Composite material resin matrix interface ultrasonic cross-scale detection method and device

Abstract

The application discloses a kind of composite material resin matrix interface ultrasonic cross-scale detection method and device, comprising: in response to micro modeling instruction, the microstructure of fiber reinforced resin matrix composite is determined representative volume element model, the equivalent stiffness of fiber and resin interface region in model is determined and introduced interface damage variable, based on the micro simulation result of ultrasonic incident signal of multiple frequency bands applied to model, frequency and interface damage sensitivity distribution are determined, based on sensitivity distribution, determine sensitive frequency band and generate multiple frequency combination;In response to multi-frequency detection instruction, based on multiple frequency combination, macro multi-frequency ultrasonic detection is carried out on the surface of the composite material structure to be detected, to determine the echo signal of each frequency band;In response to echo signal collection completion instruction, based on echo signal, determine multi-frequency ultrasonic characteristics, input interface equivalent stiffness and multi-frequency response mapping model into multi-frequency ultrasonic characteristics, determine the interface damage variable distribution of each detection area based on inversion algorithm, generate the spatial distribution and damage grade of resin matrix interface damage.

Description

Technical Field

[0001] This invention relates to the field of ultrasonic cross-scale testing technology for composite resin matrix interfaces, and more specifically, to a method and apparatus for ultrasonic cross-scale testing of composite resin matrix interfaces. Background Technology

[0002] Fiber-reinforced resin matrix composites, due to their advantages such as high specific strength, high specific stiffness, good corrosion resistance, and customizable design, have been widely used in critical load-bearing components such as large aircraft, launch vehicles, wind turbine blades, and rail transit vehicles. Their overall mechanical properties and service safety are highly dependent on the load-bearing capacity and damage resistance of the resin matrix and the fiber / resin interface. Currently, non-destructive testing of composite structures has formed a technical system mainly based on ultrasonic C-scan, phased array imaging, X-ray CT, and acoustic emission, achieving significant progress in detecting molding defects such as macroscopic delamination, porosity, and foreign matter inclusions. However, existing ultrasonic testing methods lack sufficient sensitivity to detect microscale degradation phenomena such as microcracks in the resin matrix, small pores, early aging, and slight reductions in the equivalent stiffness of the fiber / resin interface. In engineering, the frequency selection for multi-frequency or broadband ultrasonic testing is often based on an empirical compromise of "high frequency for high resolution and low frequency for strong penetration," focusing more on macroscopic defect identification and lacking quantitative physical evidence for interface damage. Meanwhile, although multi-scale numerical simulation has developed rapidly in the field of composite materials, existing work focuses on stress-strain and strength-life prediction, making it difficult to invert the microscopic interface damage state using limited macroscopic ultrasonic testing data. The ability to correlate macroscopic and microscopic scales is seriously insufficient, resulting in the inability to provide reliable early warnings when stratification has not yet formed or is not yet obvious. Summary of the Invention

[0003] This invention provides a method and apparatus for ultrasonic cross-scale detection of composite resin matrix interfaces, which at least solves the technical problems in the prior art of lacking physical basis for frequency selection in ultrasonic detection of composite materials, difficulty in quantitatively characterizing early microscopic degradation of resin matrix and fiber / resin interface, and insufficient macro-micro cross-scale correlation.

[0004] According to one aspect of the present invention, in order to achieve the above-mentioned objective, a method for ultrasonic cross-scale testing of the interface of a composite resin matrix is ​​provided, comprising:

[0005] In response to the micro-modeling command, a representative volume element model is determined based on the microstructure of fiber-reinforced resin matrix composites. The equivalent stiffness of the fiber-resin interface region in the model is determined and the interface damage variable is introduced. Based on the micro-simulation results of applying ultrasonic incident signals of multiple frequency bands to the model, the frequency and interface damage sensitivity distribution are determined. Based on the sensitivity distribution, the sensitive frequency band is determined and a multi-frequency combination is generated.

[0006] Macroscopic multi-frequency ultrasonic testing is performed on the surface of the composite material structure under test based on multi-frequency combination to determine the echo signal of each frequency band.

[0007] Multi-frequency ultrasonic features are determined based on echo signals. These features are then input into an interface equivalent stiffness and multi-frequency response mapping model. An inversion algorithm is used to determine the distribution of interface damage variables in each detection area, generating the spatial distribution and damage level of the resin matrix interface damage.

[0008] Furthermore, the equivalent stiffness of the interface region is determined and an interface damage variable is introduced, including:

[0009] The fiber-resin interface is defined as a bonding zone unit with normal stiffness and tangential stiffness, and the equivalent normal stiffness and tangential stiffness of the interface are determined.

[0010] The equivalent normal and tangential stiffness of the interface under healthy conditions are determined. The normal and tangential stiffness of the interface decrease proportionally with the increase of the interface damage variable.

[0011] Further, the frequency and interface damage sensitivity distribution are determined, including:

[0012] Based on the rate of change of the amplitude of the reflection coefficient corresponding to each candidate frequency under different interface damage variables, the sensitivity index of each candidate frequency to the interface damage variables is determined.

[0013] Based on the sensitivity index, determine the frequency versus interface damage sensitivity curve;

[0014] Based on a preset multiple threshold, frequency points whose sensitivity is higher than the average sensitivity of the entire frequency band by a preset multiple are determined as interface sensitive frequencies.

