Method and device for surveying and mapping building and electronic equipment

Abstract

The invention provides a method and device for surveying and mapping a building, electronic equipment and a non-instantaneous computer readable storage medium, and the method comprises the steps: carrying out the feature extraction of the three-dimensional data of the building, and obtaining the frame structure data of the building; performing three-dimensional modeling on the building by using the frame structure data to obtain a three-dimensional model of the building; and performing quality detection on the building by using the three-dimensional model and a preset building information model. According to the embodiment of the invention, the frame structure data of the building is obtained by performing feature extraction on the three-dimensional data of the building, so that automatic modeling of the building is realized, and the working efficiency of building surveying and mapping is improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of building surveying, and in particular, to a method and device for surveying a building, an electronic device, and a non-transitory computer-readable storage medium. BACKGROUND

[0002] With the acceleration of urbanization and the rapid development of the building industry, building engineering quality problems are directly related to the safety, durability and performance of buildings, and also affect the safety of life and property of residents and social and economic benefits. When monitoring the quality of building engineering, due to the immaturity of technology, low labor productivity, and large amount of manual surveying work, building projects generally have construction progress delays and quality problems caused by construction errors.

[0003] Therefore, how to transform from manual surveying to automatic surveying, faster and more accurate surveying of construction quality and construction progress, so as to discover deviations as soon as possible and make intelligent decisions and take corrective measures, is a problem that modern buildings urgently need to solve. SUMMARY

[0004] The present application aims to provide a method and device for surveying a building, an electronic device, and a non-transitory computer-readable storage medium to solve the problem of large amount of manual surveying work.

[0005] According to an aspect of the present application, a method for surveying a building is provided, comprising:

[0006] extracting features from three-dimensional data of the building to obtain frame structure data of the building;

[0007] performing three-dimensional modeling on the building using the frame structure data to obtain a three-dimensional model of the building;

[0008] performing quality detection on the building using the three-dimensional model and a pre-set building information model.

[0009] According to some embodiments, before extracting features from three-dimensional data of the building to obtain frame structure data of the building, the method further comprises:

[0010] performing data collection on the building to obtain three-dimensional point cloud data of the building;

[0011] preprocessing the three-dimensional point cloud data to obtain the three-dimensional data.

[0012] According to some embodiments, preprocessing the three-dimensional point cloud data to obtain the three-dimensional data comprises:

[0013] After the three-dimensional point cloud data is registered, denoised and / or down-sampled, the three-dimensional data is obtained.

[0014] According to some embodiments, the frame structure data comprises frame feature data and geometry data of the building, wherein the frame feature data comprises data of floors, data of columns and data of beams in the frame of the building, and the geometry data comprises length, width, height of the columns and the beams and / or thickness of the floors.

[0015] According to some embodiments, the three-dimensional data of the building is subjected to feature extraction to obtain frame structure data of the building, comprising:

[0016] The three-dimensional data is subjected to feature extraction to determine the frame feature data;

[0017] The point cloud density of the three-dimensional data is subjected to Euclidean clustering to identify columns in the building;

[0018] The length and width of the columns are obtained by using the cross section of the columns;

[0019] The three-dimensional point cloud data is subjected to density analysis to obtain the height of the columns after clustering analysis;

[0020] The point cloud density of the beams is detected by using a histogram method to determine the length, width and height of the beams; and / or

[0021] The distance between the upper and lower planes of the floor is calculated by using the three-dimensional data to obtain the thickness of the floor.

[0022] According to some embodiments, the quality detection comprises deformation detection and / or damage assessment.

[0023] According to some embodiments, the method further comprises: using the three-dimensional model to assess the construction progress of the building.

[0024] According to an aspect of the present application, a device for surveying a building is provided, comprising:

[0025] A frame structure data extraction unit is configured to extract features from the three-dimensional data of the building to obtain frame structure data of the building.

[0026] A three-dimensional model modeling unit is configured to model the building in three dimensions by using the structure data to obtain a three-dimensional model of the building.

[0027] A detection unit is configured to use the three-dimensional model and a pre-set building information model to detect the quality of the building.

[0028] According to an aspect of the present application, an electronic device is provided, comprising: a processor; a memory for storing a computer program; when the computer program is executed by the processor, the processor implements the method according to any one of the preceding embodiments.

