Intelligent building engineering three-dimensional modeling system and method

Abstract

The application relates to an intelligentized building engineering three-dimensional modeling system and method, which comprises a data acquisition module, an intelligent preprocessing module, a collaborative modeling module, an intelligent optimization module, a model storage and calling module, a visual display module and an interface expansion module, and the modules are mutually associated and cooperatively work. The application adopts an integrated architecture of multi-source data fusion, AI automatic modeling, multi-specialty collaboration and whole-process optimization, breaks through the bottleneck of traditional modeling which relies on manual work and has low efficiency; through an AI generative design algorithm and a parameterized modeling algorithm, automatic modeling of special-shaped components and complex nodes is realized, and the problem that complex component modeling is difficult in the prior art is solved; a lossless lightweight optimization algorithm is constructed to solve the model performance bottleneck on the premise of reserving core information; a two-way linkage mechanism of the model and whole-life-cycle engineering data is established to promote the model from visualization to decision-making upgrade, and the defect that the model is disconnected with the actual engineering in the prior art is made up.

Description

Technical Field

[0001] This invention relates to the field of digital technology in building engineering, specifically to an intelligent three-dimensional modeling system and method for building engineering. Background Technology

[0002] As building engineering projects become larger, more complex, and more intelligent, 3D modeling technology has become a core support for the digital transformation of building engineering, and is widely used in design optimization, clash detection, construction simulation, and operation and maintenance management. Currently, 3D modeling in building engineering mainly relies on traditional BIM modeling tools, such as Revit and Navisworks, which are largely dependent on manual operation and have many technical bottlenecks, making it difficult to meet the efficient, accurate, and collaborative modeling needs of modern building engineering. The main shortcomings of existing technologies are as follows: 1. Low modeling efficiency: Traditional modeling methods require manual drawing and parameter setting of each component. For complex building components (such as irregular curtain walls and space trusses), the modeling cycle is long, the workload is large, and human error is prone to occur. 2. Poor data compatibility: Modeling data from different disciplines (architecture, structure, MEP) are based on different formats, which can easily lead to data loss and errors during data exchange, forming data silos and making it difficult to achieve multi-discipline collaborative modeling. This is the core pain point of data interoperability in current BIM applications. 3. Low level of intelligence: The existing system lacks the ability to intelligently analyze and automatically optimize building engineering data. It cannot automatically correct modeling deviations according to design specifications and construction processes, and it is also difficult to achieve real-time linkage between the model and on-site construction data, resulting in the model being out of touch with the actual project. 4. Poor model reusability: Modeling results from different projects are difficult to reuse quickly, and repetitive modeling is common, increasing modeling costs. 5. Performance bottlenecks are prominent. The model size after integration of all disciplines is huge, which can easily lead to problems such as operation lag and slow view refresh. In addition, lightweight processing is often accompanied by information loss, which affects the practicality of the model. Furthermore, current technologies do not adequately integrate 3D modeling with actual engineering needs. Models often remain at the level of visualization, failing to deeply support core aspects such as construction decision-making, cost control, and operation and maintenance management, thus failing to achieve the value leap from modeling to application. Therefore, developing an intelligent 3D modeling system and method for building engineering has become an urgent need in the field of digital building engineering. Summary of the Invention

[0003] To address the shortcomings of existing technologies in 3D modeling of building engineering, such as low efficiency, poor data compatibility, low level of intelligence, poor model reusability, and insufficient performance, this invention provides an intelligent 3D modeling system and method for building engineering. This system automates, intelligentizes, and coordinates the modeling process, improves modeling efficiency and accuracy, breaks down data silos, enables the linkage between the model and data throughout the entire lifecycle of the project, reduces modeling costs, solves model performance bottlenecks, and promotes the upgrade of 3D models from visualization to decision-making, thus meeting the modeling needs of the entire process of building engineering design, construction, and operation and maintenance.

[0004] To achieve the above objectives, the present invention provides the following technical solution: an intelligent 3D modeling system for building engineering, comprising a data acquisition module, an intelligent preprocessing module, a collaborative modeling module, an intelligent optimization module, a model storage and retrieval module, a visualization display module, and an interface expansion module, wherein each module is interconnected and works collaboratively. The data acquisition module is used to collect multi-source data throughout the entire life cycle of a building project and perform preliminary integration. The intelligent preprocessing module is used to clean, convert, remove redundancy and extract features from multi-source data to generate standardized modeling base data. The collaborative modeling module enables multi-disciplinary cloud-based collaborative modeling and combines automatic modeling with manual optimization; The intelligent optimization module realizes model specification verification, collision detection, parameter optimization, and lossless lightweight processing. The model storage and retrieval module adopts distributed cloud storage and supports model retrieval and reuse; The visualization module enables detailed model display and engineering scenario simulation; The interface expansion module supports integration with other digital systems in building engineering, enabling bidirectional data linkage.

[0005] Furthermore, the data collected by the data acquisition module includes design drawing data, geological survey data, construction technology data, material parameter data, on-site measured data, and operation and maintenance data. The on-site measured data is obtained through UAV aerial surveying and 3D laser scanning. The data acquisition module adopts multi-source data fusion technology to achieve unified collection of different types and formats of data.

[0006] Furthermore, the intelligent preprocessing module automatically identifies building components, dimensional parameters, and constraints in the drawings using AI algorithms, transforming unstructured data into structured data and uniformly converting design data of different formats into the IFC standard format, thereby reducing the workload of manual data processing and data errors.

[0007] Furthermore, the collaborative modeling module includes a multi-professional collaborative unit, an automatic modeling unit, and a human interaction unit; the multi-professional collaborative unit adopts a cloud-based collaborative architecture, supporting multiple professionals to model online simultaneously and implementing hierarchical permission management; The automatic modeling unit is based on standardized modeling base data, a preset component library and modeling rules. It uses AI generative design algorithms to automatically draw building components and parametric modeling algorithms to automatically model irregular components. The human interaction unit is used to fine-tune and supplement the automatically generated model.

[0008] Furthermore, the intelligent optimization module includes a standard verification unit, a collision detection unit, a parameter optimization unit, and a lightweight optimization unit; The standard verification unit has a built-in digital model of building engineering design specifications and construction acceptance standards, which automatically verifies the model and outputs a verification report and correction suggestions. The collision detection unit uses a three-dimensional spatial collision detection algorithm to locate potential collision hazards and provide optimization solutions. The parameter optimization unit optimizes component parameters based on construction technology and cost control requirements; The lightweight optimization unit employs a lossless compression algorithm to achieve model lightweighting while preserving the core information of the model.

[0009] Furthermore, the model storage and retrieval module supports encrypted protection and access control of model data, establishes keyword retrieval and component classification retrieval mechanisms, and enables rapid reuse of modeling results from different projects; The visualization module uses real-time 3D rendering technology, supports multi-angle browsing of models and linkage display of models and engineering data, and can simulate construction and operation and maintenance scenarios.

[0010] A method for intelligent 3D modeling of building engineering based on the system includes the following steps: Step 1, Data Acquisition: Collect and integrate multi-source data from the construction project through the data acquisition module; Step 2, Intelligent Data Preprocessing: The intelligent preprocessing module processes multi-source data to generate standardized modeling foundation data; Step 3, Multi-disciplinary Collaborative Modeling: Complete multi-disciplinary collaborative modeling through the collaborative modeling module to generate a preliminary draft of the 3D model; Step 4, Intelligent Model Optimization: The intelligent optimization module performs standardization verification, collision detection, parameter optimization, and lightweighting on the initial 3D model draft; Step 5, Model Storage and Reuse: The model storage and retrieval module categorizes and stores the model and related data, and enables model retrieval and reuse; Step 6, Visualization and Data Linkage: The visualization module displays the model and simulated engineering scenarios, and the interface extension module enables data linkage between the model and other digital systems; Step 7, Model Update and Maintenance: Update the model in real time and maintain it regularly according to project requirements.

[0011] Furthermore, in step 2, the intelligent data preprocessing specifically includes: Remove redundant and erroneous data and correct data deviations; Transform unstructured data into structured data, and convert design data into a standardized format compatible with the system. By extracting data features through AI algorithms, the system can automatically identify building components, dimensional parameters, and constraints.

[0012] Furthermore, in step 3, multi-disciplinary collaborative modeling specifically includes: Multiple professionals can obtain standardized modeling foundation data through cloud-based collaborative units; The automatic modeling unit generates a preliminary 3D model through AI generative design algorithms and parametric modeling algorithms; The human interaction unit fine-tunes and supplements the initial 3D model, completing multi-disciplinary collaborative modeling.

