Feature-driven parameterized information model continuous iteration and full life cycle reuse system and method

Abstract

The invention relates to the technical field of building information models, in particular to a parameterization information model continuous iteration and full life cycle reuse system and method based on feature driving, and the method comprises the steps: S1, defining a feature parameter set: S11, carrying out demand analysis; s12, determining geometric dimension parameters; s13, obtaining material attribute parameters; s14, construction requirement parameters; s14, information parameters are operated and maintained; s15, standardization and normalization are carried out; s2, establishing a characteristic relation model, including S21, establishing a geometric constraint relation; s22, obtaining a physical constraint relationship; s23, a logical constraint relation is established; s24, managing and maintaining the constraint relationship; s3, designing a parametric modeling tool: S31, analyzing tool requirements; s32, designing a functional module; s33, performing user experience design; s34, tool development and integration; s4, implementing and verifying: S41, making an implementation plan; s42, training and guiding; s43, verifying the pilot item; s44, continuous improvement and optimization are carried out; s5, performing three-dimensional modeling and constraint assembly, namely S51, performing three-dimensional modeling on the component; s52, constraint assembly is carried out; s53, assembling verification is carried out; s6, full life cycle information reuse: S61, model reconstruction and modification; s62, extracting and reusing information; s63, carrying out cross-stage collaboration; s7, continuous iteration and optimization, including S71, data collection and feedback; s72, correcting and upgrading the model; and S73, data analysis and optimization.

Description

Technical Field

[0001] The present invention relates to the technical field of building information modeling, and in particular to a system and method for continuous iteration and full life cycle reuse of a feature-driven parametric information model. Background Art

[0002] Traditional engineering project management relies on drawings, documents and decentralized information systems, which leads to poor information flow, difficulty in updating, and difficulty in adapting to rapidly changing project needs. Especially in large and complex projects, the information isolation between different stages such as design, construction, operation and maintenance is particularly serious, which seriously restricts the overall optimization and collaborative efficiency of the project. Therefore, it is particularly important to develop a system and method that can break down information barriers and realize information integration and reuse throughout the life cycle.

[0003] The information disclosed in this background technology section is only intended to deepen the understanding of the overall background technology of the present invention, and should not be regarded as acknowledging or suggesting in any form that the information constitutes the prior art already known to those skilled in the art. Summary of the invention

[0004] The purpose of the present invention is to provide a system and method for continuous iteration and full life cycle reuse of a parameterized information model based on feature-driven, so as to solve the technical problems existing in the prior art.

[0005] In order to achieve the above object, the present invention adopts the following technical solutions: In a first aspect, the present invention provides a method for continuous iteration and full life cycle reuse of a parameterized information model based on feature-driven, which comprises: S1. Define characteristic parameter set, including: S11. Demand analysis; S12. Geometric size parameters; S13. Material property parameters; S14. Construction requirement parameters; S15. Operation and maintenance information parameters; S15. Standardization and normalization; S2. Establish feature relationship model, including: S21. Geometric constraint relationship; S22. Physical constraint relationship; S23. Logical constraint relationship; S24. Management and maintenance of constraint relationship; S3. Design parametric modeling tools, including: S31. Tool requirements analysis; S32. Functional module design; S33. User experience design; S34. Tool development and integration; S4. Implementation and verification, including: S41. Development of implementation plan; S42. Training and guidance; S43. Pilot project verification; S44. Continuous improvement and optimization; S5, 3D modeling and constrained assembly, including: S51, component 3D modeling; S52, constrained assembly; S53, assembly verification; S6, full life cycle information reuse, including: S61, model reconstruction and modification; S62, information extraction and reuse; S63, cross-stage collaboration; S7. Continuous iteration and optimization, including: S71. Data collection and feedback; S72. Model modification and upgrade; S73. Data analysis and optimization.

[0006] Preferably, step S11 demand analysis includes: Before defining the feature parameter set, a detailed requirements analysis must be performed first; The geometrical dimension parameters in step S12 include: When defining geometric dimension parameters, the comprehensiveness of the parameters should be ensured, including length, width, height, diameter, radius, and angle. At the same time, the correlation between these parameters should also be considered to ensure the coordination and consistency of the design; The material property parameters in step S13 include: Material property parameters include material strength, density, elastic modulus, hardness, wear resistance, corrosion resistance, thermal conductivity, and electrical conductivity. When defining material property parameters, appropriate parameter sets should be selected based on the actual needs of the project, and the material's processability, cost, and environmental friendliness should be considered; Step S14 construction requirement parameters include: The construction requirement parameters involve the installation, connection and commissioning of engineering products. The parameters include installation sequence, connection method, tightening torque, assembly clearance and adjustment range. When defining the construction requirement parameters, the actual situation of the construction site should be fully considered to ensure the feasibility and operability of the design scheme. The operation and maintenance information parameters in step S14 include: Operation and maintenance information parameters include maintenance cycle, maintenance records, fault warning, and spare parts management. When defining operation and maintenance information parameters, a reasonable maintenance plan and maintenance strategy should be formulated in combination with the product's use environment and life cycle; Step S15 of standardization and normalization includes: In the process of defining characteristic parameter sets, attention should be paid to standardization and normalization. By referring to relevant international and domestic standards and specifications, the accuracy and consistency of parameter definitions should be ensured. At the same time, parameter naming rules and coding systems should be established to facilitate parameter identification, management and sharing.

[0007] Preferably, the geometric constraint relationship in step S21 includes: Geometric constraints include parallelism, perpendicularity, tangency, colinearity, coplanarity, and equidistance. When establishing a geometric constraint relationship model, the geometric constraint function in the computer-aided design software should be fully utilized to ensure the accuracy and consistency of the design. The physical constraint relationship in step S22 includes: Physical constraints involve the interaction between components in mechanics, thermodynamics, and electromagnetism. These constraints include load-bearing restrictions, material compatibility, thermal expansion coefficient matching, and electromagnetic shielding. When establishing a physical constraint model, it is necessary to combine relevant knowledge of engineering mechanics and material science to conduct a comprehensive analysis of the component's stress conditions, thermal conductivity, and electromagnetic compatibility. The logical constraint relationship in step S23 includes: Logical constraints include construction sequence, functional dependency, and signal transmission path. When establishing a logical constraint model, the overall process of the project and the logical relationship of each link should be fully considered to ensure the rationality and operability of the design plan. Step S24: Management and maintenance of constraint relationships include: After establishing the feature relationship model, the constraint relationships need to be effectively managed and maintained, including regularly reviewing the correctness, completeness, and consistency of the constraint relationships; adjusting the constraint relationships based on design changes and customer needs; and ensuring the traceability and manageability of the constraint relationships through version control.

[0008] Preferably, step S31 of tool requirement analysis includes: Before designing a parametric modeling tool, a detailed tool requirements analysis is required to provide strong support for tool design by collecting user feedback, analyzing industry trends, and referring to successful cases. Step S32 functional module design includes: The functional module design of the parametric modeling tool revolves around the feature parameter set and feature relationship model, including: Parameter input module: supports users to input feature parameters through graphical interface or script language; Model generation module: automatically generates a 3D model based on input feature parameters and feature relationship models; Model preview and editing module: provides model preview function, allowing users to intuitively view the model effect; supports model editing and modification functions, allowing users to refine and adjust the model; Property update and version control module: supports dynamic update and version control of model properties; when feature parameters change, it can automatically update model properties and save historical version information; it also provides version comparison and rollback functions to cope with design changes or error repairs; Step S33: User experience design includes: interface design, interaction design, and performance optimization; Step S34 tool development and integration includes: developing and integrating tools according to the functional module design and user experience design plan.

[0009] Preferably, step S41 of formulating an implementation plan includes: Before formally implementing the feature-driven parametric modeling framework, a detailed implementation plan should be developed. The plan should include implementation goals, task decomposition, time schedule, personnel division of labor, and resource requirements. Step S42: Training and guidance includes: To ensure that team members can master the use of parametric modeling tools and understand the concept of feature-driven design, corresponding training and guidance are required; Step S43: Pilot project verification includes: Select representative pilot projects for validation; Step S44 continuous improvement and optimization includes: Add new functional modules, optimize the performance of existing functional modules and improve user experience; at the same time, strengthen integration and collaboration with other software systems to build a more complete digital design ecosystem.

[0010] Preferably, step S51 of component three-dimensional modeling includes: Based on parametric features, 3D modeling software or plug-ins are used to automatically complete the 3D modeling of components; Step S52, constraint assembly, includes: According to the constraint relationship between features, automatically or with the assistance of users, complete the assembly of geometric constraints, physical constraints and logical constraints between components; The assembly verification in step S53 includes: verifying the assembly results, and the verification content should include the accuracy of geometric dimensions, conformity of physical properties, and the degree of satisfaction of construction requirements.

[0011] Preferably, step S71 data collection and feedback includes: Collect feedback data during project execution; feedback data should cover all stages and links of the project's entire life cycle to ensure the comprehensiveness and accuracy of the data; Step S72: model modification and upgrade includes: Correct, improve and upgrade the information model based on feedback data; Step S73 data analysis and optimization includes: using big data analysis and machine learning technology to explore the potential value in the information model and provide a scientific basis for project decision-making.

[0012] In a second aspect, the present invention provides a feature-driven parameterized information model continuous iteration and full life cycle reuse system, which adopts the feature-driven parameterized information model continuous iteration and full life cycle reuse method.

[0013] By adopting the above technical solution, the present invention has the following beneficial effects: 1. Technical Effect (1) Information integration and standardization The feature-driven parametric information model (FDPIM) system proposed in this invention realizes the deep integration of multi-stage information such as design, construction, operation and maintenance. Through a unified parametric modeling framework, participants at different stages can work based on the same set of standard models, greatly improving the accuracy and consistency of information. This integration method not only reduces errors and omissions in the information conversion process, but also promotes the smooth transmission of information flow, providing a solid foundation for the full life cycle management of the project.

[0014] (2) Continuous iteration and optimization The FDPIM system supports continuous iterative optimization of the model. During the project, with the continuous input and feedback of new data, the model can be automatically or manually adjusted and optimized to adapt to changes in project requirements. This dynamic adjustment capability allows the model to always maintain a high degree of synchronization with the actual project status, providing more reliable and timely data support for project decision-making.

[0015] (3) Intelligence and automation By introducing advanced algorithms and artificial intelligence technology, the FDPIM system can achieve a certain degree of intelligence and automation. For example, the system can automatically identify and extract key features in design drawings and generate parametric models based on these features; during the operation and maintenance phase, the system can monitor the operating status of the equipment in real time, predict faults based on data analysis results, and take maintenance measures in advance. These intelligent and automated functions not only improve work efficiency, but also reduce the risk of human error.

[0016] 2. Economic Benefits (1)Cost reduction The application of the FDPIM system can significantly reduce project costs. First, by reducing information conversion and duplication of work, the system reduces labor costs; second, by optimizing the design and construction process, the system can reduce material waste and rework, thereby reducing material costs and construction costs; finally, in the operation and maintenance stage, the system reduces equipment downtime and maintenance costs by predicting failures in advance and taking measures.

[0017] (2) Improved efficiency The FDPIM system can significantly improve the efficiency of project management. First, through integrated information management, the system enables project participants to obtain the required information more quickly, thereby accelerating the decision-making process; second, through parametric modeling and automatic optimization functions, the system can reduce design time and construction cycle; finally, in the operation and maintenance stage, the system can timely discover and solve problems through real-time monitoring and data analysis functions, thereby improving equipment utilization and overall operational efficiency.

[0018] (3) Risk reduction The FDPIM system helps project managers better identify and assess potential risks by providing comprehensive, accurate and timely information support. During the design and construction phase, the system can predict potential problems and propose solutions through simulation and emulation functions; during the operation and maintenance phase, the system can predict equipment failures through data analysis functions and take maintenance measures in advance. These functions help reduce project risks and ensure the smooth progress of the project.

[0019] 3. Social Benefits (1) Promoting sustainable development The application of FDPIM system helps to promote the sustainable development of engineering projects. By optimizing the design and construction process, reducing material waste and energy consumption, and improving equipment utilization, the system can reduce the environmental impact of engineering projects and promote the development of green buildings and low-carbon economy. In addition, the system can also help project managers develop more environmentally friendly and sustainable project plans through data analysis and decision support functions.

[0020] (2) Improving industry competitiveness The application of FDPIM system can enhance the competitiveness of the entire industry. By improving the efficiency and quality of project management, reducing costs and risks, the system can enable enterprises to occupy a favorable position in the fierce market competition. At the same time, the promotion and application of the system can also drive the development of related technologies and industries, and promote technological progress and industrial upgrading of the entire industry.

[0021] (3) Promoting collaborative innovation It provides a collaborative work platform for participants at different stages. Through integrated information management and parametric modeling functions, the system enables participants at different stages such as design, construction, and operation and maintenance to communicate and collaborate more conveniently. This collaborative work model helps promote knowledge sharing and technological innovation between different fields, and promotes collaborative innovation and development of the entire industry. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] In order to more clearly illustrate the specific implementation methods of the present invention or the technical solutions in the prior art, the drawings required for use in the specific implementation methods or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some implementation methods of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0023] Figure 1 A flowchart of a method for continuous iteration and full lifecycle reuse of a feature-driven parameterized information model provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0024] The technical solution of the present invention will be described clearly and completely below in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0025] The specific implementation of the present invention is described in detail below in conjunction with the accompanying drawings. It should be understood that the specific implementation described here is only used to illustrate and explain the present invention, and is not used to limit the present invention.

[0026] Combination Figure 1 As shown, this embodiment 1 provides a method for continuous iteration and full life cycle reuse of a parameterized information model based on feature-driven, which includes: 1. Feature-driven parametric modeling framework: S1. Define the feature parameter set, including: S11. Demand Analysis Before defining the feature parameter set, a detailed requirements analysis is required. This step aims to clarify the specific goals, functional requirements, performance standards and potential constraints of the engineering project. Through communication with customers, designers, engineers and other parties, all project-related information is collected and organized to provide a basis for the subsequent feature parameter definition.

[0027] S12, Geometric Dimension Parameters Geometric parameters are one of the most basic and intuitive characteristic parameters in engineering design. They directly determine the shape, size and position of components. When defining geometric parameters, the comprehensiveness of the parameters should be ensured, including but not limited to length, width, height, diameter, radius, angle, etc. At the same time, the correlation between these parameters, such as the transfer relationship of the dimension chain, should also be considered to ensure the coordination and consistency of the design.

[0028] S13. Material property parameters Material property parameters have a crucial impact on the performance of engineering products. These parameters include material strength, density, elastic modulus, hardness, wear resistance, corrosion resistance, thermal conductivity, electrical conductivity, etc. When defining material property parameters, the appropriate parameter set should be selected according to the actual needs of the project, and factors such as material processability, cost and environmental protection should be considered.

[0029] S14. Construction requirements parameters Construction requirement parameters involve the installation, connection and commissioning of engineering products. These parameters include installation sequence, connection method (such as welding, bolt connection, riveting, etc.), tightening torque, assembly clearance, adjustment range, etc. When defining construction requirement parameters, the actual situation of the construction site should be fully considered to ensure the feasibility and operability of the design scheme.

[0030] S14. Operation and maintenance information parameters Operation and maintenance information parameters are of great significance to the long-term operation and maintenance of engineering products. These parameters include maintenance cycle, maintenance records, fault warning, spare parts management, etc. When defining operation and maintenance information parameters, we should combine the product's use environment and life cycle to formulate a reasonable maintenance plan and maintenance strategy to improve the reliability and economy of the product.

[0031] S15. Standardization and normalization In the process of defining characteristic parameter sets, attention should be paid to standardization and normalization. By referring to relevant international and domestic standards and specifications, the accuracy and consistency of parameter definitions should be ensured. At the same time, parameter naming rules and coding systems should be established to facilitate parameter identification, management and sharing.

[0032] S2. Establish a feature relationship model, including: S21. Geometric constraint relationship Geometric constraints refer to the mutual constraints between components in terms of shape, size, and position. These constraints include parallelism, perpendicularity, tangency, colinearity, coplanarity, equidistance, etc. When establishing a geometric constraint model, the geometric constraint function in computer-aided design (CAD) software should be fully utilized to ensure the accuracy and consistency of the design.

[0033] S22. Physical Constraint Relationship Physical constraints involve the interaction between components in mechanics, thermodynamics, and electromagnetics. These constraints include load-bearing restrictions, material compatibility, thermal expansion coefficient matching, and electromagnetic shielding. When establishing a physical constraint model, it is necessary to combine relevant knowledge such as engineering mechanics and material science to conduct a comprehensive analysis of the component's stress conditions, thermal conductivity, and electromagnetic compatibility.

[0034] S23. Logical constraint relationship Logical constraints refer to the interdependencies between components in terms of function, process or timing. These constraints include construction sequence, functional dependency, signal transmission path, etc. When establishing a logical constraint model, the overall process of the project and the logical relationship of each link should be fully considered to ensure the rationality and operability of the design solution.

[0035] S24. Management and maintenance of constraint relationships After establishing the feature relationship model, the constraint relationship needs to be effectively managed and maintained. This includes regularly reviewing the correctness, completeness and consistency of the constraint relationship; adjusting the constraint relationship according to design changes and customer needs; and ensuring the traceability and manageability of the constraint relationship through version control and other means.

[0036] S3. Design parametric modeling tools, including: S31. Tool Requirements Analysis Before designing a parametric modeling tool, a detailed tool requirements analysis is required. This step aims to clarify the requirements for the tool's functions, performance, and user interface. By collecting user feedback, analyzing industry trends, and referring to successful cases, strong support can be provided for tool design.

[0037] S32, Functional Module Design The functional module design of parametric modeling tools should be centered around feature parameter sets and feature relationship models. These functional modules include but are not limited to: Parameter input module: supports users to input characteristic parameters through graphical interface or script language. The interface should be simple, friendly and easy to operate; the script language should be flexible and powerful, supporting the input and calculation of complex parameters.

[0038] Model generation module: Automatically generate a 3D model based on the input feature parameters and feature relationship model. The model should accurately reflect the design intent and constraints; it also supports export and import functions in multiple formats.

[0039] Model preview and editing module: provides model preview function, allowing users to intuitively view the model effect; supports model editing and modification functions, allowing users to refine and adjust the model.

[0040] Property update and version control module: supports dynamic update and version control of model properties. When feature parameters change, it can automatically update model properties and save historical version information; it also provides version comparison and rollback functions to cope with design changes or error repairs.

[0041] S33. User Experience Design User experience design is one of the key factors for the success of parametric modeling tools. During the design process, we should focus on the following aspects: Interface design: The interface should be concise and clear, with a reasonable layout and appropriate color matching; icons and buttons should conform to user habits and be easy to identify; at the same time, provide sufficient help information and prompt information to guide user operations.

[0042] Interaction design: The interaction method should be natural and smooth, with quick response and clear feedback; support multiple input methods (such as mouse, keyboard, touch screen, etc.) to meet the needs of different users; and provide common operations such as undo and redo to improve user efficiency.

[0043] Performance optimization: The tool should have good performance including startup speed, rendering speed and stability; at the same time, it should support multi-tasking and parallel computing to improve processing efficiency.

[0044] S34. Tool development and integration The tool development and integration work is carried out according to the functional module design and user experience design plan. During the development process, attention should be paid to the readability, maintainability and scalability of the code; at the same time, the software development specifications and quality standards should be followed to ensure the quality and stability of the tool. During the integration process, the compatibility with other software systems and the convenience of data exchange should be considered to ensure that the tool can be smoothly integrated into the existing workflow and environment.

[0045] S4. Implementation and verification, including: S41. Implementation plan formulation Before formally implementing the feature-driven parametric modeling framework, a detailed implementation plan needs to be developed. The plan should include implementation goals, task decomposition, time schedule, personnel division of labor, and resource requirements. By developing an implementation plan, the orderly advancement and effective management of the project can be ensured.

[0046] S42. Training and guidance To ensure that team members can master the use of parametric modeling tools and understand the concept of feature-driven design, corresponding training and guidance are required. The training content should include the basic operation of the tool, the use of functional modules, and the explanation of design concepts; at the same time, practical opportunities and case analysis should be provided to help team members better understand and apply the knowledge they have learned.

[0047] S43. Pilot Project Verification Selecting representative pilot projects for verification is one of the important means to evaluate the effectiveness and feasibility of feature-driven parametric modeling frameworks. In the pilot projects, the advantages and characteristics of the framework should be fully demonstrated, including improving design efficiency, ensuring design quality, and promoting design innovation; at the same time, user feedback and opinions should be collected to further optimize and improve the framework.

[0048] S44. Continuous improvement and optimization The feature-driven parametric modeling framework is a system that is constantly evolving and improving. During implementation, we need to continue to pay attention to user needs and technology development trends to continuously improve and optimize the framework. This includes adding new functional modules, optimizing the performance of existing functional modules, and improving user experience; at the same time, we need to strengthen integration and collaboration with other software systems to build a more complete digital design ecosystem.

[0049] S5. 3D modeling and constraint assembly: S51, 3D modeling of components Based on parametric features, 3D modeling software or plug-ins are used to automatically complete the 3D modeling of components.

[0050] Three-dimensional modeling should accurately reflect the component's geometric shape, size, material and other characteristic information, and support users to make fine adjustments to meet project requirements.

[0051] Through 3D modeling, users can intuitively view the appearance and internal structure of components, improving design visualization and communication efficiency.

[0052] S52, Constraint Assembly Based on the constraint relationship between features, the assembly of geometric constraints, physical constraints and logical constraints between components is completed automatically or with the assistance of users.

[0053] Constrained assembly should ensure precise docking and coordination between components to avoid problems such as interference, collision or functional failure.

[0054] During the assembly process, the system should provide real-time feedback and error prompt functions to help users find and solve problems in a timely manner.

[0055] S53, Assembly Verification Verify assembly results to ensure they meet design requirements and engineering specifications.

[0056] The verification content should include but not be limited to the accuracy of geometric dimensions, conformity of physical properties, degree of satisfaction of construction requirements, etc.

[0057] Through assembly verification, the accuracy and reliability of the information model can be ensured, providing strong support for subsequent information reuse and continuous iteration.

[0058] S6. Full life cycle information reuse: S61. Model reconstruction and modification Reconstruct or modify the information model according to changes in project requirements.

[0059] Reconstruction and modification should be performed based on feature parameters and relationship models to ensure the consistency and completeness of information.

[0060] By adjusting feature parameters or adding new features, you can quickly adapt to design changes, construction adjustments, or changes in operation and maintenance requirements.

[0061] At the same time, the system should provide model comparison and difference analysis functions to help users understand the details of model changes.

[0062] S62. Information extraction and reuse Extract required information from the information model and support reuse in different stages such as design, construction, operation and maintenance.

[0063] Information extraction should be based on a unified coding system and attribute aggregation mechanism to ensure the accuracy and completeness of the information.

[0064] The extracted information can be directly used in scenarios such as optimization of design plans, formulation of construction plans, and preparation of operation and maintenance plans.

[0065] Through information reuse, the efficiency and level of project management can be significantly improved.

[0066] S63, cross-stage collaboration Establish a cross-stage, cross-field, and cross-departmental collaborative work platform to promote information sharing and collaborative work.

[0067] The collaborative platform should support multiple users to edit and view information models online at the same time, and achieve seamless connection and real-time communication between different stages such as design, construction, operation and maintenance.

[0068] Through the collaborative work platform, information barriers and departmental boundaries can be broken down, promoting close cooperation and efficient collaboration among project teams.

[0069] S7. Continuous iteration and optimization: S71. Data collection and feedback Collect feedback data during project execution, including design changes, construction records, operation and maintenance data, etc.

[0070] Feedback data should cover all stages and links of the project's entire life cycle to ensure the comprehensiveness and accuracy of the data.

[0071] Through the data collection and feedback mechanism, we can timely understand the actual situation and existing problems of the project, and provide a basis for subsequent optimization and improvement.

[0072] S72, model revision and upgrade The information model is revised, improved and upgraded based on feedback data.

[0073] Revisions may include adjustments to geometric dimensions, updates to material properties, changes to construction requirements, etc.

[0074] Upgrading may involve aspects such as model optimization algorithms, function expansion or performance improvement.

[0075] Through model revision and upgrade, we can ensure that the information model is always consistent with the actual project and continuously improve the accuracy and reliability of the model.

[0076] S73. Data analysis and optimization Utilize big data analysis and machine learning technology to explore the potential value in information models and provide a scientific basis for project decision-making.

[0077] Data analysis should cover data from all stages and links of the project's entire life cycle, and discover the intrinsic connections and patterns between data through methods such as data mining and association analysis.

[0078] Based on the data analysis results, we can optimize the design plan, improve the construction process, and improve the operation and maintenance efficiency, so as to achieve overall optimization of the project and maximize the benefits.

[0079] 1. Technical Effect (1) Information integration and standardization The feature-driven parametric information model (FDPIM) system proposed in this invention realizes the deep integration of multi-stage information such as design, construction, operation and maintenance. Through a unified parametric modeling framework, participants at different stages can work based on the same set of standard models, greatly improving the accuracy and consistency of information. This integration method not only reduces errors and omissions in the information conversion process, but also promotes the smooth transmission of information flow, providing a solid foundation for the full life cycle management of the project.

[0080] (2) Continuous iteration and optimization The FDPIM system supports continuous iterative optimization of the model. During the project, with the continuous input and feedback of new data, the model can be automatically or manually adjusted and optimized to adapt to changes in project requirements. This dynamic adjustment capability allows the model to always maintain a high degree of synchronization with the actual project status, providing more reliable and timely data support for project decision-making.

[0081] (3) Intelligence and automation By introducing advanced algorithms and artificial intelligence technology, the FDPIM system can achieve a certain degree of intelligence and automation. For example, the system can automatically identify and extract key features in design drawings and generate parametric models based on these features; during the operation and maintenance phase, the system can monitor the operating status of the equipment in real time, predict faults based on data analysis results, and take maintenance measures in advance. These intelligent and automated functions not only improve work efficiency, but also reduce the risk of human error.

[0082] 2. Economic Benefits (1)Cost reduction The application of the FDPIM system can significantly reduce project costs. First, by reducing information conversion and duplication of work, the system reduces labor costs; second, by optimizing the design and construction process, the system can reduce material waste and rework, thereby reducing material costs and construction costs; finally, in the operation and maintenance stage, the system reduces equipment downtime and maintenance costs by predicting failures in advance and taking measures.

[0083] (2) Improved efficiency The FDPIM system can significantly improve the efficiency of project management. First, through integrated information management, the system enables project participants to obtain the required information more quickly, thereby accelerating the decision-making process; second, through parametric modeling and automatic optimization functions, the system can reduce design time and construction cycle; finally, in the operation and maintenance stage, the system can timely discover and solve problems through real-time monitoring and data analysis functions, thereby improving equipment utilization and overall operational efficiency.

[0084] (3) Risk reduction The FDPIM system helps project managers better identify and assess potential risks by providing comprehensive, accurate and timely information support. During the design and construction phase, the system can predict potential problems and propose solutions through simulation and emulation functions; during the operation and maintenance phase, the system can predict equipment failures through data analysis functions and take maintenance measures in advance. These functions help reduce project risks and ensure the smooth progress of the project.

[0085] 3. Social Benefits (1) Promoting sustainable development The application of FDPIM system helps to promote the sustainable development of engineering projects. By optimizing the design and construction process, reducing material waste and energy consumption, and improving equipment utilization, the system can reduce the environmental impact of engineering projects and promote the development of green buildings and low-carbon economy. In addition, the system can also help project managers develop more environmentally friendly and sustainable project plans through data analysis and decision support functions.

[0086] (2) Improving industry competitiveness The application of FDPIM system can enhance the competitiveness of the entire industry. By improving the efficiency and quality of project management, reducing costs and risks, the system can enable enterprises to occupy a favorable position in the fierce market competition. At the same time, the promotion and application of the system can also drive the development of related technologies and industries, and promote technological progress and industrial upgrading of the entire industry.

[0087] (3) Promoting collaborative innovation It provides a collaborative work platform for participants at different stages. Through integrated information management and parametric modeling functions, the system enables participants at different stages such as design, construction, and operation and maintenance to communicate and collaborate more conveniently. This collaborative work model helps promote knowledge sharing and technological innovation between different fields, and promotes collaborative innovation and development of the entire industry.

[0088] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or replace some or all of the technical features therein with equivalents. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for continuous iteration and full life cycle reuse of parameterized information models based on feature-driven, characterized in that: include: S1. Define characteristic parameter set, including: S11. Demand analysis; S12. Geometric size parameters; S13. Material property parameters; S14. Construction requirement parameters; S15. Operation and maintenance information parameters; S15. Standardization and normalization; S2. Establish feature relationship model, including: S21. Geometric constraint relationship; S22. Physical constraint relationship; S23. Logical constraint relationship; S24. Management and maintenance of constraint relationship; S3. Design parametric modeling tools, including: S31. Tool requirements analysis; S32. Functional module design; S33. User experience design; S34. Tool development and integration; S4. Implementation and verification, including: S41. Development of implementation plan; S42. Training and guidance; S43. Pilot project verification; S44. Continuous improvement and optimization; S5, 3D modeling and constrained assembly, including: S51, component 3D modeling; S52, constrained assembly; S53, assembly verification; S6, full life cycle information reuse, including: S61, model reconstruction and modification; S62, information extraction and reuse; S63, cross-stage collaboration; S7. Continuous iteration and optimization, including: S71. Data collection and feedback; S72. Model modification and upgrade; S73. Data analysis and optimization.

2. The method for continuous iteration and full life cycle reuse of parameterized information models based on feature-driven methods according to claim 1, characterized in that: Step S11 demand analysis includes: Before defining the feature parameter set, a detailed requirements analysis must be performed first; The geometrical dimension parameters in step S12 include: When defining geometric dimension parameters, the comprehensiveness of the parameters should be ensured, including length, width, height, diameter, radius, and angle. At the same time, the correlation between these parameters should also be considered to ensure the coordination and consistency of the design; The material property parameters in step S13 include: Material property parameters include material strength, density, elastic modulus, hardness, wear resistance, corrosion resistance, thermal conductivity, and electrical conductivity. When defining material property parameters, appropriate parameter sets should be selected based on the actual needs of the project, and the material's processability, cost, and environmental friendliness should be considered; Step S14 construction requirement parameters include: The construction requirement parameters involve the installation, connection and commissioning of engineering products. The parameters include installation sequence, connection method, tightening torque, assembly clearance and adjustment range. When defining the construction requirement parameters, the actual situation of the construction site should be fully considered to ensure the feasibility and operability of the design scheme. The operation and maintenance information parameters in step S14 include: Operation and maintenance information parameters include maintenance cycle, maintenance records, fault warning, and spare parts management. When defining operation and maintenance information parameters, a reasonable maintenance plan and maintenance strategy should be formulated in combination with the product's use environment and life cycle; Step S15 of standardization and normalization includes: In the process of defining characteristic parameter sets, attention should be paid to standardization and normalization. By referring to relevant international and domestic standards and specifications, the accuracy and consistency of parameter definitions should be ensured. At the same time, parameter naming rules and coding systems should be established to facilitate parameter identification, management and sharing.

3. The method for continuous iteration and full life cycle reuse of parameterized information models based on feature-driven according to claim 1, characterized in that: Step S21 geometric constraint relationships include: Geometric constraints include parallelism, perpendicularity, tangency, colinearity, coplanarity, and equidistance. When establishing a geometric constraint relationship model, the geometric constraint function in the computer-aided design software should be fully utilized to ensure the accuracy and consistency of the design. The physical constraint relationship in step S22 includes: Physical constraints involve the interaction between components in mechanics, thermodynamics, and electromagnetism. These constraints include load-bearing restrictions, material compatibility, thermal expansion coefficient matching, and electromagnetic shielding. When establishing a physical constraint model, it is necessary to combine relevant knowledge of engineering mechanics and material science to conduct a comprehensive analysis of the component's stress conditions, thermal conductivity, and electromagnetic compatibility. The logical constraint relationship in step S23 includes: Logical constraints include construction sequence, functional dependency, and signal transmission path. When establishing a logical constraint model, the overall process of the project and the logical relationship of each link should be fully considered to ensure the rationality and operability of the design plan. Step S24: Management and maintenance of constraint relationships include: After establishing the feature relationship model, the constraint relationships need to be effectively managed and maintained, including regularly reviewing the correctness, completeness, and consistency of the constraint relationships; adjusting the constraint relationships based on design changes and customer needs; and ensuring the traceability and manageability of the constraint relationships through version control.

4. The method for continuous iteration and full life cycle reuse of parameterized information models based on feature-driven according to claim 1, characterized in that: Step S31 tool requirement analysis includes: Before designing a parametric modeling tool, a detailed tool requirements analysis is required to provide strong support for tool design by collecting user feedback, analyzing industry trends, and referring to successful cases. Step S32 functional module design includes: The functional module design of the parametric modeling tool revolves around the feature parameter set and feature relationship model, including: Parameter input module: supports users to input feature parameters through graphical interface or script language; Model generation module: automatically generates a 3D model based on input feature parameters and feature relationship models; Model preview and editing module: provides model preview function, allowing users to intuitively view the model effect; supports model editing and modification functions, allowing users to refine and adjust the model; Property update and version control module: supports dynamic update and version control of model properties; when feature parameters change, it can automatically update model properties and save historical version information; it also provides version comparison and rollback functions to cope with design changes or error repairs; Step S33: User experience design includes: interface design, interaction design, and performance optimization; Step S34 tool development and integration includes: developing and integrating tools according to the functional module design and user experience design plan.

5. The method for continuous iteration and full life cycle reuse of parameterized information models based on feature-driven methods according to claim 1, characterized in that: Step S41: formulating the implementation plan includes: Before formally implementing the feature-driven parametric modeling framework, a detailed implementation plan should be developed. The plan should include implementation goals, task decomposition, time schedule, personnel division of labor, and resource requirements. Step S42: Training and guidance includes: To ensure that team members can master the use of parametric modeling tools and understand the concept of feature-driven design, corresponding training and guidance are required; Step S43: Pilot project verification includes: Select representative pilot projects for validation; Step S44 continuous improvement and optimization includes: Add new functional modules, optimize the performance of existing functional modules and improve user experience; at the same time, strengthen integration and collaboration with other software systems to build a more complete digital design ecosystem.

6. The method for continuous iteration and full life cycle reuse of a feature-driven parameterized information model according to claim 1, characterized in that: Step S51: component three-dimensional modeling includes: Based on parametric features, 3D modeling software or plug-ins are used to automatically complete the 3D modeling of components; Step S52, constraint assembly, includes: According to the constraint relationship between features, automatically or with the assistance of users, complete the assembly of geometric constraints, physical constraints and logical constraints between components; The assembly verification in step S53 includes: verifying the assembly results, and the verification content should include the accuracy of geometric dimensions, conformity of physical properties, and the degree of satisfaction of construction requirements.

7. The method for continuous iteration and full life cycle reuse of parameterized information models based on feature-driven methods according to claim 1, characterized in that: Step S71 data collection and feedback includes: Collect feedback data during project execution; feedback data should cover all stages and links of the project's entire life cycle to ensure the comprehensiveness and accuracy of the data; Step S72: model modification and upgrade includes: Correct, improve and upgrade the information model based on feedback data; Step S73 data analysis and optimization includes: using big data analysis and machine learning technology to explore the potential value in the information model and provide a scientific basis for project decision-making.

8. A feature-driven parameterized information model continuous iteration and full life cycle reuse system, characterized in that: A method for continuous iteration and full life cycle reuse of a feature-driven parameterized information model as described in any one of claims 1 to 7 is adopted.

Images