A building measurement method, system, medium and product based on three-dimensional scanning

Abstract

A building measurement method, system, medium and product based on three-dimensional scanning, which relates to the field of surveying, includes: obtaining BIM model data and measurement parameter thresholds of a target building, and determining a partition scanning path according to the BIM model data; scanning the target building according to the partition scanning path to obtain a point cloud data set of the target building; generating a three-dimensional digital model of the target building according to the point cloud data set, and dividing the three-dimensional digital model into several feature areas; each feature area contains at least one feature component; extracting a feature point set in the feature area, and establishing a mapping relationship with a corresponding point set of a corresponding area in the BIM model data; calculating the measured parameters of the feature area based on the mapping relationship; comparing the measured parameters with the measurement parameter threshold, determining the abnormal area and generating a measurement technical report. The implementation of this method can obtain building data more comprehensively and improve the accuracy of building measurement.

Description

Technical Field

[0001] The present application relates to the field of surveying, and in particular to a building measurement method, system, medium and product based on three-dimensional scanning. Background Art

[0002] With the rapid development of the construction industry, the design and construction of buildings are becoming increasingly complex and sophisticated. During the planning supervision and completion acceptance stages, it is necessary to accurately measure key parameters such as the location, size, and height of the building to ensure that the project quality meets the design requirements.

[0003] In related technologies, building surveying mainly uses traditional surveying instruments such as total stations and levels for single-point measurement. Surveyors need to set up multiple survey control points inside and outside the building and obtain spatial coordinate data through point-by-point measurement. For the measurement of building verticality, flatness and other parameters, tools such as theodolites and rulers are usually used, and surveyors need to perform repeated measurements at multiple locations.

[0004] However, in complex spatial environments, the installation and operation of traditional measuring equipment are restricted, which affects the measurement results; for example, for special-shaped buildings and fine components, single-point measurement methods make it difficult to accurately obtain their geometric features. Summary of the invention

[0005] The present application provides a building measurement method, system, medium and product based on three-dimensional scanning, which are used to obtain building data more comprehensively and improve the accuracy of building measurement.

[0006] In a first aspect, the present application provides a building measurement method based on three-dimensional scanning, which is applied to a building measurement system, and the method includes: obtaining BIM model data and measurement parameter thresholds of a target building, and determining a partitioned scanning path according to the BIM model data; scanning the target building according to the partitioned scanning path to obtain a point cloud data set of the target building; generating a three-dimensional digital model of the target building according to the point cloud data set, and dividing the three-dimensional digital model into a number of feature areas; each feature area contains at least one feature component; extracting a feature point set in the feature area, and establishing a mapping relationship with a corresponding point set in a corresponding area in the BIM model data; calculating the measured parameters of the feature area based on the mapping relationship; comparing the measured parameters with the measurement parameter threshold, determining abnormal areas and generating a measurement technical report.

[0007] In the above embodiment, the building measurement system combines the partition scanning path to perform three-dimensional scanning, generates point cloud data and establishes a mapping relationship with the BIM model, thereby realizing comprehensive digital measurement of the building. By dividing the feature area and comparing the measured parameters, the abnormal area can be accurately identified, overcoming the limitations of traditional single-point measurement and improving the measurement efficiency and accuracy.

[0008] In combination with some embodiments of the first aspect, in some embodiments, the step of scanning the target building according to the partitioned scanning path to obtain a point cloud data set of the target building specifically includes: scanning the target building according to the partitioned scanning path, and monitoring the point cloud data density in real time during the scanning process; when the point cloud data density is lower than a preset density threshold, adjusting the sampling frequency of the scanning device; recording the time nodes and adjustment parameters of the sampling frequency adjustment; and segmenting and marking the scanned point cloud data based on the time nodes and adjustment parameters to generate a point cloud data set of the target building.

[0009] In the above embodiment, the building measurement system ensures the integrity and quality of the scanned data by real-time monitoring of the point cloud data density and dynamically adjusting the sampling frequency, and combining time nodes and adjustment parameters for segmentation marking. It can adapt to the measurement needs in complex building environments, ensure that the scanned data density meets the requirements, and improve the reliability of the measurement data.

[0010] In combination with some embodiments of the first aspect, in some embodiments, the steps of comparing the measured parameters with the measurement parameter thresholds, determining the abnormal areas and generating a measurement technical report specifically include: calculating the difference between the measured parameters and the measurement parameter thresholds to obtain a measurement deviation value; determining an abnormality degree mark for the characteristic area based on the measurement deviation value; the abnormality degree mark includes a normal area, a key focus area and a dangerous area; determining the risk index of the key focus area and the dangerous area based on the measurement deviation value, and generating risk assessment data; and generating a measurement technical report based on the abnormality degree mark and the risk assessment data.

[0011] In the above embodiment, the building measurement system establishes a hierarchical management mechanism including normal areas, key areas of concern and dangerous areas by calculating measurement deviation values ​​and marking abnormality levels, and generates risk assessment data in combination with risk indexes, thereby realizing scientific evaluation of building measurement results and risk warning.

[0012] In combination with some embodiments of the first aspect, in some embodiments, after the step of generating a measurement technical report based on the abnormality degree mark and risk assessment data, the method also includes: uploading the three-dimensional digital model and the abnormality degree mark to the remote monitoring platform to generate an abnormality monitoring task; determining the causes of abnormalities in key focus areas and dangerous areas based on the measurement technical report; and generating maintenance recommendations based on the abnormality monitoring tasks, the causes of abnormalities and the environmental monitoring data of the target building.

[0013] In the above embodiment, the building measurement system establishes a remote monitoring platform and an abnormality monitoring task system, and generates targeted maintenance suggestions by analyzing the causes of abnormalities and combining environmental monitoring data, thereby realizing continuous monitoring and preventive maintenance management of buildings.

[0014] In combination with some embodiments of the first aspect, in some embodiments, before obtaining the BIM model data and measurement parameter thresholds of the target building and determining the partition scanning path based on the BIM model data, the method also includes: collecting historical detection data of the target building; the historical detection data includes past measurement data and environmental monitoring data; performing time series analysis on the past measurement data and environmental monitoring data to determine the environmental factors affecting the deformation of the building; inputting the environmental factors into the deformation prediction model to obtain the expected deformation range of the target building in each area; and correcting the measurement parameter threshold according to the expected deformation range.

[0015] In the above embodiment, the building measurement system collects historical detection data for time series analysis, identifies environmental factors that affect building deformation, determines the expected deformation range with a deformation prediction model, realizes dynamic optimization of measurement parameter thresholds, and improves the scientific nature of the measurement standard.

