Feature line extraction method, device, electronic device and computer readable storage medium

Abstract

The present disclosure relates to a feature line extraction method, device, electronic device and computer-readable storage medium. By reading a geometric model file corresponding to a geometric model, and determining a mesh model corresponding to the geometric model. Obtain multiple grid lines corresponding to multiple grid units in the mesh model, and obtain data information of the geometric model file. Generate feature lines based on the data information and multiple grid lines, and the feature lines are used to describe the shape distribution of the geometric model. In some instances, the present disclosure can read a geometric model file, and obtain data information and a mesh model of the geometric model file, and then generate feature lines for describing the geometric features of the geometric model based on the data information and the mesh model. It can be seen that the feature line generation method used in the present disclosure is more concise and can ensure accurate feature line extraction of the geometric model.

Description

Technical Field

[0001] The present disclosure relates to the field of model processing research, and in particular to a feature line extraction method, device, electronic device and computer-readable storage medium. Background Art

[0002] At present, the research on feature extraction at home and abroad has become increasingly mature and many feature extraction methods have emerged to extract the feature lines of geometric models.

[0003] In the related art, the shape distribution method of the geometric features of the three-dimensional model is mainly obtained through random sampling, and the distribution curve of the three-dimensional model is obtained by obtaining the Euclidean distance between two points. However, geometric models with similar appearance structures but different details may also have the same shape distribution curve. Therefore, it is impossible to accurately extract the characteristic lines of different geometric models, which is not ideal for use in practical applications. Summary of the invention

[0004] In view of this, the embodiments of the present disclosure provide a feature line extraction method, device, electronic device and computer-readable storage medium to solve the problem in the related art that feature lines of different geometric models cannot be accurately extracted.

[0005] According to a first aspect of an embodiment of the present disclosure, a feature line extraction method is provided, the method comprising: reading a geometric model file corresponding to a geometric model, and determining a mesh model corresponding to the geometric model; obtaining a plurality of mesh lines corresponding to a plurality of mesh units in the mesh model, and obtaining data information of the geometric model file; generating feature lines based on the data information and the plurality of mesh lines, the feature lines being used to describe the shape distribution of the geometric model.

[0006] According to a second aspect of an embodiment of the present disclosure, a feature line extraction device is provided, which is applied to the feature line extraction device of the first aspect, and the device includes: a reading module, which is used to read a geometric model file corresponding to a geometric model, and determine a mesh model corresponding to the geometric model; an acquisition module, which is used to acquire multiple grid lines corresponding to multiple grid units in the mesh model, and acquire data information of the geometric model file; and a generation module, which is used to generate feature lines according to the data information and the multiple grid lines, and the feature lines are used to describe the shape distribution of the geometric model.

[0007] According to a third aspect of an embodiment of the present disclosure, an electronic device is provided, comprising at least one processor; and a memory for storing instructions executable by at least one processor; wherein the at least one processor is used to execute instructions to implement the steps of the above-mentioned feature line extraction method.

[0008] According to a fourth aspect of the embodiments of the present disclosure, a computer-readable storage medium is provided. When instructions in the computer-readable storage medium are executed by a processor of an electronic device, the electronic device is enabled to perform the steps of the above-mentioned feature line extraction method.

[0009] At least one of the above technical solutions adopted in the embodiments of the present disclosure can achieve the following beneficial effects: by reading the geometric model file corresponding to the geometric model and determining the mesh model corresponding to the geometric model. Obtain multiple grid lines corresponding to multiple grid units in the mesh model, and obtain data information of the geometric model file. Generate feature lines based on the data information and multiple grid lines, and the feature lines are used to describe the shape distribution of the geometric model. In some instances, the present disclosure can read the geometric model file, and obtain the data information and mesh model of the geometric model file, and then generate feature lines for describing the geometric features of the geometric model based on the data information and the mesh model. It can be seen that the feature line generation method adopted by the present disclosure is more concise and can ensure accurate feature line extraction of the geometric model. BRIEF DESCRIPTION OF THE DRAWINGS

[0010] In order to more clearly illustrate the technical solutions in the embodiments of the present disclosure, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present disclosure. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0011] Figure 1 A flowchart of a feature line extraction method provided by an exemplary embodiment of the present disclosure;

[0012] Figure 2 A schematic diagram of a structure for extracting a blade feature line that can be seen in an exemplary embodiment of the present disclosure;