[0015] Furthermore, the multi-frequency combination is a multi-frequency ultrasound detection scheme generated by combining multiple interface-sensitive frequencies. The multi-frequency combination includes a low-frequency band that is sensitive to deep interface damage and a high-frequency band that is sensitive to superficial interface damage.

[0016] Furthermore, based on multi-frequency combination, macroscopic multi-frequency ultrasonic testing is performed on the surface of the composite material structure to be tested to determine the echo signals of each frequency band, including:

[0017] Based on ultrasonic transducers or phased array probes arranged on the surface of the composite material structure to be tested, ultrasonic waves are sequentially excited according to a multi-frequency combination.

[0018] The echo signals at each excitation frequency are determined, and the echo signals are spatially partitioned and numbered based on the detection area.

[0019] Furthermore, after determining the echo signals in each frequency band, the process also includes:

[0020] The determined multi-frequency ultrasound signal is preprocessed, including noise reduction, time window truncation, normalization, and frequency division filtering.

[0021] Furthermore, the mapping model between the interface equivalent stiffness and the multi-frequency response is determined, including:

[0022] Based on a representative volume element model and specimens, the multi-frequency ultrasonic response under different interface damage variables was determined.

[0023] Data set was determined based on interface damage variables and multi-frequency ultrasound features;

[0024] Based on the fitting of multivariate regression or machine learning methods, the mapping relationship from multi-frequency ultrasonic feature quantities to interface damage variables is determined, and a surrogate model characterizing the equivalent stiffness and interface damage of the interface is generated.

[0025] Furthermore, the distribution of interface damage variables in each detection area is determined based on the inversion algorithm, including:

[0026] Based on multi-frequency ultrasonic features and mapping models, least squares inversion, Bayesian inversion, or machine learning-based surrogate model regression methods are used to determine the interface equivalent stiffness parameters and interface damage variables corresponding to each detection area in the macrostructure.

[0027] According to one embodiment of the present invention, an ultrasonic cross-scale testing device for the interface of a composite resin matrix is ​​also provided, comprising:

[0028] The response module is used to respond to micro-modeling instructions, determine representative volume element models based on the microstructure of fiber-reinforced resin matrix composites, determine the equivalent stiffness of the fiber-resin interface region in the model and introduce interface damage variables, determine the frequency and interface damage sensitivity distribution based on the micro-simulation results of applying ultrasonic incident signals of multiple frequency bands to the model, determine the sensitive frequency bands based on the sensitivity distribution and generate multi-frequency combinations.

[0029] The determination module is used to perform macroscopic multi-frequency ultrasonic testing on the surface of the composite material structure to be tested based on multi-frequency combination, and to determine the echo signal of each frequency band.

[0030] The generation module is used to determine multi-frequency ultrasonic features based on echo signals, input the multi-frequency ultrasonic features into the interface equivalent stiffness and multi-frequency response mapping model, determine the distribution of interface damage variables in each detection area based on the inversion algorithm, and generate the spatial distribution and damage level of the resin matrix interface damage.

[0031] According to another aspect of the present invention, a computer-readable storage medium is also provided, the computer-readable storage medium including a stored executable program, wherein, when the executable program is executed, it controls the device where the computer-readable storage medium is located to perform the methods of various embodiments of the present invention.

[0032] In this embodiment of the invention, by establishing a microscopic interface equivalent stiffness and multi-frequency ultrasonic response model, the frequency and interface damage sensitivity distribution are determined with the interface damage variable sensitivity as the optimization objective. Based on this, the frequency band most sensitive to interface damage is selected and a multi-frequency combination is generated, providing a clear physical basis for frequency selection and effectively improving the detection sensitivity for early damage such as microcracks and interface weakening in the resin matrix. On this basis, echo signals of each frequency band are acquired through macroscopic multi-frequency ultrasonic detection. Multi-frequency ultrasonic features are extracted and input into the pre-established interface equivalent stiffness and multi-frequency response mapping model. An inversion algorithm is used to determine the interface damage variable distribution in each detection area, generating the spatial distribution and damage level of the resin matrix interface damage. This achieves cross-scale quantitative characterization from microscopic interface equivalent stiffness parameters to macroscopic structural coordinates, enabling early warning before macroscopic delamination occurs and providing reliable data support for the safety assessment and life prediction of composite material structures. Attached Figure Description

[0033] The accompanying drawings, which are included to provide a further understanding of the invention and form part of this application, illustrate exemplary embodiments of the invention and, together with their description, serve to explain the invention and do not constitute an undue limitation thereof. In the drawings:

[0034] Figure 1 This is a flowchart of an ultrasonic cross-scale detection method for the interface of a composite resin matrix according to one embodiment of the present invention;

[0035] Figure 2 This is a flowchart of an ultrasonic cross-scale detection method for the interface of a composite resin matrix according to one embodiment of the present invention;

[0036] Figure 3 This is a structural block diagram of an ultrasonic cross-scale testing device for the interface of a composite resin matrix according to one embodiment of the present invention. Detailed Implementation

[0037] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0038] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0039] According to an embodiment of the present invention, an embodiment of an ultrasonic cross-scale detection method for the interface of a composite resin matrix is ​​provided. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Furthermore, although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order than that shown here.

