Digital pattern construction system for three-dimensional woven preform equipment

Abstract

The present application relates to a kind of digital mockup construction system for three-dimensional woven preform equipment, the system includes the construction method of five different models and the construction method of four kinds of associations between models, the construction of five different models is physical modeling, data modeling, action modeling, process modeling, simulation, four kinds of associations between models are respectively associated with data, the association of motion model and physical three-dimensional model and data model, the association of process model and motion model and data model, the association of simulation result and data model.This method constructs virtual production process twin model, and carries out two-way real-time interaction with physical production process, utilizes the dynamic update of simulation model driven by multi-source data, standardizes the construction process of digital mockup, realizes real-time monitoring to production process, improves the utilization of data, realizes closed-loop feedback and process optimization.

Description

Technical Field

[0001] This invention relates to a digital prototype construction method, specifically to a digital prototype construction system for three-dimensional woven prefabricated body equipment, belonging to the field of digital twin technology. Background Technology

[0002] The concept of digital twins was first proposed by Professor Grieves of the University of Michigan in 2003, initially called the "Mirrored Spaces Model" (MSM). This concept is defined as an object, its digital mirror image, and the connections between them. In 2010, NASA applied the digital twin concept to the simulation and prediction of the entire lifecycle of spacecraft. Since then, digital twins have received widespread attention, and related theories and technologies have developed rapidly. Vanderhorn and Mahadevan proposed a unified and generalized definition of digital twins: a virtual representation of a physical system and its associated environment and processes that is updated through information exchange between the physical and virtual systems.

[0003] In industrial production, process simulation is a crucial tool for improving product quality and optimizing process design. Traditional process simulation methods primarily rely on offline modeling, static analysis, and laboratory testing, which suffer from limitations such as insufficient real-time performance, low data utilization, and a lack of closed-loop feedback. The introduction of digital twin technology offers a new solution for process simulation. By combining the physical production process with a virtual simulation model and using real-time data to drive the dynamic updates of the simulation model, real-time monitoring, process optimization, and predictive analysis of the production process can be achieved. This significantly improves production efficiency, optimizes resource utilization, and effectively enhances the consistency and reliability of product quality. Summary of the Invention

[0004] This invention addresses the problems existing in the prior art by providing a digital prototype construction system for 3D woven prefabricated equipment. It simulates and analyzes physical entities or systems by constructing virtual digital models, reproducing the production process in a virtual environment, and simulating the processes within the production process. Based on the simulation results, the design is adjusted and the production process is optimized. The system comprises five modules: physical modeling, data modeling, motion modeling, process modeling, and simulation. These modules are interconnected, including the relationship between the physical model and data, the relationship between the motion model and the physical 3D model and data model, the relationship between the process model and the motion model and data model, and the relationship between simulation results and the data model. This solution constructs a virtual production process twin model that interacts bidirectionally and in real-time with the physical production process. It utilizes multi-source data to drive the dynamic updates of the simulation model, standardizes the digital prototype construction process, achieves real-time monitoring of the production process, improves data utilization, and realizes closed-loop feedback and process optimization.

[0005] 1) By constructing a three-dimensional geometric model consistent with the real production equipment through physical modeling and clarifying the material properties, the subsequent simulation process can more accurately reflect the physical behavior of real materials under different working conditions, realize the simulation and visualization of the production scene, and provide staff with a safe and efficient virtual simulation environment.

[0006] 2) Through data modeling, the production process is fully digitally simulated and optimized. Precise digital models of equipment are built using equipment data to simulate their physical performance; dynamic operations of equipment and workpieces are simulated using production data; and product quality performance is monitored in real time using quality data to locate potential quality defects.

[0007] 3) By connecting the 3D model with production data, the dynamic characteristics of each component in the 3D model can be accurately identified and monitored in real time; by connecting equipment data and quality data with the material properties of the model, the material characteristics and quality performance in the model can be located and tracked.

[0008] 4) By using motion modeling, a motion model that is consistent with the actual equipment motion is constructed, which can enable a specified moving object to perform simulated motion according to the set parameters.

[0009] 5) By connecting the motion model with the physical 3D model, the moving parts in the production process were identified; by connecting the motion model with the data model, the motion parameter items were identified.

[0010] 6) Through process modeling, a structured, dynamically adjustable process model that is closely coupled with the actual production process was constructed, which can realize high-precision reproduction and optimization of the entire production process in the digital twin simulation model.

[0011] 7) By connecting the process model and the motion model, the motion sequence and cycle time were clarified; by connecting the process model and the data model, the production data and quality data were clarified.

