Method for evaluating wet mechanical properties of carbon fiber composite material based on ultrasonic phase demodulation

Abstract

The invention provides a method for evaluating wet mechanical properties of a carbon fiber composite material based on ultrasonic phase demodulation, and relates to the technical field of nondestructive testing of carbon fiber composites.The method comprises the steps that S1, a time-space domain receiving signal of the carbon fiber composite material is obtained; s2, performing narrowband extraction and windowing processing on the time-space domain receiving signal of the carbon fiber composite material; s3, carrying out phase spectrum calculation and phase unwrapping processing on the time-space domain narrow-band signal of the carbon fiber composite material; s4, obtaining the ultrasonic guided wave number of the carbon fiber composite material; and S5, the elastic modulus change rate of the carbon fiber composite material is obtained, mechanical property detection of the material is completed, and early warning replacement is conducted. According to the method, ultrasonic frequency dispersion characteristic parameters which are extremely sensitive to microscopic performance changes of the carbon fiber composite material are extracted through a phase demodulation method, wave number parameters representing characteristics of the carbon fiber composite material are accurately extracted through a narrow-band extraction and frequency domain windowing dual filtering mechanism, a relation model of the elastic modulus and the wave number of the material is constructed, and the wave number of the carbon fiber composite material is calculated. The material mechanical property detection is realized.

Description

Technical Field

[0001] This invention relates to the field of nondestructive testing technology for carbon fiber composite materials, specifically to a method for evaluating the wet mechanical properties of carbon fiber composite materials based on ultrasonic phase demodulation. Background Technology

[0002] Carbon fiber reinforced polymer (CFRP) composites, due to their excellent specific strength, specific modulus, and designability, serve as core structural materials in aerospace, new energy transportation, and other fields. Their service reliability is crucial to the safety and lifespan of overall equipment. With the increasing complexity of composite material application environments, the degradation of mechanical properties caused by moisture absorption aging in humid and hot environments is becoming increasingly serious. Even trace amounts of moisture penetration can lead to plasticization of the resin matrix and debonding at the fiber-matrix interface, resulting in a significant decrease in material stiffness and strength, posing potential safety hazards. Therefore, evaluating the mechanical properties of carbon fiber composites after moisture absorption aging is of paramount importance.

[0003] Existing performance evaluation methods are mainly divided into two categories: destructive testing and non-destructive testing, both of which have certain technical limitations. First, destructive mechanical tests, such as tensile and bending tests, require the preparation of standard specimens and destructive testing, which has drawbacks such as high cost, long cycle, and inability to repeatedly track the performance evolution of the same specimen, making it difficult to meet the long-term monitoring needs of in-service structures. Second, traditional ultrasonic non-destructive testing methods usually rely on bulk wave parameters such as sound velocity and attenuation for performance characterization. However, these parameters are extremely insensitive to the microstructural changes caused by moisture absorption aging of carbon fiber composites, and have obvious technical limitations: sound velocity and attenuation parameters have very limited response to matrix microplasticization and interface weakening, making it difficult to effectively identify early performance degradation of materials; the anisotropy of materials and the multiple scattering effect of the fiber-matrix interface lead to a decrease in the signal-to-noise ratio of ultrasonic signals, and effective mechanical information is drowned out by noise.

[0004] To overcome the aforementioned technical bottlenecks, this invention innovatively proposes a method for evaluating the wet mechanical properties of carbon fiber composites based on ultrasonic phase demodulation. This method generates broadband ultrasonic guided waves by applying high-energy pulse excitation to the material surface and acquires the signals using a fixed-gap dual piezoelectric ceramic sensor. Combining a dual filtering mechanism of narrowband extraction and frequency domain windowing, it effectively separates the low-frequency symmetric mode S0, which is sensitive to in-plane stiffness, and the low-frequency antisymmetric mode A0, which is sensitive to density, thereby suppressing multi-mode wave interference. Furthermore, by constructing a phase dewinding algorithm, the phase difference between the two signals within a specific frequency band is calculated and converted into parameters characterizing the material state—the wavenumbers of the low-frequency symmetric mode S0 and the low-frequency antisymmetric mode A0. The above processing is applied to data collected from the start of moisture absorption until moisture saturation, thereby obtaining a complete wavenumber evolution sequence. This method effectively overcomes the limitation of the slow response of bulk wave parameters to changes in microstructure. By simultaneously tracking the evolution trend of wavenumbers of the low-frequency symmetric mode S0 and the low-frequency antisymmetric mode A0, and proposing the elastic modulus change rate parameter, it accurately characterizes the performance degradation of materials, thereby improving the reliability of performance evaluation. Summary of the Invention

[0005] To address the shortcomings of the existing technology, the present invention aims to provide a method for evaluating the wet mechanical properties of carbon fiber composites based on ultrasonic phase demodulation. This method extracts ultrasonic dispersion characteristic parameters that are highly sensitive to changes in the microstructure of carbon fiber composites through phase demodulation. By employing a dual filtering mechanism of narrowband extraction and frequency domain windowing, it effectively suppresses strong noise interference caused by material anisotropy and fiber scattering, accurately extracts wavenumber parameters characterizing the properties of carbon fiber composites, enhances the signal-to-noise ratio and analytical reliability, and constructs a model relating the material's elastic modulus to its wavenumber, thereby achieving accurate detection of the material's mechanical properties.

