Building structure scanning method, computer device and storage medium

Abstract

The present disclosure relates to the field of measurement technology and provides a building structure scanning method, computer device, and storage medium. The method includes: determining the multi-level structural partitions contained in the prefabricated building based on the load criticality of the structure in the prefabricated building; the multi-level structural partitions include a primary structural partition corresponding to the load connection point, a secondary structural partition corresponding to the prefabricated components as functional modules, and a tertiary structural partition corresponding to the overall prefabricated building and scene information; determining a scanning resolution and corresponding scanning equipment and execution objects that are positively correlated with the load criticality of the structural partition; completing the scanning of each level of structural partitions through the execution objects and scanning equipment adapted to each level of structural partitions, and fusing the scanning results of each partition to construct a building information model of the prefabricated building. In this way, efficient scanning is achieved according to the load criticality of the structural partitions with appropriate equipment and resolution, and the scanning results are accurate and meet the accuracy requirements.

Description

Technical Field

[0001] The present disclosure relates to the field of measurement technology, and in particular to a building structure scanning method, a computer device, and a storage medium. Background Art

[0002] Prefabricated buildings are a construction method that uses factory-fabricated concrete components (such as wall panels, floor slabs, and beams), steel structures, or wood components, which are then transported to the construction site for standardized assembly. Its core advantages lie in improving construction efficiency, reducing on-site wet work pollution, conserving resources, and ensuring consistent component quality through industrialized production.

[0003] The core technologies of prefabricated buildings include prefabricated component design, standardized mold production, and structural node connections (such as rebar sleeve grouting and bolted joints). The dimensional accuracy of prefabricated components and the reliability of node connections directly impact the overall safety and seismic performance of the building.

[0004] The current design and construction of prefabricated buildings relies heavily on architectural drawings. In theory, these drawings should fully reflect key information such as the building's structural dimensions, component connection points, and the location of embedded parts. However, during on-site assembly, component installation positions may deviate slightly from the drawings due to mechanical precision, worker skill, and environmental factors such as wind and temperature.

[0005] To mitigate the risks associated with these drawing errors, high-precision 3D scanning of completed prefabricated building structures is necessary to capture their true spatial geometry and detailed features. In particular, with the rapid development of digital twin technology, high-precision 3D point cloud models based on scanned data are also required to facilitate the precise implementation of subsequent smart building applications, building renovation / repair / maintenance, and construction optimization.

[0006] However, current building scanning operations mostly rely on the use of fixed laser scanners to complete acquisition at a fixed resolution. This results in insufficient accuracy of key structural points (for example, beam-column connection points require extremely high-precision scanning), and the identification of specific components relies on manual experience, making it impossible to achieve efficient and accurate scanning operations. Summary of the Invention

[0007] In view of the above-mentioned shortcomings of the prior art, the purpose of the present disclosure is to provide a building structure scanning method, a computer device and a storage medium to solve the problems in the related art.

[0008] A first aspect of the present disclosure provides a building structure scanning method, which is applied to three-dimensional scanning of prefabricated buildings; the method comprises: determining a multi-level structural partition contained in the prefabricated building based on the load criticality of the structure in the prefabricated building; wherein, according to the load criticality from high to low, the multi-level structural partition comprises a primary structural partition corresponding to the load connection point, a secondary structural partition corresponding to the prefabricated component as a functional module, and a tertiary structural partition corresponding to the overall prefabricated building and scene information; determining a scanning resolution and a corresponding scanning device that are adapted in a positive correlation with the load criticality of the structural partition, and determining an execution object that is adapted to the motion mode required to execute the scanning of the structural partition; completing the scanning of the structural partitions at each level by means of the execution object and scanning device adapted to the structural partitions at each level, so as to fuse the scanning results of each partition to construct a building information model of the prefabricated building.

[0009] In an embodiment of the first aspect, the scanning of the structural partitions at each level is completed through the execution objects and scanning devices adapted to the structural partitions at each level, including: identifying the current component in the secondary structural partition; when the current component in the secondary structural partition is a prefabricated component, obtaining the structural data associated with the prefabricated component as the scanning result of the current component.

[0010] In an embodiment of the first aspect, the building structure scanning method includes: scanning the structural data of each existing prefabricated component, and extracting unique corresponding structural feature information based on the measurable data therein, and associating the structural data of each prefabricated component and the corresponding structural feature information and storing them in a prefabricated component library; wherein the measurable data at least includes dimensional data; the scanning of the structural data of the structural partitions at each level is completed by using execution objects and scanning devices adapted to the structural partitions at each level, including: identifying the current component in the secondary structural partition; collecting the current structural feature information of the current component; based on the current structural feature information, matching the structural data of the associated prefabricated component in the prefabricated component library; and using the matched structural data as the scanning result of the current component.

[0011] In an embodiment of the first aspect, the identifying of the current component in the secondary structure partition includes: detecting the current component through an infrared perspective device to obtain a detection image; and identifying the boundary of the current component in the secondary structure partition based on the detection result to obtain contour information of the current component.

[0012] In an embodiment of the first aspect, the collecting of current structural feature information of the current component includes: obtaining measurable data of the current component based on measuring the acquired contour information of the current component; and extracting the current structural feature information based on the measurable data.

[0013] In an embodiment of the first aspect, the building structure scanning method further includes: in response to not obtaining structural data of the current component as a prefabricated component, determining a scanning movement trajectory based on the central axis of the current component; and performing scanning of the current structural data of the current component along the scanning movement trajectory.

[0014] In an embodiment of the first aspect, each reference positioning node in a reference positioning network is distributed as a reference positioning node in each level of the region; the fusion method of each partition scanning result includes: determining the reference position coordinates in each level of structural partitions according to the reference positioning network to map each partition scanning result into a unified spatial coordinate system; performing splicing of the partition scanning results of adjacent structural partitions based on the determination of overlapping points between adjacent structural partitions, including: if there are overlapping points belonging to structural partitions of different criticalities, taking a weighted sum of the original coordinates of the overlapping points in the multiple structural partitions in which they are located to obtain the confidence coordinates of the overlapping points; wherein the weight of the coordinate set of the overlapping points in different structural partitions is positively correlated with the load criticality of the structural partition; correcting the coordinates of other points in the original partition scanning results according to the confidence coordinates of the overlapping points to obtain the confidence partition scanning results of each of the original partition scanning results; and performing the splicing based on the confidence partition scanning results of each structural partition.

[0015] In an embodiment of the first aspect, the positioning accuracy of the reference positioning node in each structural partition is positively correlated with the load criticality of the structural partition; and / or, the implementation method of the reference positioning node in each structural partition is different, including at least one of the following: 1) the first reference positioning node in the primary structural partition includes a target ball with a built-in positioning light source; 2) the second reference positioning node in the secondary structural partition includes a UWB positioning base station; 3) the third reference positioning node in the tertiary structural partition includes a GPS / GNSS reference station; and / or, in the calculation of the weighted sum, the original coordinates of the overlapping point in the secondary structural partition are processed by a similarity transformation function that compensates for temperature deformation, and the original coordinates of the overlapping point in the tertiary partition are processed by a projection transformation function that compensates for scale difference; the method also includes: when it is detected that the displacement of the reference positioning node exceeds a preset threshold, triggering a rescan of the corresponding structural area.

