAD data model;
in order to maintain the original properties of materials, textures, colors and the like on the CAD design model, corresponding attribute values need to be assigned to the newly added feature points, and the processing method for the colors and the textures in the light model weight of Garland ([ 1]Garland M,Heckbert P S.Simplifying surfaces with color and texture using quadric error metrics[C ]// visual field. IEEE, 1998.) is used for reference, and is obtained through linear interpolation, as shown in FIG. 4:
for the color attribute of the mesh, let the triangle t= (V1, V2, V3), P be the vertex coordinates, S be the color rgb, the error metric error of the triangle T is expressed as:
wherein the method comprises the steps of
Is the square of the distance from the vertex P to the projection point P'>
S is the distance deviation from S ' and S ' is the color interpolation of the projection point P ';
for the application scene in the invention, the distance from the vertex P to the projection point P' is usually very small, the point P can be approximately considered to be positioned in the triangle T, and the appearance attribute value is obtained by directly interpolating the attribute values of the three vertices, so that the calculated amount is greatly reduced;
the lightweight CAD grid is obtained through texture material mapping processing, and comprises vertex positions, vertex colors and texture information;
and visually presenting the lightweight CAD grid through a simulation body data visual engine.
The improved QEM algorithm is adopted in the invention, only the vertexes are removed in the light weight process, and the light weight processing efficiency of the CAD grid with texture materials is very high.
What is not described in detail in this specification is prior art known to those skilled in the art.
The above description is merely of the preferred embodiments of the present invention, the protection scope of the present invention is not limited to the above embodiments, but all equivalent modifications or variations according to the disclosure of the present invention should be included in the protection scope of the claims.
Claims (9)
1. The CAD digital-analog optimization method is characterized by comprising the following steps:
step 1, reading in CAD design data from a CAD system in a volume data visualization platform; reading in CAE simulation data from a CAE system in a volume data visualization platform;
step 2, constructing a multidisciplinary data format analyzer, reading CAD design data and CAE simulation data through the multidisciplinary data format analyzer, and converting the read data into a data structure which can be processed by a pipeline and a rendering engine of a body data visualization platform;
step 3, discretizing the CAD digital model to obtain a discretized CAD grid;
step 4, taking CAE grid data as an optimization template for CAD digital-analog light weight, taking CAE grid vertices in the CAE grid data as characteristic points to be inserted into discretized CAD grids, and carrying out partial grid subdivision on the CAD grids;
step 5, processing the CAD grid according to the automatic lightweight criterion of the grid model, and reserving the characteristic points obtained in the step 4 in the lightweight processing process so as to achieve the aim of optimizing the CAD grid;
the automatic light-weight criterion of the grid model is any one of the following: maximum error weight criteria, compression percentage weight criteria.
2. The method for optimizing a CAD model of claim 1, wherein in step 1, the CAD design data comprises: geometric information and texture information; the CAD design data is CAD design data for complex products;
the CAE simulation data includes: the grid model and the calculation result are tensor calculation result or vector calculation result.
3. The method for optimizing CAD data model as claimed in claim 1, wherein in STEP 1, the CAD design data and the CAE simulation data are read in by constructing a data interface, and the CAD design data and the CAE simulation data are read in and converted by open data file formats such as STEP, 3dxml, etc.
4. The method of optimizing CAD models of claim 1, wherein in step 2, the pipeline and rendering engine employ a simulation volume data visualization engine;
the data structure comprises: CAD data corresponding to CAD data; CAE mesh data corresponding to CAE simulation data.
5. The optimization method of CAD digital-analog as set forth in claim 1, wherein in step 5, the CAD mesh is lightened by reducing the resolution of the mesh, and only geometric details that have no significant effect on the shape are removed, thereby significantly reducing the number of vertices and polygons;
when the strategy of CAD mesh weight reduction adopts the QEM method, constraint conditions are added on the selection of vertexes and edges:
constraint a, the valid edge must be the edge present in the grid;
constraint b, V c ∈{V i }，V c Refers to the lightweight vertex, { V i The vertex set before light weight, namely the new vertex is the original vertex; the constraint condition is that no new vertex is generated after the light weight is limited, so that the problem of large light weight deformation is avoided;
constraint condition c, the inserted CAE grid vertex is marked as a feature point, and is reserved in the light weight processing.
6. The method for optimizing CAD digital-analog as set forth in claim 1, wherein the specific processing steps of step 4 are:
in the simulation body data visualization engine, according to the CAE grid vertex list, starting from the first CAE grid vertex, sequentially selecting each vertex P, and after each vertex P is selected, performing the following processing:
traversing triangular patches in the CAD grid, and calculating the distances between the vertexes V1, V2 and V3 of the triangular patches and the vertexes P one by one;
when the distance between the vertex of a certain triangular surface patch and the vertex P is smaller than a preset threshold delta, marking the vertex of the certain triangular surface patch as a characteristic point;
when the distances between the vertexes of the triangular surface patches and the vertexes P are all larger than or equal to a preset threshold delta, the method comprises the following steps:
traversing the triangular patches in the CAD grid, and calculating projection distances from the vertexes P to each side of the triangular patches one by one;
when a certain projection distance is smaller than a preset threshold epsilon, inserting a projection point P 'of a vertex P on the edge into the CAD grid, and marking the projection point P' as a characteristic point;
when the projection distance from the vertex P to each side of the triangular patch is larger than or equal to a preset threshold epsilon, the following steps are:
inserting the vertex P and marking the vertex P as a feature point.
