Geometric model feature recognition method and device, equipment and storage medium

Abstract

The invention discloses a geometric model feature recognition method and device, equipment and a storage medium, and relates to the technical field of CAE, and the method comprises the steps: obtaining a surface set of a geometric model; traversing the surface set, and obtaining a target surface from the surface set; judging whether the target surface is a shell surface of a hole or not; and if yes, identifying and obtaining hole features based on the concave-convex relation between the shell surface and the adjacent surface. The hole identification speed of the three-dimensional model can be improved.

Description

Technical Field

[0001] The present application relates to the field of CAE technology, and in particular to a method, device, equipment and storage medium for geometric model feature recognition. Background Art

[0002] Feature recognition of CAE (Computer-Aided Engineering) models involves computer graphics, computational geometry and CAE simulation, and is one of the important processes in CAE simulation pre-processing. Identification and removal of three-dimensional holes in geometric models is a very frequently used function in CAE pre-processing. By removing complex circular holes in geometric models, the complexity of generated meshes can be reduced, the quality of regional meshes can be improved, and the simulation calculation process can be accelerated. The geometric models imported into CAE software cannot identify modeling features due to the loss of the parametric modeling process. How to accurately and quickly identify three-dimensional holes in geometric models has become one of the important ability evaluation criteria for CAE pre-processing software.

[0003] The current CAE pre-processing software still has the problem of slow recognition of three-dimensional holes in geometric models.

[0004] The above contents are only used to assist in understanding the technical solution of the present application and do not constitute an admission that the above contents are prior art. Summary of the invention

[0005] The main purpose of this application is to provide a method, device, equipment and storage medium for geometric model feature recognition, aiming to solve the technical problem that the current CAE pre-processing software still has slow geometric model three-dimensional hole recognition speed.

[0006] To achieve the above objectives, the present application proposes a method for geometric model feature recognition, the method comprising:

[0007] Get the face set of the geometric model;

[0008] Traversing the face set, and acquiring a target face from the face set;

[0009] Determining whether the target surface is a shell surface of a hole;

[0010] If so, the hole feature is identified based on the concave-convex relationship between the shell surface and the adjacent surface.

[0011] In one embodiment, the step of determining whether the target surface is a shell surface of a hole comprises:

[0012] Searching whether there is a ring edge on the target surface;

[0013] If it exists, the surface connected to the target surface through the ring edge is recorded as the ring edge adjacent surface, and the shell surface of the hole is identified based on the concavity and convexity of the ring edge adjacent surface.

[0014] In one embodiment, the step of identifying and obtaining hole features based on the concavity-convexity relationship of the shell surface includes:

[0015] According to the concave-convex connection relationship, the transition surface and the bottom surface of the hole are obtained by searching the adjacent surface of the shell surface of the hole;

[0016] The shell surface, transition surface and bottom surface of the hole are combined to obtain the hole feature.

[0017] In one embodiment, the step of searching whether the target surface has a ring edge comprises:

[0018] Detecting whether there is a hole between the target surface and the adjacent surface;

[0019] If it exists, a graph search algorithm is used to check whether a ring edge can be formed between the target face and the adjacent face.

[0020] In one embodiment, the graph search algorithm includes a depth-first search algorithm, and the step of checking whether a ring edge can be formed between the target face and the adjacent face by the graph search algorithm includes:

[0021] Select an edge of the target surface and record it as an initial edge;

[0022] Detecting whether the initial edge has a tangent adjacent edge;

[0023] If it exists, a recursive search is performed on the tangent adjacent edges until the initial edge is found or the accumulated edge lengths exceed a preset threshold.

[0024] In one embodiment, the step of identifying the shell surface of the hole according to the concavity and convexity of the adjacent surface of the ring edge comprises:

[0025] Obtaining the starting point and the ending point of the loop edge;

[0026] Calculating a ring direction vector from the start point to the end point based on the start point position and the end point position of the ring edge;

[0027] Calculate and obtain the normal vector of the adjacent face of the ring edge at the starting point;

[0028] Calculate the dot product of the normal vector of the adjacent face of the ring edge at the starting point and the ring direction vector;

[0029] If the dot product result is a positive number, the adjacent face of the ring edge is the shell face of the hole.

[0030] In one embodiment, the step of searching for the transition surface and the bottom surface of the hole based on the shell surface of the hole and the adjacent surface according to the concave-convex connection relationship comprises:

[0031] Search and obtain the adjacent surface of the shell surface;

[0032] Based on the concave dihedral angle relationship, the transition surface and the bottom surface of the hole are identified from the adjacent surfaces of the shell surface.

[0033] In addition, to achieve the above purpose, the present application also proposes a geometric model feature recognition device, the geometric model feature recognition device comprising:

[0034] A data acquisition module, used to acquire a face set of a geometric model;

[0035] A data traversal module, used for traversing the face set and obtaining a target face from the face set;

[0036] A shell surface judgment module, used to judge whether the target surface is the shell surface of the hole;

[0037] The feature recognition module is used to identify and obtain hole features based on the concavity-convexity relationship between the shell surface and the adjacent surface if the target surface is the shell surface of the hole.

[0038] In addition, to achieve the above-mentioned purpose, the present application also proposes a geometric model feature recognition device, which includes: a memory, a processor, and a computer program stored in the memory and executable on the processor, and the computer program is configured to implement the steps of the geometric model feature recognition method described above.

[0039] In addition, to achieve the above-mentioned purpose, the present application also proposes a storage medium, which is a computer-readable storage medium, and a computer program is stored on the storage medium. When the computer program is executed by the processor, the steps of the geometric model feature recognition method described above are implemented.

[0040] One or more technical solutions proposed in this application have at least the following technical effects:

[0041] The present application identifies hole features based on the concave-convex relationship of the shell surface, which does not require the calculation of analytical equations of the geometric surface, nor does it require topological information of the entire geometric model, thereby greatly speeding up the process of identifying three-dimensional holes. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0043] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0044] Figure 1 Schematic diagram of various types of complex holes;

[0045] Figure 2 It is a schematic diagram of complex hole composition;

[0046] Figure 3 A schematic diagram of a flow chart provided for the first embodiment of the geometric model feature recognition method of the present application;

[0047] Figure 4 This is an example of the result of feature recognition in the embodiments of the present application;

[0048] Figure 5 A schematic diagram of the geometric model feature recognition method of the present application for judging the support surface and the shell surface of the hole according to the concavity and convexity;

[0049] Figure 6 Flowchart for real-time feature recognition for this application;

[0050] Figure 7 This is a schematic diagram of the module structure of the geometric model feature recognition device according to an embodiment of the present application;

[0051] Figure 8 Schematic diagram of the device structure of the hardware operating environment involved in the feature recognition method in the embodiment of the present application.

[0052] The purpose, features and advantages of this application will be further described in conjunction with the embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0053] It should be understood that the specific embodiments described herein are only used to explain the technical solutions of the present application and are not used to limit the present application.

[0054] In order to better understand the technical solution of the present application, a detailed description will be given below in conjunction with the accompanying drawings and specific implementation methods.

[0055] In this embodiment, for ease of description, the feature recognition system is used as the execution subject for explanation below.

[0056] The current CAE pre-processing software still has the problem of slow recognition speed.

[0057] To this end, the present application provides a solution, which identifies hole features based on the concave-convex relationship of the shell surface. It does not require analytical equations for calculating geometric surfaces, nor does it require topological information of the entire geometric model, thereby greatly speeding up the process of identifying three-dimensional holes.

[0058] The main solution of the embodiment of the present application is: obtain a face set of a geometric model; traverse the face set and obtain a target face from the face set; determine whether the target face is a shell face of a hole; if so, identify the hole feature based on the convexity and concavity relationship between the shell face and the adjacent face.

[0059] It should be noted that the executor of this embodiment can be a computing service device with data processing, network communication and program running functions, such as a tablet computer, a personal computer, a mobile phone, etc., or an electronic device, a feature recognition device, etc. that can realize the above functions, or an electronic system, a feature recognition system, etc. that can realize the above functions. The following takes the feature recognition system as an example to illustrate this embodiment and the following embodiments.

[0060] In the pre-processing of Computer Aided Engineering (CAE), it is crucial to identify and process the complex holes in the geometric model.

[0061] Reference Figure 1 , Figure 1 Schematic diagram of various types of complex holes, where the hole templates include simple holes, countersunk holes, stepped holes, drilled holes, tapered holes, hole chains, etc.

[0062] It should be noted that 3D holes are often used for fastening connections between different parts in CAD design. Therefore, common 3D holes in geometric models usually have the following four characteristics:

[0063] 1. A three-dimensional hole will have a periodic side surface that is connected end to end.

[0064] 2. For multi-layer complex holes, the radius of the circular holes generally decreases from top to bottom.

[0065] 3. Conventional drilling, such as countersunk holes and stepped holes, has coaxial components.

[0066] 4. Common circular hole surfaces are usually cylindrical or conical surfaces.

[0067] Among them, you can refer to Figure 2 , Figure 2 This is a schematic diagram of the composition of a complex hole. It should be noted that the components of the complex hole include at least one or more of a supporting surface, a transition surface, a shell surface and a bottom surface.

[0068] The following explains the support surface, transition surface, shell surface and bottom surface:

[0069] Support face: refers to the plane where the hole is located;

[0070] Shell face: the inside surface of a hole;

[0071] Intermediate face: the transition surface between shell surfaces;

[0072] End face: The face at the bottom of a blind hole.

[0073] Foreign CAE pre-processing software (such as HyperMesh and ANSA) all have the function of identifying rounded corners and three-dimensional circular holes, while domestic CAE pre-processing software is almost blank in this field. Even the industry-leading CAE pre-processing software HyperMesh still has problems such as inaccurate recognition and slow recognition speed for large models.

[0074] Based on this, the present application embodiment provides a geometric model feature recognition method, referring to Figure 3 , Figure 3 A schematic diagram of the flow chart provided for the first embodiment of the geometric model feature recognition method of the present application.

[0075] In this embodiment, the geometric model feature recognition method includes steps S10 to S40:

[0076] Step S10, obtaining a face set of a geometric model;

[0077] Among them, the geometric model can be first imported from a file or a database. The geometric model can come from the CAE pre-processing software and include various geometric features and detailed information.

[0078] Then, all faces in the geometric model are extracted to obtain a face set of the geometric model.

[0079] Step S20, traversing the face set, and obtaining a target face from the face set;

[0080] Step S30, determining whether the target surface is a shell surface of a hole;

[0081] Among them, a target face can be obtained from the face set, and it is searched whether the target face has a ring edge. If so, the face connected to the target face through the ring edge is recorded as the ring edge adjacent face, and the shell face of the hole is identified based on the concavity and convexity of the ring edge adjacent face.

[0082] Step S40: If yes, the hole feature is identified based on the concave-convex relationship between the shell surface and the adjacent surface.

[0083] Among them, according to the concave-convex connection relationship, the transition surface and the bottom surface of the hole can be searched based on the shell surface of the hole and the adjacent surface, and the shell surface, transition surface and bottom surface of the hole can be combined to obtain the hole feature.

[0084] Reference Figure 4 , Figure 4 This is an example of the result of feature recognition in the embodiment of the present application, wherein the blue highlighted part is the result of feature recognition.

[0085] This embodiment provides a method for identifying geometric model features. This application identifies hole features based on the concave-convex relationship of the shell surface. It does not require the calculation of analytical equations for the geometric surface, nor does it require the topological information of the entire geometric model, thereby greatly speeding up the process of identifying three-dimensional holes. In addition, this embodiment provides a method for quickly identifying three-dimensional hole features for CAE geometric models based on the periodic topological structure and geometric concave-convex relationship of three-dimensional circular holes. It can quickly identify hole features in the geometric model through parameter control, and even more complex holes, such as countersunk holes, countersunk holes, tapered holes, stepped holes, and other complex holes can still be identified very accurately.

