Aircraft structure full-mapping high-fidelity digital twin system

Abstract

The invention provides an aircraft structure full-mapping high-fidelity digital twin system, which belongs to the technical field of aircraft structure health management and comprises a data and configuration management module group, a calculation and analysis module group and an application interface module. The data and configuration management module group is used for managing input data and an operation environment of the system; the calculation and analysis module group is used for receiving data and models of the data and configuration management module group and carrying out structural mechanical response calculation, environmental load identification, damage state identification, maintenance scheme evaluation, damage evolution analysis and performance evaluation; and the application module is used for receiving the calculation result and the state information of the calculation and analysis module group and realizing health examination and reliability evaluation based on the result and the information. According to the method, multi-dimensional application scenes such as online health detection, offline fault diagnosis, maintenance decision and life prediction are supported, and core support is provided for intelligent operation and maintenance of the aircraft.

Description

Technical Field

[0001] The present invention belongs to the technical field of aircraft structural health management, and specifically relates to a high-fidelity digital twin system with full mapping of aircraft structures. Background Art

[0002] Aircraft structural health monitoring and intelligent maintenance technologies are key enabling technologies for ensuring safety and economic efficiency in modern aviation. Digital twin technology provides crucial technical support for on-orbit status identification and monitoring of aircraft. However, traditional aircraft structural health management systems lack the ability to collaboratively collect heterogeneous data from multiple sources, preventing the fusion of multiple data sources such as loads, strains, and damage morphology. Sensor data, simulation models, and maintenance records are stored independently, lacking cross-system fusion mechanisms. Finite element models are based on idealized assumptions and fail to reflect the complex characteristics of real-world models, leading to significant simulation errors. The lack of intelligent matching between damage evolution models and repair process libraries results in low repair efficiency and high recurrence rates. Maintenance cycles are based on periodic inspections or post-repair repairs, failing to dynamically adjust to real-time health status, resulting in wasted resources and the risk of unplanned downtime. Furthermore, the lack of quantification of the impact of reuse on structural performance leaves a lack of basis for equipment reliability assessment. Therefore, the development of a fully mapped, high-fidelity digital twin system platform is urgently needed to address core issues in aircraft structural health management, including insufficient multi-source data fusion, low dynamic damage evolution prediction accuracy, and a lack of intelligent decision support. Summary of the Invention

[0003] In response to the shortcomings of the existing technology, the present invention proposes a high-fidelity digital twin system with full mapping of the aircraft structure, which provides a core tool for the safe operation and maintenance of the aircraft structure and promotes the development of reusable spacecraft technology.

[0004] The present invention is implemented through the following technical solutions: a high-fidelity digital twin system with full mapping of aircraft structure: The system includes a data and configuration management module group, a calculation and analysis module group and an application interface module; The data and configuration management module group is used to manage the input data and operating environment of the system; The calculation and analysis module group is used to receive the data and models of the data and configuration management module group, and perform structural mechanics response calculation, environmental load identification, damage state identification, maintenance plan evaluation, damage evolution analysis and performance evaluation; The application module is used to receive the calculation results and status information of the calculation and analysis module group, and implement health checks and reliability assessments based on the results and information.

[0005] Furthermore, the data and configuration management module group includes a model pre-processing module, a twin database and an operating environment configuration module; The model pre-processing module is used to perform model import, basic parameter setting, neural network model setting and model preview operations; The twin database includes a database of piezoelectric guided waves, strain history, load history and performance degradation; The operating environment configuration module is used to set the execution directory of the execution software, modify the external software call path, and select the input path of the virtual model and test database.

[0006] Furthermore, the built-in calculation examples, virtual models, physical prototype data, relevant indicators and evaluation methods stored in the twin database unit constitute the initial input data source of the system.

[0007] Furthermore, the computing and analysis module group is specifically: Mechanical behavior twin module, used for forward calculation of structural displacement, stress, and strain response; an external load identification module for identifying in real time the static load, dynamic force, or thermal load on the structure using the test strain data in the twin database unit; The damage state identification module is used to analyze the spatial location of structural failure using sensor data and obtain damage morphology data through infrared and ultrasonic non-destructive testing methods; The damage in-situ repair module is used to select the repair process and use finite element software to calculate the load limit and load-displacement curve before and after the structural repair; The damage evolution analysis module is used to combine the failure criteria and degradation models in the twin database to perform structural damage evolution analysis and calculations, simulating the crack initiation and propagation process; Residual performance evaluation module, used to calculate the residual strength, stiffness and residual life of the structure under certain loads; The reusability evaluation module is used to calculate the reliability of the reused structure taking into account the uncertainty of the structural mechanical properties and load uncertainty, and evaluate it in combination with the reusability index.