[0040] This method embodiment can be executed in an electronic device or similar computing device that includes memory and a processor. Taking operation on a terminal as an example, the terminal may include one or more processors (processors may include, but are not limited to, central processing units (CPUs), graphics processing units (GPUs), digital signal processing (DSP) chips, microcontroller units (MCUs), field-programmable gate arrays (FPGAs), neural network processors (NPUs), tensor processors (TPUs), artificial intelligence (AI) type processors, etc.) and memory for storing data. Optionally, the terminal may also include transmission devices, input / output devices, and display devices for communication functions. Those skilled in the art will understand that the above structural description is merely illustrative and does not limit the structure of the terminal. For example, the terminal may include more or fewer components than described above, or have a different configuration than described above.

[0041] The memory can be used to store computer programs, such as application software programs and modules, like the computer program corresponding to the ultrasonic cross-scale detection method for composite resin matrix interfaces in this embodiment of the invention. The processor executes various functional applications and data processing by running the computer program stored in the memory, thereby realizing the aforementioned ultrasonic cross-scale detection method for composite resin matrix interfaces. The memory may include high-speed random access memory, and may also include non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some instances, the memory may further include memory remotely located relative to the processor, and these remote memories can be connected to a mobile terminal via a network. Examples of such networks include, but are not limited to, the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof.

[0042] The transmission device is used to receive or send data via a network. Specific examples of the network mentioned above may include a wireless network provided by the mobile terminal's communication provider. In one example, the transmission device includes a Network Interface Controller (NIC), which can connect to other network devices via a base station to communicate with the Internet. In another example, the transmission device may be a Radio Frequency (RF) module, used for wireless communication with the Internet.

[0043] Display devices can be, for example, touchscreen liquid crystal displays (LCDs) and touch displays (also referred to as "touchscreens" or "touch displays"). The LCD allows users to interact with the user interface of the mobile terminal. In some embodiments, the mobile terminal has a graphical user interface (GUI), which allows users to interact with the GUI through finger contact and / or gestures on a touch-sensitive surface. Optional human-computer interaction functions include: creating web pages, drawing, word processing, creating electronic documents, playing games, video conferencing, instant messaging, sending and receiving emails, call interfaces, playing digital video, playing digital music, and / or web browsing, etc. Executable instructions for performing the above human-computer interaction functions are configured / stored in one or more processor-executable computer program products or readable storage media.

[0044] Figure 1 This is a flowchart of an ultrasonic cross-scale detection method for the interface of a composite resin matrix according to one embodiment of the present invention, as follows: Figure 1 As shown, the method includes the following steps:

[0045] Step S110: In response to the microscopic modeling command, a representative volumetric element model is determined based on the microstructure of the fiber-reinforced resin matrix composite material. The equivalent stiffness of the fiber-resin interface region in the model is determined, and an interface damage variable is introduced. Based on the microscopic simulation results of applying ultrasonic incident signals at multiple frequency bands to the model, the frequency and interface damage sensitivity distribution are determined. Based on the sensitivity distribution, sensitive frequency bands are determined, and multi-frequency combinations are generated. The specific details are as follows:

[0046] In step S110, after the detection process is initiated, the system first responds to the microscopic modeling command by acquiring the laminated ply information, material parameters, and geometric information of the composite material structure to be tested. Specifically, this includes fiber type, resin type, fiber volume fraction, ply angle, layer thickness, and structural dimensions. Based on this structural information, representative fiber and resin microstructural regions are selected to construct a microscopic representative volumetric unit model, i.e., the RVE model. This model includes the fiber phase, the resin matrix phase, and the interface region between the fibers and resin, which is used for subsequent ultrasonic propagation simulation analysis at the microscale.

[0047] After the RVE model is constructed, it is necessary to model the equivalent stiffness of the fiber-resin interface region. Specifically, the fiber-resin interface is equivalent to a bonded zone element with normal and tangential stiffness to characterize the mechanical behavior of the interface under normal and tangential loads. The equivalent normal and tangential stiffness of the interface under healthy conditions are determined through experimental data, literature data, or numerical back-calculation. Based on this, an interface damage variable is introduced, and the interface degradation process is characterized as a proportional decrease in both normal and tangential stiffness as the damage variable increases. The quantitative relationship between the equivalent stiffness of the interface and the damage variable is determined as the core parameter for subsequent microscopic simulation and sensitivity analysis.

[0048] Subsequently, ultrasonic incident signals of multiple frequency bands were applied to the RVE model. The incident waves included multiple sets of longitudinal waves, transverse waves, or guided waves of different frequencies within a predetermined frequency range. Using the time-domain finite element method or the frequency-domain finite element method, batch simulations were performed under different frequencies and interface damage variables. The reflected wave, transmitted wave, and scattered wave responses under each condition were calculated, and the corresponding ultrasonic characteristic quantities were extracted, including but not limited to reflection coefficient, transmission coefficient, phase difference, spectral energy distribution, and waveform distortion index. Through the above microscopic multi-frequency ultrasonic propagation simulation, the influence of different interface damage states on the ultrasonic propagation characteristics of each candidate frequency was obtained.

[0049] Based on the microscopic simulation results, for each candidate frequency, its sensitivity index to interface damage variables is calculated. This sensitivity index is characterized by the rate of change of ultrasonic characteristic quantities. Specifically, the rate of change of reflection coefficient amplitude is calculated under different interface damage variables, and the sensitivity index of each candidate frequency to interface damage variables is determined based on the rate of change of reflection coefficient amplitude. Based on the calculated sensitivity index, a frequency-interface damage sensitivity curve is plotted, which reflects the sensitivity of different frequencies to changes in interface damage state.

