Building construction quality detection method, device and equipment and storage medium
By optimizing flight paths and energy consumption of drones in construction scenarios, the problem of insufficient flexibility in existing detection systems has been solved, enabling efficient and comprehensive construction quality inspection.
Patent Information
- Application Number
- CN202511570039.1
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-10-30
- Publication Date
- 2026-02-10
AI Technical Summary
Existing construction quality inspection systems are not flexible enough when facing dynamic and changing construction scenarios, and cannot adapt to diverse inspection needs, resulting in insufficient comprehensiveness and real-time performance of inspections.
By acquiring building models and construction sites, the flight path of UAVs from the initial site to the construction site is used to calculate flight energy consumption. The flight path of the UAVs is optimized by using a nest site correction network model to improve detection flexibility. Construction quality inspection is carried out using UAV edge models.
It improves the flexibility and comprehensiveness of construction quality inspection, balances the energy consumption of drone flights, and ensures the inspection time and accuracy of quality inspection at each construction site.
Smart Images
Figure CN121504243A_ABST
Abstract
Description
Technical Field
[0001] This application relates to the technical field of construction testing, specifically to a method, apparatus, equipment, and storage medium for testing the quality of building construction. Background Technology
[0002] The inspection and evaluation of construction quality has always been a crucial issue and key problem in the construction industry. In traditional construction processes, quality monitoring largely relies on manual inspection, depending on workers' experience and subjective judgment. This method is not only highly inefficient, but also easily affected by various human factors, such as the inspector's professional level, work status, and personal emotions. These factors can influence the final judgment, leading to inaccurate and unreliable assessments of construction quality.
[0003] With the continuous advancement of technology, intelligent and digital technologies have gradually emerged and been widely applied. Especially against the backdrop of the rapid development of deep learning and artificial intelligence, existing technologies can now automatically detect construction quality by analyzing video images. Compared to traditional methods, this approach improves efficiency and accuracy to a certain extent. However, current technological solutions still have significant limitations. Specifically, existing construction quality inspection systems typically rely on fixed-location surveillance cameras that continuously capture video images of construction sites, which are then analyzed and judged. However, in reality, construction sites are not static but change as the project progresses. Furthermore, some construction sites may be located in remote or complex areas where there may be no suitable location for surveillance cameras. This makes existing technologies inadequate in the face of dynamically changing construction scenarios, unable to flexibly adapt to diverse inspection needs, thus revealing a significant technical deficiency of poor flexibility. This deficiency severely restricts the comprehensiveness and real-time nature of construction quality inspection and poses new challenges to the overall quality assurance of the project. Summary of the Invention
[0004] The purpose of this application is to overcome the shortcomings and deficiencies of the prior art and to provide a method, device, equipment and storage medium for testing the quality of building construction.
[0005] The first aspect of this application provides a method for inspecting the quality of building construction, including:
[0006] Obtain the architectural model of the target building to be inspected and multiple construction points;
[0007] Based on the building model and multiple construction points, the initial location of the mobile nest is obtained;
[0008] The flight energy consumption of the multiple drones is obtained based on the multiple flight paths of the multiple drones flying from the initial point to the corresponding construction point;
[0009] Based on the building model, the multiple construction points, the initial point, the multiple flight paths, and the flight energy consumption of the multiple UAVs, the point of the mobile nest is corrected to obtain the target point with high flight energy consumption scores for the multiple UAVs; wherein, the smaller the maximum flight energy consumption difference of the multiple UAVs, the higher the corresponding flight energy consumption score.
[0010] The mobile drone nest is driven to move to the target location, so that the multiple drones can fly from the target location to the multiple construction sites to conduct construction quality inspection.
[0011] As one implementation method, the step of obtaining the initial location of the mobile nest based on the building model and multiple construction points includes:
[0012] Based on the building model, obtain the three-dimensional ground data of the target building;
[0013] Based on the three-dimensional ground data, the ground point with the closest average distance to the multiple construction points is determined as the initial point.
[0014] As one implementation method, the step of obtaining the flight energy consumption of the multiple drones based on the multiple flight paths of the multiple drones flying from the initial point to the corresponding construction point includes:
[0015] Based on the building model, multiple flight paths are obtained for multiple drones to fly from the initial point around the obstacles to the corresponding construction point;
[0016] The flight path is decomposed based on the turning points to obtain multiple sub-paths of the multiple flight paths;
[0017] Based on the flight actions corresponding to the multiple sub-paths and the flight parameters of the UAV, the path energy consumption of the multiple sub-paths is obtained;
[0018] The flight energy consumption of the multiple UAVs is obtained based on the path energy consumption of the multiple sub-paths.
