CN119044316A

CN119044316A - Precise measurement method and system for assembly stress and damage of aviation composite thin-wall structure

Info

Publication number: CN119044316A
Application number: CN202411153641.0A
Authority: CN
Inventors: 郭飞燕; 鲍强伟; 黄明吉; 贾志新; 刘嘉良
Original assignee: University of Science and Technology Beijing USTB
Current assignee: University of Science and Technology Beijing USTB
Priority date: 2024-08-21
Filing date: 2024-08-21
Publication date: 2024-11-29

Abstract

The present invention provides a method and system for accurately measuring stress and damage in the assembly of thin-walled structures of aviation composite materials, including: S1: determining the measurement scheme of microscopic damage, internal stress and surface deformation; S2: deploying acoustic emission systems, ultrasonic probes and DIC markers in key assembly stress transmission and potential damage areas; S3: real-time synchronous monitoring of microscopic damage signals, internal stress states and surface deformation data; S4: processing acoustic emission data to identify microscopic damage characteristics, using ultrasonic data to analyze the internal stress distribution of composite materials, calculating the surface strain field based on DIC data, and constructing a stress-damage correlation model; S5: integrating measurement data to locate the position and degree of stress damage; S6: correcting finite element simulation models and parameters based on accurate experimental test results, and quickly and accurately predicting risks. The present invention can realize accurate measurement and virtual measurement prediction verification of internal stress and damage in composite structure assembly, and thereby clarify the influence of assembly process parameters and internal stress on damage behavior.

Description

Precise measurement method and system for assembly stress and damage of aviation composite thin-wall structure

[ Field of technology ]

The invention relates to the technical field of assembly quality detection of aviation composite parts, in particular to a method and a system for accurately measuring stress and damage in the assembly process of an aviation composite thin-wall structure.

[ Background Art ]

In the process of positioning, clamping and fastening connection of an aviation composite thin-wall workpiece, under the actions of clamping force load, clamping position deviation, connecting force and the like, stress concentration phenomenon can be generated in the assembly body structure, and excessive assembly internal stress can possibly cause damage and destruction phenomena such as matrix crushing, interlayer debonding, fiber breakage and the like in the composite thin-wall workpiece, wherein most of the damage phenomena are invisible to naked eyes, and in order to prevent damage deterioration during the service period of the assembly body structure, reduce maintenance cost, measures are needed to be taken in time to control the internal stress generated in the assembly process and inhibit the generated damage. To achieve this, it is first necessary to measure the assembly stress and damage accurately in real time to obtain the most realistic assembly quality state.

In the current field of composite structure monitoring, although a plurality of nondestructive testing techniques have been widely used for material performance evaluation and damage detection, such as ultrasonic testing, X-ray testing, thermal imaging analysis, penetration testing, etc., each of these techniques has unique advantages and limitations. However, for the complex aviation composite thin-wall structure assembly, due to different combination forms of fibers and matrixes of the material and layering directions, the internal assembly stress distribution, interlayer debonding, fiber breakage, layering and other macro and micro damage states are often difficult to effectively identify through a single detection means, and particularly, under a complex assembly environment, local damage caused by uneven stress distribution is more hidden. Accurate assessment of structural assembly performance and structural integrity is limited due to difficulty in directly and comprehensively capturing subtle changes in stress concentration areas and dynamic evolution of composite damage over time.

In view of the above, the composite thin wall monitoring needs a more comprehensive and efficient measurement solution, can integrate the advantages of various nondestructive testing techniques, complements the disadvantages thereof, so as to realize accurate measurement and evaluation of the stress state and damage condition of the aviation composite thin wall in the assembly process, and clarify the rule of influence of assembly process parameters and internal stress on damage behaviors, judge and optimize the rationality and effectiveness of the assembly process according to the detection result, and rapidly and effectively guide the on-site assembly operation.

Accordingly, there is a need to develop a method and system for accurately measuring assembly stress and damage of an aerospace composite thin-wall structure to address the deficiencies of the prior art, and to solve or alleviate one or more of the above-mentioned problems.

[ Invention ]

In view of the above, the invention provides a method and a system for accurately measuring assembly stress and damage of an aviation composite thin-wall structure.

On one hand, the invention provides an accurate measurement method for assembly stress and damage of an aviation composite thin-wall structure, which comprises the following steps:

S1, determining a measurement scheme of data types such as microscopic damage, internal stress, surface deformation and the like according to the material properties of the composite material and the thin-wall workpiece structure;

S2, deploying an acoustic emission system, an ultrasonic probe and DIC mark points in a key assembly stress transmission and potential damage area, and constructing a measurement system;

S3, monitoring microscopic damage signals, internal stress states and surface deformation data in real time synchronously;

s4, processing acoustic emission data to identify microscopic damage characteristics, analyzing and determining internal stress distribution of the composite workpiece by utilizing ultrasonic data, calculating a surface strain field according to DIC data, and constructing a stress-damage association model;

s5, integrating microscopic damage data, internal stress data and surface deformation data, precisely positioning stress damage positions and degrees, and evaluating the influence of assembly internal stress on composite material damage behaviors;

And S6, correcting the finite element simulation model and parameters according to accurate test results, and performing virtual measurement prediction and verification work so as to rapidly and accurately predict the balance of assembly stress distribution and evaluate the risk of larger damage phenomenon.

In the aspect and any possible implementation manner as described above, there is further provided an implementation manner, where the S1 specifically includes:

S11, acquiring the self characteristics of composite material components, fiber laying directions, lamination sequences and the like, analyzing the influence of the self characteristics on the acoustic wave propagation characteristics of a thin composite material wall workpiece, adopting finite element analysis software to simulate stress distribution under different working conditions, defining a key stress transmission path and a high stress concentration area, and identifying a potential damage area and a common assembly quality problem area in historical data;

s12, according to acoustic emission characteristics of the composite material, an acoustic emission AE sensor layout scheme is formulated, stress paths and potential crack expansion areas are covered in a key way, and microscopic damage data are obtained;

S13, planning an ultrasonic probe path to penetrate through the composite thin-wall structure, and taking multi-angle arrangement into consideration to acquire three-dimensional information, so that the stress state inside the composite part can be detected, and the internal stress data of the composite assembly part can be acquired;

S14, designing a DIC strain mark point distribution diagram related to a digital image, ensuring to cover the surface of the whole thin-wall part, particularly improving the density in a deformation sensitive area, and acquiring surface deformation data;

s15, calibrating sensitivity and frequency response of each AE sensor and each ultrasonic probe, calibrating a DIC system through a known deformation standard sample, correcting lens distortion, and ensuring time synchronization of all monitoring systems;

S16, carrying out comprehensive test on the actual composite material thin-wall structure by combining finite element simulation, and verifying the effectiveness of a measurement scheme, the continuity of data acquisition and the overall performance of the system.