[0016] A second aspect of the present disclosure provides a computer device, comprising: a processor and a memory; the memory stores a computer program or instructions; the processor is configured to run the computer program or instructions to execute the building structure scanning method as described in any one of the first aspects.

[0017] A second aspect of the present disclosure provides a computer-readable storage medium storing a computer program or instruction, wherein the computer program or instruction is executed to perform the building structure scanning method as described in any one of the second aspects.

[0018] As described above, the present disclosure relates to the field of measurement technology and provides a building structure scanning method, a computer device, and a storage medium. The method includes: determining the multi-level structural partitions contained in the prefabricated building based on the load criticality of the structure in the prefabricated building; wherein, according to the load criticality from high to low, the multi-level structural partitions include a primary structural partition corresponding to the load connection point, a secondary structural partition corresponding to the prefabricated component as a functional module, and a tertiary structural partition corresponding to the overall prefabricated building and scene information; determining a scanning resolution and a corresponding scanning device that are adapted in a positive correlation with the load criticality of the structural partition, and determining an execution object that is adapted to the motion mode required to execute the scanning of the structural partition; completing the scanning of the structural partitions at each level through the execution object and scanning device adapted to the structural partitions at each level, and fusing the scanning results of each partition to construct the building information model of the prefabricated building. Thus, the scanning is completed with a suitable device and resolution according to the load criticality of the structural partition, the scanning results are accurate and meet the accuracy requirements, and the process is efficient. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Figure 1 A structural diagram showing a schematic diagram of a scanning scene of an assembled building in one embodiment of the present disclosure.

[0020] Figure 2 A schematic diagram showing a flow chart of a building structure scanning method according to an embodiment of the present disclosure.

[0021] Figure 3 A schematic diagram showing an exemplary process of scanning secondary structure partitions in one embodiment of the present disclosure.

[0022] Figure 4 The organizational relationship between the structural data of prefabricated components and the corresponding structural feature information in a prefabricated component library in one embodiment of the present disclosure is demonstrated.

[0023] Figure 5 A schematic diagram showing a flow chart of scanning when the current component structure data cannot be obtained in one embodiment of the present disclosure.

[0024] Figure 6 A schematic flow chart showing a method for fusing the partition scanning results in one embodiment of the present disclosure is shown.

[0025] Figure 7 A schematic diagram showing a module of a building structure scanning device according to an embodiment of the present disclosure is shown.

[0026] Figure 8 A schematic diagram showing the structure of a computer device in one embodiment of the present disclosure is shown. DETAILED DESCRIPTION

[0027] The following describes the embodiments of the present disclosure through specific examples. Those skilled in the art can easily understand the other advantages and effects of the present disclosure from the information disclosed in this disclosure. The present disclosure can also be implemented or applied through different specific embodiments. The details of the present disclosure can also be modified or changed according to different viewpoints and application modules without departing from the spirit of the present disclosure. It should be noted that the embodiments and features in the embodiments of the present disclosure can be combined with each other unless there is a conflict.

[0028] The following is a detailed description of the embodiments of the present disclosure with reference to the accompanying drawings so that those skilled in the art can easily implement the present disclosure. The present disclosure can be embodied in many different forms and is not limited to the embodiments described herein.

[0029] Throughout the present disclosure, reference to terms such as "one embodiment," "some embodiments," "examples," "specific examples," or "some examples" means that a specific feature, structure, material, or characteristic described in conjunction with that embodiment or example is included in at least one embodiment or example of the present disclosure. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in any one or a group of embodiments or examples. Furthermore, those skilled in the art may combine and integrate different embodiments or examples, and features of different embodiments or examples, as described in the present disclosure, without conflicting requirements.

[0030] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features being referred to. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one such feature. In the context of this disclosure, "a group" means two or more, unless otherwise specifically defined.

[0031] In order to clearly describe the present disclosure, components not related to the description are omitted, and the same or similar components throughout the specification are denoted by the same reference numerals.

[0032] Throughout this specification, when a device is said to be "connected" to another device, this includes not only "direct connection" but also "indirect connection" with other elements interposed therebetween. Furthermore, when a device is said to "include" a certain component, unless otherwise stated, this does not exclude the inclusion of other components but rather implies that the device may include other components.

[0033] Although the terms first, second, etc. are used in this document to represent various elements in some examples, these elements should not be limited by these terms. These terms are only used to distinguish one element from another. For example, the first interface and the second interface, etc. are represented. Furthermore, as used in this document, the singular forms "one," "an," and "the" are intended to also include the plural forms, unless there is a contrary indication in the context. It should be further understood that the terms "comprise" and "include" indicate the presence of the described features, steps, operations, elements, modules, projects, types, and / or groups, but do not exclude the presence, occurrence, or addition of one or a group of other features, steps, operations, elements, modules, projects, types, and / or groups. The terms "or" and "and / or" used herein are interpreted as inclusive, or mean any one or any combination. Therefore, "A, B, or C" or "A, B, and / or C" means "any of the following: A; B; C; A and B; A and C; B and C; A, B, and C." Exceptions to this definition only occur when the combination of elements, functions, steps, or operations is inherently mutually exclusive in some way.

[0034] The technical terms used herein are intended only to refer to specific embodiments and are not intended to limit the present disclosure. The singular form used herein also includes the plural form unless the statement explicitly indicates otherwise. The term "comprising" as used in this specification is intended to specify specific features, regions, integers, steps, operations, elements, and / or components and does not exclude the presence or addition of other features, regions, integers, steps, operations, elements, and / or components.

[0035] Although not defined differently, all terms used herein, including technical and scientific terms, have the same meanings as those generally understood by those skilled in the art to which this disclosure belongs. Terms defined in commonly used dictionaries are additionally interpreted as having meanings consistent with relevant technical literature and the current message. Unless otherwise defined, they should not be overly interpreted as ideal or highly formalized meanings.

[0036] Prefabricated buildings are a type of building construction method in which concrete components (such as wall panels, floor slabs, beams and columns), steel structure components or wooden structure components are prefabricated in factories and transported to the construction site for standardized assembly.

[0037] Although architectural drawings of prefabricated buildings may exist, the actual assembly process can easily lead to certain details being distorted compared to the drawings. Therefore, to support applications requiring high precision, such as the construction of precise digital twin models of prefabricated buildings, actual scanning and measurement are still required to obtain the actual structural data of prefabricated buildings.

[0038] However, current building scanning operations mostly rely on the use of fixed laser scanners to complete acquisition at a fixed resolution. This results in insufficient accuracy of key structural points (for example, beam-column connection points require extremely high-precision scanning), and the identification of specific components relies on manual experience, making it impossible to achieve efficient and accurate scanning operations.