[0050] After obtaining the frequency versus interface damage sensitivity curve, frequency points with sensitivity to interface damage variables exceeding a preset threshold are selected as interface-sensitive frequencies. Multiple selected interface-sensitive frequencies are then combined and optimized to generate a multi-frequency combination for actual structural testing. This multi-frequency combination includes a low-frequency band sensitive to deep interface damage and a high-frequency band sensitive to shallow interface damage, thus achieving effective coverage of interface damage states at different depths. This multi-frequency combination serves as the excitation signal scheme for subsequent multi-frequency ultrasonic testing of macroscopic structures, providing a data foundation for cross-scale inversion.

[0051] Step S120: Perform macroscopic multi-frequency ultrasonic testing on the surface of the composite material structure to be tested based on multi-frequency combination to determine the echo signals of each frequency band. The specific details are as follows:

[0052] In step S120, after completing the selection of interface-sensitive frequency bands and multi-frequency combination optimization at the microscale, the process proceeds to the macroscopic structure multi-frequency ultrasonic testing stage. First, based on the actual shape and size of the composite material structure to be tested, ultrasonic transducers or phased array probes are arranged on the structural surface. For flat components, immersion-type or coupling agent-type longitudinal wave probes can be used for grid scanning; for large curved components, a robotic scanning system or flexible array probes can be combined to complete the transducer arrangement and positioning, ensuring that the coupling state between the probe and the surface to be tested meets the testing requirements.

[0053] After the transducers are arranged, ultrasonic waves are excited sequentially or simultaneously according to the multi-frequency combination optimized in the microscopic simulation stage. This multi-frequency combination includes multiple interface-sensitive frequencies that are sensitive to interface damage. The excitation signal can be a multi-tone superposition signal composed of each interface-sensitive frequency band or a linear frequency modulated signal to shorten the detection time. For each excitation frequency, the ultrasonic transducer emits ultrasonic waves into the interior of the composite material structure to be tested. During propagation, the ultrasonic waves interact with the resin matrix and fiber / resin interface inside the structure. The echo signal carrying interface state information is received and recorded by the same transducer or other receiving transducers.

[0054] While acquiring echo signals at various excitation frequencies, the ultrasonic signals are spatially partitioned and numbered according to the detection area. Specifically, for flat laminated plate structures, ultrasonic detection sections and scanning lines can be set at predetermined intervals along the length and width directions to form a grid-like detection mesh; for curved components such as wind turbine blade main beams and automobile body side panels, reasonable detection areas can be divided according to structural geometric characteristics, and each detection point can be calibrated and numbered. Through spatial partitioning and numbering, it is ensured that the interface damage variables obtained in subsequent inversion can correspond one-to-one with the specific spatial location of the macroscopic structure.

[0055] After acquiring the raw echo signals, the acquired multi-frequency ultrasonic signals need to be preprocessed to improve signal quality and suppress noise interference. Preprocessing specifically includes: denoising the signal to eliminate noise components caused by electromagnetic interference and mechanical vibration in the detection environment; truncation of the signal within a time window to extract the echo signal within the effective sound path range and filter out irrelevant signal components such as boundary reflections; normalization of the signal to eliminate the influence of differences in transducer coupling states and signal amplitude fluctuations; and frequency-division filtering to effectively separate the components of each frequency band, thereby obtaining a multi-frequency ultrasonic signal consistent with the characteristic quantities corresponding to the microscopic simulation stage, providing a reliable data foundation for subsequent feature extraction and cross-scale inversion.

[0056] Step S140: Based on the echo signal, determine the multi-frequency ultrasonic features, input the multi-frequency ultrasonic features into the interface equivalent stiffness and multi-frequency response mapping model, and determine the interface damage variable distribution in each detection area based on the inversion algorithm to generate the spatial distribution and damage level of the resin matrix interface damage. The specific content is as follows:

[0057] In step S140, after completing the macroscopic multi-frequency ultrasonic detection and acquiring echo signals from each measurement point and frequency band, the process proceeds to feature extraction and cross-scale inversion. First, feature extraction is performed on the preprocessed multi-frequency ultrasonic signal, extracting ultrasonic features corresponding to the microscopic simulation stage, including but not limited to reflection coefficient, transmission coefficient, time delay, spectral energy distribution, and center frequency drift at each frequency point. For each detection measurement point, the ultrasonic features extracted at different excitation frequencies are combined into a multi-frequency ultrasonic feature vector. This feature vector contains multi-dimensional information about the state of the resin matrix and fiber / resin interface at that location, serving as input data for subsequent inversion calculations.

[0058] After feature extraction, the multi-frequency ultrasonic feature vectors of each detection point are input into a pre-established interface equivalent stiffness and multi-frequency response mapping model. This mapping model is based on a representative volume element model and small-sized specimens. Through batch simulations of multi-frequency ultrasonic responses under different interface damage variables, a dataset consisting of interface damage variables and multi-frequency ultrasonic feature quantities is constructed. A surrogate model is then fitted using multiple regression or machine learning methods. This surrogate model characterizes the mapping relationship between multi-frequency ultrasonic feature quantities and interface damage variables, serving as the core link for realizing cross-scale correlation between microscopic interface parameters and macroscopic ultrasonic responses.