[0019] As one implementation method, the step of correcting the location of the mobile nest based on the building model, the multiple construction points, the initial location, the multiple flight paths, and the flight energy consumption of the multiple UAVs, to obtain the target location with high flight energy consumption scores for the multiple UAVs, includes:
[0020] A nest location correction network model is obtained; wherein the nest location correction network model is trained based on multiple nest location correction training samples, the nest location correction training samples include building model samples, construction point samples, initial point samples, flight path samples, flight energy consumption samples and target point samples; wherein the maximum flight energy consumption difference of multiple UAVs corresponding to the target point sample is less than a preset difference threshold.
[0021] The building model, the multiple construction sites, the initial site, the multiple flight paths, and the corresponding flight energy consumption are input into the trained nest site correction network model to obtain the target site.
[0022] As one implementation method, the drone is equipped with a construction quality inspection edge model;
[0023] The step of driving the mobile drone nest to the target location, and causing the multiple drones to fly from the target location to the multiple construction sites for construction quality inspection, includes:
[0024] After driving the mobile drone nest to the target location, the multiple drones are driven to fly from the target location to the corresponding construction location, so as to take construction images of the corresponding construction location through the drones, and then perform construction quality inspection on the construction images through the construction quality inspection edge model loaded by the drones.
[0025] Compared to related technologies, the construction quality inspection method of this application obtains the initial position of a mobile drone nest based on the building model of the target building and multiple construction points; then, based on multiple flight paths of multiple drones flying from the initial position to the corresponding construction points, the flight energy consumption of the multiple drones is obtained; then, based on the building model, the multiple construction points, the initial position, the multiple flight paths, and the flight energy consumption of the multiple drones, the position of the mobile drone nest is corrected to obtain the target position with the highest flight energy consumption score of the multiple drones; wherein, the smaller the maximum flight energy consumption difference of the multiple drones, the higher the corresponding flight energy consumption score; driving the mobile drone nest to move to the target position, and enabling the multiple drones to fly from the target position to the multiple construction points for construction quality inspection, can improve the flexibility of construction quality inspection, and is conducive to balancing the flight energy consumption of each drone, allowing each drone to have similar electrical energy resources for construction quality inspection, which is conducive to balancing the construction quality inspection time of each construction point and enhancing the comprehensiveness of construction quality inspection.
[0026] A second aspect of this application provides a construction quality testing device, comprising:
[0027] The model and point acquisition module is used to acquire the architectural model of the target building to be inspected and multiple construction points;
[0028] The initial location acquisition module is used to acquire the initial location of the mobile machine nest based on the building model and multiple construction locations;
[0029] The flight energy consumption acquisition module is used to obtain the flight energy consumption of the multiple drones based on the multiple flight paths of the multiple drones flying from the initial point to the corresponding construction point.
[0030] The target location acquisition module is used to correct the location of the mobile nest based on the building model, the multiple construction locations, the initial location, the multiple flight paths, and the flight energy consumption of the multiple drones, so as to obtain the target location with high flight energy consumption scores of the multiple drones; wherein, the smaller the maximum flight energy consumption difference of the multiple drones, the higher the corresponding flight energy consumption score.
[0031] The construction quality inspection module is used to drive the mobile drone nest to the target location, so that the multiple drones can fly from the target location to the multiple construction locations to conduct construction quality inspection.
[0032] Compared to related technologies, the construction quality inspection device of this application obtains the initial position of the mobile drone nest based on the building model of the target building and multiple construction points; then, based on multiple flight paths of multiple drones flying from the initial position to the corresponding construction points, it obtains the flight energy consumption of the multiple drones; then, based on the building model, the multiple construction points, the initial position, the multiple flight paths, and the flight energy consumption of the multiple drones, it corrects the position of the mobile drone nest to obtain the target position with the highest flight energy consumption score for the multiple drones; wherein, the smaller the maximum flight energy consumption difference of the multiple drones, the higher the corresponding flight energy consumption score; driving the mobile drone nest to move to the target position, enabling the multiple drones to fly from the target position to the multiple construction points for construction quality inspection, can improve the flexibility of construction quality inspection, and is conducive to balancing the flight energy consumption of each drone, allowing each drone to have similar electrical energy resources for construction quality inspection, which is conducive to balancing the construction quality inspection time of each construction point and enhancing the comprehensiveness of construction quality inspection.