[0039] In view of this, a building structure scanning method is provided in an embodiment of the present disclosure, which divides prefabricated buildings into zones according to the different criticalities of structural loads and scans them according to different accuracy requirements, thereby solving problems in related technologies.

[0040] like Figure 1 As shown, a schematic diagram of an application scenario of prefabricated building scanning in one embodiment of the present disclosure is shown.

[0041] exist Figure 1 In the figure, the prefabricated building 100 is shown as a multi-story structure. Different methods can be used to scan the prefabricated building 100 at different heights and different indoor / outdoor locations. For example, outdoors, the lower parts of the outer surface of the prefabricated building 100 can be scanned manually or by a mobile robot 200 holding a scanning device. Outdoors, the higher parts of the outer surface of the prefabricated building 100 can be scanned by an aircraft 300 (such as a drone or helicopter). Inside the prefabricated building 100, scanning can be performed manually or by a mobile robot 200 holding a scanning device. In some embodiments, all scanning work can be performed fully automatically by a drone, mobile robot 200, etc. according to a predetermined route or using simultaneous localization and mapping (SLAM) technology. In other embodiments, part of the scanning work can also be completed manually.

[0042] In some embodiments, the objects scanned outdoors on the prefabricated building 100 are mainly exterior walls, windows, roofs, etc. The objects scanned indoors on the prefabricated building 100 are mainly interior walls, beams, columns, stairs, etc. Figure 1 The prefabricated building 100 is simplified by only a rough outline, and its specific structure is omitted. Prefabricated buildings 100 of various structural types can apply the solution in the embodiment of the present disclosure.

[0043] The building structure scanning method in the embodiment of the present disclosure, when scanning the prefabricated building 100, takes into account the load criticality and accuracy requirements at different positions, divides the prefabricated building 100 into different levels of structural partitions, and adopts scanning methods of corresponding accuracy for different levels, thereby solving problems in related technologies.

[0044] like Figure 2 , which is a flow chart showing a building structure scanning method according to an embodiment of the present disclosure.

[0045] exist Figure 2 The process includes:

[0046] Step S201: Based on the load criticality of the structure in the prefabricated building, determine the multi-level structural partitions included in the prefabricated building.

[0047] Among them, according to the load criticality from high to low, the multi-level structural partition includes a primary structural partition corresponding to the load connection point, a secondary structural partition corresponding to the prefabricated components as functional modules, and a tertiary structural partition corresponding to the overall prefabricated building and scene information. In some embodiments, the load connection point includes a structural connection point, such as a beam, a column joint, an embedded part, etc. In a further example, in the relevant acceptance standards, there will be a deformation monitoring requirement of ≤1mm for the structural connection point. In some embodiments, the types of prefabricated components as functional modules include standardized prefabricated components such as wall panels / stairs that play corresponding functions. In a further example, the accuracy requirement for prefabricated components is ≤3mm to meet the installation tolerance requirements of prefabricated buildings. In some embodiments, the three-level structural partition corresponds to the macro scene information of the prefabricated building, such as the overall outline of the building and the relationship between the site. In a further example, the accuracy requirement for the macro scene information is ≤10mm, which meets the basic requirements of engineering measurement.

[0048] Step S202: determining a scanning resolution and a corresponding scanning device that are adapted in a positive correlation with the load criticality of the structural partition, and determining an execution object that is adapted to the motion mode required for executing the scanning of the structural partition.

[0049] It can be understood that based on the above examples of accuracy requirements of ≤1mm for primary structural partitions, ≤3mm for secondary structural partitions, and ≤10mm for macroscopic scene information for tertiary structural partitions, the accuracy requirements are positively correlated with the load criticality of the structural partition. Furthermore, the scanning accuracy requirements are also positively correlated with the scanning resolution of the scanning equipment: the higher the accuracy requirement, the higher the scanning resolution.

[0050] Thus, in step S202, scanning resolutions that meet the different precision requirements of the primary structure partition, the secondary structure partition, and the tertiary structure partition, as well as scanning devices capable of scanning at the scanning resolutions, can be determined. The scanning device can be implemented as a high-precision 3D laser scanner, an industrial camera, or a combination thereof.

[0051] The execution object refers to a carrier that carries a scanning device to perform a scanning operation. As an example, the first-level structural partition corresponds to important locations such as beam-column connection points, and the corresponding scanning operation needs to be performed indoors. Therefore, the first-level structural partition can be scanned by a manual / mobile robot carrying a scanning device. As an example, for the second-level structural partition, for areas containing prefabricated components, such as walls and stairs, for their indoor parts, they can be scanned by a manual / mobile robot carrying a scanning device; for their outdoor parts, at a lower height, they can be scanned by a manual / mobile robot carrying a scanning device; at a higher height, they can be scanned by an aircraft carrying a scanning device. As an example, the third-level structural partition corresponds to the macroscopic scene information of the prefabricated building, which is all collected outdoors. At a lower height, it can be scanned by a manual / mobile robot carrying a scanning device; at a higher height, it can be scanned by an aircraft carrying a scanning device.

[0052] Step S203: Scanning the structural partitions at each level is completed by using execution objects and scanning devices adapted to the structural partitions at each level, so as to fuse the scanning results of each partition to construct a building information model of the prefabricated building.

[0053] For prefabricated buildings, the prefabricated components used (such as walls, stairs, beams, columns, etc.) are often reused in large quantities with the same specifications. The same specifications may mean the same structure. For example, the prefabricated wall components on different floors of an prefabricated building have the same structure. For another example, the stairs at corresponding locations on different floors have the same structure. Moreover, because prefabricated components are basically fully assembled, their structural data will basically not change. When scanning prefabricated buildings, if each prefabricated component is scanned inch by inch without distinction, the same prefabricated components will be scanned repeatedly, resulting in reduced scanning efficiency.

[0054] To this end, the scanning method for secondary structural partitions can be optimized. In some embodiments, a database containing structural data of various prefabricated components is pre-installed. During actual scanning, if the component being scanned is identified as a prefabricated component already in the database, the corresponding structural data can be directly extracted from the database as the scan result for the current component. This can significantly improve scanning efficiency.

[0055] like Figure 3 As shown, it shows an exemplary flow chart of scanning secondary structure partitions in one embodiment of the present disclosure.

[0056] In this embodiment, the structural data of each existing prefabricated component can be pre-scanned. For example, prefabricated components of various specifications, such as walls, stairs, columns, and beams, can be pre-scanned to obtain their structural data, including but not limited to one or more of dimensional data (including length, width, height, and shape), material information, mechanical properties, appearance quality, connection methods, and inspection standards. Furthermore, uniquely corresponding structural feature information is extracted based on the measurable data in the structural data. The measurable data refers to explicit data of the prefabricated component that can be detected through scanning, such as dimensional data. The dimensional data includes features that can reflect the characteristics of the prefabricated component, such as the length-width-height ratio and shape. Therefore, in some examples, feature extraction algorithms can be used to extract uniquely corresponding structural feature information based on the measurable data. For example, the method for extracting the structural feature information may include but is not limited to a neural network-based feature extraction network or a specific encoding method (such as hashing).