In the aspect and any possible implementation manner as described above, there is further provided an implementation manner, where the S2 specifically includes:

S21, installing a sensor and arranging a sensor connecting cable based on the key stress transmission path and the potential damage area which are accurately positioned in the S1 and an AE sensor layout scheme;

S22, based on the ultrasonic probe layout scheme and the scanning path designed in the S1, setting partial ultrasonic probes for static detection to monitor the structural integrity of the interior of the composite material thin wall before and after assembly, and simultaneously deploying a movable probe for dynamic scanning to capture the stress change of the interior of the assembly body in the assembly process;

S23, sticking high-contrast mark points, namely stress zero points, on the surface of the composite material thin-wall part based on the DIC mark point layout designed in the S1;

S24, carrying out a simulated loading test of the aviation composite thin-wall part, carrying out a functional test of the measuring system before actual assembly, and judging the response capability of the assembly stress and damage measuring system.

In the aspect and any possible implementation manner as described above, there is further provided an implementation manner, where the S3 specifically includes:

S31, setting a signal threshold value of AE monitoring, setting an ultrasonic scanning path and parameters, and adjusting a DIC system installed at the position of a high-speed camera to ensure that marked points on the surface of a workpiece are clearly visible and can be captured;

S32, starting AE monitoring, analyzing acoustic emission signals, positioning a damage source, executing ultrasonic dynamic scanning, collecting internal structure images of the composite thin-wall part, evaluating a structural stress concentration area, and continuously shooting by using DIC to obtain strain and deformation data of the surface of the thin-wall part.

In the foregoing aspect and any possible implementation manner, there is further provided an implementation manner, where the S4 specifically includes:

S41, filtering out environmental noise, denoising and amplifying the acquired acoustic emission signals, identifying microscopic damage characteristics of assemblies of different types by adopting methods such as frequency spectrum analysis, waveform time domain feature extraction and the like, classifying the processed signals by using a machine learning algorithm, and identifying the corresponding damage type and severity;

S42, reinforcing and dividing ultrasonic discrete point stress detection data, measuring propagation time of ultrasonic waves in a composite material after distinguishing different medium interfaces, acquiring the position and the size of a damage defect in a fitting structure by combining known sound velocity of the material, and analyzing stress concentration areas and distribution in the material by an inversion algorithm by combining time-of-flight (TOF) data and mechanical structures of an aviation composite material thin-wall part;

S43, accurately tracking the position change of each mark point in different assembly time periods by using a digital image correlation DIC technology, recording the tiny strain of the surface, applying a strain and stress deformation conversion algorithm based on the displacement field of the mark point, and adopting an interpolation and gradient calculation method to obtain a strain distribution map of the whole observation surface, wherein the strain distribution map comprises main strain and shear strain;

and S44, integrating damage characteristics obtained by AE signal analysis, stress distribution information of ultrasonic detection and surface strain field data obtained by DIC technology, and analyzing quantitative association relation and model between stress and damage by using a data driving method based on physical principles and test data.

In the foregoing aspect and any possible implementation manner, there is further provided an implementation manner, where the S5 specifically includes:

S51, carrying out format unification and time synchronization on AE (automatic analysis) detected damage characteristic data, ultrasonic detected internal stress distribution data and DIC (digital computer) surface strain data, and firstly, completing pretreatment of all measurement data;

S52, combining time and intensity information of AE signals and internal structural details provided by an ultrasonic image, accurately positioning a damage position and a position with larger stress by using a multidimensional data fusion algorithm such as a Bayesian network;

S53, analyzing the frequency spectrum characteristics and the energy release rate parameters of AE signals, and evaluating the severity and the development trend of damage by combining a damage model, and quantifying the damage degree by adopting a damage tolerance evaluation method based on the ultrasonic detected internal crack length, layering area and DIC measured surface strain;

s54, carrying out assembly strain monitoring on the surface of a large-range composite material workpiece in a visual field range by using a multi-camera DIC, and obtaining discrete point stress detection data of a key assembly part by an ultrasonic detection method, wherein the discrete point stress detection data and the discrete point stress detection data are combined to form a stress distribution state of the whole assembly;

S55, inputting the actually measured stress distribution data into a finite element model for simulation calculation, analyzing how the stress generated in the assembly process affects the structural performance of the composite material thin wall, evaluating the interaction between the assembly stress and the damage, and identifying whether a high risk area capable of accelerating the development of the damage exists or not;

and S56, comprehensively analyzing the results to form an evaluation report of the assembly performance of the composite thin-wall structure, wherein the evaluation report comprises detailed distribution of the damage position and degree and influence analysis of the stress concentration area.

In the aspect and any possible implementation manner as described above, there is further provided an implementation manner, where the preprocessing in S51 includes alignment on a time axis, and performing outlier rejection and normalization processing at the same time.

In the aspect and any possible implementation manner as described above, further providing an implementation manner, the obtaining the stress distribution state of the whole assembly in S54 includes obtaining a stiffness matrix and an elastic constant of a relationship between stress and strain of the composite material through a test of the composite material, and converting a surface strain field of the assembly structure obtained by the DIC system into a stress field.

In the foregoing aspect and any possible implementation manner, there is further provided an implementation manner, where the S6 specifically includes:

S61, analyzing the internal stress response, damage evolution expansion, appearance and other dimensional change conditions of the composite thin-wall assembly structure under different assembly process parameters in finite element simulation software;

s62, comparing simulation data such as stress-strain response, displacement field distribution, damage sign distribution and the like obtained through finite element operation with actual measurement data, identifying a deviation source between a model and an actual situation based on a comparison result, and continuously adjusting simulation model parameters until a corrected prediction result is highly consistent with a test result;

And S63, analyzing the assembly internal stress and damage analysis results under different assembly conditions in a finite element simulation software environment, so as to realize virtual measurement prediction verification of the assembly internal stress and damage results, and evaluate the balance of the assembly stress distribution and the occurrence risk of damage phenomenon.

Aspects and any possible implementation manner as described above, further provide an accurate measurement system for assembly stress and damage of an aviation composite thin-wall structure, where the accurate measurement system for assembly stress and damage of an aviation composite thin-wall structure includes:

The measurement scheme making module is used for determining a measurement scheme of data types such as microscopic damage, internal stress, surface deformation and the like according to the material properties of the composite material and the thin-wall workpiece structure;

The measuring system building module is used for deploying the acoustic emission system, the ultrasonic probe and DIC mark points in the key assembly stress transmission and potential damage area to build the measuring system;

The data detection acquisition module is used for synchronously monitoring microscopic damage signals, internal stress states and surface deformation data in real time;

The data processing and integrating module is used for processing and integrating microscopic damage data, internal stress data and surface deformation data, constructing a stress-damage association model and evaluating the influence of assembly internal stress on the damage behavior of the composite material;

The virtual measurement verification module is used for realizing virtual measurement prediction verification of assembly internal stress and damage results and evaluating the balance of assembly stress distribution and the occurrence risk of damage phenomenon.