[0006] Specifically, the present invention provides a method for evaluating the wet mechanical properties of carbon fiber composite materials based on ultrasonic phase demodulation, which includes the following steps: S1: Construct an ultrasonic testing platform for the moisture absorption and aging of carbon fiber composite materials, and collect spatiotemporal received signals from the carbon fiber composite materials. ; S2: Narrowband extraction and windowing are performed. Frequency domain filtering technology is used to extract the narrowband component with a fixed center frequency from the broadband ultrasonic guided wave signal, and windowing is applied to obtain the spatiotemporal narrowband signal of carbon fiber composite material. ; S3: Perform phase spectrum calculation and phase dewinding processing on the spatiotemporal narrowband signal of carbon fiber composite materials; extract the phase frequency distribution through frequency domain transformation, and use phase unwinding technology to eliminate the phase winding effect and obtain continuous phase information; S4: Based on the phase information obtained in step S3, analyze the evolution law of the dispersion characteristics of carbon fiber composite materials during the moisture absorption and aging process, and determine the ultrasonic guided wavenumber of carbon fiber composite materials. ; S5: Establish a quantitative relationship model between the elastic modulus and wavenumber evolution of carbon fiber composite materials, and obtain the rate of change of the elastic modulus of carbon fiber composite materials based on multimodal wavenumber evolution: ; in, The elastic modulus of the carbon fiber composite material; Interval time parameter The change in elastic modulus of carbon fiber composite materials; This represents the wavenumber variation of the low-frequency symmetric mode S0. This represents the wavenumber variation of the low-frequency antisymmetric mode A0. The wavenumber of the low-frequency symmetrical mode S0 of the Lamb wave signal; The wavenumber of the low-frequency antisymmetric mode A0 of the Lamb wave signal; Interval time parameter The amount of density change; This represents the density of the carbon fiber composite material. This refers to the interval time parameter; Δ represents the Poisson's ratio of the carbon fiber composite material; Δ is the symbol for the change. A quantitative evaluation system for the wet mechanical properties of carbon fiber composites is constructed based on the rate of change of elastic modulus, and the replacement of carbon fiber composites is achieved through graded early warning.

[0007] Preferably, the quantitative relationship model between the elastic modulus and wavenumber evolution in step S5 is as follows: ; in, The elastic modulus of the carbon fiber composite material; This is the proportionality coefficient between the elastic modulus and the wave number parameter; Angular frequency; This is the elastic modulus proportional correction factor.

[0008] Preferably, the wavenumber of the low-frequency symmetric mode S0 of the Lamb wave signal in step S5 is... The method for obtaining it is as follows: Based on the elastic modulus of carbon fiber composites There is a functional relationship between the wavenumber of the Lamb wave signal and the wavenumber of the low-frequency symmetric mode S0, thus yielding the wavenumber of the low-frequency symmetric mode S0. Specifically: ; in, The wave velocity of the low-frequency symmetrical mode S0 of the Lamb wave signal; The thickness is that of carbon fiber composite material; The wave velocity correction coefficient for the low-frequency symmetric mode S0; This is the wavenumber ratio correction coefficient for the low-frequency symmetric mode S0. These are derivation symbols.

[0009] Preferably, the wavenumber of the low-frequency antisymmetric mode A0 of the Lamb wave signal in step S5 is... The method for obtaining it is as follows: Based on the elastic modulus of carbon fiber composites There is a functional relationship between the wavenumber of the Lamb wave signal and the wavenumber of the low-frequency antisymmetric mode A0. Specifically: ; in, The wave velocity of the low-frequency antisymmetric mode A0 of the Lamb wave signal; The thickness is that of carbon fiber composite material; The wave velocity correction coefficient for the low-frequency antisymmetric mode A0; This is the wavenumber ratio correction factor for the low-frequency antisymmetric mode A0.

[0010] Preferably, the ultrasonic guided wavenumber of the carbon fiber composite material in step S4 is... The method for obtaining it is as follows: According to the theory of ultrasonic guided wave propagation, there is a proportional relationship between wave number and phase difference. For any pair of adjacent sensors, the wave number is obtained by dividing the phase difference between the two sensors by their distance. The ultrasonic guided wave number of carbon fiber composite material is obtained as follows: ; in, The ultrasonic wave number of the carbon fiber composite material; For the first Phase vector of a narrowband signal in the spatiotemporal domain from a single sensor using carbon fiber composite material; Number the sensor measurement points; x is the spacing between adjacent sensors; n For the first The distance between the receiving sensor and the excitation sensor.

[0011] Preferably, step S2 specifically includes: S21: Receive the spatiotemporal domain signal obtained in step S1 Perform a Fourier transform to solve for the corresponding frequency domain received signal. Obtain the frequency band range and generate the time-domain excitation signal. The time-domain excitation signal is then subjected to a Fourier transform to obtain the frequency-domain excitation signal. ; frequency domain excitation signal Compared with the original frequency domain received signal Multiplication is performed to reconstruct the spatiotemporal narrowband signal of carbon fiber composite materials through inverse Fourier transform. ; S22: Constructing a spatiotemporal domain signal receiving system for carbon fiber composites Adding windows to handle triangular window functions The triangular window function is processed using windowing. The spatiotemporal narrowband signal of the carbon fiber composite material obtained in step S21 The spatiotemporal narrowband signal of the carbon fiber composite material after windowing was obtained. .

[0012] Preferably, the frequency domain excitation signal in step S21 The method for obtaining it is as follows: ; ; ; in, This is the minimum value within the frequency band. This represents the maximum value within the frequency band. It is a frequency domain excitation signal; For time-domain excitation signal; The center frequency of the excitation signal; A coefficient used to control the bandwidth range of the filter; The number of cycles of the excitation signal; The duration of the excitation signal; This represents the Fourier transform process; sin is the sine function; cos is the cosine function; This represents the signal transmission time in the frequency domain.