[0057] Furthermore, the structural data of each prefabricated component and the corresponding structural feature information are stored in the prefabricated component library. Figure 4 The figure shows the organizational relationship between the structural data and corresponding structural feature information of prefabricated components in the prefabricated component library. Furthermore, using this prefabricated component library, when the current component being scanned is identified as matching a prefabricated component in the library, the associated structural data can be directly used as the scan result for the current component and added to the building scan result. This eliminates the need to scan duplicate prefabricated components, significantly improving scanning efficiency.

[0058] exist Figure 3 The process includes:

[0059] Step S301: Identify the current component in the secondary structure partition.

[0060] During scanning, the current component must be identified to facilitate the collection of measurable data for the current component. Specifically, the current component can be identified by identifying its boundaries. Because the boundaries of prefabricated components are buried beneath the surface rather than exposed, in some embodiments, the current component can be detected using infrared fluoroscopy equipment to obtain a detection image. Based on the detection results, the boundaries of the current component in the secondary structure partition are identified to obtain the contour information of the current component.

[0061] Step S302: Collect current structural feature information of the current component.

[0062] In some embodiments, measurable data of the current component, such as length, width, height, shape, etc., can be measured based on the obtained contour information, and the current structural feature information of the current component can be extracted using the same feature extraction algorithm as the structural feature information in the prefabricated component library.

[0063] In some embodiments, the subject can use a scanning device or other device they carry to capture an image. Using a pre-calibrated scale conversion relationship between the image coordinate system and the real-space coordinate system, the actual real-space dimensions of the component can be obtained based on the image dimensions represented by the contour information in the image. In some embodiments, full dimensional data (e.g., length, width, height, and shape) of a prefabricated component (e.g., a wall) can be obtained through outdoor measurements by an aircraft. Thickness can be measured at locations on the wall where the thickness is exposed, such as windows. Alternatively, if the wall is obscured from view, partial dimensional data (e.g., length, width, and shape) of the prefabricated component can be obtained from outdoor measurements. Additional partial dimensional data (e.g., width, i.e., thickness) can be obtained by combining outdoor or indoor measurements of the prefabricated component or other prefabricated components flush with it at a corresponding height (e.g., thickness measured at an exposed location on a wall flush with it), thereby extracting features to obtain structural feature information.

[0064] In other embodiments, if architectural drawings of the prefabricated building are pre-existing, and if the architectural drawings include structural data and / or specification information for each prefabricated component, the identified current component can be used to determine its corresponding component in the architectural drawings, and the current structural feature information can be determined based on the corresponding component. For example, the structural data of the corresponding component in the architectural drawings, or the structural data indexed based on the specification information, can be used to obtain the current structural feature information of the current component through the feature extraction algorithm.

[0065] Step S303: Based on the current structural feature information, matching the structural data of the associated prefabricated components in the prefabricated component library.

[0066] Step S304: using the matched structural data as the scanning result of the current component.

[0067] The above method of extracting structural data from a prefabricated component library constructed in advance through structural feature information is only an exemplary method, and other implementation methods are possible and are not limited to this.

[0068] In other embodiments, when a prefabricated component is pre-tagged, the tag stores the structural data of the component. By configuring the execution object with a reader capable of reading the tag, the structural data of the prefabricated component can be read from the tag. Furthermore, using this structural data as a scan result, along with the identified outline of the current component, the structural data of the current component can be incorporated into the overall scan result of the secondary structure partition. Specifically, the structural data of the current component is superimposed at each coordinate position corresponding to the outline in the overall scan result. In this embodiment, calculation and associated storage of structural feature information are unnecessary. The tag can be an image tag or an electronic tag. Image tags, such as barcodes or QR codes, can be machined and formed on the surface of the prefabricated component. However, given that the exterior of the prefabricated component may be covered by other building materials, electronic tags are preferred. The electronic tag can be implemented as an RFID tag, for example, and can be embedded within the prefabricated component for protection. Preferably, the electronic tag can be implemented as a passive tag, communicating via energy transmitted by a reader, eliminating the need for battery replacement.

[0069] In some embodiments, if the structural data of the current component cannot be obtained from, for example, the tag, the structural data of the current component may be collected. In embodiments utilizing a prefabricated component library, the prefabricated component library may be updated using the collected structural data.

[0070] Specifically, such as Figure 5 As shown, the method in the embodiment of the present disclosure also includes:

[0071] Step S501: In response to not acquiring structural data of the current component as a prefabricated component, determining a scanning movement trajectory according to a central axis of the current component.

[0072] Specifically, since the scanning range of the scanning device can be fan-shaped, the scanning range can be moved by determining the central axis of the component to evenly cover the areas on both sides of the central axis, ensuring that the current component is fully scanned and avoiding omissions. For example, the scanning range can be moved up and down or left and right along the central axis of the wall.

[0073] Step S502: Scanning the current structural data of the current component along the scanning movement trajectory.

[0074] Therefore, by using adapted execution objects such as manual / mobile robots, aircraft, etc. to carry adapted scanning equipment and perform scanning operations outdoors / indoors, the structural data of each structural partition can be collected and the scanning results of each structural partition can be obtained.

[0075] In some embodiments, by fusing the scan results of various structural partitions, a building information model (BIM) corresponding to the structural data of a real prefabricated building can be constructed. For example, this building information model is known as BIM (Building Information Modeling). The core of BIM is to create a virtual three-dimensional model of the building project and, using digital technology, provide this model with a complete and realistic building information database. This database contains not only geometric information, specialized attributes, and status information describing building components, but also status information for non-component objects (such as space and motion behavior).

[0076] The scanning results of each structural partition need to be converted to a unified coordinate system to achieve the fusion of the scanning results of each structural partition. To this end, in some embodiments, a reference positioning network can be pre-set in the prefabricated building before the scanning operation. The reference positioning network includes multiple reference positioning nodes distributed in each structural partition. The position of each reference positioning node in the unified coordinate system is preset, so that the execution object can use the reference positioning node to determine the position coordinates of the scanning point in the unified coordinate system during scanning.

[0077] In some embodiments, the positioning accuracy of the reference positioning nodes in each structural partition may be positively correlated with the load criticality of the structural partition, which is manifested as different positioning devices and positioning methods implemented specifically. For example, the first reference positioning node in the primary structural partition includes a target ball with a built-in positioning light source, and its positioning accuracy can be at the millimeter level or sub-millimeter level. Exemplarily, the second reference positioning node in the secondary structural partition includes a UWB positioning base station, and its positioning accuracy can be at the centimeter level. Exemplarily, the third reference positioning node in the tertiary structural partition includes a GPS / GNSS reference station, and its positioning accuracy is at the meter level. It should be noted that the above-mentioned implementation methods of the reference positioning nodes are only examples, which can be changed in specific application scenarios and are not limited to this.