[0016] In combination with some embodiments of the first aspect, in some embodiments, before obtaining the BIM model data and measurement parameter thresholds of the target building, and determining the partition scanning path based on the BIM model data, the method also includes: collecting on-site photo data and control point coordinates of the target building; verifying the BIM model based on the on-site photo data and generating model difference marking data; updating the BIM model based on the model difference marking data to obtain corrected BIM model data; determining the scanning site location based on the corrected BIM model data and in combination with the control point coordinates; generating scanning parameters including site interval, scanning density and overlap rate based on the scanning site location, and determining the scanning order of the scanning site location.

[0017] In the above embodiment, the building measurement system verifies and updates the BIM model through on-site photo data and control point coordinates, optimizes scanning parameters based on the scanning site location, ensures the pertinence and feasibility of the measurement plan, and improves measurement efficiency.

[0018] In combination with some embodiments of the first aspect, in some embodiments, the step of verifying the BIM model based on the on-site photo data and generating model difference marking data specifically includes: converting the BIM model into a three-dimensional mesh model to generate a simulated image with the same perspective as the on-site photo data; calculating the feature similarity between the on-site photo data and the simulated image; when the feature similarity is lower than a preset similarity threshold, determining that the corresponding area is a difference area; determining the spatial distribution characteristics and component properties of the difference area, and generating model difference marking data.

[0019] In the above embodiment, the building measurement system realizes the accurate comparison between the BIM model and the actual building through three-dimensional grid model conversion and feature similarity calculation, can accurately identify the difference area and determine its spatial distribution characteristics, and improves the accuracy of model updating.

[0020] In a second aspect, an embodiment of the present application provides a building measurement system, which includes: one or more processors and a memory; the memory is coupled to the one or more processors, the memory is used to store computer program code, the computer program code includes computer instructions, and the one or more processors call the computer instructions to enable the building measurement system to perform the method described in the first aspect and any possible implementation method of the first aspect.

[0021] In a third aspect, an embodiment of the present application provides a computer program product comprising instructions, and when the computer program product is run on a building measurement system, the building measurement system executes the method described in the first aspect and any possible implementation manner of the first aspect.

[0022] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, comprising instructions. When the instructions are executed on a building measurement system, the building measurement system executes the method described in the first aspect and any possible implementation manner of the first aspect.

[0023] It can be understood that the building measurement system provided in the second aspect, the computer program product provided in the third aspect, and the computer storage medium provided in the fourth aspect are all used to execute the method provided in the embodiment of the present application. Therefore, the beneficial effects that can be achieved can refer to the beneficial effects in the corresponding method, and will not be repeated here.

[0024] One or more technical solutions provided in the embodiments of the present application have at least the following technical effects or advantages:

[0025] 1. Due to the use of partition scanning path planning and three-dimensional scanning data acquisition methods based on BIM model data, combined with the measurement mechanism established by feature area division and mapping relationship, it is possible to achieve all-round and high-precision digital measurement of buildings, effectively solving the problems of low efficiency, limited coverage, and difficulty in dealing with complex building structures in traditional single-point measurement in existing technologies, realizing the standardization of the measurement process, and improving measurement efficiency and data accuracy.

[0026] 2. Due to the use of a remote monitoring platform combined with a management mechanism for abnormal monitoring tasks, as well as an analysis of the causes of abnormalities based on measurement technology reports and a comprehensive evaluation method for environmental monitoring data, real-time monitoring and intelligent diagnosis of abnormal conditions in buildings are achieved, effectively solving the problems of difficult timely detection of abnormal conditions in buildings, incomplete risk assessment, and lack of targeted maintenance plans in existing technologies. Preventive maintenance and risk management of buildings are achieved, and the safety and service life of buildings are improved.

[0027] 3. Due to the adoption of the BIM model verification mechanism based on on-site photo data and control point coordinates, as well as the scanning site location optimization and scanning parameter adaptive adjustment method, it is possible to ensure a high degree of consistency between the measurement data and the actual building conditions, effectively solving the problems of deviation between the BIM model and the actual building, incomplete scanning coverage, and unstable measurement accuracy in the existing technology, achieving accurate planning and execution of the measurement plan, and ensuring the integrity and reliability of the measurement data. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] Figure 1 It is a flow chart of a building measurement method based on three-dimensional scanning in an embodiment of the present application;

[0029] Figure 2 is another flow chart of the building measurement method based on three-dimensional scanning in an embodiment of the present application;

[0030] Figure 3 It is a schematic diagram of the structure of a physical device of the building measurement system in the embodiment of the present application. DETAILED DESCRIPTION

[0031] The terms used in the following embodiments of the present application are only for the purpose of describing specific embodiments, and are not intended to be used as limitations to the present application. As used in the specification of the present application, the singular expressions "one", "a kind of", "above", "the" and "this" are intended to also include plural expressions, unless there is a clear indication to the contrary in the context. It should also be understood that the term "and / or" used in the present application refers to any or all possible combinations comprising one or more of the listed items.

[0032] In the following, the terms "first" and "second" are used for descriptive purposes only and are not to be understood as suggesting or implying relative importance or implicitly indicating the number of the indicated technical features. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of the features, and in the description of the embodiments of the present application, unless otherwise specified, "plurality" means two or more.

[0033] For ease of understanding, the application scenarios of the embodiments of the present application are introduced below.

[0034] A city is building a 300-meter-high super-high-rise commercial complex. Its facade adopts a hyperbolic glass curtain wall design. The internal structure is complex, including multiple special-shaped spaces and cantilever structures. During the construction process, it is necessary to regularly measure the geometric parameters of the building to ensure that the construction quality meets the design requirements. In particular, for the installation of the curtain wall system, the verticality deviation is required to be no more than 3mm / m, and the flatness deviation is required to be no more than 2mm / m. At the same time, due to the complex structure of the building, it is necessary to monitor the deformation of each floor slab and core tube to ensure structural safety.

[0035] In the related art, single-point measurement can be performed by using traditional measuring equipment such as total stations and levels, and control points can be set on the surface of the building to obtain the geometric parameters of the building by manual point-by-point measurement. This method can obtain basic position and size data, but the measurement efficiency is low and the coverage is limited. The following introduces the scenario of using the building measurement method based on 3D scanning in the related art.

[0036] The surveying team used traditional total stations and levels for single-point measurements. They set up 30 measurement control points around the building, and each measurement required four engineers to set up instruments at different locations to collect data point by point. For the verticality measurement of the curtain wall, they used a theodolite to select three measurement points on each floor for observation. This method encountered multiple problems in actual operation: sparse measurement points cannot fully reflect the state of the building; special-shaped surfaces are difficult to measure accurately; errors are prone to occur when multiple people collaborate; a single measurement takes more than two days; and in some areas, the measurement cannot be completed due to limited equipment installation.