[0013] Figure 3 A schematic diagram of a structure for extracting a cylindrical feature line with visible effect provided by an exemplary embodiment of the present disclosure;

[0014] Figure 4 A schematic diagram of a structure of discrete points on a cylindrical characteristic line provided by an exemplary embodiment of the present disclosure;

[0015] Figure 5 A schematic diagram of a structure of a quadrilateral network generated by a cylindrical feature line provided by an exemplary embodiment of the present disclosure;

[0016] Figure 6 A schematic diagram of a process flow of a quadrilateral mesh generation process for feature line extraction provided by an exemplary embodiment of the present disclosure;

[0017] Figure 7 A schematic block diagram of modules of a feature line extraction device according to an exemplary embodiment of the present disclosure is shown;

[0018] Figure 8 A schematic diagram of the structure of an electronic device provided by an exemplary embodiment of the present disclosure;

[0019] Fig. 9 A schematic diagram of the structure of a computer system provided by an exemplary embodiment of the present disclosure. DETAILED DESCRIPTION

[0020] Embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although certain embodiments of the present disclosure are shown in the accompanying drawings, it should be understood that the present disclosure can be implemented in various forms and should not be construed as being limited to the embodiments described herein, which are instead provided for a more thorough and complete understanding of the present disclosure. It should be understood that the drawings and embodiments of the present disclosure are only for exemplary purposes and are not intended to limit the scope of protection of the present disclosure.

[0021] It should be understood that the various steps described in the method embodiments of the present disclosure may be performed in different orders and / or in parallel. In addition, the method embodiments may include additional steps and / or omit the steps shown. The scope of the present disclosure is not limited in this respect.

[0022] The term "including" and its variations used in this document are open inclusions, that is, "including but not limited to". The term "based on" means "based at least in part on". The term "one embodiment" means "at least one embodiment"; the term "another embodiment" means "at least one other embodiment"; the term "some embodiments" means "at least some embodiments". Relevant definitions of other terms will be given in the description below. It should be noted that the concepts of "first", "second", etc. mentioned in this disclosure are only used to distinguish different devices, modules or units, and are not used to limit the order or interdependence of the functions performed by these devices, modules or units.

[0023] It should be noted that the modifications of "one" and "plurality" mentioned in the present disclosure are illustrative rather than restrictive, and those skilled in the art should understand that unless otherwise clearly indicated in the context, it should be understood as "one or more".

[0024] The names of the messages or information exchanged between multiple devices in the embodiments of the present disclosure are only used for illustrative purposes and are not used to limit the scope of these messages or information.

[0025] In the process of numerical simulation, after design and 3D modeling geometry tools, it is composed of special general formats, including IGES, STEP, X_T, SAT and other data formats. In the process of structural mesh generation, there are two strategies for 3D mesh generation. One is to generate volume mesh directly without generating surface mesh (also called top-down). This method is relatively simple, but the generated volume mesh has low freedom. The other is to generate surface mesh first, and then generate volume mesh based on surface mesh (also called bottom-up). This method is more complicated, but the volume mesh can be controlled by adjusting the surface mesh, and has high freedom. The generation of surface quadrilateral mesh depends on the precise discrete points of geometric edges. The latter type is paver automatic quadrilateral mesh generation; the other type is TFI interpolation; the input is all scattered point data. How to ensure the consistency of scattered point data with geometric features has become the difficulty of surface mesh generation.

[0026] For design analysts, the degree of visualization of the scattered points of the designed data dimension discrete law is low, and three-dimensional reconstruction is required to effectively group the geometric features of the data. However, this is contradictory to the mesh generation part. In the process of structural mesh generation, continuous geometric discretization is required to interpolate better and faster. Once discretized, there are no geometric features, and the binding between geometry and nodes is gone. How to quickly and efficiently complete interpolation while retaining accurate geometric features is the main technical bottleneck of the bottom-up generation solution of structural meshes. In addition, the input of the structural surface mesh generation is discrete data, and the user needs to insert points from the geometric boundary, complete the boundary discretization, and then generate a quadrilateral mesh. The input is inconsistent with user use.

[0027] In view of the above problems, the present invention provides a feature line extraction method, which can be considered from three aspects: software data structure design, feature line extraction, and boundary projection, and provides a fast feature line extraction method, which can satisfy both user interaction and surface quadrilateral mesh generation. The present invention designs a data structure for surface quadrilateral mesh generation, which can meet the interface of the quadrilateral mesh generation program, can quickly complete the conversion from continuous geometry to discrete geometry, and can also quickly complete the scattered point data classification of the geometric boundary and construct the boundary line through feature line extraction; it can also achieve the consistency of the geometric boundary and the scattered points through the projection algorithm, and establish a complete and efficient structured mesh quadrilateral mesh generation solution.

[0028] A feature line extraction method according to an embodiment of the present disclosure will be described in detail below with reference to the accompanying drawings.

[0029] Figure 1 The following is a flow chart of a feature line extraction method provided by an exemplary embodiment of the present disclosure. Figure 1 As shown, the feature line extraction method includes:

[0030] S101, reading a geometric model file corresponding to a geometric model, and determining a mesh model corresponding to the geometric model.

[0031] In some embodiments, the data interface of various types of continuous geometries can be firstly designed by the geometry engine (product design software) to complete the reading of the geometry model, and then the triangulation of the continuous geometry can be realized based on the analysis of the geometry data.

[0032] S102, obtaining a plurality of grid lines corresponding to a plurality of grid units in the grid model, and obtaining data information of the geometric model file.

[0033] In some embodiments, the geometric model can be divided into a set of finite grid units using imaginary lines or surfaces, and the grid units are only connected at nodes, and the actions between grid units are only transmitted by nodes. When the grid units are infinitely small and the nodes are infinitely many, this discrete structure will approach the actual continuous structure, so that the conversion from continuous geometry to discrete geometry can be completed quickly.

[0034] Specifically, mesh can be used as a way of spatial discretization, where mesh is a polygonal mesh, a data structure used in computer graphics to model various irregular objects. In the facets of a polygonal mesh, a triangle facet is the smallest unit to be divided, and its representation is relatively simple, flexible, and convenient for topological description, so it is widely used, so mesh often refers to a triangle facet.

[0035] S103, generating feature lines according to the data information and the plurality of grid lines, wherein the feature lines are used to describe the shape distribution of the geometric model.

[0036] In some instances, the present invention can rely on a geometry engine design interface to read in geometry model files, and quickly complete the conversion of continuous geometry data into discrete geometry data, obtain the data information and mesh model of the geometry model file, and then generate feature lines for describing the geometric features of the geometry model based on the data information and mesh model. It can be seen that the feature line generation method adopted by the present invention is more concise and can quickly complete data conversion, thereby accurately extracting feature lines from the geometry model.

[0037] In some embodiments, the data information includes unit number information and unit coordinate information, and the method further includes: determining multiple feature points according to intersection points where multiple grid lines intersect, and determining multiple feature line segments according to the grid lines and the feature points; splicing the multiple feature line segments according to the unit number information and the unit coordinate information to obtain multiple boundary feature lines of the geometric model. It should be understood that the unit coordinate information corresponding to the grid unit can be determined according to the position of the grid unit in the grid model, and the grid units can be numbered to obtain the unit number information corresponding to the grid unit.

[0038] Specifically, the data information may be discrete text data information. In order to meet the needs of polyhedral mesh generation, only the edges and faces of the geometric model need to be analyzed. Therefore, the embodiment of the present disclosure designs a discrete data text information for storing discrete point data information and discrete point coordinate information, as well as storing the number of grid cells and the cell number information and cell coordinate information belonging to the grid cells, wherein the cell number information and the discrete point coordinate information are consistent.

[0039] In practical applications, the data information also includes discrete point data information and discrete point coordinate information, and the method also includes: determining a characteristic curve according to the data information; determining a preprocessing characteristic line corresponding to the geometric model according to the discrete point data information, the discrete point coordinate information, the boundary characteristic line and the characteristic curve. Based on this, in order to be able to express the characteristics of the geometric model, the text content of the discrete data text information is designed with discrete point coordinate information and unit coordinate information. The text of the discrete data text information stores the index of the coordinate point composed of the discrete point coordinate information and the unit coordinate information. The specific format of the discrete data text information is as shown in Table 1:

[0040] Table 1 Format of discrete data text information

[0041] Discrete point coordinate information Cell coordinate information 0 10 12 3 40 4 0 8.33171924034978 12 62 5 4 0 6.66649335064295 12 61 6 5 0 6.66649335064295 12 60 63 36 0 3.33625465114116 12 9 42 10 0 1.66926659717024 12 60 36 35 0 0 12 59 60 35 1.62241099081895 0 12 59 35 34 3.20981547156779 0 12 58 59 34 4.76384672709946 0 12 58 34 33 6.27450110279006 0 12 57 45 32 7.74314688158367 0 12 57 32 31 9.18484820617307 0 12 56 57 31

[0042] In some instances, after determining the discrete data text information, the data features of the discrete points can be decomposed and the characteristic curve can be determined at the same time; wherein the characteristic curve is composed of a series of line segments of triangular units, and the endpoint of each characteristic curve is a characteristic point or an edge of a triangle.