[0086] Based on the first embodiment of the present application, in the second embodiment of the present application, the same or similar contents as those in the first embodiment can be referred to the above description, and will not be repeated in the following. On this basis, step S30, judging whether the target surface is the shell surface of the hole, also includes steps S31 to S32:

[0087] Step S31, searching whether the target surface has a ring edge;

[0088] A search operation is performed on the boundary of the target face to determine whether there is an edge ring. An edge ring generally refers to a closed ring structure formed by a face boundary.

[0089] Step S32: if it exists, the surface connected to the target surface through the ring edge is recorded as the ring edge adjacent surface, and the shell surface of the hole is identified according to the concavity and convexity of the ring edge adjacent surface.

[0090] Among them, all faces connected to the ring edge are determined and recorded, and these faces are the ring edge adjacent faces.

[0091] Then, the concavity of each edge-adjacent face is analyzed to check the geometric relationship of these faces relative to the edge. Based on the concavity analysis results, the shell faces of the hole are identified. The shell faces are the outer peripheral faces of the hole and have specific geometric characteristics and shapes.

[0092] This embodiment provides a rapid identification method for three-dimensional hole features of CAE geometric models based on the relationship between the periodic topological structure and geometric concavity of three-dimensional circular holes. The method can quickly identify the hole features in the geometric model through parameter control. Even more complex holes, such as countersunk holes, countersunk holes, tapered holes, step holes, etc., can still be identified very accurately.

[0093] Based on the first embodiment of the present application, in the third embodiment of the present application, the same or similar contents as those in the first embodiment can be referred to the above description, and will not be repeated in the following. On this basis, step S40, based on the concave-convex relationship of the shell surface, identifies the hole features, including steps S41 to S42:

[0094] Step S41, searching for the transition surface and bottom surface of the hole based on the shell surface of the hole and the adjacent surface according to the concave-convex connection relationship;

[0095] In this process, based on the shell surface of the hole, a surface connected to the shell surface and having transition properties is searched. The transition surface is the middle layer between the shell surface of the hole and the bottom surface of the hole.

[0096] Then, find the bottom face of the hole, which is usually the deepest part of the hole with a noticeable depth difference from the shell face of the hole.

[0097] Step S42, combining the shell surface, transition surface and bottom surface of the hole to obtain the hole feature.

[0098] The previously identified shell faces, transition faces, and bottom faces are combined to form a complete hole feature. The combination process involves bringing all relevant faces together to ensure their correct connection in the geometry model.

[0099] This embodiment provides a rapid identification method for three-dimensional hole features of CAE geometric models based on the relationship between the periodic topological structure and geometric concavity of three-dimensional circular holes. The method can quickly identify the hole features in the geometric model through parameter control. Even more complex holes, such as countersunk holes, countersunk holes, tapered holes, step holes, etc., can still be identified very accurately.

[0100] Based on the second embodiment of the present application, in the fourth embodiment of the present application, the same or similar contents as those in the second embodiment can be referred to the above description, and will not be repeated in the following. On this basis, step S31, searching whether the target surface has a ring edge also includes steps S311 to S312:

[0101] Step S311, detecting whether there is a hole between the target surface and the adjacent surface;

[0102] Step S312: If it exists, check whether a ring edge can be formed between the target face and the adjacent face through a graph search algorithm.

[0103] Among them, the graph search algorithm may include depth-first search, breadth-first search, graph traversal algorithm (such as Dijkstra or A* algorithm) or connected component analysis method, etc.

[0104] Taking depth-first search as an example, the steps of checking whether a ring edge can be formed between the target surface and the adjacent surface are as follows: selecting an edge of the target surface, recorded as an initial edge, and detecting whether there is a tangent adjacent edge to the initial edge; if so, recursively searching the tangent adjacent edges until the initial edge is found or the accumulated number of edge lengths exceeds a preset threshold.

[0105] This embodiment can accurately identify the existence of holes by detecting whether there are holes between the target surface and the adjacent surface, thereby ensuring that important geometric features are not missed during the design or analysis process. In addition, this embodiment uses a graph search algorithm to check whether the target surface and the adjacent surface can form a ring edge, which can effectively identify the ring edge relationship in complex geometric structures and improve the understanding and processing capabilities of hole structures.

[0106] Based on the fourth embodiment of the present application, in the fifth embodiment of the present application, the same or similar contents as those in the fourth embodiment can be referred to the above description, and will not be described in detail later. On this basis, the graph search algorithm includes a depth-first search algorithm, and step S312, through the graph search algorithm, checks whether the target face and the adjacent face can form a ring edge, and also includes steps S3121 to S3123:

[0107] Step S3121, selecting an edge of the target surface and recording it as an initial edge;

[0108] Step S3122, detecting whether the initial edge has a tangent adjacent edge;

[0109] Step S3123: If it exists, recursively search the adjacent tangent edges until the initial edge is found or the accumulated edge lengths exceed a preset threshold.

[0110] First, an edge is selected from the target surface, recorded as the initial edge, and whether the initial edge has a tangent adjacent edge is detected. If so, a recursive search is performed on the tangent adjacent edge, that is, whether the tangent adjacent edge has another tangent adjacent edge. If so, the recursive search continues until the initial edge is found, or the cumulative number of edge lengths exceeds a preset threshold, then it is considered that a ring edge can be formed between the target surface and the adjacent surface.

[0111] This embodiment can ensure complete identification of all boundaries of the target surface and avoid omissions by recursively searching for tangent adjacent edges.

[0112] Based on the second embodiment of the present application, in the sixth embodiment of the present application, the same or similar contents as those in the second embodiment can be referred to the above description, and will not be described in detail later. On this basis, step S32, according to the concavity and convexity of the adjacent surface of the ring edge, identifies the shell surface of the hole and also includes steps S321 to S325:

[0113] Step S321, obtaining the starting position and the ending position of the loop edge;

[0114] Step S322, calculating a ring direction vector from the start point to the end point based on the start point position and the end point position of the ring edge;

[0115] Reference Figure 5 , Figure 5 This is a schematic diagram of the geometric model feature recognition method of the present application for judging the support surface and the shell surface of the hole based on the concavity and convexity.

[0116] exist Figure 5 In the example, the counterclockwise outer ring can be used as the ring edge to calculate the ring direction vector V1.

[0117] Step S323, calculating and obtaining the normal vector of the adjacent surface of the ring edge at the starting point;

[0118] Wherein, the normal vector of the adjacent surface of the ring edge at the starting point is assumed to be V2.

[0119] Step S324, calculating the dot product of the normal vector of the adjacent face of the ring edge at the starting point and the ring direction vector;

[0120] Step S325: If the dot product result is a positive number, the adjacent face of the ring edge is the shell face of the hole.

[0121] The dot product result reflects the angle relationship between the two vectors. If the result is positive, it means that the angle between the two vectors is less than 90 degrees; if it is zero, it means that the angle between the two vectors is 90 degrees, and the adjacent face of the ring edge is the supporting face of the hole.

[0122] This embodiment calculates the dot product result of the normal vector of the adjacent face of the ring edge at the starting point position and the ring direction vector, and can use the dot product result to determine whether the adjacent face of the ring edge is the shell face of the hole, thereby improving the recognition speed of the three-dimensional hole feature.

[0123] Based on the third embodiment of the present application, in the seventh embodiment of the present application, the same or similar contents as those in the third embodiment can be referred to the above description, and will not be described in detail later. On this basis, step S41, based on the concave-convex connection relationship, searches for the transition surface and bottom surface of the hole based on the adjacent surface of the shell surface of the hole also include steps S411 to S412:

[0124] Step S411, searching and obtaining the adjacent surface of the shell surface;

[0125] Step S412, based on the concave dihedral angle relationship, identifying the transition surface and the bottom surface of the hole from the adjacent surfaces of the shell surface.