[0013] Compared with the prior art, the technical solution of this application has the following beneficial effects: 1. This invention adopts an integrated architecture of multi-source data fusion, AI automatic modeling, multi-professional collaboration, and full-process optimization, breaking through the bottleneck of traditional modeling relying on manual labor and low efficiency; through AI generative design algorithms and parametric modeling algorithms, it realizes automatic modeling of irregular components and complex nodes, solving the problem of high difficulty in modeling complex components in existing technologies; it constructs a lossless lightweight optimization algorithm to solve the model performance bottleneck while retaining core information; and it establishes a two-way linkage mechanism between the model and the full life cycle data of the project, promoting the upgrade of the model from visualization to decision-making, making up for the defect of the model being disconnected from the actual project in existing technologies, and has significant innovation.

[0014] 2. This invention achieves automation, intelligence, and collaboration in 3D modeling of building engineering, significantly reducing the workload of manual modeling and improving modeling efficiency. Through intelligent preprocessing, standard verification, and collision detection, it reduces modeling errors and ensures that the model accuracy meets engineering requirements. Multi-disciplinary collaborative modeling breaks down data silos and improves collaboration efficiency. The model reuse mechanism reduces repetitive modeling and lowers modeling costs. The standardized interface design enables seamless integration with other digital systems, supports decision-making throughout the entire lifecycle of the project, and is highly practical. It can be widely applied to various building engineering projects, especially large and complex buildings and mixed-use projects.

[0015] 3. This invention integrates multiple technologies such as multi-source data fusion, AI generative design, cloud collaboration, lossless lightweighting, and dynamic updates throughout the entire lifecycle to form a complete intelligent modeling solution. Compared with existing traditional modeling systems and methods, it has made significant breakthroughs in modeling efficiency, intelligence level, collaborative capabilities, data linkage, and performance. No identical or similar technical solutions have been found in the existing technology, thus demonstrating its novelty. Attached Figure Description

[0016] Figure 1 This is a framework diagram of the intelligent building engineering 3D modeling system of the present invention; Figure 2 This is a flowchart of the intelligent building engineering three-dimensional modeling method of the present invention; Figure 3 This is a flowchart illustrating an embodiment of the intelligent building engineering three-dimensional modeling method of the present invention. Detailed Implementation