[0033] In one implementation, the initial location acquisition module is used to perform the following steps:
[0034] Based on the building model, obtain the three-dimensional ground data of the target building;
[0035] Based on the three-dimensional ground data, the ground point with the closest average distance to the multiple construction points is determined as the initial point.
[0036] In one implementation, the flight energy consumption acquisition module is used to perform the following steps:
[0037] Based on the building model, multiple flight paths are obtained for multiple drones to fly from the initial point around the obstacles to the corresponding construction point;
[0038] The flight path is decomposed based on the turning points to obtain multiple sub-paths of the multiple flight paths;
[0039] Based on the flight actions corresponding to the multiple sub-paths and the flight parameters of the UAV, the path energy consumption of the multiple sub-paths is obtained;
[0040] The flight energy consumption of the multiple UAVs is obtained based on the path energy consumption of the multiple sub-paths.
[0041] A third aspect of this application provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps of the construction quality inspection method described above.
[0042] A fourth aspect of this application provides a computer device including a storage device, a processor, and a computer program stored in the storage device and executable by the processor, wherein the processor executes the computer program to implement the steps of the construction quality inspection method described above.
[0043] To provide a clearer understanding of this application, the specific embodiments of this application will be described below in conjunction with the accompanying drawings. Attached Figure Description
[0044] Figure 1 This is a flowchart of a construction quality inspection method according to one embodiment of this application.
[0045] Figure 2 This is a flowchart of step S3 of a construction quality inspection method according to an embodiment of this application.
[0046] Figure 3 This is a schematic diagram of the module connection of a building construction quality inspection device according to an embodiment of this application.
[0047] 100. Construction quality testing device; 101. Model and location acquisition module; 102. Initial location acquisition module; 103. Flight energy consumption acquisition module; 104. Target location acquisition module; 105. Construction quality testing module. Detailed Implementation
[0048] To make the objectives, technical solutions, and advantages of this application clearer, the embodiments of this application will be described in further detail below with reference to the accompanying drawings.
[0049] It should be understood that the described embodiments are merely some, not all, of the embodiments of this application. All other embodiments obtained by those skilled in the art based on the embodiments of this application without creative effort are within the scope of protection of the embodiments of this application.
[0050] In the following description, when referring to the accompanying drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. In the description of this application, it should be understood that the terms "first," "second," "third," etc., are used only to distinguish similar objects and are not necessarily used to describe a specific order or sequence, nor should they be construed as indicating or implying relative importance. Those skilled in the art can understand the specific meaning of the above terms in this application according to the specific circumstances. The singular forms "a," "the," and "the" used in this application and the appended claims are also intended to include the plural forms, unless the context clearly indicates otherwise. The word "if" as used herein can be interpreted as "when," "when," or "in response to determination."
[0051] Furthermore, in the description of this application, unless otherwise stated, "multiple" means two or more. "And / or" describes the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A alone, A and B simultaneously, or B alone. The character " / " generally indicates that the preceding and following related objects have an "or" relationship.
[0052] Please see Figure 1 This is a flowchart of a construction quality inspection method according to the first embodiment of this application. The method includes:
[0053] S1: Obtain the building model of the target building to be inspected and multiple construction points.
[0054] The building model of the target building is a Building Information Modeling (BIM) model, which is based on various relevant information and data of the building project to create a building model and simulate the real information of the building through digital information simulation.
[0055] Building Information Modeling (BIM) has the following characteristics:
[0056] Information completeness: The BIM model contains all relevant information about the building project, such as geometry, materials, attributes, parameter settings, etc.
[0057] Information Relationships: Elements in a BIM model have rich data relationships, and when one element changes, other related elements are automatically updated.
[0058] Information consistency: BIM models ensure the accuracy and consistency of information, avoiding information conflicts and errors.
[0059] Visualization: BIM models can use 3D visualization technology to display the appearance, structure and internal layout of building projects, making them easier to understand and analyze.
[0060] Coordination: BIM models can perform clash detection and coordination between different disciplines during the design phase, reducing conflicts and changes during construction.
