A BIM building model generation and processing optimization method and system

Abstract

The present invention relates to the field of building information modeling technology, and specifically to a BIM building model generation and processing optimization method and system, comprising the following steps: based on a target building to be modeled, adjusting the scanning accuracy level of the differentiated parts according to the importance and structural complexity of the differentiated parts of the building, changing the resolution parameters of a three-dimensional scanning device, and controlling the three-dimensional scanning device to scan the building to obtain basic three-dimensional scanning data. In the present invention, by dynamically adjusting the resolution parameters of the three-dimensional scanning device according to the structural complexity and importance of the building, the scanning process is effectively optimized, allowing the three-dimensional scan to more accurately focus on key structural parts, improving the quality and relevance of data acquisition, extracting structural features through comparative analysis with on-site photos, and promptly discovering and correcting structural errors, ensuring the accuracy and practicality of the model. The model's level of detail is automatically adjusted according to user-set parameters, optimizing the use of computing resources.

Description

Technical Field

[0001] The present invention relates to the technical field of building information modeling, and in particular to a BIM building model generation and processing optimization method and system. Background Art

[0002] The field of building information modeling technology involves the entire process of modeling, simulating, analyzing, and managing all aspects of a construction project through digital means. The core goal of this field is to create a comprehensive, accurate, and collaborative three-dimensional virtual building model by integrating data from multiple professional fields such as architecture, structure, and electromechanical. BIM technology not only covers various stages of the building life cycle, such as design, construction, and operation, but also involves data exchange standards, information sharing, automated calculations, and collaborative work platforms. With the development of technology, BIM has gradually evolved towards intelligence, automation, and precision. The data models involved are becoming increasingly complex, and the relevant optimization methods and algorithms are also constantly being improved to meet the needs of more efficient and accurate building design and construction.

[0003] The BIM building model generation and processing optimization method focuses on improving the efficiency and accuracy of building model generation and processing within BIM systems. This method aims to reduce computational resource consumption during model generation, accelerate the model construction process, and enhance the accuracy and operability of building information models by optimizing algorithms and processing flows. This optimization method is applicable to both the design and construction phases of a building. Through automation, it effectively reduces human error, improves the feasibility of design solutions, and enhances the accuracy of construction plans. This supports efficient management and collaborative work in construction projects, providing precise data support and technical assurance for their smooth implementation and subsequent operation and maintenance.

[0004] When dealing with large-scale or structurally complex construction projects, traditional methods lack precise consideration of the importance and structural complexity of building parts. They use a uniform scanning accuracy for differentiated parts of the building, which cannot capture all key structural details. In addition, they generate a large amount of data, resulting in resource waste and low computational efficiency in the data processing process. In terms of automatically identifying and correcting model errors, traditional methods rely on manual intervention to resolve the differences between the model and the actual building, consuming a large amount of human resources and increasing the risk of errors. Summary of the Invention

[0005] The purpose of the present invention is to solve the shortcomings of the existing technology and propose a BIM building model generation and processing optimization method and system. The technical solution is as follows:

[0006] In one aspect, a BIM building model generation and processing optimization method is provided, comprising the following steps:

[0007] S1: Based on the target building to be modeled, adjust the scanning accuracy level of the differentiated parts according to the importance and structural complexity of the differentiated parts of the building, change the resolution parameters of the 3D scanning device, control the 3D scanning device to scan the building, and obtain basic 3D scanning data;

[0008] S2: Based on the basic 3D scanning data, analyzing the 3D data points, identifying the spatial position of each data point, adjusting the 3D reconstruction parameters, constructing a 3D model of the building, and obtaining a basic 3D model;

[0009] S3: Based on the basic 3D model, compare it with photos of the actual construction site, extract the structural features of the building from the photos, analyze the differences between the 3D model and the actual scene, and obtain model error recognition information;

[0010] S4: Based on the model error identification information, analyzing the type and location of the error data, correcting each error, and obtaining a corrected building model;

[0011] S5: Based on the modified building model, the detail level is adjusted according to the parameters set by the user, the computing resource consumption is optimized, and an optimized BIM model is obtained.

[0012] On the other hand, the basic three-dimensional scanning data includes spatial coordinate accuracy and scanning point density, the basic three-dimensional model includes the three-dimensional coordinates of building components, connection data and reconstructed model texture quality, the model error identification information includes structural alignment errors, size deviations and material mismatch items, the corrected building model includes error-adjusted building angles, window positions and door frame sizes, and the optimized BIM model includes model details, rendering effects and resource occupancy data after view optimization.

[0013] On the other hand, based on the target building to be modeled, the scanning accuracy level of the differentiated parts is adjusted according to the importance and structural complexity of the differentiated parts of the building, the resolution parameters of the 3D scanning device are changed, and the 3D scanning device is controlled to scan the building to obtain the basic 3D scanning data. The specific steps are as follows:

[0014] S101: Based on the target building to be modeled, the required scanning accuracy level of the differentiated structural parts is evaluated according to the importance and structural complexity of the differentiated parts of the building, and the accuracy adjustment parameters are obtained;

[0015] S102: Based on the accuracy adjustment parameters, changing the resolution setting of the three-dimensional scanning device, adjusting the scanner operation mode, matching the scanning accuracy level of the differentiated structure, performing a three-dimensional scan on the building, and obtaining original three-dimensional scanning data;

[0016] S103: Based on the original three-dimensional scanning data, data cleaning is performed, including noise data removal and data missing part supplementation, three-dimensional structure data integration, and data integrity and accuracy verification to obtain basic three-dimensional scanning data.

