Industrial building frame structure design method based on artificial intelligence

Abstract

The invention discloses an industrial building frame structure design method based on artificial intelligence. The method comprises the following steps: a, establishing an industrial building frame structure design scheme database; b, inputting constraint conditions through a man-machine interaction platform; c, based on an artificial intelligence generative algorithm, an initial structure arrangement scheme is generated according to input constraint conditions, and automatic checking is carried out to solve the problem of collision between structural members and professional equipment; d, calling structure analysis software to verify the initial structure arrangement scheme; e, the structure engineer evaluates and analyzes the structure arrangement scheme and the calculation result, confirms the feasibility of the structure arrangement, and generates a three-dimensional structure model and a two-dimensional construction drawing based on the BIM technology; and f, performing artificial detail supplement on the construction drawing, and outputting a final construction blueprint. Structural arrangement, verification and optimization processes are automatically completed by an artificial intelligence analysis processing system, so that the labor cost is reduced, the design time is saved, and the project design period is shortened.

Description

Technical Field

[0001] This application relates to the technical field of architectural design, and particularly to a design method for the frame structure of industrial buildings based on artificial intelligence. Background Art

[0002] The traditional design of the frame structure of industrial buildings highly relies on manual experience. The design process usually includes multiple stages such as structural layout, model analysis, construction drawing drawing, and three-dimensional model generation. However, the current structural design mostly depends on manual operations. During the design process, it is necessary to repeatedly adjust the component parameters to meet the requirements of safety and economy, resulting in a large amount of repetitive work and low efficiency. At the same time, the structural design requires the cooperation of various specialties. For example, it is easy to have spatial conflicts between structural components and specialties such as process equipment and pipelines, and manual detection and adjustment are required, resulting in difficulties in cross-specialty collaboration. In addition, the process of structural verification and analysis, as well as the design processes of three-dimensional models and two-dimensional models, require a large amount of labor costs and a long design cycle.

[0003] Therefore, how to improve the design efficiency of the frame structure of industrial buildings, reduce the design cost and cycle, is a technical problem that needs to be solved urgently by those skilled in the art. Summary of the Invention

[0004] In view of this, the purpose of this application is to provide a design method for the frame structure of industrial buildings based on artificial intelligence, so as to improve the design efficiency of the frame structure of industrial buildings and reduce the design cost and cycle.

[0005] To achieve the above purpose, this application provides the following technical solutions:

[0006] A design method for the frame structure of industrial buildings based on artificial intelligence, including the following steps:

[0007] a. Establish a database for the design scheme of the frame structure of industrial buildings. The database contains the structural component model data information of existing projects. The data information includes material information, load information, component cross-sectional dimensions, and component calculation lengths.

[0008] b. Input constraint conditions through a human-computer interaction platform. The constraint conditions include structural parameter information, information provided by each specialty, and target engineering quantities.

[0009] c. Based on the artificial intelligence generative algorithm, extract the matching component model data from the database according to the input constraint conditions, generate an initial structural layout scheme, and automatically check to solve the collision problem between structural components and equipment of each specialty.

[0010] d. Call the structural analysis software to verify the initial structural layout plan. If the verification fails, feedback to the artificial intelligence system to adjust the component parameters in the problem area and regenerate the plan. Repeat this step until all areas pass the verification, and then output the structural model;

[0011] e. The structural engineer evaluates and analyzes the structural layout plan and calculation results, confirms the feasibility of the structural layout plan, stores the verified structural layout plan in the database, and generates a 3D structural model and 2D construction drawings based on BIM technology;

[0012] f. Manually supplement the details of the generated construction drawings and output the final construction blueprints.

[0013] Preferably, in the above structural design method, in step a, the structural component model data information is stored classified by beams, slabs, and columns, and the database is dynamically updated by continuously accumulating verified structural plans.

[0014] Preferably, in the above structural design method, in step d, the structural analysis software called by the artificial intelligence system includes YJK, PKPM, SAP2000, or ETABS, and the artificial intelligence system and the structural analysis software achieve data interaction through a preset interface.

[0015] Preferably, in the above structural design method, in step e, the 3D structural model is generated by Revit or Tekla Structures, and the 2D construction drawings are dynamically linked to the 3D model. Adjust the 3D model to automatically synchronize and update the 2D construction drawings.

[0016] Preferably, in the above structural design method, the human-computer interaction platform integrates structural analysis functions, allows users to view verification results and adjustment suggestions in real time, and supports multi-disciplinary collaborative input of constraint conditions.

[0017] Preferably, in the above structural design method, in step d, during the process of the structural analysis software verifying the initial structural layout plan, if the structural verification fails, the system preferentially adjusts the local component parameters according to the analysis results and generates a new plan through an iterative algorithm; if the structural verification fails after a preset number of times, the system re-adjusts the overall layout plan and conducts verification again.

[0018] Preferably, in the above structural design method, in step e, the 2D construction drawings generated based on BIM technology are automatically marked with key dimensions and material information through a customized drawing template, and the editing permission for manually supplemented details is retained.

[0019] Preferably, in the above structure design method, in step c, a collision detection module is included. The collision detection module automatically identifies and resolves spatial conflicts with process equipment and pipelines when generating the initial structure layout plan; and the collision detection module performs conflict analysis based on the geometric features of the 3D model and a preset rule library, and generates a visual report for the user to confirm.

[0020] Preferably, in the above structure design method, the artificial intelligence generative algorithm supports multi-objective optimization, including safety, economy, and construction feasibility, and achieves an overall optimal solution through weight allocation.

[0021] Preferably, in the above structure design method, the weight allocation for safety, economy, and construction feasibility includes the system's default ratio and also supports manual input of the ratio.

[0022] As can be seen from the above technical solutions, the industrial building frame structure design method based on artificial intelligence provided by the present disclosure establishes a database of industrial building frame structure design solutions, inputs constraint conditions through a human-computer interaction platform to automatically generate an initial model, further performs iterative verification through a structural analysis software to obtain model data that meets the design requirements, and automatically generates a 3D structural model and 2D construction drawings based on BIM technology. It reduces a large number of repetitive actions in the traditional design process, especially the initial design and checking, and even the construction drawing output steps. It can significantly shorten the design cycle and improve the intelligent level and design efficiency of industrial building frame structure design. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, the drawings in the following description are only some embodiments of the present application. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0024] Figure 1 It is a schematic diagram of the steps of the structure design method provided by the present disclosure;

[0025] Figure 2 It is a schematic diagram of the detailed process of the structure design method;

[0026] Figure 3 It is a schematic diagram of the design process corresponding to step S02;

[0027] Figure 4 It is a schematic diagram of the design process corresponding to steps S03 - S06. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0028] The core of this application is to disclose a design method for the frame structure of industrial buildings based on artificial intelligence, aiming to improve the design efficiency of the frame structure of industrial buildings, reduce the design cost and cycle.

[0029] To enable those skilled in the art to better understand the solution of this application, the embodiments of this application will be described below with reference to the accompanying drawings. In addition, the embodiments shown below do not impose any limitation on the inventive content recorded in the claims. Furthermore, all the contents of the configurations shown in the following embodiments are not limited to those necessary for the solution of the invention recorded in the claims.

[0030] As Figure 1 、 Figure 2 、 Figure 3 and Figure 4 shown, the present disclosure provides a design method for the frame structure of industrial buildings based on artificial intelligence to efficiently generate a structural design solution that meets the engineering requirements. Specifically, the structural design method at least includes the following steps:

[0031] S01: Establish a database for the design solutions of the frame structure of industrial buildings.

[0032] First of all, this structural design method needs to establish a database for the design solutions of the frame structure of industrial buildings. This database is the basis for subsequent intelligent design. The database stores a large amount of data information on the structural component models of existing projects and is generated by extracting the data of the structural component models in a large number of existing industrial building frame structure solutions. It should be noted that the data information of the structural component models in the database covers material information, such as the model and strength grade of steel; load information, including the magnitude and distribution of permanent loads, live loads, etc.; and the cross-sectional dimensions of components, such as the width and height of beams, and the cross-sectional shape and size of columns; as well as the calculated lengths of components, which are used for subsequent structural calculations and analyses. By collecting and sorting out these detailed data information, it provides a rich reference resource for subsequent designs.

[0033] It should be noted that based on the above database, a data analysis system can be established. Based on this analysis system, the present disclosure can execute the steps:

[0034] S02: Input constraint conditions.

[0035] Specifically, for the database and the established data analysis system provided in the above embodiments, constraint conditions are input through the human-computer interaction platform. This platform provides a convenient operation interface for designers, enabling them to accurately input various engineering-related constraint conditions into the system. Specifically, the constraint conditions input to the human-computer interaction platform include structural parameter information, such as the number of floors, height, span of the structure, etc.; information provided by each specialty, such as the building floor plan provided by the architecture specialty, the equipment location and pipeline routing provided by the mechanical and electrical specialty, etc.; and the target engineering quantity, that is, indicators such as the material consumption and the number of components that the project expects to achieve. The constraint conditions are the basic requirements that must be met during the design process. After inputting the above constraint conditions into the data analysis system through the human-computer interaction platform, subsequent steps can be carried out based on this, that is, step S03. Specifically,

[0036] S03: Extract matching component model data.

[0037] In step S03, based on the artificial intelligence generative algorithm and combined with the input constraint conditions, the system extracts matching component model data from the database to generate an initial structural layout plan. This process is implemented based on the database without the need for designers to operate. By leveraging the powerful data processing and generation capabilities of artificial intelligence, it is possible to screen out component models that meet the requirements from a large amount of data in a short time and generate a preliminary structural layout plan according to certain rules and logic.

[0038] At the same time, based on the initial structural layout plan, this algorithm also has the ability to automatically check and solve the collision problems between structural components and equipment of each specialty. Based on the constraint conditions input through the human-computer interaction platform in step S02, the data analysis system conducts spatial checks between structural components and equipment, pipelines, etc. When problems such as collisions or too small spacing occur, it will automatically make corrections to avoid the existence of collision risks. Through the automated collision detection and resolution mechanism, it is possible to effectively avoid design modifications and construction delays caused by collisions, and improve the feasibility of the design and the smoothness of construction.

[0039] S04: Structural analysis of the initial structural layout plan.

[0040] After successfully generating the initial structural layout plan without collision problems, the data analysis system then calls the structural analysis software to verify the initial structural layout plan. It should be noted that structural analysis is a key step to ensure the safety and reliability of the structure. If the verification fails, the system will feedback the problem to the artificial intelligence system. The artificial intelligence system automatically adjusts the component parameters in the problem area according to the feedback information, such as changing the cross-sectional dimensions and material strengths of the components, and then regenerates the plan. The above process will be repeated until all areas pass the verification, and finally a structural model will be output. This automated verification and adjustment mechanism greatly improves the design efficiency, reduces manual intervention, ensures the quality of the design scheme, and can cover all areas that need to be detected, thus solving the risk of omission existing in manual analysis.

[0041] After step S04 is executed, the action of step S05 can be carried out. Specifically:

[0042] S05: Generate a three-dimensional structural model and two-dimensional construction drawings.

[0043] In step S05, the structural engineer first evaluates and analyzes the structural layout plan and calculation results to confirm the feasibility of the structural layout plan. This process involves human intervention to review the plan generated by the artificial intelligence through the professional knowledge and experience of the structural engineer to ensure that it meets the actual engineering requirements and relevant code requirements. The structural layout plan confirmed to be feasible after evaluation will be stored in the database, which can not only meet the current design requirements but also provide a reference for subsequent similar projects, contributing to the continuous enrichment and improvement of the database. Further, based on the BIM (Building Information Modeling) technology, a three-dimensional structural model and two-dimensional construction drawings are generated. The application of BIM technology greatly improves the visualization degree of the structural model. The three-dimensional structural model can intuitively display the spatial form of the structure and the relationship between components, while the two-dimensional construction drawings provide detailed construction guidance for construction personnel.

[0044] It should be noted that the above system, through BIM technology, not only solves the problem of low efficiency of manual drawing but also realizes the dynamic linkage between the three-dimensional model and the two-dimensional construction drawings. When the three-dimensional model is adjusted, the two-dimensional construction drawings can be automatically updated synchronously, further improving the collaborative efficiency of design and construction.

[0045] Further, this structural design method also includes the steps:

[0046] S06: Manual detail supplement.

[0047] In step S06, manual details are supplemented to the construction drawings generated by the system to output the final construction blueprints. It should be noted that although artificial intelligence and BIM technology have been able to generate relatively complete construction drawings, manual supplementation and improvement are still required in some details. For example, some special construction requirements, local structural details, etc. These manually supplemented contents can make the construction drawings more complete and accurate, providing a more reliable basis for the construction process.

[0048] Through the above steps, the structural design method of this embodiment gives full play to the advantages of artificial intelligence and BIM technology, realizing the high-efficiency, intelligent and collaborative design of industrial building frame structures, improving the design quality and efficiency, and providing a strong guarantee for the smooth implementation of industrial building projects.

[0049] Furthermore, in the structural design method provided in the embodiments of the present disclosure, in step S01, the structural member model data information in the database is stored classified by beams, slabs, and columns. The classified storage method makes the data in the database clearer and more orderly, facilitating subsequent query and invocation. Beams, slabs, and columns are the main components in the industrial building frame structure, and they each have different force characteristics and design requirements. By storing them separately, data information related to specific components can be extracted more accurately, improving the accuracy and efficiency of the design. At the same time, it should be noted that the database in the above embodiments is dynamically updated by continuously accumulating verified structural schemes, that is, the database is not a static data set, but a dynamic system that can continuously self-improve and optimize. After a single design, the structural schemes that have passed verification in the design process will be stored in the database and become new data resources. The newly accumulated data not only enriches the content of the database, but also provides more references for subsequent designs. As time goes by and projects accumulate, the data in the database will become more and more rich and diverse, so that the structural design method provided in this embodiment can better adapt to industrial building projects of different types and scales, improving the adaptability and flexibility of the design.

[0050] Furthermore, in the structural design method provided by the embodiments of the present disclosure, in step S04, the structural analysis software called by the artificial intelligence system includes YJK (Yingjianke Software), PKPM (Engineering Management Software), SAP2000 (Finite Element Analysis Software), or ETABS (Building Structure Analysis and Design Software). These structural analysis software are widely used analysis software in the current industry, and they have powerful structural analysis functions, capable of performing precise mechanical calculations and analyses on complex structural systems. Specifically, YJK software is favored by many designers for its high calculation speed and friendly user interface; PKPM software has a wide range of applications in the domestic architectural design field, with comprehensive functions and compliance with domestic design specifications; SAP2000 and ETABS are internationally renowned structural analysis software, and they have unique advantages in dealing with complex structures and long-span structures. At the same time, the artificial intelligence system and the above-mentioned structural analysis software achieve data interaction through a preset interface, and the preset interface enables seamless docking between the artificial intelligence system and the structural analysis software, and data can be transmitted quickly and accurately between the two. When the artificial intelligence system generates an initial structural layout plan, it transmits the relevant data of the plan to the structural analysis software through the interface, and the structural analysis software performs mechanical calculations and analyses based on these data, and then feeds back the verification results to the artificial intelligence system. If the verification fails, the artificial intelligence system adjusts the component parameters according to the feedback information and regenerates the plan, and again transmits the new plan data to the structural analysis software through the interface for verification. This process is repeated continuously until all areas pass the verification. This automated data interaction method greatly improves the design efficiency, reduces the tediousness and error rate of manual operations, and also makes the design process more smooth and coherent.

[0051] In addition, it should be noted that in step S05, the verified structural layout plan is generated by Revit (Building Information Modeling Software) or Tekla Structures (Steel Structure Detail Design Software) when generating a three-dimensional structural model. It should be noted that both Revit and Tekla Structures are well-known professional software in the current Building Information Modeling (BIM) field, and they have powerful functions and advantages in three-dimensional modeling, so as to intuitively display the spatial form of the structure, the connection relationship between components, and the collaborative relationship with other disciplines such as architecture and equipment through the three-dimensional structural model, facilitating designers and constructors to have a comprehensive understanding and analysis of the structure.

[0052] Meanwhile, the 2D construction drawings generated in step S05 are dynamically linked to the 3D model, which is one of the important features of BIM technology and also the key innovation point of this embodiment. When the 3D model is adjusted, the 2D construction drawings can be automatically updated synchronously. It should be noted that in the traditional design process, the 3D model and the 2D construction drawings are usually made and managed separately. When the 3D model changes, the 2D construction drawings need to be manually modified, which not only increases the workload but also is prone to errors. However, the dynamic linkage mechanism implemented by this application through the artificial intelligence system and BIM technology can solve this problem. Any modification made by the designer in the 3D model, such as adjusting the size or changing the position of components, will be automatically reflected on the 2D construction drawings, ensuring that the 2D construction drawings are always consistent with the 3D model. This linkage mechanism greatly improves the design efficiency, reduces construction errors and delays caused by inconsistent models and drawings, and also improves the coordination between design and construction.

[0053] Furthermore, in the structural design method provided by the present disclosure, the human-computer interaction platform not only serves as a tool for inputting constraint conditions but also integrates a structural analysis function. Specifically, the human-computer interaction platform integrated in the human-computer interaction platform enables users to view the verification results and adjustment suggestions in real time during the design process. After the artificial intelligence system generates an initial structural layout plan based on the input constraint conditions, it calls a structural analysis software for verification, and the verification results will be immediately fed back to the human-computer interaction platform. Users can intuitively see whether the position setting and mechanical properties of the structural plan meet the requirements through the platform. If the verification fails, the platform will also provide corresponding adjustment suggestions, such as suggesting to change the cross-sectional size or material strength of components. This real-time feedback mechanism enables users to promptly understand the problems occurring in the design process and make corresponding modifications according to the adjustment suggestions, while ensuring the convenience of human intervention, thus greatly improving the design efficiency and accuracy.

[0054] Meanwhile, the human-computer interaction platform supports multi-professional collaborative input of constraint conditions. In industrial building design, it involves multiple professional fields such as architecture, structure, and mechanical and electrical engineering. Each profession has its specific design requirements and constraint conditions. Through the multi-professional collaborative function of the human-computer interaction platform, designers from different professions can input their respective professional constraint conditions on the same platform through different devices. For example, architecture professionals can input information such as building floor plans and building heights; mechanical and electrical professionals can input information such as equipment locations and pipeline routes; and structure professionals can input structural parameters and load information. The constraint conditions of different professions can be integrated on the same platform for comprehensive analysis, providing a comprehensive and accurate design basis for artificial intelligence generative algorithms. The multi-professional collaborative input method not only improves the design collaboration and efficiency but also ensures that the design scheme can comprehensively consider the characteristics and requirements of each profession, avoiding design conflicts and modifications caused by information asymmetry between professions.

[0055] Furthermore, in step S04, during the process of the structural analysis software verifying the initial structural layout plan, if the structural verification fails, the system will preferentially adjust the parameters of local components according to the analysis results and generate a new plan through an iterative algorithm. Specifically, when the verification fails, the system first analyzes which local components have problems and then adjusts the parameters of these local components accordingly, such as changing the cross-sectional dimensions and material strengths of the components. Through local adjustments, problems can be quickly solved in the problem areas, reducing major changes to the entire structural plan and improving design efficiency. At the same time, the system uses an iterative algorithm to generate a new plan. The iterative algorithm is an algorithm that continuously optimizes and approaches the optimal solution. It can automatically perform the next round of adjustments and verifications based on the results of each adjustment until a structural plan that meets the requirements is found. This iterative process can ensure the gradual optimization and improvement of the design plan.

[0056] It should be noted that if the structural verification fails after the preset number of times, the system will readjust the overall layout plan and verify it again. Among them, the preset number of times is set by the designer according to the project level and design level requirements. For complex projects, the preset number of times can be appropriately increased; the setting of the preset number of times is to prevent the system from falling into an infinite loop of adjustment states. When the structural plan still fails to pass the verification after multiple local adjustments, it means that there may be deeper problems in this structural design, and the overall layout plan of the entire structure needs to be reexamined and adjusted. The system will optimize the overall layout of the structure according to the previous verification results and analysis data, such as adjusting the arrangement positions of components and changing the structural system, and then re-perform structural analysis and verification. This adjustment strategy from local to overall can not only quickly solve local problems but also optimize the overall plan when necessary, ensuring that the final design plan can meet the engineering requirements.

[0057] Furthermore, in step S05, the two-dimensional construction drawings generated based on BIM technology are automatically marked with key dimensions and material information through a customized drawing template. The customized drawing template is pre-set according to the standard specifications and design requirements of the industrial building industry, which can ensure that the markings on the two-dimensional construction drawings comply with industry standards and the actual engineering requirements. The markings of key dimensions include the length, width, height, etc. of components, and the above dimension information is crucial for construction workers to construct accurately. The markings of material information include the model, specification, strength grade, etc. of materials, and these information can help construction workers select appropriate materials for construction. Through the automatic marking function, the workload and error rate of manual marking are reduced, and the accuracy and consistency of the construction drawings are improved. At the same time, it should be noted that the above two-dimensional construction drawings still retain the editing permission for manual supplement of details. Although the automatic marking function can complete most of the marking work, in some special cases, manual supplement and adjustment are still required. For example, for some special construction requirements and local structural details, the automatic marking may not be able to cover them completely. Therefore, retaining the manual editing permission enables designers and construction workers to further improve and supplement the construction drawings according to the actual situation. This editing permission for manual supplement of details not only ensures the integrity of the construction drawings, but also can meet the special requirements on the construction site, improving the applicability and flexibility of the construction drawings.

[0058] In addition, it should be noted that in step S03, the artificial intelligence system includes a collision detection module. The collision detection module automatically identifies and resolves spatial conflicts with process equipment and pipelines when generating the initial structural layout plan. In the early design stage, the collision detection module automatically detects potential collision problems and resolves them in a timely manner, avoiding design modifications and construction delays caused by collisions. After the artificial intelligence generative algorithm generates the initial structural layout plan according to the input constraint conditions, the collision detection module will immediately perform collision detection on the plan. It can identify whether there are spatial conflicts between structural components and process equipment and pipelines, such as whether a component collides with equipment or pipelines, and whether the clear distance between the component and the equipment or pipelines meets the requirements. Once a collision problem is found, the collision detection module will automatically adjust the position, size or shape of the component to resolve the conflict and generate a collision-free structural layout plan.

[0059] It should also be noted that the collision detection module can perform conflict analysis based on the geometric features of the 3D model and the preset rule library, and generate a visualization report for the user to confirm, so as to present the collision problem to the user in an intuitive way. Information such as the collision location, the components and devices involved, and the reason for the conflict will be clearly marked in the visualization report. The user can quickly understand the details of the collision problem through the report and confirm the solution measures of the collision detection module. The visualization report not only improves the transparency and understandability of collision detection, but also enables the user to participate in the collision resolution process to ensure that the solution meets the actual engineering requirements.

[0060] In addition, it should be noted that in the structural design method provided in the embodiments of the present disclosure, the artificial intelligence generative algorithm can support multi-objective optimization, that is, it includes the coupling ratio optimization of the safety, economy, and construction feasibility of the current design process. It should be noted that in industrial building design, safety is the primary goal. The structure must be able to withstand various load effects to ensure the safety and reliability of the building during use. At the same time, economy is also an important consideration. The design scheme needs to minimize the material usage and reduce the construction cost on the premise of meeting safety requirements. Secondly, construction feasibility involves whether the design scheme is convenient for construction implementation, such as whether the installation of components is convenient and whether the construction technology is feasible. Through the multi-objective optimization function of the artificial intelligence generative algorithm, these goals can be comprehensively considered in the design process to generate a structural design scheme that is safe, economical, and convenient for construction. Moreover, the algorithm achieves the comprehensive optimal solution through weight assignment. In the multi-objective optimization process, there may be certain contradictions and conflicts between different goals. For example, improving safety may increase the material usage, thus reducing the economy; while overly pursuing economy may lead to a reduction in the structural safety. To balance the relationship between these goals, the artificial intelligence generative algorithm introduces a weight assignment mechanism to assign different weights to safety, economy, and construction feasibility according to the specific requirements and priorities of the project. The magnitude of the weight determines the importance of each goal in the optimization process. So that the artificial intelligence generative algorithm can make trade-offs and optimizations among multiple goals, and finally find a comprehensive optimal solution to achieve the best balance among safety, economy, and construction feasibility in the design scheme.

[0061] Based on the above embodiments, the weight distribution for safety, economy, and construction feasibility includes the system - provided ratio. It should be noted that the system - provided ratio is pre - set according to a large amount of engineering experience and industry standards. It provides a default weight - distribution scheme for designers. The default scheme can generally balance the relationship between safety, economy, and construction feasibility well and is applicable to most industrial building design projects. At the same time, the system supports manual input of ratios. In some special projects, adjustments may be required according to specific circumstances. For example, for an industrial building project located in an earthquake - prone area, the importance of safety may be higher, and designers may need to increase the weight of safety and correspondingly reduce the weights of economy and construction feasibility. Through the system design that supports manual input of ratios, the system can meet the special needs of different projects, and designers can flexibly adjust the weight distribution according to the actual situation to further optimize the design scheme.

[0062] The terms "first", "second", "left side", "right side", etc. in the description of the specification, claims, and the above - mentioned drawings of this application are used to distinguish different objects rather than to describe a specific order. In addition, the terms "comprising" and "having" and any of their variations are intended to cover non - exclusive inclusion. For example, a process, method, system, product, or device that includes a series of steps or units is not limited to the listed steps or units but may include unlisted steps or units.

[0063] The above description of the disclosed embodiments enables those skilled in the art to implement or use this application. Various modifications to these embodiments will be obvious to those skilled in the art, and the general principles defined herein can be implemented in other embodiments without departing from the spirit or scope of this application. Therefore, this application will not be limited to these embodiments shown herein but will be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. An industrial building frame structure design method based on artificial intelligence, characterized in that, Including the following steps: a. Establish a database for the design scheme of the industrial building frame structure. The database contains the structural member model data information of existing projects. The data information includes material information, load information, member cross-sectional dimensions, and member calculation lengths; b. Input constraint conditions through a human-computer interaction platform. The constraint conditions include structural parameter information, information provided by each specialty, and target engineering quantities; c. Based on the artificial intelligence generative algorithm, extract matching member model data from the database according to the input constraint conditions, generate an initial structural layout scheme, and automatically check to solve the collision problem between structural members and equipment of each specialty; d. Call a structural analysis software to verify the initial structural layout scheme. If the verification fails, feedback it to the artificial intelligence system to adjust the member parameters in the problem area and regenerate the scheme. Repeat this step until all areas pass the verification, and output the structural model; e. The structural engineer evaluates and analyzes the structural layout scheme and calculation results, confirms the feasibility of the structural layout scheme, stores the verified structural layout scheme in the database, and generates a 3D structural model and 2D construction drawings based on BIM technology; f. Manually supplement the details of the generated construction drawings and output the final construction blueprints.

2. The structural design method according to claim 1, wherein In step a, the structural member model data information is stored classified by beams, slabs, and columns, and the database is dynamically updated by continuously accumulating verified structural schemes.

3. The structural design method according to claim 1, characterized in that In step d, the structural analysis software called by the artificial intelligence system includes YJK, PKPM, SAP2000, or ETABS, and the artificial intelligence system and the structural analysis software achieve data interaction through a preset interface.

4. The structural design method according to claim 1, characterized in that, In step e, the 3D structural model is generated by Revit or Tekla Structures, and the 2D construction drawings are dynamically linked with the 3D model. Adjust the 3D model to make the 2D construction drawings automatically synchronously updated.

5. The structural design method according to claim 1, characterized in that The human-computer interaction platform integrates structural analysis functions, allows users to view verification results and adjustment suggestions in real time, and supports multi-specialty collaborative input of constraint conditions.

6. The structural design method according to claim 1, wherein In step d, during the process of the structural analysis software verifying the initial structural layout scheme, if the structural verification fails, the system preferentially adjusts the local member parameters according to the analysis results and generates a new scheme through an iterative algorithm; if the structural verification fails for a preset number of times, the system re-adjusts the overall layout scheme and verifies it again.

7. The structural design method according to claim 1, characterized in that In step e, the 2D construction drawings generated based on BIM technology are automatically marked with key dimensions and material information through a customized drawing template, and the editing permission for manually supplemented details is reserved.

8. The structural design method according to claim 1, characterized in that, In step c, it includes a collision detection module. The collision detection module automatically identifies and solves the spatial conflicts with process equipment and pipelines when generating the initial structural layout scheme; and the collision detection module conducts conflict analysis based on the geometric features of the 3D model and a preset rule library, and generates a visual report for users to confirm.

9. The structural design method according to any one of claims 1-8, characterized in that, The artificial intelligence generative algorithm supports multi-objective optimization, including safety, economy, and construction feasibility, and achieves an overall optimal solution through weight allocation.

10. The structural design method according to claim 9, characterized in that, The weight distribution for safety, economy, and construction feasibility includes the system's built-in ratio and also supports manual input of ratios.

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