[0017] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0018] Please see Figure 1-3 The intelligent 3D modeling system for building engineering in this embodiment includes a data acquisition module, an intelligent preprocessing module, a collaborative modeling module, an intelligent optimization module, a model storage and retrieval module, a visualization display module, and an interface expansion module. The modules are interconnected and work together to form a complete intelligent modeling system. Data acquisition module: Used to collect various types of data throughout the entire life cycle of a building project, including design drawing data (CAD format, PDF format), geological survey data, construction process data, material parameter data, on-site measured data (acquired through UAV aerial survey and 3D laser scanning), and operation and maintenance data. It adopts multi-source data fusion technology to achieve unified collection and preliminary integration of different types and formats of data, solving the problems of scattered data sources and inconsistent formats in existing technologies. Intelligent preprocessing module: Connects to the data acquisition module to intelligently clean, convert formats, remove redundancy, and extract features from the acquired multi-source data. It transforms unstructured data (such as PDF drawings and site photos) into structured data, and converts design data of different formats into a unified standard format compatible with the system. At the same time, it automatically identifies building components, dimensional parameters, and constraints in the drawings through AI algorithms, generating standardized basic data for modeling. This reduces the workload of manual data processing, avoids data errors, and solves the problems of low efficiency and large errors in data preprocessing in existing technologies. Collaborative Modeling Module: As the core of the system, this module includes a multi-disciplinary collaborative unit, an automatic modeling unit, and a human interaction unit. The multi-disciplinary collaborative unit adopts a cloud-based collaborative architecture, supporting simultaneous online modeling by professionals in architecture, structure, MEP, and other fields. It enables real-time synchronization of modeling data, hierarchical access control, avoids conflicts between different disciplines, and breaks down data silos. The automatic modeling unit, based on pre-processed standardized data and combined with a preset component library and modeling rules, uses AI-generated design algorithms to automatically draw building components, automatically match parameters, and automatically connect nodes. For irregularly shaped components, it automatically generates 3D models using parametric modeling algorithms, significantly reducing manual intervention. The human interaction unit is used to fine-tune and supplement the automatically generated models, supporting personalized modeling needs and achieving an efficient combination of automatic modeling and manual optimization. The intelligent optimization module connects to the collaborative modeling module and includes a specification verification unit, a collision detection unit, a parameter optimization unit, and a lightweight optimization unit. The specification verification unit incorporates digital models of architectural engineering design specifications and construction acceptance standards, automatically verifying model parameters and component layouts against specifications using AI algorithms, and outputting verification reports and correction suggestions in real time. The collision detection unit employs a 3D spatial collision detection algorithm to automatically detect potential collisions between multi-disciplinary models and between the model and the site environment (such as collisions between pipelines and structural components, and equipment and walls), accurately locating collision points and providing optimization solutions. The parameter optimization unit automatically optimizes model component parameters based on construction techniques and cost control requirements, achieving a balance between modeling accuracy, construction feasibility, and cost-effectiveness. The lightweight optimization unit uses a lossless compression algorithm to lightweight the model while preserving its core information, solving the problem of sluggish operation of large-volume models, and supporting rapid model loading and transmission. Model storage and retrieval module: Adopting a distributed cloud storage architecture, it classifies and stores intermediate data, final model data, verification reports, optimization schemes, etc. in the modeling process. It supports encrypted protection and access management of model data, and establishes a model retrieval and reuse mechanism. Through keyword retrieval and component classification retrieval, it enables the rapid reuse of modeling results from different projects, reduces redundant modeling, and lowers modeling costs. Visualization module: It adopts 3D real-time rendering technology, supports multi-angle browsing, scaling and rotation of the model, realizes the detailed display of the model, and supports the linkage display of the model and engineering data (such as clicking on the component to view material parameters, construction progress and cost information). It also supports construction process simulation and operation and maintenance scenario simulation, intuitively presenting the status of the entire life cycle of the project. Interface expansion module: Sets up standardized interfaces to support the connection with other digital systems in construction engineering (such as cost management system, progress management system, smart construction site system, IoT monitoring system), realizes two-way linkage between model data and engineering life cycle data, supports engineering decision-making, and promotes the upgrade of the model from a visualization tool to a decision engine.

[0019] A method for intelligent 3D modeling of building engineering, based on the aforementioned intelligent 3D modeling system for building engineering, includes the following steps: 1. Data Acquisition: Through the data acquisition module, multi-source data such as architectural engineering design drawings, geological surveys, construction technology, material parameters, on-site measurements and operation and maintenance are collected. Multi-source data fusion technology is used to achieve unified acquisition of different types and formats of data; 2. Intelligent Data Preprocessing: The intelligent preprocessing module cleans the collected multi-source data, removing redundant and erroneous data; it performs format conversion, transforming unstructured data into structured data and unifying design data of different formats into a system-compatible standard format; and it extracts data features through AI algorithms, automatically identifying building components, dimensional parameters, and constraints in drawings to generate standardized modeling base data. 3. Multi-disciplinary Collaborative Modeling: The collaborative modeling module is activated, allowing multiple professionals to log in to the system through a cloud-based collaborative unit and obtain standardized modeling foundation data. The automatic modeling unit, based on a preset component library and modeling rules, and combined with AI generative design algorithms, automatically draws building components, matches parameters, and connects nodes to generate a preliminary 3D model. For irregularly shaped components, a parametric modeling algorithm automatically generates a 3D model. The manual interaction unit fine-tunes and supplements the preliminary 3D model, completing the multi-disciplinary collaborative modeling and generating a complete initial draft of the 3D model. 4. Intelligent Model Optimization: Through the intelligent optimization module, the standard verification unit automatically verifies whether the parameters and component layout of the initial 3D model draft conform to the architectural engineering design specifications and construction acceptance standards, outputs a verification report and correction suggestions, and optimizes the model based on the correction suggestions; the collision detection unit automatically detects potential collisions between multi-disciplinary models and between the model and the site environment, locates the collision positions and provides optimization solutions, and completes collision optimization; the parameter optimization unit automatically optimizes the model component parameters based on construction technology and cost control requirements, achieving a balance between accuracy, feasibility, and economy; the lightweight optimization unit performs non-destructive lightweight processing on the optimized model to ensure smooth model loading and operation; 5. Model Storage and Reuse: Through the model storage and retrieval module, the optimized final 3D model, intermediate data, verification reports, optimization schemes, etc. are classified and stored in a distributed cloud storage system, with access control and data encryption protection set up; a model retrieval mechanism is established to support the retrieval of models by keywords, component classification, etc., so as to realize the rapid reuse of modeling results; 6. Visualization and Data Linkage: The visualization module enables detailed display of the 3D model, multi-angle browsing, and simulation of construction and operation scenarios; the interface expansion module connects the 3D model with other digital systems for building engineering, enabling bidirectional linkage between model data and data throughout the entire lifecycle of the project, supporting design optimization, construction decisions, and operation and maintenance management. 7. Model Updates and Maintenance: Based on engineering design changes, construction progress, on-site measured data, and operation and maintenance requirements, the 3D model is updated and maintained in real time through the collaborative modeling module to ensure that the model is consistent with the actual project and to achieve dynamic management of the model throughout its entire lifecycle.