[0013] Preferably, the windowing process in step S22 uses a triangular window function. Specifically: ; ; in, Half the width of the triangular window; The scaling factor for the window function; This represents the number of sampling points corresponding to a complete modulation period of the signal. The center time point of the triangular window; The triangular window function is used for windowing.

[0014] Preferably, step S3 specifically includes: S31: Frequency domain transformation of the spatiotemporal narrowband signal of carbon fiber composite material; the windowed spatiotemporal narrowband signal obtained in step S2 Perform a Fourier transform to solve for the frequency domain signal of the windowed carbon fiber composite material. ; S32: Extracting the phase spectrum of the spatiotemporal narrowband signal of carbon fiber composite material from the complex spectrum; S33: Eliminate spatiotemporal narrowband signal winding processing in carbon fiber composite materials; eliminate The winding effect confines the phase difference to Within the range, the phase vector of the spatiotemporal narrowband signal of the unwound carbon fiber composite material is obtained. ; S34: Obtain the phase spectrum of the spatiotemporal narrowband signal of the carbon fiber composite material at multiple measurement points; repeat the above process for each sensor measurement point to obtain the complete phase-frequency-spatial distribution of the carbon fiber composite material spatiotemporal narrowband signal. .

[0015] Preferably, the phase vector of the spatiotemporal narrowband signal of the unwound carbon fiber composite material in step S33 is... Specifically: ; in, This refers to the phase vector of the spatiotemporal narrowband signal of the unwound carbon fiber composite material. Frequency value The phase vector of the spatiotemporal narrowband signal of the unwound carbon fiber composite material at the location; This is a modulo operation.

[0016] Compared with the prior art, the beneficial effects of the present invention are as follows: (1) The present invention extracts the ultrasonic dispersion characteristic parameter, i.e. wavenumber, which is extremely sensitive to changes in the microscopic properties of carbon fiber composites by using the phase demodulation method. This solves the limitation of traditional bulk wave parameters such as sound velocity and attenuation, which are slow to respond to matrix plasticization and interface weakening, and significantly improves the detection sensitivity of the degradation of the moisture absorption aging properties of carbon fiber composites.

[0017] (2) This invention effectively suppresses strong noise interference caused by material anisotropy and fiber scattering through a dual filtering mechanism of narrowband extraction and frequency domain windowing, accurately extracts wavenumber parameters that characterize the properties of carbon fiber composite materials, enhances the signal-to-noise ratio and analytical reliability of the signal, and overcomes the problem that the effective signal is easily submerged by noise in traditional methods.

[0018] (3) This invention achieves dynamic monitoring and complete characterization of the performance degradation process of carbon fiber composite materials by continuously processing and wavenumber tracking of data throughout the entire cycle from the start of moisture absorption to saturation, avoiding the randomness of single time point detection, making the evaluation results more comprehensive and stable, and applicable to long-term condition monitoring and life prediction in engineering practice. Attached Figure Description

[0019] Figure 1 The flowchart shows a method for evaluating the wet mechanical properties of carbon fiber composites based on ultrasonic phase demodulation. Figure 2 This is a schematic diagram showing the layout of the excitation points and receiving points in the embodiment; Figure 3 The moisture absorption rate curve of the composite material plate in the embodiment is shown. Figure 4 This is a waveform diagram of the time-domain received signal after preprocessing in the embodiment; Figure 5 This is a waveform diagram of the low-frequency symmetrical mode S0 mode signal after windowing in the embodiment; Figure 6 This is a waveform diagram of the low-frequency antisymmetric A0 mode signal after windowing in the embodiment; Figure 7 This is an angle curve diagram after unwinding in the embodiment; Figure 8 The graph shows the wavenumber of the low-frequency symmetrical mode S0 mode signal in the example as a function of the number of days of moisture absorption. Figure 9 This is a graph showing the wavenumber of the low-frequency antisymmetric mode A0 mode signal in the embodiment as a function of the number of days of moisture absorption. Figure 10 This is a graph showing the rate of change of the elastic modulus in the embodiment. Detailed Implementation

[0020] Hereinafter, embodiments of the present invention will be described with reference to the accompanying drawings.

[0021] This invention provides a method for evaluating the hygroscopic aging mechanical properties of carbon fiber composite materials based on ultrasonic phase demodulation. For example... Figure 1 As shown, the process includes the following steps: acquiring the spatiotemporal received signal of carbon fiber composite material; performing narrowband extraction and windowing on the spatiotemporal received signal of carbon fiber composite material; calculating the phase spectrum and dewinding the phase of the spatiotemporal narrowband signal of carbon fiber composite material; acquiring the ultrasonic guided wave number of carbon fiber composite material; acquiring the rate of change of elastic modulus of carbon fiber composite material, and completing the mechanical property testing of the material; Step S1: Construct an ultrasonic testing platform for moisture absorption aging of carbon fiber composite materials, and collect spatiotemporal received signals of carbon fiber composite materials at different moisture absorption time points. .

[0022] An ultrasonic testing platform for moisture absorption aging of carbon fiber composites was constructed. The specific process is as follows: L+1 lead zirconate titanate (PZT) piezoelectric ceramic sheets were adhered to the carbon fiber composite material. One PZT piezoelectric ceramic sheet served as the excitation point, and the remaining L points served as measurement points, where L is a positive integer greater than 1. A pulse generator produced an ultrasonic detection signal and input it to the excitation point. The excitation signal generated guided waves in the carbon fiber composite material, and the response signals were acquired by an oscilloscope through each measurement point. The carbon fiber composite material was placed in a constant temperature and humidity environment for moisture absorption testing. Before the start of the immersion test and at certain intervals after each test, the carbon fiber composite material was removed and its surface moisture wiped off. The mass of the carbon fiber composite material was measured using a 0.1g precision electronic balance, and the change in mass over time was recorded. Simultaneously, based on the response signals acquired by the oscilloscope through each measurement point, the spatiotemporal received signals of the carbon fiber composite material at each time point during the entire moisture absorption process were obtained. This continues until the carbon fiber composite material reaches saturation due to moisture absorption.