[0043] Specifically, feature line segments and feature points can be automatically identified based on the geometric engine design software. Feature line segments can be mesh curves on the surface of the geometric model. These curves include sharp-edged curves, intersection curves between components, high curvature contour lines such as the leading and trailing edges of blades, and open boundary lines such as symmetry surface curves. Feature points can be the intersection of three or more feature lines. Feature points can also be identified as feature points if one end of a feature line coincides with the internal point of another feature line. Feature points can be automatically identified based on the program, and the degree of the feature point is equal to the number of feature lines intersecting at the intersection point. For shear feature lines, the line ends sheared by the feature points are shear feature lines. After the feature points are identified, the feature line segments will be cut by the feature points into shear feature curves. The current technical solution for feature line segment extraction is to traverse all triangles, then determine the normals of adjacent triangles, mark two triangles with an angle greater than the given input angle value as feature line segments, and then combine all line segments to extract feature line segments.

[0044] In practical applications, for feature line extraction of discrete triangles, you can set feature line segment extraction parameters based on discrete triangles, prepare discrete data text corresponding to discrete data text information; set the control text for feature line segment extraction, including the coordinate system for feature line segment extraction, the target object file configuration input parameters for feature line segment extraction, forming the feature boundary of discrete data, the file generated after feature extraction (corner points, segmentation edges, and surfaces composed of extracted feature lines), the tolerance angle of feature line segment extraction, etc. For the geometric feature edge extraction effect, you can input discrete data text to generate plot3d format data of discrete points, plot3d format edges, plot3d format lines, and plot3d format surfaces, forming a complete set of geometric representations that convert discrete data into continuous parameter space, and generate discrete data after feature line segment extraction.

[0045] In some instances, the edges at the edges of the geometric model can also be determined as feature segments. If the angle between the normals of two internally separated quadrilaterals or triangular faces is greater than a given angle threshold, the internal edge will also be selected as a feature segment. Then, all triangles are traversed, and the normals of adjacent triangles are determined. Two triangles with an angle greater than a given input angle value are marked as feature segments. All feature segments are then combined to extract the boundary feature lines of discrete geometric data. Finally, the feature line extraction unit number information, discrete point data information, and various surface curves formed by discrete triangulation are combined to combine the surface curves and discrete points, thereby completing the geometric boundary recovery from discrete data points and forming a parameter space for feature lines, i.e., preprocessing feature lines.

[0046] In some embodiments, if there is an intersection between a feature line segment and a grid line, the feature line segment is determined to be a target feature line segment; the target feature line in the preprocessed feature line is eliminated to obtain a feature line corresponding to the geometric model.

[0047] Specifically, if the edge of the geometric model boundary is connected to other quadrilaterals or triangles, it is located on an open boundary, such as a symmetry plane, and the boundary edge is selected as a feature line segment. Then, all edges on the geometric model are traversed, and after the above conditions are judged, the feature line segments are marked, that is, the marked feature line segments are determined as target feature line segments, and finally the target feature lines in the preprocessed feature lines are eliminated to obtain the feature lines corresponding to the geometric model.

[0048] In some examples, a preset quadrilateral grid is generated based on the preprocessed feature line; a mapping relationship between the preset quadrilateral grid and the grid unit is established; and a quadrilateral grid corresponding to the feature line is generated based on the mapping relationship and the feature line, wherein the quadrilateral grid corresponds to the discrete point data information one by one.

[0049] Specifically, all edges on the geometric model can be traversed to decompose the characteristic edges of the parameter space to form a quasi-quadrilateral in the parameter space; then, the characteristic edges in the parameter space are discretized and points are arranged to form discrete coordinates in the parameter space, and a quadrilateral mesh generation method is selected to form a quadrilateral mesh in the parameter space; on this basis, the quadrilateral mesh in the parameter space is projected to ensure that the discrete triangular patch data points correspond one-to-one to the quadrilateral mesh on the same geometric surface, thereby realizing a quadrilateral mesh generation method based on feature line extraction.

