Full-aircraft model partition positioning method, device, equipment, medium and product

Abstract

The invention discloses a full-aircraft model partition positioning method, device, equipment, medium and product, and relates to the technical field of aircraft digital application, and the method comprises the steps: building a space region division model of an aircraft, and distributing a unique region number for each region block; loading a space region division model in the full-aircraft model, and extracting a model bounding box of each sub-model in the full-aircraft model; calculating an area number to which each sub-model belongs through a space judgment algorithm; storing the position information of the sub-models; when the position of the full-aircraft model is changed, re-extracting the model bounding box of each sub-model, calculating the area number, storing the position information, comparing the position information before and after the position change, detecting the change content, and updating the storage; according to the method, the area number input by the user is obtained, the stored position information is traversed, all the sub-models belonging to the area number in the whole-machine model are quickly retrieved, and model area calculation, position change checking and quick retrieval are completed through an automatic process.

Description

Technical Field

[0001] This application relates to the field of aircraft digital application technology, and in particular to a method, apparatus, equipment, medium and product for full-aircraft model zoning positioning. Background Technology

[0002] With the rapid development of the aviation industry, aircraft structures are becoming increasingly complex, and system integration is constantly improving. Throughout the entire life cycle of an aircraft, including design, manufacturing, and maintenance, it is often necessary to divide the entire aircraft into spatial areas, such as overall layout zones, modular section zones, EDZ (vulnerable zone) zones, and maintainability zones, in order to facilitate design coordination, assembly positioning, and maintenance operations.

[0003] Currently, in aerospace digital design environments, full-aircraft assembly models typically consist of tens of thousands of sub-models (parts, components, system equipment, etc.). In traditional management, the location and area information of these models largely relies on manual marking and maintenance. Specifically: manual division and numbering—designers manually assign area numbers to models based on experience, resulting in a large workload and a high risk of errors; difficulty in synchronizing changes—when a model undergoes design changes, location adjustments, or area re-division, its area information often fails to update automatically, requiring manual verification and correction; low retrieval efficiency—in large assembly models, searching for related models based on areas requires traversing a vast amount of model data, which is time-consuming and cannot guarantee completeness; and a lack of intelligent determination mechanisms—existing systems generally lack intelligent algorithms that automatically determine the spatial area a model belongs to based on its geometric information, making it difficult to achieve dynamic management and precise positioning of the model's location. Summary of the Invention

[0004] The purpose of this application is to provide a method, device, equipment, medium, and product for full-machine model zoning and positioning, which can solve the problems of manual division and numbering, which is labor-intensive and prone to errors; lack of intelligent judgment mechanism, making it difficult to achieve dynamic management and accurate positioning of model position; and realize the determination of the regional affiliation of all sub-models in a short time. It solves the problem that changes are difficult to synchronize, and regional information often cannot be automatically updated, requiring manual re-verification and correction. It realizes the automated process to complete model region calculation, position change check, and rapid retrieval.

[0005] To achieve the above objectives, this application provides the following solution: Firstly, this application provides a method for whole-machine model partitioning and localization, including: Construct a spatial region division model for the aircraft and assign a unique region number to each region block; Load the spatial region partitioning model into the full machine model, and extract the bounding boxes of each sub-model in the full machine model; Based on the spatial region division model and the bounding boxes of each sub-model, the region number to which each sub-model belongs is calculated using a spatial judgment algorithm; Store the location information of the sub-model; When the position of the entire model changes, the bounding boxes of each sub-model are re-extracted, the region number is calculated and the position information is stored. By comparing the position information before and after the position change, the changed content is detected and the storage is updated. Obtain the region number input by the user, traverse the stored location information, and quickly retrieve all sub-models belonging to that region number in the entire machine model.

[0006] Optionally, the model bounding box includes an axis-aligned bounding box and a direction bounding box. The axis-aligned bounding box is defined by the minimum and maximum point coordinates, and the direction bounding box is defined by the coordinates of eight vertices.

