A BIM-based method for storing building construction data

Abstract

The present invention relates to the technical field of storage structures, and particularly relates to a method for storing building construction data based on BIM. The method first obtains the node retrieval efficiency degree of a node to be analyzed according to the situation of the BIM model tree structure where the node to be analyzed is located; obtains the building complexity of the node to be analyzed according to the spatial complexity of the BIM model corresponding to the node to be analyzed; comprehensively obtains the node complexity possibility of the node to be analyzed based on the node retrieval efficiency degree and the building complexity corresponding to all the child nodes included in the node to be analyzed; divides all nodes into complex area nodes and simple area nodes according to the node complexity possibility; and stores the node data corresponding to the complex area nodes and the simple area nodes in the BIM model tree structure in a partitioned manner. By deeply analyzing the complexity of building areas in the BIM model, the present invention reasonably stores the building construction data of BIM and improves the data retrieval efficiency.

Description

Technical Field

[0001] The present invention relates to the technical field of storage structures, and particularly relates to a method for storing building construction data based on BIM. Background Art

[0002] A BIM (Building Information Modeling) model is a digital representation that contains all the physical and functional characteristics of a building. The building construction data of BIM refers to all the information related to building construction in the BIM model, including but not limited to data such as 3D geometric information, building object information, and physical information. In order to achieve the rational utilization of building resources, it is necessary to retrieve the building construction data of the BIM model.

[0003] Since the building construction data is relatively large, it is necessary to store the data according to the hierarchical relationship of the current building object structure to ensure the storage security and accuracy of the current building construction data. The existing technology stores data by storing the building construction data in a single area, without fully considering the complex situation of the building area in the BIM model, resulting in unreasonable storage of the building construction data of BIM and making it difficult to ensure the data retrieval efficiency. Summary of the Invention

[0004] In order to solve the technical problem that the existing technology stores the building construction data of BIM unreasonably and it is difficult to ensure the data retrieval efficiency, the purpose of the present invention is to provide a method for storing building construction data based on BIM, and the specific technical solution adopted is as follows:

[0005] A method for storing building construction data based on BIM, the method includes the following steps:

[0006] Obtain the building construction data set of the BIM model; the building construction data set contains the node data corresponding to each node in the tree structure of the BIM model;

[0007] According to the situation of the node to be analyzed in the tree structure of the BIM model, obtain the node retrieval efficiency degree of the node to be analyzed; according to the spatial complexity of the BIM model corresponding to the node to be analyzed, obtain the building complexity of the node to be analyzed; comprehensively consider the node retrieval efficiency degree and the building complexity corresponding to all the child nodes contained in the node to be analyzed, and obtain the node complexity possibility of the node to be analyzed;

[0008] According to the node complexity possibility, divide all nodes into complex area nodes and simple area nodes; store the node data corresponding to the complex area nodes and simple area nodes in the tree structure of the BIM model in different partitions.

[0009] Further, the method for obtaining the node retrieval efficiency degree includes:

[0010] Obtain the first efficiency parameter of the node to be analyzed according to the depth of the tree structure of the BIM model where the node to be analyzed is located;

[0011] Obtain the second efficiency parameter of the node to be analyzed according to the total number of child nodes included in the node to be analyzed;

[0012] Fusion the first efficiency parameter and the second efficiency parameter in the positive direction to obtain the node retrieval efficiency degree of the node to be analyzed.

[0013] Furthermore, the method for obtaining the first efficiency parameter includes:

[0014] Calculate the ratio of the corresponding level of the node to be analyzed to the maximum level of the tree structure of the BIM model to obtain the first efficiency parameter of the node to be analyzed.

[0015] Furthermore, the method for obtaining the node retrieval efficiency degree of the node to be analyzed includes:

[0016] Calculate the product of the first efficiency parameter and the second efficiency parameter and perform normalization processing to obtain the node retrieval efficiency degree of the node to be analyzed.

[0017] Furthermore, the method for obtaining the building complexity includes:

[0018] Take the space volume corresponding to the parent node of the node to be analyzed as the membership space volume of the node to be analyzed;

[0019] Take the total number of all child nodes included in the parent node of the node to be analyzed as the membership space capacity of the node to be analyzed;

[0020] Calculate the ratio of the membership space capacity to the membership space volume to obtain the building complexity of the node to be analyzed.

[0021] Furthermore, the method for obtaining the node complexity possibility includes:

[0022] Calculate the sum value of the node retrieval efficiency degree and the preset denominator value, and calculate the ratio of the building complexity to the sum value to obtain the node complexity possibility of the node to be analyzed.

[0023] Furthermore, the preset denominator value is set to 0.001.

[0024] Furthermore, the method for obtaining the complex area nodes and the simple area nodes includes:

[0025] Nodes with a node complexity probability greater than a preset complexity threshold are regarded as complex area nodes; all child nodes included in the complex area are regarded as complex area nodes; nodes other than complex area nodes in the BIM model tree structure are regarded as simple area nodes.

[0026] Further, the preset complexity threshold is set to 0.8.

[0027] Further, the method for partitioned storage includes:

[0028] The node data corresponding to each simple area node in the BIM model tree structure is stored in a normal table, and the node data corresponding to the complex area nodes in the BIM model tree structure is stored in a partitioned table.

[0029] The present invention has the following beneficial effects:

[0030] The retrieval efficiency of the node to be analyzed is measured by using the node retrieval efficiency degree, and the complexity of the BIM model space corresponding to the node to be analyzed is measured by using the building complexity; the retrieval efficiency degree of the node to be analyzed and the building complexity are comprehensively considered to evaluate the possibility that the node to be analyzed is in a complex area. According to the complexity probability of the node, the nodes are divided into complex area nodes and simple area nodes, and the complex area nodes are stored in partitions to optimize the retrieval efficiency of the database and reduce the query time of the complex area nodes. Description of the Drawings

[0031] In order to more clearly illustrate the technical solutions and advantages in the embodiments of the present invention or the prior art, the drawings required for the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0032] Figure 1 It is a flowchart of a BIM-based building construction data storage method provided by an embodiment of the present invention;

[0033] Figure 2 It is a schematic diagram of a BIM model tree structure method provided by an embodiment of the present invention. Detailed Embodiments

[0034] In order to further elaborate on the technical means and effects adopted by the present invention to achieve the intended invention purpose, the following, in conjunction with the accompanying drawings and preferred embodiments, details a BIM-based building construction data storage method proposed according to the present invention, including its specific implementation manner, structure, features, and effects, as follows. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. In addition, the specific features, structures, or characteristics in one or more embodiments can be combined in any suitable form.

[0035] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those of ordinary skill in the technical field to which the present invention belongs.

[0036] The following specifically describes the specific solution of a BIM-based building construction data storage method provided by the present invention in conjunction with the accompanying drawings.

[0037] Please refer to Figure 1 , which shows a flowchart of a BIM-based building construction data storage method provided by an embodiment of the present invention. The method includes the following steps:

[0038] Step S1: Obtain a building construction data set of the BIM model; the building construction data set includes node data corresponding to each node in the tree structure of the BIM model.

[0039] Obtain the building construction data set of the BIM model from the detection system. The specific obtaining process includes: using Linyun BIM software for BIM modeling to obtain the BIM model. Linyun BIM software supports the import and automatic integration and review of common BIM model data, and can integrate the models and information of other BIM software and 3D modeling software through the Datasmith plug-in. Extract the corresponding data of the objects from the BIM model. Usually, the data is stored in the IFC file, and use an IFC converter to convert the IFC file into a data format that supports database operations, such as XML or JSON. In the present invention, the JSON data format is selected.

[0040] Perform hierarchical decomposition according to the BIM model of the building to establish a tree structure of the BIM model. Please refer to Figure 2, which shows a schematic diagram of a BIM model tree structure method provided by an embodiment of the present invention. The BIM model tree structure reflects the hierarchical relationship among projects, buildings, floors, rooms, and objects in the BIM model. It should be noted that in the BIM model, since the building is hierarchically distinct, the acquired data can be disassembled hierarchically to construct a tree structure. In this tree structure, each node represents an object or a group of objects. After establishing the tree hierarchy structure, this structure can be traversed to obtain the node data corresponding to each node. In the present invention, the node data corresponding to the nodes in the BIM model includes: id: the unique identifier of the node, with the type being a number; name: the name of the node, with the type being a string; category: the category of the node, with the type being a string; location: the location of the node, with the type being an object, including three attributes x, y, z, representing the three-dimensional coordinates of the node; parameters: the parameters of the node, including multiple attribute-value pairs, representing various parameters of the node, such as the material of the node and the spatial volume of the node, etc. The basic building unit of the BIM model of the present invention is an object, and the object can include but is not limited to: structural objects: such as beams, columns, walls, slabs, etc., which constitute the skeleton of the building and support the weight and load of the entire structure; building objects: such as doors, windows, stairs, ceilings, floors, etc., which provide the functionality and aesthetics of the building; equipment objects: such as electrical equipment, water supply and drainage systems, heating, ventilation, and air conditioning equipment, etc., which provide the necessary services and facilities for the building; home decoration objects: such as tables, chairs, lamps, curtains, artworks, etc., which enhance the comfort and aesthetics of the building.

[0041] It should be noted that for the convenience of calculation, all the index data involved in the operations in the embodiments of the present invention have undergone data preprocessing, thereby eliminating the influence of dimensionality. The specific means of eliminating the influence of dimensionality are well-known technical means to those skilled in the art and will not be limited here.

[0042] In order to efficiently store the node data corresponding to each node in the BIM model tree structure, the PostgreSQL relational database is selected as the storage platform, and the table structure and each field type are customized. However, in the prior art, when storing building construction data, a single-region storage method is usually adopted, without fully considering the complexity and hierarchical relationship of the building regions in the BIM model, resulting in an unreasonable design of the storage structure of the building construction data and low data retrieval efficiency. To solve this problem, first, any node needs to be selected as the node to be analyzed, and its node complexity is deeply analyzed, including its hierarchical relationship and its position and role in the overall model, so as to provide a scientific basis for optimizing the storage structure and improving the retrieval efficiency.

[0043] Step S2: Obtain the node retrieval efficiency degree of the node to be analyzed according to the situation of the node to be analyzed in the BIM model tree structure; obtain the building complexity of the node to be analyzed according to the spatial complexity of the BIM model corresponding to the node to be analyzed; comprehensively consider the node retrieval efficiency degrees and the building complexities corresponding to all the child nodes included in the node to be analyzed, and obtain the node complexity possibility degree of the node to be analyzed.

[0044] Use the node retrieval efficiency degree to measure the efficiency of retrieving the node to be analyzed from the BIM model tree structure, and use the building complexity to measure the complexity of the BIM model space corresponding to the node to be analyzed; comprehensively consider the retrieval efficiency degree and the building complexity of the node to be analyzed to evaluate the possibility that the node to be analyzed is a complex area.

[0045] To measure the efficiency of retrieving the node to be analyzed from the BIM model tree structure, preferably, in an embodiment of the present invention, the method for obtaining the node retrieval efficiency degree includes:

[0046] Obtain the first efficiency parameter of the node to be analyzed according to the depth of the node to be analyzed in the BIM model tree structure;

[0047] Obtain the second efficiency parameter of the node to be analyzed according to the total number of child nodes included in the node to be analyzed;

[0048] Fusion the first efficiency parameter and the second efficiency parameter in the positive direction to obtain the node retrieval efficiency degree of the node to be analyzed.

[0049] Specifically, calculate the ratio of the corresponding level of the node to be analyzed to the maximum level of the BIM model tree structure to obtain the first efficiency parameter of the node to be analyzed; use the total number of all child nodes included in the node to be analyzed as the second efficiency parameter; it should be noted that positive fusion is a well-known prior art to those skilled in the art, and positive fusion can adopt simple multiplication, arithmetic mean or other suitable fusion methods. In an embodiment of the present invention, calculate the product of the first efficiency parameter and the second efficiency parameter and perform normalization processing to obtain the node retrieval efficiency degree of the node to be analyzed. It should be noted that the method of normalization is: use the norm normalization function for normalization, and limit the numerical range to between 0 and 1. Among them, normalization is a well-known technical means to those skilled in the art, and the choice of the normalization function can be linear normalization or standard normalization, etc. The specific normalization method is not limited here.

[0050] For the above steps, in the BIM model tree structure, building components are organized hierarchically from the root node to the leaf node. When retrieving an object, it is necessary to traverse layer by layer from the root node to the leaf node. The deeper the level of the object, the longer the retrieval path and the lower the retrieval efficiency. The more child nodes of the node to be analyzed, the more child nodes need to be traversed during retrieval and the lower the retrieval efficiency. The first efficiency parameter is used to reflect the impact of the depth of the node to be analyzed in the BIM model tree structure on the retrieval efficiency. The second efficiency parameter is used to reflect the impact of the number of child nodes of the node to be analyzed on the retrieval efficiency. The first efficiency parameter and the second efficiency parameter are fused to obtain the node retrieval efficiency degree. By calculating the node retrieval efficiency degree, the retrieval efficiency of each node can be quantified. The lower the retrieval efficiency degree, the worse the retrieval efficiency of the node and its child nodes, and partition storage may be required to optimize performance. The retrieval efficiency of the node is quantified through two dimensions: the hierarchical depth and the number of child nodes.

[0051] Preferably, in an embodiment of the present invention, the method for obtaining the building complexity includes:

[0052] Taking the space volume corresponding to the parent node of the node to be analyzed as the membership space volume of the node to be analyzed;

[0053] Taking the number of all child nodes included in the parent node of the node to be analyzed as the membership space capacity of the node to be analyzed;

[0054] Calculating the ratio of the membership space capacity to the membership space volume to obtain the building complexity of the node to be analyzed. It should be noted that the node data corresponding to the parent node of the node to be analyzed includes the space volume corresponding to the parent node of the node to be analyzed.

[0055] For the above steps, considering that in the BIM model tree structure, the parent node usually represents a larger building area, while the child node represents a specific object within that area. The larger the space volume occupied by the parent node, the sparser the distribution of objects may be and the lower the complexity. The more child nodes included in the parent node, the denser the distribution of objects may be and the higher the complexity. In order to quantify the distribution density of the components inside the parent node and reflect the complexity of this area. The membership space volume is used to reflect the space volume corresponding to the parent node of the node to be analyzed. The membership space capacity is used to reflect the number of all child nodes included in the parent node of the node to be analyzed. Calculating the ratio of the membership space capacity to the membership space volume to obtain the building complexity of the node to be analyzed. The building complexity is used to measure the complexity of the BIM model space corresponding to the node to be analyzed. By calculating the building complexity, areas with dense component distribution in the BIM model can be identified. Areas with high complexity may require partition storage to optimize data retrieval efficiency.

[0056] To evaluate the possibility that the node to be analyzed is a complex area, preferably, in an embodiment of the present invention, the method for obtaining the node complexity possibility includes:

[0057] Calculate the sum value of the node retrieval efficiency degree and the preset denominator value, and calculate the ratio of the building complexity and the sum value to obtain the node complexity possibility of the node to be analyzed. In an embodiment of the present invention, the preset denominator value is used to prevent the denominator from being 0, which is set to 0.001 in the present invention, and the implementer can set it according to the implementation requirements.

[0058] For the above steps, the node retrieval efficiency degree is used to reflect the retrieval efficiency of the node to be analyzed in the BIM model tree structure. The building complexity is used to reflect the complexity of the BIM model space corresponding to the node to be analyzed. The higher the building complexity and the lower the node retrieval efficiency degree, the greater the node complexity possibility. Calculate the sum value of the node retrieval efficiency degree and the preset denominator value, and calculate the ratio of the building complexity and the sum value to obtain the node complexity possibility of the node to be analyzed. In the BIM model tree structure, the node complexity possibility is used to dynamically identify complex area nodes.

[0059] Step S3: According to the node complexity possibility, divide all nodes into complex area nodes and simple area nodes; partition and store the node data corresponding to the complex area nodes and simple area nodes in the BIM model tree structure.

[0060] According to the complexity possibility of the nodes, divide the nodes into complex area nodes and simple area nodes, and partition and store the complex area nodes to optimize the retrieval efficiency of the database and reduce the query time of the complex area nodes.

[0061] To divide the nodes into complex area nodes and simple area nodes, preferably, in an embodiment of the present invention, the method for obtaining the complex area nodes and simple area nodes includes:

[0062] Take the nodes with the node complexity possibility greater than the preset complexity threshold as complex area nodes; take all the child nodes included in the complex area as complex area nodes; take the nodes other than the complex area nodes in the BIM model tree structure as simple area nodes. In the present invention, the preset complexity threshold is used to distinguish complex area nodes and simple area nodes. In an embodiment of the present invention, the preset complexity threshold is set to 0.8, and the implementer can set it according to the implementation requirements.

[0063] For the above steps, the node complexity probability is used to dynamically identify the nodes in complex regions. Nodes with a node complexity probability greater than a preset complexity threshold are regarded as nodes in complex regions. Nodes in complex regions usually have a relatively high node complexity probability, indicating that the components in this region are densely distributed and the retrieval efficiency is low. The nodes in complex regions and their child nodes are uniformly marked for subsequent partitioned storage. The node and all its child nodes are marked as nodes in complex regions. Nodes in the BIM model tree structure other than the nodes in complex regions are regarded as nodes in simple regions. Nodes in simple regions usually have a relatively low node complexity probability, indicating that the components in this region are sparsely distributed and the retrieval efficiency is high. Nodes in simple regions do not need to be stored in partitions and can be directly stored in a normal table.

[0064] Preferably, in an embodiment of the present invention, the method for partitioned storage includes:

[0065] The node data corresponding to each simple region node in the BIM model tree structure is stored in a normal table, and the node data corresponding to the nodes in complex regions in the BIM model tree structure is stored in a partitioned table.

[0066] Specifically, an adjacency list model is created in PostgreSQL, and fields such as id, name, category, location, and parent_id are defined. The hierarchical relationship between nodes is represented by the parent_id field. This adjacency list model serves as a normal table for storing the node data of all nodes. A partitioned table is created in PostgreSQL, and its table structure is the same as that of the normal table, including fields such as id, name, category, location, and parent_id. The partitioned table is partitioned by a partition key (such as id or parent_id). Using SQL statements, the node data of the nodes in complex regions is migrated from the normal table to the partitioned table. The node data corresponding to the nodes in complex regions in the BIM model tree structure is still stored in the partitioned table.

[0067] For the above steps, partitioned storage centrally stores the data of nodes in complex regions and optimizes the retrieval efficiency. The data of nodes in simple regions is retained in the normal table, reducing the storage and retrieval overhead. The present invention provides an efficient method for partitioned storage. This method can significantly improve the retrieval efficiency of nodes in complex regions and is applicable to the BIM data management of complex building structures.

[0068] The present invention also proposes a BIM-based building construction data storage system, which includes: a data acquisition module 101, a node complexity probability analysis module 102, and a partitioned storage module 103.

[0069] The data acquisition module 101 is used to acquire the building construction data set of the BIM model; the building construction data set includes the node data corresponding to each node in the BIM model tree structure.

[0070] The node complexity possibility analysis module 102 is used to obtain the node retrieval efficiency degree of the node to be analyzed according to the situation of the node to be analyzed in the BIM model tree structure; obtain the building complexity of the node to be analyzed according to the spatial complexity of the BIM model corresponding to the node to be analyzed; and comprehensively obtain the node retrieval efficiency degree and the building complexity corresponding to all child nodes included in the node to be analyzed, so as to obtain the node complexity possibility of the node to be analyzed.

[0071] The partition storage module 103 is used to divide all nodes into complex area nodes and simple area nodes according to the node complexity possibility; and perform partition storage on the node data corresponding to the complex area nodes and simple area nodes in the BIM model tree structure.

[0072] It should be noted that: for the system provided in the above embodiment, only the above division of each functional module is used for illustration. In actual application, the above functions can be allocated to different functional modules according to needs, that is, the internal structure of the computer device is divided into different functional modules to complete all or part of the functions described above. In addition, a BIM-based building construction data storage system and a BIM-based building construction data storage method embodiment provided in the above embodiment belong to the same concept, and the specific implementation process is detailed in the method embodiment, which will not be repeated here.

[0073] In summary, the embodiment of the present invention provides a BIM-based building construction data storage method. First, obtain the node retrieval efficiency degree of the node to be analyzed according to the situation of the node to be analyzed in the BIM model tree structure; obtain the building complexity of the node to be analyzed according to the spatial complexity of the BIM model corresponding to the node to be analyzed; comprehensively obtain the node retrieval efficiency degree and the building complexity corresponding to all child nodes included in the node to be analyzed, so as to obtain the node complexity possibility of the node to be analyzed; divide all nodes into complex area nodes and simple area nodes according to the node complexity possibility; and perform partition storage on the node data corresponding to the complex area nodes and simple area nodes in the BIM model tree structure. The present invention rationally stores the building construction data of BIM by deeply analyzing the complexity of the building area in the BIM model, and improves the data retrieval efficiency.

[0074] It should be noted that the above-mentioned order of the embodiments of the present invention is only for description and does not represent the superiority or inferiority of the embodiments. The processes depicted in the accompanying drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In certain embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0075] Each embodiment in this specification is described in a progressive manner. For the same or similar parts among the embodiments, reference can be made to each other. The key point of each embodiment is to illustrate the differences from other embodiments.

Claims

1. A BIM-based building construction data storage method, characterized in that The method includes the following steps: Obtain the building construction data set of the BIM model; the building construction data set contains the node data corresponding to each node in the BIM model tree structure; According to the situation of the node to be analyzed in the BIM model tree structure, obtain the node retrieval efficiency degree of the node to be analyzed; according to the spatial complexity of the BIM model corresponding to the node to be analyzed, obtain the building complexity of the node to be analyzed; comprehensively consider the node retrieval efficiency degrees and the building complexities corresponding to all the child nodes included in the node to be analyzed, and obtain the node complexity possibility of the node to be analyzed; According to the node complexity possibility, divide all nodes into complex area nodes and simple area nodes; store the node data corresponding to the complex area nodes and simple area nodes in the BIM model tree structure in a partitioned manner.

2. The method for storing building construction data based on BIM according to claim 1, characterized in that, The method for obtaining the node retrieval efficiency degree includes: According to the depth of the node to be analyzed in the BIM model tree structure, obtain the first efficiency parameter of the node to be analyzed; According to the total number of child nodes included in the node to be analyzed, obtain the second efficiency parameter of the node to be analyzed; Fusion the first efficiency parameter and the second efficiency parameter in a positive direction to obtain the node retrieval efficiency degree of the node to be analyzed.

3. The method for storing construction data based on BIM according to claim 2, wherein, The method for obtaining the node retrieval efficiency degree of the node to be analyzed includes: Calculate the product of the first efficiency parameter and the second efficiency parameter and perform normalization processing to obtain the node retrieval efficiency degree of the node to be analyzed.

4. A BIM-based building construction data storage method according to claim 1, characterized in that, The method for obtaining the building complexity includes: Use the spatial volume corresponding to the parent node of the node to be analyzed as the membership spatial volume of the node to be analyzed; Use the total number of all child nodes included in the parent node of the node to be analyzed as the membership space capacity of the node to be analyzed; Calculate the ratio of the membership space capacity to the membership spatial volume to obtain the building complexity of the node to be analyzed.

5. A BIM-based building construction data storage method according to claim 1, characterized in that, The method for obtaining the node complexity possibility includes: Calculate the sum value of the node retrieval efficiency degree and a preset denominator value, and calculate the ratio of the building complexity to the sum value to obtain the node complexity possibility of the node to be analyzed.

6. A BIM-based building construction data storage method according to claim 5, characterized in that, The preset denominator value is set to 0.

001.

7. A BIM-based building construction data storage method according to claim 1, wherein The method for obtaining the complex area nodes and simple area nodes includes: Take the nodes with the node complexity possibility greater than the preset complexity threshold as complex area nodes; take all the child nodes included in the complex area as complex area nodes; take the nodes in the BIM model tree structure other than the complex area nodes as simple area nodes.

8. A BIM-based building construction data storage method according to claim 7, characterized in that The preset complexity threshold is set to 0.

8.

9. A BIM-based building construction data storage method according to claim 1, characterized in that The method for partitioned storage includes: Store the node data corresponding to each simple area node in the BIM model tree structure in a normal table, and store the node data corresponding to the complex area nodes in the BIM model tree structure in a partitioned table.

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