BIM intelligent partitioning method based on data source identification

Abstract

The present invention discloses a BIM intelligent partitioning method based on data source identification, comprising the following steps: 1. creating corresponding partitions according to the project structure, and defining the partition names, data sources, and matching values; 2. parsing the corresponding component data sources in the BIM model to be processed according to the defined data sources; 3. comparing the defined matching values ​​with the corresponding values ​​in each component data source to identify the partition to which each component data source belongs; 4. checking the accuracy of the visual positioning through the BIM software environment; 5. manually modifying the partition to which each component data source with errors belongs based on the accuracy verification results of each component data source; 6. writing the partition information of each component data source into the component attributes of the corresponding BIM model. The present invention realizes a method for intelligently partitioning engineering projects in a BIM model, and can accurately and efficiently intelligently partition components in large-scale engineering projects.

Description

Technical Field

[0001] The present invention relates to the technical field of computer-aided design, and in particular to a BIM intelligent zoning method based on data source identification. Background Art

[0002] With the widespread application of BIM (Building Information Modeling) technology in the engineering field, the traditional division of engineering projects has gradually become unable to meet the needs of design and construction division. The previous method of dividing plane areas and facade elevations in CAD plan drawings and elevation drawings cannot be fully applied in the three-dimensional BIM model space and needs to be replaced by a more advanced space partitioning method.

[0003] While the current mainstream BIM software, Revit, offers zoning methods such as room, space, and building area, these are primarily used for its own calculation functions. Drawing is cumbersome, and it's difficult to assign specific attributes to components that span multiple areas, failing to fully resolve the issue. This creates significant inconvenience in subsequent project design, construction, and quantity calculations.

[0004] Therefore, how to efficiently and accurately classify the attributes and partitions of components by identifying the characteristics of the attributes in the components has become a technical problem that those skilled in the art urgently need to solve. Summary of the Invention

[0005] In view of the above-mentioned defects of the prior art, the present invention provides a BIM intelligent partitioning method based on data source identification, the purpose of which is to achieve automatic, efficient and intelligent partition identification by creating partitions that conform to the project structure and parsing the component data sources in the BIM model.

[0006] To achieve the above objectives, the present invention discloses a BIM intelligent zoning method based on data source identification, comprising the following steps:

[0007] Step 1: In the BIM software environment, create corresponding partitions according to the project structure, and define the partition name, data source and matching value for each partition;

[0008] Step 2: parsing the corresponding component data source in the BIM model to be processed according to the data source defined when each partition is created;

[0009] Step 3: Compare the matching value defined when each partition is created with the corresponding value in each component data source to identify the partition to which each component data source belongs;

[0010] Step 4: Verify the accuracy of each component data source under each partition by checking the BIM model through visual positioning in the BIM software environment;

[0011] Step 5: manually modify the partition to which each component data source having an error belongs based on the accuracy verification result of each component data source;

[0012] Step 6: Write the partition information of each component data source finally determined into the component attributes of the corresponding BIM model.

[0013] Preferably, step 1 comprises the following steps:

[0014] Step 1.1, defining partition names, specifically: dividing the structure of each partition according to the project structure, and defining the corresponding partition names;

[0015] Step 1.2, defining the data source, specifically: according to the structural characteristics of each partition, when defining and identifying the corresponding partition, the characteristics of the corresponding component data source;

[0016] Step 1.3, defining a matching value, specifically: defining the matching value of each feature according to the structural characteristics of each partition.

[0017] Preferably, in step 2, the component data source includes a visible data source in the BIM model and a hidden data source that can be called through an API in the BIM software environment.

[0018] Preferably, in step 4, the visual positioning back-check in the BIM software environment has the functions of 3D model sectioning and isolation of irrelevant components.

[0019] Preferably, in step 5, when manually modifying the partition to which each component data source having errors belongs, if all existing partitions do not meet the requirements, a new partition that meets the requirements is created.

[0020] Preferably, in step 6, in the process of writing the partition information into the component attributes of the corresponding BIM model, part or all of the partition information is written into the component attributes of the BIM model as hidden attributes.

[0021] Beneficial effects of the present invention:

[0022] The present invention realizes a method for intelligent partitioning of engineering projects in the BIM model. By creating partitions and parsing the component data source, and matching the matching values ​​defined according to the characteristics of the partition structure, tens of thousands of components in a large-scale engineering project can be accurately and efficiently partitioned intelligently, solving the problems of difficult and inefficient manual identification and extremely cumbersome modification.

[0023] This invention not only analyzes the visible data sources of components, but also analyzes the hidden data sources of components through APIs, obtaining a wide range of invisible information to help improve recognition accuracy. Furthermore, when modifying a partition, it automatically creates a new partition, reducing the need for repeated partition creation and effectively improving recognition efficiency.

[0024] The concept, specific structure and technical effects of the present invention will be further described below in conjunction with the accompanying drawings to fully understand the purpose, characteristics and effects of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] Figure 1 FIG. 1 shows an execution flow chart of an embodiment of the present invention. DETAILED DESCRIPTION

[0026] Example 1

[0027] like Figure 1 As shown, a BIM intelligent zoning method based on data source identification is characterized by comprising the following steps:

[0028] Step 1: In the BIM software environment, create corresponding partitions according to the project structure, and define the partition name, data source and matching value for each partition;

[0029] Step 2: According to the data source defined when each partition is created, the corresponding component data source in the BIM model to be processed is parsed;

[0030] Step 3: Compare the matching value defined when each partition is created with the corresponding value in each component data source to identify the partition to which each component data source belongs;

[0031] Step 4: Use the visual positioning of the BIM software environment to check the BIM model to verify the accuracy of the data source of each component in each partition;

[0032] Step 5: Based on the accuracy verification results of each component data source, manually modify the partition to which each component data source with errors belongs;

[0033] Step 6: Write the partition information of each component data source finally determined into the component attributes of the corresponding BIM model.

[0034] The principles of the present invention are as follows:

[0035] Through the study of development documents such as "Revit API 2017-2021" and ongoing projects, we can summarize the common rules of BIM component data sources and engineering project partition structures. The difference problems can be solved by openly defining partitions, data sources and matching values.

[0036] In practical applications, manually drawing partitions and manually assigning component partitions is a common method. This is inefficient, inaccurate, and cannot guarantee the rigor and rationality of partitioning. The greatest breakthrough of BIM technology is the association of project information with 3D models. Using data source identification for partitioning is an innovative method that leverages the far superior efficiency of computer recognition over manual work and ensures the consistency of the partitioning method with the project partition structure characteristics in the BIM information.

[0037] In some embodiments, step 1 includes the following steps:

[0038] Step 1.1, define the partition name, specifically: divide the structure of each partition according to the project structure, and define the corresponding partition name;

[0039] Step 1.2: Define the data source. Specifically, based on the structural characteristics of each partition, define and identify the corresponding partition and the characteristics of the corresponding component data source.

[0040] Step 1.3: Define the matching value. Specifically, define the matching value of each feature according to the structural characteristics of each partition.

[0041] In some embodiments, in step 2, the component data source includes a visible data source in the BIM model and a hidden data source that can be called through an API in the BIM software environment.

[0042] In certain embodiments, in step 4, the visual positioning backcheck in the BIM software environment has the functions of 3D model sectioning and isolation of irrelevant components.

[0043] In practical applications, the visual positioning reverse query with 3D model sectioning and irrelevant component isolation functions can effectively verify the accuracy of geometric dimension calculations and the consistency of parameter dimensions with BIM component data.

[0044] In some embodiments, in step 5, when manually modifying the partition to which each component data source with errors belongs, if all existing partitions do not meet the requirements, a new partition that meets the requirements is created.

[0045] In some embodiments, in step 6, in the process of writing the partition information into the component attributes of the corresponding BIM model, part or all of the partition information is written into the component attributes of the BIM model as hidden attributes.

[0046] Example 2

[0047] Taking the intelligent partition identification of the BIM model of a subway project in the main structure engineering of a subway platform as an example, Figure 1 The execution process shown in the figure has the following steps:

[0048] Step 1: Create partitions. Create corresponding partitions according to the structure of the subway platform, define the partition name, define the data source, and define the matching value;

[0049] Step 1 includes the following steps:

[0050] Step 1.1, define the zone name, define all 12 zones of the platform, including platform, station hall, entrance and exit 1, wind shelter, etc.;

[0051] Step 1.2: Define the data source. Define the eight data sources that need to be parsed for this station, including work sets, elevations, grids, families, types, etc.

[0052] Step 1.3: Define the matching value, which is the matching value corresponding to the platform elevation data source. The elevation value is between -18m and -12m.

[0053] Step 2: Analyze the component data source, including 12,800 components of the entire BIM model and their 8 data sources, including worksets, elevations, grids, families, types, etc.

[0054] Step 3: Identify the zones and identify 5,600 components with elevations within the platform range of -18m to -12m.

[0055] Step 4: Reverse check of the partition results. Using the visual positioning reverse check model, we found that 20 components were not in the created partitions and belonged to the partition where the subway section and the subway platform were connected.

[0056] Step 5: Manually modify the partition, assign the newly discovered 20 components to the Unicom partition, and automatically create a new partition Unicom;

[0057] Step 6: Save the partition information and write the finalized partition information into all corresponding component attributes.

[0058] The above describes in detail the preferred embodiments of the present invention. It should be understood that those skilled in the art can make numerous modifications and variations based on the concepts of the present invention without inventive effort. Therefore, any technical solutions that can be derived by those skilled in the art through logical analysis, reasoning, or limited experimentation based on the concepts of the present invention and the prior art should be within the scope of protection defined by the claims.

Claims

1. The BIM intelligent partitioning method based on data source identification is characterized by: The following steps are involved: Step 1: In the BIM software environment, create corresponding partitions according to the project structure, and define the partition name, data source and matching value for each partition; Step 1.1, defining partition names, specifically: dividing the structure of each partition according to the project structure, and defining the corresponding partition names; Step 1.2, defining the data source, specifically: according to the structural characteristics of each partition, when defining and identifying the corresponding partition, the characteristics of the corresponding component data source; Step 1.3, defining a matching value, specifically: defining the matching value of each feature according to the structural characteristics of each partition; Step 2: parsing the corresponding component data source in the BIM model to be processed according to the data source defined when each partition is created; The component data source includes a visible data source in the BIM model and a hidden data source called by an API in the BIM software environment; Step 3: Compare the matching value defined when each partition is created with the corresponding value in each component data source to identify the partition to which each component data source belongs; Step 4: Check the BIM model through visual positioning in the BIM software environment to verify the accuracy of each component data source in each partition; Step 5: manually modify the partition to which each component data source having an error belongs based on the accuracy verification result of each component data source; Step 6: Write the finally determined partition information of each component data source into the component attributes of the corresponding BIM model.

2. The BIM intelligent zoning method based on data source identification according to claim 1 is characterized in that: In step 4, the visual positioning back-check in the BIM software environment has the functions of 3D model sectioning and isolation of irrelevant components.

3. The BIM intelligent partitioning method based on data source identification according to claim 1 is characterized in that: In step 5, when manually modifying the partition to which each component data source with errors belongs, if all existing partitions do not meet the requirements, a new partition that meets the requirements is created.

4. The BIM intelligent partitioning method based on data source identification according to claim 1 is characterized in that: In step 6, in the process of writing the partition information into the component attributes of the corresponding BIM model, part or all of the partition information is written into the component attributes of the BIM model as hidden attributes.

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