[0050] In the above technical solution, the geometric key features of the complete structure of the compressor are extracted. First, the geometric features in the file are located by the fast index function, and the scattered data and feature classification are stored in temporary global variables. For example, the number of discrete data points and data are stored for the hub casing, and the number of blade sections, the number of discrete points and data are stored for the blades.

[0051] Figure 2 A schematic diagram of a structure of a blade feature line extraction method according to an exemplary embodiment of the present disclosure. Figure 2 As shown, the upper part is the geometric model of the blade, and the lower part is the characteristic line corresponding to the blade generated by the method of the embodiment of the present disclosure. Figure 3 A schematic diagram of a cylinder feature line extraction method according to an exemplary embodiment of the present disclosure. Figure 3 As shown, the upper part is the geometric model of the cylinder, and the lower part is the characteristic line corresponding to the cylinder generated by the method of the embodiment of the present disclosure.

[0052] Figure 4 A schematic diagram of a structure of discrete points on a cylindrical characteristic line provided by an exemplary embodiment of the present disclosure. Figure 4As shown, there are many discrete points on the characteristic line of the cylinder. When the distance between multiple discrete points approaches infinitesimal, the discrete structure will approach the actual geometric continuous structure.

[0053] Figure 5 A schematic diagram of a quadrilateral network structure for generating cylindrical feature lines provided by an exemplary embodiment of the present disclosure. Figure 5 As shown, you can select the characteristic line corresponding to the cylinder, that is, the parameter space corresponding to the cylinder, which is a closed area, set the quadrilateral mesh generation algorithm, generate the quadrilateral mesh of the parameter space, select the quadrilateral mesh of the parameter space and the geometric data before extraction, set the projection, project the quadrilateral mesh of the parameter space, and form a surface quadrilateral mesh consistent with the discrete geometric data on the surface of the cylinder.

[0054] Figure 6 The following is a flow chart of a process of generating a quadrilateral mesh for feature line extraction provided by an exemplary embodiment of the present disclosure. Figure 6 As shown in the figure, the quadrilateral mesh generation process for feature line extraction includes:

[0055] S601, geometric discrete triangle data preparation.

[0056] Specifically, the discrete geometry or continuous geometry data corresponding to the geometric model can be converted into spare triangular patch data, which includes the index of discrete point coordinate information and the index of unit coordinate information of each triangular unit, wherein the unit number information is consistent with the discrete point coordinate information and is consistent with the geometric coordinate point on the geometric model.

[0057] S602, feature line extraction based on discrete geometry.

[0058] Specifically, the coordinate system for feature line segment extraction, the extracted discrete file objects, the output geometric corners, points, edges, and faces, and the geometric tolerance angle can be set to generate discrete data after feature line segment extraction.

[0059] S603, parameter space characteristic line decomposition and discretization.

[0060] Specifically, the characteristic lines of the parameter space are formed according to the discrete data after the characteristic line segments are extracted, and the decomposition is completed on the characteristic lines according to the complexity of the geometric structure.

[0061] S604, closed feature line quadrilateral mesh generation.

[0062] Specifically, the decomposed characteristic edges are discretized in the parameter space to form discrete coordinate points in the parameter space.

[0063] S605, parameter space quadrilateral mesh projection.

[0064] Specifically, according to the right-hand rule, four closed sides can be selected, a quadrilateral generation method can be selected, and a quadrilateral in the parameter space can be generated.

[0065] S606, geometric quadrilateral mesh output.

[0066] Specifically, the quadrilateral in the parameter space can be projected to form a quadrilateral mesh on the object surface, and finally the mesh data in plot3d format can be output.

[0067] The main function of the present invention is to automatically extract feature lines of discrete triangular face data. Commercial software for mesh generation generally has a built-in geometry engine. The geometric topology and geometric data are derived from the CAD kernel, and there is no need to extract geometric feature lines. After the geometric model is read in, the data in the parameter space is directly used as the input data for quadrilateral face mesh generation. The geometric edges are selected, the quadrilateral mesh generation method is selected, the quadrilateral mesh generation is realized in the parameterized space, and the geometric data is bound to realize the quadrilateral mesh generation. However, in the full-link data structure process of software autonomous development, there is a lack of geometry engines. What is completed on the design side is discrete data or the program input for mesh generation is discrete triangular facets, which directly determines that when facing discrete data, feature lines need to be extracted, a new parameter space needs to be established, feature lines need to be decomposed in the parameter space, feature lines need to be discretized in the parameter space, and new projection calculations are required to ensure that the discrete geometric coordinate points designed after the quadrilateral mesh generation are completely meshed quadrilaterals can correspond one to one. In this process, the present invention solves the extraction of discrete triangular face feature lines, quadrilateral decomposition based on parameter space feature lines, parameter space calculation of feature line scatter points of triangular face, discretization of parameter space feature lines, generation of parameter space quadrilateral mesh, and projection of parameter space quadrilateral mesh on discrete triangular face.