[0008] Furthermore, the application module includes applications for the following scenarios: Based on the output of the external load identification module and the damage state identification module, online health detection of structural strength is performed; Based on the output of the mechanical behavior twin module, the digital twin of the structural mechanical behavior, load environment, and fault status is realized; Based on the outputs of the damage state identification module and the damage in-situ repair module, structural fault state identification and performance recovery are achieved; Based on the outputs of the residual performance evaluation module and the reusability evaluation module, structural residual performance analysis and structural reliability evaluation considering uncertainty are realized.

[0009] A control method for an aircraft structure digital twin system: the method specifically comprises the following steps: Step 1: Parameter setting and data import: set the basic parameters of the structure through the model pre-processing module, and import the built-in calculation examples, virtual models or physical prototype data into the twin database; Step 2: Use the test data stored in the twin database to monitor and identify the structural condition: Step 3: Based on the identified damage, conduct a damage repair assessment: Step 4: Conduct damage evolution analysis and assessment based on the assessment results: Step 5: Based on the identification result of step 2, the maintenance assessment result of step 3, and the analysis and assessment result of step 4, drive the application module to perform health check and reliability assessment.

[0010] Furthermore, in step 2, Through the external load identification module, the static load, dynamic force or thermal load on the structure can be identified in real time using the test strain data; Through the damage state identification module, the spatial location of the structural failure is analyzed using sensor data, and the damage morphology data is obtained through infrared or ultrasonic non-destructive testing methods; Furthermore, in step 4, Through the damage evolution analysis module, combined with the failure criteria and degradation model stored in the twin database, structural damage evolution analysis calculation is performed to simulate the crack initiation and propagation process; The residual performance evaluation module is used to calculate and determine the residual strength, stiffness and residual life of the structure under load; The reliability of the reused structure is calculated by taking into account the uncertainty of the structural mechanical properties and the load uncertainty through the reusability evaluation module; An electronic device includes a memory and a processor, wherein the memory stores a computer program, and the processor implements the steps of the above method when executing the computer program.

[0011] A computer-readable storage medium is used to store computer instructions, which implement the steps of the above method when executed by a processor.

[0012] Beneficial effects of the present invention Compared with the prior art, the present invention has the following advantages: 1. Integrate multi-source online and offline data such as piezoelectric guided waves and infrared thermal imaging to achieve the synchronous evolution of structural displacement, stress, and damage evolution, and realize high-fidelity dynamic mapping between virtual models and physical entities.

[0013] 2. The present invention supports the generation of repair plans based on damage types, verifies feasibility through virtual repair simulation, considers mechanical property uncertainty and load history, calculates the reliability of the reused structure, and provides a decision-making basis for reuse.

[0014] 3. Covering key links such as structural strength monitoring, load environment perception, damage evolution prediction and reusability assessment, it supports multi-dimensional application scenarios such as online health detection, offline fault diagnosis, maintenance decision-making and life prediction, providing core support for intelligent operation and maintenance of aircraft. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 Schematic diagram of a high-fidelity digital twin system for full mapping of aircraft structure according to the present invention; Figure 2 This is a schematic diagram of a control method for a high-fidelity digital twin system with full mapping of aircraft structure according to the present invention. DETAILED DESCRIPTION

[0016] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts shall fall within the scope of protection of the present invention.

[0017] The experimental methods used in the following examples are conventional methods unless otherwise specified. The materials, reagents, methods, and instruments used are conventional in the art and can be obtained commercially by those skilled in the art unless otherwise specified.

[0018] A high-fidelity digital twin system with full mapping of aircraft structure. At the input layer, the software input is clearly defined, including built-in calculation examples, virtual models, physical prototype data, relevant indicators and evaluation methods, etc.

[0019] The data and configuration management module group (software tool layer) includes three main modules (software tools), namely the model pre-processing module, the twin database, and the software operating environment configuration module.

[0020] The model pre-processing module includes basic operation functions such as model import, basic parameter setting, export, and preview.

[0021] The twin database contains actual test data such as piezoelectric guided waves, strain response, and external structural loads, as well as material damage and failure models, performance degradation schemes, and basic material performance parameters under different environmental conditions.