[0017] On the other hand, the formula for evaluating the scanning accuracy level required for the differentiated structural part is:

[0018]

[0019] Among them, J is the scanning accuracy level, R represents the structural complexity, C represents the component importance weight, I represents the intervention factor, and a J 、b J and c J is the weight coefficient, d J is the normalization coefficient.

[0020] On the other hand, based on the basic 3D scanning data, the 3D data points are analyzed, the spatial position of each data point is identified, the 3D reconstruction parameters are adjusted, and the 3D model of the building is constructed. The steps of obtaining the basic 3D model are specifically as follows:

[0021] S201: Based on the basic three-dimensional scanning data, perform spatial position analysis on the data points, and use coordinate transformation technology to map each scanning point to a corresponding position on the building model to obtain spatial positioning information of the data points;

[0022] S202: Based on the spatial positioning information of the data points and in accordance with the actual model accuracy requirements of the building, adjusting the vertex density of the model, optimizing the distribution of vertices and the performance of the curved surface, and adjusting the 3D reconstruction parameters to obtain 3D reconstruction adjustment information;

[0023] S203: Based on the 3D reconstruction adjustment information, a 3D model of the building is constructed, vertex connection and facet generation are performed, and structural refinement processing is performed on building details, including window frames and door sills. Corresponding materials are assigned to differentiated structures, and the accuracy and detail richness of the model are optimized to obtain a basic 3D model.

[0024] On the other hand, the formula for adjusting the vertex density of the model is:

[0025]

[0026] Among them, V new is the vertex density of the adjusted model, K represents the target accuracy coefficient of the model, S represents the spatial coverage of the data points, L represents the local detail importance coefficient, D represents the average data point density, M is the adjustment factor of the model, P represents the expected number of vertices, and T represents the current number of vertices.

[0027] On the other hand, the steps of comparing the basic 3D model with photos of the actual construction site, extracting the structural features of the building from the photos, analyzing the differences between the 3D model and the actual scene, and obtaining model error recognition information are as follows:

[0028] S301: Based on the basic 3D model, compare the photos of the actual construction site to check the shape and position of the building's external features in the photos, including windows and doors, identify and record basic structural features from the photos, and obtain a list of extracted structural features;

[0029] S302: Based on the extracted structural feature list, the corresponding structural features in the 3D model are compared, and structures that do not match those in the real-life photo are marked, including window positions and door sizes, to obtain erroneous structure identification information;

[0030] S303: Based on the error structure identification information, record the actual value and deviation value corresponding to each error structure data, organize the data, and obtain model error identification information.

[0031] On the other hand, based on the model error identification information, the type and location of the error data are analyzed, and each error is corrected to obtain the corrected building model. Specifically, the steps are:

[0032] S401: Based on the model error identification information, each structural error is assigned to a corresponding error type, including marking the error as structural mismatch, dimensional error, and position deviation, to obtain an error analysis result;

[0033] S402: Based on the error analysis results, correct each error and adjust the parameters of the three-dimensional model, including correcting the building angle, modifying the window size, and correcting the door position. Each error parameter is adjusted to match the actual building state, and a correction parameter list is obtained.

[0034] S403: Based on the correction parameter list, verify that each error is corrected by repeated verification and comparison with the actual scene, and obtain a corrected building model.

[0035] On the other hand, based on the modified building model, the detail level is adjusted according to the parameters set by the user to optimize the computing resource consumption, and the steps of obtaining the optimized BIM model are specifically as follows:

[0036] S501: Based on the modified building model, collecting user-set parameters, including view angle and target resolution, analyzing corresponding rendering details under differentiated views, and obtaining user parameter analysis results;

[0037] S502: Based on the user parameter analysis result, adjust the level of detail of the three-dimensional model, including reducing the number of vertices of invisible and secondary parts in rendering, reducing the complexity of the model, reducing the consumption of computing resources, and obtaining level of detail adjustment information;

[0038] S503: Based on the detail level adjustment information, automatically adjust the detail level in the model, optimize the view display and the computing efficiency of the processor, optimize the running effect of the model on differentiated devices, and obtain an optimized BIM model.