[0023] The carbon fiber composite material used in this embodiment has dimensions of 300mm × 160mm × 3mm. One excitation point and eight measurement points are set on the plate surface. All points are distributed along a straight line, with a 2mm spacing between adjacent measurement points. The excitation point is 80mm away from the first measurement point. The specific layout is as follows: Figure 2 As shown. Initial mass of the composite material plate without piezoelectric ceramic sheets. The total mass of the carbon fiber composite material was 271.2g, measured before immersion in water after attaching the piezoelectric ceramic sheet. The total mass of the carbon fiber composite material was 288.7g, and the total mass of the piezoelectric ceramic sheet was 17.5g. An accelerated moisture absorption test was conducted by placing the carbon fiber composite material in water at 25℃. The material was removed on days 1, 2, 3, 4, 7, and 9 after immersion, and the surface moisture was wiped off before its mass was immediately measured. The water absorption rates were calculated for the following days: Day 1: 289.0g, Day 2: 289.4g, Day 3: 290.0g, Day 4: 290.0g, Day 7: 290.0g, and Day 9: 290.0g. The current water absorption rate of the carbon fiber composite material was also calculated. After each weighing, ultrasonic signal measurements were performed on an ultrasonic testing platform for moisture absorption and aging of carbon fiber composite materials to obtain the spatiotemporal received signals of the carbon fiber composite materials. Based on the plate mass data after subtracting the mass of the piezoelectric ceramic sheet, plot the water absorption rate-time curve and the moisture saturation curve, as shown below. Figure 3 As shown, the results indicate that the carbon fiber composite material reaches equilibrium after being soaked at room temperature for 3 days, with a saturated moisture absorption rate of 0.48%.

[0024] Step S2: Receive the spatiotemporal signal of the carbon fiber composite material obtained in step S1. Narrowband extraction and windowing are performed. Frequency domain filtering techniques are used to extract narrowband components with a fixed center frequency from broadband ultrasonic guided wave signals. Windowing is then used to extract signals of specific modes, such as the low-frequency symmetric mode S0 and the low-frequency antisymmetric mode A0, to prevent the signals of different modes from overlapping and interfering with each other in the time domain. This also suppresses spectral leakage and provides preprocessed signals for subsequent high-precision phase analysis.

[0025] Step S21: Extract the spatiotemporal received signal of carbon fiber composite material Narrowband signal; spatiotemporal received signal obtained in step S1 Perform a Fourier transform to solve for the corresponding frequency domain received signal. for: ; in, The signal is received in the original frequency domain; For receiving signals in the spatiotemporal domain of carbon fiber composite materials; The distance between the receiving sensor and the excitation sensor; This refers to the signal transmission time received in the frequency domain. The frequency of the received signal in the frequency domain; The imaginary unit; π is the constant of pi; e is the base of the natural logarithm.

[0026] Obtain the frequency band range and generate the time-domain excitation signal. The time-domain excitation signal is then subjected to a Fourier transform to solve for the corresponding frequency-domain excitation signal. Specifically: ; ; ; in, This is the minimum value within the frequency band. This represents the maximum value within the frequency band. It is a frequency domain excitation signal; For time-domain excitation signal; The center frequency of the excitation signal; A coefficient used to control the bandwidth range of the filter; The number of cycles of the excitation signal; The duration of the excitation signal; This represents the Fourier transform process; sin is the sine function; cos is the cosine function.

[0027] frequency domain excitation signal Compared with the original frequency domain received signal Multiplication is performed to reconstruct the spatiotemporal narrowband signal of carbon fiber composite materials through inverse Fourier transform. for: ; in, This is a narrowband signal in the spatiotemporal domain for carbon fiber composite materials; This is the inverse Fourier transform process.

[0028] The center frequency of the excitation signal in the embodiments of the present invention The coefficient for controlling the bandwidth range of the filter is 200kHz. The excitation signal cycle number is 10. The duration of the excitation signal is 10. The time is 400 microseconds. The waveform of the preprocessed time-domain received signal is as follows: Figure 4 As shown, obvious wave packets were observed. Through comparison with theoretical dispersion curves and waveform analysis, it was confirmed that the first arriving wave packet with a higher frequency and shorter period was the low-frequency symmetric mode S0 mode; the wave packet with a longer period that followed was the low-frequency antisymmetric mode A0 mode.

[0029] Step S22: Constructing a spatiotemporal domain signal receiving system for carbon fiber composite materials Adding windows to handle triangular window functions Specifically: ; ; in, Half the width of the triangular window; This is the window function scaling factor, which is set to 0.8 in this example; This represents the number of sampling points corresponding to a complete modulation period of the signal. The center time point of the triangular window; The triangular window function is used for windowing.

[0030] Using windowing to process the triangular window function The spatiotemporal narrowband signal of the carbon fiber composite material obtained in step S21 Windowing was performed to obtain the windowed spatiotemporal narrowband signal of the carbon fiber composite material. for: ; in, This is the spatiotemporal narrowband signal of carbon fiber composite material after windowing.

