BIM delivery self-examination method based on Revit plug-in

Abstract

The invention relates to the field of building information model delivery, and particularly discloses a BIM delivery self-examination method based on a Revit plug-in, and the method comprises the steps: S1, extracting core attribute data in a model component; s2, exporting the model as a. Ifc format file; s3, establishing a matching mechanism of dictionary values and delivery specifications; s4, executing component logic normative verification of geometric legality, topological relation consistency and field dependency legality; s5, carrying out area conformity detection, calculating room and building areas, and comparing a deviation rate with a platform standard area rule through a simulation algorithm; s6, performing three-dimensional visualization feedback, visually presenting a detection result in the three-dimensional model, and providing a problem component ID; and S7, exporting a self-examination problem report and an operation log. According to the method, attribute integrity verification, geometric structure detection, standard rule examination and interactive three-dimensional feedback are realized, a problem report and a log can be automatically generated, and the model delivery quality, efficiency and passing rate are remarkably improved.

Description

Technical Field

[0001] This invention relates to the field of building information modeling (BIM) delivery technology, specifically a self-audit method for BIM delivery based on a Revit plugin. Background Technology

[0002] As some regions fully promote BIM technology in urban construction, the standardization, completeness, and compliance of models during the delivery phase have become crucial aspects of building approval, construction management, and completion filing. Especially in actual projects, differences in understanding of model component information, spatial division, component attributes, and industry standards among different entities lead to high delivery failure rates and significant rework.

[0003] Currently, the industry mainly relies on manual verification of models before delivery, which is time-consuming, labor-intensive, prone to omissions, and difficult to standardize. Although some inspection software has some rule review capabilities, it cannot be deeply integrated with modeling software and lacks efficient interactivity, repair capabilities, and real-time feedback capabilities.

[0004] Therefore, we have invented a delivery method that can be deeply integrated into the Revit modeling platform and has the capabilities of self-review, error correction, feedback and summary. This method effectively solves the pain points of manual verification, which is time-consuming, labor-intensive, prone to omissions and difficult to unify standards. At the same time, it makes up for the shortcomings of existing inspection software and modeling platform, such as low integration, insufficient interactive repair and real-time feedback. Summary of the Invention

[0005] To address the aforementioned problems in the prior art, this invention provides a BIM delivery self-review method based on a Revit plugin, effectively solving the difficulties of inefficient and error-prone manual verification, insufficient software integration, and high delivery failure rate, thereby effectively improving the quality, efficiency, and pass rate of model delivery.

[0006] To achieve the above objectives, this invention proposes a BIM delivery self-review method based on a Revit plugin, comprising: S1. Extract the core attribute data from the model components; S2. Export the model as an .ifc format file; S3. Establish a matching mechanism between dictionary values ​​and delivery specifications. Based on the preset dictionary table, select the corresponding rule file to detect missing attribute items, incorrect attribute values, missing geographic information, incorrect color settings, and non-standard model structure. S4. Perform component logic standardization checks for geometric validity, topological relationship consistency, and field dependency validity; S5. Perform area compliance testing, calculate the room and building areas, and compare the deviation rate with the platform's standard area rules through simulation algorithms; S6. Provide 3D visualization feedback, visualize the detection results in the 3D model, and provide the ID of the problematic component; S7. Export self-audit problem report and operation log.

[0007] Preferably, in S1, the core attribute data includes building number, room function, room number, floor number, main function category, component type, material, fire resistance rating, and entrance / exit direction.

[0008] Preferably, in S2, when exporting .ifc format files, efficient filtering is performed based on model rules to remove unnecessary information.

[0009] Preferably, in S3, the dictionary value comparison uses a configurable rule dictionary, supports plugin embedding, Excel import or database call, and allows users to edit extended rule files.

[0010] Preferably, in S4, the geometric compliance check includes whether the component exceeds the boundary, whether the height is reasonable, whether the number of vertices exceeds the limit, component interpenetration detection, and component size legality analysis.

[0011] Preferably, in S4, the topology consistency check includes determining whether there are structural logic problems such as components not being closed, overlapping, misaligned fire wall sleeves, or fire extinguisher boxes not fitting the wall.

[0012] Preferably, in S5, the specific steps of the area conformity detection are as follows: extract the calculation area through the room boundary recognition algorithm, detect whether the space that can be included in the area has drawn room boundaries and labels, identify empty rooms, duplicate rooms, rooms without numbers or missing labels, and compare the model building area field value.

[0013] Preferably, in S6, 3D visualization feedback is used to highlight problematic components. Problematic components are highlighted in red, orange, and yellow according to their severity. The error list is linked with the model, and clicking on a list item will automatically focus on the corresponding component.

[0014] Preferably, in S6, the 3D visualization feedback also provides a quick error correction entry, supports automatic attribute filling, naming format repair, component replacement or deletion operations, and allows marking issues with statuses such as "ignore", "manually handle", and "pending review".

[0015] Preferably, in S7, the self-audit problem report supports the export of detailed inspection reports. The self-audit problem report includes component attribute missing statistics, dictionary value deviation analysis, model anomaly description, area deviation analysis, operation log records each self-audit result and repair action, and supports secondary self-audit, version comparison and historical record rollback.

[0016] Therefore, this invention proposes a BIM delivery self-review method based on a Revit plugin, which has the following advantages: (1) Significantly improves review efficiency and accuracy, replacing traditional manual verification. By automatically extracting attributes, comparing dictionary values, and verifying logic specifications, it reduces time consumption and omissions, and lowers the probability of delivery failure and rework.

[0017] (2) Achieve deep integration and interactive closed loop. The plugin is embedded in the Revit platform, supporting three-dimensional visualization feedback (highlighting and focusing on problematic components) and rapid error correction (automatic attribute filling, etc.), allowing users to complete the entire process of "detection-location-repair" within the modeling environment.

[0018] (3) It facilitates management and traceability, automatically generates reports and operation logs with detailed analysis, supports secondary self-review, version comparison and rollback, which is conducive to project approval and subsequent traceability.

[0019] The technical solution of the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. Attached Figure Description

[0020] Figure 1 This is a flowchart of a BIM delivery self-review method based on a Revit plugin, according to the present invention. Figure 2 This is an example of a self-review method for BIM delivery based on a Revit plugin, as described in the present invention, showing the review results of a conference reception building project. Figure 3 This is an example of a self-review method for BIM delivery based on a Revit plugin, as described in the present invention, showing the review results of a VIP reception building project. Detailed Implementation

[0021] To make the technical solutions, advantages, and objectives of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below. The described embodiments are only some, not all, of the embodiments of the present invention. All other embodiments obtained by those skilled in the art based on the described embodiments of the present invention without creative effort are within the protection scope of this application.

[0022] Unless otherwise defined, the technical or scientific terms used in this invention shall have the ordinary meaning as understood by one of ordinary skill in the art to which this invention pertains.

[0023] like Figure 1 As shown, the present invention provides a BIM delivery self-review method based on a Revit plugin, comprising: S1. Extract the core attribute data from the model components. The core attribute data includes building number, room function, room number, floor number, main function category, component type, material, fire resistance rating, and entrance / exit direction. S2. Export the model as an .ifc format file. Specifically, based on the model rules, an efficient filtering mechanism is used to remove unnecessary information and convert the delivered model into an .ifc file. S3. Establish a matching mechanism between dictionary values ​​and delivery specifications. Select the corresponding rule file based on the preset dictionary table to detect missing attribute items, incorrect attribute values, missing geographic information, incorrect color settings, and non-standard model structure. The dictionary value comparison uses a configurable rule dictionary and supports plugin embedding, Excel import, or database call. It also allows users to edit extended rule files. The specific steps of the test are as follows: Define "mandatory attribute set": a set of attributes and field types that must exist within the system; Load "Dictionary Value Table": The plugin embeds or imports the standard value range corresponding to each attribute (such as function category classification, floor numbering rules, etc.). Matching and Analysis: For each component, compare the parameters item by item to see if they exist, if they are empty, and if they are within the allowed dictionary value range; Self-audit feedback: Generate an attribute completeness statistics table, with missing items marked in red and items that pass in green; S4. Perform component logic standardization checks for geometric validity, topological relationship consistency, and field dependency validity; Geometric compliance checks include checking whether components exceed boundaries, whether their height is reasonable, whether the number of vertices exceeds limits, component interpenetration detection, and component size legality analysis. Topological consistency verification includes determining whether there are structural logic problems such as components not being closed, overlapping, misaligned fire wall sleeves, and fire extinguisher boxes not fitting properly against the wall. S5. Perform area compliance testing, calculate the room and building areas, and compare the deviation rate with the platform's standard area rules through simulation algorithms; The specific steps of the area conformity detection are as follows: extract the calculation area through the room boundary recognition algorithm, detect whether the space that can be included in the area has drawn room boundaries and labels, identify empty rooms, duplicate rooms, rooms without numbers or missing labels, and compare the values ​​of the building area field in the model.

[0024] S6. Provide 3D visualization feedback, visualize the detection results in the 3D model, and provide the ID of the problematic component; The system uses 3D visualization feedback to highlight problematic components, which are then highlighted in red, orange, and yellow according to their severity. It supports linkage between the error list and the model, and clicking on a list item will automatically focus on the corresponding component.

[0025] The 3D visualization feedback also provides a quick error correction entry, supports automatic attribute filling, naming format correction, component replacement or deletion operations, and allows marking issues with statuses such as "ignore", "manually handle", and "pending review".

[0026] S7. Export self-audit problem report and operation log.

[0027] The self-audit issue report supports exporting detailed inspection reports, which include component attribute missing statistics, dictionary value deviation analysis, model anomaly descriptions, and area deviation analysis. The operation log records the results and repair actions of each self-audit, and supports secondary self-audit, version comparison, and historical rollback.

[0028] Example 1 The following is the entire process of conducting a pre-delivery self-review of the Revit model for a conference reception building project using a Revit plugin: First, open the Revit model file of the target project and start the installed IFC conversion plugin. The plugin will automatically traverse all components of the specified category in the model (such as walls, columns, beams, slabs, doors, windows, rooms, etc.) in the background and extract the core attribute data of each component. These attributes include, but are not limited to, family name, component name, component category, professional category, etc. The extracted data is used for subsequent verification.

[0029] Then, the model review platform is launched, and a .ifc format file of a conference reception building is imported. After the model is imported, the pre-configured review rules are loaded and the model check is run. The review platform will perform automated verification based on the extracted core attribute data and review rules. All non-compliance items (problematic components) found during the verification process and their specific reasons for violations (such as "incorrect object naming", "incorrect attribute value", etc.) are recorded in detail and associated with the component's unique ID.

[0030] The review platform displays all detected issues in real-time in the 3D view; clicking on a problematic component will highlight it in the model. The platform's sidebar provides a "Model Quality Inspection" section, listing the IDs and descriptions of all problematic components. Clicking on an item in the list will automatically zoom in and highlight the corresponding component.

[0031] After reviewing the visualization results, a report is generated via the platform interface, automatically summarizing all inspection results and generating a structured self-review issue report. The report includes: basic model information, basic rule information, a summary of inspection results, and the inspection results themselves. The review identified a total of 167,687 inspection items for a certain conference reception building project, with a pass rate of 92.59% and a failure rate of 7.41%. The review results are as follows: Figure 2 As shown.

[0032] Finally, based on the review report, by accurately locating the problematic components, the Revit model of a certain conference reception building project was modified item by item, which significantly improved the quality, efficiency and traceability of model delivery and reduced delivery risks.

[0033] Example 2 Following the above procedures, a pre-delivery review was conducted on the BIM model of a VIP reception building project in Xiong'an New Area. A total of 44,421 components were reviewed, with a pass rate of 89.42% and a failure rate of 10.58%. Modifications were made to the model based on the review report, significantly improving the modification speed and facilitating the project's successful BIM delivery review. The review results are as follows: Figure 3 As shown.

[0034] Therefore, this invention provides a BIM delivery self-review method based on a Revit plugin. By extracting component attributes, comparing dictionary values, analyzing construction logic, and verifying area calculations, it completes a comprehensive self-review of the BIM model before delivery. This method achieves attribute integrity verification, geometric structure detection, review of specifications and rules, and interactive 3D feedback. It can also automatically generate problem reports and logs, helping users achieve a self-closing, efficient, and compliant model delivery preparation process within the modeling platform. It has broad engineering applicability and promotional value.

[0035] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit them. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the technical solutions of the present invention, and these modifications or equivalent substitutions cannot cause the modified technical solutions to deviate from the spirit and scope of the technical solutions of the present invention.

Claims

1. A BIM delivery self-review method based on a Revit plugin, characterized in that, include: S1. Extract the core attribute data from the model components; S2. Export the model as an .ifc format file; S3. Establish a matching mechanism between dictionary values ​​and delivery specifications. Based on the preset dictionary table, select the corresponding rule file to detect missing attribute items, incorrect attribute values, missing geographic information, incorrect color settings, and non-standard model structure. S4. Perform component logic standardization checks for geometric validity, topological relationship consistency, and field dependency validity; S5. Perform area compliance testing, calculate the room and building areas, and compare the deviation rate with the platform's standard area rules through simulation algorithms; S6. Provide 3D visualization feedback, visualize the detection results in the 3D model, and provide the ID of the problematic component; S7. Export self-audit problem report and operation log.

2. The BIM delivery self-review method based on a Revit plugin according to claim 1, characterized in that, In S1, the core attribute data includes building number, room function, room number, floor number, main function category, component type, material, fire resistance rating, and entrance / exit direction.

3. The BIM delivery self-review method based on a Revit plugin according to claim 1, characterized in that, In S2, when exporting .ifc format files, efficient filtering is performed based on model rules to remove unnecessary information.

4. The BIM delivery self-review method based on a Revit plugin according to claim 1, characterized in that, In S3, the dictionary value comparison uses a configurable rule dictionary and supports plugin embedding, Excel import or database call, and allows users to edit extended rule files.

5. A BIM delivery self-review method based on a Revit plugin according to claim 1, characterized in that, In S4, the geometric compliance check includes whether the component exceeds the boundary, whether the height is reasonable, whether the number of vertices exceeds the limit, component interpenetration detection, and component size legality analysis.

6. A BIM delivery self-review method based on a Revit plugin according to claim 1, characterized in that, In S4, the topology consistency check includes determining whether there are structural logic problems such as components not being closed, overlapping, misaligned fire wall sleeves, and fire extinguisher boxes not fitting the wall.

7. A BIM delivery self-review method based on a Revit plugin according to claim 1, characterized in that, In S5, the specific steps of the area conformity detection are to extract the calculation area through the room boundary recognition algorithm, detect whether the space that can be included in the area has drawn room boundaries and labels, identify empty rooms, duplicate rooms, rooms without numbers or missing labels, and compare the model building area field value.

8. A BIM delivery self-review method based on a Revit plugin according to claim 1, characterized in that, In S6, 3D visualization feedback is used to highlight problematic components. Problematic components are highlighted in red, orange, and yellow according to their severity. The error list is linked with the model, and clicking on a list item will automatically focus on the corresponding component.

9. A BIM delivery self-review method based on a Revit plugin according to claim 1, characterized in that, In S6, the 3D visualization feedback also provides a quick error correction entry, supports automatic attribute filling, naming format repair, component replacement or deletion operations, and allows marking issues with statuses such as "ignore", "manually handle", and "pending review".

10. A BIM delivery self-inspection method based on a Revit plugin according to claim 1, characterized in that, In S7, the self-audit issue report supports the export of detailed inspection reports. The self-audit issue report includes component attribute missing statistics, dictionary value deviation analysis, model anomaly description, area deviation analysis, operation log records the results of each self-audit and repair actions, and supports secondary self-audit, version comparison and historical record rollback.

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