[0039] In one aspect, a BIM building model generation and processing optimization system is provided, wherein the BIM building model generation and processing optimization system is configured to execute the above-mentioned BIM building model generation and processing optimization method, and the system comprises:

[0040] The building 3D structure scanning module is based on the target building to be modeled. According to the importance and structural complexity of the differentiated parts of the building, it adjusts the scanning accuracy level of the differentiated parts, changes the resolution parameters of the 3D scanning equipment, controls the 3D scanning equipment to scan the building, collects the 3D structural data of the building, and obtains basic 3D scanning data;

[0041] The 3D model construction module analyzes the 3D data points based on the basic 3D scanning data, identifies the spatial position of each data point, adjusts the 3D reconstruction parameters according to the spatial position and the predetermined model accuracy requirements, constructs a 3D model of the building, and obtains a basic 3D model;

[0042] The model error correction module compares the basic 3D model with photos of the actual construction site, extracts the structural features of the building from the photos, analyzes the differences between the 3D model and the actual scene, corrects each error, and obtains a corrected building model;

[0043] The model detail level optimization module adjusts the detail level based on the modified building model according to the parameters set by the user, including the view angle and the target resolution, optimizes the computing resource consumption, and obtains the optimized BIM model.

[0044] The beneficial effects brought about by the technical solution provided by the embodiment of the present invention include at least:

[0045] In the present invention, by dynamically adjusting the resolution parameters of the 3D scanning equipment according to the structural complexity and importance of the building, the scanning process is effectively optimized, so that the 3D scanning can be more accurately focused on the key structural parts, and the quality and relevance of data acquisition are improved. By comparing and analyzing the structural features with the on-site photos, structural errors can be discovered and corrected in time to ensure the accuracy and practicality of the model. The detail level of the model is automatically adjusted according to the parameters set by the user, which optimizes the use of computing resources, reduces unnecessary processing time and resource consumption, and makes the entire BIM model more economical and efficient. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0047] Figure 1 It is a schematic diagram of the workflow of the present invention;

[0048] Figure 2 This is a detailed flow chart of S1 of the present invention;

[0049] Figure 3 This is a detailed flow chart of S2 of the present invention;

[0050] Figure 4 This is a detailed flow chart of S3 of the present invention;

[0051] Figure 5 This is a detailed flow chart of S4 of the present invention;

[0052] Figure 6 This is a detailed flow chart of S5 of the present invention;

[0053] Figure 7 It is a system flow chart of the present invention. DETAILED DESCRIPTION

[0054] The technical solution of the present invention is described below in conjunction with the accompanying drawings.

[0055] In the embodiments of the present invention, words such as "exemplarily" and "for example" are used to indicate examples, illustrations, or explanations. Any embodiment or design described as an "exemplary" in the present invention should not be interpreted as being preferred or advantageous over other embodiments or designs. Rather, the use of the word "exemplary" is intended to present concepts in a concrete manner. Furthermore, in the embodiments of the present invention, "and / or" can mean both or either of the two.

[0056] In the embodiments of the present invention, the terms "image" and "picture" may be used interchangeably. It should be noted that, when the distinction between them is not emphasized, their intended meanings are the same. The terms "of," "corresponding," and "corresponding" may be used interchangeably. It should be noted that, when the distinction between them is not emphasized, their intended meanings are the same.

[0057] In the embodiments of the present invention, sometimes a subscript such as W1 may be written as a non-subscript such as W1. When the difference is not emphasized, the meanings to be expressed are the same.

[0058] In order to make the technical problems, technical solutions and advantages to be solved by the present invention clearer, a detailed description will be given below with reference to the accompanying drawings and specific embodiments.

[0059] See also Figure 1 The present invention provides a technical solution: a BIM building model generation and processing optimization method, comprising the following steps:

[0060] S1: Based on the target building to be modeled, adjust the scanning accuracy level of the differentiated parts according to the importance and structural complexity of the differentiated parts of the building, change the resolution parameters of the 3D scanning device, control the 3D scanning device to scan the building, collect the 3D structural data of the building, and obtain basic 3D scanning data;

[0061] S2: Based on the basic 3D scanning data, the 3D data points are analyzed to identify the spatial position of each data point. According to the spatial position and the predetermined model accuracy requirements, the 3D reconstruction parameters, including vertex density and surface smoothness, are adjusted to construct a 3D model of the building and obtain a basic 3D model.

[0062] S3: Based on the basic 3D model, the model is compared with photos of the actual construction site to extract the building's structural features, including window locations and door sizes. The differences between the 3D model and the actual scene are analyzed to identify structural errors and inconsistencies in the 3D model and obtain model error recognition information.

[0063] S4: Based on the model error identification information, the type and location of the error data are analyzed, each error is corrected, and parameters are adjusted, including building angle adjustment, window size modification, and door position correction, to match the actual building status, optimize the practicality and accuracy of the model, and obtain the corrected building model;

[0064] S5: Based on the revised building model, the level of detail is adjusted according to the user-set parameters, including view angle and target resolution. The required level of detail under the target view is analyzed, and computing resource consumption is optimized to obtain the optimized BIM model.

[0065] The basic 3D scanning data includes the spatial coordinate accuracy and scanning point density; the basic 3D model includes the 3D coordinates of building components, connection data and the reconstructed model texture quality; the model error identification information includes structural alignment errors, size deviations and material mismatch items; the corrected building model includes the building angle, window position and door frame size after error adjustment; the optimized BIM model includes the model details, rendering effects and resource usage data after view optimization.