[0078] It is understood that in order to utilize a reference positioning node to obtain reference position coordinates, the execution object or its accompanying scanning device may include a functional module for communicating with the reference positioning node. For example, a target sphere with a built-in positioning light source may be equipped with an optical sensing device capable of sensing the light emitted by the target sphere, such as a camera or photodetector. Another example is a UWB positioning base station, equipped with a UWB communication module capable of communicating with the UWB positioning base station. Another example is a GPS / GNSS reference station, equipped with a corresponding GPS / GNSS communication module.

[0079] Through the reference positioning network, the partition scanning results of each structural partition can be converted into a unified coordinate system. Furthermore, the matching relationship of overlapping points between each structural partition can be used to achieve the fusion of the partition results.

[0080] like Figure 6 As shown, a flow chart of a method for fusing the partition scanning results in one embodiment of the present disclosure is shown.

[0081] exist Figure 6 The process includes:

[0082] Step S601: Determine the reference position coordinates in each level of structural partitions according to the reference positioning network, so as to map the scanning results of each partition into a unified spatial coordinate system.

[0083] In some embodiments, the unified spatial coordinate system may be a global spatial coordinate system established corresponding to the assembled building. The partition scanning results of each structural partition include point cloud data of each point based on the reference position coordinates.

[0084] Step S602: based on the determination of overlapping points between adjacent structural partitions, executing splicing of the partition scanning results of adjacent structural partitions.

[0085] In some embodiments, the determination of overlapping points between adjacent structural partitions can be achieved by searching for matching points in the partition scanning results of adjacent structural partitions using feature detection algorithms such as SIFT, SURF, or ORB. SIFT is a scale-invariant feature transform. Its principle is to convolve the image with a Gaussian filter at different scales, and use continuous Gaussian blurring to find key points. The key points are determined based on the maximum and minimum values ​​of the Difference of Gaussians (DoG) at different scales. In addition, the position and scale of the key points are accurately determined, and the key points are accurately located by fitting the Taylor expansion of the DoG function, and low-contrast and unstable edge response points are removed. Then, the points are assigned directions, and the gradient direction histogram is calculated for each key point. One or more directions are assigned to the key points based on the gradient direction distribution, so that the operator has rotation invariance. ORB (Oriented FAST and Rotated BRIEF) does combine FAST key point detection and BRIEF descriptor technology, and has the advantages of speed, scale invariance, rotation invariance, etc. It is widely used in computer vision fields such as object recognition, tracking, image stitching, etc.

[0086] SURF (Speeded Up Robust Features) calculates the gradient value of each pixel in the image and calculates the response function based on the gradient value to detect corners. It has good invariance to image scale transformation, perspective transformation, illumination change, etc., and its calculation speed is faster than SIFT.

[0087] In some embodiments, overlapping points between adjacent structural partitions may belong to structural partitions with different load criticality levels. For example, overlapping points between a primary and secondary structural partition, between a secondary and tertiary structural partition, between a primary and tertiary structural partition, or between a primary, secondary, and tertiary structural partition. Because structural partitions of varying criticality may have varying degrees of accuracy when scanned, even if a partition scanning result for each structural partition in a unified coordinate system is obtained using a reference positioning network, there may still be a certain degree of error between them. Specifically, this may manifest as a certain degree of error between the original coordinates of overlapping points in structural partitions with varying load criticality levels. Alternatively, weights can be assigned to the original coordinates of overlapping points in structural partitions with varying load criticality, based on the positive correlation between the load criticality levels, and weighted fusion can be performed to obtain confident coordinates of the overlapping points to replace the original coordinates. For example, the overlapping points between a primary and secondary structural partition can be weighted fused based on the weight distribution between the primary and secondary structural partitions. The overlapping points between a primary and tertiary structural partition can be weighted fused based on the weight distribution between the primary and tertiary structural partitions. The overlapping points between the secondary and tertiary structure partitions are weightedly fused based on the weight distribution between the secondary and tertiary structure partitions. The overlapping points between the primary, secondary, and tertiary structure partitions are weightedly fused based on the weight distribution between the primary, secondary, and tertiary structure partitions.

[0088] Therefore, illustratively, step S602 includes:

[0089] Step S621: If there are overlapping points belonging to structural partitions of different criticality, a weighted sum is calculated between the original coordinates of the overlapping points in the multiple structural partitions to obtain the confidence coordinates of the overlapping points.

[0090] The weight of the coordinate sets of overlapping points in different structural partitions is positively correlated with the load criticality of the structural partition. The higher the load criticality, the greater the weight, i.e., the weights of the primary, secondary, and tertiary structural partitions decrease one by one. In some embodiments, in the calculation of the weighted sum, the coordinates of the overlapping points can be represented as vectors. For example, for point M, its coordinates are represented as M = [x, y, z]. Optionally, the original coordinates of the overlapping points in the secondary structural partition can be processed by a similarity transformation function to compensate for temperature deformation, while the original coordinates of the overlapping points in the tertiary structural partition can be processed by a projection transformation function to compensate for scale differences. In other words, in addition to the weights, the coordinate sets of the overlapping points are also transformed to compensate for corresponding errors. Similarity transformations are a subset of affine transformations, including rotations, translations, and other processes, used to compensate for the deformation of the measured points caused by temperature changes due to thermal expansion and contraction. Projection transformation is a core technology in 3D scanning, particularly in structured light 3D scanning and optical 3D measurement. Its core purpose is to convert the surface information of three-dimensional objects into measurable features in two-dimensional images by precisely controlling the projection and imaging of light, and then reconstruct the three-dimensional geometric data through inverse calculation to solve scale differences.

[0091] As an example, assuming that point M is an overlapping point among the primary structure partition, the secondary structure partition, and the tertiary structure partition, the calculation formula of the weighted sum can be expressed as:

[0092] M'=W1×PL1+W2×T(PL2)+W3×K(PL3);

[0093] Wherein, M' is the confidence coordinate of point M, PL1, PL2, and PL3 are the original coordinates of M in each structural partition, which can be in the form of a vector of [x, y, z]; W1, W2, and W3 are the weights of M in the three structural partitions, respectively; T is the similarity transformation function. In a specific example, the calculation process of the similarity transformation function can be implemented by multiplying the matrix of the original coordinates of the corresponding processing through an updateable similarity transformation matrix and obtaining the result; K is the projection transformation function. In a specific example, the calculation process of the projection transformation function can be implemented by multiplying the matrix of the original coordinates of the corresponding processing through an updateable projection transformation parameter and obtaining the result. In some embodiments, the weights, similarity transformation matrix, projection transformation parameters, etc. can be designed based on experience or experiments; they can also be obtained through training by iterative calculation with the goal of reducing the error between the confidence coordinates and the measured coordinates. It should be noted that the similarity transformation matrix and projection transformation parameters are not required. When the corresponding error is negligible or not obvious, they can be omitted to simplify the calculation process and improve the calculation efficiency.

[0094] It can be understood that the above formula is only a correction process for the original coordinates of overlapping points in three structural partitions. Although the correction process for the original coordinates of overlapping points in two structural partitions is not shown, those skilled in the art should be able to implement it under the guidance of this specification.