[0059] After sequentially inputting the multi-frequency ultrasonic feature vectors of each detection point into the aforementioned mapping model, the equivalent interface stiffness parameters and interface damage variables corresponding to each detection point region are calculated based on the inversion algorithm. Specifically, the inversion algorithm can employ the least squares inversion method, the Bayesian inversion method, or the surrogate model regression method based on machine learning. It uses the measured multi-frequency ultrasonic features to inversely deduce the specific values ​​of the interface damage variables, achieving a quantitative inversion from macroscopic ultrasonic detection data to microscopic interface mechanical parameters. Through the above inversion calculation, the interface damage variables and the reduction ratio of the equivalent interface stiffness corresponding to each detection region of the composite material structure under test can be obtained, establishing a quantitative correspondence from the microscopic interface damage state to the macroscopic structural location.

[0060] After obtaining the interface damage variables for all test points, the damage level is classified according to the magnitude of the interface damage variables. Specifically, when the interface damage variable is less than the first threshold, the interface is considered basically intact; when the interface damage variable is between the first and second thresholds, it is considered slightly degraded; when the interface damage variable is between the second and third thresholds, it is considered moderately degraded; and when the interface damage variable is greater than or equal to the third threshold, it is considered severely degraded or has significant debonding. The interface damage variables and damage levels of each test point are correlated with the macroscopic structural coordinates, and an interpolation method is used to generate a cross-scale distribution map of resin matrix / interface damage covering the entire test area. This distribution map can intuitively display the interface damage state at each spatial location. Finally, the cross-scale damage distribution map, damage level information for each region, and corresponding interface equivalent stiffness parameters are output as test results, realizing cross-scale detection and quantitative evaluation of composite resin matrix and fiber / resin interface from micro to macro, providing a basis for safety assessment and maintenance decisions of composite structures.

[0061] Based on steps S110 to S140 above, in this embodiment of the invention, by establishing a microscopic interface equivalent stiffness and multi-frequency ultrasonic response model, the frequency and interface damage sensitivity distribution are determined with the interface damage variable sensitivity as the optimization objective. Accordingly, the frequency band most sensitive to interface damage is selected and a multi-frequency combination is generated, providing a clear physical basis for frequency selection and effectively improving the detection sensitivity for early damage such as microcracks and interface weakening in the resin matrix. On this basis, echo signals of each frequency band are acquired through macroscopic multi-frequency ultrasonic detection, multi-frequency ultrasonic features are extracted and input into the pre-established interface equivalent stiffness and multi-frequency response mapping model, and an inversion algorithm is used to determine the interface damage variable distribution in each detection area. This generates the spatial distribution and damage level of the resin matrix interface damage, achieving cross-scale quantitative characterization from microscopic interface equivalent stiffness parameters to macroscopic structural coordinates. This enables early warning before macroscopic delamination occurs, providing reliable data support for the safety assessment and life prediction of composite material structures.

[0062] The ultrasonic cross-scale detection method for the interface of composite resin matrix in embodiments of the present invention determines the equivalent stiffness of the interface region and introduces the interface damage variable, including: defining the fiber-resin interface as a bonding zone unit with normal stiffness and tangential stiffness, determining the interface equivalent normal stiffness and tangential stiffness; determining the interface equivalent normal stiffness and tangential stiffness under healthy conditions, wherein the interface normal stiffness and tangential stiffness decrease proportionally with the increase of the interface damage variable.

[0063] Further, the frequency and interface damage sensitivity distribution is determined, including: determining the sensitivity index of each candidate frequency to the interface damage variable based on the rate of change of the amplitude of the reflection coefficient corresponding to each candidate frequency under different interface damage variables; determining the frequency and interface damage sensitivity curve based on the sensitivity index; and determining the frequency points with a sensitivity higher than the average sensitivity of the whole frequency band as interface sensitive frequencies based on a preset multiple threshold.

[0064] Furthermore, the multi-frequency combination is a multi-frequency ultrasound detection scheme generated by combining multiple interface-sensitive frequencies. The multi-frequency combination includes a low-frequency band that is sensitive to deep interface damage and a high-frequency band that is sensitive to superficial interface damage.

[0065] Furthermore, based on multi-frequency combination, macroscopic multi-frequency ultrasonic testing is performed on the surface of the composite material structure to be tested to determine the echo signal of each frequency band, including: based on the ultrasonic transducer or phased array probe arranged on the surface of the composite material structure to be tested, ultrasonic waves are excited sequentially according to the multi-frequency combination; the echo signal at each excitation frequency is determined, and the echo signal is spatially partitioned and numbered based on the detection area.

[0066] Furthermore, after determining the echo signals in each frequency band, the process also includes:

[0067] The determined multi-frequency ultrasound signal is preprocessed, including noise reduction, time window truncation, normalization, and frequency division filtering.

[0068] Furthermore, the mapping model between the interface equivalent stiffness and the multi-frequency response is determined, including: determining the multi-frequency ultrasonic response under different interface damage variables based on the representative volume element model and the specimen; determining the dataset based on the interface damage variables and the multi-frequency ultrasonic feature quantities; and determining the mapping relationship from the multi-frequency ultrasonic feature quantities to the interface damage variables based on multiple regression or machine learning methods to generate a surrogate model characterizing the interface equivalent stiffness and interface damage.

[0069] Furthermore, the distribution of interface damage variables in each detection area is determined based on the inversion algorithm, including: based on multi-frequency ultrasonic features and mapping models, using least squares inversion, Bayesian inversion or machine learning-based surrogate model regression methods, to determine the interface equivalent stiffness parameters and interface damage variables corresponding to each detection area in the macrostructure.