[0031] The window function scaling factor in this example Setting it to 0.8 determines the number of sampling points corresponding to a complete modulation period of the signal. The value is 1250. This can be achieved by setting different center time points for the triangular windows. The signal is searched for different modes. In this embodiment, the center time point of the triangular window function is set to 850 to obtain the signal of the low-frequency symmetric mode S0, and the center time point is set to 2550 to obtain the signal of the low-frequency antisymmetric mode A0. The signal waveforms of different modes are as follows: Figure 5 and Figure 6 As shown, the waveforms of the low-frequency symmetric mode S0 and the low-frequency antisymmetric mode A0 extracted using triangular window functions at different center time points are presented respectively. Figure 5 As shown, the low-frequency symmetric mode S0 mode signal has a compact waveform and a high oscillation frequency, and its propagation speed is sensitive to the in-plane stiffness of the material and the fiber-matrix interface state; while Figure 6 The low-frequency antisymmetric mode A0 exhibits typical low-frequency characteristics, and its propagation properties better reflect the density increase caused by water absorption. The comparison of the two figures clearly verifies the ability of this invention to effectively separate multiple modes through time-domain windowing, providing a foundation for subsequent mechanical property inversion using the dispersion characteristics of the low-frequency symmetric mode S0 and the low-frequency antisymmetric mode A0, respectively.

[0032] Step S3: Perform phase spectrum calculation and phase dewinding processing on the spatiotemporal narrowband signal of the carbon fiber composite material. Obtain the windowed spatiotemporal narrowband signal obtained in step S2. The phase frequency distribution is extracted through frequency domain transformation, and phase unwrapping technology is used to eliminate the phase winding effect, thereby obtaining continuous phase information. Multiple measurement points set in step S1 are repeatedly calculated to obtain the phase spectrum of multiple measurement points, providing a high-precision data foundation for wavenumber calculation.

[0033] Step S31: Frequency domain transformation of the spatiotemporal narrowband signal of carbon fiber composite material; the spatiotemporal narrowband signal obtained in step S2 after windowing. Perform a Fourier transform to solve for the frequency domain signal of the windowed carbon fiber composite material. for: ; in, This is the frequency domain signal of the carbon fiber composite material after windowing.

[0034] Step S32: Extract the phase spectrum of the spatiotemporal narrowband signal of the carbon fiber composite material from the complex spectrum, specifically: ; in, The phase spectrum of the spatiotemporal narrowband signal of carbon fiber composite material; It is a two-parameter arctangent function; To take the imaginary part of a complex number; To take the real part of the complex number.

[0035] Step S33: Eliminate spatiotemporal narrowband signal winding processing of carbon fiber composite materials; eliminate The winding effect confines the phase difference to Within the range, the phase vector of the spatiotemporal narrowband signal of the unwound carbon fiber composite material is obtained. for: ; in, This refers to the phase vector of the spatiotemporal narrowband signal of the unwound carbon fiber composite material. Frequency value The phase vector of the spatiotemporal narrowband signal of the carbon fiber composite material after unwinding is used as the reference for the current unwinding. For modulo operation, used to adjust the phase difference to... Within the specified range, ensure the continuity of the unwinding process.

[0036] The angles of the two spatial positions after unwinding are as follows: Figure 7 As shown, the angle signals at the two spatial locations exhibit a clear and continuous trend after unwinding. The unwinding operation effectively eliminates the discontinuities caused by periodic jumps in the original phase data, restoring the true physical laws of the angle. The angle curves all show smooth evolution characteristics after unwinding, providing a reliable data foundation for the subsequent accurate calculation of the key propagation parameter—the wavenumber.

[0037] Step S34: Obtain the phase spectrum of the spatiotemporal narrowband signal of the carbon fiber composite material at multiple measurement points; repeat the above process for each sensor measurement point to obtain the complete phase-frequency-spatial distribution of the spatiotemporal narrowband signal of the carbon fiber composite material. for: ; in, Phase-frequency-spatial distribution of narrowband signals in the spatiotemporal domain for carbon fiber composite materials; Let L be the phase vector of the carbon fiber composite material narrowband signal in the spatiotemporal domain of the Lth sensor; L is the total number of sensor measurement points.

[0038] Step S4: Obtain the ultrasonic guided wave number of the carbon fiber composite material. Based on the phase information obtained in Step S3, the relationship between the ultrasonic guided wave number and the number of days the carbon fiber composite material absorbs moisture is obtained, and the evolution law of the dispersion characteristics of the carbon fiber composite material during the moisture absorption and aging process is analyzed. According to the ultrasonic guided wave propagation theory, there is a certain proportional relationship between the wave number and the phase difference. For any pair of adjacent sensors, the wave number is obtained by dividing the phase difference of the pair of sensors by the distance between them. Based on this principle, the ultrasonic guided wave number of the carbon fiber composite material is obtained as follows: ; in, The ultrasonic wave number of the carbon fiber composite material; The sensor measurement points are numbered, as shown in the example. Pick ; x is the spacing between adjacent sensors; n For the first The distance between the receiving sensor and the excitation sensor.