[0126] It should be noted that the hole transition surface and the hole bottom surface can be quickly identified based on the concave dihedral angle relationship between the surfaces.

[0127] Among them, the dihedral angle between the hole support surface and the hole shell surface must be greater than 180°, while the dihedral angles between the hole transition surface and the hole bottom surface and the hole shell surface are less than 180°.

[0128] This embodiment searches for all adjacent faces of the hole shell surface, and then identifies all transition faces and bottom faces adjacent to the shell surface through the dihedral angle relationship, thereby identifying the features of the entire hole.

[0129] Reference Figure 6 , Figure 6 Flowchart for real-time feature recognition for this application.

[0130] like Figure 6 As shown, the process of real-time feature recognition in this application includes the following five steps:

[0131] Step S01, obtain the face set of the geometric body and traverse all faces.

[0132] Step S02, check each face to see if there is a loop edge. Specifically, it can be detected whether there is a hole between the target face and the adjacent face. If there is, a graph search algorithm is used to check whether the target face and the adjacent face can form a loop edge.

[0133] Step S03, identifying the shell surface of the hole according to the concavity of the adjacent surface of the ring edge. Specifically, the starting position and the end position of the ring edge can be obtained; the ring direction vector from the starting point to the end point is calculated based on the starting position and the end position of the ring edge; the normal vector of the adjacent surface of the ring edge at the starting position is calculated; the dot product result of the normal vector of the adjacent surface of the ring edge at the starting position and the ring direction vector is calculated; if the dot product result is a positive number, the adjacent surface of the ring edge is the shell surface of the hole.

[0134] Step S04, identifying the transition surface and bottom surface connected to the hole surface according to the concavity and convexity. Specifically, the hole transition surface and the hole bottom surface can be quickly identified according to the dihedral angle relationship between the surfaces. The dihedral angle between the hole support surface and the hole shell surface must be greater than 180°, while the dihedral angle between the hole transition surface and the hole bottom surface and the hole shell surface is less than 180°.

[0135] Step S05, outputting the identified three-dimensional hole features. Specifically, the shell surface, transition surface and bottom surface of the hole may be combined to obtain and output the three-dimensional hole features.

[0136] It should be noted that the above examples are only used to understand the present application and do not constitute a limitation on the geometric model feature recognition method of the present application. More simple transformations based on this technical concept are all within the scope of protection of the present application.

[0137] This application also provides a geometric model feature recognition device, please refer to Figure 7 , the feature recognition device comprises:

[0138] A data acquisition module 10 is used to acquire a face set of a geometric model;

[0139] A data traversal module 20, used for traversing the face set and obtaining a target face from the face set;

[0140] A shell surface judgment module 30, used to judge whether the target surface is a shell surface of a hole;

[0141] The feature recognition module 40 is used to identify and obtain hole features based on the concavity-convexity relationship between the shell surface and the adjacent surface if the target surface is the shell surface of the hole.

[0142] The geometric model feature recognition device provided by the present application adopts the geometric model feature recognition method in the above embodiment, which can solve the technical problem that the current CAE pre-processing software still has a slow recognition speed. Compared with the prior art, the beneficial effects of the geometric model feature recognition device provided by the present application are the same as the beneficial effects of the geometric model feature recognition method provided by the above embodiment, and other technical features in the geometric model feature recognition device are the same as the features disclosed in the above embodiment method, which will not be repeated here.

[0143] The present application provides a geometric model feature recognition device, which includes: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the feature recognition method in the above-mentioned embodiment one.

[0144] Reference below Figure 8, which shows a schematic diagram of the structure of a feature recognition device suitable for implementing the embodiment of the present application. The feature recognition device in the embodiment of the present application may include but is not limited to mobile terminals such as mobile phones, laptop computers, digital broadcast receivers, PDAs (Personal Digital Assistants), PADs (Portable Application Descriptions), PMPs (Portable Media Players), vehicle-mounted terminals (such as vehicle-mounted navigation terminals), etc., and fixed terminals such as digital TVs, desktop computers, etc. Figure 8 The feature recognition device shown is merely an example and should not bring any limitation to the functions and scope of use of the embodiments of the present application.