[0066] See also Figure 2 Based on the target building to be modeled, the scanning accuracy level of the differentiated parts is adjusted according to the importance and structural complexity of the differentiated parts of the building, the resolution parameters of the 3D scanning device are changed, the 3D scanning device is controlled to scan the building, and the 3D structural data of the building is collected. The steps to obtain basic 3D scanning data are as follows:

[0067] S101: Based on the target building to be modeled, the required scanning accuracy level of the differentiated structural parts is evaluated according to the importance and structural complexity of the differentiated parts of the building, and the accuracy adjustment parameters are obtained;

[0068] The formula for evaluating the level of scanning accuracy required for differentiated structural parts is:

[0069]

[0070] Among them, J is the scanning accuracy level, R represents the structural complexity, C represents the component importance weight, I represents the intervention factor, and a J 、b J and c J is the weight coefficient, d J is the normalization coefficient.

[0071] The formula is:

[0072]

[0073] Parameter details and how to obtain them:

[0074] R: Structural complexity, which indicates the geometric complexity and construction difficulty of the building structure. It is quantified through building design documents and architects' evaluations. It is usually scored based on the number, type and complexity of the interactions of structural elements, and the range is usually set from 1 to 10.

[0075] C: Component Importance Weight, which is based on the functional importance of the building component in the overall structure. The weight can be obtained through an expert scoring system, and the score is usually between 1 and 5. Important structural elements (such as load-bearing walls) will receive higher scores.

[0076] I: Interference factor, which includes possible scan deviations caused by building materials or environmental factors. The factor is obtained through site condition investigation and material testing, and the score is usually between 0 and 1. More complex or unstable environments will result in a higher interference factor.

[0077] a J 、b J and c J : Weight coefficients, which measure the impact of each factor on the overall accuracy requirement. These coefficients are typically determined through historical data analysis and professional expertise, and their specific values ​​depend on the calibration of the model.

[0078] d J : A normalization factor used to balance the results and ensure the appropriateness of the accuracy level. The factor is usually set to the inverse of the sum of all coefficients in the regression model to ensure that the final accuracy level falls within a suitable range.

[0079] Calculation example:

[0080] The following parameter values ​​were set: R = 8 (high complexity), C = 3 (medium importance), I = 0.2 (low environmental interference), a J =5,b J =0.3, c J =0.2, (weight coefficient), d J =1.25.

[0081] Calculation precision level:

[0082]

[0083]

[0084] The result, J = 6, indicates that, based on the given project parameters and the set regression coefficient, the scanning equipment needs to be set to level 6 accuracy to meet the required accuracy of the building model. This ensures that the scan quality is consistent with the details of the actual building and is suitable for architectural projects with high complexity and low environmental impact.

[0085] S102: Based on the accuracy adjustment parameters, the resolution setting of the 3D scanning device is changed, the scanner operation mode is adjusted, and the scanning accuracy level of the differentiated structure is matched, and the building is 3D scanned to obtain original 3D scanning data.

[0086] Based on the accuracy adjustment parameters, the resolution settings of the 3D scanning device are modified, including adjusting the optical resolution and scanning speed of the scanner to adapt to different structural complexities and the required level of detail. The operating mode of the scanner is adjusted according to the specific characteristics of the building, such as switching from static scanning to dynamic scanning, or using augmented reality technology to improve the scanning effect. During the scanning process, the scanning parameters are monitored and adjusted in real time to ensure that every detail can be accurately captured, and a comprehensive 3D scan of the building is performed to obtain the original 3D scanning data.

[0087] S103: Based on the original 3D scanning data, data cleaning is performed, including noise data removal and data missing part supplementation, 3D structure data integration, and data integrity and accuracy verification to obtain basic 3D scanning data.

[0088] Based on the original 3D scan data, a noise reduction algorithm is used to remove noise data, which usually involves frequency analysis and amplitude filtering to exclude data points that do not meet the preset standards. For missing data, an interpolation algorithm or reconstruction technology based on adjacent data points is used to supplement the missing data. During the process, the data integrity and accuracy verification program is run multiple times, including comparing the initial design data with the scan results, and adjusting the data processing parameters until the final data meets the predetermined quality standards to obtain basic 3D scan data.

[0089] See also Figure 3 Based on the basic 3D scanning data, the 3D data points are analyzed and the spatial position of each data point is identified. According to the spatial position and the predetermined model accuracy requirements, the 3D reconstruction parameters, including vertex density and surface smoothness, are adjusted to construct a 3D model of the building. The specific steps to obtain the basic 3D model are as follows:

[0090] S201: Based on the basic 3D scanning data, perform spatial position analysis on the data points, and use coordinate transformation technology to map each scanning point to a corresponding position on the building model to obtain spatial positioning information of the data points;

[0091] Based on the basic 3D scanning data, the data is matched with the specific position of the building model. Using coordinate conversion technology, the scan data is imported into professional 3D modeling software. By setting the coordinate base point, the local coordinates of the scan point are converted into the global building model coordinates using the coordinate conversion formula to ensure that each data point can be accurately mapped to the building model. Iterative checking and error correction are then performed to improve the mapping accuracy and obtain the spatial positioning information of the data point.