[0029] According to an aspect of the present application, a non-transitory computer-readable storage medium is provided, having computer-readable instructions stored thereon, when the instructions are executed by a processor, the processor executes the method according to any one of the preceding embodiments.

[0030] According to the embodiments of the present application, the frame structure data of the building is obtained by feature extraction on the three-dimensional data of the building, not only the automatic modeling of the building is realized, but also the working efficiency of the building surveying and mapping is improved.

[0031] It should be understood that the above general description and the following detailed description are only exemplary and do not limit the present application. BRIEF DESCRIPTION OF DRAWINGS

[0032] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed to be used in the embodiment description will be briefly introduced. The above and other objects, features and advantages of the present application will become more apparent through the detailed description of the example embodiments with reference to the drawings.

[0033] Figure 1 A method flowchart for surveying and mapping a building according to an example embodiment of the present application is shown.

[0034] Figure 2a A three-dimensional point cloud data schematic diagram according to an example embodiment of the present application is shown.

[0035] Figure 2b A frame unit schematic diagram according to an example embodiment of the present application is shown.

[0036] Figure 2c A noise reduction schematic diagram according to an example embodiment of the present application is shown.

[0037] Figure 2d A down-sampling schematic diagram according to an example embodiment of the present application is shown.

[0038] Figure 2e A frame feature data schematic diagram according to an example embodiment of the present application is shown.

[0039] Figure 2f A three-dimensional model schematic diagram according to an example embodiment of the present application is shown.

[0040] Figure 3A process diagram for determining floor structure data using three-dimensional data is shown in accordance with an example embodiment of the present application.

[0041] Figure 4 A process diagram for determining column structure data in a building using three-dimensional data is shown in accordance with an example embodiment of the present application.

[0042] Figure 5 A process diagram for determining beam structure data in a building using three-dimensional data is shown in accordance with an example embodiment of the present application.

[0043] Figure 6a A three-dimensional point cloud data diagram is shown in accordance with an example embodiment of the present application.

[0044] Figure 6b A three-dimensional model diagram is shown in accordance with an example embodiment of the present application.

[0045] Figure 7a A three-dimensional point cloud data diagram is shown in accordance with an example embodiment of the present application.

[0046] Figure 7b A three-dimensional model diagram is shown in accordance with an example embodiment of the present application.

[0047] Figure 8a An implementation diagram for surveying a building is shown in accordance with an example embodiment of the present application.

[0048] Figure 8b A method flow diagram for surveying a building is shown in accordance with an example embodiment of the present application.

[0049] Figure 9 A registration diagram for three-dimensional point cloud data is shown in accordance with an example embodiment of the present application.

[0050] Figure 10 A block diagram of an apparatus for surveying a building is shown in accordance with an example embodiment of the present application.

[0051] Figure 11 An electronic device is shown in accordance with an example embodiment of the present application. DETAILED DESCRIPTION

[0052] Example embodiments now will be described more fully hereinafter with reference to the accompanying drawings; however, the example embodiments can be implemented in many different forms and should not be construed as limited to the embodiments set forth herein; rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the example embodiments to those skilled in the art. Like reference numerals refer to like elements throughout the several views.

[0053] The described features, structures, or characteristics can be combined in any suitable manner in one or more embodiments. In the following description, numerous specific details are provided to give a thorough understanding of embodiments of the disclosure. One skilled in the relevant art will recognize, however, that the technology can be practiced without one or more of the specific details, or with other methods, components, materials, and so forth. In some instances, detailed descriptions of well-known structures, methods, devices, materials, and so forth are omitted so as to not obscure the description of the technology.

[0054] The flowcharts shown in the drawings are merely illustrative and do not necessarily include all the contents and operations / steps, nor are they necessarily executed in the order described. For example, some operations / steps can be further broken down, and some operations / steps can be combined or partially combined, so the actual execution order can be changed according to actual conditions.

[0055] The terms "first", "second", and so on in the specification and claims of the present application and the above-described drawings are used to distinguish different objects, and are not used to describe a specific order. In addition, the terms "include" and "have" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or device that includes a series of steps or units is not limited to the listed steps or units, but can optionally include steps or units not listed, or can optionally include other steps or units inherent to the process, method, product, or device.