[0068] In the case of dividing each functional module according to each function, an exemplary embodiment of the present disclosure provides a feature line extraction device. Figure 7 FIG. 2 shows a schematic block diagram of a module of a feature line extraction device according to an exemplary embodiment of the present disclosure. Figure 7 As shown, the apparatus 700 includes:

[0069] A reading module 701 is used to read a geometric model file corresponding to a geometric model and determine a mesh model corresponding to the geometric model;

[0070] An acquisition module 702 is used to acquire a plurality of grid lines corresponding to a plurality of grid units in the grid model, and acquire data information of the geometric model file;

[0071] The generating module 703 is used to generate feature lines according to the data information and the plurality of grid lines, wherein the feature lines are used to describe the shape distribution of the geometric model.

[0072] As a possible implementation manner, the data information includes unit number information and unit coordinate information, and the method further includes: determining multiple feature points based on intersection points where multiple grid lines intersect, and determining multiple feature line segments based on the grid lines and the feature points; splicing the multiple feature line segments based on the unit number information and the unit coordinate information to obtain multiple boundary feature lines of the geometric model.

[0073] As a possible implementation manner, the method further includes: determining the unit coordinate information corresponding to the grid unit according to the position of the grid unit in the grid model, and numbering the grid units to obtain the unit number information corresponding to the grid units.

[0074] As a possible implementation method, the data information also includes discrete point data information and discrete point coordinate information, and the method also includes: determining a characteristic curve based on the data information; determining a preprocessing characteristic line corresponding to the geometric model based on the discrete point data information, the discrete point coordinate information, the boundary characteristic line and the characteristic curve.

[0075] As a possible implementation manner, if the feature line segment has an intersection with the grid line, the feature line segment is determined to be a target feature line segment; the target feature line in the preprocessed feature line is eliminated to obtain a feature line corresponding to the geometric model.

[0076] As a possible implementation, a preset quadrilateral mesh is generated according to the preprocessed feature line; a mapping relationship between the preset quadrilateral mesh and mesh units is established; and a quadrilateral mesh corresponding to the feature line is generated according to the mapping relationship and the feature line.

[0077] As a possible implementation manner, the quadrilateral grid corresponds one-to-one to the discrete point data information.

[0078] An embodiment of the present disclosure also provides an electronic device, comprising: at least one processor; a memory for storing instructions executable by at least one processor; wherein the at least one processor is used to execute instructions to implement the steps of the above method disclosed in the embodiment of the present disclosure.

[0079] Figure 8 The structure diagram of an electronic device provided by an exemplary embodiment of the present disclosure is shown in FIG. Figure 8 As shown, the electronic device 800 includes at least one processor 801 and a memory 802 coupled to the processor 801 , and the processor 801 can execute corresponding steps in the above method disclosed in the embodiment of the present disclosure.

[0080] The processor 801 may also be referred to as a central processing unit (CPU), which may be an integrated circuit chip having signal processing capabilities. Each step in the method disclosed in the embodiment of the present disclosure may be completed by an integrated logic circuit of hardware in the processor 801 or by instructions in the form of software. The processor 801 may be a general-purpose processor, a digital signal processor (DSP), an ASIC, a field-programmable gate array (FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components. A general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc. The steps of the method disclosed in the embodiment of the present disclosure may be directly embodied as being executed by a hardware decoding processor, or may be executed by a combination of hardware and software modules in a decoding processor. The software module may be located in a memory 802, such as a random access memory, a flash memory, a read-only memory, a programmable read-only memory or an electrically erasable programmable memory, a register, or other mature storage media in the art. The processor 801 reads the information in the memory 802 and completes the steps of the method in combination with its hardware.

[0081] In addition, when various operations / processes according to the present disclosure are implemented by software and / or firmware, they can be transmitted from a storage medium or a network to a computer system having a dedicated hardware structure, for example, Fig. 9 The computer system 900 shown is installed with the programs constituting the software. When the various programs are installed, the computer system can execute various functions, including the functions described above. Fig. 9 A schematic diagram of the structure of a computer system provided by an exemplary embodiment of the present disclosure.