[0061] Simulation: BIM models can simulate the actual construction process, operation and maintenance of buildings, providing a basis for project decision-making.
[0062] Optimization: BIM models can optimize design and construction plans by analyzing data and information, thereby improving the economic and social benefits of projects.
[0063] Drawing capabilities: BIM models can generate various drawings and reports as needed, such as floor plans, elevations, sections, bills of quantities, etc.
[0064] S2: Based on the building model and multiple construction points, obtain the initial location of the mobile nest;
[0065] S3: Based on the multiple flight paths of the multiple drones flying from the initial point to the corresponding construction point, the flight energy consumption of the multiple drones is obtained;
[0066] Based on the flight path and the drone's flight information, the flight energy consumption of the drone along the flight path can be obtained. The drone's flight information includes parameters such as the drone's size, type, translational flight power consumption, and takeoff and landing power consumption.
[0067] S4: Based on the building model, the multiple construction points, the initial point, the multiple flight paths, and the flight energy consumption of the multiple UAVs, correct the point of the mobile nest to obtain the target point with high flight energy consumption scores for the multiple UAVs; wherein, the smaller the maximum flight energy consumption difference of the multiple UAVs, the higher the corresponding flight energy consumption score.
[0068] S5: Drive the mobile drone nest to the target location, so that the multiple drones can fly from the target location to the multiple construction locations to conduct construction quality inspection.
[0069] Compared to related technologies, the construction quality inspection method of this application obtains the initial position of a mobile drone nest based on the building model of the target building and multiple construction points; then, based on multiple flight paths of multiple drones flying from the initial position to the corresponding construction points, the flight energy consumption of the multiple drones is obtained; then, based on the building model, the multiple construction points, the initial position, the multiple flight paths, and the flight energy consumption of the multiple drones, the position of the mobile drone nest is corrected to obtain the target position with the highest flight energy consumption score of the multiple drones; wherein, the smaller the maximum flight energy consumption difference of the multiple drones, the higher the corresponding flight energy consumption score; driving the mobile drone nest to move to the target position, and enabling the multiple drones to fly from the target position to the multiple construction points for construction quality inspection, can improve the flexibility of construction quality inspection, and is conducive to balancing the flight energy consumption of each drone, allowing each drone to have similar electrical energy resources for construction quality inspection, which is conducive to balancing the construction quality inspection time of each construction point and enhancing the comprehensiveness of construction quality inspection.
[0070] In a feasible embodiment, step S2: obtaining the initial location of the mobile hoist nest based on the building model and multiple construction points, includes:
[0071] S21: Based on the building model, obtain the three-dimensional ground data of the target building;
[0072] The three-dimensional ground data includes data information on the base ground and the ground of each floor, including the ground height of the upper surface of each floor relative to the base ground, the width of each floor, etc.
[0073] S22: Based on the three-dimensional ground data, the ground point with the closest average distance to the plurality of construction points is determined as the initial point.
[0074] The ground points include those on the base floor and the floors of each building. The average distance between these points and multiple construction points can be obtained using the following formula:
[0075]
[0076] Where S is the average distance, n is the total number of construction sites, and x i y i z i Let x0, y0, and z0 be the coordinate parameters of the i-th construction point, and let x0, y0, and z0 be the coordinate parameters of the ground point.
[0077] In this embodiment, the initial point closest to the average distance of the multiple construction points can be accurately obtained by combining the three-dimensional ground data of the building model.
[0078] Please see Figure 2 In one feasible embodiment, step S3: obtaining the flight energy consumption of the multiple drones based on multiple flight paths of the multiple drones flying from the initial point to the corresponding construction point, includes:
[0079] S31: Based on the building model, obtain multiple flight paths for multiple drones to fly from the initial point around the obstacle to the corresponding construction point;
[0080] S32: Decompose the flight path according to the turning points to obtain multiple sub-paths of the multiple flight paths;
[0081] The sub-paths include ascending paths, descending paths, and translation paths in various directions.
[0082] S33: Based on the flight actions corresponding to the multiple sub-paths and the flight parameters of the UAV, obtain the path energy consumption of the multiple sub-paths.
[0083] Flight parameters include the power consumption of the UAV during ascent, descent, and translation.
[0084] S34: Based on the path energy consumption of the multiple sub-paths, obtain the flight energy consumption of the multiple UAVs.
[0085] The sum of the energy consumption of multiple sub-paths corresponding to the same flight path is the flight energy consumption of the corresponding UAV flying along the flight path.
[0086] In this embodiment, by breaking down the flight path, the flight energy consumption of the UAV flying along the flight path can be predicted more accurately.
[0087] In a feasible embodiment, step S4: correcting the location of the mobile nest based on the building model, the multiple construction points, the initial location, the multiple flight paths, and the flight energy consumption of the multiple UAVs, to obtain the target location with high flight energy consumption scores for the multiple UAVs, includes:
[0088] S41: Obtain the nest location correction network model; wherein, the nest location correction network model is trained based on multiple nest location correction training samples, the nest location correction training samples include building model samples, construction point samples, initial point samples, flight path samples, flight energy consumption samples and target point samples; wherein, the maximum flight energy consumption difference of multiple UAVs corresponding to the target point samples is less than a preset difference threshold.
[0089] The preset difference threshold is set by the user. The nest location correction network model can be obtained by training a deep learning network model using multiple nest location correction training samples.
[0090] S42: Input the building model, the multiple construction points, the initial point, the multiple flight paths and the corresponding flight energy consumption into the trained nest point correction network model to obtain the target point.
[0091] In this embodiment, the building model, the multiple construction points, the initial point, the multiple flight paths, and the corresponding flight energy consumption are input into the trained nest point correction network model to accurately obtain the target point.
[0092] In one feasible embodiment, the drone is equipped with a construction quality inspection edge model. This edge model is a lightweight network model of the construction quality inspection cloud model, which helps reduce the computational load and energy consumption of the drone during construction quality inspection. The construction quality inspection cloud model is a big data model trained on a large number of construction quality inspection samples, including construction image samples and corresponding quality inspection results.
[0093] S5: The step of driving the mobile drone nest to the target location, and causing the multiple drones to fly from the target location to the multiple construction sites for construction quality inspection, includes:
[0094] After driving the mobile drone nest to the target location, the multiple drones are driven to fly from the target location to the corresponding construction location, so as to take construction images of the corresponding construction location through the drones, and then perform construction quality inspection on the construction images through the construction quality inspection edge model loaded by the drones.
[0095] In some implementations, if the construction quality inspection determines that there is an anomaly in the construction quality, the drone will issue a voice alert to notify the construction personnel at the construction site to suspend construction and upload the corresponding construction images to the cloud server. The cloud server's construction quality inspection cloud model will then re-inspect the construction images. If the re-inspection still determines that there is an anomaly in the construction quality, the cloud server will issue an anomaly notification to the construction supervisor. If the re-inspection determines that the construction quality is normal, the drone will notify the construction personnel at the construction site to continue construction. The construction images and the results of the re-inspection will be used as training samples to train the construction quality inspection edge model, thereby improving the accuracy of the construction quality inspection edge model.
[0096] In this embodiment, the construction quality of the construction site is detected by using the construction quality detection edge model of the UAV to quickly obtain the construction quality detection results on site.
[0097] Please see Figure 3 The second embodiment of this application provides a construction quality inspection device 100, comprising:
[0098] The model and point acquisition module 101 is used to acquire the building model and multiple construction points of the target building to be inspected;
[0099] The initial location acquisition module 102 is used to acquire the initial location of the mobile machine nest based on the building model and multiple construction locations;
[0100] The flight energy consumption acquisition module 103 is used to obtain the flight energy consumption of the multiple drones based on the multiple flight paths of the multiple drones flying from the initial point to the corresponding construction point.
[0101] The target location acquisition module 104 is used to correct the location of the mobile nest based on the building model, the multiple construction locations, the initial location, the multiple flight paths and the flight energy consumption of the multiple UAVs, so as to obtain the target location with high flight energy consumption scores of the multiple UAVs; wherein, the smaller the maximum flight energy consumption difference of the multiple UAVs, the higher the corresponding flight energy consumption score.
[0102] The construction quality inspection module 105 is used to drive the mobile drone nest to the target location, so that the multiple drones can fly from the target location to the multiple construction locations to carry out construction quality inspection.
[0103] Compared to related technologies, the construction quality inspection device 100 of this application obtains the initial position of the mobile drone nest based on the building model of the target building and multiple construction points; then, based on multiple flight paths of multiple drones flying from the initial position to the corresponding construction points, it obtains the flight energy consumption of the multiple drones; then, based on the building model, the multiple construction points, the initial position, the multiple flight paths, and the flight energy consumption of the multiple drones, it corrects the position of the mobile drone nest to obtain the target position with the highest flight energy consumption score for the multiple drones; wherein, the smaller the maximum flight energy consumption difference of the multiple drones, the higher the corresponding flight energy consumption score; driving the mobile drone nest to move to the target position, enabling the multiple drones to fly from the target position to the multiple construction points for construction quality inspection, can improve the flexibility of construction quality inspection, and is conducive to balancing the flight energy consumption of each drone, allowing each drone to have similar electrical energy resources for construction quality inspection, which is conducive to balancing the construction quality inspection time of each construction point and enhancing the comprehensiveness of construction quality inspection.
[0104] In one implementation, the initial point acquisition module 102 is used to perform the following steps:
[0105] Based on the building model, obtain the three-dimensional ground data of the target building;
[0106] Based on the three-dimensional ground data, the ground point with the closest average distance to the multiple construction points is determined as the initial point.
[0107] In one implementation, the flight energy consumption acquisition module 103 is used to perform the following steps:
[0108] Based on the building model, multiple flight paths are obtained for multiple drones to fly from the initial point around the obstacles to the corresponding construction point;
[0109] The flight path is decomposed based on the turning points to obtain multiple sub-paths of the multiple flight paths;
[0110] Based on the flight actions corresponding to the multiple sub-paths and the flight parameters of the UAV, the path energy consumption of the multiple sub-paths is obtained;
[0111] The flight energy consumption of the multiple UAVs is obtained based on the path energy consumption of the multiple sub-paths.
[0112] It should be noted that the construction quality testing device 100 provided in the second embodiment of this application is only illustrated by the above-described division of functional modules when performing the construction quality testing method. In actual applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above. In addition, the construction quality testing device 100 provided in the second embodiment of this application and the construction quality testing method of the first embodiment of this application belong to the same concept, and its implementation process is detailed in the method embodiment, which will not be repeated here.
[0113] A third aspect of this application provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps of the construction quality inspection method described above.
[0114] A fourth aspect of this application provides a computer device including a storage device, a processor, and a computer program stored in the storage device and executable by the processor, wherein the processor executes the computer program to implement the steps of the construction quality inspection method described above.
[0115] The device embodiments described above are merely illustrative. The components described as separate parts may or may not be physically separate, and the components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this application according to actual needs. Those skilled in the art can understand and implement this without any inventive effort.
[0116] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.
[0117] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 The computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function selected in one or more boxes.
[0118] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function selected in one or more boxes.
[0119] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.
[0120] Memory may include non-persistent memory in computer-readable media, such as random access memory (RAM) and / or non-volatile memory, like read-only memory (ROM) or flash RAM. Memory is an example of computer-readable media.
[0121] Computer-readable media includes both permanent and non-permanent, removable and non-removable media that can store information using any method or technology. Information can be computer-readable instructions, data structures, modules of programs, or other data. Examples of computer storage media include, but are not limited to, phase-change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, CD-ROM, digital versatile optical disc (DVD) or other optical storage, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other non-transferable medium that can be used to store information accessible by a computing device. As defined herein, computer-readable media does not include transient computer-readable media, such as modulated data signals and carrier waves.
[0122] It should also be noted that the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element.
[0123] The above are merely embodiments of this application and are not intended to limit the scope of this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the scope of the claims of this application.
Claims
1. A method for inspecting the quality of building construction, characterized in that, include: Obtain the architectural model of the target building to be inspected and multiple construction points; Based on the building model and multiple construction points, the initial location of the mobile nest is obtained; The flight energy consumption of the multiple drones is obtained based on the multiple flight paths of the multiple drones flying from the initial point to the corresponding construction point; Based on the building model, the multiple construction points, the initial point, the multiple flight paths, and the flight energy consumption of the multiple drones, the point of the mobile nest is corrected to obtain the target point with high flight energy consumption scores for the multiple drones; wherein, the smaller the maximum flight energy consumption difference of the multiple drones, the higher the corresponding flight energy consumption score. The mobile drone nest is driven to move to the target location, so that the multiple drones can fly from the target location to the multiple construction sites to conduct construction quality inspection.
2. The construction quality inspection method according to claim 1, characterized in that, The step of obtaining the initial location of the mobile drone nest based on the building model and multiple construction points includes: Based on the building model, obtain the three-dimensional ground data of the target building; Based on the three-dimensional ground data, the ground point with the closest average distance to the multiple construction points is determined as the initial point.
3. The construction quality inspection method according to claim 1, characterized in that, The step of obtaining the flight energy consumption of the multiple drones based on the multiple flight paths of the multiple drones flying from the initial point to the corresponding construction point includes: Based on the building model, multiple flight paths are obtained for multiple drones to fly from the initial point around the obstacles to the corresponding construction point; The flight path is decomposed based on the turning points to obtain multiple sub-paths of the multiple flight paths; Based on the flight actions corresponding to the multiple sub-paths and the flight parameters of the UAV, the path energy consumption of the multiple sub-paths is obtained; The flight energy consumption of the multiple UAVs is obtained based on the path energy consumption of the multiple sub-paths.
4. The construction quality inspection method according to claim 1, characterized in that, The step of correcting the location of the mobile drone nest based on the building model, the multiple construction points, the initial location, the multiple flight paths, and the flight energy consumption of the multiple drones, to obtain the target location with high flight energy consumption scores for the multiple drones, includes: A nest location correction network model is obtained; wherein the nest location correction network model is trained based on multiple nest location correction training samples, the nest location correction training samples include building model samples, construction point samples, initial point samples, flight path samples, flight energy consumption samples and target point samples; wherein the maximum flight energy consumption difference of multiple UAVs corresponding to the target point sample is less than a preset difference threshold. The building model, the multiple construction sites, the initial site, the multiple flight paths, and the corresponding flight energy consumption are input into the trained nest site correction network model to obtain the target site.
5. The construction quality inspection method according to claim 1, characterized in that, The drone is equipped with a construction quality inspection edge model; The step of driving the mobile drone nest to the target location, and causing the multiple drones to fly from the target location to the multiple construction sites for construction quality inspection, includes: After driving the mobile drone nest to the target location, the multiple drones are driven to fly from the target location to the corresponding construction location, so as to take construction images of the corresponding construction location through the drones, and then perform construction quality inspection on the construction images through the construction quality inspection edge model loaded by the drones.
6. A construction quality testing device, characterized in that, include: The model and point acquisition module is used to acquire the architectural model of the target building to be inspected and multiple construction points; The initial location acquisition module is used to acquire the initial location of the mobile machine nest based on the building model and multiple construction locations; The flight energy consumption acquisition module is used to obtain the flight energy consumption of the multiple drones based on the multiple flight paths of the multiple drones flying from the initial point to the corresponding construction point. The target location acquisition module is used to correct the location of the mobile nest based on the building model, the multiple construction locations, the initial location, the multiple flight paths, and the flight energy consumption of the multiple drones, so as to obtain the target location with high flight energy consumption scores of the multiple drones; wherein, the smaller the maximum flight energy consumption difference of the multiple drones, the higher the corresponding flight energy consumption score. The construction quality inspection module is used to drive the mobile drone nest to the target location, so that the multiple drones can fly from the target location to the multiple construction locations to conduct construction quality inspection.
7. The construction quality testing device according to claim 6, characterized in that, The initial location acquisition module is used to perform the following steps: Based on the building model, obtain the three-dimensional ground data of the target building; Based on the three-dimensional ground data, the ground point with the closest average distance to the multiple construction points is determined as the initial point.
8. The construction quality testing device according to claim 6, characterized in that, The flight energy consumption acquisition module is used to perform the following steps: Based on the building model, multiple flight paths are obtained for multiple drones to fly from the initial point around the obstacles to the corresponding construction point; The flight path is decomposed based on the turning points to obtain multiple sub-paths of the multiple flight paths; Based on the flight actions corresponding to the multiple sub-paths and the flight parameters of the UAV, the path energy consumption of the multiple sub-paths is obtained; The flight energy consumption of the multiple UAVs is obtained based on the path energy consumption of the multiple sub-paths.
9. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by the processor, it implements the steps of the construction quality inspection method as described in any one of claims 1 to 5.
10. A computer device, characterized in that: It includes a storage device, a processor, and a computer program stored in the storage device and executable by the processor, wherein the processor executes the computer program to implement the steps of the construction quality inspection method as described in any one of claims 1 to 5.