[0145] like Figure 8 As shown, the feature recognition device may include a processing device 1001 (e.g., a central processing unit, a graphics processor, etc.), which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM: Read Only Memory) 1002 or a program loaded from a storage device 1003 to a random access memory (RAM: Random Access Memory) 1004. In RAM1004, various programs and data required for the operation of the feature recognition device are also stored. The processing device 1001, ROM1002, and RAM1004 are connected to each other through a bus 1005. An input / output (I / O) interface 1006 is also connected to the bus. Generally, the following systems can be connected to the I / O interface 1006: an input device 1007 including, for example, a touch screen, a touch pad, a keyboard, a mouse, an image sensor, a microphone, an accelerometer, a gyroscope, etc.; an output device 1008 including, for example, a liquid crystal display (LCD: Liquid Crystal Display), a speaker, a vibrator, etc.; a storage device 1003 including, for example, a magnetic tape, a hard disk, etc.; and a communication device 1009. The communication device 1009 can allow the feature recognition device to communicate with other devices wirelessly or by wire to exchange data. Although the feature recognition device with various systems is shown in the figure, it should be understood that it is not required to implement or have all the systems shown. More or fewer systems can be implemented or have alternatively.

[0146] In particular, according to the embodiments disclosed in the present application, the process described above with reference to the flowchart can be implemented as a computer software program. For example, the embodiments disclosed in the present application include a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program includes a program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network through a communication device, or installed from a storage device 1003, or installed from a ROM 1002. When the computer program is executed by the processing device 1001, the above-mentioned functions defined in the method of the embodiment disclosed in the present application are executed.

[0147] The geometric model feature recognition device provided by the present application adopts the feature recognition method in the above embodiment, which can solve the technical problem that the current CAE pre-processing software still has a slow recognition speed. Compared with the prior art, the beneficial effects of the feature recognition device provided by the present application are the same as the beneficial effects of the feature recognition method provided by the above embodiment, and other technical features in the feature recognition device are the same as the features disclosed in the method of the previous embodiment, which will not be repeated here.

[0148] It should be understood that the various parts disclosed in this application can be implemented by hardware, software, firmware or a combination thereof. In the description of the above embodiments, specific features, structures, materials or characteristics can be combined in any one or more embodiments or examples in a suitable manner.

[0149] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

[0150] The present application provides a computer-readable storage medium having computer-readable program instructions (ie, computer programs) stored thereon, wherein the computer-readable program instructions are used to execute the geometric model feature recognition method in the above-mentioned embodiment.

[0151] The computer-readable storage medium provided in the present application may be, for example, a USB flash drive, but is not limited to electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, systems or devices, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, 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 above. In this embodiment, the computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in combination with an instruction execution system, system or device. The program code contained on the computer-readable storage medium may be transmitted using any appropriate medium, including but not limited to: wires, optical cables, RF (Radio Frequency), etc., or any suitable combination of the above.

[0152] The computer-readable storage medium may be included in the feature recognition device; or may exist independently without being assembled into the geometric model feature recognition device.

[0153] The above-mentioned computer-readable storage medium carries one or more programs. When the above-mentioned one or more programs are executed by the feature recognition device, the geometric model feature recognition device: obtains a face set of the geometric model; traverses the face set and obtains a target face from the face set; determines whether the target face is a shell face of a hole; if so, obtains the hole feature based on the convexity and concavity relationship between the shell face and the adjacent face.

[0154] Computer program code for performing the operations of the present application may be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, C++, and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a separate software package, partially on the user's computer and 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 through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0155] 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 application. 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 alternative implementations, 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.

[0156] The modules involved in the embodiments described in this application may be implemented by software or hardware, wherein the name of the module does not constitute a limitation on the unit itself in some cases.