Compared with the prior art, the invention can obtain the following technical effects:

1) According to the material properties of the composite material and the structural characteristics of the thin-wall workpiece, key assembly stress transmission and potential damage areas are obtained through a finite element analysis method, and a nondestructive measurement scheme for the assembly stress and damage of an acoustic emission system, an ultrasonic probe and DIC mark points is provided.

2) The method has the advantages that the method provides a multi-dimensional measurement data fusion processing analysis scheme for assembly stress and damage, can process acoustic emission data to identify microscopic damage characteristics, utilizes ultrasonic data analysis to determine internal stress distribution of a composite workpiece, calculates a surface strain field according to DIC data, and can accurately position stress damage positions and degrees through integration and conversion of the microscopic damage data, the internal stress data and the surface deformation data, thereby providing comprehensive and effective data support for judging complex stress and damage modes and defining the rule of influence of assembly internal stress on composite damage behaviors.

3) The finite element simulation model and parameters are corrected according to the accurate test result, the consistency between the digital simulation and the real measurement result is ensured, virtual measurement prediction and verification work is carried out, the balance of assembly stress distribution can be rapidly and accurately predicted, the risk of larger damage phenomenon is estimated, and the assembly test and measurement times are reduced.

Of course, it is not necessary for any of the products embodying the invention to achieve all of the technical effects described above at the same time.

[ Description of the drawings ]

In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings that are needed in the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and that other drawings can be obtained according to these drawings without inventive effort for a person skilled in the art.

FIG. 1 is a step diagram of an assembly stress and damage accurate measurement technique of an aviation composite thin-wall structure;

FIG. 2 is a flow chart of an assembly stress and damage accuracy measurement technique provided by an embodiment of the present invention;

FIG. 3 is an exploded view of the overall structure of a certain wing box component provided by one embodiment of the present invention;

Fig. 4 is an explanatory diagram of the structure and the adjustable functions of the assembly fixture for the typical box section of the invention.

[ Detailed description ] of the invention

For a better understanding of the technical solution of the present invention, the following detailed description of the embodiments of the present invention refers to the accompanying drawings.

It should be understood that the described embodiments are merely some, but not all, embodiments of the invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.

The terminology used in the embodiments of the invention is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. As used in this application and the appended claims, the singular forms "a," "an," and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise.

The invention provides a method and a system for accurately measuring assembly stress and damage of an aviation composite thin-wall structure, and fig. 1 is a step diagram of implementation of the scheme in the embodiment. The invention solves the technical problems by adopting the following general ideas:

Firstly, deeply analyzing the characteristics of the composite material and the influence of the composite material on the acoustic wave propagation characteristics, identifying key structural elements in the thin wall of the composite material, planning the arrangement scheme of AE sensors, ultrasonic probes and DIC mark points based on the key structural elements, and completing the accurate verification of each detection system. Secondly, based on an arrangement scheme of an AE sensor, an ultrasonic probe and DIC mark points, the sensor is installed, the layout of the ultrasonic probe is optimized, the structural integrity of the thin wall of the aviation composite material can be monitored statically, the stress change in the assembly process can be captured dynamically, meanwhile, the mark points are pasted, and a high-contrast observation reference is provided for a DIC system. Thirdly, configuring and initializing the measurement system, setting monitoring parameters, configuring a high-precision probe, installing a DIC system, and ensuring time synchronization and preliminary fusion of data of all monitoring devices, thereby laying a solid foundation for real-time monitoring and data analysis. The method comprises the steps of acquiring acoustic emission signals, carrying out data processing integration and damage assessment, effectively identifying and classifying the type and severity of damage through noise reduction processing and machine learning algorithm analysis on the acquired acoustic emission signals, revealing the position and the size of the internal defects of the thin wall of the aviation composite material based on the application of related technologies of ultrasonic image analysis and digital images, accurately describing a surface strain field and an internal stress field through integration and conversion of microscopic damage data, internal stress data and surface deformation data, and providing detailed data support for constructing a stress and damage association model. And finally, integrating the information, uniformly processing and time synchronizing the data, and accurately positioning the damage position by utilizing a multidimensional data fusion technology to evaluate the severity and development trend of the damage position. In addition, the finite element simulation model and parameters are corrected according to accurate test results, the real consistency of the number is realized, virtual measurement prediction verification of assembly internal stress and damage results under other assembly process conditions is carried out, and the balance of assembly stress distribution and the occurrence risk of damage phenomena are evaluated.

The invention provides an accurate measurement technique for assembly stress and damage of an aviation composite thin-wall structure, which aims at the problems of damage of composite materials, and the like, which are possibly caused by overlarge assembly stress in the composite thin-wall caused by the actions of multiple physical field factors such as clamping load, displacement deviation constraint, connecting load and the like in the assembly positioning clamping and fastening connection stage of the aviation composite thin-wall structure, and aims at directly and comprehensively capturing the fine change of a stress concentration area, the invention provides a more comprehensive and efficient measurement solution to realize accurate measurement and evaluation of stress states and damage conditions of the thin wall of the aviation composite material in the assembly process, and the method is used for judging and optimizing the rationality and effectiveness of the assembly process and rapidly and effectively guiding the on-site assembly operation by taking measurement data as a basis to clearly understand the rule of influence of assembly process parameters and internal stress on damage behaviors. As shown in fig. 2, the precise measurement technique for the assembly stress and damage of the thin-wall structure of the aviation composite material comprises the following specific implementation procedures:

s1, determining a measurement scheme of data types such as microscopic damage, internal stress, surface deformation and the like according to the material properties of the composite material and the specific structure of the thin-wall workpiece.

Specifically, firstly, the material properties of the aviation composite material, including composite material components, fiber laying directions, lamination sequences, the kinds proportion of a resin matrix and reinforcing fibers, and the sequence and layout of a lamination structure, are deeply analyzed, the influence of the factors on the propagation characteristics of sound waves is analyzed, secondly, finite element analysis software is adopted to simulate stress distribution under different working conditions, a critical stress transmission path and a high stress concentration area are clarified, potential damage areas and common assembly quality problem areas in historical data, such as joints, holes, variable cross sections and the like, are identified, and the areas become stress concentration and easy to cause initial damage due to the change of geometric shapes or the interruption of material continuity.

Further, when designing a sensor layout scheme based on the acoustic emission characteristics of the aviation composite material thin wall, considering possible positions and propagation paths of acoustic emission sources, mainly covering areas with obvious stress paths and places easy to crack propagation in historical experience or theoretical prediction, and considering the coverage range and sensitivity of the sensor, so that any tiny acoustic emission signals can be effectively captured, and microscopic damage data can be obtained.