[0082] Electronic devices are intended to represent various forms of digital electronic computer devices, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. Electronic devices may also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present disclosure described and / or claimed herein.

[0083] like Fig. 9As shown, the computer system 900 includes a computing unit 901, which can perform various appropriate actions and processes according to a computer program stored in a read-only memory (ROM) 902 or a computer program loaded from a storage unit 908 into a random access memory (RAM) 903. In the RAM 903, various programs and data required for the operation of the computer system 900 can also be stored. The computing unit 901, the ROM 902, and the RAM 903 are connected to each other via a bus 904. An input / output (I / O) interface 905 is also connected to the bus 904.

[0084] A plurality of components in the computer system 900 are connected to the I / O interface 905, including: an input unit 906, an output unit 907, a storage unit 908, and a communication unit 909. The input unit 906 may be any type of device capable of inputting information to the computer system 900, and the input unit 906 may receive input digital or character information, and generate key signal inputs related to user settings and / or function control of the electronic device. The output unit 907 may be any type of device capable of presenting information, and may include, but is not limited to, a display, a speaker, a video / audio output terminal, a vibrator, and / or a printer. The storage unit 908 may include, but is not limited to, a disk, an optical disk. The communication unit 909 allows the computer system 900 to exchange information / data with other devices over a network such as the Internet, and may include, but is not limited to, a modem, a network card, an infrared communication device, a wireless communication transceiver, and / or a chipset, for example, a Bluetooth™ device, a WiFi device, a WiMax device, a cellular communication device, and / or the like.

[0085] The computing unit 901 may be a variety of general and / or special processing components with processing and computing capabilities. Some examples of the computing unit 901 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various dedicated artificial intelligence (AI) computing chips, various computing units running machine learning model algorithms, digital signal processors (DSPs), and any appropriate processors, controllers, microcontrollers, etc. The computing unit 901 performs the various methods and processes described above. For example, in some embodiments, the above methods disclosed in the embodiments of the present disclosure may be implemented as a computer software program, which is tangibly included in a machine-readable medium, such as a storage unit 908. In some embodiments, part or all of the computer program may be loaded and / or installed on an electronic device via a ROM 902 and / or a communication unit 909. In some embodiments, the computing unit 901 may be configured to perform the above methods disclosed in the embodiments of the present disclosure in any other appropriate manner (e.g., by means of firmware).

[0086] The embodiment of the present disclosure also provides a computer-readable storage medium, wherein when the instructions in the computer-readable storage medium are executed by a processor of an electronic device, the electronic device is enabled to execute the above method disclosed in the embodiment of the present disclosure.

[0087] The computer-readable storage medium in the disclosed embodiments may be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, device, or equipment. The computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices, or equipment, or any suitable combination of the foregoing. More specifically, the computer-readable storage medium may include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0088] The computer-readable medium may be included in the electronic device, or may exist independently without being incorporated into the electronic device.

[0089] The embodiments of the present disclosure also provide a computer program product, including a computer program, wherein the computer program implements the above method disclosed in the embodiments of the present disclosure when executed by a processor.

[0090] In embodiments of the present disclosure, computer program codes for performing the operations of the present disclosure may be written in one or more programming languages ​​or combinations thereof, including but not limited to object-oriented programming languages, such as Java, Smalltalk, C++, and conventional procedural programming languages, such as "C" language or similar programming languages. The program code may be executed entirely on a user's computer, partially on a user's computer, as an independent software package, partially on a user's computer, partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer via any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer.

[0091] The flow chart and block diagram in the accompanying drawings illustrate the possible architecture, function and operation of the system, method and computer program product according to various embodiments of the present disclosure. In this regard, each square box in the flow chart or block diagram can represent a module, a program segment or a part of a code, and the module, the program segment or a part of the code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some implementations as replacements, the functions marked in the square box can also occur in a sequence different from that marked in the accompanying drawings. For example, two square boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each square box in the block diagram and / or flow chart, and the combination of the square boxes in the block diagram and / or flow chart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0092] The modules, components or units involved in the embodiments described in the present disclosure may be implemented by software or hardware, wherein the names of the modules, components or units do not, in some cases, limit the modules, components or units themselves.

[0093] The functions described above herein may be performed at least in part by one or more hardware logic components. For example, without limitation, exemplary hardware logic components that may be used include: field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chip (SOCs), complex programmable logic devices (CPLDs), and the like.