[0037] The building measurement method based on 3D scanning in the embodiment of the present application is adopted, through comprehensive scanning and real-time monitoring mechanism, high-precision and all-round measurement of buildings is achieved, and measurement efficiency is improved. The following introduces the scenario of using the building measurement method based on 3D scanning in the present application.

[0038] After adopting this solution, the team first obtained the BIM model of the building, systematically planned 15 optimal scanning sites, and used a 3D laser scanner for automated measurement. During the scanning process, the system monitored data density in real time and automatically adjusted sampling parameters to ensure measurement quality. Finally, the entire building was scanned within 8 hours, and complete point cloud data with an accuracy of 1mm was obtained, accurately identifying all abnormal areas.

[0039] It can be seen that the use of the three-dimensional scanning-based building measurement method in the embodiment of the present application can not only achieve accurate measurement of buildings, but also effectively solve the problems of limited coverage, low efficiency, and difficulty in dealing with complex structures in traditional measurement methods, thereby realizing intelligent and precise building measurement.

[0040] For ease of understanding, the following describes the process of the method provided by this implementation in combination with the above scenario. Figure 1 , which is a flow chart of a building measurement method based on three-dimensional scanning in an embodiment of the present application.

[0041] S101, acquiring BIM model data and measurement parameter thresholds of a target building, and determining a partition scanning path according to the BIM model data.

[0042] Among them, BIM model data represents the digital expression of the building information model, including the geometric information, spatial relationships and component properties of the building; the measurement parameter threshold refers to the allowable deviation range of various measurement indicators of the building, such as the standard limit of parameters such as verticality and flatness; the partition scanning path is used to represent the movement trajectory of the 3D scanning equipment during the measurement process and the measurement station layout plan. For example, the BIM model data of an office building contains information such as the floor plan layout and facade structure of each floor, and the measurement parameter threshold stipulates that the verticality deviation of the wall does not exceed 3mm / m.

[0043] Before starting the measurement task, the building measurement system needs to first obtain the basic data and reference standards required for measurement. Specifically, the system first reads the BIM model data of the target building from the database or file system, and obtains the measurement parameter thresholds specified in the relevant specifications. Then, based on the spatial layout information in the BIM model, combined with factors such as the complexity of the building and the measurement accuracy requirements, the system divides the entire building into multiple measurement areas through a spatial division algorithm, and plans the optimal scanning path for each area to ensure the integrity and accuracy of the scanning data.

[0044] In some embodiments, the scanning path planning can be implemented in a variety of ways: optionally, these steps include first dividing the building area, determining the importance of each area, generating a regional scanning order table, calculating the optimal station position of the scanning device, and connecting each station position to form a scanning path; optionally, these steps include defining the measurement area grid based on a graphic search algorithm, calculating the accessibility of each grid unit, optimizing the site layout density, generating a measurement path map, and verifying the feasibility of the path. It is understandable that other algorithms or methods can also be used to implement the scanning path planning, which is not limited here.

[0045] S102: Scan the target building according to the partition scanning path to obtain a point cloud data set of the target building.

[0046] Point cloud datasets are used to represent digital measurement results consisting of a large number of spatial coordinate points, each of which contains information such as location coordinates and reflection intensity. For example, scanning a building facade may require setting up multiple scanning stations at different heights and angles, with each station collecting millions of measurement points.

[0047] After completing the scanning path planning, the building measurement system starts to perform field scanning and measurement. Specifically, the system controls the 3D laser scanner to perform measurements in sequence according to the preset partition scanning path, and obtains spatial point data on the building surface through horizontal and vertical rotation scanning at each scanning station. During the scanning process, the system records the 3D coordinates, reflection intensity, scanning angle and other information of each measurement point in real time, and organizes these data into a structured point cloud data set.

[0048] In some embodiments, point cloud data can be collected in a variety of ways: optionally, these steps include setting scanning resolution parameters, adjusting the horizontal position of the scanner, performing 360-degree rotation scanning, recording raw measurement data, and performing noise filtering; optionally, these steps include configuring a multi-station joint scanning solution, laying out a control point network, performing regional scanning, real-time monitoring of data quality, and merging multi-station data. It is understandable that other scanning strategies or data collection methods can also be used, which are not limited here.

[0049] S103: Generate a three-dimensional digital model of the target building according to the point cloud data set, and divide the three-dimensional digital model into a plurality of feature areas.

[0050] Among them, the 3D digital model represents the virtual geometric model of the building reconstructed based on the point cloud data, including geometric features such as surface and edge; the characteristic area refers to the building space unit with specific functions or structural characteristics; the characteristic component is used to represent the basic structural elements such as walls, columns, beams, etc. in the building. For example, the facade of a building can be divided into characteristic areas such as curtain wall area and entrance and exit area.

[0051] After obtaining a complete point cloud data set, the building measurement system needs to process the data and reconstruct the model. Specifically, the system first registers, de-noises and simplifies the point cloud data, and then uses a surface reconstruction algorithm to generate a three-dimensional mesh model of the building. Next, based on the geometric features and spatial relationships of the building components, the system divides the three-dimensional model into multiple feature areas with clear boundaries, each of which contains one or more complete building components.

[0052] In some embodiments, model reconstruction and region division can be achieved in a variety of ways: optionally, these steps include performing point cloud data filtering, constructing triangular meshes, generating surface models, identifying geometric features, and dividing feature regions; optionally, these steps include extracting the main direction of the point cloud, fitting basic geometric bodies, reconstructing component models, analyzing spatial relationships, and determining region boundaries. It is understandable that other model reconstruction or region division methods can also be used, which are not limited here.

[0053] S104: extracting a feature point set in the feature area, and establishing a mapping relationship with a corresponding point set in the corresponding area in the BIM model data.

[0054] The feature point set refers to a set of representative key measurement points in the feature area; the corresponding point set refers to the theoretical reference points in the BIM model that correspond to the positions of the feature point set. For example, the feature point set of a wall may include key position points such as the four corner points and the center point.

[0055] After completing the division of feature areas, the building measurement system needs to establish the correspondence between the measured data and the design model. Specifically, the system first extracts representative feature points in each feature area, such as boundary points, corner points, and endpoints of feature lines. Then, the system searches for theoretical position points corresponding to these feature points in the BIM model, and establishes a mapping relationship between the two sets of points through a spatial transformation algorithm, providing a basis for subsequent parameter calculations.

[0056] In some embodiments, feature point mapping can be implemented in a variety of ways: optionally, these steps include detecting regional feature points, matching theoretical reference points, calculating transformation matrices, optimizing mapping parameters, and verifying mapping accuracy; optionally, these steps include extracting regional contours, locating feature nodes, establishing spatial correspondences, estimating deformation parameters, and evaluating matching quality. It is understandable that other feature extraction or mapping methods can also be used, which are not limited here.