[0056] The specific embodiments according to the present application are described in detail below with reference to the accompanying drawings.

[0057] Figure 1 A method flowchart for mapping a building according to an example embodiment of the present application is shown in FIG. 1. Figure 1 The method shown includes steps S101, S103, and S105. The method for mapping a building according to an example embodiment of the present application is described in detail below with reference to Figure 1

[0058] As shown in FIG. 1, in step S101, feature extraction is performed on three-dimensional data of a building to obtain frame structure data of the building. Figure 1 According to an embodiment of the present application, before step S101, data collection is also needed for the building to obtain three-dimensional point cloud data of the building; then, the three-dimensional point cloud data is preprocessed to obtain the three-dimensional data.

[0059]

[0060] ​​In the prior art, field mapping is usually performed by professional surveyors using tools such as laser range finders, tape measures, etc. to actually measure spatial dimension information such as length, width, height, etc. of a house. Based on high-precision three-dimensional point cloud data obtained in the field, the frame structure data of the building (e.g. length, width, height dimension information of building components such as boards, columns and beams, etc.) is obtained by feature extraction on the three-dimensional data of the building.

[0061] It should be noted that the present application does not limit the specific implementation of data collection of the building. In some embodiments, a laser and visual SLAM (Simultaneous Localization and Mapping, also known as real-time positioning and mapping) scanner or a shape capturing machine can be used to collect three-dimensional point cloud data of the building, as shown in Figure 2a .

[0062] In other embodiments, the three-dimensional point cloud data also needs to be cut before being preprocessed, to obtain a frame unit, as shown in Figure 2b . After that, the preprocessing operation is performed based on the frame unit.

[0063] In order to facilitate subsequent data processing, in some embodiments, the point cloud data is shifted to the origin position before preprocessing.

[0064] According to embodiments of the present application, the preprocessing of the three-dimensional point cloud data includes registration, denoising and downsampling operations on the three-dimensional point cloud data to obtain the three-dimensional data.

[0065] In specific embodiments, when the three-dimensional point cloud data is registered, the four edges of a column are calibrated and the point cloud normal is perpendicular to the ground to perform the registration operation. By finding the four corner points of the column section, the corner points are sorted to ensure that they are arranged in a fixed order, the required rotation angle is calculated through the corner points, and finally the entire point cloud is rotated and transformed to align the column to the coordinate axis.

[0066] If the ground has complex textures or obstacles, there will be interference from non-ground areas. The present application first performs conditional filtering to make a slice at 2m to 2.3m at one end of the column to avoid the interference of non-ground areas.

[0067] In other embodiments, when the three-dimensional point cloud data is denoised, statistical filtering is used for statistical filtering to remove outliers, as shown in Figure 2c .

[0068] In other embodiments, when the three-dimensional point cloud data is downsampled, the point cloud in space is divided into voxels, and then voxel grid filtering is used to perform the downsampling operation, as shown in Figure 2d or 2e.

[0069] According to an embodiment of the present application, the frame structure data comprises frame feature data and geometry data of the building, wherein the frame feature data comprises data of floors, data of columns and data of beams in the frame of the building, and the geometry data comprises length, width, height of the columns and the beams and / or thickness of the floors.

[0070] In some embodiments, the frame feature data is obtained by feature extraction on the three-dimensional point cloud data, for example, floor, column, beam and the like data. The start of the face of the frame feature data is determined according to the density data of the three-dimensional point cloud, so that the length, width and height of the corresponding frame feature data can be determined according to the coordinate data of the frame feature data.

[0071] In step S103, the three-dimensional model of the building is obtained by using the frame structure data to perform three-dimensional modeling on the building.