Further, a probe path required by an ultrasonic detection technology is planned, and the depth and the angle of penetrating through the composite thin-wall workpiece are considered, so that the ultrasonic energy can fully cover the inside of the composite thin-wall, and especially the key area is ensured. By adopting a multi-angle arrangement strategy and combining ultrasonic waves with different incidence angles, the stress state in the composite part can be detected, the three-dimensional stress distribution in the thin wall of the composite part is rebuilt, more accurate internal state information is provided, and the internal stress data of the composite part are acquired.

Further, a distribution diagram of DIC mark points related to the digital image is designed, so that the mark points can be uniformly distributed on the surface of the composite thin-wall workpiece, and particularly, the density of the mark points is increased in a region with larger expected deformation, so that the tracking precision of a DIC system on the surface micro deformation is improved, and the surface deformation data are obtained.

Furthermore, the sensitivity and the frequency response of the AE sensor and the ultrasonic probe are calibrated, so that the AE sensor and the ultrasonic probe can accurately respond to the expected signal range, meanwhile, the standard deformation sample is used for calibrating the DIC system, the image distortion caused by the lens and the optical system is corrected, and the time synchronization of all monitoring systems is ensured.

Further, the validity of the measurement scheme and the continuity of data acquisition are verified through a simulation loading test and a finite element simulation on the actual composite thin-wall structure, wherein the verification comprises the verification of the response speed, the data quality and the capturing capability of the monitoring system on the actual damage event under different working conditions.

And S2, deploying an acoustic emission system, an ultrasonic probe and DIC mark points in a key assembly stress transmission and potential damage area, and constructing a measurement system.

Specifically, based on the key stress transmission path and the potential damage area which are accurately positioned in the S1 and the AE sensor layout scheme, a proper adhesive is selected according to the material characteristics of the aviation composite workpiece, so that the stability and long-term reliability of the sensor in a complex stress environment are ensured, meanwhile, the connection line layout of the sensor is reasonably planned, and unnecessary mechanical stress is avoided in the assembly process.

Further, based on the ultrasonic probe arrangement scheme of the S1 planning, according to the penetration characteristics of ultrasonic waves and the required detection depth, all key areas are covered, a couplant with high matching degree with an aviation composite material thin-wall material is selected, and the transmission efficiency of the ultrasonic waves is optimized. And (3) deploying a part of probes for static detection, monitoring the integrity of the interior of the composite thin wall before and after assembly, and simultaneously, dynamically scanning by using another part of movable probes to capture the stress change in the assembly process in real time.

Further, based on the arrangement scheme of DIC mark points planned by S1, mark points with high contrast, namely stress zero points, are stuck on the surface of the composite material thin wall, and the layout of the mark points can not only uniformly cover the surface of the composite material thin wall, but also adapt to the special form and stress distribution characteristics of the aviation composite material thin wall.

Further, after the installation is finished, the acoustic emission sensor, the ultrasonic probe and the marking point are subjected to functional tests, so that each component can accurately receive and transmit signals. In addition, a simulated loading test of the aviation composite material thin-wall part is carried out, and the stress state of the composite material thin-wall part in the actual assembly process is simulated before the actual assembly, so that the response capacity and the data acquisition accuracy of the monitoring system are verified.

And S3, monitoring microscopic damage signals, internal stress states and surface deformation data in real time.

Specifically, for an AE monitoring system, a reasonable signal threshold is set according to early analysis, background noise is filtered, only signals really caused by damage or stress are ensured to be captured, meanwhile, the data acquisition speed is optimized, and the tiny damage can be recorded in real time and accurately. For an ultrasonic detection system, a scanning path and parameter setting are carefully planned, and a high-precision ultrasonic probe is selected to dynamically monitor the stress change in the composite assembly body. For the DIC system, the position and the view angle of the high-speed camera are adjusted, so that high-contrast mark points on the thin-wall surface of the aviation composite material can be clearly captured under any illumination condition.

Further, the AE monitoring system is started, each acoustic emission signal is analyzed through a signal processing algorithm, and any possible damage source is rapidly located. And performing ultrasonic dynamic scanning, continuously collecting images of the composite material thin-wall internal stress structure, and evaluating the structural integrity and the state change of the stress concentration area through image contrast analysis. The DIC system is used for continuously shooting the surface of the composite material workpiece, the image processing technology is used for accurately calculating the tiny deformation of the surface of the composite material thin-wall workpiece, and then a high-resolution strain distribution map is generated, and the strain and deformation distribution conditions of the surface of the composite material thin-wall structure are intuitively displayed.

S4, processing acoustic emission data to identify microscopic damage characteristics, analyzing and determining internal stress distribution of the composite workpiece by utilizing ultrasonic data, calculating a surface strain field according to DIC data, and constructing a stress-damage correlation model.

Specifically, environmental noise is filtered, and the acquired acoustic emission signals are subjected to denoising and amplification treatment, so that the signal quality is improved. Then adopting methods such as frequency spectrum analysis, waveform time domain feature extraction and the like to analyze signal features from frequency dimension, extracting unique modes of waveforms in time domain, and identifying microscopic damage features of assemblies of different types; and performing deep learning classification on the preprocessed signals by using a machine learning algorithm, identifying the corresponding damage type and evaluating the severity of the damage type.

Further, the ultrasonic discrete point stress detection data are enhanced and segmented, so that different medium interfaces are clearly distinguished in the image. And the propagation time of ultrasonic waves in the composite thin-wall workpiece and known sound velocity are utilized, the ToF data are combined to obtain the position and the size of the damage defect in the assembly structure, and then the material models such as the flight time ToF data and the mechanical structure of the aviation composite thin-wall workpiece can be combined, the stress concentration area and the distribution in the material are analyzed through an inversion algorithm, and the stress distribution mode is depicted.

Further, a digital image correlation DIC technology is used for accurately tracking the position change of each mark point in different assembly time periods, the surface micro strain is recorded, a composite material thin-wall surface displacement field is constructed, a strain and stress deformation transformation algorithm is applied based on the displacement field of the mark point, and an interpolation and gradient calculation method is adopted to calculate the strain distribution of the whole aviation composite material thin-wall observation surface, including main strain and shear strain.

Further, the damage characteristics of AE signal analysis, internal stress distribution information of ultrasonic detection and surface strain field data captured by DIC technology are synthesized, and based on a physical principle and a large amount of test data, quantitative association relation and model between stress and damage are analyzed by using a data driving method. The model is continuously verified and perfected through the comparison of continuous model parameter optimization and actual test results, so that the damage development trend of the composite structure under different working conditions can be accurately predicted.

And S5, integrating microscopic damage data, internal stress data and surface deformation data, precisely positioning the stress damage position and degree, and evaluating the influence of the assembly internal stress on the composite material damage behavior.