[0039] In this embodiment, the spacing between adjacent sensors is 2mm, and the wavenumber of different modal signals of the two sets of adjacent sensor data varies with the number of days of moisture absorption as follows: Figure 8 and Figure 9 As shown. Figure 8 As shown, with the increase of moisture absorption days, the wavenumber of the low-frequency symmetric mode S0 exhibits a significant decreasing trend. This phenomenon mainly stems from two key changes occurring within the material during moisture absorption aging: the release of residual stress and the softening of the fiber-matrix interface. Both of these factors contribute to a decrease in the material's equivalent stiffness in the in-plane direction. Since the low-frequency symmetric mode S0 is a symmetric mode dominated by in-plane stretching vibration, it is particularly sensitive to the material's in-plane stiffness. The reduction in in-plane stiffness decreases the resistance to elastic wave propagation, which is manifested in the figure as a decrease in wavenumber. Figure 9 As shown, within the same moisture absorption aging cycle, the wavenumber of the low-frequency antisymmetric mode A0 exhibits a steady upward trend. Its dominant mechanism differs from that of the low-frequency symmetric mode S0: First, after water absorption, the overall density of the material increases significantly due to the penetration of water molecules; second, the plasticizing effect of moisture may also affect the bending stiffness of the matrix itself. The low-frequency antisymmetric mode A0 is an antisymmetric mode dominated by bending vibration, and its wave velocity is strongly influenced by both material density and bending stiffness. The increase in the wavenumber of the low-frequency antisymmetric mode A0 mainly captures the density effect caused by moisture absorption and the change in its resistance to bending deformation, revealing the impact of aging on material properties from another dimension.

[0040] Step S5: Obtain the rate of change of elastic modulus of carbon fiber composite material based on multimodal wavenumber evolution, complete the strength test of carbon fiber composite material under moisture aging, construct a quantitative evaluation system for the wet mechanical properties of carbon fiber composite material, and realize the replacement of carbon fiber composite material through graded early warning.

[0041] According to the dispersion theory of Lamb waves in flat plate structures, the elastic modulus of carbon fiber composite materials is... There is a functional relationship between the wavenumbers of the low-frequency antisymmetric mode A0 and the low-frequency symmetric mode S0, as shown below: ; ; in, The wave velocity of the low-frequency symmetrical mode S0 of the Lamb wave signal; The wave velocity of the low-frequency antisymmetric mode A0 of the Lamb wave signal; The wavenumber of the low-frequency symmetrical mode S0 of the Lamb wave signal; The wavenumber of the low-frequency antisymmetric mode A0 of the Lamb wave signal; The elastic modulus of the carbon fiber composite material; This represents the density of the carbon fiber composite material. Poisson's ratio for carbon fiber composites; Angular frequency; The thickness is that of carbon fiber composite material; The wave velocity correction coefficient for the low-frequency symmetric mode S0; This is the wavenumber ratio correction coefficient for the low-frequency symmetric mode S0. The wave velocity correction coefficient for the low-frequency antisymmetric mode A0; This is the wavenumber ratio correction factor for the low-frequency antisymmetric mode A0.

[0042] Based on dimensional analysis and multimodal coupling theory, a quantitative relationship model between elastic modulus and wavenumber evolution is established, specifically as follows: ; in, The elastic modulus of the carbon fiber composite material; This is the proportionality coefficient between the elastic modulus and the wave number parameter; This is the elastic modulus proportional correction factor.

[0043] Due to the anisotropic properties, complex microstructure, and various uncertainties in the actual testing environment of carbon fiber composites, directly determining the absolute value of the elastic modulus through ultrasonic guided wave measurement presents theoretical and technical difficulties. Therefore, this invention innovatively proposes using the rate of change of the elastic modulus to characterize performance degradation. Advantages include: constant terms in the relative change calculation cancel each other out, eliminating systematic errors; even if the absolute value deviates, the trend still accurately reflects performance degradation; and it does not require precise knowledge of all constitutive parameters of the carbon fiber composite. Based on the proportional relationship of the elastic modulus, taking its logarithm and differentiating it yields the relative rate of change of the elastic modulus: ; in, Interval time parameter The change in elastic modulus; Interval time parameter The amount of density change; This represents the wavenumber variation of the low-frequency symmetric mode S0. This represents the wavenumber variation of the low-frequency antisymmetric mode A0. The interval time parameter is set to 24 hours in this embodiment of the invention.

[0044] The rate of change of elastic modulus in this embodiment is as follows: Figure 10 As shown, the rate of change of the elastic modulus is consistently negative and gradually decreases over time, indicating that the carbon fiber composite material is undergoing a continuous and accelerated deterioration process. A negative rate of change means that the elastic modulus of the carbon fiber composite material is decreasing daily; the decreasing rate of change indicates that the rate of elastic modulus decline is accelerating. This suggests irreversible damage accumulation within the carbon fiber composite material, such as the continuous propagation of microcracks, increased porosity, or continuous disintegration of the internal structure. This trend indicates that the load-bearing capacity and resistance to deformation of the carbon fiber composite material are weakening, and its performance degradation is worsening. Based on this, it is determined that the strength of the moisture-absorbing and aged carbon fiber composite material no longer meets the usage requirements, necessitating replacement to ensure normal use.

[0045] Based on the theories of material damage mechanics and structural reliability, a quantitative evaluation system for maintenance decisions of carbon fiber composite materials is established. According to the correlation between the rate of change of elastic modulus and the residual strength of the material, a graded early warning model is constructed, specifically as follows: ; When the absolute value of the rate of change of elastic modulus reaches a preset critical threshold of 8%, it is determined that the material has lost its safe load-bearing capacity, and the replacement process is automatically triggered.

[0046] Maintenance decision analysis was conducted based on the test data of this embodiment: On the first day of moisture absorption, the absolute value of the change rate of the elastic modulus was less than 3%, within the safe range. At this stage, the material performance slightly degraded, not affecting structural safety. It was recommended to continue normal use, maintain the regular monitoring frequency, and record the performance change trend. On the second day of moisture absorption, the absolute value of the cumulative change rate of the elastic modulus was between 5% and 8%, entering a critical state. At this stage, the material performance had significantly degraded, and the structural safety margin was significantly reduced. Maintenance should be initiated immediately, with local reinforcement and enhanced monitoring. On the third day of moisture absorption, the absolute value of the cumulative change rate of the elastic modulus exceeded 8%, far exceeding the danger threshold, indicating an emergency danger state. At this point, the material's load-bearing capacity was severely insufficient, posing a significant safety hazard. The structural components must be immediately taken out of service and replaced. In this embodiment, the material no longer met the safety requirements from the second day, reaching an emergency state requiring immediate replacement on the third day. This decision ensured that effective measures were taken before the material performance completely failed, guaranteeing structural safety.

[0047] This invention proposes a set of technical means based on modal separation and phase demodulation to solve the problem of sluggish response of traditional bulk wave methods to moisture absorption aging of carbon fiber reinforced polymer (CFRP) composites. The principle is as follows: water absorption changes the elastic parameters of the carbon fiber composite, further changes the propagation speed of ultrasonic waves, and thus changes the phase of ultrasonic waves. The wave number changes of different modes are calculated, and the rate of change of elastic modulus is calculated accordingly. This allows for the inverse estimation of the performance of the carbon fiber composite—the change in elastic modulus—and thus determines whether the carbon fiber composite meets engineering requirements, enabling timely replacement and ensuring engineering safety.

[0048] The beneficial effects of this invention are as follows: This invention proposes a method for evaluating the wet mechanical properties of carbon fiber composites based on ultrasonic phase demodulation. The phase demodulation method extracts the ultrasonic dispersion characteristic parameter, i.e., the wavenumber, which is highly sensitive to changes in the microscopic properties of carbon fiber composites. Through a dual filtering mechanism of narrowband extraction and frequency domain windowing, strong noise interference caused by material anisotropy and fiber scattering is effectively suppressed, accurately extracting the wavenumber parameter characterizing the properties of carbon fiber composites, enhancing the signal-to-noise ratio and analytical reliability, and overcoming the problem of effective signals being easily submerged by noise in traditional methods. By continuously processing and tracking the wavenumber of data throughout the entire cycle from the start of moisture absorption to saturation, dynamic monitoring and complete characterization of the performance degradation process of carbon fiber composites are achieved, avoiding the randomness of single-time-point detection, making the evaluation results more comprehensive and stable, and suitable for long-term state monitoring and life prediction in engineering practice. It solves the limitations of traditional bulk wave parameters such as sound velocity and attenuation, which are slow to respond to matrix plasticization and interface weakening, significantly improving the detection sensitivity of the moisture-absorbing aging performance degradation of carbon fiber composites. Experimental verification and analysis prove that this method can accurately measure the mechanical properties of carbon fiber composites under moisture-absorbing aging.

[0049] The embodiments described above are merely preferred embodiments of the present invention and are not intended to limit the scope of the present invention. Various modifications and improvements made by those skilled in the art to the technical solutions of the present invention without departing from the spirit of the present invention should fall within the protection scope defined by the claims of the present invention.

Claims

1. A method for evaluating the wet mechanical properties of carbon fiber composites based on ultrasonic phase demodulation, characterized by, It comprises: S1: Build an ultrasonic testing platform for hygroaging of carbon fiber composites, and collect spatiotemporal receiving signals of carbon fiber composites ; S2: Narrow-band extraction and windowing processing are performed, frequency domain filtering technology is adopted to extract narrow-band components with a fixed center frequency from the wide frequency ultrasonic guided wave signal, and through windowing processing, the carbon fiber composite material space-time domain narrow-band signal is obtained ; S3: the phase spectrum calculation and phase unwrapping processing of the carbon fiber composite material space-time narrowband signal are carried out; the phase frequency distribution is extracted through the frequency domain transformation, the phase unwrapping effect is eliminated by using the phase unfolding technology, and continuous phase information is obtained; S4: According to the phase information obtained in step S3, the evolution law of the dispersion characteristics of the carbon fiber composite material in the hygroaging process is analyzed, and the ultrasonic guided wave wavenumber of the carbon fiber composite material is determined ; S5: a quantitative relationship model of the elastic modulus and the wave number evolution of the carbon fiber composite material is established, and the elastic modulus change rate of the carbon fiber composite material is obtained according to the multi-mode wave number evolution: ； wherein, is the elastic modulus of the carbon fiber composite material; is the interval time parameter is the change in the elastic modulus of the carbon fiber composite material; is the change in the wave number of the low-frequency symmetric mode S0 mode; is the change in the wave number of the low-frequency anti-symmetric mode A0 mode; is the wave number of the low-frequency symmetric mode S0 mode of the Lamb wave signal; is the wave number of the low-frequency anti-symmetric mode A0 mode of the Lamb wave signal; is the interval time parameter is the change in the density; is the density of the carbon fiber composite material; is the interval time parameter; is the Poisson's ratio of the carbon fiber composite material; Delta is the change amount symbol; According to the elastic modulus change rate, a quantitative evaluation system of the wet mechanical properties of the carbon fiber composite material is constructed, and the replacement of the carbon fiber composite material is realized through grading early warning.

2. The method for evaluating the wet mechanical properties of carbon fiber composites based on ultrasonic phase demodulation according to claim 1, characterized in that: The quantitative relationship model of the elastic modulus and the wave number evolution in step S5 is specifically: ； wherein, E is the elastic modulus of the carbon fiber composite material; is a proportionality coefficient between the elastic modulus and the wave number parameter; is an angular frequency; is an elastic modulus proportionality correction coefficient.

3. The ultrasonic phase demodulation-based wet mechanical property evaluation method for carbon fiber composites according to claim 2, characterized in that: The wave number of the Lamb wave signal low-frequency symmetric mode S0 mode in step S5 The acquisition method is as follows: According to the elastic modulus of the carbon fiber composite material There is a functional relationship between the wave number of the low-frequency symmetric mode S0 mode and the wave number of the Lamb wave signal low-frequency symmetric mode S0 mode , specifically: ； wherein, is the wave speed of the low frequency symmetric mode S0 mode of the Lamb wave signal; is the thickness of the carbon fiber composite material; is the wave speed correction coefficient of the low frequency symmetric mode S0 mode; is the wave number proportion correction coefficient of the low frequency symmetric mode S0 mode; is the derivation symbol.

4. The ultrasonic phase demodulation-based wet mechanical property evaluation method for carbon fiber composites according to claim 2, characterized in that: the wave number of the low-frequency anti-symmetry mode A0 mode of the Lamb wave signal in step S5 The acquisition method is as follows: According to the elastic modulus of the carbon fiber composite material There is a functional relationship between the wave number of the low-frequency anti-symmetry mode A0 mode and the wave number of the low-frequency anti-symmetry mode A0 mode of the Lamb wave signal Specifically: ； wherein, is the wave speed of the low frequency anti-symmetric mode A0 mode of the Lamb wave signal; is the thickness of the carbon fiber composite material; is the wave speed correction coefficient of the low frequency anti-symmetric mode A0 mode; is the wave number proportion correction coefficient of the low frequency anti-symmetric mode A0 mode.

5. The ultrasonic phase demodulation-based wet mechanical property evaluation method for carbon fiber composites according to claim 1, characterized in that: The ultrasonic guided wave wave number of the carbon fiber composite material in step S4 The acquisition method is: According to the ultrasonic guided wave propagation theory, there is a proportional relationship between the wave number and the phase difference, for any pair of adjacent sensors, the wave number is obtained by dividing the phase difference of the pair of sensors by the interval; the ultrasonic guided wave wave number of the carbon fiber composite material is: ； wherein, is the ultrasonic guided wave wavenumber for the carbon fiber composite material; is the carbon fiber composite material spatial domain narrowband signal phase vector for the th sensor; is the sensor measurement point number; is the adjacent sensor spacing;x n is the distance between the th receiving sensor and the excitation sensor.

6. The ultrasonic phase demodulation-based wet mechanical property evaluation method for carbon fiber composites according to claim 1, characterized in that: Step S2 is specifically: S21: Fourier transform is performed on the space-time domain receiving signal obtained in step S1 to obtain a corresponding frequency domain receiving signal S22: A frequency band range is obtained, and a time domain excitation signal is generated S23: Fourier transform is performed on the time domain excitation signal to obtain a frequency domain excitation signal S24: The frequency domain excitation signal is multiplied by the original frequency domain receiving signal to reconstruct a carbon fiber composite material space-time domain narrowband signal through inverse Fourier transform​​​ S22: constructing a carbon fiber composite material space-time domain receiving signal window processing a triangular window function , adopting window processing a triangular window function to the carbon fiber composite material space-time domain narrowband signal obtained in step S21 , obtaining a carbon fiber composite material space-time domain narrowband signal after window processing .

7. The ultrasonic phase demodulation-based wet mechanical property evaluation method for carbon fiber composites according to claim 6, characterized in that: The frequency domain excitation signal in step S21 The acquisition method is as follows: ； ； ； wherein is a minimum value of the frequency band range; is a maximum value of the frequency band range; is a frequency domain excitation signal; is a time domain excitation signal; is a center frequency of the excitation signal; is a coefficient controlling the filter band width range; is a number of periods of the excitation signal; is a duration of the excitation signal; is a Fourier transform process; sin is a sine function; cos is a cosine function; is a frequency domain received signal transfer time.

8. The ultrasonic phase demodulation-based wet mechanical property evaluation method for carbon fiber composites according to claim 6, characterized in that: The windowing processing in step S22 is a triangular window function In particular, ； ； wherein, is the half-width of the triangular window; is the window function scaling factor; is the number of sampling points corresponding to a complete modulation period of the signal; is the center time point of the triangular window; is the windowing process triangular window function.

9. The ultrasonic phase demodulation-based wet mechanical property evaluation method for carbon fiber composites according to claim 1, characterized in that: Step S3 is specifically: S31: Frequency domain transformation of the carbon fiber composite material time-space domain narrowband signal; performing frequency domain transformation on the time-space domain narrowband signal obtained in step S2 after windowing processing performing Fourier transformation to solve the carbon fiber composite material frequency domain signal after windowing processing ; S32: the phase spectrum of the carbon fiber composite material space-time narrowband signal is extracted from the complex frequency spectrum; S33: Eliminate the carbon fiber composite material when the spatial narrowband signal winding processing; eliminate Winding effect, the phase difference is limited to The range, get the unwound carbon fiber composite material space-time narrowband signal phase vector ; S34: Obtain the phase spectrum of the carbon fiber composite material's time-space domain narrowband signal at multiple measurement points; repeat the above process for each sensor measurement point to obtain the complete carbon fiber composite material's time-space domain narrowband signal phase-frequency-space distribution .

10. The method for evaluating the wet mechanical properties of carbon fiber composites based on ultrasonic phase demodulation according to claim 9, characterized in that: The phase vector of the time-space domain narrowband signal of the carbon fiber composite material after unwinding in step S33 Specifically: ； wherein, is the unwound carbon fiber composite material spatio-temporal narrowband signal phase vector at time is the frequency value is the unwound carbon fiber composite material spatio-temporal narrowband signal phase vector at time is a modulo operation.

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