[0057] S105. Calculate measured parameters of the feature area based on the mapping relationship.

[0058] The mapping relationship represents the spatial transformation relationship between the measured feature points and the BIM model reference points; the measured parameters refer to the actual geometric parameters of the building obtained through calculation, including verticality, flatness, inclination and other measurement indicators. For example, the actual verticality parameters of the wall can be obtained by calculating the spatial distribution of the feature points on the wall.

[0059] After establishing the point set mapping relationship, the building measurement system begins to calculate various measured parameters. Specifically, the system first calculates the spatial transformation matrix between the measured point set and the theoretical point set in each feature area based on the established mapping relationship. Then, the system calculates the measured values ​​of various geometric parameters, such as the position deviation, angle deviation, and deformation of the component, based on the transformation matrix and point set distribution characteristics. The reliability of the parameters is also evaluated during the calculation process to ensure the accuracy of the measurement results.

[0060] In some embodiments, parameter calculation can be implemented in a variety of ways: optionally, these steps include constructing a least squares equation, solving transformation parameters, calculating geometric features, evaluating calculation accuracy, and generating a parameter report; optionally, these steps include establishing geometric constraint relationships, fitting characteristic surfaces, calculating measurement indicators, analyzing error sources, and outputting calculation results. It is understandable that other mathematical models or calculation methods can also be used to implement parameter solution, which is not limited here.

[0061] S106: Compare the measured parameters with the measurement parameter thresholds, determine the abnormal area and generate a measurement technical report.

[0062] The measurement parameter threshold represents the allowable deviation range of each measurement indicator; the abnormal area refers to the building area where the measured parameters exceed the threshold range; the measurement technical report is used to represent a comprehensive document containing measurement results, abnormal analysis and evaluation suggestions. For example, when the verticality deviation of a column exceeds the specification requirements, the area will be marked as an abnormal area.

[0063] After obtaining all measured parameters, the building measurement system conducts quality assessment and abnormality analysis. Specifically, the system compares the measured parameters of each feature area with the preset parameter threshold and identifies abnormal areas that exceed the allowable deviation range. For the abnormal areas found, the system further analyzes their abnormality degree and spatial distribution characteristics, and comprehensively evaluates the overall quality of the building. Finally, the system automatically generates a technical report containing measurement data, abnormality analysis and processing suggestions.

[0064] In some embodiments, abnormality analysis and report generation can be implemented in a variety of ways: optionally, these steps include checking parameter compliance, calculating abnormality degree, determining risk level, analyzing abnormality causes, and generating treatment suggestions; optionally, these steps include establishing an abnormality assessment model, analyzing spatial correlation, assessing structural safety, formulating monitoring plans, and compiling technical reports. It is understandable that other assessment methods or report formats can also be used to implement abnormality analysis and result output, which are not limited here.

[0065] It should be noted that the anomaly assessment model used in this application uses labeled anomaly case data for training during model training. The input includes measurement deviation values, component importance, environmental conditions and other features, and the output is risk level and early warning suggestions. The training standard is to improve the accuracy and recall rate of anomaly identification. The anomaly assessment model adopts a multi-level evaluation structure, including a parameter deviation analysis layer, a risk level determination layer and an early warning strategy generation layer, to achieve end-to-end analysis from measurement data to risk assessment. The anomaly assessment model receives the deviation data of the measured parameters and the threshold, outputs the evaluation results including the abnormality degree mark (normal area, key focus area and dangerous area) and the risk index, and generates corresponding maintenance recommendations.

[0066] In the above embodiment, the system achieves comprehensive measurement of the building by acquiring BIM model data and measurement parameter thresholds combined with 3D scanning technology. In actual applications, the system can dynamically adjust scanning parameters according to real-time monitoring results to ensure the integrity and accuracy of measurement data, and achieve continuous status monitoring and early warning through a remote monitoring platform.

[0067] The following is a supplement to the scenario of this embodiment.

[0068] As the project progressed, the system accumulated a large amount of historical measurement data. Through analysis, it was found that temperature changes and wind loads were the main environmental factors affecting curtain wall deformation. Based on this, the system optimized the measurement parameter thresholds and established an intelligent early warning mechanism. After detecting that the local deformation of the 12-story curtain wall exceeded the standard, the system immediately started the abnormal monitoring task and continued to track the change trend through the remote monitoring platform. Combined with the analysis of environmental monitoring data, it accurately determined that the problem was caused by installation stress concentration, and provided professional maintenance suggestions in a timely manner. This intelligent monitoring and early warning mechanism improves the efficiency and accuracy of building maintenance.

[0069] After combining the above scenarios, the following is a more detailed description of the process of the method provided by this implementation. Figure 2 , is another flow chart of the building measurement method based on three-dimensional scanning in an embodiment of the present application.

[0070] S201, collecting on-site photo data and control point coordinates of the target building.

[0071] Among them, the on-site photo data refers to a set of high-definition images obtained by taking full-scale photos of the target building; the control point coordinates refer to fixed measurement reference points with known three-dimensional coordinates arranged on the building. For example, a building facade may have 10 control points, each of which has a precise spatial coordinate value and is equipped with high-definition photos from three angles: near, medium, and far.

[0072] Before starting the measurement work, the building measurement system needs to obtain the actual condition data of the building. Specifically, the building measurement system first obtains all-round photos of the building from different angles and distances based on the high-definition camera used by the surveyors to ensure that each area has sufficiently clear image coverage. At the same time, the building measurement system can also communicate with high-precision measurement equipment such as total stations used by surveyors to measure the coordinates of control points pre-arranged on the surface of the building, and establish a complete control network system to provide a benchmark for subsequent model verification and scanning positioning.

[0073] S202: Verify the BIM model based on the on-site photo data and generate model difference marking data.

[0074] Model difference mark data refers to a data set that records the location, type, and degree of difference between the actual building and the BIM model; feature similarity is used to indicate the degree of match between the actual image and the model-generated image. For example, if the actual size of a building's exterior wall deviates by 5 cm from the BIM model, it will be recorded as a size difference mark.

[0075] After the building measurement system obtains the on-site data, it needs to verify the accuracy of the BIM model. Specifically, the system first converts the BIM model into a rendered image with the same perspective as the on-site photo, and then compares the feature similarity between the on-site photo and the rendered image through an image matching algorithm. For areas where the similarity is lower than the threshold, the system automatically marks them as difference areas, and records the type, location and degree of the difference, generating structured difference marking data.

[0076] In some embodiments, model verification can be implemented in a variety of ways: optionally, these steps include generating model views, extracting image features, calculating feature matching, identifying difference areas, classifying difference types, and recording difference information; optionally, these steps include aligning image coordinates, constructing feature descriptions, performing similarity analysis, determining difference boundaries, evaluating the degree of difference, and generating difference reports. It is understandable that other image processing or model comparison methods can also be used to implement the verification process, which is not limited here.

