Aircraft typical structure online identification method and system based on finite element model

Abstract

The invention discloses an airplane typical structure online identification method and system based on a finite element model. The method comprises the following steps: S1, importing and analyzing data; step S2, identification and classification; and S3, loading and rendering. According to the method, automatic identification and careful classification of the typical structure of the aircraft are realized, the efficiency and accuracy of aircraft structure analysis are greatly improved through three-dimensional visual display and interactive operation, and the method has the advantages of improving the aircraft structure analysis efficiency, improving the identification precision and reliability, enhancing the interactivity and flexibility and adapting to diversified engineering requirements.

Description

Technical Field

[0001] The present invention relates to the field of aerospace technology, and in particular, to an online identification method and system for typical aircraft structures based on a finite element model. Background Art

[0002] In existing commercial strength analysis software, there is a lack of a function for identifying and displaying typical structures of a finite element model. After importing the finite element model of a large aircraft, engineers need to manually subdivide and identify the structures in the section. This process is not only time-consuming and laborious but also error-prone, seriously affecting the efficiency of design and analysis.

[0003] For complex aircraft structures (such as wings, tails, etc.), their geometric shapes and topological relationships are complex, and traditional manual identification methods are difficult to accurately distinguish different types of structural units. Especially in areas with high curvature or complex connection relationships, the difficulty of manual identification further increases, resulting in insufficient identification accuracy and reliability, which may affect the accuracy of subsequent strength analysis and the safety of design.

[0004] In the prior art, the structure identification process is mostly static and lacks interactivity. Engineers cannot quickly select and display target structural units through an intuitive three-dimensional view, nor can they dynamically correct the identification results. This not only reduces the user experience but also limits the flexibility of analysis work. At the same time, existing methods are usually optimized for specific types of structures or models and lack generality. For different types of aircraft structures, the identification strategy needs to be readjusted, making it difficult to meet diverse engineering requirements.

[0005] In actual engineering, the design and analysis of aircraft structures are a dynamic process and may need to be adjusted according to different design stages or analysis requirements. However, existing methods lack dynamic adaptability and are difficult to meet such flexible adjustment requirements.

[0006] In addition, since there is no information related to business names stored in the model units, it is necessary to automatically identify the units online so as to divide the units according to business scenarios, thereby improving the usage efficiency.

[0007] In view of the above problems, the prior art urgently needs to be improved. Summary of the Invention

[0008] To solve at least one of the problems existing in the prior art described above, a first aspect of the present invention provides an online identification method for typical aircraft structures based on a finite element model, wherein the typical aircraft structures at least include one of the following: wing structure, tail structure, fuselage structure, landing gear structure;

[0009] The online identification method for typical aircraft structures includes the following steps:

[0010] Step S1: Data import and parsing; wherein, the original data file of the finite element model is imported into the system and the structural unit information of the finite element model is extracted; the structural unit information includes at least one of the following: element number, node coordinates, element type, connection relationship;

[0011] Step S2: Identification and classification; wherein, the typical structural units of the finite element model are classified according to structural characteristics and stored in a non-relational cloud database;

[0012] Step S3: Loading and rendering; wherein, the classified structural unit data is loaded into a 3D visualization component to form a visualized 3D model for front-end rendering, completing the classified display of views; and, after clicking on the typical structural points of the aircraft in the view, all subordinate structural units can be selected.

[0013] In the online identification method for typical aircraft structures based on a finite element model as described above, optionally, step S1 specifically includes the following steps:

[0014] Step S1.1: Upload the finite element model to the system in the form of a bdf file;

[0015] Step S1.2: Parse the bdf file and extract the structural unit information of the finite element model.

[0016] In the online identification method for typical aircraft structures based on a finite element model as described above, optionally, step S2 specifically includes the following steps:

[0017] Step S2.1: Determine and select different aircraft sections according to the first character of the element number in the finite element model;

[0018] Step S2.2: Classify the two-dimensional elements within the selected section into different typical structural units;

[0019] Step S2.3: Identify and classify one-dimensional elements according to the connection form between the typical structural units.

[0020] In the online identification method for typical aircraft structures based on a finite element model as described above, optionally, in step S2.2, calculate the normal vector of the two-dimensional element, compare the calculated unit normal vector with the x-axis, y-axis, and z-axis of the global coordinate system, calculate the angle between the two-dimensional element and the adjacent element, and identify the element with an angle less than the preset threshold as a co-vector element and classify it into the same subclass.

[0021] In the above-mentioned online identification method of typical aircraft structures based on a finite element model, optionally, in step S2.2, vector comparison is first performed locally, and then the scope is gradually expanded. By comprehensively considering vector features at different scales and calculating the normal vector change rate between adjacent elements, high-curvature regions are identified to accurately classify typical structural elements of complex wing structures with curved surfaces and irregular shapes.

[0022] In the above-mentioned online identification method of typical aircraft structures based on a finite element model, optionally, in step S2.3, the one-dimensional elements are classified according to the topological connection relationship between the one-dimensional elements and the classified two-dimensional elements; among them, according to the node coordinates, if the one-dimensional element shares nodes with the two-dimensional element, the type of the one-dimensional element is determined according to the classification of the two-dimensional element.

[0023] In the above-mentioned online identification method of typical aircraft structures based on a finite element model, optionally, the step of classifying the one-dimensional elements further includes:

[0024] Analyze the ratio of the length of the one-dimensional element to the size of the connected two-dimensional element;

[0025] According to the size ratio relationship between the one-dimensional element and the two-dimensional element, the one-dimensional element is further subdivided and classified: the one-dimensional element with a length much larger than the size of the connected two-dimensional element is classified as a stringer.

[0026] To achieve the above object, a second aspect of the present invention provides an online identification system for typical aircraft structures based on a finite element model, wherein the online identification method of typical aircraft structures based on a finite element model described in any one of the above-mentioned first aspects is used, including:

[0027] A client that uploads the original data file of the finite element model to the server;

[0028] A server, including:

[0029] A data import and parsing module: imports the original data file of the finite element model into the system and extracts the structural element information of the finite element model; the structural element information includes at least one of the following: element number, node coordinates, element type, connection relationship;

[0030] An identification and classification module: classifies the typical structural elements of the finite element model according to structural characteristics and stores them in a non-relational cloud database; among them, the cloud database includes at least a non-relational database NoSQL;

[0031] Loading and rendering module: Load the classified structural unit data into a 3D visualization component to form a visualized 3D model for front-end rendering, and complete the classification display of views; moreover, after clicking on the typical structure points of the aircraft in the view, all subordinate structural units can be selected all at once.

[0032] To achieve the above object, a third aspect of the present invention provides a computer device, including a memory, a processor, and a computer program stored on the memory and executable on the processor. Wherein, when the processor runs the program, it implements the method for online identification of typical aircraft structures based on a finite element model as described in any one of the foregoing first aspects.

[0033] To achieve the above object, a fourth aspect of the present invention provides a computer-readable storage medium. Wherein, the computer-readable storage medium stores computer-executable instructions or a computer program. When the computer-executable instructions or the computer program are processed and executed, the method for online identification of typical aircraft structures based on a finite element model as described in any one of the foregoing first aspect embodiments is implemented.

[0034] The method and system for online identification of typical aircraft structures based on a finite element model provided by the present invention realizes the automatic identification and detailed classification of typical aircraft structures, and through 3D visualization display and interactive operations, greatly improves the efficiency and accuracy of aircraft structure analysis, and has the advantages of improving the efficiency of aircraft structure analysis, enhancing the recognition accuracy and reliability, enhancing the interactivity and flexibility, and adapting to diverse engineering requirements.

[0035] The following will further illustrate the concept, specific structure, and technical effects generated by the present invention in conjunction with the accompanying drawings to fully understand the purpose, features, and effects of the present invention. Description of the Drawings

[0036] To more clearly illustrate the technical solutions of the embodiments of the present invention, the following will briefly introduce the accompanying drawings required for use in the embodiments or the description of the prior art. Obviously, the following-described accompanying drawings are only some embodiments of the present invention. For those of ordinary skill in the art, other accompanying drawings can be obtained based on these drawings without creative labor.

[0037] Figure 1 is a schematic flowchart of an embodiment of a method for online identification of typical aircraft structures based on a finite element model of the present invention;

[0038] Figure 2 is Figure 1 the system architecture diagram of the method for online identification of typical aircraft structures based on a finite element model in

[0039] Figure 3 is usingFigure 1 The schematic diagram of the structural division of typical structures of the vertical tail and horizontal tail of an aircraft in a finite element model in

[0040] Figure 4 This is the complete schematic diagram of the aircraft finite element model in the global coordinate system;

[0041] Figure 5 This is in Figure 4 The schematic diagram of the vertical tail structure in the global coordinate system of

[0042] Figure 6 This is in Figure 4 The schematic diagram of the horizontal tail structure in the global coordinate system of

[0043] Figure 7 This is in Figure 2 The schematic diagram of the effect after the selection of the beam web structure points in the system. Specific implementation manners

[0044] To make the objectives, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are some but not all of the embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0045] Terms such as "comprising" and "including" indicate that in addition to the components directly and clearly stated in the description and claims, the technical solutions of the present invention do not exclude the situation of having other components not directly or clearly stated.

[0046] First of all, it should be noted that the typical structures of an aircraft refer to the structural components that are representative, have clear functions and significant geometric features in aircraft design and manufacturing. These structural components are commonly present in different models of aircraft and play key mechanical and functional roles. For example, the spar, rib, and skin in the wing structure, the vertical tail and horizontal tail in the tail structure, and the fuselage frame and stringer in the fuselage structure all belong to the typical structures of an aircraft. These structures not only determine the aerodynamic performance of the aircraft but also directly affect its strength, stiffness and durability.

[0047] In aircraft finite element analysis, the identification of typical aircraft structures is the basis for optimal design and strength analysis. However, traditional finite element models (such as models stored in BDF file format) usually only contain the geometric information and topological relationships of elements, and do not directly store data related to structural functions or names. Therefore, algorithms are needed to classify and identify these elements so that they can be corresponded to specific typical structures.

[0048] In this application, typical aircraft structures can at least include one of the following: wing structure, empennage structure, fuselage structure, landing gear structure.

[0049] As Figure 1 and Figure 2 shown, a method for online identification of typical aircraft structures based on a finite element model provided by the present invention can specifically include the following steps:

[0050] Step S1: Data import and parsing.

[0051] In step S1, the original data file of the finite element model is imported into the system and the structural element information of the finite element model is extracted.

[0052] In an optional embodiment, step S1 can specifically include the following sub-steps:

[0053] Step S1.1: Upload the finite element model to the system in BDF file format. The user can select the file for upload through the system interface or directly upload the file to the system through the API interface. After the upload is completed, the system will verify the file to ensure the integrity and correctness of the file format and content.

[0054] Step S1.2: Parse the BDF file and extract the structural element information of the finite element model. Specifically, the structural element information can at least include one of the following: element number, node coordinates, element type, connection relationship. The parsing process can be carried out through predefined rules and algorithms, and regular expressions or specific parsing libraries are used to extract the required information. The extracted structural element information can be stored in the database of the system for subsequent processing and analysis. In this embodiment, a non-relational cloud database NoSQL is used to store the structural element information of BDF data. Specifically, it can be MongoDB, which has high scalability and high performance and can efficiently store and manage a large amount of structural element data.

[0055] This step can quickly and accurately extract the structural element information of the finite element model, providing a high-quality data basis for subsequent structural identification and analysis.

[0056] Step S2: Identification and classification.

[0057] In step S2, the typical structural units of the finite element model are classified according to their structural characteristics and stored in a non-relational cloud database.

[0058] In an alternative embodiment, step S2 may specifically include the following steps:

[0059] Step S2.1: Determine and select different aircraft sections according to the first character of the element number in the finite element model. This step can effectively perform a preliminary partition of the complex aircraft structure, facilitating subsequent processing.

[0060] Since the normal vectors of the vertical fin beam, rib, and panel units are different, the section can be determined according to the first digit of the element number. Specifically, the first character of the element number in the horizontal tail units is 6, and that in the vertical tail units is 5. This method of division based on the first character of the element number is not only simple and efficient but also can quickly identify the structural units of different sections, providing a basis for subsequent structure classification and analysis.

[0061] Step S2.2: Classify the two-dimensional units within the selected section into different typical structural units. This step can refine the recognition result and improve the recognition accuracy.

[0062] In an alternative embodiment, in step S2.2, the normal vector of the two-dimensional unit can be calculated, and the calculated unit normal vector can be compared with the x-axis, y-axis, and z-axis of the global coordinate system. The angle between the two-dimensional unit and the adjacent unit can be calculated, and the unit with an angle less than the preset threshold is identified as a co-vector unit and classified into the same subclass.

[0063] After the section division is completed, further structure classification can be achieved by analyzing the normal vector of the unit. Due to the differences in the geometric layout and functions of the beam, rib, and panel units, their normal vector directions are also different. By calculating the normal vector of the unit and comparing it with the axes of the global coordinate system, accurate classification of the typical structural units can be achieved:

[0064] Beam unit: It has a long straight shape, and the direction of its normal vector is perpendicular to the axis of the beam.

[0065] Rib unit: It is perpendicular to the beam, and the direction of its normal vector is perpendicular to the plane of the rib.

[0066] Panel unit: It is a large-area planar structure, and the direction of its normal vector is perpendicular to the surface of the panel.

[0067] The classification of specific aircraft typical structures is shown in Table 1 below:

[0068]

[0069] Table 1

[0070] It should be noted that in the finite element model of the aircraft structure, two-dimensional elements (such as CQUAD4, CTRIA3, etc.) are used to simulate planar structures such as panels, rib webs, and beam webs, while one-dimensional elements (such as CBAR, CROD) are used to simulate linear structures such as stringers, rib flanges, and beam flanges. To achieve a complete classification of these elements, it is necessary to further identify the one-dimensional elements connected to them on the basis of the two-dimensional element classification. Specifically, CQUAD4 represents a four-node quadrilateral shell element (Four-Node Quadrilateral Shell Element), which is used to simulate thin-walled structures (such as wing skins, fuselage panels, etc.) in structural analysis; CTRIA3 represents a three-node triangular shell element (Three-Node Triangular Shell Element), which is a low-order element for simulating thin-walled structures and is particularly suitable for mesh generation of complex geometries and local detail analysis; CBAR represents a one-dimensional rod element with two nodes, which is used to simulate one-dimensional structures (such as beams, rods, trusses, etc.); CROD represents a rod element (Rod Element), which is another element used to simulate one-dimensional structures (such as tension rods, compression rods, trusses, etc.), and is suitable for structural analysis under axial loads and for simulating the axial tension and compression behavior of structures without considering bending and shear deformations.

[0071] Taking the panel element as an example, the panel elements of two-dimensional elements can include three categories: CQUAD4, CSHEAR, and CTRIA3. Under the aircraft global coordinate system as shown in Figure 4 it is possible to compare the normal vectors of the panel elements on the beam structure, rib structure, and panel structure of the vertical tail and / or horizontal tail as shown in Figure 3 , Figure 5 and Figure 6 with the x-axis, y-axis, and z-axis of the global coordinate system. The elements within a range of 45 degrees difference can be identified as co-vector elements, which serve as the basis for identification.

[0072] This method solves the problem of identifying co-vector elements of complex two-dimensional elements by accurately calculating the normal vectors and angles, and uses the calculation of normal vectors and angles to achieve efficient and accurate element classification, ensuring the accuracy and reliability of the identification process.

[0073] In practical applications, when dealing with the wing structure, due to the large variation in its surface curvature, simply relying on the angle with the coordinate axes for classification may lead to misidentification. For example, the curved parts at the leading and trailing edges of the wing may be misidentified as rib or beam structures. In addition, various openings on the wing (such as landing gear doors, inspection hatches, etc.) will interrupt the continuous surface, increasing the difficulty of identification.