[0072] The existing three-dimensional reconstruction technology converts two-dimensional photo data of geographical areas, scenes or objects in the physical world into high-definition real scene three-dimensional digital models through diversified means such as multi-view stereo reconstruction, laser scanning, structured light scanning and deep neural network. Due to the deep learning method in the existing point cloud surveying and mapping technology, a large number of samples and a relatively long training time are required, which is high in cost and long in period. Moreover, the three-dimensional modeling tool in the prior art cannot automatically read the frame structure data, and needs to be manually imported. In order to facilitate the three-dimensional modeling of the building and improve the modeling efficiency of the building, according to an embodiment of the present application, the frame structure data is generated into a Json file according to a preset format, and in step S103, the coordinate data of the frame structure is read from the Json file by using a dynamic link library generated by C#, and then a three-dimensional modeling tool is used to generate a three-dimensional model of the building, as shown in Figure 2f .

[0073] In a specific embodiment, the Revit software can be used to perform three-dimensional reconstruction on the frame structure data to realize the drawing of the frame feature data. Since a large number of samples and a relatively long training time are not required, the period is short and the cost is low.

[0074] In step S105, the three-dimensional model and the preset building information model are used to perform quality detection on the building.

[0075] According to an embodiment of the present application, when the quality of the building is detected, the frame structure data in the three-dimensional model and the frame structure data in the preset building information model are compared in size and shape, so as to realize the quality detection of the building. The quality detection comprises deformation detection and / or damage assessment. According to another embodiment of the present application, the method further comprises using the three-dimensional model to evaluate the construction progress of the building. Figure 1 ​

[0076] For example, the completed framework structure is determined according to the three-dimensional model, and is compared with preset planning data, so as to evaluate the construction progress of the building.

[0077] In some embodiments, when a quality problem or project delay occurs, early warning information is sent to relevant parties, so as to realize real-time monitoring of the building engineering.

[0078] According to Figure 1 As shown in the embodiments, the framework structure data of the building is obtained by feature extraction on the three-dimensional data of the building, which not only realizes automatic modeling of the building, but also improves the working efficiency of building surveying and mapping.

[0079] Figure 3 A process diagram for determining floor structure data by using three-dimensional data is shown according to an example embodiment of the present application.

[0080] As Figure 3 shown, in step S301, the three-dimensional point cloud data of the building is segmented to obtain the upper plane and lower plane data of the floor.

[0081] In step S303, the thickness data of the floor is calculated by using the upper plane and lower plane data of the floor.

[0082] It should be noted that, in order to improve the calculation accuracy of the height data, in step S303, when calculating the height of the floor, it is necessary to ensure that the normals of the upper and lower planes of the floor are perpendicular.

[0083] For example, the upper plane and lower plane data of the floor are calculated by using a plane fitting algorithm or a plane distance algorithm.

[0084] In some embodiments, the coordinate data of the floor is also determined by using the three-dimensional point cloud data of the building through the established coordinate system.

[0085] Figure 4 A process diagram for determining column structure data in a building by using three-dimensional data is shown according to an example embodiment of the present application. In the prior art, the principal component analysis method based on the PCL library is used to determine the clusters after clustering, which needs to be based on the size of the column in the design drawing, to perform conditional filtering, to segment the column components, and to obtain the column of the building. In the present application, the coordinates in different directions are projected based on the PCL library, the edge of the column is determined by the change of the point cloud density, and the length, width and height are determined, without the need to know the size of the column in advance, which is more suitable.

[0086] As Figure 4As shown, in step S401, the point cloud density of the three-dimensional data is Euclidean clustered to identify the column in the building. In step S403, the length and width of the column are obtained by using the cross section of the column.

[0087] According to the embodiments of the present application, in step S403, the column is first cut, the column cross section is calculated, the x-axis and y-axis coordinates of the column in the preset coordinate system are obtained, and then the length and width of the column are obtained.

[0088] In step S405, the three-dimensional point cloud data is analyzed by density to obtain the height of the column after clustering analysis.

[0089] In some embodiments, the height of the column is calculated by detecting the point cloud density on the Z-axis of the preset coordinate system through the density analysis algorithm. In some embodiments, the plane where the x-axis and y-axis of the preset coordinate system are located is parallel to the cross section of the column, and the plane where the z-axis is located is perpendicular to the plane where the x-axis and y-axis are located.

[0090] In specific embodiments, in order to avoid the influence of ground vehicles, cutting is performed at two meters of the column height.

[0091] Figure 5 A process diagram for determining the beam structure data in the building using three-dimensional data according to an example embodiment of the present application is shown. In the prior art, some are based on deep learning technology, which requires a large amount of data set and a long training period, and some are based on principal component analysis method of PCL library, which needs to know the design data of the beam in advance, and performs conditional filtering to complete the segmentation of the beam components. The present application projects the beam on the coordinate axes of the preset coordinate system, checks the boundary of the beam by the point cloud density through the histogram method, and does not need to know the design size of the beam in advance, and has wider applicability.

[0092] As Figure 5 shown, in step S501, the three-dimensional point cloud data of the building is cut to obtain the point cloud data of the beam. The determined beam of the building includes the main beam and the secondary beam.

[0093] In some embodiments, the three-dimensional point cloud data of the building is conditionally filtered based on the design data of the beam to complete the segmentation of the beam components.

[0094] In step S503, the three-dimensional point cloud data is analyzed by density at the position of the beam to calculate the length, width and height data of the beam in the horizontal and vertical directions.

[0095] In some embodiments, when the three-dimensional point cloud data is analyzed by density at the position of the beam, the point cloud within the range of mean value plus or minus three standard deviations is determined by using the point cloud density through the histogram method to determine the boundary of the beam component in the preset three-dimensional coordinate axis, and the length, width and height are calculated through the coordinate data of the beam.

[0096] According to the embodiments of the present application, in Figure 3 , Figure 4 , Figure 5 After that, three-dimensional reconstruction is performed using the obtained structural data of the building to obtain the corresponding three-dimensional model, as shown in Figure 6a (4 columns and 7 beams) and Figure 6b (4 columns and 17 beams) are different building point cloud files cut out, Figure 7a and Figure 7b are the corresponding three-dimensional reconstruction.

[0097] Figure 8a An implementation manner diagram of mapping a building according to an example embodiment of the present application is shown, Figure 8b A method flowchart of mapping a building according to an example embodiment of the present application is shown. The implementation process of mapping a building according to an example embodiment of the present application is described in detail below in combination with Figure 8a and Figure 8b .

[0098] As shown in Figure 8a and 8b , first, point cloud data of the building is collected.

[0099] For example, the point cloud data is collected by a shape keeping machine 360, and the laser and visual SLAM (Simultaneous Localization and Mapping, also known as real-time positioning and map construction) technology is used to process the point cloud data.

[0100] Then, the three-dimensional point cloud data is cut to obtain a frame unit.

[0101] The three-dimensional point cloud data is registered, as shown in Figure 9 , the farthest point, i.e., the corner point, is found out by using the point-to-diagonal distance. Then, the corner points are sorted to ensure that they are arranged in a fixed order. The required rotation angle is calculated through the corner points, and finally the entire point cloud is rotated and transformed to align the columns to the coordinate axis.

[0102] Then, the three-dimensional point cloud data is preprocessed, including registration, denoising and downsampling operations on the three-dimensional point cloud data, to obtain three-dimensional data.

[0103] Then, the plates, columns and beams in the three-dimensional data are respectively filtered and measured, and the plates, columns and beams in the three-dimensional data are calculated and saved in the Json format.

[0104] As shown in Figure 8bAs shown, when measuring the slab, the 3D data is segmented to obtain the upper and lower slab planes, and the thickness (i.e., height) of the slab is calculated using the upper and lower slab plane data through a plane fitting algorithm or a plane distance algorithm.

[0105] When measuring the columns, the columns are first cut, and different columns are obtained through Euclidean clustering algorithm. By calculating the column cross-section, the length and width of different columns are obtained according to their positions in the preset coordinate system. Finally, the column height is obtained by detecting the point cloud density and using density analysis algorithm.

[0106] When measuring the beam, the point cloud density of the beam in the preset coordinate system is detected by the histogram method, and the length, width and height of the beam are calculated by algorithms such as density analysis and boundary extraction.

[0107] Next, the framework structure data is read from the JSON file using a dynamic link library generated in C#, and then a 3D model of the building is generated using a 3D modeling tool (such as Revit).

[0108] Finally, the generated 3D model is compared with the point cloud data of the design drawings to determine the differences between the two, thereby confirming whether there are quality problems or project delays. When the triggering conditions are met, an early warning is issued and pushed to the relevant parties.

[0109] The above description primarily focuses on the methodological aspects of the embodiments of this application. Those skilled in the art should readily recognize that, based on the operations or steps described in conjunction with the embodiments disclosed herein, this application can be implemented in hardware or a combination of hardware and computer software. Those skilled in the art can implement the described functionality in different ways for each specific operation or method, and such implementations should not be considered beyond the scope of this application.

[0110] The apparatus embodiments of this application are described below. For details not described in the apparatus embodiments of this application, please refer to the method embodiments of this application.

[0111] Figure 10 A block diagram of an apparatus for surveying a building according to an example embodiment of this application is shown, such as... Figure 10 The device shown includes a frame structure data extraction unit 1001, a 3D model modeling unit 1003, and a detection unit 1005. The frame structure data extraction unit 1001 extracts features from the 3D data of the building to obtain the building's frame structure data; the 3D model modeling unit 1003 uses the structural data to create a 3D model of the building to obtain the building's 3D model; and the detection unit 1005 uses the 3D model and a preset building information model to perform quality inspection on the building.

[0112] Figure 11 An electronic device according to an exemplary embodiment of this application is shown. Reference is made below. Figure 11 To describe an electronic device 200 according to this embodiment of the present application. Figure 11 The electronic device 200 shown is merely an example and should not impose any limitations on the functionality and scope of use of the embodiments of this application.

[0113] like Figure 11 As shown, the electronic device 200 is presented in the form of a general-purpose computing device. The components of the electronic device 200 may include, but are not limited to: at least one processing unit 210, at least one storage unit 220, a bus 230 connecting different system components (including storage unit 220 and processing unit 210), a display unit 240, etc.

[0114] The storage unit stores program code, which can be executed by the processing unit 210 to perform the methods described in this specification according to various exemplary embodiments of this application. For example, the processing unit 210 can perform, for example... Figure 1 The method shown.

[0115] Storage unit 220 may include readable media in the form of volatile storage units, such as random access memory (RAM) 2201 and / or cache memory 2202, and may further include read-only memory (ROM) 2203.

[0116] Storage unit 220 may also include a program / utility 2204 having a set (at least one) program module 2205, such program module 2205 including but not limited to: operating system, one or more application programs, other program modules and program data, each or some combination of these examples may include an implementation of a network environment.

[0117] Bus 230 can represent one or more of several types of bus structures, including a memory cell bus or memory cell controller, a peripheral bus, a graphics acceleration port, a processing unit, or a local bus using any of the various bus structures.

[0118] Electronic device 200 can also communicate with one or more external devices 300 (e.g., keyboard, pointing device, Bluetooth device, etc.), and with one or more devices that enable a user to interact with electronic device 200, and / or with any device that enables electronic device 200 to communicate with one or more other computing devices (e.g., router, modem, etc.). This communication can be performed via input / output (I / O) interface 250. Furthermore, electronic device 200 can also communicate with one or more networks (e.g., local area network (LAN), wide area network (WAN), and / or public networks, such as the Internet) via network adapter 260. Network adapter 260 can communicate with other modules of electronic device 200 via bus 230. It should be understood that, although not shown in the figures, other hardware and / or software modules can be used in conjunction with electronic device 200, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems.

[0119] Through the above description of the embodiments, those skilled in the art will readily understand that the exemplary embodiments described herein can be implemented by software or by combining software with necessary hardware. The technical solutions according to the embodiments of this application can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (such as a CD-ROM, USB flash drive, external hard drive, etc.) or on a network, including several instructions to cause a computing device (such as a personal computer, server, or network device, etc.) to execute the methods described above according to the embodiments of this application.

[0120] Software products may employ any combination of one or more readable media. A readable medium may be a readable signal medium or a readable storage medium. A readable storage medium may be, for example,, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of readable storage media (a non-exhaustive list) include: electrical connections with one or more wires, portable disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof.

[0121] Computer-readable storage media may include data signals propagated in baseband or as part of a carrier wave, carrying readable program code. Such propagated data signals may take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. A readable storage medium may also be any readable medium other than a readable storage medium that can transmit, propagate, or transfer a program for use by or in connection with an instruction execution system, apparatus, or device. The program code contained on the readable storage medium may be transmitted using any suitable medium, including but not limited to wireless, wired, optical fiber, RF, etc., or any suitable combination thereof.