[0022] Specifically, the material damage failure model and performance degradation scheme used depend on the material type and damage behavior. Taking fiber-reinforced resin-based composites as an example, damage failure models can use the maximum stress criterion, maximum strain criterion, Hashin criterion, Tsai-Wu criterion, Hoffman criterion, Tsai-Hill criterion, etc., and performance degradation schemes can use stiffness / strength parameter gradual decline model and sudden decline model.

[0023] The software operating environment configuration module includes functions such as software execution directory setting, external software call path modification, virtual model and test database input path selection, etc.

[0024] The computational analysis layer (computational analysis module group) is composed of multiple functional modules, including mechanical behavior twinning, external load identification, damage state identification, offline non-destructive testing, in-situ damage repair, damage evolution analysis and residual performance evaluation. It has functions such as data import and transmission, real-time status output, cloud map display, and data comparison and export.

[0025] Among them: Forward twin (mechanical behavior twin) calculation module: performs forward calculation of structural displacement, stress, and strain response; External environment perception module (external load identification): uses test strain data to identify the static load, dynamic force, and thermal load on the structure in real time; Fault state identification module (damage state identification, offline non-destructive testing): uses sensor data to analyze the spatial location of structural failures and obtains damage morphology data through non-destructive testing methods such as infrared and ultrasonic testing; The structural in-situ repair module (damage in-situ repair) selects a reasonable repair process and uses finite element software to calculate the load-bearing extreme value and load-displacement curve before and after structural repair; Specifically, finite element analysis software such as ABAQUS, COMSOL, ANSYS, and SIMULINK can be used to calculate structural strength, stiffness, deformation, fatigue life, etc., and to examine the structural performance recovery capability.

[0026] Mechanical properties prediction module (damage evolution analysis, residual performance evaluation): Combined with failure criteria and degradation models, it performs structural damage evolution analysis and calculations, simulates the crack initiation and propagation process, and calculates and determines the structural residual strength, stiffness, and remaining life under load; Reusability evaluation module: Taking into account the uncertainty of structural mechanical properties and load uncertainty, the reliability of the reused structure is calculated and evaluated in combination with reusability indicators.

[0027] Specifically, the Monte Carlo method can be used to establish a Kriging or neural network proxy model to calculate the failure probability and structural reliability. Industry experts will then make a comprehensive assessment of whether the aircraft can perform the next flight mission based on the calculation results.

[0028] The application scenario layer includes four types of scenarios: the first type of scenario is online health detection for structural strength; the second type of scenario is digital twins of structural mechanical behavior, load environment, and fault status; the third type of scenario is structural fault status identification and performance recovery; the fourth type of scenario is structural residual performance analysis and structural reliability assessment considering uncertainty.

[0029] The present invention designs a high-fidelity digital twin system for full mapping of aircraft structure based on the following method: 1) The first level of technical route execution: Based on the needs, the main tasks of the twin system platform development are clarified, including three main parts: building the overall architecture of the system platform; developing the underlying modules of the twin system platform; and realizing the integration of each module and the interaction with the software interface.

[0030] 2) The second level of technical route execution: Identification, sorting and research of key technical points. The key technologies that need to be implemented include: environmental load identification and reconstruction and multi-field decoupling technology, online damage location and fault behavior diagnosis method, multi-source complex damage offline non-destructive testing method, aircraft structure maintenance decision-making method and process, high-fidelity model data synchronous update evolution technology, multi-module data interaction and multi-platform collaborative simulation technology.

[0031] 3) The third level of technical route execution: using key technologies to integrate related models, write underlying codes, develop various modules of the platform, and realize full mapping and real-time interaction of virtual and real data in each part.

[0032] 4) Technical route execution fourth level: After the module development is completed, aircraft structural fault behavior diagnosis and evaluation examples are established based on typical aircraft structural objects, and the various software functions and technical indicators are verified.