[0095] Step S622: Correcting the coordinates of other points in the original partition scanning results according to the confidence coordinates of the overlapping points to obtain confidence partition scanning results of each of the original partition scanning results.

[0096] Since the positional relationships between the points in the original partitioned scan results are already determined, when the original coordinates of the overlapping points are replaced by the confidence coordinates, the coordinates of all points other than the overlapping points can be corrected by combining the deviation between the original coordinates and the confidence coordinates with the determined positional relationships between the points. Thus, the confidence partitioned scan results of the original partitioned scan results can be obtained.

[0097] Step S623: performing the splicing based on the confidence partition scanning results of each structural partition.

[0098] Thus, by stitching together the scan results of each confidence partition to complete the fusion, compared to directly stitching together the original partition scan results, coordinate errors are effectively reduced and accuracy is improved. In some embodiments, the stitching of the confidence partition scan results can be performed based on some stitching algorithms.

[0099] In some embodiments, optimized stitching algorithms can be used to achieve better stitching results for partitioned scans. For example, the Random Sample Array Consensus (RANSAC) algorithm can be used. The core goal of image stitching is to transform multiple images with overlapping regions into the same coordinate system to produce a seamless stitching result. The Random Sample Array Consensus (RANSAC) algorithm removes mismatched feature points, which may exist in the images, to obtain more accurate matching pairs. The RANSAC algorithm then uses random sampling to ultimately find the optimal matching set that can achieve image stitching. This process is repeated until a model with a sufficient number of inliers is found or a predetermined number of iterations is reached. Specifically, the stitching calculation process can be implemented as follows: First, feature extraction and matching are performed, namely, key points in the two images are detected and initially matched (possibly with mismatches). Existing algorithms such as SIFT and SURF can be used in this step. Second, RANSAC is used to estimate the transformation model, filter inliers, and calculate the optimal homography matrix. Finally, image transformation and fusion are performed. The transformation model is used to apply perspective transformation to the images, which are then superimposed and fused to create a global image. Combining feature extraction, image transformation, and fusion techniques, RANSAC enables efficient and stable image stitching, producing high-quality stitching results. RANSAC's advantage lies in its ability to avoid false matches through random sampling and inlier voting, finding inliers supported only by correctly matched points, thereby improving robustness. Furthermore, inlier optimization ensures model accuracy, making it applicable to a variety of scenarios, including perspective transformation, rotation, and scaling.

[0100] In some embodiments, the reference positioning nodes in prefabricated buildings may shift due to external vibrations or forces, resulting in displacement in the front and back images. Therefore, the displacement of each reference positioning node can be detected using a detection device such as a camera. When the displacement of a reference positioning node exceeds a preset threshold, a rescan of the corresponding structural area is triggered. Furthermore, due to changes in the coordinate position of the reference, the similarity transformation parameters and projection transformation parameters can optionally be updated based on the displacement of the reference positioning node.

[0101] like Figure 7 FIG2 is a block diagram showing a building structure scanning device according to an embodiment of the present disclosure. It should be noted that the principle and technical implementation of the building structure scanning device can refer to the building structure scanning method in the previous embodiment, and thus will not be repeated in this embodiment.

[0102] exist Figure 7 In the embodiment, the building structure scanning device 700 is applied to three-dimensional scanning of prefabricated buildings, and includes:

[0103] The structural partitioning module 701 is used to determine the multi-level structural partitions contained in the prefabricated building based on the load criticality of the structure in the prefabricated building; wherein, according to the load criticality from high to low, the multi-level structural partitions include a primary structural partition corresponding to the load connection point, a secondary structural partition corresponding to the prefabricated components as functional modules, and a tertiary structural partition corresponding to the overall prefabricated building and scene information.

[0104] The scanning mode determination module 702 is used to determine a scanning resolution and a corresponding scanning device that are adapted in a positive correlation with the load criticality of the structural partition, and to determine an execution object that is adapted to the motion mode required to execute the scanning of the structural partition.

[0105] It can be understood that based on the above examples of accuracy requirements of ≤1mm for primary structural partitions, ≤3mm for secondary structural partitions, and ≤10mm for macroscopic scene information for tertiary structural partitions, the accuracy requirements are positively correlated with the load criticality of the structural partition. Furthermore, the scanning accuracy requirements are also positively correlated with the scanning resolution of the scanning equipment: the higher the accuracy requirement, the higher the scanning resolution.

[0106] The scanning execution module 703 is used to complete the scanning of the structural partitions at each level through the execution objects and scanning devices adapted to the structural partitions at each level, so as to fuse the scanning results of each partition to construct the building information model of the prefabricated building. In the embodiment of the first aspect, the scanning of the structural partitions at each level is completed through the execution objects and scanning devices adapted to the structural partitions at each level, including: identifying the current component in the secondary structural partition; when the current component in the secondary structural partition is a prefabricated component, obtaining the structural data associated with the prefabricated component as the scanning result of the current component.

[0107] In some embodiments, the building structure scanning method includes: scanning the structural data of each existing prefabricated component, and extracting unique corresponding structural feature information based on the measurable data therein, and associating the structural data of each prefabricated component and the corresponding structural feature information and storing them in a prefabricated component library; wherein the measurable data at least includes dimensional data; the scanning of the structural data of the structural partitions at each level is completed by using execution objects and scanning equipment adapted to the structural partitions at each level, including: identifying the current component in the secondary structural partition; collecting the current structural feature information of the current component; based on the current structural feature information, matching the structural data of the associated prefabricated component in the prefabricated component library; and using the matched structural data as the scanning result of the current component.

[0108] For prefabricated buildings, the prefabricated components used (such as walls, stairs, beams, columns, etc.) are often reused in large quantities with the same specifications. The same specifications may mean the same structure. For example, the prefabricated wall components on different floors of an prefabricated building have the same structure. For another example, the stairs at corresponding locations on different floors have the same structure. Moreover, because prefabricated components are basically fully assembled, their structural data will basically not change. When scanning prefabricated buildings, if each prefabricated component is scanned inch by inch without distinction, the same prefabricated components will be scanned repeatedly, resulting in reduced scanning efficiency.

[0109] To this end, the scanning method for secondary structural partitions can be optimized. In some embodiments, a database containing structural data of various prefabricated components is pre-installed. During actual scanning, if the component being scanned is identified as a prefabricated component already in the database, the corresponding structural data can be directly extracted from the database as the scan result for the current component. This can significantly improve scanning efficiency.

[0110] In some embodiments, the identifying of the current component in the secondary structure partition includes: detecting the current component through an infrared perspective device to obtain a detection image; and identifying the boundary of the current component in the secondary structure partition based on the detection result to obtain contour information of the current component.

[0111] In some embodiments, collecting the current structural feature information of the current component includes: obtaining measurable data of the current component based on measuring the acquired contour information of the current component; and extracting the current structural feature information according to the measurable data.

[0112] In some embodiments, the building structure scanning method further includes: in response to not obtaining structural data of the current component as a prefabricated component, determining a scanning movement trajectory based on the central axis of the current component; and performing a scan of the current structural data of the current component along the scanning movement trajectory.