[0157] The readable storage medium provided by the present application is a computer-readable storage medium, which stores computer-readable program instructions (i.e., computer programs) for executing the above-mentioned feature recognition method, and can solve the technical problem that the current CAE pre-processing software still has a slow recognition speed. Compared with the prior art, the beneficial effects of the computer-readable storage medium provided by the present application are the same as the beneficial effects of the feature recognition method provided by the above-mentioned embodiment, and will not be repeated here.

[0158] The above descriptions are only some embodiments of the present application, and are not intended to limit the patent scope of the present application. All equivalent structural changes made using the contents of the present application specification and drawings under the technical concept of the present application, or direct / indirect applications in other related technical fields are included in the patent protection scope of the present application.

Claims

1. A geometric model feature recognition method, characterized in that: The method comprises: Get the face set of the geometric model; Traversing the face set, and acquiring a target face from the face set; Determining whether the target surface is a shell surface of a hole; If so, the hole feature is identified based on the concave-convex relationship between the shell surface and the adjacent surface.

2. The method according to claim 1, characterized in that The step of determining whether the target surface is a shell surface of a hole comprises: Searching whether there is a ring edge on the target surface; If it exists, the surface connected to the target surface through the ring edge is recorded as the ring edge adjacent surface, and the shell surface of the hole is identified based on the concavity and convexity of the ring edge adjacent surface.

3. The method according to claim 1, characterized in that The step of identifying and obtaining hole features based on the concave-convex relationship of the shell surface comprises: According to the concave-convex connection relationship, the transition surface and the bottom surface of the hole are obtained by searching the adjacent surface of the shell surface of the hole; The shell surface, transition surface and bottom surface of the hole are combined to obtain the hole feature.

4. The method according to claim 2, characterized in that The step of searching whether the target surface has a ring edge comprises: Detecting whether there is a hole between the target surface and the adjacent surface; If it exists, a graph search algorithm is used to check whether a ring edge can be formed between the target face and the adjacent face.

5. The method according to claim 4, characterized in that The graph search algorithm includes a depth-first search algorithm. The step of checking whether a ring edge can be formed between the target face and the adjacent face by using the graph search algorithm includes: Select an edge of the target surface and record it as an initial edge; Detecting whether the initial edge has a tangent adjacent edge; If it exists, a recursive search is performed on the tangent adjacent edges until the initial edge is found or the accumulated edge lengths exceed a preset threshold.

6. The method according to claim 2, characterized in that The step of identifying the shell surface of the hole according to the concavity and convexity of the adjacent surface of the ring edge comprises: Obtaining the starting point and the ending point of the loop edge; Calculating a ring direction vector from the start point to the end point based on the start point position and the end point position of the ring edge; Calculate and obtain the normal vector of the adjacent face of the ring edge at the starting point; Calculate the dot product of the normal vector of the adjacent face of the ring edge at the starting point and the ring direction vector; If the dot product result is a positive number, the adjacent face of the ring edge is the shell face of the hole.

7. The method according to claim 3, characterized in that The step of searching for the transition surface and the bottom surface of the hole based on the shell surface of the hole and the adjacent surface according to the concave-convex connection relationship comprises: Search and obtain the adjacent surface of the shell surface; Based on the concave dihedral angle relationship, the transition surface and the bottom surface of the hole are identified from the adjacent surfaces of the shell surface.

8. A geometric model feature recognition device, characterized in that: The device comprises: A data acquisition module, used to acquire a face set of a geometric model; A data traversal module, used for traversing the face set and obtaining a target face from the face set; A shell surface judgment module, used to judge whether the target surface is the shell surface of the hole; The feature recognition module is used to identify and obtain hole features based on the concavity-convexity relationship between the shell surface and the adjacent surface if the target surface is the shell surface of the hole.

9. A geometric model feature recognition device, characterized in that: The device comprises: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the computer program is configured to implement the steps of the geometric model feature recognition method according to any one of claims 1 to 7.

10. A storage medium, characterized in that: The storage medium is a computer-readable storage medium, and a computer program is stored on the storage medium. When the computer program is executed by a processor, the steps of the geometric model feature recognition method according to any one of claims 1 to 7 are implemented.

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