[0092] S202: Based on the spatial positioning information of the data points and in accordance with the actual model accuracy requirements of the building, the vertex density of the model is adjusted to optimize the distribution of vertices and the performance of the surface, and the 3D reconstruction parameters are adjusted to obtain 3D reconstruction adjustment information;

[0093] The formula for adjusting the vertex density of the model is:

[0094]

[0095] Among them, V new is the vertex density of the adjusted model, K represents the target accuracy coefficient of the model, S represents the spatial coverage of the data points, L represents the local detail importance coefficient, D represents the average data point density, M is the adjustment factor of the model, P represents the expected number of vertices, and T represents the current number of vertices.

[0096] formula:

[0097]

[0098] Parameter details and how to obtain them:

[0099] K is the target accuracy factor of the model: This is a user-defined factor that defines the target accuracy level of the model. The factor is set by assessing the detail requirements of the building model and is typically set between 1 and 10.

[0100] S is the spatial coverage of the data points: This represents the distribution of the data points on the building model and is calculated as the percentage of the building model volume covered by the data points. This parameter is obtained from the data provided by the scanning device and ranges from 0 to 1.

[0101] L is the local detail importance coefficient: a coefficient that quantifies the visual or functional importance of a building part, usually rated by an architect or designer, with a value ranging from 1 to 5.

[0102] D is the average data point density: it represents the number of data points per unit volume, usually calculated based on 3D scanning data statistics.

[0103] M is the model adjustment factor: it is used to balance the distribution of vertices of the entire model and is often set based on the total volume of the building.

[0104] P and T are the expected and current number of vertices: P is the number of vertices preset according to design requirements, while T is the number of vertices in the current model. The difference between the two is used to calculate the need for vertex adjustment.

[0105] Calculation example:

[0106] The parameters are set as follows: K = 5, indicating a high accuracy requirement, S = 0.8, a high data point coverage, L = 3, where details of some structures are important, D = 250 points / m3, indicating a high data point density, M = 0.1, P = 5000, the ideal number of vertices set by the designer, and T = 3000, the number of vertices in the current model.

[0107] Calculation process:

[0108]

[0109] Calculation result V new =168, indicating the ideal model point density based on the current building model data and accuracy requirements.

[0110] S203: Based on the 3D reconstruction adjustment information, a 3D model of the building is constructed, vertex connection and facet generation are performed, and structural refinement processing is performed on building details, including window frames and door sills. Corresponding materials are assigned to differentiated structures, and the accuracy and detail richness of the model are optimized to obtain a basic 3D model.

[0111] Based on the 3D reconstruction adjustment information, 3D modeling software is used to generate connection points and facets to ensure the stability and accuracy of the constructed mesh model structure. For detailed parts of the building, such as window frames and door sills, additional structural refinement is performed, including adding additional vertices and adjusting the position of the vertices to better express the structural characteristics of the details. At the same time, materials consistent with the architectural design are selected and applied to different structural parts to optimize the accuracy and detail richness of the model, thus obtaining a basic 3D model.

[0112] See also Figure 4 Based on the basic 3D model, the model is compared with photos of the actual construction site. The structural features of the building, including window positions and door sizes, are extracted from the photos. The differences between the 3D model and the actual scene are analyzed, and structural errors and inconsistencies in the 3D model are identified. The specific steps for obtaining model error identification information are as follows:

[0113] S301: Based on the basic 3D model, compare the photos of the actual construction site to check the shape and position of the building's external features in the photos, including windows and doors, identify and record basic structural features from the photos, and obtain a list of extracted structural features;

[0114] Based on the basic three-dimensional model, according to multiple exterior photos of the building taken in actual scenes, the coordinates of the reference points marked in the architectural design drawings are read from the file, and the exterior wall contours, window frame edges, and door opening positions visible in the photos are marked one by one in the model coordinate system. By comparing the length values ​​displayed on the ruler on the photo, the horizontal and vertical pixel distances of the windows are converted into actual sizes, and the opening width of the door opening and the relative position of the door sill are recorded as corresponding values. The measured data are listed in sequence in a table file using the window number and door opening identification number as marks to obtain a list of extracted structural features.

[0115] S302: Based on the extracted structural feature list, the corresponding structural features in the 3D model are compared, and structures that do not match those in the real-life photo are marked, including window positions and door sizes, to obtain erroneous structure recognition information;

[0116] Based on the extracted structural feature list, the basic three-dimensional model file is called in the computer. According to the window numbers, door opening identification numbers and corresponding dimensions and coordinates recorded in the list, the list data is compared with the window frame nodes and door opening edges at the same position in the model. By checking the coordinate values ​​and dimension values ​​of each corresponding point in the modeling software, the measured data recorded in the list are compared one-to-one with the existing values ​​of the model. For elements with coordinate deviations or inconsistent dimension values, the degree of deviation is recorded as a specific value, and the corresponding window numbers and door opening identification numbers are marked separately in independent text to obtain error structure identification information.

[0117] S303: Based on the error structure identification information, record the actual value and deviation value corresponding to each error structure data, organize the data, and obtain model error identification information.

[0118] Based on the error structure identification information, the measured dimension values ​​and model data values ​​corresponding to each erroneous element listed therein are read separately in rows, the difference between the two is written into adjacent fields, the identification numbers of windows and door openings are marked separately in independent columns, all error entries are recorded in a fixed format in a newly created table file, and all deviation entries are rearranged and classified according to the numbering sequence and difference size to obtain model error identification information.

[0119] See also Figure 5 Based on the model error identification information, the type and location of the error data are analyzed, each error is corrected, and the parameters are adjusted, including building angle adjustment, window size modification and door position correction, to match the actual building status, optimize the practicality and accuracy of the model, and obtain the corrected building model. The specific steps are as follows:

[0120] S401: Based on the model error identification information, each structural error is assigned to a corresponding error type, including marking the error as structural mismatch, dimensional error, and position deviation, to obtain an error analysis result;

[0121] Based on the model error identification information, multiple data items listed therein are extracted. Each data item includes a component identification number, a measured length value, a design reference value, and coordinate positioning data. The measured value in each data item is compared with the corresponding design value. Data that is inconsistent with the original structural contour is marked as a morphological difference, data whose values ​​are not equal to the reference values ​​are marked as a size difference, and data whose coordinate values ​​do not match the predetermined position are marked as a position difference. After completing the classification one by one, the classified information is reorganized into an independent text file to obtain the error analysis results;

[0122] S402: Based on the error analysis results, each error is corrected and the parameters of the 3D model are adjusted, including correcting the building angle, modifying the window size, and correcting the door position. Each error parameter is adjusted to match the actual building state, and a correction parameter list is obtained;

[0123] Based on the error analysis results, read the records one by one, directly subtract the value listed in the angle difference entry from the original design angle to obtain the angle correction value, subtract the measured length listed in the size difference entry from the reference length to obtain the size correction value, subtract the measured coordinates from the design coordinates in the position difference entry to obtain the position correction value, integrate the difference values ​​and record them in a newly created parameter file, arrange similar values ​​in adjacent data columns, enter each value in the parameter list into the model editing interface in turn, enter the calculated angle correction value into the angle field of the corresponding component, enter the size correction value into the size field, and enter the position correction value into the coordinate field, correct each error, adjust the parameters of the 3D model, and generate a correction parameter list.

[0124] S403: Based on the correction parameter list, verify that each error is corrected by repeated verification and comparison with the actual scene, and obtain a corrected building model.

[0125] Based on the correction parameter list, the established 3D model is opened on the computer, and the actual construction site photo file is loaded again. The measurement values ​​of the corresponding components on the model are compared with the scale reference data in the photo. If new deviations are found, the correction parameter input steps are repeated. After all deviation items are adjusted, the corrected building model is obtained.

[0126] See also Figure 6 Based on the revised building model, the details level is adjusted according to the parameters set by the user, including the view angle and target resolution, the required details level is analyzed under the target view, and the computing resource consumption is optimized. The steps to obtain the optimized BIM model are as follows:

[0127] S501: Based on the modified building model, collect the user's set parameters, including view angle and target resolution, analyze the corresponding rendering details under the differentiated views, and obtain the user parameter analysis results;

[0128] Based on the revised building model, the user selects different view angle options in the software interface, such as front, side, and top views, sets the viewing direction and height for each view, then enters or selects a specific value for the target resolution and adjusts the resolution level using the input box or slider. The system saves the parameters to the configuration file, automatically reads the angle and resolution settings for each view, applies them to the corresponding rendering configuration one by one, checks the rendering detail requirements under each view, determines the building details and overall structure that need to be displayed based on the different view angles, records the rendering detail requirements for each view, and generates user parameter analysis results.

[0129] S502: Based on the user parameter analysis results, adjust the detail level of the three-dimensional model, including reducing the number of vertices of invisible and secondary parts in the rendering, reducing the complexity of the model, reducing the consumption of computing resources, and obtaining detail level adjustment information;

[0130] Based on the results of user parameter analysis and the level of detail required to be displayed in each view, determine which parts of the model are invisible or secondary in that view. Use modeling software to select parts that do not require high details, batch reduce the number of vertices in these parts, ensure that the main structure and details of the model maintain high precision, adjust the vertex distribution to optimize the overall performance of the model, and record the specific values ​​and positions of each adjustment. Organize all adjustment information to generate detail level adjustment information.

[0131] S503: Based on the detail level adjustment information, automatically adjust the detail level in the model, optimize the view display and the computing efficiency of the processor, optimize the running effect of the model on differentiated devices, and obtain an optimized BIM model.

[0132] Based on the detail level adjustment information, the detail level adjustment information is imported into the modeling software. According to the instructions in the adjustment information, the corresponding detail level in the model is automatically selected and modified to reduce the number of vertices in invisible and minor parts, optimize the overall complexity of the model, and ensure that the rendering details in each view meet the parameters set by the user. During the adjustment process, the changes in the model are monitored in real time, and the results of each adjustment are recorded. After completing the automatic adjustment of all detail levels, the optimized BIM model is generated.

[0133] See also Figure 7 A BIM building model generation and processing optimization system is provided. The BIM building model generation and processing optimization system is used to execute the above-mentioned BIM building model generation and processing optimization method. The system includes:

[0134] The building 3D structure scanning module is based on the target building to be modeled. According to the importance and structural complexity of the differentiated parts of the building, it adjusts the scanning accuracy level of the differentiated parts, changes the resolution parameters of the 3D scanning equipment, controls the 3D scanning equipment to scan the building, collects the 3D structural data of the building, and obtains basic 3D scanning data;

[0135] The 3D model construction module analyzes the 3D data points based on the basic 3D scanning data, identifies the spatial position of each data point, adjusts the 3D reconstruction parameters according to the spatial position and the predetermined model accuracy requirements, constructs the 3D model of the building, and obtains the basic 3D model;

[0136] The model error correction module compares the basic 3D model with photos of the actual construction site, extracts the structural features of the building from the photos, analyzes the differences between the 3D model and the actual scene, corrects each error, and obtains the corrected building model;

[0137] The model detail level optimization module is based on the revised building model and adjusts the detail level according to the parameters set by the user, including view angle and target resolution, to optimize computing resource consumption and obtain the optimized BIM model.

[0138] It should be understood that the term "and / or" as used herein simply describes a relationship between associated objects, indicating that three possible relationships exist. For example, "A and / or B" can represent: A alone, A and B together, or B alone. A and B can be singular or plural. Furthermore, the character " / " as used herein generally indicates an "or" relationship between the associated objects, but it may also indicate an "and / or" relationship. For specific understanding, please refer to the context.

[0139] In this disclosure, "at least one" means one or more, and "plurality" means two or more. "At least one of the following" or similar expressions refers to any combination of these items, including any combination of single or plural items. For example, "at least one of a, b, or c" can mean: a, b, c, ab, ac, bc, or abc, where a, b, and c can be single or plural.

[0140] It should be understood that in various embodiments of the present invention, the size of the serial numbers of the above-mentioned processes does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

[0141] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professionals and technicians can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of the present invention.

[0142] Those skilled in the art will clearly understand that, for the convenience and brevity of description, the specific working processes of the above-described equipment, devices and units can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0143] In the several embodiments provided by the present invention, it should be understood that the disclosed devices, apparatuses and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For example, the division of the units is merely a logical function division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another device, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interface, indirect coupling or communication connection of the device or unit, which can be electrical, mechanical or other forms.

[0144] The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of these units may be selected to achieve the purpose of this embodiment according to actual needs.

[0145] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0146] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for enabling a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk.

[0147] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any modifications or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in the present invention should be included in the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be based on the scope of protection of the claims.

Claims

1. A BIM building model generation and processing optimization method, characterized in that: The following steps are involved: S1: Based on the target building to be modeled, adjust the scanning accuracy level of the differentiated parts according to the importance and structural complexity of the differentiated parts of the building, change the resolution parameters of the 3D scanning device, control the 3D scanning device to scan the building, and obtain basic 3D scanning data; S2: Based on the basic 3D scanning data, analyzing the 3D data points, identifying the spatial position of each data point, adjusting the 3D reconstruction parameters, constructing a 3D model of the building, and obtaining a basic 3D model; S3: Based on the basic 3D model, compare it with photos of the actual construction site, extract the structural features of the building from the photos, analyze the differences between the 3D model and the actual scene, and obtain model error recognition information; S4: Based on the model error identification information, analyzing the type and location of the error data, correcting each error, and obtaining a corrected building model; S5: Based on the modified building model, the detail level is adjusted according to the parameters set by the user, the computing resource consumption is optimized, and an optimized BIM model is obtained; Based on the modified building model, the detail level is adjusted according to the parameters set by the user to optimize the consumption of computing resources and obtain the optimized BIM model in the following steps: S501: Based on the modified building model, collecting user-set parameters, including view angle and target resolution, analyzing corresponding rendering details under differentiated views, and obtaining user parameter analysis results; S502: Based on the user parameter analysis result, adjust the level of detail of the three-dimensional model, including reducing the number of vertices of invisible and secondary parts in rendering, reducing the complexity of the model, reducing the consumption of computing resources, and obtaining level of detail adjustment information; S503: Based on the detail level adjustment information, automatically adjust the detail level in the model, optimize the view display and the computing efficiency of the processor, optimize the running effect of the model on differentiated devices, and obtain an optimized BIM model.

2. The BIM building model generation and processing optimization method according to claim 1, characterized in that: The basic three-dimensional scanning data includes spatial coordinate accuracy and scanning point density; the basic three-dimensional model includes the three-dimensional coordinates of building components, connection data and reconstructed model texture quality; the model error identification information includes structural alignment errors, size deviations and material mismatch items; the corrected building model includes error-adjusted building angles, window positions and door frame sizes; the optimized BIM model includes model details, rendering effects and resource usage data after view optimization.

3. The BIM building model generation and processing optimization method according to claim 1, characterized in that: Based on the target building to be modeled, the scanning accuracy level of the differentiated parts is adjusted according to the importance and structural complexity of the differentiated parts of the building, the resolution parameters of the 3D scanning device are changed, and the 3D scanning device is controlled to scan the building to obtain basic 3D scanning data. The specific steps are as follows: S101: Based on the target building to be modeled, the required scanning accuracy level of the differentiated structural parts is evaluated according to the importance and structural complexity of the differentiated parts of the building, and the accuracy adjustment parameters are obtained; S102: Based on the accuracy adjustment parameters, changing the resolution setting of the three-dimensional scanning device, adjusting the scanner operation mode, matching the scanning accuracy level of the differentiated structure, performing a three-dimensional scan on the building, and obtaining original three-dimensional scanning data; S103: Based on the original three-dimensional scanning data, data cleaning is performed, including noise data removal and data missing part supplementation, three-dimensional structure data integration, and data integrity and accuracy verification to obtain basic three-dimensional scanning data.

4. The BIM building model generation and processing optimization method according to claim 3, characterized in that: The formula for evaluating the level of scanning accuracy required for differential structural parts is: Among them, J is the scanning accuracy level, R represents the structural complexity, C represents the component importance weight, I represents the intervention factor, and a J 、b J and c J is the weight coefficient, d J is the normalization coefficient.

5. The BIM building model generation and processing optimization method according to claim 1, characterized in that: Based on the basic 3D scanning data, the 3D data points are analyzed, the spatial position of each data point is identified, the 3D reconstruction parameters are adjusted, and a 3D model of the building is constructed. The steps for obtaining the basic 3D model are as follows: S201: Based on the basic three-dimensional scanning data, perform spatial position analysis on the data points, and use coordinate transformation technology to map each scanning point to a corresponding position on the building model to obtain spatial positioning information of the data points; S202: Based on the spatial positioning information of the data points and in accordance with the actual model accuracy requirements of the building, adjusting the vertex density of the model, optimizing the distribution of vertices and the performance of the curved surface, and adjusting the 3D reconstruction parameters to obtain 3D reconstruction adjustment information; S203: Based on the 3D reconstruction adjustment information, a 3D model of the building is constructed, vertex connection and facet generation are performed, and structural refinement processing is performed on building details, including window frames and door sills. Corresponding materials are assigned to differentiated structures, and the accuracy and detail richness of the model are optimized to obtain a basic 3D model.

6. The BIM building model generation and processing optimization method according to claim 5, characterized in that: The formula for adjusting the vertex density of the model is: Among them, V new is the vertex density of the adjusted model, K represents the target accuracy coefficient of the model, S represents the spatial coverage of the data points, L represents the local detail importance coefficient, D represents the average data point density, M is the adjustment factor of the model, P represents the expected number of vertices, and T represents the current number of vertices.

7. The BIM building model generation and processing optimization method according to claim 1, characterized in that: The steps of comparing the basic 3D model with photos of the actual construction site, extracting the structural features of the building from the photos, analyzing the differences between the 3D model and the actual scene, and obtaining model error recognition information are as follows: S301: Based on the basic 3D model, compare the photos of the actual construction site to check the shape and position of the building's external features in the photos, including windows and doors, identify and record basic structural features from the photos, and obtain a list of extracted structural features; S302: Based on the extracted structural feature list, the corresponding structural features in the 3D model are compared, and structures that do not match those in the real-life photo are marked, including window positions and door sizes, to obtain erroneous structure identification information; S303: Based on the error structure identification information, record the actual value and deviation value corresponding to each error structure data, organize the data, and obtain model error identification information.

8. The BIM building model generation and processing optimization method according to claim 1, characterized in that: Based on the model error identification information, the type and location of the error data are analyzed, and each error is corrected to obtain a corrected building model. Specifically, the steps are: S401: Based on the model error identification information, each structural error is assigned to a corresponding error type, including marking the error as structural mismatch, dimensional error, and position deviation, to obtain an error analysis result; S402: Based on the error analysis results, correct each error and adjust the parameters of the three-dimensional model, including correcting the building angle, modifying the window size, and correcting the door position. Each error parameter is adjusted to match the actual building state, and a correction parameter list is obtained. S403: Based on the correction parameter list, verify that each error is corrected by repeated verification and comparison with the actual scene, and obtain a corrected building model.

9. A BIM building model generation and processing optimization system, characterized in that: The BIM building model generation and processing optimization method according to any one of claims 1 to 8, wherein the system comprises: The building 3D structure scanning module is based on the target building to be modeled. According to the importance and structural complexity of the differentiated parts of the building, it adjusts the scanning accuracy level of the differentiated parts, changes the resolution parameters of the 3D scanning equipment, controls the 3D scanning equipment to scan the building, collects the 3D structural data of the building, and obtains basic 3D scanning data; The 3D model construction module analyzes the 3D data points based on the basic 3D scanning data, identifies the spatial position of each data point, adjusts the 3D reconstruction parameters according to the spatial position and the predetermined model accuracy requirements, constructs a 3D model of the building, and obtains a basic 3D model; The model error correction module compares the basic 3D model with photos of the actual construction site, extracts the structural features of the building from the photos, analyzes the differences between the 3D model and the actual scene, corrects each error, and obtains a corrected building model; The model detail level optimization module adjusts the detail level based on the modified building model according to the parameters set by the user, including the view angle and the target resolution, optimizes the computing resource consumption, and obtains the optimized BIM model.

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