Part data generation method and device based on multiple tables, equipment and storage medium

Abstract

Embodiments of the present application provide a multi-table-based part data generation method and device, equipment and a storage medium, and belong to the technical field of 3D models. The method comprises: acquiring a main attribute table of a part, wherein the main attribute table comprises attribute information and product technical parameters of the part; if there is a pairing constraint relationship between the product technical parameters of the part, acquiring a pairing attribute table of the part, wherein the pairing attribute table comprises the pairing constraint relationship between the product technical parameters of the part; and generating a model parameter table of the part based on the main attribute table and the pairing attribute table. The multi-table-based part data generation method provided by the embodiments of the present application greatly simplifies the originally very cumbersome data construction work by accurately setting the pairing constraint relationship between the product technical parameters of the part, and lays a solid foundation for establishing an efficient and accurate engineering database.

Description

Technical Field

[0001] This application relates to the field of 3D modeling technology, and in particular to a method, apparatus, device and storage medium for generating component data based on multiple tables. Background Technology

[0002] With the continuous development of technology, manufacturing is also evolving. Market demand is driving manufacturing enterprises towards standardization and localization, leading to the emergence of numerous industrial basic resource databases. The construction of these databases is a massive undertaking, involving a vast array of mechanical parts. These parts are diverse, each with its unique structure, function, and application. Furthermore, each part contains multiple key technical parameters that are not isolated but interconnected and mutually influential, increasing the difficulty of data processing. Faced with such a massive amount of data and complex parameter relationships, efficiently constructing and managing engineering databases while ensuring data accuracy and consistency is a significant challenge for manufacturing enterprises. Summary of the Invention

[0003] The main objective of this application is to propose a method, apparatus, device, and storage medium for generating component data based on multiple tables. The aim is to greatly simplify the originally cumbersome data construction work by systematically organizing and standardizing the large number of complex technical parameters involved in mechanical components.

[0004] To achieve the above objectives, a first aspect of this application proposes a method for generating component data based on multiple tables, the method comprising:

[0005] Obtain the main attribute table of the component, which includes the attribute information and product technical parameters of the component;

[0006] If the product technical parameters of the component have a pairing constraint relationship, then obtain the pairing attribute table of the component, which includes the pairing constraint relationship of the product technical parameters of the component;

[0007] Based on the main attribute table and the paired attribute table, a model parameter table for the component is generated.

[0008] In some embodiments, the step of obtaining the main attribute table of the component specifically includes:

[0009] Collect the product name, product model, manufacturer, and 3D model of the components;

[0010] Collect several product technical parameters of the components;

[0011] Based on the product name, product model, manufacturer, 3D model, and several product technical parameters of the components, a main attribute table is generated.

[0012] In some embodiments, the step of generating the model parameter table of the component based on the main attribute table and the paired attribute table specifically includes:

[0013] Based on the product technical parameters in the main attribute table and several pairing constraints in the pairing attribute table, several matching model parameters for the component are generated.

[0014] The attribute information of the main attribute table is set as the table header, and the model parameters are filled into the table to generate the model parameter table of the component.

[0015] In some embodiments, the step of generating several matching model parameters for the component based on the product technical parameters of the main attribute table and several pairing constraints of the pairing attribute table specifically includes:

[0016] Based on the product technical parameters in the main attribute table and several pairing constraints in the pairing attribute table, several compatible model parameters for the component are generated.

[0017] The compatible model parameters are deduplicated to obtain several matching model parameters.

[0018] In some embodiments, the method further includes:

[0019] Obtain the 3D model generation instruction and display the selectable model parameters based on the model parameter table;

[0020] Collect the parameters of the selected model, and based on the selected model parameters and the basic model of the component, generate 3D models corresponding to the selected model parameters in batches.

[0021] In some embodiments, the step of obtaining the main attribute table of the component specifically includes:

[0022] Collect the attribute information and product technical parameters of the components;

[0023] If the attribute information of the component is determined to be non-empty and the product technical parameters are within a set range, a main attribute table is generated based on the attribute information and the product technical parameters.

[0024] In some embodiments, the method further includes:

[0025] Obtain the first technical parameter, and output the selectable component model based on the first technical parameter and the model parameter table.

[0026] To achieve the above objectives, a second aspect of this application provides a component data generation apparatus based on multiple tables, the apparatus comprising:

[0027] The attribute acquisition module is used to acquire the main attribute table of the component, which includes the attribute information and product technical parameters of the component;

[0028] The constraint acquisition module is used to acquire the pairing attribute table of the component if there is a pairing constraint relationship between the product technical parameters of the component. The pairing attribute table includes the pairing constraint relationship between the product technical parameters of the component.

[0029] The data generation module is used to generate a model parameter table for the component based on the main attribute table and the paired attribute table.

[0030] To achieve the above objectives, a third aspect of this application provides an electronic device, which includes a memory and a processor. The memory stores a computer program, and the processor executes the computer program to implement the above-described multi-table-based component data generation method.

[0031] To achieve the above objectives, a fourth aspect of the present application provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described multi-table-based component data generation method.

[0032] This application proposes a multi-table-based method, apparatus, equipment, and storage medium for generating component data. This method acquires component attribute information and product technical parameters, and generates a component model parameter table based on existing pairing constraints between these parameters. This approach allows manufacturing enterprises to manage component data more efficiently, reduce repetitive work, and improve production efficiency and product quality. Attached Figure Description

[0033] Figure 1 This is a flowchart of a multi-table-based component data generation method provided in an embodiment of this application;

[0034] Figure 2 yes Figure 1 The flowchart of step S101 in the text;

[0035] Figure 3 This is a schematic diagram of the structure of the multi-table-based component data generation device provided in the embodiments of this application;

[0036] Figure 4 This is a schematic diagram of the hardware structure of the electronic device provided in the embodiments of this application. Detailed Implementation

[0037] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0038] It should be noted that although functional modules are divided in the device schematic diagram and a logical order is shown in the flowchart, in some cases, the steps shown or described may be performed in a different order than the module division in the device or the order in the flowchart. The terms "first," "second," etc., in the specification, claims, and the aforementioned drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence.

[0039] Unless otherwise defined, 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 application belongs. The terminology used herein is for the purpose of describing embodiments of this application only and is not intended to limit this application.

[0040] First, let's analyze some of the terms used in this application:

[0041] 3D models: 3D models are models with three-dimensional data constructed using 3D software in a virtual 3D space. They are commonly used in fields such as 3D printing, computer graphics, film, television, video games, and virtual reality. These models define the shape, size, position, and surface properties of objects in a three-dimensional coordinate system through a series of geometric elements such as points, lines, and surfaces. 3D models can represent real-world objects or scenes in great detail, including their shape, texture, color, lighting effects, etc. They can be created using various 3D modeling software, such as Blender, 3ds Max, Maya, Cinema4D, and SketchUp. The process of creating a 3D model typically involves steps such as design, modeling, texture mapping, lighting, and rendering.

[0042] Cloud Server: A cloud server is a virtual server provided based on cloud computing technology, which users can access and use via the internet. Cloud servers use virtualization technology to partition the resources of a physical server (such as CPU, memory, and storage) and allocate them to users on demand. This technology allows users to utilize computing resources flexibly and efficiently without worrying about the maintenance and management of physical servers.

[0043] In today's rapidly developing society, the manufacturing sector is undergoing profound changes. With increasingly diversified and personalized market demands, manufacturing enterprises are gradually moving towards standardization and localization to enhance their competitiveness. In this process, the construction of an industrial basic resource database is particularly important. It is not only a crucial carrier for the accumulation and inheritance of enterprise knowledge but also a key infrastructure for promoting product innovation and technological progress. However, building an industrial basic resource database is no easy task; the workload is immense. Many components play a vital role in the same product, and their key technical parameters are not only numerous but also have complex interrelationships. These relationships may involve multiple disciplines such as mechanics, thermodynamics, and electromagnetism, requiring comprehensive consideration of various factors for accurate description. Therefore, during data construction, a scientific classification system and standardized data models must be established to clearly express these relationships and facilitate subsequent data analysis and application. For a product, there may be thousands of models. Although their 3D models may look similar, they often differ only in dimensional parameters. However, because many manufacturers have not yet adopted parametric modeling technology, each modification to dimensions requires recreating or adjusting the model, significantly increasing the workload of building the engineering database.

[0044] Based on this, embodiments of this application provide a method, apparatus, device, and storage medium for generating component data based on multiple tables, aiming to achieve automatic generation of component model data through a multi-table approach. The method, apparatus, device, and storage medium for generating component data based on multiple tables provided in this application are specifically described through the following embodiments. First, the method for generating component data based on multiple tables in this application is described.

[0045] The component data generation method based on multiple tables provided in this application relates to the field of 3D modeling technology. This method can be applied to a terminal, a server, or software running on either a terminal or a server. In some embodiments, the terminal can be a smartphone, tablet, laptop, desktop computer, etc.; the server can be configured as an independent physical server, a server cluster or distributed system composed of multiple physical servers, or a cloud server providing basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, CDN, and big data and artificial intelligence platforms; the software can implement the component data generation method based on multiple tables, but is not limited to the above forms.

[0046] This application can be used in a wide variety of general-purpose or special-purpose computer system environments or configurations. Examples include: personal computers, server computers, handheld or portable devices, tablet devices, multiprocessor systems, microprocessor-based systems, set-top boxes, programmable consumer electronics, network PCs, minicomputers, mainframe computers, and distributed computing environments including any of the above systems or devices. This application can be described in the general context of computer-executable instructions executed by a computer, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, etc., that perform specific tasks or implement specific abstract data types. This application can also be practiced in distributed computing environments where tasks are performed by remote processing devices connected via a communication network. In distributed computing environments, program modules can reside in local and remote computer storage media, including storage devices.

[0047] It should be noted that in all specific embodiments of this application, when processing data related to user identity or characteristics, such as user information, user behavior data, user historical data, and user location information, user permission or consent will be obtained first. Furthermore, the collection, use, and processing of this data will comply with relevant laws, regulations, and standards. In addition, when embodiments of this application require access to sensitive personal information of users, separate permission or consent from the user will be obtained through pop-ups or redirects to confirmation pages. Only after obtaining the user's separate permission or consent will the necessary user-related data for the normal operation of the embodiments of this application be obtained.

[0048] Figure 1 This is an optional flowchart of the multi-table-based component data generation method provided in the embodiments of this application. Figure 1 The method may include, but is not limited to, steps S101 to S103.

[0049] Step S101: Obtain the main attribute table of the component, wherein the main attribute table includes the attribute information of the component and the product technical parameters;

[0050] Step S102: If the product technical parameters of the component have a pairing constraint relationship, then obtain the pairing attribute table of the component, the pairing attribute table includes the pairing constraint relationship of the product technical parameters of the component;

[0051] Step S103: Based on the main attribute table and the paired attribute table, generate the model parameter table of the component.

[0052] Steps S101 to S103 as shown in the embodiments of this application store the basic information of the components through the main attribute table of the components, store the pairing constraint relationship of the product technical parameters of the components through the pairing attribute table of the components, and finally generate a model parameter table including multiple component model parameters based on the basic information of the components and the pairing constraint relationship of the product technical parameters.

[0053] Specifically, the first step is to obtain the master attribute table of the components. This table forms the foundation of the component data, containing basic attribute information and product technical parameters. If there are pairing constraints between the component's product technical parameters, a pairing attribute table is needed. This table details the pairing constraints between the technical parameters and is crucial for ensuring that the component's performance and function meet requirements. Next, using the data from the master and pairing attribute tables, a model parameter table for the components is generated through specific algorithms and logic. This model parameter table not only contains the component's basic attribute information and product technical parameters but also reflects the pairing constraints between these parameters, representing the final result of the component data generation.

[0054] More specifically, when the product technical parameters of a component do not require confirmation through other attribute associations, a master table approach is used. The master attribute table is divided into two parts: mandatory key attribute information and manufacturer-defined attribute information. Mandatory items include common attributes such as product name, product model, manufacturer information, and 3D model, while manufacturer-defined attributes contain the key technical parameters under the product model. When the product technical parameters of a component have complex pairing relationships, a multi-master table approach is used, combining a master attribute table with other paired attribute tables. The structure of the master attribute table is the same as that of a single master table, while the paired attribute tables are used to establish the constraint relationships between the key technical parameters in the master attribute table.

[0055] In step S101 of some embodiments, referring to Figure 2 Specifically, it includes:

[0056] S1011. Collect the product name, product model, manufacturer, and 3D model of the components;

[0057] S1012. Collect several product technical parameters of the components;

[0058] S1013. Generate a main attribute table based on the product name, product model, manufacturer, 3D model, and several product technical parameters of the component.

[0059] Specifically, in constructing the master attribute table for a component, it is necessary to collect basic information about the component, including product name, product model, manufacturer, and 3D model. The product name is the component's generic or proprietary name, used to uniquely identify the component in the data system; the product model is a unique identifier or number assigned by the manufacturer to a specific component, typically containing information about the component's specifications, performance, or application; the manufacturer is the name of the company or manufacturer that produces or supplies the component; and the 3D model is the component's three-dimensional digital representation used for visualization, analysis, and simulation, and can be CAD files, STL files, or other formats of 3D data. Simultaneously, multiple technical parameters of the component also need to be collected. The master attribute table is generated by integrating the previously collected basic information and technical parameters into a single table.

[0060] In some embodiments, step S103 specifically includes:

[0061] Based on the product technical parameters in the main attribute table and several pairing constraints in the pairing attribute table, several matching model parameters for the component are generated.

[0062] The attribute information of the main attribute table is set as the table header, and the model parameters are filled into the table to generate the model parameter table of the component.

[0063] Specifically, during the generation of the model parameter table, pairing constraints define the interdependencies and limitations between technical parameters in the main attribute table. For example, a dimensional parameter may be constrained by another dimensional parameter or material parameter, or certain performance parameters must vary within a specific range to maintain the overall performance of the component. Based on these constraints, the system generates matching model parameters by calculating or selecting values ​​that meet the conditions. These parameters may include different sizes, power, speeds, capacities, etc., to meet the needs of different customers or application scenarios. After generating the matching model parameters, the next step is to organize this information into a structured table, namely the model parameter table. This table will serve as one of the final deliverables of the component data construction, for use in subsequent design, production, and procurement stages. The header of the model parameter table will contain key attribute information from the main attribute table, such as product name, product model, manufacturer, and 3D model. Below the header, the system will populate the corresponding data based on the generated matching model parameters. Each model or specification will correspond to one row of data, containing all the key parameters and attribute values ​​for that model or specification. Through these two steps, the system can generate model parameter tables for parts based on the main attribute table and the paired attribute table, providing accurate and reliable data support for all aspects of the manufacturing industry.

[0064] In some embodiments, the step of generating several matching model parameters for the component based on the product technical parameters of the main attribute table and several pairing constraints of the pairing attribute table specifically includes:

[0065] Based on the product technical parameters in the main attribute table and several pairing constraints in the pairing attribute table, several compatible model parameters for the component are generated.

[0066] The compatible model parameters are deduplicated to obtain several matching model parameters.

[0067] Specifically, in generating matching model parameters, the system first filters out all potential model parameters that meet the requirements of the technical parameters in the main attribute table. Next, the system further verifies these potential model parameters based on the pairing constraints in the pairing attribute table. Only model parameters that simultaneously satisfy both the technical parameters and the pairing constraints are considered compatible model parameters. After generating compatible model parameters, duplicate or similar model parameters may be found. To avoid data redundancy and confusion, the system needs to deduplicate these compatible model parameters. The deduplication logic can be defined according to specific application scenarios and requirements. Generally, the system compares the fields of different model parameters. If two or more model parameters have the same or very similar values ​​in all key fields, they are considered duplicates, and one is retained as a representative. After deduplication, the system obtains a set of unique and accurate matching model parameters. These model parameters will serve as an important component of the component data for subsequent design, production, and procurement processes.

[0068] In some embodiments, the method further includes:

[0069] Obtain the 3D model generation instruction and display the selectable model parameters based on the model parameter table;

[0070] Collect the parameters of the selected model, and based on the selected model parameters and the basic model of the component, generate 3D models corresponding to the selected model parameters in batches.

[0071] Specifically, upon receiving a 3D model generation instruction, the system dynamically displays a set of optional model parameters based on the previously generated model parameter table. These optional model parameters represent different models or specifications of the parts, which the user can select according to their needs. After the optional model parameters are displayed, the user can select one or more model parameters. The system collects these selected model parameters and, based on them and the basic model of the parts, generates corresponding 3D models in batches. The basic model is a fundamental 3D representation of the parts, containing the main structure and shape of the parts, but may not include specific dimensions, details, or configurations. This model forms the basis for generating specific model models. Simultaneously, the system uses parametric modeling technology to adjust and optimize the basic model according to the specific values ​​in the selected model parameters. In this way, each generated 3D model accurately reflects the characteristics and requirements of the corresponding model parameter. Since users may select multiple model parameters for generation, the system needs to support batch processing. This means that the system can automatically perform the above modeling process for each selected model parameter and output the corresponding 3D model file.

[0072] In some embodiments, the step of obtaining the main attribute table of the component specifically includes:

[0073] Collect the attribute information and product technical parameters of the components;

[0074] If the attribute information of the component is determined to be non-empty and the product technical parameters are within a set range, a main attribute table is generated based on the attribute information and the product technical parameters.

[0075] Specifically, in acquiring the master attribute table of components, the system collects the component's attribute information and product technical parameters. Attribute information typically includes basic component information such as product name, model number, and manufacturer, used to identify and describe the component. Product technical parameters provide more specific details about the component's performance, dimensions, materials, weight, and other key characteristics. After data collection, the system performs a series of data verifications and checks to ensure data integrity and validity. Specifically, the system confirms that component attribute information, such as product name and model number, is not empty. Simultaneously, the system checks whether the product technical parameters are within a set valid range. The range of technical parameters is determined based on industry standards, design requirements, or empirical values ​​to ensure that the component's performance and specifications meet specific requirements. After confirming data validity, the system generates a master attribute table based on the attribute information and product technical parameters. The master attribute table is a structured data table containing all the component's key attribute information and technical parameters. Through this step, the system ensures that the data in the acquired master attribute table is complete, accurate, and valid, thereby improving the reliability and efficiency of the entire data processing flow.

[0076] In some embodiments, the method further includes:

[0077] Obtain the first technical parameter, and output the selectable component model based on the first technical parameter and the model parameter table.

[0078] Specifically, after obtaining the part model parameter table, the system can output the corresponding part model and its parameters that meet the user's requirements based on the user's constraints on the product's technical parameters. The system needs to obtain the first technical parameters provided by the user or other systems. These technical parameters can be any indicators related to the performance of the parts, such as size, weight, power, speed, and material properties. Users may provide these technical parameters as filtering conditions based on their needs or application scenarios. After obtaining the first technical parameters, the system will match them with the model parameter table, which is a data table containing multiple part models and their corresponding technical parameters. The system will search the model parameter table for all part models that meet the requirements of the first technical parameter. After matching, the system will output all part models that meet the requirements of the first technical parameter as optional models. These optional models can be arranged in a certain order for the user to select and further operate. In actual use, it is not limited to only one technical parameter; users can select multiple technical parameters according to their needs to filter out the part models that meet their requirements. This step allows users to quickly select the model that meets their needs from a large number of component models, improving the efficiency and accuracy of selection. At the same time, it also provides strong support for subsequent procurement, design, or production processes.

[0079] Please see Figure 3 This application also provides a component data generation device based on multiple tables, the device comprising:

[0080] The attribute acquisition module 101 is used to acquire the main attribute table of the component, which includes the attribute information and product technical parameters of the component;

[0081] The constraint acquisition module 102 is used to acquire the pairing attribute table of the component if there is a pairing constraint relationship between the product technical parameters of the component. The pairing attribute table includes the pairing constraint relationship between the product technical parameters of the component.

[0082] The data generation module 103 is used to generate a model parameter table for the component based on the main attribute table and the paired attribute table.

[0083] The specific implementation of the multi-table-based component data generation device is basically the same as the specific implementation of the multi-table-based component data generation method described above, and will not be repeated here.

[0084] Please see Figure 4 , Figure 4 The hardware structure of an electronic device according to another embodiment is illustrated. The electronic device includes:

[0085] The processor 401 can be implemented using a general-purpose CPU (Central Processing Unit), microprocessor, application-specific integrated circuit (ASIC), or one or more integrated circuits, and is used to execute relevant programs to implement the technical solutions provided in the embodiments of this application.

[0086] The memory 402 can be implemented as a read-only memory (ROM), static storage device, dynamic storage device, or random access memory (RAM). The memory 402 can store the operating system and other applications. When the technical solutions provided in the embodiments of this specification are implemented through software or firmware, the relevant program code is stored in the memory 402 and is called and executed by the processor 401 to execute the multi-table-based component data generation method of the embodiments of this application.

[0087] Input / output interface 403 is used to implement information input and output;

[0088] The communication interface 404 is used to enable communication and interaction between this device and other devices. Communication can be achieved through wired means (such as USB, network cable, etc.) or wireless means (such as mobile network, WIFI, Bluetooth, etc.).

[0089] Bus 405 transmits information between various components of the device (e.g., processor 401, memory 402, input / output interface 403, and communication interface 404);

[0090] The processor 401, memory 402, input / output interface 403 and communication interface 404 are connected to each other within the device via bus 405.

[0091] This application also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described multi-table-based component data generation method.

[0092] Memory, as a non-transitory computer-readable storage medium, can be used to store non-transitory software programs and non-transitory computer-executable programs. Furthermore, memory may include high-speed random access memory, and may also include non-transitory memory, such as at least one disk storage device, flash memory device, or other non-transitory solid-state storage device. In some embodiments, memory may optionally include memory remotely located relative to the processor, and these remote memories can be connected to the processor via a network. Examples of such networks include, but are not limited to, the Internet, intranets, local area networks, mobile communication networks, and combinations thereof.

[0093] The component data generation method, device, electronic device, and storage medium based on multiple tables provided in this application embodiment store basic information of components through a main attribute table, store the pairing constraint relationship of product technical parameters of components through a pairing attribute table, and finally generate a model parameter table including multiple component model parameters based on the basic information of components and the pairing constraint relationship of product technical parameters. This allows for more efficient management of component data, reduces repetitive work, and improves production efficiency and product quality.

[0094] The embodiments described in this application are for the purpose of more clearly illustrating the technical solutions of the embodiments of this application, and do not constitute a limitation on the technical solutions provided in the embodiments of this application. Those skilled in the art will know that with the evolution of technology and the emergence of new application scenarios, the technical solutions provided in the embodiments of this application are also applicable to similar technical problems.

[0095] Those skilled in the art will understand that the technical solutions shown in the figures do not constitute a limitation on the embodiments of this application, and may include more or fewer steps than shown, or combine certain steps, or different steps.

[0096] Those skilled in the art will understand that all or some of the steps in the methods disclosed above, as well as the functional modules / units in the systems and devices, can be implemented as software, firmware, hardware, or suitable combinations thereof.

[0097] The terms “first,” “second,” “third,” “fourth,” etc. (if present) in the specification and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms “comprising” and “having,” and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0098] It should be understood that in this application, "at least one (item)" means one or more, and "more than" means two or more. "And / or" is used to describe the relationship between related objects, indicating that three relationships can exist. For example, "A and / or B" can represent three cases: only A exists, only B exists, and both A and B exist simultaneously, where A and B can be singular or plural. The character " / " generally indicates that the preceding and following related objects are in an "or" relationship. "At least one (item) of the following" or similar expressions refer to any combination of these items, including any combination of single or plural items. For example, at least one (item) of a, b, or c can represent: a, b, c, "a and b", "a and c", "b and c", or "a and b and c", where a, b, and c can be single or multiple.

[0099] In the several embodiments provided in this application, it should be understood that the disclosed apparatus and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of the units described above is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between apparatuses or units may be electrical, mechanical, or other forms.

[0100] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0101] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes multiple instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this application. The aforementioned storage medium includes various media capable of storing programs, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0102] The preferred embodiments of the present application have been described above with reference to the accompanying drawings, but this does not limit the scope of the claims of the present application. Any modifications, equivalent substitutions, and improvements made by those skilled in the art without departing from the scope and substance of the embodiments of the present application shall be within the scope of the claims of the present application.

Claims

1. A method for generating component data based on multiple tables, characterized in that, The method includes: Obtain the main attribute table of the component. The main attribute table includes the attribute information and product technical parameters of the component. The main attribute table is divided into two parts: the key attribute information of the required items and the manufacturer-defined attribute information. The key attribute information of the required items includes the product name, product model, manufacturer information, and 3D model. The manufacturer-defined attribute information includes the technical parameters under the product model. If the product technical parameters of the component have a pairing constraint relationship, then obtain the pairing attribute table of the component, which includes the pairing constraint relationship of the product technical parameters of the component; Based on the main attribute table and the paired attribute table, a model parameter table for the component is generated, including: Based on the product technical parameters of the main attribute table and several pairing constraints of the pairing attribute table, several matching model parameters of the component are generated, including: based on the product technical parameters of the main attribute table and several pairing constraints of the pairing attribute table, several compatible model parameters of the component are generated; the compatible model parameters are deduplicated to obtain several matching model parameters. Set the attribute information of the main attribute table as the table header, fill the model parameters into the table, and generate the model parameter table of the component; Obtain the first technical parameter, and output the selectable component model based on the first technical parameter and the model parameter table; Obtain the 3D model generation instruction and display the selectable model parameters based on the model parameter table; Collect the parameters of the selected model. Based on the parameters of the selected model and the basic model of the component, use parametric modeling technology to adjust and optimize the basic model of the component according to the specific values ​​in the parameters of the selected model, and generate 3D models corresponding to the parameters of the selected model in batches.

2. The method for generating component data based on multiple tables according to claim 1, characterized in that, The step of obtaining the main attribute table of the component specifically includes: Collect the product name, product model, manufacturer, and 3D model of the components; Collect several product technical parameters of the components; Based on the product name, product model, manufacturer, 3D model, and several product technical parameters of the components, a main attribute table is generated.

3. The method for generating component data based on multiple tables according to claim 1, characterized in that, The step of obtaining the main attribute table of the component specifically includes: Collect the attribute information and product technical parameters of the components; If the attribute information of the component is determined to be non-empty and the product technical parameters are within a set range, a main attribute table is generated based on the attribute information and the product technical parameters.

4. A component data generation device based on multiple tables, characterized in that, The device includes: The attribute acquisition module is used to acquire the main attribute table of the parts. The main attribute table includes the attribute information and product technical parameters of the parts. The main attribute table is divided into two parts: the key attribute information of the required items and the manufacturer-defined attribute information. The key attribute information of the required items includes the product name, product model, manufacturer information, and 3D model. The manufacturer-defined attribute information includes the technical parameters under the product model. The constraint acquisition module is used to acquire the pairing attribute table of the component if there is a pairing constraint relationship between the product technical parameters of the component. The pairing attribute table includes the pairing constraint relationship between the product technical parameters of the component. The data generation module is used to generate a model parameter table for the component based on the main attribute table and the paired attribute table, including: generating several matching model parameters for the component based on the product technical parameters of the main attribute table and several paired constraint relationships of the paired attribute table; generating several compatible model parameters for the component based on the product technical parameters of the main attribute table and several paired constraint relationships of the paired attribute table; deduplicating the compatible model parameters to obtain several matching model parameters; setting the attribute information of the main attribute table as the table header, filling the table with the model parameters, and generating the model parameter table for the component. The device is also configured to acquire first technical parameters, output optional component models based on the first technical parameters and the model parameter table; acquire 3D model generation instructions, display optional model parameters based on the model parameter table; collect selected model parameters, and based on the selected model parameters and the basic model of the component, use parametric modeling technology to adjust and optimize the basic model of the component according to the specific values ​​in the selected model parameters, and batch generate 3D models corresponding to the selected model parameters.

5. An electronic device, characterized in that, The electronic device includes a memory and a processor. The memory stores a computer program, and when the processor executes the computer program, it implements the multi-table-based component data generation method according to any one of claims 1 to 3.

6. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it implements the multi-table-based component data generation method according to any one of claims 1 to 3.

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