[0012] 8) Through process simulation, the rationality and stability of the production process design can be verified; through product quality simulation, the product quality characteristics can be predicted.

[0013] 9) By linking simulation results with data models, references and guidance can be provided for further production process improvements, potential product quality problems can be identified, and preventive quality control can be carried out.

[0014] To achieve the above objectives, the technical solution of this invention is as follows: a digital prototype construction system for three-dimensional woven prefabricated equipment. This system simulates and analyzes physical entities or systems by constructing virtual digital models, reproducing the production process in a virtual environment, and simulating the processes involved in the production process. Based on the simulation results, the design is adjusted and the production process is optimized. The system comprises five modules: physical modeling, data modeling, motion modeling, process modeling, and simulation. These modules are interconnected, including the correlation between the physical model and data, the correlation between the motion model and the physical 3D model and data model, the correlation between the process model and the motion model and data model, and the correlation between the simulation results and the data model. Specifically, the construction part includes physical modeling. Through physical modeling, a three-dimensional geometric model consistent with the actual production equipment is constructed, and the material properties are clarified. This allows the subsequent simulation process to more accurately reflect the physical behavior of real materials under different working conditions, achieving the simulation and visualization of the production scene and providing workers with a safe and efficient virtual simulation environment.

[0015] 1) Constructing a 3D model

[0016] a) Collect information such as the size, shape and structure of the equipment, draw sketches of the parts in modeling software, generate three-dimensional shapes through functions such as stretching and rotating, and perform detailed processing, such as chamfering or rounding.

[0017] b) Import the part model into the assembly environment, apply constraints to complete the assembly, check for interference and verify the motion function, and finally output it in a suitable file format to support further analysis and application.

[0018] 2) Assign materials to the 3D model and specify the material properties.

[0019] a) Select appropriate materials from the material library of the modeling software, and assign materials to the 3D model according to the design requirements and application scenarios of the model.

[0020] b) Define detailed property parameters for the model material, including but not limited to elastic modulus, Poisson's ratio, stiffness, hardness, and tensile strength.

[0021] The construction includes data modeling, which enables comprehensive digital simulation and optimization of the production process. It utilizes equipment data to build accurate digital models of equipment and simulate their physical performance; it uses production data to simulate the dynamic operation of equipment and workpieces; and it uses quality data to monitor product quality performance in real time and locate potential quality defects.

[0022] 1) Clearly define the data items and data types, and list the key data items in the production process, such as equipment data such as stiffness, voltage, mass, and running time, production data such as speed, acceleration, and displacement, and quality data such as product quality parameters; clearly define the representation format of each data item, such as integer type, floating-point type, status type, etc.

[0023] 2) Create forms in the database to systematically store and manage data, ensuring that the form structure can effectively support fast data retrieval and flexible updates.

[0024] 3) Complete the entity class construction and corresponding service interface writing in Java code, so that each data item has a clear object representation in the software system, and develop matching service interfaces to support data access and operation.

[0025] The construction includes the association between the physical model and the data. By connecting the 3D model with production data, the dynamic characteristics of each component in the 3D model can be accurately identified and monitored in real time. By connecting equipment data and quality data with the material properties of the model, the material properties and quality performance in the model can be located and tracked.

[0026] 1) Associate specific components in the 3D model with the table name of the production data form and dynamically bind them with the production data items. The production data form includes production data items such as acceleration, velocity, and displacement.

[0027] 2) The material properties of the 3D model are associated with the equipment and quality data form content through the form name. The material properties and quality data items are dynamically bound and connected with the specific values ​​of the equipment data. The equipment and quality data forms include equipment data such as mass, stiffness, and voltage, as well as quality data items such as product quality parameters.

[0028] The construction includes motion modeling, which builds a motion model that is consistent with the actual equipment motion, enabling a specified moving object to perform simulated motion according to set parameters.

[0029] 1) Define moving parts and pre-set interfaces or placeholders for them.

[0030] 2) Design motion patterns and write motion functions to simulate the motion behavior of actual production equipment components.

[0031] 3) Design motion parameters to provide a parameter framework and interface for subsequent production simulation.

[0032] The construction process includes the connection between the motion model, the physical 3D model, and the data model. By connecting the motion model with the physical 3D model, the moving parts in the production process are identified; and by connecting the motion model with the data model, the motion parameter entries are identified.

[0033] 1) By using the names of the components in the 3D model, the interfaces preset for moving parts in the motion model can be matched with the components in the 3D model.

[0034] 2) Based on the connection between the physical model and the data, the names of the components in the 3D model can be associated with the corresponding table names in the production data form, thus realizing the connection between the motion parameters in the motion model and the production data items in the data model.

[0035] The construction includes process modeling, which creates a structured, dynamically adjustable process model that is closely coupled with the actual production process. This allows for high-precision reproduction and optimization of the entire production process within the digital twin simulation model.

[0036] 1) Analyze the process card and extract key information, including processing steps, working conditions such as stress and constraints, equipment data, production data, quality data, and operating procedures.

[0037] 2) Determine the sequence of process actions, analyze the logical relationships between different process actions (including parallel relationships, conflict relationships, etc.), and arrange the execution order of each process step.

[0038] 3) Determine the cycle time of the process actions. Refer to the process requirements and equipment performance to determine the execution time of each process action. For process actions that need to be repeated, clarify their cycle frequency requirements.

[0039] The construction includes the connection between the process model, motion model, and data model. By connecting the process model and motion model, the motion sequence and cycle time are clarified; by connecting the process model and data model, the production data and quality data are clarified.

[0040] 1) Connect the process actions in the process model with the specific motion functions in the motion model.

[0041] 2) Through the form interface built in the data model, the specific production data and quality data in the process model are populated into the production data and quality data forms in the data model.

[0042] The construction includes a simulation process, which verifies the rationality and stability of the production process design through process motion simulation; and it enables the prediction of product quality characteristics through product quality simulation.

[0043] 1) Based on the physical model, data model, motion model, process model and the relationship between the models, the simulation of process actions can be realized, which can detect whether the design of process actions in the production process is reasonable and identify potential deviations and interference problems.

[0044] 2) Product quality simulation solution

[0045] The physical model provides a three-dimensional geometric model with physical properties, while the process model provides loads and constraints for the physical model to simulate the actual working environment. CAE tools are used to carry out simulation calculations to obtain data related to product quality, such as stress and strain.

[0046] The construction includes the correlation between simulation results and data models. By correlating the simulation results with the data models, references and guidance can be provided for further production process improvements, potential product quality problems can be identified, and preventive quality control can be carried out.

[0047] 1) The quality information data obtained from the product quality simulation through finite element analysis is displayed in a visual graphical format.

[0048] 2) Based on the connection between the process model and the data model, the specific quality data in the process model has been filled into the quality data form in the data model. The quality information data obtained from the product quality simulation is compared and analyzed with the product quality parameters in the quality data form in the data model.

[0049] Five models and four associations together constitute a digital prototype construction method for three-dimensional woven prefabricated equipment, realizing dynamic simulation and analysis of the entire production process.

[0050] Compared with existing technologies, this invention has the following advantages: the five different models and four associated construction methods explored in this technical solution can provide guiding suggestions for the construction of digital prototypes. At the same time, the method standardizes the construction process of digital prototypes, and by monitoring key data in the production process in real time, it can fully improve the efficiency of data collection, analysis and utilization, and realize closed-loop feedback and production process optimization. Attached Figure Description

[0051] Figure 1 A schematic diagram illustrating the construction method of a digital prototype for a three-dimensional woven prefabricated body equipment.

[0052] Figure 2 This relates the physical model to the data.

[0053] Figure 3 This relates the motion model to the physical model and the data model.

[0054] Figure 4 This relates the process model to the motion model and the data model.

[0055] Figure 5 To establish the correlation between simulation results and data models. Detailed Implementation

[0056] To enhance understanding of the present invention, the embodiments will be described in detail below with reference to the accompanying drawings.

[0057] Example 1: See Figure 1 A digital prototype construction system for 3D woven prefabrication equipment includes the following nine parts:

[0058] 1) By constructing a three-dimensional geometric model consistent with the real production equipment through physical modeling and clarifying the material properties, the subsequent simulation process can more accurately reflect the physical behavior of real materials under different working conditions, realize the simulation and visualization of the production scene, and provide staff with a safe and efficient virtual simulation environment.

[0059] 2) Through data modeling, the production process is fully digitally simulated and optimized. Precise digital models of equipment are built using equipment data to simulate their physical performance; dynamic operations of equipment and workpieces are simulated using production data; and product quality performance is monitored in real time using quality data to locate potential quality defects.

[0060] 3) By connecting the 3D model with production data, the dynamic characteristics of each component in the 3D model can be accurately identified and monitored in real time; by connecting equipment data and quality data with the material properties of the model, the material characteristics and quality performance in the model can be located and tracked.

[0061] 4) By using motion modeling, a motion model that is consistent with the actual equipment motion is constructed, which can enable a specified moving object to perform simulated motion according to the set parameters.

[0062] 5) By connecting the motion model with the physical 3D model, the moving parts in the production process were identified; by connecting the motion model with the data model, the motion parameter items were identified.

[0063] 6) Through process modeling, a structured, dynamically adjustable process model that is closely coupled with the actual production process was constructed, which can realize high-precision reproduction and optimization of the entire production process in the digital twin simulation model.

[0064] 7) By connecting the process model and the motion model, the motion sequence and cycle time were clarified; by connecting the process model and the data model, the production data and quality data were clarified.

[0065] 8) Through process simulation, the rationality and stability of the production process design can be verified; through product quality simulation, the product quality characteristics can be predicted.

[0066] 9) By linking simulation results with data models, references and guidance can be provided for further production process improvements, potential product quality problems can be identified, and preventive quality control can be carried out.

[0067] The construction includes physical modeling, which creates a three-dimensional geometric model consistent with the real production equipment and clarifies the material properties. This allows the subsequent simulation process to more accurately reflect the physical behavior of real materials under different working conditions, realize the simulation and visualization of production scenarios, and provide staff with a safe and efficient virtual simulation environment.

[0068] 1) Constructing a 3D model

[0069] a) Collect information such as the size, shape and structure of the equipment, draw sketches of the parts in modeling software, generate three-dimensional shapes through functions such as stretching and rotating, and perform detailed processing, such as chamfering or rounding.

[0070] b) Import the part model into the assembly environment, apply constraints to complete the assembly, check for interference and verify the motion function, and finally output it in a suitable file format to support further analysis and application.

[0071] 2) Assign materials to the 3D model and specify the material properties.

[0072] a) Select appropriate materials from the material library of the modeling software, and assign materials to the 3D model according to the design requirements and application scenarios of the model.

[0073] b) Define detailed property parameters for the model material, including but not limited to elastic modulus, Poisson's ratio, stiffness, hardness, and tensile strength.

[0074] The construction includes data modeling, which enables comprehensive digital simulation and optimization of the production process. It utilizes equipment data to build accurate digital models of equipment and simulate their physical performance; it uses production data to simulate the dynamic operation of equipment and workpieces; and it uses quality data to monitor product quality performance in real time and locate potential quality defects.

[0075] 1) Clearly define the data items and data types, and list the key data items in the production process, such as equipment data such as stiffness, voltage, mass, and running time, production data such as speed, acceleration, and displacement, and quality data such as product quality parameters; clearly define the representation format of each data item, such as integer type, floating-point type, status type, etc.

[0076] 2) Create forms in the database to systematically store and manage data, ensuring that the form structure can effectively support fast data retrieval and flexible updates.

[0077] 3) Complete the entity class construction and corresponding service interface writing in Java code, so that each data item has a clear object representation in the software system, and develop matching service interfaces to support data access and operation.

[0078] The construction includes the association between the physical model and the data. By connecting the 3D model with production data, the dynamic characteristics of each component in the 3D model can be accurately identified and monitored in real time. By connecting equipment data and quality data with the material properties of the model, the material properties and quality performance in the model can be located and tracked.

[0079] 1) Associate specific components in the 3D model with the table name of the production data form and dynamically bind them with the production data items. The production data form includes production data items such as acceleration, velocity, and displacement.

[0080] 2) The material properties of the 3D model are associated with the equipment and quality data form content through the form name. The material properties and quality data items are dynamically bound and connected with the specific values ​​of the equipment data. The equipment and quality data forms include equipment data such as mass, stiffness, and voltage, as well as quality data items such as product quality parameters.

[0081] The construction includes motion modeling, which builds a motion model that is consistent with the actual equipment motion, enabling a specified moving object to perform simulated motion according to set parameters.

[0082] 1) Define moving parts and pre-set interfaces or placeholders for them.

[0083] 2) Design motion patterns and write motion functions to simulate the motion behavior of actual production equipment components.

[0084] 3) Design motion parameters to provide a parameter framework and interface for subsequent production simulation.

[0085] The construction process includes the connection between the motion model, the physical 3D model, and the data model. By connecting the motion model with the physical 3D model, the moving parts in the production process are identified; and by connecting the motion model with the data model, the motion parameter entries are identified.

[0086] 1) By using the names of the components in the 3D model, the interfaces preset for moving parts in the motion model can be matched with the components in the 3D model.

[0087] 2) Based on the connection between the physical model and the data, the names of the components in the 3D model can be associated with the corresponding table names in the production data form, thus realizing the connection between the motion parameters in the motion model and the production data items in the data model.

[0088] The construction includes process modeling, which creates a structured, dynamically adjustable process model that is closely coupled with the actual production process. This allows for high-precision reproduction and optimization of the entire production process within the digital twin simulation model.

[0089] 1) Analyze the process card and extract key information, including processing steps, working conditions such as stress and constraints, equipment data, production data, quality data, and operating procedures.

[0090] 2) Determine the sequence of process actions, analyze the logical relationships between different process actions (including parallel relationships, conflict relationships, etc.), and arrange the execution order of each process step.

[0091] 3) Determine the cycle time of the process actions. Refer to the process requirements and equipment performance to determine the execution time of each process action. For process actions that need to be repeated, clarify their cycle frequency requirements.

[0092] The construction includes the connection between the process model, motion model, and data model. By connecting the process model and motion model, the motion sequence and cycle time are clarified; by connecting the process model and data model, the production data and quality data are clarified.

[0093] 1) Connect the process actions in the process model with the specific motion functions in the motion model.

[0094] 2) Through the form interface built in the data model, the specific production data and quality data in the process model are populated into the production data and quality data forms in the data model.

[0095] The construction includes a simulation process, which verifies the rationality and stability of the production process design through process motion simulation; and it enables the prediction of product quality characteristics through product quality simulation.

[0096] 1) Based on the physical model, data model, motion model, process model and the relationship between the models, the simulation of process actions can be realized, which can detect whether the design of process actions in the production process is reasonable and identify potential deviations and interference problems.

[0097] 2) Product quality simulation solution

[0098] The physical model provides a three-dimensional geometric model with physical properties, while the process model provides loads and constraints for the physical model to simulate the actual working environment. CAE tools are used to carry out simulation calculations to obtain data related to product quality, such as stress and strain.

[0099] The construction includes the correlation between simulation results and data models. By correlating the simulation results with the data models, references and guidance can be provided for further production process improvements, potential product quality problems can be identified, and preventive quality control can be carried out.

[0100] 1) The quality information data obtained from the product quality simulation through finite element analysis is displayed in a visual graphical format.

[0101] 2) Based on the connection between the process model and the data model, the specific quality data in the process model has been filled into the quality data form in the data model. The quality information data obtained from the product quality simulation is compared and analyzed with the product quality parameters in the quality data form in the data model.

[0102] Five models and four associations together constitute a digital prototype construction method for three-dimensional woven prefabricated equipment, realizing dynamic simulation and analysis of the entire production process.

[0103] The technical solution explores five different models and four related construction methods, which can provide guiding suggestions for the construction of digital prototypes. At the same time, the method standardizes the construction process of digital prototypes, and by monitoring key data in the production process in real time, it can fully improve the efficiency of data collection, analysis and utilization, and realize closed-loop feedback and production process optimization.

[0104] Example 2:

[0105] Figures 2-5 As shown, taking a three-dimensional woven prefabricated body equipment of a glass fiber research institute as an example, this paper illustrates the digital prototype construction method for three-dimensional woven prefabricated body equipment. The construction includes physical modeling. Through physical modeling, a three-dimensional geometric model consistent with the real production equipment is constructed and the material properties are clarified. This allows the subsequent simulation process to more accurately reflect the physical behavior of real materials under different working conditions, realize the simulation and visualization of production scenarios, and provide staff with a safe and efficient virtual simulation environment.

[0106] 1) Constructing a 3D model

[0107] a) Collect information on the size, shape, and structure of the 3D woven prefabricated equipment, draw part sketches in the modeling software SolidWorks, generate 3D shapes through functions such as stretching and rotating, and perform detail processing, such as chamfering or rounding.

[0108] b) Import various part models into the assembly environment, such as parallel weft insertion reed seats, guide rail positioning plates, limit blocks, parallel weft insertion brackets, connecting shafts, connecting sleeves, connecting rods, connecting rod connecting shafts, etc., and complete the assembly using constraints such as overlap, distance, and width. Check for interference and verify motion functions, and finally output in STEP format to support further analysis and application. 2) Assign materials to the 3D model and define the material property parameters.

[0109] a) In ANSYS software, by selecting the geometry to be assigned material in the Mechanical module, ...

[0110] The “Material Assignment” field assigns existing material names to the selected geometry. Based on the design requirements and application scenario of the model, it assigns appropriate materials to the 3D model without needing to specify the specific property parameters of the materials in advance. If there are no materials in the material library that meet the requirements, you can create a new material and name it by returning to the “EngineeringData” module of Workbench, and then assign the newly added material to the corresponding geometry. For example, aluminum alloy material is assigned to the weft storage system and warp feed frame, iron alloy material is assigned to the jacquard head, 45# steel material is assigned to the support column and traction assembly, and polyester fiber material is assigned to the heddle yarn.

[0111] b) In the "Engineering Data" module of Workbench, define or supplement the property parameters of the materials assigned to the geometry. These parameters include, but are not limited to, elastic modulus, Poisson's ratio, yield strength, tensile strength, elongation, hardness, stiffness, and wear resistance. Once modified, these parameters are automatically applied to the corresponding material in the model. The construction includes data modeling, which performs comprehensive digital simulation and optimization of the production process. It utilizes equipment data to build accurate digital models of equipment, simulating their physical properties; it uses production data to simulate the dynamic operation of equipment and workpieces; and it uses quality data to monitor product quality performance in real time and locate potential quality defects.

[0112] 1) Clearly define data items and data types, and list key data items in the production process, such as PLC status, weft insertion measurement guide position, jacquard encoder angle, warp feed alarm unit, current weft count, current weft density, weft insertion time, jacquard time, and other equipment data; actual values ​​of rapier position, actual weft selection speed, actual weft insertion torque, actual traction current, and other production data; and quality data such as product quality parameters. Clearly define the representation format of each data item, such as PLC status, current weft density, and actual weft insertion torque as double type, and weft insertion time and jacquard time as time type.

[0113] 2) Create forms in the database to systematically store and manage data, ensuring that the form structure can effectively support fast data retrieval and flexible updates.

[0114] 3) Complete the entity class construction and corresponding service interface writing in Java code, so that each data item has a clear object representation in the software system, and develop matching service interfaces to support data access and operation.

[0115] The construction includes the association between the physical model and the data. By connecting the 3D model with production data, the dynamic characteristics of each component in the 3D model can be accurately identified and monitored in real time. By connecting equipment data and quality data with the material properties of the model, the material properties and quality performance in the model can be located and tracked.

[0116] 1) Associate specific components in the 3D woven prefabricated equipment model with the table names in the production data form. For example, associate the parallel weft insertion reed seat and the weft insertion rapier with the table names "Production Data of Equipment 1" and "Production Data of Equipment 2" respectively. The parallel weft insertion reed seat is dynamically bound to production data items such as weft insertion speed and load force of the weft insertion motor. The weft insertion rapier is dynamically bound to production data items such as rapier speed and clamp switch signal.

[0117] 2) Associate some material attributes contained in the 3D woven prefabricated equipment model with the equipment and quality data form content through form table names. For example, material attribute 1, material attribute 2, and material attribute 3 are linked with the specific values ​​of equipment parameter 1, equipment parameter 2, and equipment parameter 3. Material attribute 4, material attribute 5, and material attribute 6 are dynamically bound to the three quality data items of quality parameter 1, quality parameter 2, and quality parameter 3.

[0118] The construction includes motion modeling, which builds a motion model that is consistent with the actual equipment motion, enabling a specified moving object to perform simulated motion according to set parameters.

[0119] 1) Define moving parts and pre-set interfaces or placeholders for them.

[0120] 2) Design a motion pattern and write a motion function that can realize reciprocating translation to simulate the motion behavior of the parallel weft insertion reed and weft rapier in the three-dimensional woven prefabricated body equipment.

[0121] 3) Design motion parameters to provide a parameter framework and interface for subsequent production simulation.

[0122] The construction process includes the connection between the motion model, the physical 3D model, and the data model. By connecting the motion model with the physical 3D model, the moving parts in the production process are identified; and by connecting the motion model with the data model, the motion parameter entries are identified.

[0123] 1) By using the names of the two components, the parallel weft insertion reed seat and the weft insertion rapier, in the three-dimensional woven prefabricated body equipment, the interfaces preset for the moving parts in the motion model are connected and corresponded with the two components, the parallel weft insertion reed seat and the weft insertion rapier.

[0124] 2) Based on the connection between the physical model and the data, the names of the two components, the parallel weft insertion reed seat and the weft insertion rapier, can be associated with the corresponding table names in the production data form, thus realizing the connection between the motion parameters in the motion model and the production data items such as weft insertion speed and rapier speed in the data model.

[0125] The construction includes process modeling, which creates a structured, dynamically adjustable process model that is closely coupled with the actual production process. This allows for high-precision reproduction and optimization of the entire production process within the digital twin simulation model.

[0126] 1) Analyze the process card and extract key information, including processing steps, working conditions such as stress and constraints, equipment data, production data, quality data, and operating procedures.

[0127] 2) Determine the sequence of process actions and analyze the logical relationships between different process actions (including parallel relationships, conflicting relationships, etc.). For example, the weft insertion action and the weft beat-up action are sequential. Arrange the execution order of each process step, such as processing according to the steps of twisting, winding, installing the yarn spool to the yarn frame to form warp yarn, and introducing the weft yarn into the warp yarn of the jacquard machine through the weft insertion device to form the fabric.

[0128] 3) Determine the cycle time of the process actions. Refer to the process requirements and equipment performance to determine the execution time of each process action. For process actions that need to be repeated, clarify their cycle frequency requirements.

[0129] The construction includes the connection between the process model, motion model, and data model. By connecting the process model and motion model, the motion sequence and cycle time are clarified; by connecting the process model and data model, the production data and quality data are clarified.

[0130] 1) Connect the process actions in the process model with the specific motion functions in the motion model, such as connecting the weft insertion and weft raising actions with the reciprocating translational motion functions in the motion model.

[0131] 2) Through the form interface built in the data model, the specific production data and quality data in the process model are populated into the production data and quality data forms in the data model.

[0132] The construction includes a simulation process, which verifies the rationality and stability of the production process design through process motion simulation; and it enables the prediction of product quality characteristics through product quality simulation.

[0133] 1) Based on the physical model, data model, motion model, process model and the relationship between the models, the simulation of process actions can be realized, which can detect whether the design of process actions in the production process is reasonable and identify potential deviations and interference problems.

[0134] 2) Product quality simulation solution

[0135] The physical model provides a three-dimensional geometric model with physical properties, while the process model provides loads and constraints for the physical model. Loading methods can include point loads, distributed loads, torque loading, etc. Constraints are used to limit the displacement or rotation of model components, thereby constructing a simulation scenario that closely resembles real working conditions. After importing the physical model into CAE software, meshing is performed, and numerical solutions are executed to obtain data related to product quality, such as stress and strain.

[0136] The construction includes the correlation between simulation results and data models. By correlating the simulation results with the data models, references and guidance can be provided for further production process improvements, potential product quality problems can be identified, and preventive quality control can be carried out.

[0137] 1) The quality information data obtained from the product quality simulation through finite element analysis is displayed in a visual graphical format.

[0138] 2) Based on the connection between the process model and the data model, the specific quality data in the process model has been filled into the quality data form in the data model. The quality information data obtained from the product quality simulation is compared and analyzed with the product quality parameters in the quality data form in the data model.

[0139] The above five models and four associations together constitute a digital prototype construction method for three-dimensional woven prefabricated equipment, realizing dynamic simulation and analysis of the entire production process.

[0140] It should be noted that the above embodiments are not intended to limit the scope of protection of the present invention. Equivalent transformations or substitutions made based on the above technical solutions all fall within the scope of protection of the claims of the present invention.

Claims

1. A digital prototype construction system for three-dimensional woven prefabricated body equipment, characterized in that, The system uses virtual digital models to simulate and analyze physical entities or systems, reproduces the production process in a virtual environment, and simulates the processes in the production process. Based on the simulation results, the design is adjusted and the production process is optimized. The system consists of five modules: physical modeling, data modeling, motion modeling, process modeling, and simulation. There are connections between different modules, including the connection between the physical model and the data, the connection between the motion model and the physical 3D model and the data model, the connection between the process model and the motion model and the data model, and the connection between the simulation results and the data model. The physical modeling described above constructs a three-dimensional geometric model consistent with the actual production equipment and clarifies the material properties. This allows subsequent simulation processes to more accurately reflect the physical behavior of real materials under different working conditions, achieving the simulation and visualization of production scenarios. It provides workers with a safe and efficient virtual simulation environment, as detailed below. 1) Constructing a 3D model a) Collect information on the size, shape, and structure of the equipment, draw sketches of the parts in modeling software, generate three-dimensional shapes through functions such as extrusion and rotation, and perform detail processing, including chamfering or filleting. b) Import the part model into the assembly environment, apply constraints to complete the assembly, check for interference and verify the motion function, and finally output it in a suitable file format to support further analysis and application. 2) Assign materials to the 3D model and specify the material properties. a) Select appropriate materials from the modeling software's material library, and assign materials to the 3D model according to the model's design requirements and application scenario. b) Define detailed property parameters for the model material, including elastic modulus, Poisson's ratio, stiffness, hardness, and tensile strength; The data modeling described herein involves comprehensive digital simulation and optimization of the production process. It utilizes equipment data to construct precise digital models of the equipment, simulating its physical performance; it uses production data to simulate the dynamic operation of equipment and workpieces; and it uses quality data to monitor product quality performance in real time and locate potential quality defects. Specifically, as follows: 1) Clearly define data items and data types, listing key data items in the production process, including equipment data such as stiffness, voltage, mass, and runtime; production data such as speed, acceleration, and displacement; and product quality parameters. Specify the representation format of each data item, including integer, floating-point, and status types. 2) Establish forms in the database to systematically store and manage data, ensuring that the form structure effectively supports rapid data retrieval and flexible updates. 3) Complete the entity class construction and corresponding service interface writing in Java code, so that each data item has a clear object representation in the software system, and develop matching service interfaces to support data access and operation; The physical model is linked to the data. By connecting the 3D model with production data, it enables precise identification and real-time monitoring of the dynamic characteristics of each component within the 3D model. Furthermore, by connecting equipment data and quality data with the model's material properties, it enables the location and tracking of material characteristics and quality performance within the model. 1) Associate specific components in the 3D model with the table names in the production data form, and dynamically bind them to the production data items. The production data form includes acceleration, velocity, and displacement production data items. 2) The material properties of the 3D model are associated with the equipment and quality data form content through the form name. The material properties are dynamically bound to the quality data items and connected with the specific values ​​of the equipment data. The equipment and quality data forms include equipment data such as mass, stiffness, and voltage, as well as product quality parameter quality data items. The motion modeling described above constructs a motion model that matches the actual movements of the equipment, enabling a specified moving object to perform simulated motion according to set parameters, as detailed below. 1) Define moving parts and pre-set interfaces or placeholders for them. 2) Design motion patterns and write motion functions to simulate the motion behavior of actual production equipment components. 3) Design motion parameters to provide a parameter framework and interface for subsequent production simulation.

2. The digital pattern building system for a three-dimensional woven preform apparatus of claim 1, wherein, The connection between the motion model, the physical 3D model, and the data model clarifies the moving parts during the production process through the connection between the motion model and the physical 3D model; and clarifies the motion parameter entries through the connection between the motion model and the data model, as detailed below. 1) By using the names of the 3D model components, the interfaces pre-defined for moving parts in the motion model are mapped to the components in the 3D model. 2) Based on the connection between the physical model and the data, the names of the components in the 3D model can be associated with the corresponding table names in the production data form, thus realizing the connection between the motion parameters in the motion model and the production data items in the data model.

3. The digital pattern building system for a three-dimensional woven preform apparatus of claim 2, wherein, The process modeling described above constructs a structured, dynamically adjustable process model that is closely coupled with the actual production process. This model enables high-precision reproduction and optimization of the entire production process within a digital twin simulation model, as detailed below. 1) Analyze the process card and extract key information, including processing steps, stress and constraint conditions, equipment data, production data, quality data, and operating procedures. 2) Determine the timing of process actions, analyze the logical relationships between different process actions (including parallel relationships, conflicting relationships, etc.), and arrange the execution order of each process step. 3) Determine the cycle time of the process actions. Refer to the process requirements and equipment performance to determine the execution time of each process action. For process actions that need to be repeated, clarify their cycle frequency requirements.

4. The digital pattern building system for a three-dimensional woven preform apparatus of claim 3, wherein, The connection between the process model, motion model, and data model clarifies the motion sequence and cycle time through the connection between the process model and the motion model; and clarifies the production data and quality data through the connection between the process model and the data model, as detailed below. 1) Connect the process actions in the process model with the specific motion functions in the motion model. 2) Through the form interface built in the data model, the specific production data and quality data in the process model are populated into the production data and quality data forms in the data model.

5. The digital pattern building system for a three-dimensional woven preform apparatus of claim 4, wherein, The simulation process verifies the rationality and stability of the production process design through process motion simulation; and predicts product quality characteristics through product quality simulation. 1) By simulating the process actions based on the model and the relationships between models, it is possible to detect whether the design of the process actions in the production process is reasonable, and identify potential deviations and interference problems. 2) Product quality simulation solution: The physical model provides a three-dimensional geometric model with physical properties, and the process model provides loads and constraints for the physical model to simulate the actual working environment. CAE tools are used to carry out simulation calculations to obtain data such as stress and strain related to product quality.

6. The digital pattern building system for a three-dimensional woven preform apparatus of claim 5, wherein, The correlation between the simulation results and the data model can provide reference and guidance for further production process improvements, identify potential product quality problems, and implement preventative quality control. 1) The quality information data obtained from product quality simulation through finite element analysis is displayed in a visual graphical format. 2) Based on the connection between the process model and the data model, the specific quality data in the process model has been filled into the quality data form in the data model. The quality information data obtained from the product quality simulation is compared and analyzed with the product quality parameters in the quality data form in the data model.

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