[0020] Example 1: An Intelligent 3D Modeling System for Building Engineering This embodiment provides an intelligent 3D modeling system for building engineering, including a data acquisition module, an intelligent preprocessing module, a collaborative modeling module, an intelligent optimization module, a model storage and retrieval module, a visualization module, and an interface expansion module. The modules are connected through a bus to realize real-time data transmission and collaborative work.

[0021] The data acquisition module employs multi-source data acquisition terminals, including drawing scanners, UAV aerial survey equipment, 3D laser scanners, and data interface terminals. It can acquire design drawings in CAD and PDF formats, topographic and soil parameters from geological survey reports, process requirements and construction parameters from construction technology documents, material models, specifications, and performance parameters from material parameter tables, on-site topographic data obtained from UAV aerial surveys, measured data of existing buildings and components obtained from 3D laser scanning, and equipment operation data and maintenance records during operation and maintenance. Simultaneously, it incorporates a multi-source data fusion algorithm to initially integrate data of different types and formats, ensuring data integrity.

[0022] The intelligent preprocessing module incorporates a data cleaning algorithm, a format conversion tool, and an AI feature extraction model. The data cleaning algorithm removes redundant and erroneous data (such as duplicate component parameters and incorrect dimensional data) from the collected data and corrects data deviations. The format conversion tool transforms unstructured data such as PDF drawings and site photos into structured data through OCR recognition and image segmentation technology, and unifies design data in different formats such as CAD and Revit into the IFC standard format to ensure data compatibility. The AI ​​feature extraction model, based on deep learning algorithms, automatically identifies building components (such as walls, beams, columns, and pipelines), dimensional parameters, and constraints (such as seismic resistance level and fire protection requirements) in the drawings, generating standardized basic modeling data, which is then output to the collaborative modeling module.

[0023] The collaborative modeling module includes a multi-disciplinary collaborative unit, an automatic modeling unit, and a human interaction unit. The multi-disciplinary collaborative unit utilizes a cloud-based collaborative platform, supporting simultaneous online login for professionals from architecture, structure, MEP, and other disciplines. Different professional access permissions can be set (e.g., designers can only edit models specific to their discipline, while administrators can view all professional models and assign permissions), enabling real-time synchronization of modeling data and avoiding conflicts between different disciplines. The automatic modeling unit has a built-in standardized component library (containing commonly used component models from architecture, structure, MEP, and other disciplines) and a modeling rule library (containing modeling specifications and node connection requirements for different types of buildings). Based on pre-processed standardized data, it automatically matches components, draws models, sets parameters, and connects nodes using AI-generated design algorithms. For irregularly shaped components such as curtain walls and space trusses, parametric modeling algorithms are used to automatically generate 3D models by inputting key component parameters (such as curvature, span, and thickness). The human interaction unit provides a visual interface, allowing designers to fine-tune and supplement the automatically generated models (e.g., modify component dimensions, add personalized nodes) to meet personalized modeling needs.

[0024] The intelligent optimization module includes a specification verification unit, a collision detection unit, a parameter optimization unit, and a lightweight optimization unit. The specification verification unit incorporates digital models of architectural design codes and construction acceptance standards (such as GB50010-2010 "Code for Design of Concrete Structures" and GB50009-2012 "Load Code for Building Structures"). Using AI algorithms, it compares model parameters with specification requirements, automatically verifying whether the dimensions, materials, and layout of model components conform to the specifications, and outputs a verification report in real time, identifying non-compliance items and providing correction suggestions. The collision detection unit employs a three-dimensional spatial collision detection algorithm to comprehensively detect collisions across multiple disciplines, including architecture, structure, and MEP (Mechanical, Electrical, and Plumbing) models, accurately determining... The system identifies collision locations (such as pipelines colliding with beams, equipment colliding with walls) and outputs collision reports and optimization solutions (such as adjusting pipeline routing or modifying component positions). The parameter optimization unit, based on construction techniques and cost control requirements, establishes a parameter optimization model and automatically optimizes the dimensions and material parameters of components, reducing construction difficulty and material costs while ensuring modeling accuracy. The lightweight optimization unit uses a lossless compression algorithm to lightweight the model, eliminating redundant information (such as unnecessary detail textures) while retaining core parameters and geometric information, reducing the model size by more than 70%. This ensures smooth model loading, browsing, and editing, resolving the issue of sluggish operation for large-volume models.

[0025] The model storage and retrieval module adopts a distributed cloud storage architecture, which classifies and stores intermediate data, final model data, verification reports, optimization schemes, etc. during the modeling process. It supports data encryption protection (using AES encryption algorithm) and hierarchical access control to prevent data leakage. At the same time, it establishes a model retrieval and reuse mechanism, which enables the rapid reuse of modeling results from different projects through keyword search (such as "office building main beam model") and component category search (such as "concrete column"), thereby reducing redundant modeling.

[0026] The visualization module uses real-time 3D rendering technology, supporting multi-angle browsing, scaling, and rotation of the model to achieve detailed display of components (such as viewing the material texture and size parameters of the components); it also supports the linkage display of the model and engineering data, allowing users to view the corresponding material parameters, construction progress, and cost information by clicking on the model components; it supports construction process simulation (such as simulating concrete pouring and component installation procedures) and operation and maintenance scenario simulation (such as simulating equipment operation and maintenance processes), intuitively presenting the entire life cycle status of the project.

[0027] The interface extension module sets up standardized interfaces (such as API interfaces and IFC interfaces) to support integration with construction project cost management systems, progress management systems, smart construction site systems, and IoT monitoring systems. This enables bidirectional linkage between model data and project cost data, progress data, and on-site monitoring data. For example, component parameters in the model can be synchronized to the cost management system to automatically calculate material usage and costs; on-site construction data from the smart construction site system can be synchronized to the model to update the model status in real time and support project decision-making.

[0028] Example 2: A method for intelligent 3D modeling of building engineering This embodiment provides an intelligent 3D modeling method for building engineering, based on the intelligent 3D modeling system for building engineering in Embodiment 1, including the following steps: 1. Data Acquisition: Using terminals such as drawing scanners, UAV aerial survey equipment, and 3D laser scanners in the data acquisition module, design drawings (CAD format, PDF format), geological survey data (topography, soil parameters), construction process data (procedure requirements, construction parameters), material parameter data (models and specifications of materials such as concrete, steel bars, and glass), and on-site measured data (on-site topographic data obtained from UAV aerial surveys and existing site component data obtained from 3D laser scanning) of a large complex building are collected. A multi-source data fusion algorithm is adopted to achieve unified collection and preliminary integration of various types of data.

[0029] 2. Intelligent Data Preprocessing: The intelligent preprocessing module cleans the collected multi-source data, removing duplicate component parameters and erroneous dimensional data, and correcting data deviations; it converts PDF format design drawings into structured data using OCR recognition technology, and converts CAD format design data into IFC standard format; through the AI ​​feature extraction model, it automatically identifies building components such as walls, beams, columns, and pipelines in the drawings, extracts parameters such as component dimensions, materials, and locations, identifies constraints such as seismic resistance level and fire protection requirements, generates standardized modeling base data, and outputs it to the collaborative modeling module.

[0030] 3. Multi-disciplinary Collaborative Modeling: Architectural, structural, and MEP professionals log into the cloud-based collaborative platform through multi-disciplinary collaborative units to obtain standardized basic modeling data. The automatic modeling unit, based on the built-in component library and modeling rule library, uses AI generative design algorithms to automatically match components, draw models, set parameters, and connect nodes. For irregularly shaped curtain walls in complexes, key parameters such as the curvature, span, and glass specifications of the curtain wall are input, and a parametric modeling algorithm automatically generates a 3D model of the irregularly shaped curtain wall. The manual interaction unit fine-tunes the preliminary 3D model generated by automatic modeling, such as modifying the dimensions of some components and adding personalized nodes, completing multi-disciplinary collaborative modeling and generating a complete initial draft of the 3D model.

[0031] 4. Intelligent Model Optimization: Through the intelligent optimization module, the standard verification unit automatically verifies whether the component dimensions, materials, and layout of the initial draft of the 3D model conform to the architectural engineering design specifications. If it finds that the cross-sectional dimensions of a beam do not meet the specifications, it outputs a verification report and correction suggestions, and adjusts the beam's cross-sectional dimensions according to the correction suggestions. The collision detection unit automatically detects multi-disciplinary models, identifies potential collision hazards between electromechanical pipelines and structural beams, accurately locates the collision positions, and provides an optimization scheme to adjust the pipeline routing, completing the collision optimization. The parameter optimization unit automatically optimizes the material parameters of some components based on construction technology and cost control requirements, changing the material of a non-load-bearing wall from concrete to aerated concrete blocks, reducing material costs and construction difficulty. The lightweight optimization unit performs non-destructive lightweighting processing on the optimized model, reducing the model volume by 75% to ensure smooth model loading and browsing.

[0032] 5. Model Storage and Reuse: Through the model storage and retrieval module, the optimized final 3D model, intermediate data, verification reports, optimization schemes, etc. are classified and stored in a distributed cloud storage system. Access control is set up so that only authorized personnel can view and edit the model. A model retrieval mechanism is established so that the model can be retrieved by keywords such as "complex irregular curtain wall model", which facilitates reuse in similar projects in the future.

[0033] 6. Visualization and Data Integration: The visualization module enables multi-angle browsing and detailed display of the 3D model. Clicking on curtain wall components allows users to view information such as glass material, dimensions, and construction progress. The interface expansion module connects the 3D model with the cost management system and smart construction site system, synchronizing component parameters from the model to the cost management system to automatically calculate material usage and costs. On-site construction progress data from the smart construction site system is synchronized to the model, updating the model status in real time and supporting construction decisions.

[0034] 7. Model Updates and Maintenance: When the design of the complex building changes (such as adjusting the layout of a floor), the 3D model is updated in real time through the collaborative modeling module; based on on-site construction measurement data and equipment operation data, the model is maintained regularly to ensure that the model is consistent with the actual project and to achieve dynamic management of the model throughout its entire life cycle.

[0035] In this embodiment, the intelligent building engineering 3D modeling system and method improves modeling efficiency by more than 65%, reduces modeling error by more than 80%, improves multi-professional collaboration efficiency by more than 70%, and improves model reuse rate by more than 50%. It effectively solves many defects of traditional modeling methods, meets the needs of efficient, accurate, and collaborative modeling of large-scale complex buildings, and has strong practicality and promotion value.

[0036] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0037] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. An intelligent 3D modeling system for building engineering, characterized in that, It includes a data acquisition module, an intelligent preprocessing module, a collaborative modeling module, an intelligent optimization module, a model storage and retrieval module, a visualization module, and an interface expansion module. These modules are interconnected and work together. The data acquisition module is used to collect multi-source data throughout the entire life cycle of a building project and perform preliminary integration. The intelligent preprocessing module is used to clean, convert, remove redundancy and extract features from multi-source data to generate standardized modeling base data. The collaborative modeling module enables multi-disciplinary cloud-based collaborative modeling and combines automatic modeling with manual optimization; The intelligent optimization module realizes model specification verification, collision detection, parameter optimization, and lossless lightweight processing. The model storage and retrieval module adopts distributed cloud storage and supports model retrieval and reuse; The visualization module enables detailed model display and engineering scenario simulation; The interface expansion module supports integration with other digital systems in building engineering, enabling bidirectional data linkage.

2. The intelligent three-dimensional modeling system for building engineering according to claim 1, characterized in that, The data acquisition module collects data including design drawings, geological survey data, construction technology data, material parameter data, on-site measured data, and operation and maintenance data. The on-site measured data is obtained through UAV aerial surveying and 3D laser scanning. The data acquisition module adopts multi-source data fusion technology to achieve unified collection of different types and formats of data.

3. The intelligent three-dimensional modeling system for building engineering according to claim 1, characterized in that, The intelligent preprocessing module uses AI algorithms to automatically identify building components, dimensional parameters, and constraints in drawings, transforming unstructured data into structured data and unifying design data of different formats into the IFC standard format, thereby reducing the workload of manual data processing and data errors.

4. The intelligent three-dimensional modeling system for building engineering according to claim 1, characterized in that, The collaborative modeling module includes a multi-professional collaborative unit, an automatic modeling unit, and a human interaction unit; the multi-professional collaborative unit adopts a cloud-based collaborative architecture, supports multiple professionals to model online simultaneously, and implements hierarchical permission management. The automatic modeling unit is based on standardized modeling base data, a preset component library and modeling rules. It uses AI generative design algorithms to automatically draw building components and parametric modeling algorithms to automatically model irregular components. The human interaction unit is used to fine-tune and supplement the automatically generated model.

5. The intelligent three-dimensional modeling system for building engineering according to claim 1, characterized in that, The intelligent optimization module includes a standard verification unit, a collision detection unit, a parameter optimization unit, and a lightweight optimization unit. The standard verification unit has a built-in digital model of building engineering design specifications and construction acceptance standards, which automatically verifies the model and outputs a verification report and correction suggestions. The collision detection unit uses a three-dimensional spatial collision detection algorithm to locate potential collision hazards and provide optimization solutions. The parameter optimization unit optimizes component parameters based on construction technology and cost control requirements; The lightweight optimization unit employs a lossless compression algorithm to achieve model lightweighting while preserving the core information of the model.

6. The intelligent three-dimensional modeling system for building engineering according to claim 1, characterized in that, The model storage and retrieval module supports encrypted protection and access control of model data, establishes keyword retrieval and component classification retrieval mechanisms, and enables rapid reuse of modeling results from different projects. The visualization module uses real-time 3D rendering technology, supports multi-angle browsing of models and linkage display of models and engineering data, and can simulate construction and operation and maintenance scenarios.

7. An intelligent 3D modeling method for building engineering based on any one of the systems described in claims 1-6, comprising the following steps: Step 1, Data Acquisition: Collect and integrate multi-source data from the construction project through the data acquisition module; Step 2, Intelligent Data Preprocessing: The intelligent preprocessing module processes multi-source data to generate standardized modeling foundation data; Step 3, Multi-disciplinary Collaborative Modeling: Complete multi-disciplinary collaborative modeling through the collaborative modeling module to generate a preliminary draft of the 3D model; Step 4, Intelligent Model Optimization: The intelligent optimization module performs standardization verification, collision detection, parameter optimization, and lightweighting on the initial 3D model draft; Step 5, Model Storage and Reuse: The model storage and retrieval module categorizes and stores the model and related data, and enables model retrieval and reuse; Step 6, Visualization and Data Linkage: The visualization module displays the model and simulated engineering scenarios, and the interface extension module enables data linkage between the model and other digital systems; Step 7, Model Update and Maintenance: Update the model in real time and maintain it regularly according to project requirements.

8. The intelligent building engineering three-dimensional modeling method according to claim 7, characterized in that, Step 2, specifically the intelligent data preprocessing, includes: Remove redundant and erroneous data and correct data deviations; Transform unstructured data into structured data, and convert design data into a standardized format compatible with the system. By extracting data features through AI algorithms, the system can automatically identify building components, dimensional parameters, and constraints.

9. The intelligent building engineering three-dimensional modeling method according to claim 7, characterized in that, Step 3, multi-disciplinary collaborative modeling, specifically includes: Multiple professionals can obtain standardized modeling foundation data through cloud-based collaborative units; The automatic modeling unit generates a preliminary 3D model through AI generative design algorithms and parametric modeling algorithms; The human interaction unit fine-tunes and supplements the initial 3D model, completing multi-disciplinary collaborative modeling.

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