7. The method for optimizing a CAD model of claim 6, wherein in step 4, the step of performing local mesh subdivision on the CAD mesh means performing CAD model triangulation by using feature points, forming a new triangle by re-topology, and adding the feature points into a linked list of vertices of the CAD model.
8. A method for visualizing a CAD model, characterized in that texture mapping is performed based on a linked list of vertices of the CAD model obtained by the method for optimizing a CAD model according to any one of claims 1 to 7;
the lightweight CAD grid is obtained through texture material mapping processing, and comprises vertex positions, vertex colors and texture information;
and visually presenting the lightweight CAD grid through a simulation body data visual engine.
9. A method of visualizing a CAD phantom as in claim 8, wherein for the color properties of the mesh, let the triangle t= (V1, V2, V3), P be the vertex coordinates, S be the color rgb, and the error metric error of the triangle T be expressed as:
wherein the method comprises the steps of
Is the square of the distance from the vertex P to the projection point P'>
S is the distance deviation from S ' and S ' is the color interpolation of the projection point P ';
the distance from the vertex P to the projection point P' is usually very small, and the point P can be approximately considered to be positioned in the triangle T, and the appearance attribute value is obtained by directly interpolating the attribute values at the three vertices, so that the calculation amount is greatly reduced.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310122960.4A CN116401904A (en) | 2023-02-16 | 2023-02-16 | CAD digital-analog optimization method and visualization method |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310122960.4A CN116401904A (en) | 2023-02-16 | 2023-02-16 | CAD digital-analog optimization method and visualization method |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN116401904A true CN116401904A (en) | 2023-07-07 |
Family
ID=87011255
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202310122960.4A Pending CN116401904A (en) | 2023-02-16 | 2023-02-16 | CAD digital-analog optimization method and visualization method |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN116401904A (en) |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117892602A (en) * | 2024-03-15 | 2024-04-16 | 芯瑞微(上海)电子科技有限公司 | Meshing method and related equipment of 2.5D model based on industrial simulation software |
| CN117892602B (en) * | 2024-03-15 | 2024-06-07 | 芯瑞微(上海)电子科技有限公司 | Meshing method and related equipment of 2.5D model based on industrial simulation software |
-
2023
- 2023-02-16 CN CN202310122960.4A patent/CN116401904A/en active Pending
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117892602A (en) * | 2024-03-15 | 2024-04-16 | 芯瑞微(上海)电子科技有限公司 | Meshing method and related equipment of 2.5D model based on industrial simulation software |
| CN117892602B (en) * | 2024-03-15 | 2024-06-07 | 芯瑞微(上海)电子科技有限公司 | Meshing method and related equipment of 2.5D model based on industrial simulation software |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN108595858B (en) | BIM-based lightweight advanced treatment working method | |
| WO2020192354A1 (en) | Blended urban design scene simulation method and system | |
| CN113158288B (en) | Information model geometric lightweight method based on component reuse and reassembly | |
| CN102214254B (en) | By the Element Design of parallel geodesic curves modeling | |
| Guo et al. | Automatic and high-quality surface mesh generation for CAD models | |
| US6720963B2 (en) | Three-dimensional CAD system and recording medium for three-dimensional CAD system | |
| Farin et al. | Geometric Modeling | |
| US20240153123A1 (en) | Isogeometric Analysis Method Based on a Geometric Reconstruction Model | |
| KR20030073424A (en) | A rendering system, rendering method, and recording medium therefor | |
| CN115345988A (en) | Secondary error measurement edge folding BIM lightweight method based on vertex importance | |
| CN111462328B (en) | Interpolation method for multiple three-dimensional grid models based on progressive interpolation subdivision surface | |
| CN113987659A (en) | Building design method based on BIM technology | |
| Taylor et al. | Geometry Modelling: Underlying Concepts and Requirements for Computational Simulation | |
| CN115358001A (en) | Aerodynamic stealth comprehensive optimization method for front edge radius of flying wing layout aircraft | |
| CN117315192B (en) | Three-dimensional grid model simplification method for Chinese space station | |
| CN116401904A (en) | CAD digital-analog optimization method and visualization method | |
| JP3786410B2 (en) | Fillet creation method and 3D CAD program | |
| CN109684656B (en) | Assembly constraint inheritance method based on SolidWorks | |
| CN113888701A (en) | Method and system for converting curved surface 3D model into mesh 3D model in Obj format | |
| CN114633850B (en) | Virtual visual reconstruction method for finite element model of ship structure | |
| Großmann et al. | Volumetric geometry reconstruction of turbine blades for aircraft engines | |
| Chen et al. | Research on 3D modeling in scene simulation based on Creator and 3dsmax | |
| Li et al. | Turbine blade temperature transfer using the load surface method | |
| Zhao | Application Research in Computer Aided Development Modeling System of Art Design 3D Technology | |
| jielin | 3D Garment Designing Method of Human Body Based on Surface Modeling Technology |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |