Data-real fusion test method and system for aerospace equipment manufacturing

Abstract

The invention discloses a digital-real fusion test method and system for aerospace equipment manufacturing, and belongs to the field of aerospace equipment manufacturing, and the method comprises the steps: designing an aerospace equipment digital twinborn resource library module which comprises a material library unit, a modeling simulation unit and a process evaluation unit, wherein the material unit provides a metal or non-metal material for equipment manufacturing, the modeling simulation unit is responsible for establishing a three-dimensional model of equipment and completing coupled physical field simulation, and the process evaluation unit stores process parameters and equipment energy efficiency data in the equipment manufacturing process; designing an aerospace equipment iterative optimization module, wherein the module completes equipment structure optimization and equipment manufacturing process optimization based on a multi-model collaborative optimization strategy; and an aerospace equipment data-real fusion consistency verification module is designed, and the module synchronizes resource library data and completes data-real consistency verification after data migration of the aerospace equipment based on data-real real-time interaction. The method disclosed by the invention can effectively improve the manufacturing process efficiency of aerospace equipment and shorten the production cycle.

Description

Technical Field

[0001] The present invention belongs to the field of aerospace equipment manufacturing, and specifically relates to a digital-real fusion test method and system for aerospace equipment manufacturing. Background Art

[0002] With the rapid development of aerospace equipment technology, traditional test methods can no longer meet the requirements of efficiency and accuracy of new equipment in the design, manufacturing and testing processes. Current test methods mostly rely on physical experiments, facing problems such as high cost, long cycle, and low data processing efficiency. Therefore, the present invention discloses a digital-real fusion test method, which improves equipment manufacturing efficiency and shortens the production cycle by designing a digital twin resource library module for aerospace equipment, an iterative optimization module for aerospace equipment, and a digital-real fusion consistency verification module for aerospace equipment, and by leveraging the accuracy and efficiency of real-time interaction between digital twins and equipment entities. Summary of the invention

[0003] The technical problem to be solved by the present invention is: to provide a digital-real fusion test method and system for aerospace equipment manufacturing. Through the design of an aerospace equipment digital twin resource library module, an aerospace equipment iterative optimization module and an aerospace equipment digital-real fusion consistency verification module, the design and manufacturing cycle of aerospace equipment can be shortened to a certain extent, and the design accuracy and reliability can be improved.

[0004] The present invention solves the technical problem by adopting the following technical solution: a digital-real fusion test method for aerospace equipment manufacturing, comprising the following steps:

[0005] Step (1), designing the digital twin resource library module of aerospace equipment, including material library unit, modeling and simulation unit, and process evaluation unit;

[0006] Step (2): design an aerospace equipment iteration optimization module to complete the iteration and process optimization of the aerospace equipment digital twin model based on the aerospace equipment manufacturing process and resource library data;

[0007] Step (3), designing a space equipment digital-real fusion consistency check module, which synchronizes resource library data and completes digital-real consistency check after space equipment data migration based on digital-real real-time interaction;

[0008] The present invention also provides a digital-real fusion test system for aerospace equipment manufacturing, comprising:

[0009] The digital twin resource library module of aerospace equipment includes material library unit, modeling and simulation unit, and process evaluation unit;

[0010] The aerospace equipment iteration optimization module completes the iteration and process optimization of the aerospace equipment digital twin model based on the aerospace equipment manufacturing process and resource library data;

[0011] The digital-real fusion consistency verification module for aerospace equipment synchronizes resource library data and completes the digital-real consistency verification after the migration of aerospace equipment data based on real-time interaction between digital and real data.

[0012] The advantages of the present invention compared with the prior art are:

[0013] Combining digital twin technology with physical experiments, the design and production processes are optimized through real-time interaction and data migration to improve design accuracy and reliability. It not only uses virtual simulation predictions but also verifies through actual physical experiments. At the same time, based on real-time feedback, design parameters can be adjusted quickly, reducing the design cycle and improving design accuracy and reliability. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] Figure 1 This is a flowchart of a digital-physical fusion test method for aerospace equipment manufacturing according to the present invention. DETAILED DESCRIPTION

[0015] In order to make the purpose, technical scheme and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention. In addition, the technical features involved in each embodiment of the present invention described below can be combined with each other as long as they do not conflict with each other. To achieve the above-mentioned purpose, the present invention adopts the following technical scheme.

[0016] The present invention provides a digital-real fusion test method and system for aerospace equipment manufacturing. The method includes the design of an aerospace equipment digital twin resource library module, an aerospace equipment iterative optimization module, and an aerospace equipment digital-real fusion consistency verification module. It can shorten the design and manufacturing cycle of aerospace equipment to a certain extent and improve the design accuracy and reliability.

[0017] The flowchart of the present invention is as follows Figure 1 As shown, the specific implementation is as follows:

[0018] Step (1) Design the digital twin resource library module of aerospace equipment, including the material library unit, modeling and simulation unit, and process evaluation unit. The specific implementation is as follows;

[0019] The material library unit provides metal or non-metal materials used in equipment manufacturing, and stores physical properties such as material density, thermal expansion coefficient, strength and stiffness;

[0020] The modeling and simulation unit is responsible for establishing the three-dimensional model of aerospace equipment and completing coupled physical field simulation. It uses CAD, CAE and other software to perform three-dimensional modeling of aerospace equipment, and uses finite element analysis FEA and computational fluid dynamics CFD software to perform multi-physical field simulations such as mechanics and thermals to build a digital twin model of aerospace equipment.

[0021] The process evaluation unit stores the process parameters of the equipment manufacturing process and the equipment energy efficiency data, including the equipment energy input, energy conversion process, energy dissipation, and performance index data;

[0022] Standardize the data format to ensure that all data can be effectively used by the digital twin resource library module and the aerospace equipment iterative optimization module, and complete data preprocessing;

[0023] Step (2): Design an aerospace equipment iteration optimization module to complete the iteration and process optimization of the aerospace equipment digital twin model based on the aerospace equipment manufacturing process and resource library data. The specific implementation is as follows;

[0024] The iteration of the digital twin model of aerospace equipment is based on the optimization of the material, surface texture, and topological structure of the digital twin model, and the model with the lowest production energy consumption and the shortest production cycle is selected first, so that the aerospace equipment can meet the application scenario requirements and meet the requirements of efficient and high-quality manufacturing processes;

[0025] The aerospace equipment iterative optimization module sends the optimized data to the aerospace equipment digital-real fusion consistency verification module. If the verification feedback meets the consistency requirements, the latest data is stored in the aerospace equipment digital twin resource library;

[0026] Step (3) designs a space equipment digital-real fusion consistency check module, which synchronizes resource library data and completes digital-real consistency check after space equipment data migration based on digital-real real-time interaction. The specific implementation is as follows;

[0027] Establish verification rules, determine the key performance indicators that need to be verified, such as Young's modulus and Poisson's ratio, and set the tolerance range of each key performance indicator parameter within 1%;

[0028] Select some components for physical production and test their performance, map the sensor data to the corresponding parts in the digital twin model, compare the predicted values ​​in the digital twin model with the actual values ​​one by one, and check whether they are within the tolerance range;

[0029] Establish an automatic correction mechanism. If the deviation exceeds the tolerance range, adopt a feedback loop to adjust the parameters in the digital twin model. Use a machine learning regression algorithm, use historical data and deviation conditions as the machine learning training set, and use the trained machine learning model to dynamically adjust the model parameters to improve prediction accuracy.

[0030] In summary, the present invention discloses a digital-real fusion test method and system for aerospace equipment manufacturing, including the design of an aerospace equipment digital twin resource library module, an aerospace equipment iterative optimization module, and an aerospace equipment digital-real fusion consistency verification module, which can shorten the design and manufacturing cycle of aerospace equipment to a certain extent and improve the design accuracy and reliability.

[0031] The contents not described in detail in the specification of the present invention belong to the prior art known to the professional and technical personnel in this field.

[0032] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principle of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. A digital-real fusion test method for aerospace equipment manufacturing, characterized in that: The following steps are involved: Step (1), designing the digital twin resource library module of aerospace equipment, including material library unit, modeling and simulation unit, and process evaluation unit; Step (2): design an aerospace equipment iteration optimization module to complete the iteration and process optimization of the aerospace equipment digital twin model based on the aerospace equipment manufacturing process and resource library data; Step (3): Design a digital-real fusion consistency verification module for aerospace equipment. This module synchronizes resource library data and completes digital-real consistency verification after aerospace equipment data migration based on real-time digital-real interaction.

2. A digital-real fusion test method for aerospace equipment manufacturing according to claim 1, characterized in that: Step (1) is specifically implemented as follows: The material library unit provides metal or non-metal materials used for equipment manufacturing, and stores physical properties such as material density, thermal expansion coefficient, strength and stiffness; The modeling and simulation unit is used to establish a three-dimensional model of the equipment and complete coupled physical field simulation. It uses CAD, CAE and other software to perform three-dimensional modeling of aerospace equipment, and uses finite element analysis FEA and computational fluid dynamics CFD software to perform multi-physical field simulations such as mechanics and thermals to build a digital twin model of aerospace equipment. The process evaluation unit stores the process parameters of the equipment manufacturing process and the equipment energy efficiency data, including the equipment energy input, energy conversion process, energy dissipation, and performance index data; Standardize data formats so that all data can be used effectively and complete data preprocessing.

3. A digital-real fusion test method for aerospace equipment manufacturing according to claim 2, characterized in that: Step (2) is specifically implemented as follows: The iteration of the digital twin model of aerospace equipment is based on the optimization of the material, surface texture, and topological structure of the digital twin model, and the model with the lowest production energy consumption and the shortest production cycle is selected, so that the aerospace equipment meets the requirements of application scenarios and meets the requirements of efficient and high-quality manufacturing processes; The optimization objective function is set based on the best energy efficiency as an indicator, and the process data in the digital twin resource library is optimized and solved. According to the nature of the problem, the search algorithm of genetic algorithm and particle swarm optimization is selected to achieve the optimization, and then constraints are added to ensure that the solution meets the actual engineering needs; The aerospace equipment iterative optimization module sends the optimized data to the aerospace equipment digital-real fusion consistency verification module. If the verification feedback meets the consistency requirements, the latest data will be stored in the aerospace equipment digital twin resource library.

4. A digital-real fusion test method for aerospace equipment manufacturing according to claim 3, characterized in that: Step (3) is specifically implemented as follows: Establish verification rules, determine the key performance indicators that need to be verified, and set a reasonable tolerance range for each key performance indicator parameter; Select some components for physical production and test their performance, map the sensor data to the corresponding parts in the digital twin model, compare the predicted values ​​in the digital twin model with the actual values ​​one by one, and check whether they are within the tolerance range; Establish an automatic correction mechanism. If the deviation exceeds the tolerance range, adopt a feedback loop to adjust the parameters in the digital twin model. Use a machine learning regression algorithm, use historical data and deviation conditions as a machine learning training set, and use the trained machine learning model to dynamically adjust the model parameters to improve prediction accuracy.

5. A digital-real fusion test system for aerospace equipment manufacturing, characterized in that: include: The digital twin resource library module of aerospace equipment includes material library unit, modeling and simulation unit, and process evaluation unit; The aerospace equipment iteration optimization module completes the iteration and process optimization of the aerospace equipment digital twin model based on the aerospace equipment manufacturing process and resource library data; The digital-real fusion consistency verification module for aerospace equipment synchronizes resource library data and completes the digital-real consistency verification after the migration of aerospace equipment data based on real-time interaction between digital and real data.

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