[0094] The above descriptions are only some embodiments of the present disclosure and an explanation of the technical principles used. Those skilled in the art should understand that the scope of disclosure involved in the present disclosure is not limited to the technical solutions formed by a specific combination of the above technical features, but should also cover other technical solutions formed by any combination of the above technical features or their equivalent features without departing from the above disclosed concept. For example, a technical solution formed by replacing the above features with the technical features with similar functions disclosed in the present disclosure (but not limited to).

[0095] Although some specific embodiments of the present disclosure have been described in detail by way of example, it should be understood by those skilled in the art that the above examples are for illustration only and are not intended to limit the scope of the present disclosure. It should be understood by those skilled in the art that the above embodiments may be modified without departing from the scope and spirit of the present disclosure. The scope of the present disclosure is defined by the appended claims.

Claims

1. A feature line extraction method, characterized in that: include: Reading a geometric model file corresponding to the geometric model, and determining a mesh model corresponding to the geometric model; Acquire a plurality of grid lines corresponding to a plurality of grid units in the grid model, and acquire data information of the geometric model file, wherein the grid unit is a quadrilateral grid; generating feature lines according to the data information and the plurality of grid lines, wherein the feature lines are used to describe the shape distribution of the geometric model, wherein the data information includes discrete point data information and discrete point coordinate information; The data information includes unit number information and unit coordinate information, and the method further includes: Determine a plurality of feature points according to intersection points where a plurality of the grid lines intersect, and determine a plurality of feature line segments according to the grid lines and the feature points; splicing the plurality of characteristic line segments according to the unit number information and the unit coordinate information to obtain a plurality of boundary characteristic lines of the geometric model; determining a characteristic curve according to the data information; Determine a preprocessing characteristic line corresponding to the geometric model according to the discrete point data information, the discrete point coordinate information, the boundary characteristic line and the characteristic curve; Generate a preset quadrilateral grid according to the preprocessed feature lines; Establishing a mapping relationship between the preset quadrilateral grid and the grid unit; A quadrilateral mesh corresponding to the feature line is generated according to the mapping relationship and the feature line.

2. The method according to claim 1, characterized in that The method further comprises: The unit coordinate information corresponding to the grid unit is determined according to the position of the grid unit in the grid model, and the grid units are numbered to obtain the unit number information corresponding to the grid units.

3. The method according to claim 1, characterized in that The method further comprises: If the feature line segment and the grid line have an intersection, determining the feature line segment as a target feature line segment; The target feature lines in the preprocessed feature lines are eliminated to obtain the feature lines corresponding to the geometric model.

4. The method according to claim 1, characterized in that: The method further comprises: The quadrilateral grid corresponds to the discrete point data information one by one.

5. A feature line extraction device, characterized in that: include: A reading module, used for reading a geometric model file corresponding to the geometric model, and determining a mesh model corresponding to the geometric model; An acquisition module, used to acquire a plurality of grid lines corresponding to a plurality of grid units in the grid model, and to acquire data information of the geometric model file, wherein the grid unit is a quadrilateral grid; A generating module, used for generating a feature line according to the data information and the plurality of grid lines, wherein the feature line is used for describing the shape distribution of the geometric model, wherein the data information includes discrete point data information and discrete point coordinate information; The data information includes unit number information and unit coordinate information, and the device is further used for: Determine a plurality of feature points according to intersection points where a plurality of the grid lines intersect, and determine a plurality of feature line segments according to the grid lines and the feature points; splicing the plurality of characteristic line segments according to the unit number information and the unit coordinate information to obtain a plurality of boundary characteristic lines of the geometric model; determining a characteristic curve according to the data information; Determine a preprocessing characteristic line corresponding to the geometric model according to the discrete point data information, the discrete point coordinate information, the boundary characteristic line and the characteristic curve; Generate a preset quadrilateral grid according to the preprocessed feature lines; Establishing a mapping relationship between the preset quadrilateral grid and the grid unit; A quadrilateral mesh corresponding to the feature line is generated according to the mapping relationship and the feature line.

6. An electronic device, characterized in that: include: at least one processor; a memory for storing the at least one processor-executable instruction; The at least one processor is configured to execute the instructions to implement the method as claimed in any one of claims 1 to 4.

7. A computer-readable storage medium, characterized in that: When the instructions in the computer-readable storage medium are executed by a processor of an electronic device, the electronic device is enabled to perform the method as claimed in any one of claims 1 to 4.

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