Specifically, the damage characteristic data monitored by AE, the internal stress distribution information revealed by ultrasonic detection and the surface strain field data provided by DIC technology are unified in format, so that compatibility among various data and synchronism in time are ensured. In addition, the data collected from different source heads is ensured to be aligned on a time axis so that the causal relationship of the event can be accurately reflected in subsequent analysis. And meanwhile, preprocessing such as outlier rejection and standardization processing is performed so as to eliminate potential deviation and noise and improve the accuracy of data analysis.

Further, the high-integration data resource is utilized, the time sequence and intensity information of AE signals, the internal structural details presented by an ultrasonic image and full-field strain field data provided by the DIC technology are combined, a multidimensional data fusion algorithm such as a Bayesian network is utilized to accurately position the damage position and the position with larger stress, and the full-field strain data of the DIC technology is utilized to assist in confirming the extension range of damage on the thin-wall surface of the composite material, so that the positioning accuracy is improved.

Further, by analyzing the frequency spectrum characteristics and the energy release rate of AE signals and combining an established damage model, the current severity degree of damage and the possible future development trend of the damage are estimated, the information of the internal crack length, the layering area and the like detected by ultrasonic are integrated to directly reflect the physical state of the damage, the surface deformation degree measured by DIC is integrated, and the damage degree is quantified by adopting a damage tolerance estimation method.

The method comprises the steps of obtaining a rigidity matrix and an elastic constant of a relation between stress and strain of a composite material through test and test of the composite material, monitoring assembly strain of the surface of a large-range composite material workpiece in a visual field range by using a multi-camera DIC, converting an assembly structure surface strain field obtained by a DIC system into a stress field, obtaining discrete point stress detection data of a key assembly part through an ultrasonic detection method, and combining the two to form a stress distribution state of the whole assembly.

Further, the actually measured stress distribution data are input into a finite element model for simulation calculation, how the stress generated in the assembly process affects the structural performance of the composite material thin wall is analyzed, an interaction mechanism between the assembly stress and the damage is evaluated, and whether a high risk area which can accelerate the development of the damage exists is identified.

Further, by combining all the measurement and analysis results, an evaluation report of the assembly performance of the composite thin-wall structure is compiled, wherein the report comprises the distribution of the damage position and the severity degree of the composite thin-wall structure, the stress strain distribution and the size of the composite thin-wall structure and the potential influence of the composite thin-wall structure on the assembly performance of the composite thin-wall part.

Specifically, a three-dimensional model is constructed by utilizing finite element analysis software ABAQUS, meshes are reasonably planned in a predicted stress concentration area and a predicted damage-prone position, the resolution and accuracy of simulation are improved, meanwhile, under different assembly process parameters, contact conditions, friction coefficients and possible pre-stress states are reasonably set, the physical reality of the model is ensured, and simulation data such as stress-strain response, displacement field distribution, damage sign distribution and the like are obtained.

Further, comparing the finite element simulation analysis data with the actual measurement data, identifying a deviation source between the model and the actual situation based on the comparison result, correcting and optimizing the finite element model by adjusting the simulation model, material parameters, thinning grids, improving boundary conditions or adopting a higher-level damage model, and continuously adjusting the simulation model parameters until the corrected prediction result is highly consistent with the test result.

Further, in a finite element simulation software environment, the corresponding assembly internal stress and damage analysis result are rapidly and accurately simulated by combining different assembly conditions and assembly process parameters, virtual measurement prediction verification of the assembly internal stress and damage result is achieved, the balance of assembly stress distribution and the occurrence risk of damage phenomenon are evaluated according to specific results, the rule of influence of the assembly process parameters and the internal stress on damage behaviors is clarified, the rationality and the effectiveness of the assembly process are judged and optimized according to detection results, and site assembly operation is rapidly and effectively guided.

The invention provides an accurate measurement technology for assembly stress and damage of an aviation composite thin-wall structure, which provides an effective solution idea for solving the problems that the assembly and use processes of the aviation composite thin-wall are difficult to monitor and evaluate the damage and stress state in real time by combining AE monitoring, ultrasonic detection and DIC monitoring technologies, and provides powerful technical support for accurate measurement of the composite structural stress and damage.

The invention mainly comprises three parts of contents, namely, formulation of an assembly stress and damage measurement scheme, multi-dimensional measurement data fusion processing analysis, virtual simulation correction and prediction verification. In the assembly process, AE is used for monitoring and capturing microscopic damage events in real time, ultrasonic detection is used for deeply analyzing the stress state in the structure, DIC technology records surface deformation and strain, the three work cooperatively, damage characteristic identification, stress field construction and surface strain analysis are realized through integration and conversion of microscopic damage data, internal stress data and surface deformation data, an accurate stress-damage association model is built through multidimensional data analysis and fusion, comprehensive and accurate data support can be provided for identification of complex stress and damage modes, finite element simulation models and parameters are corrected according to accurate test results, real consistency of numbers is realized, and virtual measurement prediction and verification work under other assembly process conditions can be carried out. Through example optimization verification, the invention can realize:

1) According to the material properties of the composite material and the structural characteristics of the thin-wall workpiece, key assembly stress transmission and potential damage areas are obtained through a finite element analysis method, a nondestructive measurement scheme for deploying assembly stress and damage of an acoustic emission system, an ultrasonic probe and DIC mark points is formed, and a multi-dimensional measurement system is formed through integration of three technologies.

2) The method comprises the steps of forming a multi-dimensional measurement data fusion processing analysis scheme of assembly stress and damage, processing acoustic emission data to identify microscopic damage characteristics, utilizing ultrasonic data analysis to determine internal stress distribution of a composite workpiece, calculating a surface strain field according to DIC data, and accurately positioning stress damage positions and degrees through integration and conversion of the microscopic damage data, the internal stress data and the surface deformation data, so that comprehensive and effective data support is provided for judging complex stress and damage modes, and the rule of influence of the assembly internal stress on composite damage behaviors is clarified.

3) The finite element simulation model and parameters are corrected according to accurate test results, the real numbers are consistent, virtual measurement prediction and verification work is carried out according to the real numbers, the balance of assembly stress distribution can be rapidly and accurately predicted, the risk of larger damage phenomenon is estimated, and the assembly test and measurement times are reduced.