[0113] In some embodiments, each reference positioning node in a reference positioning network is distributed among the reference positioning nodes in each level of the region; the fusion method of each partition scanning result includes: determining the reference position coordinates in each level of structural partitions according to the reference positioning network to map each partition scanning result into a unified spatial coordinate system; performing splicing of the partition scanning results of adjacent structural partitions according to the determination of overlapping points between adjacent structural partitions, including: if there are overlapping points belonging to structural partitions of different criticality, taking a weighted sum of the original coordinates of the overlapping points in the multiple structural partitions in which they are located to obtain the confidence coordinates of the overlapping points; wherein the weight of the coordinate set of the overlapping points in different structural partitions is positively correlated with the load criticality of the structural partition; correcting the coordinates of other points in the original partition scanning results according to the confidence coordinates of the overlapping points to obtain the confidence partition scanning results of each of the original partition scanning results; and performing the splicing based on the confidence partition scanning results of each structural partition.

[0114] In some embodiments, the positioning accuracy of the reference positioning node in each structural partition is positively correlated with the load criticality of the structural partition; and / or, the implementation method of the reference positioning node in each structural partition is different, including at least one of the following: 1) the first reference positioning node in the primary structural partition includes a target ball with a built-in positioning light source; 2) the second reference positioning node in the secondary structural partition includes a UWB positioning base station; 3) the third reference positioning node in the tertiary structural partition includes a GPS / GNSS reference station; and / or, in the calculation of the weighted sum, the original coordinates of the overlapping points in the secondary structural partition are processed by a similarity transformation function that compensates for temperature deformation, and the original coordinates of the overlapping points in the tertiary partition are processed by a projection transformation function that compensates for scale differences; the method also includes: when it is detected that the displacement of the reference positioning node exceeds a preset threshold, triggering a rescan of the corresponding structural area.

[0115] It should be noted that in Figure 7 The various functional modules in the embodiments can be implemented in whole or in part by software, hardware, firmware, or any combination thereof. When implemented using software, they can be implemented in whole or in part in the form of a computer program or instruction product. A computer program or instruction product includes one or a group of computer programs or instructions. When a computer program or instruction is loaded and executed on a computer, the process or function according to the present disclosure is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer program or instruction can be stored in a computer-readable storage medium or transferred from one computer-readable storage medium to another computer-readable storage medium.

[0116] and, Figure 7The devices disclosed in the embodiments can be implemented using other module division methods. The device embodiments shown above are merely illustrative. For example, the module division is merely a logical functional division. In actual implementation, other division methods may be used, such as a group of modules or modules that can be combined or dynamically integrated into another system, or some features that can be ignored or not executed. In addition, the coupling or direct coupling or communication connection between devices or modules shown or discussed can be through some interface, and the indirect coupling or communication connection between devices or modules can be electrical or other forms.

[0117] in addition, Figure 7 Each functional module and submodule in the embodiments may be dynamically integrated into a single processing component, each module may exist physically independently, or two or more modules may be dynamically integrated into a single component. The aforementioned dynamic components may be implemented in hardware or as software functional modules. If the aforementioned dynamic components are implemented as software functional modules and sold or used as independent products, they may also be stored in a computer-readable storage medium. The storage medium may be a read-only memory, a magnetic disk, or an optical disk, etc.

[0118] It should be noted that the processes or methods represented by the flowcharts of the above embodiments of the present disclosure can be understood as modules, segments, or portions of code that include one or more sets of executable instructions configured to implement specific logical functions or steps of a process. Furthermore, the scope of the preferred embodiments of the present disclosure includes alternative implementations in which functions may be performed in a different order than that shown or discussed, including performing functions substantially simultaneously or in reverse order depending on the functions involved.

[0119] For example, Figure 2 The order of the steps in the method embodiments may be changed in specific scenarios and is not limited to the above.

[0120] like Figure 8 FIG. 1 is a schematic diagram showing the structure of a computer device in one embodiment of the present disclosure.

[0121] The computer device 800 may be exemplified as a processing terminal, such as a server, a desktop computer, a laptop computer, a tablet computer, a smart phone, or other terminals.

[0122] The computer device 800 includes a bus 801, a processor 802, and a memory 803. The processor 802 and the memory 803 can communicate with each other via the bus 801. The memory 803 can store computer programs or instructions. The processor 802 implements the method flow or function of the previous embodiment by running the computer program or instruction in the memory 803, for example Figure 2 、 Figure 3 、 Figure 5 、 Figure 6 shown.

[0123] Bus 801 can be a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus. Buses can be divided into address buses, data buses, control buses, etc. For ease of illustration, although only one thick line is used in the figure, this does not mean that there is only one bus or only one type of bus.

[0124] In some embodiments, the processor 802 may be implemented as a central processing unit (CPU), a microprocessor unit (MCU), a system on a chip (SoC), or a field programmable gate array (FPGA). The memory 803 may include volatile memory, such as random access memory (RAM), for temporarily storing data while running programs.

[0125] The memory 803 may also include a non-volatile memory (non-volatile memory) for data storage, such as a read-only memory (ROM), a flash memory, a hard disk drive (HDD), or a solid-state disk (SSD).

[0126] In some embodiments, the computer device 800 may further include a communicator 804. The communicator 804 is used to communicate with the outside world. In a specific example, the communicator 804 may include one or a group of wired and / or wireless communication circuit modules. For example, the communicator 804 may include one or more of a wired network card, a USB module, a serial interface module, etc. The wireless communication protocols followed by the wireless communication module include, for example, near field communication (NFC) technology, infrared (IR) technology, Global System for Mobile communications (GSM), General Packet Radio Service (GPRS), Code Division Multiple Access (CDMA), Wideband Code Division Multiple Access (WCDMA), Time-Division Code Division Multiple Access (TD-SCDMA), Long Term Evolution (LTE), Bluetooth (BT), Global Navigation Satellite System (GNSS), etc. One or more of the following.

[0127] In an embodiment of the present disclosure, a computer-readable storage medium may be provided, storing a computer program or instruction, which implements the method flow or function of any of the previous embodiments when executed.

[0128] That is, the method steps in the above embodiments are implemented as software or computer code that can be stored in a recording medium (such as a CD ROM, RAM, floppy disk, hard disk or magneto-optical disk), or are implemented as computer code originally stored in a remote recording medium or a non-transitory machine-readable medium downloaded via a network and to be stored in a local recording medium, so that the method represented herein can be stored in such software processing on a recording medium using a general-purpose computer, a dedicated processor or programmable or dedicated hardware (such as an ASIC or FPGA).

[0129] The present disclosure may also provide a computer program product, which includes one or more computer programs or instructions that, when executed, fully or partially execute the processes or functions in the present disclosure. The computer program product includes one or more computer programs or instructions.

