A method and system for implementing a universal data format that adapts to multiple system types

Abstract

This disclosure provides a method and system for implementing a universal data format application that adapts to multiple system types, relating to the fields of data processing and industrial software technology. The method includes: receiving a data stream in a universal data format; reading the data stream header module; parsing the source system type identifier and the target system type identifier; and verifying data integrity using a checksum; locating and parsing a core data description module based on preset identifier bits and data offsets; extracting a subset of point cloud data, CAD data, or CAE data; reading an index module that reads the association relationships between point cloud data, CAD data, and CAE data; and parsing the association mapping relationships between the subsets of point cloud data, CAD data, and CAE data; and converting the extracted data subsets and association mapping relationships into a data structure recognizable by the target system based on the target system type identifier. This disclosure solves the problem of data format incompatibility, enabling direct data interaction between the three types of systems without complex conversions.

Description

Technical Field

[0001] This disclosure relates to the fields of data processing and industrial software technology, specifically to a general data application implementation method and system for a point cloud data-CAD-CAE system. Background Technology

[0002] The statements in this section are merely background information relating to this disclosure and do not necessarily constitute prior art.

[0003] In the industrial product development process, point cloud systems, CAD systems, and CAE systems are the three core tools: point cloud systems are mainly used to acquire three-dimensional spatial point data of physical objects through methods such as laser scanning, providing basic data support for reverse design; CAD systems are used to construct geometric models and design details of products, generating product models that include geometric features and non-geometric attributes; and CAE systems perform simulation analysis based on CAD models, outputting simulation results data such as structural strength and thermodynamic performance, guiding product optimization design.

[0004] However, these three types of systems currently use their own independent data formats, resulting in a serious "data silo" problem: common point cloud system formats include PLY and PCD, which can only focus on storing basic information of spatial points and cannot be compatible with the topological structure and constraint relationships of CAD models; mainstream CAD system formats include STEP, IGES, and DWG, which can describe geometric models well, but lack the ability to adapt to CAE simulation data (such as mesh generation, load conditions, and simulation results); common CAE system formats such as ANSYS's CDB and Abaqus' INP are mainly geared towards simulation analysis processes, making it difficult to directly connect to the acquisition parameters and spatial characteristics of point cloud data, and also unable to fully preserve the non-geometric attributes of CAD models.

[0005] In summary, this data format incompatibility issue necessitates complex format conversions during cross-system data interaction. This not only leads to data loss (such as point cloud normal vector information, CAD constraint relationships, and CAE simulation error data), but also increases data processing time and conversion costs, reducing product development efficiency. Furthermore, existing conversion tools are mostly dedicated tools that only support one-way conversion between the two systems, failing to achieve bidirectional interoperability and traceability of point cloud, CAD, and CAE data, further limiting the collaborative nature of the development process. Summary of the Invention

[0006] To address the aforementioned issues, this disclosure proposes a universal data format application implementation method and system that adapts to multiple system types. It provides a universal data format that can adapt to the data characteristics of point cloud, CAD, and CAE systems, enabling complete data storage, correlation mapping, and efficient cross-system interaction and processing, thereby improving the collaboration and efficiency of industrial product development.

[0007] According to some embodiments, the present disclosure adopts the following technical solutions: A method for implementing a universal data format that adapts to multiple system types includes: Receive a data stream in a common data format, which includes a data header module, a core data description module, a relation index module, and an extended field module; The data header module reads the data stream, parses the source system type identifier and the target system type identifier, and uses the checksum to verify data integrity; Based on the preset identifier and data offset, locate and parse the core data description module, and extract a subset of point cloud data, a subset of CAD data, or a subset of CAE data. The module reads the association relationship index between point cloud data, CAD data, and CAE data, and parses the association mapping relationship between subsets of point cloud data, subsets of CAD data, and subsets of CAE data. Based on the target system type identifier, the extracted data subsets and associated mapping relationships are converted into a data structure that the target system can recognize.

[0008] According to some embodiments, the present disclosure adopts the following technical solutions: A universal data format application implementation system adaptable to multiple system types includes: The interface module is used to receive data streams in a common data format, which includes a data header module, a core data description module, a relation index module, and an extended field module. The parsing module is used to read the data header module of the data stream, parse the source system type identifier and the target system type identifier, and verify the data integrity using the checksum; according to the preset identifier bits and data offset, it locates and parses the core data description module, extracting a subset of point cloud data, a subset of CAD data, or a subset of CAE data; and it reads the association index module between point cloud data, CAD data, and CAE data, parsing the association mapping relationship between the subsets of point cloud data, CAD data, and CAE data. The processing module is used to convert the extracted data subset and associated mapping relationship into a data structure that the target system can recognize, based on the target system type identifier.

[0009] According to some embodiments, the present disclosure adopts the following technical solutions: A computer program product includes a computer program that, when executed by a processor, implements the method for applying a general data format that adapts to multiple types of systems.

[0010] According to some embodiments, the present disclosure adopts the following technical solutions: A non-transitory computer-readable storage medium is provided for storing computer instructions, which, when executed by a processor, implement a method for applying a general data format adapted to multiple types of systems.

[0011] According to some embodiments, the present disclosure adopts the following technical solutions: An electronic device includes a processor, a memory, and a computer program; wherein the processor is connected to the memory, the computer program is stored in the memory, and when the electronic device is running, the processor executes the computer program stored in the memory to enable the electronic device to implement a method for applying a universal data format that adapts to multiple types of systems.

[0012] Compared with the prior art, the beneficial effects of this disclosure are as follows: This disclosure presents a method for implementing a universal data format that adapts to multiple types of systems. By specifically designing subsets of point cloud, CAD, and CAE data, it fully covers the data characteristics of the three types of systems, solves the problem of data format incompatibility in the prior art, and enables direct data interaction between the three types of systems without complex conversion, thus achieving cross-system data compatibility.

[0013] This disclosure discloses a general data format application implementation method that is adaptable to multiple types of systems. The core data description module accurately stores key information of various types of data (such as the normal vector of point cloud, the constraint relationship of CAD, and the simulation error data of CAE). With the help of the verification code mechanism, it ensures the integrity of data transmission and storage and avoids data tampering or loss.

[0014] This disclosure discloses a general data format application implementation method that is adaptable to multiple types of systems. The association index module realizes the association mapping and dynamic update of three types of data, supports data traceability and linkage analysis (such as quickly querying the corresponding point cloud data and CAE simulation results through CAD part ID), improves the collaboration of industrial product development, and increases collaboration efficiency.

[0015] This disclosure presents a method for implementing a universal data format that adapts to multiple types of systems. The extended field module supports the storage of personalized data, adapting to the special needs of different systems. At the same time, the version number mechanism supports iterative optimization and backward compatibility of the format, improving the universality and lifespan of the format and providing good scalability. Attached Figure Description

[0016] The accompanying drawings, which form part of this disclosure, are used to provide a further understanding of this disclosure. The illustrative embodiments of this disclosure and their descriptions are used to explain this disclosure and do not constitute an undue limitation of this disclosure.

[0017] Figure 1This is a schematic diagram of the overall structure of the general data format in the embodiments of this disclosure; Figure 2 This is a schematic diagram showing the detailed structure of the core data description module in an embodiment of this disclosure; Figure 3 This is a schematic diagram illustrating the data cross-system interaction process according to an embodiment of this disclosure. Detailed Implementation

[0018] The present disclosure will be further described below with reference to the accompanying drawings and embodiments.

[0019] It should be noted that the following detailed descriptions are illustrative and intended to provide further explanation of this disclosure. Unless otherwise specified, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this disclosure pertains.

[0020] It should be noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the exemplary embodiments according to this disclosure. As used herein, the singular form is intended to include the plural form as well, unless the context clearly indicates otherwise. Furthermore, it should be understood that when the terms “comprising” and / or “including” are used in this specification, they indicate the presence of features, steps, operations, devices, components, and / or combinations thereof.

[0021] Example 1 One embodiment of this disclosure provides a method for implementing a universal data format that adapts to multiple system types. It can adapt to the data characteristics of point cloud, CAD, and CAE systems, achieving complete data storage, association mapping, and efficient cross-system interaction. The specific method steps include: Step 1: Receive a data stream in a common data format, which includes a data header module, a core data description module, a relation index module, and an extended field module; Step 2: Read the data header module of the data stream, parse the source system type identifier and the target system type identifier, and use the checksum to verify data integrity; Step 3: Based on the preset identifier and data offset, locate and parse the core data description module, and extract the point cloud data subset, CAD data subset, or CAE data subset; Step 4: Read the association index module between point cloud data, CAD data, and CAE data, and parse the association mapping relationship between subsets of point cloud data, CAD data, and CAE data; Step 5: Based on the target system type identifier, convert the extracted data subset and associated mapping relationships into a data structure that the target system can recognize.

[0022] As one embodiment, this disclosure provides a method for implementing a universal data format that adapts to multiple system types. This method is applicable to cross-system data interaction and sharing in scenarios such as industrial product design, simulation analysis, and reverse engineering. Specific details include: This disclosure designs a general data format, such as Figure 1 As shown, the general data format includes a data header module, a core data description module, a relation index module, and an extended field module; Furthermore, the data header module is the basic identifier of the data format, including the format version number, data generation timestamp, source system type identifier, target system type identifier, total data length, and checksum; Among them, (1) the format version number adopts the format of "major version number.minor version number.revision number". The major version number is used to represent major changes in the core structure, the minor version number is used to represent the addition or optimization of functional modules, and the revision number is used to represent the adjustment of detailed parameters, supporting backward compatibility of different versions; (2) The source system type identifier and the target system type identifier are encoded with 3 bits to represent the data source (point cloud system, CAD system, CAE system) and the type of the target system to be imported, respectively; (3) The verification code is generated by encrypting the content of the core data description module through a preset verification algorithm (such as MD5, SHA-256, CRC, etc.) and is used for integrity verification during data transmission and storage to prevent data tampering or loss.

[0023] Furthermore, the major version number, minor version number, and revision number are used to characterize major changes to the core structure, the addition or optimization of functional modules, and the adjustment of detailed parameters, respectively. The common data format of different versions supports backward compatibility.

[0024] The core data description module is the core storage part of the data format, containing subsets of point cloud data, CAD data, and CAE data. Each subset has a 1-bit data type identifier to distinguish the data category, ensuring quick location of the target data during parsing. The specific content of each subset includes: (1) Point cloud data subset: used to store the three-dimensional spatial point data and related acquisition parameters output by the point cloud system. The data features include: the unique identifier ID (64-bit integer) of each spatial point, three-dimensional coordinate information (with preset coordinate precision, such as retaining 6 decimal places), point cloud intensity value (0-255), color information (RGB three-color channel values, value range 0-255), normal vector information (X, Y, Z axis normal vector components, precision retained to 4 decimal places) and point cloud acquisition parameters (acquisition device model, acquisition distance, sampling frequency, ambient temperature).

[0025] To improve retrieval efficiency, point cloud data is stored in blocks. Each data block contains 1,000-10,000 configurable spatial point data. Each data block is set with a block identifier ID, the number of points in the block, and the block bounding box information (minimum and maximum X, Y, and Z axis coordinates of the bounding box). At the same time, a point cloud deduplication flag is set to indicate whether the data has been deduplicated. If it has been deduplicated, the deduplication algorithm type (such as distance threshold-based deduplication algorithm or grid-based deduplication algorithm) and deduplication threshold parameters are stored separately.

[0026] (2) CAD Data Subset: Used to store the geometric model and non-geometric attribute data output by the CAD system. Data features include: basic information of the geometric model, topological structure information, geometric feature parameters, constraint relationship information, and non-geometric attributes. Among them, the geometric feature parameters adopt a parametric storage method. For standard geometric features, the feature type and key parameters are stored; for custom geometric features, the contour point coordinates and generation method parameters of the feature are stored. The constraint relationship information is stored in a structured data format (such as XML, JSON, YAML, etc.). The dimensional constraints and geometric constraints are distinguished by tags or key-value pairs. The dimensional constraint data includes the constraint object ID, constraint dimension value, and dimensional tolerance; the geometric constraint data includes the constraint object ID and constraint type. In addition, version iteration information is also included to record the version change records of the CAD model.

[0027] Furthermore, the CAD data subset also includes version iteration information, which records the version change history of the CAD model, including version number, change time, description of the change content and information of the person making the change, supporting the tracing and comparison of model versions.

[0028] (3) CAE Data Subset: Used to store simulation analysis-related data output by the CAE system. Data characteristics include: basic information of the simulation model, mesh generation data, load and boundary condition data, material performance parameters, simulation result data, and simulation parameters. Among them, the simulation result data supports storage in multiple formats, including raw numerical format, visualization texture format, and statistical report format. The raw numerical format is used for accurate calculation, the visualization texture format is used for fast rendering and display, and the statistical report format is used to output statistical information.

[0029] It also includes simulation error analysis data, which is used to record the deviation value, deviation percentage and deviation distribution area between the simulation results and the experimental data. The deviation distribution area is located by the unique identifier ID of the associated node or unit.

[0030] The association index module is used to establish association mappings between point cloud data, CAD data, and CAE data. It achieves the correspondence between different data types by constructing an association table. As shown in Table 3, the association table contains the unique identifier ID of data within each data subset, the associated data type, and the unique identifier ID of the associated data. It supports mappings between point cloud data and CAD model surfaces (e.g., the relationship between point cloud spatial points and CAD surfaces), geometric associations between CAD models and CAE simulation models (e.g., the correspondence between CAD parts and CAE mesh elements), and the correspondence between CAE simulation results and CAD parts (e.g., the association between the stress distribution result of a part and its ID). The association table supports dynamic updates. When data in the core data description module is added, deleted, or modified, the association mapping relationships are automatically adjusted through an update mechanism of "data change detection → association verification → association table refresh" to ensure the accuracy of the associations.

[0031] Table 3. Schematic diagram of the relationship table structure

[0032] Furthermore, the association table in the association index module supports dynamic updates. When data in the core data description module is added, deleted, or modified, the association mapping relationship in the association table is automatically adjusted by triggering an update mechanism. The update mechanism includes three steps: data change detection, association verification, and association table refresh.

[0033] The extended field module is a configurable field used to store personalized data for different systems. It includes extended field identifier (representing the type of personalized data), extended field length (representing the number of bytes of personalized data), and extended field content (specific information of personalized data). It supports adding data items according to the special needs of point cloud, CAD, and CAE systems (such as scan path information of point cloud systems, lightweight model data of CAD systems, multi-condition comparison data of CAE systems, etc.).

[0034] Example 2 One embodiment of this disclosure provides a method for implementing a universal data format that adapts to multiple system types. The specific values ​​mentioned in the following embodiments (such as 6 decimal places, MD5 algorithm, XML format, etc.) are merely preferred embodiments of this disclosure and not limitations on the scope of protection of this disclosure. Other verification algorithms (such as CRC, SHA), data formats (such as JSON, Protobuf), or precision ranges can be selected according to the needs of the actual application scenario.

[0035] As one embodiment, the construction of the general data format and the storage of point cloud data described in Embodiment 1 include: Step 1: Determine the data source and target system. In this embodiment, the source system is a point cloud scanning system (model: Trimble X7), and the target system is a CAD system (SolidWorks 2024). The data header module is configured as follows: format version number is "1.0.0", data generation timestamp is "2025-10-20 14:30:00", source system type identifier is "001", target system type identifier is "010", and the total data length is 128,000 bytes. The checksum is generated by encrypting the point cloud data subset of the core data description module using the MD5 algorithm, with a value of "E8F123...C12".

[0036] Step 2: Construct a subset of point cloud data for the core data description module. Using a block storage method, the 5000 collected spatial point data points are divided into 5 data blocks. Each spatial point has a unique identifier ID "PC_0001~PC_5000". In this embodiment, the 3D coordinate information is preserved to 6 decimal places (e.g., X=123.456789), the point cloud intensity value is "205", the color information is "R=150, G=150, B=150", and the normal vector information is preserved to 4 decimal places. Point cloud acquisition parameters include device model, distance, etc. Each data block contains 1000 (preset number) spatial point data points.

[0037] Step 3: Build the association index module. Since only point cloud data is currently stored, the association table will only record the unique identifier ID of the point cloud data for the time being, and the association data type will be set to "unassociated".

[0038] Step 4: The extended field module stores the personalized data of the point cloud system, and the extended field is identified as "scan path".

[0039] Step 5: Each module is associated with the data offset through a preset flag. The offset of the data header module is 0-64 bytes, the offset of the core data description module is 65-120000 bytes, and so on.

[0040] Example 3 One embodiment of this disclosure provides a method for implementing a universal data format that adapts to multiple system types. The implementation process of CAD data storage and point cloud-CAD data association includes: Step 1: Import the point cloud data from Example 1 into the CAD system for reverse engineering. After generating the CAD model, update the general data format. Change the source system type identifier in the data header module to "010", change the target system type identifier to "100", and recalculate the checksum.

[0041] Step 2: Add a new CAD data subset to the core data description module. In the geometric feature parameters, standard geometric features store feature types and key parameters; constraint relationship information is stored in XML format in this embodiment, for example, "<Dimensional Constraint Constraint Object ID=L1 Constraint Dimension Value=20.000000 Dimensional Tolerance=±0.05>"; non-geometric attributes include material type, part number, etc.

[0042] Step 3: Update the association table in the association relationship index module to establish the association mapping between point cloud data and CAD data. For example, "Point cloud data ID: PC_100 Association data type: CAD surface association data ID: S1".

[0043] As one example, the implementation process of CAE data storage and association with CAD-CAE data includes: Step 1: Import the CAD model from Example 2 into the CAE system for simulation. After generating simulation data, update the general data format again.

[0044] Step 2: Add a new CAE data subset to the core data description module. Simulation results data are stored in multiple formats: the original numerical format records nodal displacements and stress values; simulation error analysis data records deviation values ​​and their distribution areas.

[0045] Step 3: Update the association table in the association index module to establish the association mapping between CAD data and CAE data. For example, "CAD data ID: B1 Association data type: CAE grid cell Association data ID: 1~10000".

[0046] Example 4 One embodiment of this disclosure provides a method for implementing a universal data format that adapts to multiple types of systems. The method includes a data processing flow based on the universal data format, which runs within the data conversion system proposed in this disclosure. The specific process includes: 1. Data Reception and Verification: The system's interface module receives the data stream and first reads the first 64 bytes of the header. The parsing module extracts the "checksum" field and calls the built-in verification algorithm library (configured to the same algorithm as the generator, such as MD5) to recalculate the hash value of the core data. If the calculated value matches the extracted value, the data is considered complete, and the process proceeds to the next step.

[0047] 2. Dynamic Parsing and Positioning: The parsing module jumps directly to the memory address (e.g., byte 65) based on the "data offset" parameter in the data header to begin reading the core data description module. The system identifies whether the currently read data block belongs to a point cloud, CAD, or a subset of CAE based on the "data type identifier".

[0048] 3. Association Relationship Construction: The processing module reads the association relationship index module and constructs a hash map in memory to bidirectionally bind point cloud IDs, CAD face IDs, and CAE unit IDs. For example, when a user clicks on a surface in the CAD system, the system uses this map to look up the corresponding original point cloud data block.

[0049] 4. Format Conversion and Output: Based on the "Target System Type Identifier" (e.g., 010-CAD System) in the data header, the processing module calls the corresponding conversion driver. For example, it parses the "XML constraint data" in the general format into a DOM tree and maps it to API call parameters that the target CAD software (e.g., SolidWorks, Catia) can recognize, thus completing the lossless import of data.

[0050] As can be seen from the above embodiments, the general data format and system disclosed herein can completely store data from three types of systems: point cloud, CAD, and CAE, enabling cross-system data interaction and correlation tracing, and effectively solving the data silo problem of existing technologies.

[0051] Example 5 One embodiment of this disclosure provides a universal data format application implementation system adaptable to multiple types of systems, including: The interface module is used to receive data streams in a common data format, which includes a data header module, a core data description module, a relation index module, and an extended field module. The parsing module is used to read the data header module of the data stream, parse the source system type identifier and the target system type identifier, and verify the data integrity using the checksum; according to the preset identifier bits and data offset, it locates and parses the core data description module, extracting a subset of point cloud data, a subset of CAD data, or a subset of CAE data; and it reads the association index module between point cloud data, CAD data, and CAE data, parsing the association mapping relationship between the subsets of point cloud data, CAD data, and CAE data. The processing module is used to convert the extracted data subset and associated mapping relationship into a data structure that the target system can recognize, based on the target system type identifier.

[0052] The point cloud system, CAD system, and CAE system disclosed herein achieve bidirectional data interaction through the general data format disclosed herein, demonstrating the cross-system adaptability of the format.

[0053] Example 6 One embodiment of this disclosure provides a computer program product, including a computer program that, when executed by a processor, implements the method for applying a general data format that adapts to multiple types of systems.

[0054] Example 7 One embodiment of this disclosure provides a non-transitory computer-readable storage medium for storing computer instructions. When these computer instructions are executed by a processor, they implement a general data format application implementation method adapted to multiple types of systems.

[0055] Example 8 One embodiment of this disclosure provides an electronic device, including: a processor, a memory, and a computer program; wherein the processor is connected to the memory, the computer program is stored in the memory, and when the electronic device is running, the processor executes the computer program stored in the memory to enable the electronic device to implement a general data format application implementation method adapted to multiple types of systems.

[0056] This disclosure is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this disclosure. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create a machine for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0057] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0058] While the specific embodiments of this disclosure have been described above in conjunction with the accompanying drawings, this is not intended to limit the scope of protection of this disclosure. Those skilled in the art should understand that various modifications or variations that can be made by those skilled in the art without creative effort based on the technical solutions of this disclosure are still within the scope of protection of this disclosure.

Claims

1. A method for implementing a universal data format that adapts to multiple system types, characterized in that, include: Receive a data stream in a common data format, which includes a data header module, a core data description module, a relation index module, and an extended field module; The data header module reads the data stream, parses the source system type identifier and the target system type identifier, and uses the checksum to verify data integrity; Based on the preset identifier and data offset, locate and parse the core data description module, and extract a subset of point cloud data, a subset of CAD data, or a subset of CAE data. The module reads the association relationship index between point cloud data, CAD data, and CAE data, and parses the association mapping relationship between subsets of point cloud data, subsets of CAD data, and subsets of CAE data. Based on the target system type identifier, the extracted data subsets and associated mapping relationships are converted into a data structure that the target system can recognize.

2. The method for implementing a universal data format adaptable to multiple system types as described in claim 1, characterized in that, The data header module is the basic identifier part of the general data format, including the format version number, data generation timestamp, source system type identifier, target system type identifier, total data length, and checksum. The format version number adopts the format "major version number.minor version number.revision number". The major version number represents a major change in the core structure, the minor version number represents the addition or optimization of functional modules, and the revision number represents the adjustment of detailed parameters, supporting backward compatibility between different versions. The source system type identifier and the target system type identifier adopt 3-bit binary encoding, respectively representing the data source of the three systems and the type of the target system to be imported. The checksum is generated by encrypting the content of the core data description module through a preset checksum algorithm.

3. The method for implementing a universal data format adaptable to multiple system types as described in claim 1, characterized in that, The core data description module is the core storage part of the data format, which includes a subset of point cloud data, a subset of CAD data, and a subset of CAE data. Each subset is set with a 1-bit data type identifier to distinguish the data category. The subset of point cloud data is used to store the three-dimensional spatial point data and related acquisition parameters output by the point cloud system. The data features include: a unique identifier (ID) for each spatial point, three-dimensional coordinate information, point cloud intensity value, color information, normal vector information, and point cloud acquisition parameters. The CAD data subset is used to store the geometric model and non-geometric attribute data output by the CAD system. The data features include: basic information of the geometric model, topological structure information, geometric feature parameters, constraint relationship information, and non-geometric attributes. The CAE data subset is used to store simulation analysis-related data output by the CAE system. The data characteristics include: basic information of the simulation model, mesh generation data, load and boundary condition data, material property parameters, simulation result data, and simulation parameters.

4. The method for implementing a universal data format adaptable to multiple system types as described in claim 1, characterized in that, The association index module is used to establish the association mapping between point cloud data, CAD data, and CAE data. It realizes the correspondence of different types of data by constructing an association table. The association table contains the unique identifier ID of the data in each data subset, the associated data type, and the unique identifier ID of the associated data. It supports the mapping between point cloud data and CAD model surface, the geometric association between CAD model and CAE simulation model, and the correspondence between CAE simulation results and CAD parts.

5. The method for implementing a universal data format adaptable to multiple system types as described in claim 1, characterized in that, The extended field module is a configurable field used to store personalized data for different systems. It includes extended field identifier, extended field length, and extended field content, and supports adding data items according to the special needs of point cloud, CAD, and CAE systems.

6. The method for implementing a universal data format adaptable to multiple system types as described in claim 1, characterized in that, The process of constructing the general data format and storing point cloud data includes: Step 1: Determine the data source and target system; Step 2: Construct a subset of point cloud data for the core data description module, using a block storage method to divide the collected spatial point data into multiple data blocks; Step 3: Build the association index module. Currently, only point cloud data is stored. The association table only records the unique identifier ID of the point cloud data. The association data type is set to "not associated". Step 4: The extended field module stores the personalized data of the point cloud system, and the extended field is identified as "scan path"; Step 5: Each module is associated with the data offset through a preset flag.

7. A universal data format application implementation system adaptable to multiple system types, characterized in that, include: The interface module is used to receive data streams in a common data format, which includes a data header module, a core data description module, a relation index module, and an extended field module. The parsing module is used to read the data header module of the data stream, parse the source system type identifier and the target system type identifier, and verify the data integrity using the checksum; according to the preset identifier bits and data offset, it locates and parses the core data description module, extracting a subset of point cloud data, a subset of CAD data, or a subset of CAE data; and it reads the association index module between point cloud data, CAD data, and CAE data, parsing the association mapping relationship between the subsets of point cloud data, CAD data, and CAE data. The processing module is used to convert the extracted data subset and associated mapping relationship into a data structure that the target system can recognize, based on the target system type identifier.

8. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by the processor, it implements the general data format application implementation method for adapting to multiple types of systems as described in any one of claims 1-6.

9. A non-transitory computer-readable storage medium, characterized in that, The non-transitory computer-readable storage medium is used to store computer instructions, which, when executed by a processor, implement a general data format application implementation method adapted to multiple types of systems as described in any one of claims 1-6.

10. An electronic device, characterized in that, include: The device includes a processor, a memory, and a computer program; wherein the processor is connected to the memory, the computer program is stored in the memory, and when the electronic device is running, the processor executes the computer program stored in the memory to enable the electronic device to implement a general data format application implementation method adapted to multiple types of systems as described in any one of claims 1-6.

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