[0077] In some embodiments, the building measurement system converts the BIM model into a three-dimensional grid model, generates a simulated image with the same perspective as the on-site photo data; calculates the feature similarity between the on-site photo data and the simulated image; when the feature similarity is lower than a preset similarity threshold, determines the corresponding area as a difference area; determines the spatial distribution characteristics and component properties of the difference area, and generates model difference marking data.

[0078] Among them, the three-dimensional mesh model represents a digital building model composed of polygonal meshes; the simulated image refers to a rendered image of a specific perspective generated based on the BIM model; the feature similarity is used to indicate the degree of matching between the two images in terms of texture, edges and other features; the difference area indicates the spatial range where there is a significant inconsistency between the actual building and the model; the component attributes refer to the basic features of the building components, such as type and material. For example, when the actual texture of a building's exterior wall is less than 80% similar to the simulated image generated by the BIM model, the area will be marked as a difference area.

[0079] When the building measurement system verifies the BIM model, it needs to convert the model data into a comparable form. Specifically, the system first converts the BIM model into a three-dimensional grid structure, and generates a corresponding simulated image based on the shooting position and angle of the on-site photos. Then, the image processing algorithm is used to extract and compare the feature information of the two types of images, and the feature similarity is calculated. When the similarity is lower than the preset threshold, the system automatically marks it as a difference area, and further analyzes the spatial distribution and component characteristics of these areas, and finally generates detailed difference marking data.

[0080] In some embodiments, model verification and difference analysis can be implemented in a variety of ways: optionally, these steps include importing BIM models, generating grid structures, setting rendering parameters, generating simulated images, extracting image features, and calculating feature matching; optionally, these steps include aligning image coordinates, building feature descriptors, performing similarity analysis, marking difference locations, analyzing spatial relationships, and generating difference reports. It is understandable that other image processing or model comparison methods can also be used to implement the verification process, which is not limited here.

[0081] S203: updating the BIM model according to the model difference mark data to obtain corrected BIM model data.

[0082] After completing the model verification, the building measurement system will update and correct the BIM model. Specifically, the system will modify the BIM model according to the preset model update rules based on the various types of difference information recorded in the difference mark data. The modification process includes adjusting component parameters, updating geometric features, correcting spatial relationships, etc., to ensure that the revised model can accurately reflect the actual condition of the building.

[0083] In some embodiments, model updating can be achieved in a variety of ways: optionally, these steps include analyzing difference types, determining update strategies, modifying model parameters, verifying update results, recording modification history, and exporting updated models; optionally, these steps include extracting difference information, establishing modification plans, performing parameter adjustments, checking model consistency, evaluating update effects, and saving model versions. It is understandable that other modeling methods or update strategies can also be used to achieve model correction, which is not limited here.

[0084] S204: Determine the scanning site location based on the corrected BIM model data and the control point coordinates.

[0085] The scanning station location refers to the location of the 3D laser scanner; the control point coordinates refer to the known coordinate points used for positioning and registration. For example, 20 scanning stations may be required around a building to ensure complete coverage.

[0086] After obtaining an accurate BIM model, the building measurement system begins to plan the scanning measurement plan. Specifically, the system performs field analysis based on the revised BIM model, combines the spatial distribution of control points, and calculates the best scanning site location through an optimization algorithm. The site layout will be based on the technical parameters of the scanning equipment, the complexity of the building, obstruction conditions and other factors to ensure the integrity and accuracy of the measurement data.

[0087] In some embodiments, site planning can be implemented in a variety of ways: optionally, these steps include performing visibility analysis, calculating coverage, optimizing site distribution, evaluating measurement accuracy, determining site coordinates, and generating a site map; optionally, these steps include establishing a spatial grid, analyzing occlusion relationships, calculating optimal positions, verifying measurement angles, adjusting site density, and outputting a layout plan. It is understandable that other optimization algorithms or planning methods can also be used to implement site layout, which is not limited here.

[0088] S205 . Generate scanning parameters including station interval, scanning density and overlap rate according to the scanning station positions, and determine the scanning order of the scanning station positions.

[0089] Among them, the station interval refers to the spatial distance between adjacent scanning stations; the scanning density refers to the number of measurement points per unit area; the overlap rate is used to indicate the degree of data overlap between adjacent scanning areas; and the scanning order indicates the measurement order of each station. For example, a building facade scan may require that the station interval does not exceed 10 meters, the point density is not less than 100 points / square meter, and the overlap rate of adjacent stations reaches 30%.

[0090] After determining the site location, the building measurement system needs to develop a detailed scanning parameter plan. Specifically, the system calculates the optimal site spacing, scanning density, and overlap rate parameters based on the building's geometric characteristics and measurement accuracy requirements. At the same time, the system considers measurement efficiency and on-site conditions, optimizes the measurement sequence of scanning sites, and generates a complete scanning operation guidance plan.

[0091] In some embodiments, scanning parameter planning can be implemented in a variety of ways: optionally, these steps include analyzing measurement requirements, setting basic parameters, calculating site spacing, determining density levels, optimizing overlapping areas, and planning scanning routes; optionally, these steps include evaluating measurement accuracy, adjusting scanning parameters, verifying coverage, optimizing measurement sequences, generating work instructions, and formulating emergency plans. It is understandable that other parameter optimization or path planning methods can also be used to implement scanning scheme design, which is not limited here.

[0092] S206: Obtain BIM model data and measurement parameter thresholds of the target building, and determine a partition scanning path according to the BIM model data.

[0093] Referring to step S101 , the building measurement system determines BIM model data, measurement parameter thresholds, and partition scanning paths.

[0094] In some embodiments, the building measurement system collects historical inspection data of the target building; the historical inspection data includes past measurement data and environmental monitoring data; time series analysis is performed on the past measurement data and environmental monitoring data to determine the environmental factors that affect the deformation of the building; the environmental factors are input into the deformation prediction model to obtain the expected deformation range of the target building in each area; and the measurement parameter threshold is corrected according to the expected deformation range.

[0095] Among them, historical inspection data refers to the measurement and monitoring records of the building in the past; past measurement data refers to the measurement results of various geometric parameters previously conducted; environmental monitoring data is used to represent the historical records of environmental factors such as temperature, humidity, and load. For example, the seasonal deformation data of a building caused by temperature changes in the past year can be used to predict future deformation trends.

[0096] Before determining the threshold of measurement parameters, the building measurement system needs to analyze historical data to improve the scientific nature of the threshold. Specifically, the system first extracts the historical inspection records of the building from the database, including regular measurement data and continuous environmental monitoring data. Through the time series analysis method, the system identifies the key environmental factors that affect the deformation of the building, and inputs these factors into a special deformation prediction model to calculate the expected deformation range of each area, and finally makes reasonable adjustments to the measurement parameter threshold accordingly.