[0070] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods according to the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) and includes several instructions to cause a terminal device (which may be a mobile phone, computer, server, or network device, etc.) to execute the methods of the various embodiments of the present invention.

[0071] This invention also provides an ultrasonic cross-scale testing device for the interface of a composite resin matrix, which is used to implement the above embodiments and preferred embodiments, and will not be repeated as already described. As used below, the term "module" can refer to a combination of software and / or hardware that performs a predetermined function. Although the device described in the following embodiments is preferably implemented in software, hardware implementation, or a combination of software and hardware, is also possible and contemplated.

[0072] Another method for ultrasonic cross-scale testing of composite resin matrix interfaces according to one embodiment of the present invention, such as... Figure 2 As shown, the method includes the following steps:

[0073] Step S201: Acquisition of composite material structure information and preparation for modeling.

[0074] Acquire the laminated ply information, material parameters, and geometric information of the composite material structure to be tested, including fiber type, resin type, fiber volume fraction, ply angle, layer thickness, and structural dimensions. Select representative fiber / resin microstructure regions to construct a representative microstructure element (RVE) model, which includes the fiber phase, resin matrix phase, and the interface region between them.

[0075] Step S202: Model the equivalent stiffness of the interface.

[0076] The fiber / resin interface is equivalent to an interface element with normal and tangential stiffness. The bonding zone model is used to represent the interface mechanical behavior, and the equivalent normal stiffness K of the interface is defined. n and tangential stiffness K t The equivalent interface stiffness parameter K under the initial healthy state is determined through experimental data, literature data, or numerical back-calculation. n0 K t0 And set the interface damage variable D, and represent the interface degradation process as K. n =(1−D)K n0 K t =(1−D)K t0 .

[0077] Step S203: Simulation and sensitivity analysis of microscopic multi-frequency ultrasonic propagation.

[0078] An incident ultrasonic boundary condition is applied to the RVE model, wherein the incident wave includes a predetermined frequency range f. min to f max Multiple sets of longitudinal waves, transverse waves, or guided waves of different frequencies are generated within the device. Using the time-domain finite element method or the frequency-domain finite element method, the reflected, transmitted, and scattered wave responses under different interface damage variables D and different frequency ultrasonic incident conditions are calculated. Corresponding ultrasonic characteristic quantities are extracted, including but not limited to reflection coefficient, transmission coefficient, phase difference, spectral energy distribution, and waveform distortion index. For each candidate frequency f... i The sensitivity index to the interface damage variable D was calculated, and the frequency-interface damage sensitivity curve was obtained by using the characteristic quantity change rate information.

[0079] Step S204: Selection of interface-sensitive frequency bands and optimization of multi-frequency combinations.

[0080] Based on the frequency-interface damage sensitivity curve, several interface-sensitive frequency bands with sensitivity to the interface damage variable D exceeding a preset threshold are selected. These interface-sensitive frequency bands are then combined and optimized to obtain a multi-frequency combination for actual structural testing. This multi-frequency combination includes at least one interface-sensitive low-frequency band and at least one interface-sensitive high-frequency band. A mapping relationship is established between the interface equivalent stiffness parameter, the interface damage variable, and the corresponding multi-frequency ultrasonic characteristics, serving as a priori model for subsequent inversion.

[0081] Step S205: Macroscopic structure multi-frequency ultrasonic testing.

[0082] An ultrasonic transducer or phased array probe is placed on the macroscopic structure of the composite material to be tested, and ultrasonic waves are excited sequentially or simultaneously according to the multi-frequency combination selected in step S4. Echo signals at each excitation frequency are collected, and the ultrasonic signals are spatially partitioned and numbered according to the detection area. The collected multi-frequency ultrasonic signals are preprocessed, including noise reduction, time window truncation, normalization, and frequency division filtering.

[0083] Step S206: Multi-frequency ultrasound feature extraction and cross-scale inversion.

[0084] For the preprocessed multi-frequency ultrasonic signals, the feature quantities corresponding to step S3 are extracted, including reflection coefficient, transmission coefficient, time delay, spectral energy, and center frequency drift. The extracted multi-frequency ultrasonic features are input into a pre-established interface equivalent stiffness-multi-frequency ultrasonic mapping model. Least squares inversion, Bayesian inversion, or machine learning regression methods are used to obtain the interface equivalent stiffness parameters and interface damage variables corresponding to each detection region in the macrostructure. Based on the magnitude of the interface damage variables, the interface damage is divided into multiple levels and correlated with the macrostructure coordinates to form a cross-scale distribution map of composite resin matrix / interface damage.

[0085] Step S207, Evaluation and Result Output of Resin Matrix / Interface Damage

[0086] Based on the cross-scale distribution map of interface damage, and in conjunction with structural design criteria and safety assessment standards, the damage status of the resin matrix / interface in each region is quantitatively evaluated. The output includes information such as the location of the damaged area and the level of interface damage.

[0087] Figure 3 According to one embodiment of the present invention, an ultrasonic cross-scale testing device for the interface of a composite resin matrix includes:

[0088] The response module 301 is used to respond to the micro-modeling command, determine the representative volume element model based on the microstructure of the fiber-reinforced resin matrix composite material, determine the equivalent stiffness of the fiber-resin interface region in the model and introduce the interface damage variable, determine the frequency and interface damage sensitivity distribution based on the micro-simulation results of applying ultrasonic incident signals of multiple frequency bands to the model, determine the sensitive frequency band based on the sensitivity distribution and generate a multi-frequency combination.