Example 1:

In this embodiment, an example of application of a composite wing box of an aircraft is shown in fig. 3. Firstly, component structure analysis and material property evaluation are carried out, and data type measurement schemes such as microscopic damage, internal stress, surface deformation and the like of the wing box component assembly are determined. The method comprises the steps of constructing a composite wing box, such as analyzing geometric characteristics and material properties of a left wall, a right wall, each frame, rib plates, upper and lower wall plates, simulating stress distribution under different working conditions, determining key stress transmission paths and high stress concentration areas, identifying potential damage areas and common assembly quality problem areas in historical data, grasping response of each workpiece material to sound wave transmission characteristics such as sound velocity and attenuation through acoustic characteristic test, designing acoustic emission sensor layout, preferentially covering theoretical prediction points of the stress concentration areas and easy to crack to obtain microscopic damage data, planning probe paths of ultrasonic detection, ensuring ultrasonic energy to penetrate the inside of the wing box by utilizing a multi-angle arrangement strategy, realizing reconstruction of three-dimensional stress distribution, obtaining internal stress data of a composite wing box assembly, formulating graph distribution of digital image correlation method (DIC) marking points to improve accuracy of deformation tracking of each component workpiece, and carrying out ultrasonic sensor, The method comprises the steps of performing sensitivity calibration and frequency response test on monitoring equipment of an ultrasonic probe and a DIC system, performing image distortion correction on the DIC system through a standard sample to ensure accuracy and synchronism of data of the whole measurement system, performing simulation of an assembly process by using ABAQUS software to obtain predicted data of damage, stress and strain, performing visual display, verifying actual efficiency of the measurement system through comprehensive test of a wing box scaling model, comparing the simulated data with experimental data, and ensuring reliability and response speed of the measurement system. Secondly, on-site assembly and real-time monitoring are carried out, wherein AE sensors are bonded between composite wing box skeleton structures, between skeleton assemblies and upper and lower wall plates according to planning, wiring is optimized, an ultrasonic probe is installed by selecting a proper coupling agent, and meanwhile, high-contrast mark points are stuck on the surfaces of the wing boxes, so that a finished measuring system is built. Thirdly, starting a monitoring system, tracking AE signals in real time, carrying out ultrasonic scanning and DIC surface deformation, and immediately analyzing structural integrity and stress states between framework structures of wing boxes and between framework components and upper and lower wall plates. Fourthly, processing acoustic emission data to identify microscopic damage characteristics, analyzing and determining internal stress distribution among all the component parts of the composite wing box by utilizing ultrasonic data, calculating surface strain fields of all the component parts according to DIC data, and constructing a stress-damage association model. And integrating microscopic damage data, internal stress data and surface deformation data of the parts at each assembly stage, accurately positioning the stress damage position and degree, evaluating the influence of the assembly internal stress on the damage behavior of the wing box assembly body structure, integrating all analysis results, compiling a detailed structural performance evaluation report, determining the damage position, severity and stress distribution condition, and identifying potential risk areas. Finally, the interaction between the internal stress and the damage of each assembly stage of the composite wing box part is deeply explored by utilizing the finite element analysis and combining with the actual measurement data, and the finite element simulation model and parameters are corrected according to the accurate test result, so that virtual measurement prediction and verification work is performed, and the internal stress distribution balance under different assembly working conditions is rapidly and accurately predicted and the risk of larger damage phenomenon is evaluated. The precise measurement technology for the stress and damage of the composite wing box of the certain type of airplane comprises the following steps:

Specifically, the structural composition of the composite wing box part, such as a left wall, a right wall, each frame, rib plates, upper and lower wall plates and other workpieces, is subjected to geometric characteristic and material attribute analysis, the stress distribution under actual assembly working conditions is simulated, the key stress transmission path and the high stress concentration area are defined, and the potential damage area and the common assembly quality problem area in historical data are identified.

Further, the analysis wing box component is assembled by parts such as a left wall, a right wall, a first frame, a second frame, a third frame, a fourth frame, two rib plates, an upper wall plate and a lower wall plate, and then the geometric characteristics, the resin matrix, the types and the proportions of reinforcing fibers of each component, the sequence and the layout of a laminated structure are analyzed, and the influence of the composite material on the sound velocity, the attenuation, the reflection, the refraction and other propagation characteristics of sound waves is obtained by carrying out acoustic characteristic test on the material sample pieces of each component.

Further, based on the acoustic emission characteristics of the skeleton parts formed by the wing box parts, the acoustic emission sensors mounted on the parts such as the left wall, the right wall, the first frame, the second frame, the third frame, the fourth frame, the two rib plates, the upper wall plate and the lower wall plate are subjected to layout design, the acoustic emission sensors mounted on the parts mainly cover the areas with obvious stress paths and the places easy to crack and expand in historical experience or theoretical prediction, the sensor layout covers the key areas of the wing box, the sensitivity is high, and the fact that any tiny acoustic emission signals can be effectively captured is ensured, so that the internal stress data of the composite wing box assembly body is obtained.

Further, planning the probe path required by the ultrasonic detection technology in the critical area of each part of the wing box, considering the penetration depth and angle of each part of the wing box, ensures that the ultrasonic waves can cover the inside of the wing box in a full range, especially in the critical area. And reconstructing three-dimensional stress distribution in the wing box by adopting a multi-angle arrangement strategy and combining ultrasonic waves with different incidence angles, and obtaining internal stress data of the composite wing box assembly.

Further, in order to accurately measure the surface deformation and strain of each workpiece, a distribution diagram of mark points is designed on the parts such as a left wall, a right wall, a first frame, a second frame, a third frame, a fourth frame, two rib plates, an upper wall plate, a lower wall plate and the like of the wing box component parts, the density of the mark points is increased in the area with large expected deformation and the key measurement area, and the tracking precision of the DIC system on the micro deformation and strain of the surface of each workpiece formed by the wing box is improved.

Furthermore, the sensitivity and the frequency response of the AE sensor and the ultrasonic probe are calibrated, meanwhile, the standard deformation sample is used for calibrating the DIC system, the image distortion caused by the lens and the optical system is corrected, and the clock synchronization of the AE, the DIC and the ultrasonic monitoring system is ensured.

Furthermore, assembly simulation is carried out in ABAQUS according to the actual assembly process of the wing box, damage, stress and strain data of the inside and the surface of each part of the wing box are obtained through post-processing, and visual display is carried out by combining with cloud pictures.

Further, the simulation loading test of clamping and connecting loads and positioning position constraint thereof in the assembling process is carried out, the comprehensive test is carried out on the wing box shrinkage model, and the damage, stress and strain data of the inside and the surface of each component of the wing box obtained through the test are compared with the data obtained by ABAQUS, so that the response speed, the data quality and the capturing capability of a monitoring system under different working conditions for real damage events are verified.

Furthermore, based on the planned AE sensor arrangement scheme, a proper adhesive is selected, the AE sensor is adhered to each part of the wing box, and meanwhile, the connection line layout of the sensor is reasonably planned, so that unnecessary mechanical stress is avoided in the assembly process.

Further, for the field scene of the wing box, based on the planned arrangement scheme of the ultrasonic probe, the ultrasonic probe is installed, and as the materials of all the components of the wing box are different, the coupling agents with high matching degree of the materials are required to be respectively selected and installed. And a part of deployed probes are used for static detection, the integrity of the inside of the wing box before and after assembly is monitored, and the other part of the probes can be used for dynamic scanning, so that the internal stress change of the wing box structure in the assembly process is captured in real time, and particularly, the key parts for shielding the field vision and the hole periphery stress concentration parts for bolting are used.

