FEA data extraction method and device based on BIM space coordinates

Abstract

The invention discloses an FEA data extraction method and device based on BIM space coordinates, and belongs to the technical field of data processing. The method comprises the following steps: in an FEA application and a BIM application, performing unification processing on a coordinate system of a simulation model to be calculated, so that a coordinate origin of the simulation model in the FEA application is aligned with a coordinate origin in the BIM application; for a to-be-retrieved target instance, obtaining identification data of the target instance; based on the identification data of the target instance, retrieving the IFC data to obtain a target ID of the target instance in the IFC data; obtaining a first space coordinate of the target instance in the BIM application based on the target ID, and obtaining a target calculation unit from the FEA application based on the first space coordinate and second space coordinates of the plurality of nodes in the FEA application; the target calculation unit comprises two nodes; extracting simulation data of the target calculation unit from the FEA application, and extracting model data corresponding to the target instance from the BIM application; and writing the simulation data and the model data into a preset data table.

Description

Technical Field

[0001] This disclosure belongs to the field of data processing technology, and in particular relates to a method and apparatus for extracting FEA data based on BIM spatial coordinates. Background Technology

[0002] Building Information Modeling (BIM) technology, as a core supporting technology in the informatization and intelligent transformation of civil engineering, is a digital carrier of civil engineering physical elements, recording data such as geometric models and attribute information used to characterize physical elements; therefore, BIM is also a core source of basic data in engineering construction data management.

[0003] Finite Element Analysis (FEA) technology, as the core supporting technology for structural behavior simulation in civil engineering, is mainly used for mechanical simulation and analysis of engineering structures. It is an important means of determining whether an engineering structure is safe. Therefore, FEA data intuitively reflects the real-time mechanical state of the engineering structure and is an indispensable and important data component in engineering construction data management.

[0004] BIM data and FEA data respectively record the ontological and behavioral data of the engineering construction object. They are key data sources for comprehensively perceiving and depicting the overall picture of the engineering construction and are also important components of engineering construction data fusion. Among them, engineering construction data fusion, as an important concept and method in engineering construction data management, is a necessary process and means for data governance and the formation of data assets. Data fusion helps to build a unified data environment (CDE), forming a unified data management platform, facilitating the storage, retrieval, and use of project data, improving data utilization efficiency, and fully realizing the value of data.

[0005] However, the extraction and fusion of BIM and FEA data are currently mostly based on manual retrieval, which mainly has the following problems: First, extracting FEA target data requires manually locating target nodes and computational units within the FEA calculation model before data extraction. For large amounts of scattered target data, this process is tedious, time-consuming, and inefficient. Second, while BIM data supports batch extraction, BIM and FEA data are generated by different software, with different data sources and formats. This lack of interoperability between BIM and FEA data means that BIM data cannot drive FEA data extraction, and the data cannot be directly integrated.

[0006] The aforementioned issues pose certain challenges to the integration, fusion, and unified management of engineering data. Summary of the Invention

[0007] A first aspect of this disclosure provides a method for extracting FEA data based on BIM spatial coordinates, the method comprising: Step S1: In the FEA application and BIM application, the coordinate system of the simulation model to be calculated is uniformized so that the coordinate origin of the simulation model in the FEA application is aligned with the coordinate origin in the BIM application; wherein, the uniformization process includes converting the simulation model into IFC data and then loading it into the BIM application. Step S2: For the target instance to be retrieved, obtain the identification data of the target instance; Step S3: Based on the identifier data of the target instance, retrieve the IFC data to obtain the target ID of the target instance in the IFC data; Step S4: Based on the target ID, obtain the first spatial coordinates of the target instance in the BIM application, and based on the first spatial coordinates and the second spatial coordinates of multiple nodes in the FEA application, obtain the target calculation unit from the FEA application; the target calculation unit includes two nodes; Step S5: Extract the simulation data of the target computing unit from the FEA application, and extract the model data corresponding to the target instance from the BIM application; Step S6: Write the simulation data and the model data into a preset data table.

[0008] In an exemplary embodiment, the process of unifying the coordinate system of the simulation model to be calculated in both FEA and BIM applications includes: Set the coordinate system of the FEA application to the Cartesian coordinate system, and take the center or edge of the simulation model to be calculated as the origin of the Cartesian coordinate system. Convert the simulation model into IFC data; The IFC data is loaded into the BIM application, and the coordinate origin of the BIM application and the coordinate origin of the simulation model are aligned.

[0009] In an exemplary embodiment, the identification data includes a target identifier and a target attribute value; the step of retrieving the IFC data based on the identification data of the target instance to obtain the target ID of the target instance in the IFC data includes: Parse and process IFC data, which includes multiple instances, as well as attribute values ​​and identifiers for each instance; The identifiers of multiple instances are matched with the target identifier to retrieve a preliminary selection of instances that match the target identifier; The attribute values ​​of the initially selected instance are matched with the target attribute values ​​to retrieve the target ID in the target instance.

[0010] In an exemplary embodiment, the identification data includes a target identifier and a target attribute value; the step of retrieving the IFC data based on the identification data of the target instance to obtain the target ID of the target instance in the IFC data includes: Define the function check_element_attributes for attribute checking to retrieve instances that match the target identifier; Define the function check_property_set to perform property set definition checks in order to retrieve instances that match the target property value and the target identifier; The target ID of the target instance is determined based on instances that match the target identifier and instances that match the target attribute value and the target identifier.

[0011] In an exemplary embodiment, the target computing unit is obtained from the FEA application based on the first spatial coordinates and the second spatial coordinates of multiple nodes in the FEA application; the target computing unit includes two of the nodes, including: Among the multiple nodes in the FEA application, determine the candidate node whose distance between the second spatial coordinates and the first spatial coordinates is closest; Among the multiple computing units of the FEA application, multiple candidate computing units containing the candidate nodes are identified; The target computing unit is retrieved from a plurality of candidate computing units based on the distance between the second spatial coordinates of the nodes included in the candidate computing unit and the first spatial coordinates.

[0012] In an exemplary embodiment, retrieving the target computing unit from a plurality of candidate computing units based on the distance between the second spatial coordinates of the nodes included in the candidate computing unit and the first spatial coordinates includes: For each candidate computation unit, determine the maximum and minimum coordinate values ​​of the first and second nodes in the candidate computation unit in the same coordinate direction; Candidate calculation units whose maximum and minimum coordinate values ​​satisfy preset conditions are determined as the target calculation units; The preset conditions include: the maximum coordinate value in any coordinate direction is greater than the target coordinate value of the first spatial coordinate in that direction, and the minimum coordinate value in any coordinate direction is less than the target coordinate value.

[0013] In an exemplary embodiment, the method further includes creating the preset data table, wherein creating the preset data table includes: In the Python environment, import the mysql.connector toolkit to enable the Python environment to interact with the MySQL database; Define the connect_to_database function to connect to the target MySQL database; After connecting to the target MySQL database, a data table is created, and the type of each type of data to be written in the data table is defined; wherein, the created data table serves as the preset data table.

[0014] In an exemplary embodiment, the preset data table includes multiple fields, which respectively correspond to the model data, the target computing unit and the node information in the target computing unit in the simulation data, and the simulation calculation result data of the target computing unit; The step of writing the simulation data and the model data into a preset data table includes: Define the `save_to_database` function, which uses a cursor to insert the simulation data and the model data into a database table based on the specified table name.

[0015] In an exemplary embodiment, the method further includes: An interactive graphical user interface is created, comprising at least three functional modules, wherein the functional modules respectively correspond to an original data file path input module, an identification data attribute and attribute value input module, and a database connection information input module; wherein the database connection information input module is used to define the data source address for writing to the preset data table; Set interactive controls in the interactive graphical user interface; In response to the touch of the interactive control, based on the input of the original data file path input module, the identification data attribute and attribute value input module and the database link information input module, at least one step of steps S2-S6 is executed.

[0016] A second aspect of this disclosure provides a device for extracting FEA data based on BIM spatial coordinates, comprising: The coordinate setting module is used to perform coordinate system unification processing on the simulation model to be calculated in FEA and BIM applications, so that the coordinate origin of the simulation model in the FEA application is aligned with the coordinate origin in the BIM application; wherein, the unification processing includes converting the simulation model into IFC data and then loading it into the BIM application. The identifier data acquisition module is used to acquire the identifier data of the target instance to be retrieved; The first retrieval module is used to retrieve the IFC data based on the identifier data of the target instance to obtain the target ID of the target instance in the IFC data; The second retrieval module is used to obtain the first spatial coordinates of the target instance in the BIM application based on the target ID, and to obtain the target calculation unit from the FEA application based on the first spatial coordinates and the second spatial coordinates of multiple nodes in the FEA application; the target calculation unit includes two nodes. The data extraction module is used to extract simulation data of the target computing unit from the FEA application and model data corresponding to the target instance from the BIM application. The data fusion module is used to write the simulation data and the model data into a preset data table.

[0017] The above description is merely an overview of the technical solution disclosed herein. In order to better understand the technical means of this disclosure and to implement it in accordance with the contents of the specification, and to make the above and other objects, features and advantages of this disclosure more apparent and understandable, specific embodiments of this disclosure are described below. Attached Figure Description

[0018] To more clearly illustrate the technical solutions in the embodiments or related technologies of this disclosure, the accompanying drawings used in the description of the embodiments or related technologies will be briefly introduced below. Obviously, the accompanying drawings described below are some embodiments of this disclosure. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort. It should be noted that the scale in the drawings is for illustration only and does not represent the actual scale.

[0019] Figure 1 A flowchart illustrating the steps of the FEA data extraction method based on BIM spatial coordinates is shown. Figure 2 A schematic diagram illustrating the consistency of coordinate systems across software geometric models is shown. Figure 3 It is a customized identification data attribute and attribute value illustration in BIM applications; Figure 4 This is a partial excerpt of the calculation results data from the FEA simulation software. Figure 5 This is an example illustration of writing simulation data and model data into a pre-defined data table based on MySQL; Figure 6It is a batch extraction and illustration of BIM instance spatial coordinates based on IFC data; Figure 7 This is a partial excerpt of the node-coordinate data of the geometric model in the FEA simulation software. Figure 8 This is a partial excerpt of the geometric model element-node data from the FEA simulation software. Figure 9 This is a diagram illustrating the functional modules of an interactive graphical user interface (GUI); Figure 10 This is a diagram of the GUI interface for inputting parameters before the test case program runs; Figure 11 This is a diagram of the GUI interface for inputting parameters before the test case program runs; Figure 12 This is a graphical representation of the instance data results in the final data table of the test case; Figure 13 This is a schematic diagram of the FEA data extraction device based on BIM spatial coordinates. Detailed Implementation

[0020] To make the above-mentioned objectives, features, and advantages of this disclosure more apparent and understandable, the technical solutions of the embodiments of this disclosure will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this disclosure. Based on the embodiments of this disclosure, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this disclosure.

[0021] In related technologies, extracting FEA target data typically involves manually locating target nodes and units within the FEA calculation model before data extraction. When extracting large amounts of dispersed target data, this process is cumbersome, time-consuming, and inefficient. Furthermore, because BIM data and FEA data are generated by different software, with different data sources and formats, they cannot be directly integrated.

[0022] In view of this, the applicant proposes an automatic FEA data extraction method based on BIM spatial coordinates. Specifically, it proposes a cross-software unified data reference establishment method based on spatial coordinates, using BIM spatial coordinate data to drive the extraction of FEA target data, realizing parametric batch retrieval and automatic extraction of BIM and FEA data. Furthermore, it automatically stores the extracted data based on a relational database, and achieves automatic fusion and storage of BIM and FEA target data at the semantic level. This breaks down the data barriers caused by different software formats, providing an innovative solution for linking and interoperating engineering data. At the same time, this invention significantly improves data utilization efficiency, providing a more efficient and practical method for data fusion processes in fields such as engineering data governance, smart construction sites, and digital twins.

[0023] The following description, with reference to the accompanying drawings, provides an exemplary account of the FEA data extraction method and apparatus based on BIM spatial coordinates as described in this disclosure.

[0024] First, please refer to Figure 1 As shown, Figure 1 This diagram illustrates the steps of a FEA data extraction method based on BIM spatial coordinates. Figure 1 As shown, the FEA data extraction method based on BIM spatial coordinates can be applied to electronic devices, such as personal computers and all-in-one displays. In these electronic devices, FEA and BIM applications are installed, and the FEA data extraction method based on BIM spatial coordinates can be executed by the electronic devices.

[0025] like Figure 1 As shown, the specific steps may include: Step S1: In both the FEA and BIM applications, the coordinate system of the simulation model to be calculated is made consistent so that the origin of the simulation model in the FEA application is aligned with the origin of the model in the BIM application. The standardization process includes converting the simulation model into IFC data and then loading it into the BIM application.

[0026] In this embodiment, the FEA application is also referred to as FEA software, and the BIM application is also referred to as BIM software. The FEA application and the BIM application can be two independent applications running on the electronic device.

[0027] In this embodiment, the simulation model to be calculated can refer to a building model, which may include multiple components of the building, and each component can be called an instance.

[0028] In this embodiment, the spatial coordinates of the same building model can be unified in both FEA and BIM applications. For example, the building model uses the same coordinate system in both FEA and BIM applications, and the origin of the coordinate systems in both applications is the same point.

[0029] For example, such as Figure 2 As shown, Figure 2 A schematic diagram illustrating the uniformity of coordinate systems across software geometric models is shown. Figure 2 The left image corresponds to BIM application, and the right image corresponds to FEA application. Both building models use the same point as the origin of their coordinate systems. This ensures coordinate system consistency between the building models in FEA and BIM applications, thus achieving coordinate consistency across software systems.

[0030] It should be noted that in FEA applications, a building model is called a simulation model, while in BIM applications it can be called a virtual building. It can be understood as the same "building" being represented in different applications.

[0031] In this embodiment, when unifying the coordinate system in FEA and BIM applications, the simulation model in FEA can be converted into IFC data, and the IFC data can be loaded into the BIM application.

[0032] Among them, IFC (Industry Foundation Classes) is an international standard data exchange format in the field of Building Information Modeling (BIM), which aims to achieve cross-software and cross-platform data interoperability in the architecture, engineering and construction (AEC) industry. Its core is to realize the digital management and collaboration of building space throughout its entire life cycle through standardized entity definitions and relationship descriptions.

[0033] Step S2: For the target instance to be retrieved, obtain the identification data of the target instance.

[0034] In this embodiment, the building model in the BIM application may include multiple instances, and different instances may be referred to as different components in the building model.

[0035] In BIM applications, each instance in a building model can be tagged with attributes, which can be used to uniquely identify an instance in a building model.

[0036] In this embodiment, the attribute tag may include an identifier for adding the instance, and the attribute value of the instance. The identifier and attribute value can jointly represent the instance. Thus, the identification data of the target instance may include the identifier and the attribute value.

[0037] For example, please refer to Figure 3 As shown, Figure 3 These are customized identifier data attributes and attribute value diagrams in BIM applications, such as... Figure 3 As shown, identifiers can be used to represent the attributes of an instance, such as attribute names. For example, the identifier of an instance can be "sensor". Attribute values ​​can be the encoding of the instance. For example, attribute values ​​can be 1, 2, 3, etc.

[0038] The identification data of the target instance can be input by the user into the electronic device through an external input device. For example, the electronic device can display an interactive graphical user interface, which may include an input box (the identification data attribute and attribute value input module described below), in which the identification data of the target instance can be entered.

[0039] It should be noted that, in the following text, the identifier of the target instance can be called the target identifier, and the attribute value of the target instance can be called the target attribute value.

[0040] In particular, after adding attribute tags to the target instance to be retrieved, it can be used as the retrieval basis for retrieving the corresponding instance in the IFC data.

[0041] It should be noted that a target instance can be understood as an instance in the original building model that exists in the BIM application.

[0042] This can include one target instance or multiple target instances.

[0043] Step S3: Based on the identification data of the target instance, retrieve the IFC data to obtain the target ID of the target instance in the IFC data.

[0044] In this embodiment, the ID of the instance that matches the identification data can be retrieved from the IFC data based on the identification data of the target instance, and this ID is the target ID.

[0045] Among these methods, the ifcopenshell toolkit can be used to retrieve target instances from IFC data based on the characteristics of IFC data.

[0046] The IFC data can include characteristic data for each instance, which can include the attributes of each instance. Based on whether the attribute contains the instance identifier and the attribute value, the instance that matches the target instance is found based on the matching relationship between the attribute and the attribute value.

[0047] Next, the ID of the instance retrieved from the IFC data can be used as the target ID.

[0048] Step S4: Based on the target ID, obtain the first spatial coordinates of the target instance in the BIM application, and based on the first spatial coordinates and the second spatial coordinates of multiple nodes in the FEA application, obtain the target calculation unit from the FEA application; The target computing unit includes two nodes.

[0049] Specifically, based on the coordinate system used when loading IFC data into BIM, and based on the target ID of the target instance, the first spatial coordinates of the target instance can be extracted from the BIM. These first spatial coordinates can be three-dimensional coordinates, thus realizing the extraction of the coordinate position of the instance based on IFC data.

[0050] In FEA applications, the simulation model can include multiple nodes. A node can be understood as an instance, i.e. a building component. In FEA applications, each node corresponds to a second spatial coordinate. Since BIM applications and FEA applications have achieved the unification of coordinate systems and the alignment of coordinate origins in the aforementioned step S1, the second spatial coordinate and the first spatial coordinate can be understood as the coordinates of the unified building component in different applications.

[0051] The first spatial coordinate can be represented as (x, y, z), and the second spatial coordinate can be represented as (x, y, z). , , ).

[0052] In this embodiment, the second spatial coordinates of multiple nodes can be matched with the first spatial coordinates respectively to find the target node that is the same as or closest to the first spatial coordinates.

[0053] In finite element structural calculation simulation, the calculation logic is to divide the model into several calculation units. During finite element calculation, the calculation results are ultimately stored in each calculation unit. Each unit contains two nodes, left and right, and each node records spatial coordinates. "Unit" and "node" are the basic components of finite element simulation calculation software.

[0054] To facilitate the extraction of subsequent simulation data, the target computing unit where the target node is located can be extracted from multiple computing units in the FEA application based on the target node. In other words, the target computing unit from which the simulation data needs to be extracted is deduced by the matching relationship between the second spatial coordinates of the node and the first spatial coordinates of the target instance.

[0055] In this way, by using spatial coordinates with a consistent coordinate system, the relationship between components in the building model is established across applications, thereby realizing the extraction of calculation units in FEA applications based on spatial coordinates of BIM applications.

[0056] Step S5: Extract the simulation data of the target computing unit from the FEA application, and extract the model data corresponding to the target instance from the BIM application.

[0057] In this embodiment, simulation data of the target computational unit can be extracted from the FEA application. This simulation data characterizes various data of the target instance in the finite element structure calculation simulation, such as... Figure 4 The figure shows a partial excerpt of the calculation results data from the FEA simulation software. The simulation data may include simulation data such as axial force, shear force, bending moment (+y), bending moment (-y), bending moment (+z), bending moment (-z), Cb1(-y+z), Cb2(-y+z), Cb3(-y+z), and Cb4(-y+z).

[0058] In this embodiment, model data of the target instance can also be extracted from the BIM application. This BIM model data may include data such as SensorIDIfc, SensorGUIDIfc, and SensorCoordinateIfc.

[0059] In this embodiment, the pandas toolkit can be used to read the simulation data of the target computing unit of the simulation model in the FEA application.

[0060] Step S6: Write the simulation data and the model data into a preset data table.

[0061] In this embodiment, both simulation data and model data can be written into the same preset data table, which can be a data table in a MySQL database.

[0062] For example, please refer to Figure 5 As shown, Figure 5 The illustration shows an example of writing simulation data and model data to a pre-defined data table in MySQL, such as... Figure 5 As shown, each type of data in the model data and simulation data can be written into different fields of the preset data table, for example, into different columns of the preset data table.

[0063] For example, such as Figure 5As shown, the extracted simulation data can include information about the target computing unit and the nodes in that target computing unit, such as ElementIDFEA, Node1FEA, Node2FEA, Node1CoordinateFEA, and Node2CoordinateFEA; the simulation data can also include simulation structure data, such as TypeFEA, StageFEA, and DataValueFEA. ElementIDFEA, Node1FEA, Node2FEA, Node1CoordinateFEA, Node2CoordinateFEA, TypeFEA, StageFEA, and DataValueFEA are written to different columns of a preset data table.

[0064] Similarly, data such as SensorIDIfc, SensorGUIDIfc, and SensorCoordinateIfc in the model data are written to different columns of a preset data table.

[0065] Therefore, simulation data extracted from FEA applications and model data extracted from BIM applications can be integrated into the same preset data table, overcoming the problem that BIM data and FEA data cannot be directly integrated because they are generated by different software in related technologies.

[0066] The FEA data extraction method based on BIM spatial coordinates in this embodiment unifies the coordinate systems of FEA and BIM applications and aligns the origins of the coordinate systems in the two applications. This allows components in the building model to be aligned in spatial position in different applications. Based on the aligned spatial coordinates, the corresponding calculation units can be automatically retrieved from the FEA application based on the spatial coordinates of the BIM application, and the simulation data of the calculation units can be extracted. This eliminates the need to manually locate target nodes and calculation units in FEA, enabling the extraction of simulation data from a large number of dispersed nodes and calculation units, greatly improving data extraction efficiency and reducing the difficulty of operation for personnel.

[0067] Simultaneously, simulation data and model data are written into the same preset data table, which can be a MySQL database table. This allows data from different applications to be automatically merged into a single table, overcoming the problem of direct fusion between BIM data and FEA data in related technologies.

[0068] In some embodiments, in step S1, the coordinate system of the FEA application can be set to a Cartesian coordinate system, and the center or edge of the simulation model to be calculated can be used as the origin of the Cartesian coordinate system; then, the simulation model is converted into IFC data; after that, the IFC data is loaded into the BIM application, and the origin of the BIM application and the origin of the simulation model are aligned.

[0069] In this embodiment, in FEA applications (such as Midas), the coordinate system can be selected as the Cartesian coordinate system, and the origin of the coordinate system can be visualized.

[0070] For example, the origin of the coordinate system can be set at the center or edge of the simulation model to be calculated, such as... Figure 2 As shown, the origin of the coordinate system is located at the lower left corner of the simulation model.

[0071] In this process, the simulation model can be converted into IFC data using FEA applications (such as Midas); then, the IFC data is loaded into BIM applications (such as Revit), and the project base points of the building model are visualized in the BIM application so that the project base points can be aligned with the origin of the coordinate system in the FEA simulation software.

[0072] Here, "project base point" refers to the reference starting point of the coordinate system, and visualizing the project base point means visualizing the "project base point" of the IFC data of the above-converted simulation model in BIM applications.

[0073] The building models used in BIM applications also employ the Cartesian coordinate system.

[0074] In some embodiments, as described in the foregoing embodiments, in step S2, the instance to be identified can be tagged with attributes to obtain the instance's identification data; wherein, the identification data may include the instance's target identifier and target attribute value.

[0075] Specifically, based on the conventional model of BIM software (such as Revit), customized identifiers and attribute values ​​can be added to the project properties. For example, during the creation of BIM model instances, identifiers and attribute values ​​can be set for each instance, and different instances can be distinguished by the identifiers and attribute values.

[0076] Accordingly, in step S3, when obtaining the target ID of the target instance, IFC data can be parsed and processed. The IFC data includes multiple instances, as well as the attribute values ​​and identifiers of each instance. Then, the identifiers of the multiple instances can be matched with the target identifier to retrieve the initial selected instances that match the target identifier. After that, the attribute values ​​of the initial selected instances can be matched with the target attribute values ​​to retrieve the target ID of the target instance.

[0077] In this embodiment, IFC data can be parsed and processed by importing the ifcopenshell toolkit.

[0078] In this embodiment, after parsing and processing the IFC data, the target ID of the target instance in the IFC data can be retrieved using the ifcopenshell toolkit.

[0079] For example, the target ID of a target instance can be retrieved through retrieval methods that include attribute inspection and attribute set definition inspection.

[0080] Attribute checking can refer to identifier-based matching. For example, the identifiers of multiple instances can be matched against the target identifier of the target instance, and the instances in the IFC data that match the target identifier are selected as initial instances. Then, the attribute values ​​of the initial instances can be matched against the target attribute values ​​of the target instance, and the initial instances that match the target attribute values ​​are selected as the target instances.

[0081] In this embodiment, "matching" can mean "identical".

[0082] In another embodiment, when retrieving the target ID of a target instance, attribute checking and attribute set definition checking can be employed. Attribute checking can use Python's built-in functions `dir()` and `getattr()` to dynamically access instance attributes in the IFC data and perform identifier consistency checks. Attribute set definition checking (such as the `IFCelement.IsDefinedBy` attribute) first retrieves the set of instances that match the attribute set definition (e.g., the `IFCelement.IsDefinedBy` attribute), then retrieves the type of the attribute set of the instance set, as well as each attribute in the attribute set, to determine the instance that matches the target identifier and target attribute value.

[0083] Specifically, the target ID of a target instance can be determined by combining instances that match the target identifier retrieved in the attribute check and instances that match the target attribute value and the target identifier in the attribute set definition check.

[0084] In this embodiment, during attribute checking, the function check_element_attributes can be defined for attribute checking. This function dynamically accesses the attributes of each instance in the IFC data through Python's built-in functions dir() and getattr(), and checks whether these attributes contain an identifier attribute named mark. If the value of this attribute matches the target identifier (target_mark), it returns True; otherwise, it returns False. Thus, the instance corresponding to the result that returns true is used as the initial selected instance.

[0085] In this embodiment, when performing attribute set definition checks, the `IFCelement.IsDefinedBy` function of `ifcopenshell` can be called, and the `check_property_set` function can be defined for attribute set definition checks. The `check_property_set` function first checks whether the instance in the IFC data contains an instance of the `IfcRelDefinesByProperties` class; if it does, it further checks the attribute definitions associated with that instance; specifically, it checks whether the attribute set associated with that instance belongs to an instance of the `IfcPropertySet` class; if so, it iterates through each attribute in the attribute set, checks whether it is of type `IfcPropertySingleValue`, and determines whether the attribute name matches the target identifier; if the attribute name matches the target identifier and the attribute value is the same as the target attribute value, it returns `True`, indicating that the instance meets the conditions.

[0086] Finally, when the target instance is determined, the find_sensors function can be defined to check whether each instance in elements_ifc contains customized identification data through attribute checks and attribute set definition checks. If it does, the instance is added to the list of returned results and the element.GlobalId of the instance is obtained, which is the GUID, i.e., the target ID.

[0087] Here, GUID can refer to the unique identifier of the target instance in the BIM application.

[0088] In this embodiment, after obtaining the GUID of the target instance, the first spatial coordinates of the target instance can be retrieved from the IFC data using the ifcopenshell toolkit.

[0089] For example, a `get_absolute_location` function can be defined to extract the spatial coordinates of a target instance in a BIM application. This function first obtains the location of the target instance using its `element.GlobalId`, i.e., `element.ObjectPlacement`. Then, it retrieves the absolute location of the target instance from the given placement object. If the target instance uses the `IfcLocalPlacement` or `IfcAxis2Placement3D` type positioning method, the function will return the three-dimensional coordinates (x, y, z) of that location and convert the default metric units of IFC to millimeter units through coordinate transformation.

[0090] Please refer to Figure 6 As shown, Figure 6 This diagram illustrates the batch extraction of instance spatial coordinates from BIM data based on IFC data. Figure 6 Using three target instances as examples, this diagram illustrates how to extract the spatial coordinates of each target instance from a BIM application. Figure 6 In this context, (x, y, z) are coordinates converted to millimeter units.

[0091] In some embodiments, when obtaining the target computing unit of the simulation model from the FEA reference in step S4, a candidate node whose distance between the second spatial coordinate and the first spatial coordinate is closest can be determined among the multiple nodes of the FEA application; then, multiple candidate computing units containing the candidate node are determined among the multiple computing units of the FEA application; and then, the target computing unit is retrieved from the multiple candidate computing units based on the distance between the second spatial coordinate of the node included in the candidate computing unit and the first spatial coordinate.

[0092] In this embodiment, the simulation model can be arranged in the FEA simulation software according to node-coordinate ( , , Export in the form of ), such as Figure 7 As shown.

[0093] Secondly, in the Python environment, import the numpy and pandas toolkits, and set the first spatial coordinates of the retrieved target instance ( , , () as the target coordinates; Next, the pandas toolkit is used to read the node information data of the simulation model in the FEA application and form an index-data array; the numpy toolkit is used to calculate the second spatial coordinates of each node of the FEA simulation model according to the Euclidean algorithm. , , ), and the first spatial coordinates of the target instance ( , , The distance between them.

[0094] The distance calculation formula is shown in equation (1): Distance = Equation (1) Where Distance represents the distance between the second spatial coordinates and the first spatial coordinates.

[0095] In this embodiment, the index of the minimum distance Distance can be recorded. The node corresponding to this index is the candidate node nearest_node_id that is closest to the first spatial coordinate of the target instance. like Figure 8 As shown, Figure 8 This diagram illustrates a partial excerpt of element-node data from a simulation model used in FEA applications; as shown below. Figure 8 As shown, in FEA applications, each computing unit in the simulation software corresponds to two nodes; therefore, the same node ID may appear in multiple computing units. It is necessary to use the pandas toolkit to retrieve all computing units related_elements containing this candidate node based on the nearest_node_id, and record the two nodes node1_id and node2_id contained in these computing units. Next, the first spatial coordinates of the target instance can be used ( , , Determine the final target computational unit ElementID.

[0096] In some examples, when retrieving a target computing unit, for each candidate computing unit, the maximum and minimum coordinate values ​​of the first and second nodes in the candidate computing unit in the same coordinate direction can be determined; and the candidate computing unit whose maximum and minimum coordinate values ​​satisfy a preset condition can be determined as the target computing unit. The preset conditions include: the maximum coordinate value in at least one coordinate direction is greater than the target coordinate value of the first spatial coordinate in that direction, and the minimum coordinate value in that coordinate direction is less than the target coordinate value.

[0097] In this embodiment, spatial coordinates may include three-dimensional coordinates, that is, coordinate values ​​in three coordinate directions, such as the first spatial coordinates and the second spatial coordinates both including coordinate values ​​in the x, y, and z coordinate directions.

[0098] For each candidate computation unit, the maximum and minimum coordinate values ​​of the first node and the second node in the candidate computation unit in the same coordinate direction can be determined. For example, the coordinate values ​​of the first node and the second node in the x direction are determined, and the smaller coordinate value of the first node and the second node in the x direction is taken as the minimum coordinate value, and the larger coordinate value of the first node and the second node in the x direction is taken as the maximum coordinate value.

[0099] For example, suppose the candidate computation unit Element includes a first node nodel1 and a second node nodel2, wherein the second spatial coordinates of the first node nodel1 are (x1, y1, z1) and the second spatial coordinates of the second node nodel1 are (x2, y2, z2); if x1 is greater than x2, then x1 is the maximum coordinate value in the x direction and x2 is the minimum coordinate value in the x direction.

[0100] Similarly, the maximum and minimum coordinate values ​​in the y and z directions can be obtained.

[0101] Among them, candidate calculation units whose maximum and minimum coordinate values ​​meet preset conditions can be used as target calculation units.

[0102] For example, the preset condition may refer to the following: in at least one coordinate direction, the maximum coordinate value is greater than the target coordinate value of the first spatial coordinate in that direction, and the minimum coordinate value in that coordinate direction is less than the target coordinate value.

[0103] For example, the final target computational unit can be determined according to the following equations 2-4: Min ( , )≤ ≤Max ( , (2) Min ( , ) ≤ ≤ Max ( , (3) Min ( , ) ≤ ≤ Max ( , (4).

[0104] Specifically, the preset condition can be: the final target calculation unit can be determined as long as any one of the judgment conditions in Equation 2-4 is satisfied.

[0105] in, This represents the x-coordinate value of node 1 in the computational unit. This represents the x-coordinate value of node 2 in the computational unit. Similarly, This represents the y-coordinate value of node 1 in the computational unit. This represents the y-coordinate value of node 2 in the computational unit; This represents the z-coordinate value of node 1 in the computational unit. This represents the z-coordinate value of node 2 in the computational unit.

[0106] Of course, if multiple candidate computation units satisfy any of the judgment conditions in Equation 2-4, then the candidate computation unit with the smallest coordinate difference between the second spatial coordinate and the first spatial coordinate can be taken as the target computation unit.

[0107] For example, it can be With Min ( , ) and Max ( , The candidate computational unit with the smallest coordinate difference between the two is selected as the target computational unit.

[0108] Since simulation data and model data need to be written to a preset data table, a preset data table can be created in advance. For example, in a Python environment, the mysql.connector toolkit can be imported to enable interaction between the Python environment and the MySQL database; the connect_to_database function can be defined to connect to the target MySQL database; after connecting to the target MySQL database, a data table can be created, and the type of each category of data to be written in the data table can be defined; wherein, the created data table serves as the preset data table.

[0109] In this embodiment, the mysql.connector toolkit is imported into the Python environment for interaction between the Python environment and the MySQL database. The connect_to_database function is defined to connect to the specified MySQL database. In the connect_to_database function, the database address (host), database name (database), username (user), and password (password) are used as connection parameters. If the database connection is successful, a database connection object is returned; if the connection fails, error information is captured and printed, ensuring timely handling of errors that occur during the database connection process.

[0110] Next, the `create_table` function can be defined to create a data table after a successful database connection is established. This table is used to store simulation data and model data that are associated across software. The structure of this data table includes multiple fields, which correspond to model data (such as SensorIDIfc, SensorGUIDIfc, SensorCoordinateIfc), simulation data (such as ElementIDFEA, Node1FEA, Node2FEA, Node1CoordinateFEA, Node2CoordinateFEA), and FEA simulation calculation result data (such as TypeFEA, StageFEA, DataValueFEA).

[0111] In this embodiment, during the creation of the data table, it is necessary to define the data type of each type of data, that is, the data type of the data written into each column of the preset data table. Common data types include VARCHAR(255), INT, FLOAT, etc.

[0112] This allows data of different data types included in simulation data and model data to be written into specified fields (such as columns) in a preset data table.

[0113] In this embodiment, after successfully connecting to the MySQL relational database and creating a preset data table, the save_to_database function can be defined to use a cursor to insert simulation data and model data into the database table according to the specified table name.

[0114] In some embodiments, to facilitate the automatic extraction of simulation data in FEA applications, an interactive graphical user interface can be provided, allowing users to operate on the interactive graphical user interface to extract the corresponding simulation data and model data.

[0115] Specifically, an interactive graphical user interface can be created; and a human-computer interaction information input text box and interactive controls can be set in the interactive graphical user interface; then, in response to the touch of the interactive controls, at least one of the steps S1-S6 can be executed based on the input of the original data file path input module, the identification data attribute and attribute value input module and the database link information input module.

[0116] The interactive graphical user interface includes at least three functional modules, which respectively correspond to the original data file path input module, the data attribute and attribute value input module, and the database link information input module; wherein, the database link information input module is used to define the data source address to be written to the preset data table.

[0117] Please refer to Figure 9 As shown, Figure 9 The diagram illustrates the functional modules of the interactive graphical user interface (GUI), such as... Figure 9 As shown, it includes three functional modules: the original data file path input module (Original data files browsing area), the parameter and value range input area (Parameter and value range input area), and the MySQL database information input area (MySQL database information input area).

[0118] The raw data file path input module includes input units for the file paths of computational units in the FEA application, the file paths of nodes in the FEA application, the simulation result file paths in the FEA application, and the file paths of IFC data. Users can enter the file storage address in each of the four input units.

[0119] The identification data attribute and attribute value input module allows users to enter the identifier (i.e., target identifier) ​​and attribute value (target attribute value) of the target instance.

[0120] The database connection information input module can include the name of the preset data table, the login account name, the login password, and the project name (named for each data extraction).

[0121] The interactive control can be a touch button. This interactive control integrates and encapsulates the different functions described in steps S2-S6 above. That is, it can extract relevant result data from the simulation database of the FEA application with one click based on the spatial coordinates in the BIM application, and realize interoperability between BIM data and FEA data across software.

[0122] Specifically, when the interactive control is touched, steps S2-S6 above can be executed sequentially, that is, extracting the simulation data of the input target instance in the FEA application and the model data in the BIM application from the specified file path.

[0123] For example, the tkinter toolkit can be imported into a Python environment for the design and development of interactive graphical user interfaces (GUIs).

[0124] In some embodiments, steps S2-S6 above are tested using an interactive graphical user interface. The testing process is as follows: The test case randomly set the target locations of 12 target instances in the building model of the BIM application based on Revit software. The purpose of the test is to extract the simulation data corresponding to the 12 target instances in the building model of the BIM application from the simulation data of the simulation model of the FEA application Midas. The Midas computational model has a FEA node data size of 5880 rows and 4 columns, a FEA cell data size of 1616 rows and 3 columns, a simulation result data size of 64600 rows and 18 columns, an IFC data file size of 25.3MB, and 96 target data entries (including simulation data and model data). The GUI input parameters before running are as follows: Figure 10 As shown.

[0125] After the operation is completed, such as Figure 11 As shown, a data table for storing the target data has been successfully created in MySQL; the final instance data result of the data table is as follows. Figure 12 As shown; When executing steps S2-S6, the total program execution time is 8.3696 seconds, of which the data reading time is 7.5023 seconds, the data retrieval time is 0.7270 seconds, and the data writing time is 0.1403 seconds.

[0126] The present invention provides a BIM spatial coordinate-based FEA data extraction method, which innovatively proposes a cross-software unified data reference establishment method based on spatial coordinates to realize the linking and interoperability of BIM and FEA data; at the same time, it proposes a BIM spatial coordinate data-driven FEA target data extraction method to realize the batch automatic extraction of FEA target data; in addition, it proposes a relational database-based automatic data storage method to realize the automatic and orderly fusion and storage of BIM and FEA target data.

[0127] This invention not only solves the problem of cumbersome and inefficient manual extraction of simulation data in FEA applications, but also addresses the fundamental issue of different data sources and formats between BIM and FEA, resulting in a lack of data interoperability and the inability to directly fuse multi-source heterogeneous data. This invention provides a cross-software data interoperability method for engineering data fusion; significantly improves the efficiency of extracting corresponding target data in FEA applications with numerous and dispersed scenarios; expands the application scenarios of BIM parametric data and enriches the BIM application ecosystem; and provides a more efficient and practical method for data fusion processes in fields such as engineering data governance, smart construction sites, and digital twins.

[0128] Based on the same inventive concept, this disclosure also provides a device for extracting FEA data based on BIM spatial coordinates, such as... Figure 13 As shown, Figure 13 This diagram illustrates the structure of a FEA data extraction device based on BIM spatial coordinates. Figure 13 As shown, the device may include: The coordinate setting module is used to perform coordinate system unification processing on the simulation model to be calculated in FEA and BIM applications, so that the coordinate origin of the simulation model in the FEA application is aligned with the coordinate origin in the BIM application; wherein, the unification processing includes converting the simulation model into IFC data and then loading it into the BIM application. The identifier data acquisition module is used to acquire the identifier data of the target instance to be retrieved; The first retrieval module is used to retrieve the IFC data based on the identifier data of the target instance to obtain the target ID of the target instance in the IFC data; The second retrieval module is used to obtain the first spatial coordinates of the target instance in the BIM application based on the target ID, and to obtain the target calculation unit from the FEA application based on the first spatial coordinates and the second spatial coordinates of multiple nodes in the FEA application; the target calculation unit includes two nodes. The data extraction module is used to extract simulation data of the target computing unit from the FEA application and model data corresponding to the target instance from the BIM application. The data fusion module is used to write the simulation data and the model data into a preset data table.

[0129] In some embodiments, the coordinate setting module includes: The first setting unit is used to set the coordinate system of the FEA application to a Cartesian coordinate system, and to take the center or edge of the simulation model to be calculated as the origin of the Cartesian coordinate system. A conversion unit is used to convert the simulation model into IFC data; The loading unit is used to load the IFC data into the BIM application and align the coordinate origin of the BIM application with the coordinate origin of the simulation model.

[0130] In some embodiments, the identification data includes a target identifier and a target attribute value; the first retrieval module includes: A parsing unit is used to parse and process IFC data, which includes multiple instances, as well as attribute values ​​and identifiers for each instance; The first matching unit is used to match the identifiers of the multiple instances with the target identifier and retrieve the initial selection instances that match the target identifier; The second matching unit is used to match the attribute values ​​of the initially selected instance with the target attribute values ​​to retrieve the target ID of the target instance.

[0131] In some embodiments, the identification data includes a target identifier and a target attribute value; the first retrieval module includes: An attribute checking unit is used to define the check_element_attributes function for attribute checking to retrieve instances that match the target identifier. The attribute set definition checking unit is used to define the check_property_set function to perform attribute set definition checking in order to retrieve instances that match the target attribute value and the target identifier; The retrieval unit is configured to determine the target ID of the target instance based on instances that match the target identifier and instances that match the target attribute value and the target identifier.

[0132] In some embodiments, the second retrieval module includes: A candidate node search unit is used to determine, among the multiple nodes in the FEA application, the candidate node whose distance between the second spatial coordinates and the first spatial coordinates is closest. A candidate computing unit search unit is used to identify multiple candidate computing units that include the candidate node among multiple computing units in the FEA application. The search unit is used to retrieve the target computing unit from a plurality of candidate computing units based on the distance between the second spatial coordinates of the nodes included in the candidate computing unit and the first spatial coordinates.

[0133] In some embodiments, the search unit is specifically configured to, for each candidate calculation unit, determine the maximum and minimum coordinate values ​​of the first node and the second node in the same coordinate direction in that candidate calculation unit; and determine the candidate calculation unit whose maximum and minimum coordinate values ​​satisfy a preset condition as the target calculation unit. The preset conditions include: the maximum coordinate value in at least one coordinate direction is greater than the target coordinate value of the first spatial coordinate in that direction, and the minimum coordinate value in that coordinate direction is less than the target coordinate value.

[0134] In some embodiments, the apparatus further includes a data table creation module, which is specifically configured to import the mysql.connector toolkit in a Python environment to enable interaction between the Python environment and the MySQL database; define the connect_to_database function to connect to the target MySQL database; and, after connecting to the target MySQL database, create a data table and define the type of each type of data to be written in the data table; wherein the created data table serves as the preset data table.

[0135] In some embodiments, the preset data table includes multiple fields, which correspond to the model data, the target computing unit and the node information in the target computing unit in the simulation data, and the simulation calculation result data of the target computing unit, respectively. The data fusion module is specifically used to define the save_to_database function, which uses a cursor to insert the simulation data and the model data into a database table according to the specified table name.

[0136] In some embodiments, the apparatus further includes: An interactive graphical user interface creation module is used to create an interactive graphical user interface. The interactive graphical user interface includes at least three functional modules, which respectively correspond to the original data file path input module, the data attribute and attribute value input module, and the database connection information input module. The database connection information input module is used to define the data source address to be written to the preset data table. A control setting module is used to set interactive controls in the interactive graphical user interface; The running module is configured to respond to the touch of the interactive control and, based on the input from the original data file path input module, the identification data attribute and attribute value input module, and the database link information input module, execute at least one of the steps S2-S6.

[0137] For details regarding the embodiments of the FEA data extraction device based on BIM spatial coordinates, please refer to the description of the relevant parts of the embodiments of the FEA data extraction method based on BIM spatial coordinates.

[0138] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on the differences from other embodiments. The same or similar parts between the various embodiments can be referred to each other.

[0139] Finally, it should be noted that in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0140] The foregoing has provided a detailed description of a method and apparatus for extracting FEA data based on BIM spatial coordinates. Specific examples have been used to illustrate the principles and implementation methods of this disclosure. The descriptions of the above embodiments are only for the purpose of helping to understand the method and its core ideas. At the same time, for those skilled in the art, there will be changes in the specific implementation methods and application scope based on the ideas of this disclosure. Therefore, the content of this specification should not be construed as a limitation of this disclosure.

[0141] Other embodiments of this disclosure will readily occur to those skilled in the art upon consideration of the specification and practice of the invention disclosed herein. This disclosure is intended to cover any variations, uses, or adaptations of this disclosure that follow the general principles of this disclosure and include common knowledge or customary techniques in the art not disclosed herein. The specification and examples are to be considered exemplary only, and the true scope and spirit of this disclosure are indicated by the following claims.

[0142] It should be understood that this disclosure is not limited to the precise structures described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of this disclosure is limited only by the appended claims.

[0143] The terms "an embodiment," "embodiment," or "one or more embodiments" as used herein mean that a particular feature, structure, or characteristic described in connection with an embodiment is included in at least one embodiment of this disclosure. Furthermore, please note that the examples of the phrase "in one embodiment" do not necessarily all refer to the same embodiment.

[0144] Numerous specific details are set forth in the specification provided herein. However, it will be understood that embodiments of this disclosure may be practiced without these specific details. In some instances, well-known methods, structures, and techniques have not been shown in detail so as not to obscure the understanding of this specification.

[0145] In the claims, any reference signs placed between parentheses should not be construed as limiting the claims. The word "comprising" does not exclude the presence of elements or steps not listed in the claims. The word "a" or "an" preceding an element does not exclude the presence of a plurality of such elements. This disclosure can be implemented by means of hardware comprising a plurality of different elements and by means of a suitably programmed computer. In a unit claim enumerating a plurality of means, several of these means may be embodied by the same item of hardware. The use of the words first, second, and third, etc., does not indicate any order. These words may be interpreted as names.

[0146] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of this disclosure, and are not intended to limit them. Although this disclosure has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this disclosure.

Claims

1. A method for extracting FEA data based on BIM spatial coordinates, characterized in that, The method includes: Step S1: In the FEA application and BIM application, the coordinate system of the simulation model to be calculated is uniformized so that the coordinate origin of the simulation model in the FEA application is aligned with the coordinate origin in the BIM application; wherein, the uniformization process includes converting the simulation model into IFC data and then loading it into the BIM application. Step S2: For the target instance to be retrieved, obtain the identification data of the target instance; Step S3: Based on the identifier data of the target instance, retrieve the IFC data to obtain the target ID of the target instance in the IFC data; Step S4: Based on the target ID, obtain the first spatial coordinates of the target instance in the BIM application, and based on the first spatial coordinates and the second spatial coordinates of multiple nodes in the FEA application, obtain the target calculation unit from the FEA application; the target calculation unit includes two nodes; Step S5: Extract the simulation data of the target computing unit from the FEA application, and extract the model data corresponding to the target instance from the BIM application; Step S6: Write the simulation data and the model data into a preset data table.

2. The FEA data extraction method based on BIM spatial coordinates according to claim 1, characterized in that, In FEA and BIM applications, the process of standardizing the coordinate system of the simulation model to be calculated includes: Set the coordinate system of the FEA application to the Cartesian coordinate system, and take the center or edge of the simulation model to be calculated as the origin of the Cartesian coordinate system. Convert the simulation model into IFC data; The IFC data is loaded into the BIM application, and the coordinate origin of the BIM application and the coordinate origin of the simulation model are aligned.

3. The FEA data extraction method based on BIM spatial coordinates according to claim 1, characterized in that, The identification data includes a target identifier and a target attribute value; the step of retrieving the IFC data based on the identification data of the target instance to obtain the target ID of the target instance in the IFC data includes: Parse and process IFC data, which includes multiple instances, as well as attribute values ​​and identifiers for each instance; The identifiers of multiple instances are matched with the target identifier to retrieve the initial selection instances that match the target identifier; The attribute values ​​of the initially selected instance are matched with the target attribute values ​​to retrieve the target ID in the target instance.

4. The FEA data extraction method based on BIM spatial coordinates according to claim 1 or 3, characterized in that, The identification data includes a target identifier and a target attribute value; the step of retrieving the IFC data based on the identification data of the target instance to obtain the target ID of the target instance in the IFC data includes: Define the function check_element_attributes for attribute checking to retrieve instances that match the target identifier; Define the function check_property_set to perform property set definition checks in order to retrieve instances that match the target property value and the target identifier; The target ID of the target instance is determined based on instances that match the target identifier and instances that match the target attribute value and the target identifier.

5. The FEA data extraction method based on BIM spatial coordinates according to claim 1, characterized in that, The target computing unit is obtained from the FEA application based on the first spatial coordinates and the second spatial coordinates of multiple nodes in the FEA application. The target computing unit includes two nodes, including: Among the multiple nodes in the FEA application, determine the candidate node whose distance between the second spatial coordinates and the first spatial coordinates is closest; Among the multiple computing units of the FEA application, multiple candidate computing units containing the candidate nodes are identified; The target computing unit is retrieved from a plurality of candidate computing units based on the distance between the second spatial coordinates of the nodes included in the candidate computing unit and the first spatial coordinates.

6. The FEA data extraction method based on BIM spatial coordinates according to claim 5, characterized in that, The step of retrieving the target computing unit from a plurality of candidate computing units based on the distance between the second spatial coordinates of the nodes included in the candidate computing unit and the first spatial coordinates includes: For each candidate computation unit, determine the maximum and minimum coordinate values ​​of the first and second nodes in the candidate computation unit in the same coordinate direction; Candidate calculation units whose maximum and minimum coordinate values ​​satisfy preset conditions are determined as the target calculation units; The preset conditions include: the maximum coordinate value in at least one coordinate direction is greater than the target coordinate value of the first spatial coordinate in that direction, and the minimum coordinate value in that coordinate direction is less than the target coordinate value.

7. The FEA data extraction method based on BIM spatial coordinates according to claim 1, characterized in that, The method further includes creating the preset data table, wherein creating the preset data table includes: In the Python environment, import the mysql.connector toolkit to enable the Python environment to interact with the MySQL database; Define the connect_to_database function to connect to the target MySQL database; After connecting to the target MySQL database, a data table is created, and the type of each type of data to be written in the data table is defined; wherein, the created data table serves as the preset data table.

8. The FEA data extraction method based on BIM spatial coordinates according to claim 1, characterized in that, The preset data table includes multiple fields, which correspond to the model data, the target computing unit and the node information in the target computing unit in the simulation data, and the simulation calculation result data of the target computing unit, respectively. The step of writing the simulation data and the model data into a preset data table includes: Define the `save_to_database` function, which uses a cursor to insert the simulation data and the model data into a database table based on the specified table name.

9. The FEA data extraction method based on BIM spatial coordinates according to claim 1, characterized in that, The method further includes: An interactive graphical user interface is created, comprising at least three functional modules, wherein the functional modules respectively correspond to an original data file path input module, an identification data attribute and attribute value input module, and a database connection information input module; wherein the database connection information input module is used to define the data source address for writing to the preset data table; Set interactive controls in the interactive graphical user interface; In response to the touch of the interactive control, based on the input of the original data file path input module, the identification data attribute and attribute value input module and the database link information input module, at least one step of steps S2-S6 is executed.

10. A device for extracting FEA data based on BIM spatial coordinates, characterized in that, include: The coordinate setting module is used to perform coordinate system unification processing on the simulation model to be calculated in FEA and BIM applications, so that the coordinate origin of the simulation model in the FEA application is aligned with the coordinate origin in the BIM application; wherein, the unification processing includes converting the simulation model into IFC data and then loading it into the BIM application. The identifier data acquisition module is used to acquire the identifier data of the target instance to be retrieved; The first retrieval module is used to retrieve the IFC data based on the identifier data of the target instance to obtain the target ID of the target instance in the IFC data; The second retrieval module is used to obtain the first spatial coordinates of the target instance in the BIM application based on the target ID, and to obtain the target calculation unit from the FEA application based on the first spatial coordinates and the second spatial coordinates of multiple nodes in the FEA application; the target calculation unit includes two nodes. The data extraction module is used to extract simulation data of the target computing unit from the FEA application and model data corresponding to the target instance from the BIM application. The data fusion module is used to write the simulation data and the model data into a preset data table.

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