[0089] The determination module 302 is used to perform macroscopic multi-frequency ultrasonic testing on the surface of the composite material structure to be tested based on multi-frequency combination, and to determine the echo signal of each frequency band.

[0090] The generation module 303 is used to determine the multi-frequency ultrasonic features based on the echo signal, input the multi-frequency ultrasonic features into the interface equivalent stiffness and multi-frequency response mapping model, determine the distribution of interface damage variables in each detection area based on the inversion algorithm, and generate the spatial distribution and damage level of the resin matrix interface damage.

[0091] It should be noted that the above modules can be implemented by software or hardware. For the latter, they can be implemented in the following ways, but are not limited to: all the above modules are located in the same processor; or, the above modules are located in different processors in any combination.

[0092] According to one embodiment of the present invention, an electronic device is also provided, comprising: a memory storing an executable program; and a processor for running the program, wherein the program executes the above-described ultrasonic cross-scale detection method for the interface of a composite resin matrix.

[0093] Optionally, in this embodiment, the processor can be configured to perform the following steps via a computer program:

[0094] Step S1: In response to the micro-modeling instruction, a representative volumetric unit model is determined based on the microstructure of the fiber-reinforced resin matrix composite material. The equivalent stiffness of the fiber-resin interface region in the model is determined and the interface damage variable is introduced. Based on the micro-simulation results of applying ultrasonic incident signals of multiple frequency bands to the model, the frequency and interface damage sensitivity distribution are determined. Based on the sensitivity distribution, the sensitive frequency band is determined and a multi-frequency combination is generated.

[0095] Step S2: Perform macroscopic multi-frequency ultrasonic testing on the surface of the composite material structure to be tested based on multi-frequency combination to determine the echo signal of each frequency band;

[0096] Step S3: Determine the multi-frequency ultrasonic features based on the echo signal, input the multi-frequency ultrasonic features into the interface equivalent stiffness and multi-frequency response mapping model, determine the distribution of interface damage variables in each detection area based on the inversion algorithm, and generate the spatial distribution and damage level of the resin matrix interface damage.

[0097] According to one embodiment of the present invention, a computer-readable storage medium is also provided, the computer-readable storage medium including a stored executable program, wherein, when the executable program is running, it controls the device where the storage medium is located to perform the above-described ultrasonic cross-scale detection method for the interface of composite resin matrix.

[0098] Optionally, in this embodiment, the storage medium may be configured to store a computer program for performing the following steps:

[0099] Step S1: In response to the micro-modeling instruction, a representative volumetric unit model is determined based on the microstructure of the fiber-reinforced resin matrix composite material. The equivalent stiffness of the fiber-resin interface region in the model is determined and the interface damage variable is introduced. Based on the micro-simulation results of applying ultrasonic incident signals of multiple frequency bands to the model, the frequency and interface damage sensitivity distribution are determined. Based on the sensitivity distribution, the sensitive frequency band is determined and a multi-frequency combination is generated.

[0100] Step S2: Perform macroscopic multi-frequency ultrasonic testing on the surface of the composite material structure to be tested based on multi-frequency combination to determine the echo signal of each frequency band;

[0101] Step S3: Determine the multi-frequency ultrasonic features based on the echo signal, input the multi-frequency ultrasonic features into the interface equivalent stiffness and multi-frequency response mapping model, determine the distribution of interface damage variables in each detection area based on the inversion algorithm, and generate the spatial distribution and damage level of the resin matrix interface damage.

[0102] Optionally, in this embodiment, the storage medium may include, but is not limited to, various media capable of storing computer programs, such as USB flash drives, read-only memory (ROM), random access memory (RAM), portable hard drives, magnetic disks, or optical disks.

[0103] According to one embodiment of the present invention, a computer program product is also provided, including a computer program that, when executed by a processor, implements the above-described ultrasonic cross-scale detection method for the interface of a composite resin matrix.

[0104] Optionally, in this embodiment, the above-mentioned computer program product can be configured as a computer program that performs the following steps:

[0105] Step S1: In response to the micro-modeling instruction, a representative volumetric unit model is determined based on the microstructure of the fiber-reinforced resin matrix composite material. The equivalent stiffness of the fiber-resin interface region in the model is determined and the interface damage variable is introduced. Based on the micro-simulation results of applying ultrasonic incident signals of multiple frequency bands to the model, the frequency and interface damage sensitivity distribution are determined. Based on the sensitivity distribution, the sensitive frequency band is determined and a multi-frequency combination is generated.

[0106] Step S2: Perform macroscopic multi-frequency ultrasonic testing on the surface of the composite material structure to be tested based on multi-frequency combination to determine the echo signal of each frequency band;

[0107] Step S3: Determine the multi-frequency ultrasonic features based on the echo signal, input the multi-frequency ultrasonic features into the interface equivalent stiffness and multi-frequency response mapping model, determine the distribution of interface damage variables in each detection area based on the inversion algorithm, and generate the spatial distribution and damage level of the resin matrix interface damage.

[0108] Optionally, specific examples in this embodiment can refer to the examples described in the above embodiments and optional implementations, and will not be repeated here.

[0109] In the above embodiments of the present invention, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0110] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. The device embodiments described above are merely illustrative; for example, the division of units can be a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the displayed or discussed mutual couplings, direct couplings, or communication connections may be through some interfaces; indirect couplings or communication connections between units or modules may be electrical or other forms.

