75 results about "Building code" patented technology

The invention relates to the technical field of data processing, and discloses a BIM-based building construction quality information intelligent supervision system, which is used for improving the efficiency and accuracy of BIM-based building construction quality information intelligent supervision. The method comprises the following steps: a modeling module performs BIM modeling processing on a building engineering design drawing and building specification data to obtain a building twinborn body; the deployment module carries out field data acquisition system deployment on the building twinborn body to obtain a real-time data acquisition system; the detection module performs anomaly detection processing on the data acquired by the system to obtain a quality anomaly alarm and a priority processing level; the processing module carries out multi-dimensional visualization processing on the quality abnormity alarm and the priority processing level to obtain a visual interface; the decision-making module performs intelligent decision-making analysis on the quality abnormal information in the visual interface to obtain a target processing scheme; and the analysis module performs time sequence analysis and multivariable correlation analysis on the target processing scheme to obtain a dynamic quality evaluation report.

The invention relates to the technical field of building engineering, in particular to a building data processing method and system based on multiple building specifications, and the method comprises the steps: building model data standardization processing: extracting geometric attributes, material attributes and spatial topological relations of components through a BIM software interface, and generating model data in a standard format; constructing a multi-source specification rule tree, performing semantic analysis on national standard, local standard and industrial standard provisions, extracting triple constraint conditions, and fusing to generate a unified rule tree containing hierarchical relationships and conflict marks; on the basis of a spatial topology mapping relationship between the model and the rule tree, identifying a specification conflict and generating an optimization rule set according to a specification effectiveness level and a spatial attribute priority; and finally, real-time compliance verification is executed, and a three-dimensional compliance report including conflict positioning, article basis and correction suggestions is output. According to the method, multi-source specifications can be automatically adapted, model violation components are accurately recognized, a correction scheme is given, and the specification compliance and the verification efficiency in the design stage are improved.

The invention provides a building construction scheme intelligent auditing system based on a large model, and belongs to the field of building construction. According to the technical scheme, the method comprises the steps that a construction scheme template library and a building construction standard specification library are constructed, a building specification knowledge graph is constructed, a to-be-audited construction scheme document is received and subjected to structural division and preprocessing, semantic vector data are obtained, matching operation is conducted on the semantic vector data and graph nodes in the building specification knowledge graph, and the graph nodes in the building specification knowledge graph are obtained; and outputting audit target data, analyzing and generating an analysis result data structure based on the audit target data, generating an audit report according to an analysis result, and completing recording and tracking of an audit process. The method has the beneficial effects that automatic auditing and whole-process tracking of the construction scheme are realized by constructing the structured template and the standard specification knowledge graph in combination with semantic vector matching and rule work efficiency comparison, the accuracy, consistency and efficiency of auditing are effectively improved, and the informatization and intelligence level of building construction management is remarkably enhanced.

The invention relates to a building specification compliance verification method based on dynamic prompt and map dual drive. The method comprises the steps of obtaining a to-be-examined construction organization design scheme text; preprocessing is carried out, and a core construction object set is identified; generating a high-confidence structured design element set; matching the structured design element set with specification terms in the building specification knowledge graph; performing logic comparison on parameter values in the structured design elements and compliance requirements in the matched standard terms, judging a compliance state and generating deviation information; and generating a compliance verification report according to a comparison result. The method has the beneficial effects that through a dynamic multi-round prompt chain technology, the large language model is guided to carry out iterative extraction, conflict verification and context completion on the construction scheme text, and the defects that omission, ambiguity and logic contradictions are easy to occur in a complex and lengthy document in single extraction are overcome.

The invention discloses a knowledge graph-based old building reconstruction scheme automatic recommendation method. The method comprises the following steps of S1, obtaining and preprocessing old building house data; s2, extracting a semantic entity and attribute relationship from a transformation case library, a building specification library and a construction scheme library, and constructing a knowledge graph; s3, mapping the house data to knowledge graph entity nodes, and executing graph embedding to generate building semantic representation; s4, constructing a graph neural network, calculating node semantic relevancy, and generating a building state vector; s5, inputting the building state vector into the reinforcement learning decision network, and optimizing the strategy to obtain an optimal transformation action; s6, screening reconstruction measures from the knowledge graph according to the optimal reconstruction action, and performing scoring to form candidate schemes; and S7, sorting the candidate schemes, selecting the scheme with the highest score, and recommending and updating the knowledge graph. According to the method, intelligent generation and self-optimization recommendation of the old building reconstruction scheme are realized, and the reconstruction efficiency of the scheme is remarkably improved.

The invention relates to a programmed reconstruction method, system and device for a building structure and computer equipment. The method comprises the steps of obtaining point cloud data of a target building, and performing feature extraction on the point cloud data to obtain a geometric feature map; based on a preset coding language, the geometric feature map is converted into a building coding statement, and the building coding statement is used for representing a building structure; the building coding statement is converted into a target building tree, the target building tree comprises a plurality of nodes, and the plurality of nodes represent heights and contours of different levels in a target building; and constructing a three-dimensional building model of the target building based on the target building tree. The method can effectively solve the challenges in the prior art when processing the sparse, more-noise and non-uniformly-distributed point cloud data, and provides a new way for efficiently and accurately recovering the complex building three-dimensional model from the low-quality point cloud data.

The present disclosure presents systems and methods for integrating and executing a building code check tool. One such method comprises obtaining a construction model of a construction project, wherein the construction model includes construction project parameters; and obtaining an input specifying a regulatory building code section. The method further comprises performing a compliance code check against the regulatory building code section by capturing the construction model parameters from the construction model; prompting a user to provide additional construction model parameters; and evaluating the construction model against the regulatory building code section using the captured construction model parameters and the additional construction model parameters; and outputting a list of model elements, wherein a result of the compliance code check for a model element is indicated next to the model element, wherein selection of the model element causes a location of the model element to be displayed within the construction model.

The invention discloses a point cloud generation method and system for deep learning semantic segmentation of a building prefabricated component. The method mainly comprises the steps of creating a structured text of a building prefabricated part generation rule, automatically generating a standardized building prefabricated part model based on a Revit secondary development environment, and generating point cloud data by using a graphics method. According to the method, the document is divided into three parts, namely the prefabricated part category, the corresponding size and the geometric feature, so that the structured building prefabricated part text is obtained, the readability of the building specification is improved, a reader can understand the text conveniently, the building prefabricated part model meeting the requirements of the building specification is generated in an automatic mode, and the working efficiency is greatly improved. The method can efficiently realize automatic and standardized generation of the point cloud data of the building prefabricated part model, and serves for size and quality detection of the building prefabricated part.

The invention discloses an automatic generation method for a beam-lifting wood structure building model and a construction drawing, and aims to solve the problem that research and practice for realizing automatic generation of components of a beam-lifting wood structure building in the prior art are still relatively deficient on the premise of strictly following a traditional construction rule. The method comprises the following steps: determining a building plane range of a beam-lifting wood structure building, determining a building overall layout according to building preset parameters input by a user, generating a building plane axis, generating a foundation support column component based on the building preset parameters and an axis grid according to corresponding building specifications, and constructing a three-dimensional beam frame positioning and reference system. Automatically calculating and generating a roof support member and an auxiliary connection and support member to form a complete wood structure building model; after modeling and node derivation are completed, building construction drawings and drawings and control data used for CNC machining are automatically generated; and a two-dimensional expansion graph is generated, and a three-dimensional processing model is synchronously exported. According to the invention, the problems are solved.

The invention discloses a Langchain-based building specification graphical representation multi-modal question answering method and equipment, belongs to the technical field of artificial intelligence and building industry crossing, and is used for solving the problems of difficulty in processing multi-modal information, low query efficiency and the like in building industry specification graphical representation question answering. The method comprises the following steps: constructing a building specification multi-modal database, and carrying out storage management on building specification multi-modal data; based on a user query instruction, retrieving the multi-modal database from different dimensions; generating a structured answer corresponding to the user query instruction according to the retrieval result; and performing image-text consistency verification on the structured answer, and after the verification is passed, outputting the answer corresponding to the user query instruction. According to the method, a complete building specification question answering system is constructed, efficient and accurate building specification multi-mode question answering is achieved, and the building specification query efficiency is improved.

The invention relates to the technical field of building intelligent management, and discloses a BIM-based indoor optimization design method and system, and the method comprises the following steps: a) building a building information model through BIM software, and collecting the space size, material parameters, structure parameters, environment data and user demand data of a building; and b) an indoor space optimization target is set according to design specifications and user requirements, design constraint conditions are formulated, and the design constraint conditions comprise building specifications, fire protection requirements, human flow lines, functional requirements and ergonomic parameters. According to the invention, through multi-source data fusion, high-precision and low-delay data acquisition is realized; through hybrid modeling, the balance between the accuracy of energy consumption prediction and the calculation efficiency is realized; through reinforcement learning and fuzzy control, adaptive optimization of building environment adjustment is realized; through the modular architecture and the block chain, high expansibility and data security of the system are realized.

Disclosed embodiments perform automated design for buildings or portions of buildings and machine-generate architectural design and floor plans. Computer-implemented systems and methods of designing multi-unit buildings and portions of buildings include a set of one or more input requirements, a relationships module, an options placement system, a layout predictor system, and a design plan generator. The input requirements include one or more pre-defined footprints and may include local regulatory requirements such as building code, zoning, accessibility, among others. The design plan generator generates an architectural design plan for the building or portion of a building that can be built on the one or more pre-defined footprints. Disclosed systems and methods substantially reduce the design time and cost while increasing the profitability, sustainability and efficiency of construction projects.

The invention relates to the technical field of building intelligent heating and ventilation system design and software development, and provides a fresh air system wiring method and system.The fresh air system wiring method comprises the steps that a building space model is analyzed, and space structure parameters of a room are obtained; according to the space structure parameters of the rooms, on the basis of preset air quality standards and building specifications, the ventilation times or unit area air volume values corresponding to the different rooms are automatically matched, and the fresh air volume and the return air volume of each room are calculated; according to a room type matching arrangement rule, determining an air supply / exhaust dominant strategy, generating an air port candidate position set meeting a preset obstacle avoidance rule in combination with room structure obstacle data and an avoidance condition, and outputting room air port coordinates and installation parameters based on an air quantity demand and a candidate position scoring result; and building the building space into a node network, defining a communication relation between nodes and an edge weight, and generating an optimal air pipe arrangement path from the air port to the host through a path planning algorithm.

The invention relates to a building space layout optimization design method and device, equipment and a medium. The method comprises the following steps: analyzing a building base contour, a room type library and a building specification text to generate structured data; based on the geometric boundary, the hard constraint rule set and the spatial topological relation graph, an optimized sampling scheme set is obtained through Latin hypercube sampling, reinforcement learning strategy and supplementary sampling processing, and based on the spatial topological relation graph, the attribute matrix and the soft constraint target set, multi-target calculation and agent model training processing are conducted on the optimized sampling scheme set, so that the optimal sampling scheme set is obtained. Obtaining a full-scheme evaluation set; and based on the hard constraint rule set and the soft constraint target set, performing Pareto screening, hard constraint repair and soft constraint optimization processing on the whole scheme evaluation set to generate a final optimization layout scheme. According to the method, by means of building design information structured analysis, multi-strategy sampling, multi-target evaluation and the like, the design efficiency, scheme compliance and multi-target performance global optimality of building space layout are improved.

A method and system for generating a design scheme for a variable-space residential building, relating to the field of residential design, includes: obtaining an initial three-dimensional residential model containing fixed and variable functional areas to provide a foundation for subsequent design; generating multiple preselected locations in the fixed functional areas based on preset building codes and structural requirements, and calculating comprehensive performance indicators to determine the optimal location distribution; generating preselected locations in the variable functional areas based on user demand parameters, spatial variability rules, and the location distribution of the fixed functional areas; then optimizing the layout by obtaining parameter values ​​through spatial variability simulation; and finally, placing preselected modules in the corresponding areas to generate a three-dimensional residential design model. The preselected modules are standardized, complete sets of industrial products, ensuring modular production efficiency while meeting the personalized spatial needs of different families at different stages of development. Implementing this method can improve the efficiency of variable-space residential design.

The invention discloses a model compliance checking method and device based on a building information model, and belongs to the technical field of BIM, and the method comprises the following steps: collecting and sorting related building specifications and standards, and converting the specifications into formats which can be read and processed by BIM software; preparing a BIM model to be checked; defining a series of inspection rules according to building specifications and standards; the rules cover all aspects from structure safety to energy efficiency; automatically comparing the BIM model with a pre-defined rule through an algorithm of BIM software; detecting whether each element in the model meets the rule requirement, and analyzing and reporting results: summarizing the detection results, analyzing non-compliant parts in the model, and providing a detailed report; the report not only points out specific positions and reasons of non-compliance, but also provides modification suggestions or possible solutions; and modifying and optimizing the BIM model according to an inspection result, and performing compliance inspection again until the model completely conforms to all specified standards and specifications.

The application discloses a kind of fusion BIM and AI's construction method, system, equipment and storage medium, it is related to intelligent construction and building digitization technical field, including importing building data into BIM modeling software, obtain BIM building data;Call AI design model, based on BIM building data and the design requirement of user, generate building layout scheme and space arrangement result, and automatically update to BIM model;AI drawing optimization is carried out to the BIM model after updating, load building specification library and user-defined rule, identify cross-professional conflict point in combination with collision detection algorithm;In construction stage, call the BIM model after drawing optimization, carry out risk prediction and decision deduction to real-time construction and operation data by AI.The method described in the application realizes automatic design and model dynamic updating, can improve compliance and cross-professional consistency in design stage, can realize dynamic monitoring and intelligent decision support in whole construction process.

The present disclosure belongs to the technical field of computer image processing, and relates to a method and device for processing architectural drawings, a storage medium, and an electronic device. The method includes: obtaining an initial building outline in an architectural drawing and architectural specification data corresponding to the architectural drawing, and generating a target building outline according to the initial building outline; calculating the building attributes according to the architectural drawing, and matching the building attributes with the architectural specification data to obtain contour line data; based on the initial building outline or the target building outline, drawing building auxiliary lines in the architectural drawing according to the contour line data. The present disclosure provides a data basis and theoretical support for drawing building auxiliary lines, ensures that the arrangement method meets national and local standards, provides an automated and intelligent drawing method for building auxiliary lines, realizes rule digitization and visualization drawing effects, can set an adjustable interface accordingly, has strong flexibility and practicality, and enriches the application scenarios of drawing building auxiliary lines.

A knowledge enhancement-based building model automatic compliance check method comprises the following steps: collecting text building specifications and carrying out structured processing, sequentially extracting specification provision entities and specification provision events for generating a code framework, complementing the code framework, and finally carrying out compliance check to obtain the building model. And constructing a model data set and outputting a compliance check result. According to the method, multi-modal building specifications are converted into specifications in a computer recognizable form by pre-training the large model and the BIM model, knowledge enhancement is realized by performing information extraction on the building specifications, and the problem that a traditional automatic compliance inspection method is greatly dependent on manual annotation and is poor in applicability to different professional building specifications is solved.

Methods and apparatus operative for analyzing water closet compliance with relevant building codes using artificial intelligence (AI). The system involves receiving design plans and representing them as dynamic components, which include various fixtures and architectural elements. Each dynamic component may include a parameter that is changeable via an interactive user interface. An AI engine identifies water closet areas, ascertains design parameters, and compares them against a set of compliance conditions. The AI engine can simulate various scenarios, such as wheelchair accessibility, and evaluate multiple design parameters like height, distance, size, and placement of fixtures. The interactive user interface allows users to view compliance status and receive automated suggestions for non-compliant features. The AI determines clearances within a water closet and assesses compliance with codes such as the Americans with Disabilities Act. Additionally, the AI provides recommendations to correct any code violations identified.

The present invention discloses a building information model inspection method, inspection device, and terminal device. The method includes: extracting objects, geometric attributes, and non-geometric attributes from a building information model to be inspected to form a model analysis data set; compiling each natural language building code clause into a rule consisting of an object, a calculation variable, and a verification paragraph, with multiple rules corresponding to natural language building code clauses forming a rule set; extracting objects, geometric attributes and non-geometric attributes corresponding to the objects, and calculated values ​​obtained by generalized calculation of the geometric attributes of multiple objects from the model analysis data set to form an information mapping table; for each rule in the rule set, extracting objects from the information mapping table and extracting judgment predicates from the verification paragraph to form a calculation mapping table; and comparing all objects screened out from the information mapping table with the corresponding judgment predicates in the calculation mapping table to generate a verification result. The inspection technology of the present invention is highly efficient and accurate.

The system according to the embodiment aims to efficiently create architectural design patterns from photographs and drawings. [Solution] A system according to an embodiment includes a reception unit, an analysis unit, and a generation unit. The reception unit inputs photographs and drawings. The analysis unit analyzes the information input by the reception unit. The generation unit creates a pattern of building guidelines based on the information analyzed by the analysis unit.

The present invention provides a method and system for rapid construction and reuse of an application framework, which relates to the technical field of application framework construction, including mapping code snippets to a high-dimensional tensor space, extracting multi-level code features, and constructing a code association graph and a deep semantic network; constructing a hierarchical Bayesian network based on a spatiotemporal feature graph, performing variational reasoning and adaptive particle filtering, and generating reconstructed code; using a dual-dimensional discriminator to drive a multi-level generation network, optimizing code structure and dependency, and generating final optimized code through program slicing and incremental synthesis; the present invention realizes rapid construction and reuse of an application framework, and improves code quality and execution efficiency.

Self-supporting concrete slabs can eliminate the need for temporary backshoring, streamlining the building process and enhancing productivity. These slabs are engineered to support their own weight and additional loads without relying on external supports, reducing labor and material costs while accelerating construction schedules. The process incorporates advanced reinforcement techniques, including post-tensioning and code-compliant splicing methods, to ensure structural integrity, continuity, and compliance with building codes. By simplifying forming processes and enabling early access for other trades, self-supporting slabs offer significant economic and operational advantages, making them a superior alternative to traditional slab designs.

The disclosure is directed at a method and system for generating dynamic building inspection checklists. The system and method compares tasks for a construction project with building code requirements and then generates a building inspection checklist based on the comparison. The system and method may then determine which tasks within the inspection checklist may result in a more negative impact if the task does not pass inspection and updates the checklist accordingly.

The present invention relates to a system and method for automatically generating a complete and precise bill of materials by learning the structural and logical relationships between design components using a graph neural network (GNN) from heterogeneous design data sources such as 2D CAD drawings, 3D BIM models, and specifications, and by predicting and interpolating the actual quantities to be input at the time of final completion from incomplete initial design data using a generative adversarial interpolation neural network (GAIN). The effects according to the present invention are as follows. First, the present invention precisely interpolates missing attributes using a Generative Adversarial Interpolation Network (GAIN) even in incomplete situations where input data, such as drawings, BIM, and specifications, is heterogeneous and some information (thickness, material, specifications, etc.) is missing. Through this, the reliability and integrity of input data, which forms the basis of quantity calculation, can be dramatically improved even in the initial design stage where data quality is low. Second, active risk management and design quality improvement through learning design change trajectories. Unlike existing methods that simply sum dimensions on drawings or predict only the final result, this invention predicts future change risks in advance by learning the trajectory of design changes through LSTM-based time-series historical analysis. By providing real-time feedback to the designer regarding warnings and alternatives for potential change-inducing factors, it fundamentally prevents unnecessary design changes, maximizes the accuracy of completion predictions, and minimizes the risk of increased construction costs and project delays. Third, it structurally learns the physical support, connectivity, inclusion, and spatial adjacency relationships of a building through a Graph Neural Network (GNN). This enables the automatic generation of a consistent bill of materials that aligns with the structural hierarchy and engineering correlations of the entire building (e.g., the relationship between column load and foundation reinforcement quantity), rather than merely calculating the fragmentary quantities of individual objects. Fourth, by utilizing a Large Language Model (LLM), the generated bill of materials items are double-checked to ensure they logically align with text-based specifications and building codes. By comprehensively evaluating semantic similarity and logical validity, legal and technical risks are minimized by preventing errors in advance where the quantity is correct but the specifications are incorrect (e.g., standard gypsum board vs. fire-resistant gypsum board). Fifth, by applying X-ray Influence Analysis (XAI) technology to the results generated by AI, it explains, using 3D heatmaps and causal text, which object (node) on the drawing is the origin of a specific volume increase. This resolves the 'black box' problem of AI and provides a reliable environment where users can clearly trace the basis of calculations. Sixth, regarding scalability, it enables risk-based estimation by providing multiple scenarios in the form of 'average value + range of variation (confidence interval)' rather than a single predicted value. Furthermore, by linking the calculated quantity data with cost and schedule data, it provides full-cycle project management efficiency that allows for the immediate simulation of the impact of design changes on total construction costs (5D) and construction duration (4D).

The application provides a building space segmentation method and system based on a maximum inscribed rectangle, comprising: acquiring a building space image to be segmented, reading the number of marked text points in the building space image to be segmented; solving the maximum inscribed rectangle of the building space image to be segmented based on the marked text points, obtaining the maximum inscribed rectangle of the marked text points; for the building space image to be segmented with different numbers of marked text points, different processing is performed on the maximum inscribed rectangle of each marked text point to obtain a space segmentation result, and a building space segmentation image is output; the method performs multi-space division based on the maximum inscribed rectangle, turns the abstract space division problem into an actual image processing problem, and accurately divides the building space in various marked text point situations in accordance with the building specification.

The invention discloses an indoor space rule knowledge graph construction method and system, terminal equipment and a medium, and relates to the technical field of knowledge graph construction, and the method comprises the steps: obtaining an indoor space rule; constructing an ontology model; based on the ontology model, performing information extraction on the indoor space rule by using a large language model to obtain an information set; and based on the information set, constructing a knowledge graph corresponding to the indoor space rule. According to the method, the ontology model is constructed, and the local model is used as the assistance of the large language model, so that the indoor space knowledge is accurately extracted from the building specification text. The constructed mapping knowledge domain can guide building indoor plane generation, check design scheme compliance, and effectively improve scientificity and normalization of building design.

The invention provides an integrated structure intelligent design system and method oriented to the field of building industry, and the system comprises a structure performance prediction module which generates corresponding input features based on the design parameters of a target component, and predicts the structure performance indexes of the target component; the parameter optimization module is used for executing two-stage optimization in a preset design variable space by taking a structural performance index and material cost as multi-objective optimization objectives: firstly, performing global search by adopting an improved genetic algorithm to generate a Pareto leading edge candidate scheme set; then, the performance of the candidate schemes is optimized in combination with a gradient descent method, and the optimized candidate schemes are obtained; and the scheme generation module is used for inputting the optimized candidate scheme into a pre-constructed building specification knowledge graph, automatically matching related design terms, executing compliance verification, and generating a structure calculation book and a component list after the verification is passed. By means of a full-process architecture generated by data driving, intelligent analysis and scheme, technical independence can be achieved, and the design efficiency is improved.

The invention discloses an intelligent examination method and system for a building construction drawing, and belongs to the technical field of building construction. The technical problems that a traditional manual review mode is low in efficiency and prone to making mistakes, and an existing automatic system is difficult to process heterogeneous drawing data and understand complex building specifications are solved. According to the technical scheme, the method comprises the steps of receiving original drawing files generated by different drawing software through a data interface and analyzing the original drawing files into standardized structured data objects; fusing two-dimensional geometric and text information based on the data object, and reconstructing a lightweight three-dimensional building information model with semantic attributes; converting the building standard provisions into structured computational logic rule nodes through natural language processing to form a standard knowledge graph; and finally, carrying out dynamic matching reasoning on the three-dimensional model and the knowledge graph, automatically identifying violation through parameterization calculation and logic judgment, and generating a visual review report. The system is mainly used for realizing automatic, intelligent and precise examination of the building construction drawing.