[0074] Thus, further, in step S2.2, vector comparison can be first performed locally, and then the scope can be gradually expanded. By comprehensively considering vector features at different scales and calculating the change rate of normal vectors between adjacent units, high-curvature regions can be identified to achieve accurate classification of typical structural units of curved surfaces and irregular-shaped complex wing structures. This method can not only accurately identify high-curvature regions but also accurately classify curved surfaces and irregular shapes in complex wing structures. For example, in complex wing structures, the identification of curved surfaces and irregular shapes is a difficult point, and this problem can be effectively solved by the method of this application.

[0075] Specifically, as a preferred implementation manner, multiple mathematical models and algorithms can be used to calculate the change rate of normal vectors. For example, the curvature calculation method based on differential geometry or the numerical calculation method based on finite element analysis can be used. Thus, the method of this application has significant advantages. In terms of software, adaptive mesh refinement and machine learning-assisted identification can be introduced. Adaptive mesh refinement enables this application to automatically perform local mesh refinement when high-curvature regions are identified to improve the identification accuracy of these regions. At the same time, machine learning algorithms are introduced, and a model is trained to identify complex structural patterns. This model can learn to identify various typical wing structure features, such as leading edges, trailing edges, wing tips, etc. In terms of interaction, users are allowed to perform interactive correction and parametric definition. The preliminary classification results of the algorithm are manually marked or corrected through a graphical interface, and specific parameters (such as curvature thresholds, vector angle tolerances, etc.) are defined to adapt to different types of wing structures.

[0076] Compared with the prior art, the method of this application can more accurately identify and classify typical structural units in complex wing structures, improve the accuracy and reliability of identification, reduce the influence of human factors, and enhance the efficiency of design and analysis. In addition, this method has high versatility and can adapt to different types of aircraft structures to meet diverse engineering needs.

[0077] Step S2.3: Identify and classify one-dimensional units according to the connection form between typical structural units. This step helps to further refine and accurately classify, improving the comprehensiveness and accuracy of identification.

[0078] Optionally, in step S2.3, the one-dimensional elements are classified according to the topological connection relationship between the one-dimensional elements and the classified two-dimensional elements. Among them, based on the node coordinates of the one-dimensional and two-dimensional elements, if a one-dimensional element shares nodes with a two-dimensional element, the type of the one-dimensional element is determined according to the classification of the two-dimensional element. By identifying the topological connection relationship between the one-dimensional and two-dimensional elements, the one-dimensional elements can be effectively classified, and further, by the way of sharing nodes, the type of the one-dimensional element is determined according to the classified two-dimensional elements. This method improves the accuracy and efficiency of classification, reduces the error of manual identification, and enhances the automation and intelligence of the system.

[0079] In this embodiment, this step can be implemented by using topological sorting or the connected component algorithm in graph theory to analyze the connection relationship between elements. In addition, machine learning algorithms can also be combined to improve the accuracy of classification through a large amount of training data.

[0080] Furthermore, step S2.3 may further include:

[0081] Analyze the length ratio of the one-dimensional element to the size of the connected two-dimensional element;

[0082] According to the size ratio relationship between the one-dimensional and two-dimensional elements, the one-dimensional elements are further subdivided and classified: the one-dimensional elements with a length much larger than the size of the connected two-dimensional elements are classified as stringer-like.

[0083] As a preferred implementation manner, a length ratio threshold can be preset in the system. When the length ratio of the one-dimensional element to the size of the connected two-dimensional element exceeds this threshold, the one-dimensional element can be classified as stringer-like. For example, set the length ratio threshold to 10. When the length of the one-dimensional element is more than 10 times the size of the connected two-dimensional element, the one-dimensional element is classified as stringer-like.

[0084] Thus, through this method of subdivision and classification, the one-dimensional elements can be recognized and classified more precisely, significantly improving the accuracy and reliability of recognition.

[0085] Continuing with the example of the panel element, after the classification of the panel element of the two-dimensional element is completed, on the basis of the two-dimensional element, the classification of the one-dimensional elements CBAR and CROD is continued. Specifically, for example, the CBAR at the connection part of the beam and the panel belongs to the beam flange. That is, if a CBAR element shares nodes with the panel skin element and its position and direction conform to the characteristics of the beam flange, then the CBAR element is classified as the beam flange. Similarly, if a CROD element shares nodes with the rib web element and its position and direction conform to the characteristics of the rib flange, then the CROD element is classified as the rib flange.

[0086] This method not only improves the integrity of structural classification, but also provides more accurate structural information for subsequent strength analysis and design optimization.

[0087] Taking the horizontal tail structure as an example, as described in the above steps, for the horizontal tail structure, two-dimensional elements can be classified into elements of different typical structures according to the normal directions of the panel skin, rib web, and beam web elements, and then one-dimensional elements (stringers, rib flanges, beam flanges) can be determined according to the connection forms of the elements.

[0088] Step S3: Loading and rendering.

[0089] In step S3, the classified structural element data is loaded into a 3D visualization component to form a visualized 3D model for front-end rendering, completing the classified display of the view. Moreover, after clicking on the typical aircraft structure in the view, all subordinate structural elements can be selected.

[0090] After completing the recognition and classification of the typical aircraft structures, the system presents the classification results to the user in an intuitive and highly interactive manner. As Figure 2 shown, in order to accelerate rendering at the front end, the present application can add rendering information based on the element information. Specifically, the rendering information is the correspondence between faces and elements, etc. The rendering information uses binary and can be directly sent to the GPU for rendering without parsing, thus significantly reducing the computational overhead of the CPU. This step reduces memory occupancy, improves the performance of the system, enabling the system to process larger-scale data and consume fewer resources.

[0091] Optionally, this process is implemented through a front-end and back-end separated architecture, and the specific steps are as follows:

[0092] Step S3.1: The back end returns the classified data structure.

[0093] Data structure design: The back-end system organizes the recognized and classified structural data into a unified data structure, which needs to contain sufficient information to support front-end display and interactive operations. For example, the data structure can be a nested JSON object, where each typical structure (such as beams, ribs, panels, etc.) serves as the main node, and its subordinate elements (such as beam flanges, rib flanges, panel skin elements, etc.) serve as sub-nodes.

[0094] Data transmission: The back end returns the classified data structure to the front end in JSON format through an API interface. This data structure not only contains the geometric information of each element (such as node coordinates, element types, etc.), but also contains the typical structure type and hierarchical relationship to which it belongs.

[0095] Step S3.2: The front-end visualization component parses the data.

[0096] Data parsing: After the front end receives the classified data structure returned by the back end, it parses the data through a visualization component (such as a WebGL renderer or a 3D visualization library). The visualization component maps each typical structure and its subordinate units into a 3D model and performs visual display according to their types and hierarchical relationships.

[0097] In an alternative embodiment, as Figure 2 shown, the 3D visualization component can be a view component based on WebGL and three.js, which creates rendering geometries for lines and surfaces respectively to enhance the visual realism.

[0098] Classification display: The visualization component differentiates different types of typical structures with different colors, styles or labels according to the classification information in the data structure, enabling users to intuitively identify structures such as beams, ribs, and panels and their subordinate units.

[0099] Step S3.3: Interactive operation: Click and select all functions.

[0100] Click and select function: In the view, the user can click (click and select) a certain typical structure (such as a beam or a panel) with the mouse. The visualization component will identify the selected typical structure and all its subordinate units according to the data structure returned by the back end.

[0101] Select all function: Once the user clicks and selects a typical structure, the system will automatically select that structure and all its subordinate units. For example, when the user clicks and selects a beam, the system will automatically select that beam and all its beam flange units. This select all function is implemented through the hierarchical relationship in the data structure to ensure that users can quickly and efficiently select the target structure and all its related units. Taking the typical structure of a beam web as an example, the click and select effect is as Figure 7 shown.

[0102] To achieve the above object, the present invention also provides an online recognition system for aircraft typical structures based on a finite element model, which specifically may include:

[0103] A client that uploads the original data file of the finite element model to the server;

[0104] A server, including:

[0105] A data import and parsing module that imports the original data file of the finite element model into the system and extracts the structural unit information of the finite element model; the structural unit information includes at least one of the following: element number, node coordinates, element type, connection relationship;

[0106] Recognition and Classification Module: Classify the typical structural units of the finite element model according to structural characteristics and store them in a non-relational cloud database; wherein, the cloud database at least includes a non-relational database NoSQL.

[0107] Loading and Rendering Module: Load the classified structural unit data into a 3D visualization component to form a visualized 3D model for front-end rendering, and complete the classified display of views; moreover, after clicking on the typical structural points of the aircraft in the view, the full selection of all subordinate structural units can be realized. The specific methods and system architectures have been described in detail above and will not be elaborated here.

[0108] To achieve the above object, the present invention also provides a computer device, including a memory, a processor, and a program stored on the memory and executable on the processor. When the processor runs the program, it can implement the steps of a method for online recognition of typical aircraft structures based on a finite element model as described in any of the foregoing embodiments.

[0109] The processor and the memory can be set separately or integrated together. For example, they can be integrated on a system on chip (SOC) of a terminal device. It should be understood that the processor in the embodiments of the present application may be an integrated circuit chip with signal processing capabilities. In the implementation process, the steps of the above method embodiments can be completed by the integrated logic circuit in the hardware of the processor or instructions in software form. The above-mentioned processor can be a general-purpose processor, a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components. It can implement or execute the various methods, steps, and logic block diagrams disclosed in the embodiments of the present application. The general-purpose processor can be a microprocessor or the processor can also be any conventional processor, etc. The steps of the method disclosed in combination with the embodiments of the present application can be directly embodied as being executed and completed by a hardware decoding processor, or by a combination of hardware and software modules in the decoding processor. The software module can be located in a mature storage medium in the art 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, etc. This storage medium is located in the memory, and the processor reads the information in the memory and combines its hardware to complete the steps of the above method.

[0110] To achieve the above object, the present invention further provides a computer-readable storage medium storing executable instructions or programs, which, when processed and executed, implement the online identification method for typical aircraft structures based on a finite element model as described in any of the previous embodiments.

[0111] The readable storage medium is, for example, a memory. The memory may be a volatile memory or a non-volatile memory, or the memory may include both a volatile memory and a non-volatile memory. Among them, the non-volatile memory may be a read-only memory (ROM), a programmable ROM (PROM), an erasable programmable ROM (EPROM), an electrically erasable programmable ROM (EEPROM), or a flash memory. The volatile memory may be a random access memory (RAM), which is used as an external cache. By way of example but not limitation, many forms of RAM are available, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDR SDRAM), enhanced SDRAM (ESDRAM), synchlink DRAM (SLDRAM), and direct rambus RAM (DR RAM).

[0112] If the integrated units in the above embodiments are implemented in the form of software functional units and sold or used as independent products, they can be stored in the above-readable storage medium. Based on such an understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product stored in a storage medium, including several instructions for causing one or more devices (which may be personal terminals, clients, or network devices, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention.

[0113] The preferred specific embodiments of the present invention have been described in detail above. Only several implementation manners of the present invention are expressed, but it should not be construed as a limitation to the scope of the patent. The technical features of the above embodiments can be combined arbitrarily. For the sake of concise description, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, it should be considered as the scope recorded in this specification. It should be understood that those of ordinary skill in the art can make many modifications and variations according to the concept of the present invention without creative labor. Therefore, without departing from the concept of the present invention, all technical solutions that can be obtained by those skilled in the art in the technical field according to the concept of the present invention through logical analysis, reasoning or limited experiments on the basis of the prior art should be within the protection scope determined by the claims.

Claims

1. An online identification method for typical aircraft structures based on finite element models, characterized in that: The typical aircraft structure includes at least one of the following: wing structure, tail structure, fuselage structure, and landing gear structure; The method for online identification of typical aircraft structures comprises the following steps: Step S1: data import and analysis; wherein, the original data file of the finite element model is imported into the system and the structural unit information of the finite element model is extracted; the structural unit information includes at least one of: unit number, node coordinates, unit type, and connection relationship; Step S2: identification and classification; wherein the typical structural units of the finite element model are classified according to structural features and stored in a non-relational cloud database; Step S3: loading and rendering; wherein the classified structural unit data is loaded into the three-dimensional visualization component to form a visualized three-dimensional model and rendered on the front end to complete the classified display of the view; and, after clicking on the typical structure of the aircraft in the view, all subordinate structural units are selected.

2. The method for online identification of typical aircraft structures based on finite element model according to claim 1, characterized in that: The step S1 specifically includes the following steps: Step S1.1: Upload the finite element model into the system in bdf file format; Step S1.2: Parse the bdf file and extract structural unit information of the finite element model.

3. The method for online identification of typical aircraft structures based on finite element model according to claim 1, characterized in that: The step S2 specifically includes the following steps: Step S2.1: determining and selecting different aircraft sections according to the first character of the unit number in the finite element model; Step S2.2: Differentiate the two-dimensional units in the selected section into different typical structural units; Step S2.3: Identify and classify one-dimensional units according to the connection form between the typical structural units.

4. The method for online identification of typical aircraft structures based on finite element model according to claim 3 is characterized in that: In step S2.2, the normal vector of the two-dimensional unit is calculated, and the calculated unit normal vector is compared with the x-axis, y-axis, and z-axis of the global coordinate system, and the angle between the two-dimensional unit and the adjacent unit is calculated. The units with angles less than a preset threshold are identified as co-vector units and classified into the same subcategory.

5. The method for online identification of typical aircraft structures based on finite element model according to claim 4, characterized in that: In step S2.2, vector comparison is first performed locally, and then the scope is gradually expanded, and vector features at different scales are comprehensively considered. High curvature areas are identified by calculating the normal vector change rate between adjacent units to achieve accurate classification of typical structural units of complex wing structures with curved surfaces and irregular shapes.

6. The method for online identification of typical aircraft structures based on finite element model according to claim 3, characterized in that: In step S2.3, the one-dimensional unit is classified according to the topological connection relationship between the one-dimensional unit and the classified two-dimensional unit; wherein, according to the node coordinates, if the one-dimensional unit shares a node with the two-dimensional unit, the type of the one-dimensional unit is determined according to the classification of the two-dimensional unit.

7. The method for online identification of typical aircraft structures based on finite element model according to claim 6, characterized in that: The step of classifying the one-dimensional units also includes: Analyzing the ratio of the length of the one-dimensional unit to the size of the connected two-dimensional unit; According to the size ratio relationship between the one-dimensional unit and the two-dimensional unit, the one-dimensional unit is further subdivided and classified: the one-dimensional unit whose length is much larger than the size of the connected two-dimensional unit is classified as a long stringer.

8. An online identification system for typical aircraft structures based on finite element models, characterized in that: The method for online identification of typical aircraft structures based on a finite element model as claimed in any one of claims 1 to 7 comprises: A client, wherein the client uploads the original data file of the finite element model to the server; The server side includes: Data import and analysis module: import the original data file of the finite element model into the system and extract the structural unit information of the finite element model; the structural unit information includes at least one of the following: unit number, node coordinates, unit type, and connection relationship; Identification and classification module: classify the typical structural units of the finite element model according to the structural features and store them in a non-relational cloud database; wherein the cloud database at least includes a non-relational database NoSQL; Loading and rendering module: Load the classified structural unit data into the 3D visualization component to form a visualized 3D model and render it on the front end to complete the classified display of the view; and, by clicking on the typical structure of the aircraft in the view, all subordinate structural units can be selected.

9. A computer device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, characterized in that: When the processor runs the program, the online identification method for typical aircraft structures based on a finite element model as described in any one of claims 1 to 7 is implemented.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer-executable instructions or a computer program, and when the computer-executable instructions or the computer program are processed and executed, the online identification method of a typical structure of an aircraft based on a finite element model according to any one of claims 1 to 7 is implemented.

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