[0097] It should be noted that when training the deformation prediction model, the historical inspection data of the building is used as the training set, including past measurement data (such as displacement and deformation of each component) and environmental monitoring data (such as temperature, humidity, wind force, load, etc.). The mapping relationship between environmental factors and building deformation is established through the time series analysis method. The training goal is to minimize the error between the predicted deformation value and the actual deformation value. The deformation prediction model adopts a time series prediction architecture, including an environmental factor feature extraction module, a time series correlation analysis module, and a deformation prediction module, which can capture the impact of environmental changes on building deformation at different time scales. The deformation prediction model receives real-time environmental monitoring data as input and outputs the expected deformation range of each area, which is used to dynamically adjust the measurement parameter threshold.

[0098] In some embodiments, historical data analysis and threshold correction can be achieved in a variety of ways: optionally, these steps include collecting historical data, cleaning outliers, performing time series analysis, identifying key factors, establishing a prediction model, and calculating deformation expectations; optionally, these steps include building a data model, analyzing change rules, evaluating environmental impacts, predicting deformation trends, optimizing threshold parameters, and generating analysis reports. It is understandable that other data analysis or prediction methods can also be used to achieve scientific determination of thresholds, which is not limited here.

[0099] S207, scanning the target building according to the partition scanning path, and monitoring the point cloud data density in real time during the scanning process.

[0100] The point cloud data density refers to the number of measurement points actually acquired per unit area. For example, the system may monitor whether the point density of the current scanning area meets the standard every 1 second.

[0101] When the building measurement system starts field scanning, it needs to ensure the quality of data collection. Specifically, the system performs the measurement task according to the partitioned scanning path, and starts the real-time monitoring module to continuously evaluate the collection density of point cloud data. The monitoring process includes calculating the point density of the local area, analyzing the uniformity of data distribution, evaluating the quality of measurement data, etc., to ensure that the scanning results meet the measurement requirements.

[0102] In some embodiments, scanning monitoring can be implemented in a variety of ways: optionally, these steps include performing regional scanning, calculating real-time density, comparing target requirements, marking abnormal areas, adjusting scanning parameters, and recording monitoring data; optionally, these steps include dividing the monitoring grid, counting point distribution, analyzing density changes, identifying problem areas, generating monitoring reports, and saving raw data. It is understandable that other monitoring algorithms or quality control methods can also be used to implement scanning process management, which is not limited here.

[0103] S208. When the point cloud data density is lower than a preset density threshold, adjust the sampling frequency of the scanning device.

[0104] The preset density threshold represents the minimum point density requirement for the scanned data; the sampling frequency refers to the data acquisition rate of the scanning device. For example, when the point density of a certain area is detected to be lower than 80 points / square meter, the system will automatically increase the sampling frequency.

[0105] When performing density monitoring, the building measurement system needs to respond to abnormal situations in a timely manner. Specifically, the system compares the monitored point cloud density with the preset threshold in real time. When the density is found to be insufficient, the sampling frequency adjustment mechanism is immediately triggered. The adjustment process needs to consider factors such as equipment performance limitations, measurement accuracy requirements, and scanning efficiency to ensure data collection quality while maintaining reasonable operating efficiency.

[0106] In some embodiments, parameter adjustment can be implemented in a variety of ways: optionally, these steps include detecting density anomalies, calculating adjustment amplitudes, modifying sampling parameters, verifying adjustment effects, recording parameter changes, and monitoring device status; optionally, these steps include analyzing density distribution, establishing adjustment models, performing progressive adjustments, evaluating data quality, optimizing adjustment strategies, and saving adjustment records. It is understandable that other adaptive algorithms or control strategies can also be used to implement sampling parameter adjustment, which is not limited here.

[0107] S209: Record the time node and adjustment parameters of the sampling frequency adjustment.

[0108] The time node indicates the specific moment when the sampling frequency is adjusted; the adjustment parameter refers to the change value of the sampling frequency at each adjustment. For example, the system may adjust the sampling frequency from 50Hz to 75Hz at 10:30:45, and all information about this adjustment event will be fully recorded.

[0109] When the building measurement system performs sampling frequency adjustment, it needs to save complete information of the adjustment process. Specifically, the system will accurately record the timestamp of each adjustment, the parameter values ​​before and after the adjustment, the reason for the adjustment, and other information. These records contain both time series information and spatial location information, forming complete parameter adjustment history data, which provides an important basis for subsequent data processing and quality assessment.

[0110] In some embodiments, parameter recording can be implemented in a variety of ways: optionally, these steps include generating timestamps, saving parameter values, recording adjustment reasons, associating spatial locations, establishing index structures, and verifying record integrity; optionally, these steps include creating log entries, storing environmental data, marking data segments, maintaining adjustment history, analyzing adjustment rules, and exporting record reports. It is understandable that other data recording or storage methods can also be used to implement tracking and management of parameter adjustments, which are not limited here.

[0111] S210 , segment and label the scanned point cloud data based on the time nodes and adjustment parameters to generate a point cloud data set of the target building.

[0112] The segmentation mark refers to the identification information for dividing the time period of the point cloud data; the point cloud dataset refers to the structured data that fully records the three-dimensional spatial information of the building. For example, a facade scan may contain multiple data segments with different sampling parameters, and each data segment has a corresponding parameter mark.

[0113] After the building measurement system completes the scan, it needs to organize and mark the collected data. Specifically, the system divides the point cloud data obtained during the entire scanning process into multiple data segments according to the recorded time nodes and adjustment parameters. Corresponding parameter tags are added to each data segment, including sampling frequency, scanning density, quality assessment and other information, and finally all data segments are integrated into a complete point cloud data set.

[0114] In some embodiments, data collation can be achieved in a variety of ways: optionally, these steps include dividing time periods, adding parameter tags, merging data segments, checking data integrity, evaluating data quality, and generating data reports; optionally, these steps include establishing data indexes, associating parameter information, marking data attributes, optimizing data structures, verifying data consistency, and exporting collation results. It is understandable that other data organization or management methods can also be used to achieve segmented labeling of point cloud data, which is not limited here.

[0115] S211, generating a three-dimensional digital model of the target building according to the point cloud data set, and dividing the three-dimensional digital model into a plurality of characteristic regions, each of which contains at least one characteristic component.

[0116] Referring to step S103 , the building measurement system generates a three-dimensional digital model and determines the characteristic area.

[0117] S212: Extract feature point sets in the feature area, and establish a mapping relationship with corresponding point sets in the corresponding area in the BIM model data.

[0118] Referring to step S104 , the building measurement system will suggest a mapping relationship.

[0119] S213. Calculate measured parameters of the feature area based on the mapping relationship.

[0120] Referring to step S105 , the building measurement system determines the measured parameters.

[0121] S214: Compare the measured parameters with the measurement parameter thresholds, determine the abnormal area and generate a measurement technical report.

[0122] Referring to step S106 , the building measurement system generates a technical report.

[0123] In some embodiments, the building measurement system calculates the difference between the measured parameters and the measurement parameter threshold to obtain a measurement deviation value; determines the abnormality degree mark of the characteristic area based on the measurement deviation value; the abnormality degree mark includes a normal area, a key focus area and a dangerous area; determines the risk index of the key focus area and the dangerous area based on the measurement deviation value, and generates risk assessment data; generates a measurement technical report based on the abnormality degree mark and the risk assessment data.

[0124] Among them, the abnormal degree mark refers to the graded identification of the safety status of the building area; the risk index is used to indicate the quantitative value of the danger level of the abnormal area; and the risk assessment data represents the assessment result including comprehensive information such as risk level and impact range. For example, when the verticality deviation of a support column exceeds the threshold of 20%, it may be marked as a key focus area and assigned a corresponding risk index.

[0125] After obtaining the measured parameters, the building measurement system needs to conduct a systematic risk assessment. Specifically, the system first calculates the difference between the measured parameters and the threshold value of each characteristic area, and classifies the area into three levels: normal, key concern, and dangerous according to the degree of deviation. For abnormal areas, the system further calculates its risk index, comprehensively considers factors such as the deviation size, component importance, and impact range, and finally generates a technical report containing detailed assessment results and recommended measures.

[0126] In some embodiments, the building measurement system uploads the three-dimensional digital model and abnormality degree mark to the remote monitoring platform to generate an abnormality monitoring task; determines the causes of abnormalities in key focus areas and dangerous areas based on the measurement technical report; and generates maintenance recommendations based on the abnormality monitoring task, the causes of abnormalities and the environmental monitoring data of the target building.

[0127] Among them, the remote monitoring platform refers to the network system used to monitor and manage the status of the building in real time; the abnormal monitoring task refers to the continuous monitoring plan for the abnormal area; the abnormal cause is used to indicate the specific cause of the parameter abnormality; the maintenance suggestion refers to the maintenance plan proposed based on the monitoring results. For example, the system may recommend weekly deformation monitoring of a tilted wall.

[0128] After completing the risk assessment, the building measurement system needs to establish a continuous monitoring mechanism. Specifically, the system uploads the 3D digital model and abnormal marking information to the remote platform and automatically generates targeted monitoring tasks. By analyzing the measurement report and environmental data, the system determines the cause of the abnormal phenomenon and formulates maintenance recommendations based on this information, including monitoring frequency, maintenance methods, emergency plans, etc.

[0129] In some embodiments, remote monitoring and maintenance recommendations can be implemented in a variety of ways: optionally, these steps include configuring monitoring parameters, uploading model data, creating monitoring tasks, analyzing abnormal causes, evaluating maintenance needs, and generating disposal plans; optionally, these steps include establishing a monitoring mechanism, tracking abnormal development, analyzing environmental impacts, formulating maintenance plans, setting warning thresholds, and outputting recommendation reports. It is understandable that other monitoring strategies or maintenance methods can also be used to achieve continuous management of buildings, which are not limited here.

[0130] It should be noted that the above-mentioned determination of the causes of abnormal phenomena and maintenance recommendations uses an exception handling model. The exception handling model is an intelligent system specifically used for building anomaly analysis and processing. In the model training phase, the exception handling model uses a large amount of annotated building anomaly case data as a training set, including measurement data (deviation data between measured parameters and design values, deformation trend data), environmental data (environmental monitoring data such as temperature, humidity, wind load, geological conditions, etc.), component information (basic information such as component type, material properties, stress state, etc.), and expert-confirmed anomaly type, cause analysis, and treatment plan, etc., as well as anomaly annotation information. The training standard is to minimize the error rate of abnormal cause judgment and the unreasonableness of maintenance recommendations, while improving the accuracy of abnormal cause explanation and the feasibility of maintenance plans. The exception handling model adopts a multi-level analysis structure, including feature extraction module, cause analysis module, risk assessment module, and solution generation module, which can realize full-process intelligent analysis from raw data processing to solution generation. The abnormality handling model can receive the currently detected abnormal parameter values, historical monitoring data of the abnormal area, environmental monitoring data and building component information as input, and through multi-level analysis and processing, output a comprehensive analysis result including an abnormality cause analysis report (detailed description of the specific cause of the abnormality), development trend prediction (prediction of the evolution trend of the abnormal situation), risk level assessment (quantitative assessment of the degree of danger of the abnormality) and maintenance suggestions (including treatment plans, monitoring plans and preventive measures). In this way, the abnormality handling model can realize the intelligent processing of the whole process from abnormal phenomenon identification to cause analysis, from risk assessment to plan formulation, and effectively improve the efficiency and accuracy of building maintenance management.

[0131] In the embodiments of the present application, due to the use of three-dimensional scanning measurement technology based on the BIM model, real-time data quality monitoring mechanism, anomaly analysis and remote monitoring methods, it is possible to achieve all-round automated measurement of building geometric parameters and intelligent identification of abnormal conditions, effectively solving the problems of low measurement efficiency, limited coverage, difficulty in dealing with complex structures, and inability to detect anomalies in a timely manner in traditional measurement methods, and realizing the automation of the measurement process, the comprehensiveness of data collection, the accuracy of anomaly identification and the intelligence of maintenance management, thereby improving the efficiency and accuracy of building measurement.

[0132] The following describes the building measurement system in the embodiment of the present invention from the perspective of hardware processing. Figure 3 , which is a schematic diagram of a physical device structure of a building measurement system in an embodiment of the present application.

[0133] It should be noted that Figure 3 The structure of the building measurement system shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present invention.

[0134] like Figure 3 As shown, the building measurement system includes a central processing unit (CPU) 301, which can perform various appropriate actions and processes according to the program stored in the read-only memory (ROM) 302 or the program loaded from the storage part 308 to the random access memory (RAM) 303, such as executing the method described in the above embodiment. In the RAM 303, various programs and data required for system operation are also stored. The CPU 301, the ROM 302 and the RAM 303 are connected to each other through the bus 304. The input / output (I / O) interface 305 is also connected to the bus 304.

[0135] The following components are connected to the I / O interface 305: an input section 306 including an audio input device, a button switch, etc.; an output section 307 including a liquid crystal display (LCD) and an audio output device, an indicator light, etc.; a storage section 308 including a hard disk, etc.; and a communication section 309 including a network interface card such as a LAN (Local Area Network) card, a modem, etc. The communication section 309 performs communication processing via a network such as the Internet. A drive 310 is also connected to the I / O interface 305 as needed. A removable medium 311, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., is installed on the drive 310 as needed so that a computer program read therefrom is installed into the storage section 308 as needed.

[0136] In particular, according to an embodiment of the present invention, the process described above with reference to the flowchart can be implemented as a computer software program. For example, an embodiment of the present invention includes a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program includes a computer program for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network through the communication part 309, and / or installed from a removable medium 311. When the computer program is executed by the central processing unit (CPU) 301, various functions defined in the present invention are performed.

[0137] It should be noted that specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM), a flash memory, an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof. In the present invention, a computer-readable storage medium may be any tangible medium containing or storing a program that may be used by or in combination with an instruction execution system, apparatus, or device.

[0138] The flowcharts and block diagrams in the accompanying drawings illustrate the possible architecture, functions and operations of the systems, methods and computer program products according to various embodiments of the present invention. Each box in the flowchart or block diagram may represent a module, a program segment, or a part of a code, and the above-mentioned module, program segment, or a part of a code contains one or more executable instructions for implementing the specified logical functions. It should also be noted that in some alternative implementations, the functions marked in the box may also occur in an order different from that marked in the accompanying drawings.

[0139] Specifically, the building measurement system of this embodiment includes a processor and a memory. The memory stores a computer program. When the computer program is executed by the processor, the building measurement method based on three-dimensional scanning provided in the above embodiment is implemented.

[0140] As another aspect, the present invention further provides a computer-readable storage medium, which may be included in the building measurement system described in the above embodiment; or may exist independently without being assembled into the building measurement system. The above storage medium carries one or more computer programs, and when the above one or more computer programs are executed by a processor of the building measurement system, the building measurement system implements the building measurement method based on three-dimensional scanning provided in the above embodiment.

[0141] As described above, the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present application.

[0142] As used in the above embodiments, the term "when..." may be interpreted to mean "if..." or "after..." or "in response to determining..." or "in response to detecting...", depending on the context. Similarly, the phrases "upon determining..." or "if (the stated condition or event) is detected" may be interpreted to mean "if determining..." or "in response to determining..." or "upon detecting (the stated condition or event)" or "in response to detecting (the stated condition or event)", depending on the context.

[0143] Those skilled in the art can understand that to implement all or part of the processes in the above-mentioned embodiments, the processes can be completed by computer programs to instruct related hardware, and the programs can be stored in computer-readable storage media. When the programs are executed, they can include the processes of the above-mentioned method embodiments. The aforementioned storage media include: ROM or random access memory RAM, magnetic disk or optical disk and other media that can store program codes.

Claims

1. A building measurement method based on three-dimensional scanning, characterized in that: Applied to a building measurement system, the method comprises: Collect on-site photo data and control point coordinates of the target building; Converting the BIM model into a three-dimensional mesh model to generate a simulated image having the same viewing angle as the on-site photo data; Calculating feature similarity between the on-site photo data and the simulated image; When the feature similarity is lower than a preset similarity threshold, determining the corresponding area as a difference area; Determine the spatial distribution characteristics and component attributes of the difference area, and generate model difference marking data; Update the BIM model according to the model difference mark data to obtain revised BIM model data; Based on the corrected BIM model data and in combination with the control point coordinates, the scanning site location is determined; According to the scanning site positions, generating scanning parameters including site interval, scanning density and overlap rate, and determining the scanning order of the scanning site positions; Acquire BIM model data and measurement parameter thresholds of the target building, and determine a partition scanning path according to the BIM model data; Scan the target building according to the partition scanning path to obtain a point cloud data set of the target building; Generating a three-dimensional digital model of the target building according to the point cloud data set, and dividing the three-dimensional digital model into a plurality of characteristic regions; each characteristic region includes at least one characteristic component; Extracting a feature point set in the feature area and establishing a mapping relationship with a corresponding point set in the corresponding area in the BIM model data; Calculate the measured parameters of the feature area based on the mapping relationship; The measured parameters are compared with the measured parameter thresholds to determine abnormal areas and generate a measurement technical report.

2. The method according to claim 1, characterized in that The step of scanning the target building according to the partition scanning path to obtain a point cloud data set of the target building specifically includes: Scanning the target building according to the partitioned scanning path, and monitoring the point cloud data density in real time during the scanning process; When the density of the point cloud data is lower than a preset density threshold, adjusting the sampling frequency of the scanning device; Recording the time point and adjustment parameters of the sampling frequency adjustment; The scanned point cloud data is segmented and labeled based on the time nodes and the adjustment parameters to generate a point cloud data set of the target building.

3. The method according to claim 1, characterized in that The step of comparing the measured parameter with the measurement parameter threshold, determining the abnormal area and generating a measurement technical report specifically includes: Calculating the difference between the measured parameter and the measured parameter threshold to obtain a measurement deviation value; Determine the abnormality mark of the characteristic area according to the measured deviation value; the abnormality mark includes a normal area, a key focus area and a dangerous area; Determine the risk index of the key focus area and the dangerous area according to the measurement deviation value, and generate risk assessment data; A measurement technology report is generated based on the abnormality level mark and the risk assessment data.

4. The method according to claim 3, characterized in that After the step of generating a measurement technology report according to the abnormality level mark and the risk assessment data, the method further comprises: Uploading the three-dimensional digital model and the abnormality degree mark to a remote monitoring platform to generate an abnormality monitoring task; Determine the causes of abnormalities in the key focus area and the dangerous area based on the measurement technology report; A maintenance suggestion is generated according to the abnormal monitoring task, the abnormal cause and the environmental monitoring data of the target building.

5. The method according to claim 1, characterized in that Before the step of acquiring the BIM model data and the measurement parameter threshold of the target building and determining the partition scanning path according to the BIM model data, the method further includes: Collecting historical inspection data of the target building; the historical inspection data includes past measurement data and environmental monitoring data; Performing time series analysis on the past measurement data and the environmental monitoring data to determine environmental factors that affect building deformation; Inputting the environmental factors into a deformation prediction model to obtain the expected deformation range of the target building in each area; The measurement parameter threshold is modified according to the expected deformation range.

6. A building measurement system, characterized in that: The building measurement system includes: one or more processors and a memory; the memory is coupled to the one or more processors, the memory is used to store computer program code, the computer program code includes computer instructions, and the one or more processors call the computer instructions to enable the building measurement system to execute the method described in any one of claims 1-5.

7. A computer-readable storage medium comprising instructions, characterized in that: When the instructions are executed on a building measurement system, the building measurement system is caused to execute the method according to any one of claims 1 to 5.

8. A computer program product, characterized in that When the computer program product is run on a building measurement system, the building measurement system is enabled to perform the method according to any one of claims 1 to 5.

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