[0007] Optionally, the specific process of calculating the region number to which each sub-model belongs using the spatial judgment algorithm includes: Determine whether the bounding box of the sub-model intersects with the region block. If they intersect, determine that the sub-model is located within the region block. If they do not intersect, obtain the center point of the model's bounding box; The center point of the model bounding box is vertically projected onto the region block. If the projection fails, it is determined that the sub-model is neither within the region block nor in the vicinity of the region block. If the projection is successful, obtain the projection point, and construct a ray with the center point as the starting point and the projection point as the target point; Determine whether the ray intersects with the region block; if it does not intersect, determine that the sub-model is not within the region block. If they intersect, obtain the number of intersection points; Determine the number of intersection points. If the number of intersection points is odd, determine that the sub-model is located within the region block; if the number of intersection points is even, determine that the sub-model is not located within the region block. Label the region number corresponding to the region block to the sub-model located within that region block.

[0008] Optionally, the location information of the sub-model includes model bounding box information and region number information.

[0009] Optionally, the changes include alterations to the region to which the sub-model belongs and changes to the model's bounding box coordinates.

[0010] Optionally, the fast retrieval is achieved by building an inverted index using region numbers.

[0011] Secondly, this application provides a full-machine model partitioning positioning device, comprising: The region partitioning module is used to build and manage the spatial region partitioning model of the aircraft; The location extraction module is used to extract the bounding boxes of each sub-model in the whole machine model; The region determination module is used to calculate the region number to which each sub-model belongs; The storage management module is used to store the location information of the sub-models; The change detection module is used to detect changes and update the storage. The retrieval module is used to quickly retrieve all sub-models belonging to a given region number.

[0012] Thirdly, this application provides a computer device, including: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the full-machine model partitioning positioning method described in any one of the above.

[0013] Fourthly, this application provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the full-machine model partitioning and positioning method described in any one of the above descriptions.

[0014] Fifthly, this application provides a computer program product, including a computer program that, when executed by a processor, implements the steps of the full-machine model partitioning positioning method described above.

[0015] According to the specific embodiments provided in this application, the following technical effects are disclosed: This application provides a method, apparatus, device, medium, and product for zoning and positioning a full-aircraft model. It constructs a spatial region division model of the aircraft and assigns a unique region number to each region block. The spatial region division model is loaded into the full-aircraft model, and the bounding boxes of each sub-model in the full-aircraft model are extracted. Based on the spatial region division model and the bounding boxes of each sub-model, a spatial judgment algorithm calculates the region number to which each sub-model belongs. This solves the problems of manual division and numbering, where designers manually assign region numbers to models based on experience, which is labor-intensive and prone to errors; and the lack of intelligent judgment mechanisms. Existing systems generally lack intelligent algorithms that automatically determine the spatial region to which a model belongs based on its geometric information, making it difficult to achieve dynamic management and accurate positioning of the model's position. This application enables automated calculation to determine the region affiliation of all sub-models in scenarios such as full-aircraft assembly models containing a large number of sub-models in a short time, improving efficiency by tens or even hundreds of times compared to manual operation. Simultaneously, it eliminates the need for professional personnel to spend a lot of time on position verification, significantly reducing labor costs and the probability of human error. By storing the position information of the sub-models, when the full-aircraft model... When a location change occurs, the bounding boxes of each sub-model are re-extracted, the region number is calculated, and the location information is stored. By comparing the location information before and after the change, the changed content is detected and the storage is updated. The region number input by the user is obtained, and the stored location information is traversed to quickly retrieve all sub-models belonging to that region number in the entire aircraft model. This solves the problem of difficulty in synchronizing changes. When a model undergoes design changes, location adjustments, or region re-division, its region information often cannot be automatically updated and requires manual verification and correction. The retrieval efficiency is low. In large assembly models, when searching for related models based on regions, a large amount of model data needs to be traversed, which is time-consuming and cannot guarantee completeness. This system automates the process of calculating model regions, checking for location changes, and quickly retrieving them. It completely changes the traditional mode of relying on manual inspection and recording of model positions one by one. It can form a standardized location information database, providing a unified location information query entry for personnel in different stages such as design, assembly, and maintenance. Accurate location information and change data can provide precise support for layout optimization in overall aircraft design and fault location in maintenance work, thus contributing to the scientific nature of related decisions. Attached Figure Description

[0016] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0017] Figure 1 A flowchart illustrating a full-machine model partitioning and positioning method provided in an embodiment of this application; Figure 2 for Figure 1 A detailed flowchart illustrating the steps of the mid-space judgment algorithm; Figure 3 This is a schematic diagram of the structure of a computer device provided in an embodiment of this application. Detailed Implementation

[0018] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0019] To make the above-mentioned objectives, features and advantages of this application more apparent and understandable, the application will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0020] In one exemplary embodiment, such as Figure 1 As shown, a method for whole-machine model partitioning and localization is provided. This method is executed by a computer device and includes the following steps 101 to 106. Wherein: Step 101: Construct a spatial region division model for the aircraft and assign a unique region number to each region block; Step 102: Load the spatial region partitioning model into the full machine model and extract the model bounding boxes of each sub-model in the full machine model; Step 103: Based on the spatial region division model and the model bounding boxes of each sub-model, calculate the region number to which each sub-model belongs using a spatial judgment algorithm; Step 104: Store the location information of the sub-model; Step 105: When the position of the whole model changes, the bounding boxes of each sub-model are re-extracted, the region number is calculated and the position information is stored. By comparing the position information before and after the position change, the changed content is detected and the storage is updated. Step 106: Obtain the region number input by the user, traverse the stored location information, and quickly retrieve all sub-models belonging to that region number in the whole machine model.

[0021] Implementing steps 101 to 106 solves the problems of manual division and numbering, where designers manually assign area numbers to models based on experience, which is labor-intensive and prone to errors; the lack of intelligent determination mechanisms, as existing systems generally lack intelligent algorithms that automatically determine the spatial region of a model based on its geometric information, making it difficult to achieve dynamic management and precise positioning of the model's location; and the realization of automated calculation in scenarios such as full-machine assembly models containing a large number of sub-models, which can complete the region assignment determination of all sub-models in a short time, improving efficiency by tens or even hundreds of times compared to manual operation; at the same time, it eliminates the need for professional personnel to spend a lot of time checking the location, significantly reducing labor costs and the probability of human error; and it solves the problem of difficulty in synchronizing changes, when the model undergoes design changes. When there are design changes, location adjustments, or area re-divisions, the area information often cannot be updated automatically, requiring manual verification and correction. This results in low retrieval efficiency; in large assembly models, finding relevant models by area requires traversing a large amount of model data, which is time-consuming and cannot guarantee completeness. This system automates the model area calculation, location change checks, and rapid retrieval, completely changing the traditional model that relies on manual checking and recording of model positions. It can form a standardized location information database, providing a unified location information query portal for personnel in different stages such as design, assembly, and maintenance. Accurate location information and change data can provide precise support for layout optimization in overall aircraft design and fault location in maintenance work, contributing to the scientific nature of related decisions.

[0022] Specifically, the spatial region partitioning model of an aircraft can be a lightweight three-dimensional geometric model, typically composed of closed region blocks formed by multiple polygons (such as triangular meshes) or parametric surfaces (such as NURBS surfaces). Each region block corresponds to a functional or structural partition of the aircraft, such as "left wing fuel tank" or "cockpit instrument area." The construction process of the spatial region partitioning model can be based on the aircraft's overall layout drawing, with region boundaries manually drawn in a three-dimensional environment; or it can be based on existing region partitioning standards (such as ATA chapters or maintenance manual partitions), automatically generating corresponding three-dimensional region blocks. Each region block is assigned a unique region number, which can be associated with region codes, ATA codes, etc., in the business system for easy subsequent information integration.

[0023] As an optional implementation, the axis-aligned bounding box is defined by the minimum and maximum point coordinates, and the orientation bounding box is defined by the coordinates of eight vertices.

[0024] Specifically, an Axis-Aligned Bounding Box (AABB) is the smallest regular hexahedron with sides parallel to the target sub-model's coordinate system. Its orientation is fixed and consistent with the coordinate axes, allowing for quick characterization of the target sub-model's position using a simple coordinate range. An Oriented Bounding Box (OBB) is the smallest regular hexahedron capable of containing the target sub-model. Its orientation can be arbitrarily adjusted relative to the coordinate axes and can be aligned with the target sub-model's geometric principal axes. Precisely defined by the coordinate data of its eight vertices, it more closely matches the actual shape of the target sub-model, improving the accuracy of its position description.

[0025] A complete aircraft model is typically a 3D assembly model derived from a CAD system (such as CATIA, NX, Creo). Its data structure is a tree-like assembly hierarchy, containing tens of thousands to hundreds of thousands of components, parts, and standard parts. When extracting the bounding boxes of each sub-model within the complete aircraft model, the process starts from the root node (the overall assembly) and traverses the entire assembly structure tree using a depth-first or breadth-first search algorithm. During this traversal, sub-models that serve as the basic logical management units are identified. A sub-model is a logical component, a device, or a subsystem (such as a "hydraulic pump assembly" or "cockpit display"), and its internal structure is considered a whole at this stage. For each identified sub-model, its precise boundary geometric data, including the surface, curved surfaces, and vertices, is obtained through the CAD system's application programming interface. The coordinates of all vertices of the sub-model in the global assembly coordinate system are obtained, and the minimum and maximum values ​​on the X, Y, and Z axes are found. The axis-aligned bounding boxes of this sub-model are defined by the points (Xmin, Ymin, Zmin) and (Xmax, Ymax, Zmax). By calculating the covariance matrix of the sub-model geometry, its eigenvectors (i.e., the principal directions of the sub-model in space) are obtained. The vertices of the sub-model are projected onto a local coordinate system formed by the principal directions, and the axis-aligned bounding box in this coordinate system is found. Then, the eight vertices of this local axis-aligned bounding box are transformed back to the global assembly coordinate system to obtain the final coordinates of the eight vertices of the orientation bounding box. When extracting the model bounding boxes of each sub-model in the full machine model, the optimal type of bounding box can be automatically selected based on the geometric characteristics of the sub-model, or it can be specified by the user. For complex components, multi-level bounding boxes (such as part-level, component-level, and system-level) can be supported to improve the efficiency of spatial judgment.

[0026] As an optional implementation method, such as Figure 2 As shown, the specific process of calculating the region number to which each sub-model belongs using the spatial judgment algorithm includes: Determine whether the bounding box of the sub-model intersects with the region block. If they intersect, determine that the sub-model is located within the region block. If they do not intersect, obtain the center point of the model's bounding box; The center point of the model bounding box is vertically projected onto the region block. If the projection fails, it is determined that the sub-model is neither within the region block nor in the vicinity of the region block. If the projection is successful, obtain the projection point, and construct a ray with the center point as the starting point and the projection point as the target point; Determine whether the ray intersects with the region block; if it does not intersect, determine that the sub-model is not within the region block. If they intersect, obtain the number of intersection points; Determine the number of intersection points. If the number of intersection points is odd, determine that the sub-model is located within the region block; if the number of intersection points is even, determine that the sub-model is not located within the region block. Label the region number corresponding to the region block to the sub-model located within that region block.

[0027] Specifically, axis-aligned bounding boxes are suitable for most rigid body parts, offering fast calculation speeds and are suitable for initial screening; directional bounding boxes are suitable for long, curved models (such as pipes and cables), providing higher fit. When calculating the region number of each sub-model using the spatial judgment algorithm, the model bounding box type can be automatically selected based on the geometric characteristics of the region block, or it can be specified by the user. Alternatively, a layered judgment strategy can be adopted to improve efficiency. An intersection test is performed between axis-aligned bounding boxes and region blocks for rapid coarse screening, eliminating obviously irrelevant sub-models; then, for potentially related sub-models, a precise geometric intersection test is performed between directional bounding boxes and region blocks. The position description methods using axis-aligned and directional bounding boxes balance simplicity and accuracy in position representation, providing a reliable data foundation for region assignment calculations. Furthermore, the progressive calculation logic of "intersection judgment - center point projection - ray intersection - intersection point parity judgment" ensures the accuracy of sub-model region assignment judgments, effectively avoiding design deviations or maintenance errors caused by incorrect position determination.

[0028] In the step of determining whether the bounding box of a sub-model intersects with a region block, if the bounding box does not intersect with the region block, it does not necessarily mean that the sub-model is far from the region. The sub-model may be close to the outer side of the region surface, partially embedded but with a bounding box that does not intersect (for precisely fitted irregular models), or located near the region boundary. In this case, "center point projection" serves as a quick orientation determination tool to confirm the relative orientation of the sub-model and the region. Its main purpose is to filter out obviously unrelated models. If the center point cannot be projected onto the region surface (e.g., the region is behind the model), it can be quickly determined that the model is not in the region. At the same time, it provides a precise endpoint for subsequent ray detection. The projection point serves as the target point of the ray, ensuring that ray detection follows the shortest path from the center of the sub-model to the region, thus improving the accuracy of the judgment. Since the region is closed, a ray must leave once to return to the outside every time it enters the region. Therefore, if the center point is outside the region, the number of times the ray enters and leaves is equal, and the number of intersections is even. If the center point is inside the region, the ray must first pass through the region before it can enter and pass through again. There is already an intersection before the first time it passes through, and the number of intersections is odd.

[0029] As an optional implementation, the location information of the sub-model includes model bounding box information and region number information.

[0030] Specifically, the location information of the sub-model can be stored in a relational database or a NoSQL database, and an example of the data structure is shown in Table 1.

[0031] Table 1. Examples of Data Structures

[0032] As an optional implementation, the changes include alterations to the region to which the sub-model belongs and changes to the model bounding box coordinates.

[0033] Specifically, changes to the region to which a sub-model belongs can be due to a significant alteration in its geometric position (e.g., a hydraulic pump moving from the wing root region to the central wing box region), or a change in the definition of the spatial region partitioning model (e.g., expanding the boundary of an inspection port for maintenance convenience, causing components previously on that boundary to be re-included in that region). Changes to the model bounding box coordinates can be due to modifications to the shape and size of the sub-model itself (e.g., lengthening a pipe or replacing it with a larger device), or translation or rotation of the sub-model's position and attitude within the assembly (e.g., adjusting the routing of a cable bundle or rotating the angle of a mounting bracket), or replacing an old component with a new component of different geometric dimensions. When either the sub-model's region or the model bounding box coordinates change, automatic recalculation and correlation updates are triggered, ensuring the real-time nature, consistency, and accuracy of the location information database. This completely solves the problems of delayed and incorrect regional information caused by model changes in traditional manual methods, providing a reliable data foundation for various location-based aerospace engineering activities.

[0034] As an optional implementation, the fast retrieval is achieved by building an inverted index using region numbers.

[0035] Specifically, after the spatial determination algorithm completes the region assignment calculation for all sub-models, it iterates through all sub-models and their assigned region ID lists. For each region ID belonging to each sub-model, the sub-model's ID is added to the index list corresponding to that region ID. When a sub-model's position change is detected (whether it's a change in bounding box coordinates or a change in its region), and recalculation is completed, an incremental update of the inverted index is triggered. The sub-model ID is removed from the index list corresponding to all region IDs that the sub-model originally belonged to, and added to the index list corresponding to all newly calculated region IDs. When a user enters a target region ID (e.g., "EDZ-07") for retrieval, it is no longer necessary to traverse tens of thousands of sub-model position records for real-time spatial calculation. Instead, it directly uses "EDZ-07" as the key to search in the inverted index data structure (e.g., using a hash table). A pre-compiled list of all sub-model IDs belonging to that region is obtained. Based on this ID list, detailed information about these sub-models (such as name, type, 3D geometric data, etc.) can be quickly loaded from the model database or memory and highlighted, displayed in a list, or generated in the user interface.

[0036] This application also provides an application scenario in which the above-described whole-aircraft model partitioning and positioning method is applied. Specifically, the whole-aircraft model partitioning and positioning method provided in this embodiment can be applied to the component positioning and replacement inspection scenario in aircraft maintenance work.

[0037] For example, at a major airline's maintenance base, engineers needed to conduct a systematic inspection and component replacement of a specific area on a commercial airliner undergoing routine overhaul. The full aircraft model contained over 100,000 sub-models (including fuselage structural components, system piping, electrical cables, and onboard equipment). According to the maintenance manual, the key area to be inspected was the EDZ-07 area (vulnerable area number) corresponding to the "right wing leading edge anti-icing system."

[0038] The traditional workflow is as follows: engineers need to search through a huge technical database to find a list of all parts and location diagrams corresponding to the EDZ-07 area; in the 3D assembly model, engineers need to manually select, search, and check each part to see if it belongs to the area; if the whole machine model has undergone design changes after the last maintenance (such as pipeline routing adjustment), the old drawings are inconsistent with the current model, which can easily lead to missed or false detections; the area screening task alone may take several hours and is prone to errors due to fatigue or negligence.

[0039] The specific process after applying the full-aircraft model zoning and positioning method of this application is as follows: The maintenance base has pre-constructed a spatial area division model that conforms to the maintenance zoning standards of this aircraft model using computer equipment, and each area (such as EDZ-07) has been assigned a unique number; the area division model is loaded into the full-aircraft assembly model of the aircraft; the bounding boxes of all sub-models (parts, pipes, equipment, etc.) in the full-aircraft model are automatically extracted; the area number to which each sub-model belongs is automatically determined through a spatial judgment algorithm, and the result is stored in the location information database; the engineer enters "EDZ-07" in the interface, clicks search, and immediately returns a list of all sub-models in the area through the inverted index, which is highlighted in the 3D view. The engineer can view the bounding box information and area number information of each component with one click; if a section of pipe is rearranged (location changed) during this overhaul, the bounding box of the pipe is automatically recalculated after the model is updated, the change of its area is re-determined, and the location information of the component in the database is automatically updated; the engineer can quickly formulate the disassembly and assembly sequence and tool preparation plan based on the provided accurate area component list.

[0040] The whole-aircraft model zoning and positioning method described in this application realizes an intelligent transformation from "human-finded parts" to "system-pushed parts" in the typical application scenario of aircraft maintenance. It not only greatly improves the efficiency of maintenance preparation and execution, but also ensures the accuracy, consistency and traceability of maintenance work through automated area determination, change detection and rapid retrieval. It is a key technical support for the construction of aircraft digital maintenance system.

[0041] Based on the same inventive concept, this application also provides a full-machine model partitioning positioning device for implementing the full-machine model partitioning positioning method described above. The solution provided by this device is similar to the solution described in the above method. Therefore, the specific limitations of one or more full-machine model partitioning positioning device embodiments provided below can be found in the limitations of the full-machine model partitioning positioning method above, and will not be repeated here.

[0042] In one exemplary embodiment, a full-machine model partitioning positioning device is provided, comprising: The region partitioning module is used to build and manage the spatial region partitioning model of the aircraft; The location extraction module is used to extract the bounding boxes of each sub-model in the whole machine model; The region determination module is used to calculate the region number to which each sub-model belongs; The storage management module is used to store the location information of the sub-models; The change detection module is used to detect changes and update the storage. The retrieval module is used to quickly retrieve all sub-models belonging to a given region number.

[0043] In one exemplary embodiment, a computer device is provided, which may be a server or a terminal, and its internal structure diagram may be as follows. Figure 3 As shown, this computer device includes a processor, memory, input / output interfaces (I / O), and a communication interface. The processor, memory, and I / O interfaces are connected via a system bus, and the communication interface is also connected to the system bus via the I / O interfaces. The processor provides computational and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system, computer programs, and a database. The internal memory provides the environment for the operation of the operating system and computer programs stored in the non-volatile storage media. The database stores video tag processing data. The I / O interfaces are used for exchanging information between the processor and external devices. The communication interface is used for communication with external terminals via a network connection. When executed by the processor, the computer program implements a full-machine model partitioning positioning method.

[0044] Those skilled in the art will understand that Figure 3 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0045] In one exemplary embodiment, a computer device is also provided, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps in the above-described method embodiments.

[0046] In one exemplary embodiment, a computer-readable storage medium is provided storing a computer program that, when executed by a processor, implements the steps in the above-described method embodiments.

[0047] In one exemplary embodiment, a computer program product is provided, including a computer program that, when executed by a processor, implements the steps in the above-described method embodiments.

[0048] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of the relevant data must comply with relevant regulations.

[0049] Those skilled in the art will understand that all or part of the processes in the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium. When executed, the computer program can include the processes of the embodiments described above. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM).

[0050] The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, etc., and are not limited to these.

[0051] The technical features of the above embodiments can be combined in any way. For the sake of brevity, 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, they should be considered to be within the scope of this specification.

[0052] This document uses specific examples to illustrate the principles and implementation methods of this application. The descriptions of the above embodiments are only for the purpose of helping to understand the methods and core ideas of this application. Furthermore, those skilled in the art will recognize that, based on the ideas of this application, there will be changes in the specific implementation methods and application scope. Therefore, the content of this specification should not be construed as a limitation of this application.

Claims

1. A method for zonal localization of a full-machine model, characterized in that, The whole-machine model partitioning and localization method includes: Construct a spatial region division model for the aircraft and assign a unique region number to each region block; Load the spatial region partitioning model into the full machine model, and extract the bounding boxes of each sub-model in the full machine model; Based on the spatial region division model and the bounding boxes of each sub-model, the region number to which each sub-model belongs is calculated using a spatial judgment algorithm; Store the location information of the sub-model; When the position of the entire model changes, the bounding boxes of each sub-model are re-extracted, the region number is calculated and the position information is stored. By comparing the position information before and after the position change, the changed content is detected and the storage is updated. Obtain the region number input by the user, traverse the stored location information, and quickly retrieve all sub-models belonging to that region number in the entire machine model.

2. The whole-machine model partitioning and positioning method according to claim 1, characterized in that, The model bounding box includes an axis-aligned bounding box and a direction bounding box. The axis-aligned bounding box is defined by the minimum and maximum point coordinates, and the direction bounding box is defined by the coordinates of eight vertices.

3. The whole-machine model partitioning and positioning method according to claim 1, characterized in that, The specific process of calculating the region number to which each sub-model belongs using the spatial judgment algorithm includes: Determine whether the bounding box of the sub-model intersects with the region block. If they intersect, determine that the sub-model is located within the region block. If they do not intersect, obtain the center point of the model's bounding box; The center point of the model bounding box is vertically projected onto the region block. If the projection fails, it is determined that the sub-model is neither within the region block nor in the vicinity of the region block. If the projection is successful, obtain the projection point, and construct a ray with the center point as the starting point and the projection point as the target point; Determine whether the ray intersects with the region block; if it does not intersect, determine that the sub-model is not within the region block. If they intersect, obtain the number of intersection points; Determine the number of intersection points. If the number of intersection points is odd, determine that the sub-model is located within the region block; if the number of intersection points is even, determine that the sub-model is not located within the region block. Label the region number corresponding to the region block to the sub-model located within that region block.

4. The whole-machine model partitioning and positioning method according to claim 1, characterized in that, The location information of the sub-model includes model bounding box information and region number information.

5. The whole-machine model partitioning and positioning method according to claim 1, characterized in that, The changes include alterations to the region to which the sub-model belongs and changes to the coordinates of the model's bounding box.

6. The whole-machine model partitioning and positioning method according to claim 1, characterized in that, The fast retrieval is achieved by building an inverted index using region numbers.

7. A full-scale model partitioning positioning device, characterized in that, The full-machine model partition positioning device includes: The region partitioning module is used to build and manage the spatial region partitioning model of the aircraft; The location extraction module is used to extract the bounding boxes of each sub-model in the whole machine model; The region determination module is used to calculate the region number to which each sub-model belongs; The storage management module is used to store the location information of the sub-models; The change detection module is used to detect changes and update the storage. The retrieval module is used to quickly retrieve all sub-models belonging to a given region number.

8. A computer device, comprising: A memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that the processor executes the computer program to implement the steps of the full-machine model partitioning positioning method according to any one of claims 1-6.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the steps of the full-machine model partitioning and positioning method as described in any one of claims 1-6.

10. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by the processor, it implements the steps of the full-machine model partitioning and positioning method as described in any one of claims 1-6.

Images