[0111] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0112] Furthermore, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0113] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, read-only memory (ROM), random access memory (RAM), portable hard drives, magnetic disks, or optical disks.

[0114] The above are merely preferred embodiments of the present invention. It should be noted that those skilled in the art can make various improvements and modifications without departing from the principle of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. A method for ultrasonic cross-scale testing of the interface of a composite resin matrix, characterized in that, include: In response to the micro-modeling command, a representative volumetric unit model is determined based on the microstructure of the fiber-reinforced resin matrix composite material. The equivalent stiffness of the fiber-resin interface region in the model is determined and an interface damage variable is introduced. Based on the micro-simulation results of applying ultrasonic incident signals of multiple frequency bands to the model, the frequency and interface damage sensitivity distribution are determined. Based on the sensitivity distribution, the sensitive frequency band is determined and a multi-frequency combination is generated. Based on the multi-frequency combination, macroscopic multi-frequency ultrasonic testing is performed on the surface of the composite material structure to be tested to determine the echo signal of each frequency band. Based on the echo signal, multi-frequency ultrasonic features are determined. These features are then input into the interface equivalent stiffness and multi-frequency response mapping model. Based on the inversion algorithm, the distribution of interface damage variables in each detection area is determined, generating the spatial distribution and damage level of the resin matrix interface damage.

2. The method according to claim 1, characterized in that, Determining the equivalent stiffness of the interface region and introducing the interface damage variable includes: The fiber-resin interface is defined as a bonding zone unit with normal stiffness and tangential stiffness, and the equivalent normal stiffness and tangential stiffness of the interface are determined. The equivalent normal stiffness and tangential stiffness of the interface under healthy conditions are determined, wherein the interface normal stiffness and the tangential stiffness decrease proportionally as the interface damage variable increases.

3. The method according to claim 1, characterized in that, Determining the frequency and interface damage sensitivity distribution includes: Based on the rate of change of the amplitude of the reflection coefficient corresponding to each candidate frequency under different interface damage variables, the sensitivity index of each candidate frequency to the interface damage variables is determined. Based on the aforementioned sensitivity index, determine the frequency versus interface damage sensitivity curve; Based on a preset multiple threshold, frequency points whose sensitivity is higher than the average sensitivity of the entire frequency band by the preset multiple are determined as interface sensitive frequencies.

4. The method according to claim 3, characterized in that, The multi-frequency combination is a multi-frequency ultrasound detection scheme generated by combining multiple interface-sensitive frequencies. The multi-frequency combination includes a low-frequency band that is sensitive to deep interface damage and a high-frequency band that is sensitive to superficial interface damage.

5. The method according to claim 1, characterized in that, Macroscopic multi-frequency ultrasonic testing is performed on the surface of the composite material structure to be tested based on the aforementioned multi-frequency combination to determine the echo signals of each frequency band, including: Based on ultrasonic transducers or phased array probes arranged on the surface of the composite material structure to be tested, ultrasonic waves are sequentially excited according to the multi-frequency combination. The echo signals at each excitation frequency are determined, and the echo signals are spatially partitioned and numbered based on the detection area.

6. The method according to claim 5, characterized in that, After determining the echo signals for each frequency band, the following is also included: The determined multi-frequency ultrasound signal is preprocessed, including noise reduction, time window truncation, normalization, and frequency division filtering.

7. The method according to claim 1, characterized in that, Determining the interface equivalent stiffness and multi-frequency response mapping model includes: Based on the representative volume element model and the sample, the multi-frequency ultrasonic response under different interface damage variables was determined. The dataset is determined based on the interface damage variables and multi-frequency ultrasound features. The mapping relationship between the multi-frequency ultrasonic feature quantities and the interface damage variables is determined by fitting multiple regression or machine learning methods, and a surrogate model characterizing the interface equivalent stiffness and interface damage is generated.

8. The method according to claim 7, characterized in that, The distribution of interface damage variables in each detection area is determined based on the inversion algorithm, including: Based on the multi-frequency ultrasonic features and the mapping model, the equivalent stiffness parameters and interface damage variables of each detection area in the macrostructure are determined by using least squares inversion, Bayesian inversion, or surrogate model regression methods based on machine learning.

9. An ultrasonic multi-scale testing device for the interface of a composite resin matrix, characterized in that, include: The response module is used to respond to micro-modeling instructions, determine a representative volume element model based on the microstructure of fiber-reinforced resin matrix composites, determine the equivalent stiffness of the fiber-resin interface region in the model and introduce interface damage variables, determine the frequency and interface damage sensitivity distribution based on the micro-simulation results of applying ultrasonic incident signals of multiple frequency bands to the model, determine the sensitive frequency bands based on the sensitivity distribution and generate multi-frequency combinations. The determination module is used to perform macroscopic multi-frequency ultrasonic testing on the surface of the composite material structure to be tested based on the multi-frequency combination, and to determine the echo signal of each frequency band. The generation module is used to determine the multi-frequency ultrasonic features based on the echo signal, input the multi-frequency ultrasonic features into the interface equivalent stiffness and multi-frequency response mapping model, determine the distribution of interface damage variables in each detection area based on the inversion algorithm, and generate the spatial distribution and damage level of the resin matrix interface damage.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium includes a stored executable program, wherein, when the executable program is executed, it controls the device on which the storage medium is located to perform the ultrasonic cross-scale testing method for the interface of a composite resin matrix according to any one of claims 1 to 8.

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