[0033] Based on the above content, the present invention proposes a control method for an aircraft structure digital twin system. The method specifically comprises the following steps: Step 1: Parameter setting and data import: set the basic parameters of the structure through the model pre-processing module, and import the built-in calculation examples, virtual models or physical prototype data into the twin database; Step 2: Use the test data stored in the twin database to monitor and identify the structural condition: Through the external load identification module, the static load, dynamic force or thermal load on the structure can be identified in real time using the test strain data; Through the damage state identification module, the spatial location of the structural failure is analyzed using sensor data, and the damage morphology data is obtained through infrared or ultrasonic non-destructive testing methods; Step 3: Based on the identified damage, perform damage repair assessment using the calculation and analysis module group: Select a reasonable repair process through the damage in-situ repair module, and use finite element software to calculate the load limit and load-displacement curve before and after the structural repair; Step 4: Based on the evaluation results, the calculation and analysis module group performs damage evolution analysis and evaluation: Through the damage evolution analysis module, combined with the failure criteria and degradation model stored in the twin database, structural damage evolution analysis calculation is performed to simulate the crack initiation and propagation process; The residual performance evaluation module is used to calculate and determine the residual strength, stiffness and residual life of the structure under load; The reliability of the reused structure is calculated by taking into account the uncertainty of the structural mechanical properties and the load uncertainty through the reusability evaluation module; Step 5: Based on the identification result of step 2, the maintenance assessment result of step 3, and the analysis and assessment result of step 4, drive the application module to perform at least one of the following functions: Conduct online health checks on structural strength; Achieve digital twins of structural mechanical behavior, load environment, and fault status; Achieve structural fault status identification and performance recovery; Realize structural residual performance analysis and structural reliability assessment considering uncertainty.

[0034] An electronic device includes a memory and a processor, wherein the memory stores a computer program, and the processor implements the steps of the above method when executing the computer program.

[0035] A computer-readable storage medium is used to store computer instructions, which implement the steps of the above method when executed by a processor.

[0036] The memory in the embodiments of the present application can be volatile memory or non-volatile memory, or can include both volatile and non-volatile memory. The non-volatile memory can be read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), or flash memory. The volatile memory can be random access memory (RAM), which is used as an external cache. By way of example and not limitation, many forms of RAM are available, such as static random access memory (SRAM), dynamic random access memory (DRAM), synchronous dynamic random access memory (SDRAM), double data rate synchronous dynamic random access memory (DDR SDRAM), enhanced synchronous dynamic random access memory (ESDRAM), synchronous link dynamic random access memory (SLDRAM), and direct RAM bus random access memory (DR RAM). It should be noted that memory of the methods described herein is intended to comprise, but not be limited to, these and any other suitable types of memory.

[0037] In the above embodiments, all or part of the embodiments can be implemented using software, hardware, firmware, or any combination thereof. When implemented using software, all or part of the embodiments can be implemented in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer instructions are loaded and executed on a computer, all or part of the processes or functions described in the embodiments of the present application are generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via a wired connection such as a coaxial cable, optical fiber, digital subscriber line (DSL), or wireless connection such as infrared, wireless, or microwave. The computer-readable storage medium can be any available medium that can be accessed by a computer, or a data storage device such as a server or data center that integrates one or more available media. The available medium can be a magnetic medium such as a floppy disk, hard disk, magnetic tape, an optical medium such as a high-density digital video disc (DVD), or a semiconductor medium such as a solid-state disc (SSD).

[0038] During implementation, each step of the above method can be completed by an integrated logic circuit of the hardware in the processor or by instructions in the form of software. The steps of the method disclosed in conjunction with the embodiments of the present application can be directly embodied as being executed by a hardware processor, or can be executed by a combination of hardware and software modules in the processor. The software module can be located in a storage medium mature in the art such as a random access memory, a flash memory, a read-only memory, a programmable read-only memory or an electrically erasable programmable memory, a register, etc. The storage medium is located in the memory, and the processor reads the information in the memory and completes the steps of the above method in conjunction with its hardware. To avoid repetition, it will not be described in detail here.

[0039] It should be noted that the processor in the embodiments of the present application can be an integrated circuit chip with signal processing capabilities. During implementation, each step of the above-described method embodiment can be completed by hardware integrated logic circuits in the processor or by software instructions. The above-described processor can be a general-purpose processor, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic device, discrete gate or transistor logic device, or discrete hardware components. The various methods, steps, and logic block diagrams disclosed in the embodiments of the present application can be implemented or executed. The general-purpose processor can be a microprocessor or any conventional processor. The steps of the methods disclosed in the embodiments of the present application can be directly implemented and executed by a hardware decoding processor, or by a combination of hardware and software modules in the decoding processor. The software module can be located in a storage medium well-known in the art, such as random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, registers, etc. The storage medium is located in the memory, and the processor reads the information in the memory and, in conjunction with its hardware, completes the steps of the above-described method.

[0040] The above is a detailed introduction to the high-fidelity digital twin system for fully mapping the aircraft structure proposed in the present invention, and the principles and implementation methods of the present invention are explained. The description of the above embodiments is only used to help understand the method of the present invention and its core idea; at the same time, for those skilled in the art, based on the ideas of the present invention, there will be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as limiting the present invention.

Claims

1. A high-fidelity digital twin system with full mapping of aircraft structure, characterized by: The system includes a data and configuration management module group, a calculation and analysis module group and an application interface module; The data and configuration management module group is used to manage the input data and operating environment of the system; The calculation and analysis module group is used to receive the data and models of the data and configuration management module group, and perform structural mechanics response calculation, environmental load identification, damage state identification, maintenance plan evaluation, damage evolution analysis and performance evaluation; The application module is used to receive the calculation results and status information of the calculation and analysis module group, and implement health checks and reliability assessments based on the results and information.

2. The system according to claim 1, characterized in that: The data and configuration management module group includes a model pre-processing module, a twin database and an operating environment configuration module; The model pre-processing module is used to perform model import, basic parameter setting, neural network model setting and model preview operations; The twin database includes a database of piezoelectric guided waves, strain history, load history and performance degradation; The operating environment configuration module is used to set the execution directory of the execution software, modify the external software call path, and select the input path of the virtual model and test database.

3. The system according to claim 2, characterized in that: The built-in calculation examples, virtual models, physical prototype data, relevant indicators and evaluation methods stored in the twin database unit constitute the initial input data source of the system.

4. The system according to claim 3, characterized in that: The computing and analysis module group is specifically: Mechanical behavior twin module, used for forward calculation of structural displacement, stress, and strain response; an external load identification module for identifying in real time the static load, dynamic force, or thermal load on the structure using the test strain data in the twin database unit; The damage state identification module is used to analyze the spatial location of structural failure using sensor data and obtain damage morphology data through infrared and ultrasonic non-destructive testing methods; The damage in-situ repair module is used to select the repair process and use finite element software to calculate the load limit and load-displacement curve before and after the structural repair; The damage evolution analysis module is used to combine the failure criteria and degradation models in the twin database to perform structural damage evolution analysis and calculations, simulating the crack initiation and propagation process; Residual performance evaluation module, used to calculate the residual strength, stiffness and residual life of the structure under certain loads; The reusability evaluation module is used to calculate the reliability of the reused structure taking into account the uncertainty of the structural mechanical properties and load uncertainty, and evaluate it in combination with the reusability index.

5. The system according to claim 4, characterized in that: The application module includes applications for the following scenarios: Based on the output of the external load identification module and the damage state identification module, online health detection of structural strength is performed; Based on the output of the mechanical behavior twin module, the digital twin of the structural mechanical behavior, load environment, and fault status is realized; Based on the outputs of the damage state identification module and the damage in-situ repair module, structural fault state identification and performance recovery are achieved; Based on the outputs of the residual performance evaluation module and the reusability evaluation module, structural residual performance analysis and structural reliability evaluation considering uncertainty are realized.

6. A control method for an aircraft structure digital twin system according to any one of claims 1 to 5, characterized in that: The method specifically comprises the following steps: Step 1: Parameter setting and data import: set the basic parameters of the structure through the model pre-processing module, and import the built-in calculation examples, virtual models or physical prototype data into the twin database; Step 2: Use the test data stored in the twin database to monitor and identify the structural condition: Step 3: Based on the identified damage, conduct a damage repair assessment: Step 4: Conduct damage evolution analysis and assessment based on the assessment results: Step 5: Based on the identification result of step 2, the maintenance assessment result of step 3, and the analysis and assessment result of step 4, drive the application module to perform health check and reliability assessment.

7. The control method according to claim 6, characterized in that: In step 2, Through the external load identification module, the static load, dynamic force or thermal load on the structure can be identified in real time using the test strain data; Through the damage state identification module, sensor data is used to analyze the spatial location of structural failure, and damage morphology data is obtained through infrared or ultrasonic non-destructive testing methods.

8. The control method according to claim 7, characterized in that: In step 4, Through the damage evolution analysis module, combined with the failure criteria and degradation model stored in the twin database, structural damage evolution analysis calculation is performed to simulate the crack initiation and propagation process; The residual performance evaluation module is used to calculate and determine the residual strength, stiffness and residual life of the structure under load; Through the reusability evaluation module, the reliability of the reused structure is calculated taking into account the uncertainty of the structural mechanical properties and the load uncertainty.

9. An electronic device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 6 to 8 are implemented.

10. A computer-readable storage medium for storing computer instructions, characterized in that: When the computer instructions are executed by a processor, the steps of the method according to any one of claims 6 to 8 are implemented.

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