[0122] Program code for performing the operations of this application can be written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Java and C++, and conventional procedural programming languages ​​such as C or similar languages. The program code can execute entirely on the user's computing device, partially on the user's computing device, as a standalone software package, partially on the user's computing device and partially on a remote computing device, or entirely on a remote computing device or server. In cases involving remote computing devices, the remote computing device can be connected to the user's computing device via any type of network, including a local area network (LAN) or a wide area network (WAN), or it can be connected to an external computing device (e.g., via the Internet using an Internet service provider).

[0123] The aforementioned computer-readable medium carries one or more programs, which, when executed by a device, cause the computer-readable medium to perform the aforementioned functions.

[0124] Those skilled in the art will understand that the above modules can be distributed in the device as described in the embodiments, or they can be modified accordingly and placed in one or more devices that are unique to this embodiment. The modules in the above embodiments can be combined into one module, or they can be further divided into multiple sub-modules.

[0125] According to an embodiment of this application, a computer program is proposed, including a computer program or instructions, which, when executed by a processor, can perform the methods described above.

[0126] The embodiments of this application have been described in detail above. Specific examples have been used to illustrate the principles and implementation methods of this application. The descriptions of the embodiments above are only for the purpose of helping to understand the method and core ideas of this application. Furthermore, any changes or modifications made by those skilled in the art based on the ideas of this application, and on the specific implementation methods and application scope of this application, are all within the scope of protection of this application. Therefore, the content of this specification should not be construed as a limitation of this application.

Claims

1. A method for surveying buildings, characterized in that, include: Feature extraction is performed on the three-dimensional data of the building to obtain the frame structure data of the building; The building is modeled in three dimensions using the frame structure data to obtain a three-dimensional model of the building. The quality of the building is inspected using the three-dimensional model and the preset building information model.

2. The method according to claim 1, characterized in that, Before extracting features from the three-dimensional data of the building to obtain the frame structure data of the building, the process also includes: Data is collected from the building to obtain its three-dimensional point cloud data; The three-dimensional point cloud data is preprocessed to obtain the three-dimensional data.

3. The method according to claim 2, characterized in that, The three-dimensional point cloud data is preprocessed to obtain the three-dimensional data, including: The three-dimensional data is obtained by registering, denoising, and / or downsampling the three-dimensional point cloud data.

4. The method according to claim 2, characterized in that, The frame structure data includes the frame feature data and geometric data of the building. The frame feature data includes the data of the floor slabs, columns and beams in the frame of the building. The geometric data includes the length, width and height of the columns and beams and / or the thickness of the floor slabs.

5. The method according to claim 4, characterized in that, Feature extraction is performed on the three-dimensional data of the building to obtain the frame structure data of the building, including: Feature extraction is performed on the three-dimensional data to determine the frame feature data; Euclidean clustering is performed on the point cloud density of the three-dimensional data to identify columns in buildings; The length and width of the column are obtained using its cross-section; Density analysis was performed on the 3D point cloud data to obtain the height of the columns after cluster analysis; The point cloud density of the beam is detected using a histogram method to determine the beam's length, width, and height; and / or The distance between the upper and lower planes of the floor slab is calculated using the three-dimensional data to obtain the thickness of the floor slab.

6. The method according to claim 1, characterized in that, The quality inspection includes deformation detection and / or damage assessment.

7. The method according to claim 1, characterized in that, Also includes: The construction progress of the building is assessed using the three-dimensional model.

8. A device for surveying buildings, characterized in that, include: The frame structure data extraction unit is used to extract features from the three-dimensional data of the building to obtain the frame structure data of the building. A 3D modeling unit is used to perform 3D modeling of the building using the structural data to obtain a 3D model of the building. The detection unit is used to perform quality inspection on the building using the three-dimensional model and the preset building information model.

9. An electronic device, characterized in that, include: processor; Memory, used to store computer programs; When the computer program is executed by the processor, the processor causes the processor to implement the method as described in any one of claims 1-7.

10. A non-transitory computer-readable storage medium having stored thereon computer-readable instructions that, when executed by a processor, cause the processor to perform the method as described in any one of claims 1-7.

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