[0130] A computer program or instruction can be stored in a readable storage medium or transferred from one readable storage medium to another. For example, the computer program or instruction can be transferred from one website, computer, server, or data center to another website, computer, server, or data center via wired or wireless means. The readable storage medium can be any accessible medium or a data storage device such as a server or data center that integrates one or more accessible media. The accessible medium can be a magnetic medium such as a floppy disk, hard disk, or magnetic tape; an optical medium such as a digital video disk; or a semiconductor medium such as a solid-state drive. The computer-readable storage medium can be a volatile or non-volatile storage medium, or can include both volatile and non-volatile types of storage media.

[0131] In summary, the present disclosure relates to the field of measurement technology, and provides a building structure scanning method, a computer device, and a storage medium. The method includes: determining the multi-level structural partitions contained in the prefabricated building based on the load criticality of the structure in the prefabricated building; wherein, according to the load criticality from high to low, the multi-level structural partitions include a primary structural partition corresponding to the load connection point, a secondary structural partition corresponding to the prefabricated component as a functional module, and a tertiary structural partition corresponding to the overall prefabricated building and scene information; determining a scanning resolution and a corresponding scanning device that are adapted in a positive correlation with the load criticality of the structural partition, and determining an execution object that is adapted to the motion mode required to execute the scanning of the structural partition; through the execution object and scanning device adapted to the structural partitions at each level, the scanning of the structural partitions at each level is completed, and the scanning results of each partition are integrated to construct the building information model of the prefabricated building. In this way, the scanning is completed with appropriate equipment and resolution according to the load criticality of the structural partition, the scanning results are accurate and meet the accuracy requirements, and the process is efficient.

[0132] The above embodiments are merely illustrative of the principles and effects of this disclosure and are not intended to limit this disclosure. Anyone skilled in the art may modify or alter the above embodiments without departing from the spirit and scope of this disclosure. Therefore, any equivalent modifications or alterations made by a person skilled in the art without departing from the spirit and technical concepts disclosed herein shall be encompassed by the scope of protection of this disclosure.

Claims

1. A building structure scanning method, characterized in that: Applied to three-dimensional scanning of prefabricated buildings; the method comprises: Based on the load criticality of the structure in the prefabricated building, determine the multi-level structural partitions contained in the prefabricated building; wherein, in descending order of load criticality, the multi-level structural partitions include a primary structural partition corresponding to the load connection point, a secondary structural partition corresponding to the prefabricated components as functional modules, and a tertiary structural partition corresponding to the overall prefabricated building and scene information; Determining a scanning resolution and a corresponding scanning device that are adapted in a positive correlation with the load criticality of the structural partition, and determining an execution object that is adapted to the motion mode required to perform the scanning of the structural partition; Scanning of the structural partitions at each level is completed by using execution objects and scanning devices adapted to the structural partitions at each level, and the scanning results of each partition are integrated to construct the building information model of the prefabricated building; each reference positioning node in a reference positioning network is distributed among the reference positioning nodes in each level of the area; and the integration method of the scanning results of each partition includes: Determine the reference position coordinates in each level of structural partitions based on the reference positioning network to map the scanning results of each partition into a unified spatial coordinate system; Based on the determination of overlapping points between adjacent structural partitions, the partition scanning results of adjacent structural partitions are spliced, including: if there are overlapping points belonging to structural partitions of different criticality, taking a weighted sum between the original coordinates of the overlapping points in the multiple structural partitions in which they are located to obtain the confidence coordinates of the overlapping points; wherein the weights of the coordinate sets of the overlapping points in different structural partitions are positively correlated with the load criticality of the structural partitions; according to the confidence coordinates of the overlapping points, the coordinates of other points in the original partition scanning results are corrected to obtain the confidence partition scanning results of each of the original partition scanning results; and the splicing is performed based on the confidence partition scanning results of each structural partition.

2. The building structure scanning method according to claim 1, characterized in that: The scanning of the structural partitions at each level is completed by using the execution objects and scanning devices adapted to the structural partitions at each level, including: identifying the current building block in the secondary structure partition; When the current component is found to be a prefabricated component in the secondary structure partition, structural data associated with the prefabricated component is obtained as a scanning result of the current component.

3. The building structure scanning method according to claim 1, characterized in that: include: Scanning the existing structural data of each prefabricated component, extracting unique corresponding structural feature information based on the measurable data therein, and associating the structural data of each prefabricated component and the corresponding structural feature information and storing them in a prefabricated component library; wherein the measurable data includes at least dimensional data; The scanning of the structural data of the structural partitions at each level is completed by using the execution objects and scanning devices adapted to the structural partitions at each level, including: identifying the current building block in the secondary structure partition; Collect current structural feature information of the current component; Based on the current structural feature information, matching the structural data of the associated prefabricated components in the prefabricated component library; The matched structural data is used as the scanning result of the current component.

4. The building structure scanning method according to claim 2 or 3, characterized in that: The identifying the current component in the secondary structure partition comprises: Detecting the current component by using an infrared perspective device to obtain a detection image; The boundary of the current component in the secondary structure partition is identified according to the detection result to obtain the contour information of the current component.

5. The building structure scanning method according to claim 3, characterized in that: The collecting of current structural feature information of the current component includes: Measuring the acquired contour information of the current component to obtain measurable data of the current component; Current structural feature information is extracted according to the measurable data.

6. The building structure scanning method according to claim 2, characterized in that: The obtaining of the structural data associated with the prefabricated component as the scanning result of the current component includes at least one of the following: 1) determining a corresponding component of the current component in the architectural drawing, and using the structural data associated with the corresponding component as the scanning result of the current component; 2) In the case where a prefabricated component is pre-set with a tag storing its structural data, the structural data pre-set in the tag in the current component is read as the scanning result of the current component.

7. The building structure scanning method according to claim 2, characterized in that: Also includes: In response to not acquiring structural data of the current component as the prefabricated component, determining a scanning movement trajectory according to a central axis of the current component; Scanning of current structural data of the current component is performed along the scanning movement trajectory.

8. The building structure scanning method according to claim 1, characterized in that: The positioning accuracy of the reference positioning node in each structural partition is positively correlated with the load criticality of the structural partition; and / or, the implementation method of the reference positioning node in each structural partition is different, including at least one of the following: 1) the first reference positioning node in the primary structural partition includes a target sphere with a built-in positioning light source; 2) the second reference positioning node in the secondary structural partition includes a UWB positioning base station; 3) the third reference positioning node in the tertiary structural partition includes a GPS / GNSS reference station; and / or, in the calculation of the weighted sum, the original coordinates of the overlapping points in the secondary structural partition are processed by a similarity transformation function that compensates for temperature deformation, and the original coordinates of the overlapping points in the tertiary partition are processed by a projection transformation function that compensates for scale difference; The method further includes: triggering a rescan of the corresponding structural area when detecting that the displacement of the reference positioning node exceeds a preset threshold.

9. A computer device, characterized in that: include: processor and memory; The memory stores computer programs or instructions; The processor is configured to run the computer program or instructions to perform the building structure scanning method according to any one of claims 1 to 8.

10. A computer-readable storage medium, characterized in that A computer program or instruction is stored, and the computer program or instruction is executed to perform the building structure scanning method according to any one of claims 1 to 8.

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