Further, based on the above-described planned DIC-marker placement scheme, marker points with high contrast, i.e., stress zero points, are pasted on the wing box component surfaces.

Further, after the installation is finished, functional tests are carried out on the systems, simulated loading tests are carried out on the wing box parts, stress states of all the component parts of the wing box in the actual assembly process are simulated, the monitoring and measuring systems are used for testing, data acquired by the ABAQUS are compared, and the response capacity and the data acquisition accuracy of the monitoring system are verified.

Further, an AE monitoring system is started, a reasonable signal threshold is set according to early analysis, the data acquisition speed is optimized, and the real-time and accurate recording of the tiny damage is ensured. For an ultrasonic detection system, a scanning path and parameter setting are planned, a high-precision ultrasonic probe is selected, and the internal stress change of the composite wing box part is dynamically monitored. For the DIC system, the position and the view angle of the high-speed camera are adjusted, so that high-contrast mark points on the surfaces of all parts of the wing box can be clearly captured under any illumination condition.

Further, when the wing box is assembled on the tooling (fig. 4), the AE monitoring system is started, each acoustic emission signal is analyzed through a signal processing algorithm, and any possible damage sources of all parts of the wing box are rapidly positioned. And performing ultrasonic dynamic scanning, continuously collecting stress structure images in the wing box, and evaluating structural integrity and stress state change of each assembly stage of the wing box through image contrast analysis. The DIC system is used for continuously shooting the surfaces of the workpieces formed by the wing boxes in the assembly process, the image processing and DIC algorithm is used for calculating the tiny deformation and strain state of the surfaces of the workpieces of the wing boxes, a high-resolution strain distribution map is generated, and the strain and deformation distribution conditions of the surfaces of the composite wing box structure are intuitively displayed.

Further, environmental noise is filtered, noise removal and amplification processing are carried out on the collected acoustic emission signals, signal characteristics are analyzed from frequency dimension by adopting methods such as frequency spectrum analysis, waveform time domain characteristic extraction and the like, meanwhile, unique modes of waveforms are extracted in time domain, microscopic damage characteristics of assemblies of different types are identified, a machine learning algorithm is used for carrying out deep learning classification on the preprocessed signals, damage types corresponding to each assembly stage of the wing box are identified, and severity of the damage types is estimated.

Further, the ultrasonic discrete point stress detection data are enhanced and segmented, so that different medium interfaces are clearly distinguished in the image. And (3) acquiring the position and the size of the damage defect in the wing box structure by utilizing the propagation time of ultrasonic waves in the composite wing box workpiece and the known sound velocity and combining the TOF data, then analyzing the stress concentration area and distribution in the material by an inversion algorithm by combining the time-of-flight TOF data with a mechanical structure and other material models of the composite wing box workpiece, and drawing the stress distribution mode.

Further, the digital image related DIC technology is used for accurately tracking the position change of each mark point in different assembly time periods, recording the tiny strain of the surfaces of parts in the wing box assembly process, constructing a surface displacement field, applying a strain and stress deformation transformation algorithm based on the displacement field of the mark point, and adopting interpolation and gradient calculation methods to calculate the strain distribution of the observation surfaces of the parts such as the left wall, the right wall, the first frame, the second frame, the third frame, the fourth frame, the two rib plates, the upper wall plate and the lower wall plate, and the like, including main strain and shear strain.

Further, the damage characteristics of AE signal analysis, the internal stress distribution information of the wing box detected by ultrasonic and the surface strain field data of each part of the wing box captured by DIC technology are fused, and a quantitative model between stress and damage is constructed by a data driving method based on a physical principle and a large amount of test data.

Further, the damage characteristics of AE signal analysis, internal stress distribution information of ultrasonic detection and surface strain field data captured by DIC technology are synthesized, based on physical principles and a large amount of test data, through unification of data formats and alignment of data collected from different source heads on a time axis, pretreatment such as outlier rejection and standardization treatment is needed to eliminate potential deviation and noise, and then quantitative association relation and model between wing box assembly internal stress and damage are analyzed by a data driving method. The model is continuously verified and perfected through the comparison of continuous model parameter optimization and actual test results, so that the damage development trend of the composite wing box structure under different working conditions can be accurately predicted.

Furthermore, the method utilizes highly integrated data resources, combines time sequence and intensity information of AE signals, internal structural details presented by an ultrasonic image and full-field strain field data provided by a DIC technology, utilizes a multidimensional data fusion algorithm such as a Bayesian network to accurately position damaged positions and larger stress positions of components of the wing box, utilizes the full-field strain data of the DIC technology to assist in confirming the extending range of damage on the surface of a composite workpiece, and improves the positioning accuracy of damaged positions of the components of the wing box.

Further, by analyzing the frequency spectrum characteristics and the energy release rate of the AE signals, and combining the established damage model, the current severity degree of damage and the possible future development trend thereof are estimated, the information of the ultrasonic detection on the internal crack length, the layering area and the like which directly reflect the physical state of the damage is integrated, the surface deformation degree measured by the DIC is integrated, and the damage degree of the wing box part under the current assembly process is quantified by adopting a damage tolerance estimation method.

Further, the stiffness matrix and the elastic constant of the relation between the stress and the strain of the composite material are obtained through the test and the test of the composite material used by the wing box part, the assembly strain monitoring of the surface of a large-range wing box workpiece in the visual field range is carried out by using a multi-camera DIC, the surface strain field of an assembly structure obtained by a DIC system is converted into a stress field, the stress detection data of discrete points of key parts of each assembly stage of the wing box part are obtained through an ultrasonic detection method, and the stress detection data are combined to form the stress distribution state of the whole composite material wing box assembly body.

Further, the actually measured stress distribution data are input into a finite element model corresponding to each assembly stage of the wing box to carry out simulation calculation, how the stress generated in the assembly process affects the structural performance of the whole wing box part is analyzed, an interaction mechanism between the assembly stress and the damage is evaluated, and whether a high risk area which can accelerate the development of the damage exists is identified.

Further, based on all the analysis results, a wing box structure performance evaluation report is compiled, wherein the report comprises distribution of internal damage positions and severity degrees, stress distribution areas and sizes corresponding to each assembly stage of the wing box, and potential influences of stress concentration areas in the wing box assembly process on the assembly performance of the wing box.

Further, a three-dimensional model of the wing box assembly process is constructed by utilizing finite element analysis software ABAQUS, grids are reasonably planned in a predicted stress concentration area and a damage easily-occurring part, the resolution and accuracy of simulation are improved, meanwhile, under different assembly process parameters, contact conditions, friction coefficients and possible prestress states are reasonably set, the physical reality of the wing box assembly performance simulation model is ensured, and simulation data such as stress-strain response, displacement field distribution, damage sign distribution and the like are obtained.

Further, comparing the finite element simulation analysis data of the composite wing box assembly process with the actual measurement data, identifying a deviation source between the model and the actual situation based on the comparison result, correcting and optimizing the finite element model by adjusting the simulation model, material parameters, thinning grids, improving boundary conditions or adopting a higher-level damage model, and continuously adjusting the simulation model parameters until the corrected wing box assembly performance prediction result is highly consistent with the test measurement result.

Further, in a finite element simulation software environment, by combining different assembly conditions and assembly process parameters, the assembly internal stress and damage analysis results corresponding to each assembly stage of the wing box are rapidly and accurately simulated, virtual measurement prediction verification of the assembly internal stress and damage results is achieved, the balance of assembly stress distribution and the occurrence risk of damage phenomenon are evaluated according to specific results, the influence rule of the assembly process parameters and the internal stress on the damage behavior of the whole assembly structure of the wing box is clarified, the rationality and the effectiveness of the assembly process are discriminated and optimized according to detection results, and the field assembly operation of the wing box part is rapidly and effectively guided.

The invention provides an accurate measurement technology for assembly stress and damage of an aviation composite thin-wall structure, which mainly comprises the following three parts of formulation of an assembly stress and damage measurement scheme, fusion processing analysis of multidimensional measurement data, virtual simulation correction and prediction verification. In the assembly process, AE is used for monitoring and capturing microscopic damage events in real time, ultrasonic detection is used for deeply analyzing the stress state in the structure, DIC technology records surface deformation and strain, the three work cooperatively, damage characteristic identification, stress field construction and surface strain analysis are realized through integration and conversion of microscopic damage data, internal stress data and surface deformation data, an accurate stress-damage association model is built through multidimensional data analysis and fusion, comprehensive and accurate data support can be provided for identification of complex stress and damage modes, finite element simulation models and parameters are corrected according to accurate test results, real consistency of numbers is realized, and virtual measurement prediction and verification work under other assembly process conditions can be carried out. ① according to the material property of the composite material and the structural characteristics of the thin-wall workpiece, acquiring key assembly stress transmission and potential damage areas by means of finite element analysis, forming a nondestructive measurement scheme for the assembly stress and damage of an acoustic emission system, an ultrasonic probe and DIC mark points, and forming a multi-dimensional measurement system by integrating three technologies. ② The method comprises the steps of forming a multi-dimensional measurement data fusion processing analysis scheme of assembly stress and damage, processing acoustic emission data to identify microscopic damage characteristics, utilizing ultrasonic data analysis to determine internal stress distribution of a composite workpiece, calculating a surface strain field according to DIC data, and accurately positioning stress damage positions and degrees through integration and conversion of the microscopic damage data, the internal stress data and the surface deformation data, so that comprehensive and effective data support is provided for judging complex stress and damage modes, and the rule of influence of the assembly internal stress on composite damage behaviors is clarified. ③ The finite element simulation model and parameters are corrected according to the accurate test result, the consistency between the digital simulation and the real measurement result is ensured, virtual measurement prediction and verification work is carried out, the balance of assembly stress distribution can be rapidly and accurately predicted, the risk of larger damage phenomenon is estimated, and the assembly test and measurement times are reduced.

The method and the system for accurately measuring the assembly stress and the damage of the aviation composite thin-wall structure provided by the embodiment of the application are described in detail. While the foregoing examples have been provided to assist those of ordinary skill in the art in understanding the methods and concepts underlying the application, those skilled in the art will recognize that there may be variations in the embodiments and applications of the application in light of the foregoing, and that the application is not to be construed as limited to what is described herein.

Certain terms are used throughout the description and claims to refer to particular components. Those of skill in the art will appreciate that a hardware manufacturer may refer to the same component by different names. The description and claims do not take the form of an element differentiated by name, but rather by functionality. As referred to throughout the specification and claims, the terms "comprising," including, "and" includes "are intended to be interpreted as" including/comprising, but not limited to. By "substantially" is meant that within an acceptable error range, a person skilled in the art is able to solve the technical problem within a certain error range, substantially achieving the technical effect. The description hereinafter sets forth a preferred embodiment for practicing the application, but is not intended to limit the scope of the application, as the description is given for the purpose of illustrating the general principles of the application. The scope of the application is defined by the appended claims.

It should also be noted that the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a product or system that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such product or system. Without further limitation, an element defined by the phrase "comprising one of the elements" does not exclude the presence of additional identical elements in a commodity or system comprising the element.

It should be understood that the term "and/or" as used herein is merely an association relationship describing the associated object, and means that there may be three relationships, e.g., a and/or B, and that there may be three cases where a exists alone, while a and B exist together, and B exists alone. In addition, the character "/" herein generally indicates that the front and rear associated objects are an "or" relationship.

While the foregoing description illustrates and describes the preferred embodiments of the present application, it is to be understood that the application is not limited to the forms disclosed herein, but is not to be construed as limited to other embodiments, and is capable of numerous other combinations, modifications and environments and is capable of changes or modifications within the scope of the inventive concept as expressed herein, either as a result of the foregoing teachings or as a result of the knowledge or technology of the relevant art. And that modifications and variations which do not depart from the spirit and scope of the application are intended to be within the scope of the appended claims.

Claims

1. The method for accurately measuring the assembly stress and the damage of the aviation composite thin-wall structure is characterized by comprising the following steps of:

2. The method for precisely measuring assembly stress and damage of an aviation composite thin-wall structure according to claim 1, wherein the S1 specifically comprises:

3. The method for precisely measuring assembly stress and damage of an aviation composite thin-wall structure according to claim 1, wherein the step S2 specifically comprises:

4. The method for precisely measuring assembly stress and damage of an aviation composite thin-wall structure according to claim 1, wherein the step S3 specifically comprises:

5. The method for precisely measuring assembly stress and damage of an aviation composite thin-wall structure according to claim 1, wherein the step S4 specifically comprises:

6. The method for precisely measuring assembly stress and damage of an aviation composite thin-wall structure according to claim 1, wherein the step S5 specifically comprises:

7. The method for accurately measuring assembly stress and damage of an aviation composite thin-wall structure according to claim 6, wherein the preprocessing in S51 comprises alignment on a time axis and outlier rejection and standardization processing.

8. The method for accurately measuring assembly stress and damage of an aviation composite thin-wall structure according to claim 6, wherein the step of obtaining the stress distribution state of the whole assembly in the step S54 comprises the steps of obtaining a rigidity matrix and an elastic constant of the relation between stress and strain of the composite material through a test of the composite material, and converting an assembly structure surface strain field obtained by a DIC system into a stress field.

9. The method for precisely measuring assembly stress and damage of an aviation composite thin-wall structure according to claim 1, wherein the step S6 specifically comprises:

10. The utility model provides an accurate measurement system of aviation composite thin wall structure assembly stress and damage, its characterized in that, accurate measurement system of aviation composite thin wall structure assembly stress and damage includes: