Non-linear guided wave-based carbon fiber prepreg laying layer defect detection method and system

Abstract

The invention discloses a carbon fiber prepreg laying layer defect detection method and system based on nonlinear guided waves, and the method comprises the steps: arranging excitation and receiving sensor arrays at the inner side and the outer side of a carbon fiber prepreg region, transmitting Hanning window modulation sine wave signals through the excitation sensor arrays, arranging an acoustic metamaterial layer on the surface of a detection region, and detecting the defects of the carbon fiber prepreg laying layer through the acoustic metamaterial layer. An excitation sensor array is divided into two groups to emit different phase signals, so that wave beams are focused at specified positions in a detection area and interact with each other, normalized time-frequency analysis is performed on reference signals and to-be-detected signals, second harmonic components and sideband frequency components are extracted, a relative nonlinear coefficient is calculated based on a signal difference value, and the relative nonlinear coefficient is calculated. And processing and receiving full matrix data of the sensor array by adopting a full focusing method, and reconstructing a nonlinear coefficient distribution image in the carbon fiber prepreg to carry out defect positioning and quantitative evaluation on the acoustic metamaterial layer. According to the invention, accurate and reliable detection and early warning of micro-defects in the carbon fiber prepreg laying process are realized.

Description

Technical Field

[0001] This invention belongs to the field of carbon fiber prepreg defect detection technology, and relates to a carbon fiber prepreg layup defect detection method based on nonlinear guided waves, and also relates to a carbon fiber prepreg layup defect detection system based on nonlinear guided waves. Background Technology

[0002] Carbon fiber prepreg is used as a carbon fiber reinforced composite material. F ibre Rein f orcedPolymer, C F Prepregs are critical intermediate materials in prepreg manufacturing, and the quality of their layup process directly determines the performance and reliability of the final component. During the layup stage, improper processing can easily introduce initial defects such as porosity, fiber wrinkles, foreign matter inclusions, and weak interlayer adhesion. If these defects are not detected and addressed in a timely manner, they will become potential failure sources after the component has cured, seriously threatening structural safety.

[0003] Currently, for C after curing F Non-destructive testing techniques for RP components (such as ultrasonic C-scanning and X-ray inspection) are relatively mature, but none are suitable for online, in-situ quality monitoring during the layup process. Current layup process inspections mainly rely on manual visual inspection, which is inefficient and unreliable. Ultrasonic guided wave technology, due to its high detection efficiency and sensitivity to plate-like structures, is considered an ideal means of achieving online monitoring. However, traditional linear ultrasonic guided wave methods (based on changes in parameters such as wave velocity and attenuation) lack sufficient sensitivity to "closed" defects such as microscale initial defects and weak interfacial adhesion in prepregs, making early warning difficult.

[0004] Nonlinear ultrasonic testing technology provides a new approach for the accurate identification of micro-defects by extracting the nonlinear acoustic response (such as higher harmonics and lower harmonics) induced by material damage. Among these methods, the mixed-frequency nonlinear ultrasonic method has received widespread attention in recent years. This method is based on two different frequency ( f c , f s The guided wave undergoes nonlinear interaction at the material defect, generating a sum-frequency (SF) frequency. f c + f s ) and difference frequency ( f c – f sSideband frequency components; compared with the second harmonic generated by single-frequency excitation, the mixing effect has a clear physical meaning and can be effectively separated from the inherent "pseudo-nonlinear" response of the sensor and system, thus exhibiting a higher signal-to-noise ratio and sensitivity for detecting micro-defects. However, in media with high acoustic attenuation and strong anisotropy, such as carbon fiber prepreg, how to effectively excite pure guided wave modes and promote their nonlinear mixing effect at defects, while stably extracting weak sideband components from complex received signals, remains a current technical challenge.

[0005] Acoustic metamaterials, as functional materials with artificially designed periodic structures, can achieve precise control over the propagation of elastic waves, such as forming band gaps at specific frequencies. This characteristic provides a novel technological approach for improving the efficiency of nonlinear ultrasonic testing: if an acoustic metamaterial can be designed whose band gap precisely matches the sideband frequencies generated by nonlinear mixing, then theoretically, an "acoustic resonant cavity" or "acoustic filter" can be constructed in the detection region, thereby selectively enhancing or efficiently transmitting key sideband signals while suppressing interference frequency components, ultimately achieving the multiplication and purification of the mixing nonlinear effect.

[0006] Therefore, there is an urgent need for a novel detection method that integrates mixed-frequency nonlinear ultrasonic guided waves with acoustic metamaterials to overcome the bottlenecks in sensitivity and reliability of micro-defect detection during carbon fiber prepreg layup. This has become a key scientific problem to be solved in this field and also has significant engineering application value. Summary of the Invention

[0007] The technical problem to be solved by the present invention is to provide a method and system for detecting defects in carbon fiber prepreg layup based on nonlinear guided waves, which provides micro-defect detection during the carbon fiber prepreg layup process, with high accuracy and reliability, high sensitivity, and the ability to achieve early warning.

[0008] To address the aforementioned technical problems, the present invention employs the following technical solution: a method for detecting defects in carbon fiber prepreg layup based on nonlinear guided waves, comprising the following steps: Step 1: Sensor Array Arrangement: To ensure strict geometric symmetry between the arrays, excitation sensor arrays and receiving sensor arrays are arranged in parallel linear arrays on both the inner and outer sides of the carbon fiber prepreg area to be detected. This ensures the regularity of full-matrix data acquisition and provides the foundation for beam focusing and phase control of frequency mixing excitation in subsequent steps. Step 2, Excitation Signal Transmission and Pseudo-Nonlinearity Suppression: The excitation center frequency is transmitted through the excitation sensor array. f c The Hanning window modulated sinusoidal signal, where is used to balance the propagation attenuation, dispersion effect, and detection sensitivity of the guided wave in the carbon fiber prepreg. fc The frequency range is 100kHz-500kHz. Simultaneously, to optimize the balance between sufficient nonlinear interaction energy and effective coverage of the metamaterial bandgap, the number of cycles of the Hanning window-modulated sinusoidal signal is 10-30 cycles to enhance the nonlinear excitation effect. An acoustic metamaterial layer is deposited on the surface of the detection region between the excitation sensor array and the receiving sensor array, with the bandwidth designed to cover the excitation center frequency. f c The second harmonic frequency 2 f c The frequency range in which it is located; Step 3, Array Partition Mixing Excitation and Beam Focusing: The excitation sensor array is divided into a first array element and a second array element; the first array element emits a continuous sine wave signal, and the second array element emits a transient sine wave signal modulated by a Hanning window; by controlling the phase of the signals emitted by the first array element and the second array element respectively, the beam is focused and interacts at a specified position in the detection area to enhance the nonlinear mixing effect in the focal region; Step 4, Recursive Layup Inspection and Benchmark Update: After laying the first layer of prepreg on the substrate as the metamaterial matrix, its health status is first verified using X-ray or infrared non-destructive testing methods, and the ultrasonic guided wave signal of this status is collected as the initial benchmark signal. Based on this, during subsequent layup processes, the current signal is collected as the test signal after each new layup is completed, and compared with the benchmark signal of the previous layup to evaluate the quality of the new layup. If the quality is qualified, the current signal is updated as the new benchmark for subsequent inspections. In addition, after establishing the initial benchmark, known artificial simulated damage needs to be introduced into the first layer of prepreg and the subsequent identification process is executed, providing a basis for setting the defect identification threshold. Step 5, Dual-Indicator Defect Identification: Perform normalized time-frequency analysis on the reference signal and the signal under test to extract the second harmonic component and sideband frequency components; calculate the relative change ΔA1 of the second harmonic amplitude of the signal under test relative to the reference signal, and the relative change ΔA2 of the sideband frequency amplitude; based on the thresholds statistically determined on defect-free samples, when both ΔA1 and ΔA2 exceed the threshold, it is determined as a clear defect, and when either indicator exceeds the threshold, it is determined as a suspected defect.

[0009] Furthermore, in step 1 above, the arrangement direction of the excitation sensor array and the receiving sensor array is configured to be consistent with the main fiber direction of the currently detected layup, so as to excite modally pure and damage-sensitive guided waves in the layup; the element spacing of the excitation sensor array and the receiving sensor array is set to one-half to one guided wave wavelength, so as to ensure complete coverage of the detection area while avoiding spatial overlap. Furthermore, in step 3 above, the center frequency of the Hanning window modulated sine wave signal is... fc The frequency of the continuous sinusoidal signal is f s ;in, f s and f c All are within the range of 100kHz to 500kHz, and f s The value is less than f c This configuration allows the two beams to interact at the focal point, producing a significant sum-frequency response. f c +f s With difference frequency f c -f s The sideband signal; preferably, the f c for f s 2 times.

[0010] Furthermore, in step 2 above, the acoustic metamaterial layer is composed of multiple periodically arranged acoustic metamaterial cells; the bandgap center frequency of the acoustic metamaterial cells is designed to cover the excitation center frequency selected in step 3. f c The second harmonic frequency 2 f c .

[0011] Furthermore, the aforementioned acoustic metamaterial cell is a three-layer cylindrical columnar structure, comprising a matrix layer, an intermediate layer, and a top layer stacked sequentially from bottom to top, with the matrix layer serving as the substrate. The length and width of the matrix layer are equal, both being lattice constants, and the thickness of the matrix layer is equal to the thickness of the substrate. The length and width of the intermediate layer and the top layer are equal, and these lengths and widths are smaller than the lattice constants. The matrix layer and the intermediate layer are made of the same metallic material, and the material density of the top layer is greater than that of the matrix layer and the intermediate layer. When designing the material density and geometry of the top layer, the required bandgap is first determined in advance based on the range of second harmonic frequencies to be suppressed, and then the material density and geometry of the top layer are designed accordingly to achieve targeted absorption of specific second harmonic frequencies by the acoustic metamaterial layer.

[0012] Furthermore, the bandgap center frequency and bandwidth of the aforementioned acoustic metamaterial cell are determined by the equivalent mass of the top layer. By replacing the top layer with one of different size or density, the bandgap characteristics of the acoustic metamaterial layer can be adjusted.

[0013] Furthermore, the relationship between the equivalent quality of the top layer and the center frequency and bandwidth of the bandgap is as follows: as the equivalent quality increases, the center frequency of the bandgap decreases and the bandwidth increases; conversely, as the equivalent quality decreases, the center frequency of the bandgap increases and the bandwidth decreases.

[0014] Furthermore, the lattice constant of the aforementioned acoustic metamaterial cell is smaller than the transverse wave wavelength for detecting ultrasonic guided waves.

[0015] A carbon fiber prepreg layup defect detection system based on nonlinear guided waves includes: The area of ​​carbon fiber prepreg to be inspected; An excitation sensor array and a receiving sensor array are arranged in a parallel linear array on the inner and outer sides of the carbon fiber prepreg area to be detected. An acoustic metamaterial layer is disposed around the detection area; A signal generator and amplifier, connected to an excitation sensor array, for generating and amplifying the dual-frequency excitation signal; A data acquisition device, which is connected to a receiving sensor array, is used to acquire signals from the receiving sensor array. Signal processing and localization unit for dual-index defect identification.

[0016] The beneficial effects of the present invention are: the defect detection method of the present invention can provide micro-defect detection and early defect detection warning during the carbon fiber prepreg layup process, with high detection sensitivity and accurate and reliable detection. Attached Figure Description

[0017] Figure 1 This is a schematic diagram of the overall testing method; Figure 2 Phase velocity curve of T7000 carbon fiber prepreg; Figure 3 A diagram of a 30-cycle sinusoidal signal modulated using the Hanning window; Figure 4 The second harmonic waveform is for a 200kHz excitation. Figure 5 This is a schematic diagram of the phononic crystal structure of a metamaterial. Figure 6 This is a band structure diagram of a phononic crystal. Figure 7 The sideband diagram for the 200kHz-50kHz mixer excitation; Figure 8 This is a schematic diagram of a unidirectional recursive ply structure. Figure 9 This is a schematic diagram of an orthogonal recursive layered structure. Detailed Implementation

[0018] Example 1: As Figures 1-9 As shown, the method for detecting defects in carbon fiber prepreg layup based on nonlinear guided waves includes the following steps: Step 1: This step aims to establish a regularized full-matrix data acquisition system. F The MC system is used to determine the waveguide mode most sensitive to defects and the optimal operating frequency based on the dispersion characteristics of the prepreg, such as... Figure 1 As shown in the schematic diagram of the overall detection method, excitation sensor arrays (T) are arranged in a parallel linear array on both the inner and outer sides of the carbon fiber prepreg area to be detected. x (array) and receiver sensor array (R) x The array ensures the regularity of full-matrix data acquisition. This dual-sided, linear array configuration ensures the integrity and regularity of full-matrix data acquisition, providing a data foundation for subsequent high-resolution full-focus defect localization. In this embodiment, the excitation sensor array (T... x (array) and receiver sensor array (R) x The arrays all use an 8-element configuration (N=8), and the element type is piezoelectric ceramic (PZT) to ensure high electromechanical conversion efficiency over a wide bandwidth.

[0019] Carbon fiber prepreg, as a typical transversely isotropic laminated structure, exhibits complex waveguide dispersion characteristics. To ensure waveform stability and detection effectiveness, modes that are sensitive to damage and have low dispersion within the operating frequency band must be selected. For example... Figure 2 C shown F RP T7000 prepreg unidirectional (Φ=0°) phase velocity dispersion curve Figure 2 In this embodiment, the S0 symmetric mode, which has low dispersion in the low-frequency region, is selected as the main working mode. Since the S0 mode is primarily characterized by in-plane stretching, but its group velocity is sensitive to changes in the material's elastic constant in the low-frequency region, it is suitable for detecting early material stiffness degradation and subtle changes in fiber orientation. To excite a modally pure S0 mode, the arrangement of the excitation sensor array and the receiving sensor array is configured to align with the main fiber direction of the currently detected layup, thereby exciting a modally pure, damage-sensitive guided wave in that layup.

[0020] The array orientations of the excitation and receiving sensor arrays are consistent (parallel), but the carbon fiber prepreg layup can be in different orientations. Simply changing the layup orientation of the carbon fiber prepreg allows for the excitation of a guided wave that is more sensitive to damage and has a purer mode (i.e., only one mode exists, and its wave velocity or energy changes significantly or is more sensitive as the size of material damage changes). The element spacing between the excitation and receiving sensor arrays is from one-half to one guided wave wavelength to avoid spatial aliasing and ensure complete coverage of the detection area. The selection of the element spacing d is crucial to avoiding spatial signal aliasing. In this embodiment, the excitation fundamental frequency (in step 2) is selected. f c )frequency f c =200kHz, its guided wave wavelength λ is approximately 10mm. To satisfy the spatial sampling theorem and take into account the convenience of engineering applications, the element spacing d must satisfy: (1), In this embodiment, the element spacing d is set to 5 mm. This is while strictly adhering to T... F For the M-algorithm to require coherent superposition, the element spacing d must be less than the shortest wavelength λ. min half: (2), Precise control of this parameter ensures the accuracy of subsequent phased array focusing defect location and focal sound field reconstruction. Step 2, Excitation Signal Transmission and Pseudo-Nonlinearity Suppression: The excitation center frequency is transmitted through the excitation sensor array. f c The Hanning window modulated sinusoidal signal, where is used to balance the propagation attenuation, dispersion effect, and detection sensitivity of the guided wave in the carbon fiber prepreg. f c The frequency range is 100kHz-500kHz; this embodiment selects 200kHz. To balance the propagation attenuation and dispersion effects of the guided wave in the carbon fiber prepreg with the sensitivity to detect minor damage, the number of cycles of the Hanning window modulated sine wave signal is 10-30 cycles; this embodiment selects 30 cycles to improve the nonlinear excitation effect. An acoustic metamaterial layer is placed on the surface of the detection region between the excitation sensor array and the receiving sensor array. The bandwidth of the acoustic metamaterial layer is designed to cover the excitation center frequency. f c The second harmonic frequency 2 f c The frequency range in which it is located; such as Figure 3 The time-domain waveform and single-amplitude spectrum of a 30-cycle sinusoidal signal modulated by the Hanning window are shown. A high-cycle-number signal can provide sufficient interaction distance x. According to nonlinear theory, the second harmonic amplitude A2 is proportional to the square of the propagation distance x and the fundamental amplitude A1, i.e., A2 ∝ x × A1², thus enhancing the nonlinear effect. f c The fundamental frequency signal of 200kHz interacts with the material defect, generating a second harmonic frequency of 2. f c Nonlinear signals of 400kHz, such as Figure 4 The second harmonic of the 200kHz excitation is shown.

[0021] To address the 400kHz pseudo-nonlinear signal interference caused by factors such as excitation source, instrument system, and sensor coupling, an acoustic metamaterial layer is precisely deposited on the surface of the detection area between the excitation and receiving arrays. This acoustic metamaterial layer employs a locally resonant cellular structure, with the cellular unit being a three-layer cylindrical structure comprising a matrix layer, an intermediate layer, and a top layer stacked sequentially from bottom to top. The matrix layer has equal length and width, both being lattice constants, and its thickness is equal to the substrate thickness. The intermediate and top layers also have equal length and width, which are smaller than their lattice constants. The matrix and intermediate layers are made of the same metallic material, while the top layer has a higher material density than the matrix and intermediate layers. Figure 5 As shown in the acoustic metamaterial crystal structure, the bandgap center frequency and bandwidth of the acoustic metamaterial unit cell are determined by the equivalent mass of the top layer. By replacing the top layer with one of different sizes or densities, the bandgap characteristics of the acoustic metamaterial layer can be adjusted. The relationship between the equivalent mass of the top layer and the bandgap center frequency and bandwidth is as follows: increasing the equivalent mass decreases the bandgap center frequency and increases the bandwidth; conversely, decreasing the equivalent mass increases the bandgap center frequency and decreases the bandwidth. The lattice constant of the acoustic metamaterial unit cell is less than the transverse wave wavelength for detecting ultrasonic guided waves. This structure can be simplified to a spring-mass oscillator model, and its design goal is to maximize the bandgap center frequency. f c With the second harmonic frequency 2 f c Exact match: (3), The band gap center frequency of the metamaterial cell f c Its resonant center frequency can be initially estimated using a simplified spring-mass model. f 0 satisfies: (4), in, The equivalent stiffness of the intermediate layer, This represents the equivalent quality of the top layer. This is achieved by optimizing the height of the top layer (copper). h 2 and diameter d 1. Precisely control its equivalent mass , Make f c = 400kHz. Ultimately, the metamaterial achieves a complete bandgap at 400kHz, as... Figure 6The bandgap diagram of the acoustic crystal shown indicates a bandgap width from 361 kHz to 432 kHz, encompassing a center frequency of 400 kHz. The material parameters used are shown in Table 1: the lattice constant of the unit cell is a = 3 mm, the radii of the intermediate and top layers are 2 mm, the matrix layer height h1 is 1 mm, the intermediate layer height h2 is 2 mm, and the top layer height h3 is 1 mm. The metamaterial utilizes its bandgap effect to physically isolate externally introduced pseudo-nonlinear signals, ensuring that the received second harmonic signal A2 truly originates from internal material defects.

[0022] Table 1 Phononic Crystal Material Parameters <![CDATA[Density (kg / m 3 ).]]> Young's modulus (Pa) Poisson's ratio Substrate layer (steel) 7850 <![CDATA[200e 9 ]]> 0.3 Intermediate layer (steel) 7850 <![CDATA[200e 9 ]]> 0.3 Top layer (copper) 8800 <![CDATA[120e 9 ]]> 0.35 Step 3, Array Partition Mixing Excitation and Beam Focusing: The excitation sensor array is divided into a first array element and a second array element; the first array element emits a continuous sine wave signal, and the second array element emits a transient sine wave signal modulated by a Hanning window; by controlling the phase of the signals emitted by the first array element and the second array element respectively, the beam is focused at a specified position in the detection area and interacts with each other. By utilizing mixing frequency and phased array focusing algorithm, the sound field energy is locally enhanced in the defect area to improve the excitation efficiency of nonlinear signals.

[0023] The N=8 excitation sensor array is divided into a first array element group (elements 1-4) and a second array element group (elements 5-8); the first array element group emits a continuous sine wave signal with a frequency set to [frequency value missing]. f s =50kHz; the second array element transmits a Hanning window modulated transient sine wave signal, with the frequency set to . f c =200kHz.

[0024] Two sets of signals f c and f s Nonlinear interactions occur at the defect, generating a difference frequency signal. f d = | f c - f s | =150kHz sum frequency signal f h = f c + f s =250kHz. For example... Figure 7 The 250-50kHz mixer excitation sideband effect shown has a mixer signal amplitude A. s The sensitivity to damage is generally higher than that of second harmonics generated by single-frequency excitation. The amplitude A of the mixed wave... s(x) is proportional to the propagation distance x and the nonlinear energy flow f suref-s and f vol-s : (5), Among them, energy flow term f suref-s and f vol-s It includes the material's third elastic constant C ijklmn .

[0025] By independently controlling the phase and delay t of the transmitted signal of each array element i,p Using the Delayed Sum (DAS) algorithm, f a and f b The beam is precisely and synchronously focused at a specified focal point P(x,y) within the detection area. The time delay t required for focusing is... i,p Determined by the following formula: (6), Where, d i , P For array element i To focus P The distance, c( f () represents the corresponding frequency f The guided wave phase velocity is lowered. This local focusing can exponentially increase the strain field intensity at the focal point, efficiently exciting nonlinear signals. Simultaneously, to ensure effective accumulation of the mixing signal, the selected mode combination must satisfy the phase matching condition ks = ka + kb to achieve nonlinear resonance. Step 4, Recursive layup detection and benchmark update: After laying the first layer of prepreg on the substrate as the matrix layer of the metamaterial, the substrate signal is used as the initial benchmark. During the laying of unidirectional or orthogonal layup prepreg, the current signal is collected after each layer is laid. This signal is used as the test signal to evaluate the quality of the current layer and updated as the benchmark signal for the next layer detection. A unidirectional recursive strategy is employed to eliminate the interference of accumulated nonlinearity in the structure; such as... Figure 8 As shown in the unidirectional recursive layup, this method utilizes the nonlinear response of the mold substrate signal. β base This serves as the initial reference. During the laying of unidirectional or orthogonal ply prepreg, the nonlinear response signal of the current N-layer structure is collected after each layer (the Nth layer) is laid. β N This signal is used as the test signal to evaluate the quality of the current layer, and is calculated... β N With the previous complete ply structureβ N-1 Nonlinear response difference β S = β N - β N-1 This recursive differential method is used to determine whether there are abnormal defects in the newly added Nth layer. It effectively eliminates the intrinsic nonlinear cumulative effect of the cured layer structure, ensuring that defect detection only applies to the quality status of the currently added layer. If the Nth layer passes the inspection (i.e., ...), the defect is determined to be within the quality state of the newly added layer. β S Within the threshold, the signal of the N-layer structure is... β N Set as the reference signal for the next layer of detection β N-1 .

[0026] Step 5, Dual-Indicator Defect Identification: Perform normalized time-frequency analysis on the reference signal and the signal under test to extract the second harmonic component and sideband frequency components; calculate the relative change ΔA1 of the second harmonic amplitude of the signal under test relative to the reference signal, and the relative change ΔA2 of the sideband frequency amplitude; based on thresholds statistically determined on defect-free samples, when both ΔA1 and ΔA2 exceed the threshold, it is determined as a definite defect; when either indicator exceeds the threshold, it is determined as a suspected defect; the details are as follows: Nonlinear signal processing and dual-index defect identification are employed to perform precise time-frequency analysis on the acquired data. A dual-index criterion is constructed using the second harmonic amplitude variation and the sideband frequency amplitude variation to improve the accuracy and reliability of defect identification. Signals acquired by the sensor array are received and processed by the data acquisition card before entering the signal processing and positioning unit. The processing unit performs normalized time-frequency analysis on the reference signal and the signal under test, and then applies a Fast Fourier Transform (FFT) to the data. FF T) Extract the fundamental amplitude A1 at 200kHz, the second harmonic amplitude A2 at 400kHz, and the mixing sideband amplitude A. s (150kHz and 250kHz).

[0027] This embodiment uses the square of the second harmonic amplitude A2 relative to the fundamental amplitude A1, combined with the propagation distance x, to calculate the relative nonlinear coefficient. β This coefficient is used to quantify the degree of early damage to materials, and its calculation formula is as follows: (7), Where A1 is the fundamental frequency amplitude, A2 is the second harmonic frequency amplitude, and x is the propagation distance. Then, the signal to be measured is calculated. β N Relative to reference signal β N-1 relative change βS . β Value and the third elastic constant C of the material ijklmn It is proportional to and stably characterizes the nonlinear enhancement caused by microscopic defects.

[0028] Calculate the amplitude A of the mixing sideband frequency of the signal under test. s Relative to reference signal A s-base The relative change ΔA. This index utilizes the high sensitivity of the mixing effect to interface defects, providing an independent nonlinear criterion.

[0029] Defect identification is performed based on a statistically determined threshold τ on defect-free samples. When ΔA1 and ΔA2 exceed the statistically determined threshold τ, they are determined to be definite defects.

[0030] When only one indicator exceeds the threshold τ, it is judged as a suspected defect, and further review or testing with increased excitation energy is required.

[0031] Example 2: A carbon fiber prepreg layup defect detection system based on nonlinear guided waves, comprising: The area of ​​carbon fiber prepreg to be inspected; An excitation sensor array and a receiving sensor array are arranged in a parallel linear array on the inner and outer sides of the carbon fiber prepreg area to be detected. An acoustic metamaterial layer is arranged around the detection area, which is a carbon fiber prepreg area that needs to be framed by the acoustic metamaterial. The acoustic metamaterial is placed on the substrate to frame the carbon fiber prepreg. A signal generator and amplifier, connected to an excitation sensor array, for generating and amplifying the dual-frequency excitation signal; A data acquisition device, which is connected to a receiving sensor array, is used to acquire signals from the receiving sensor array. The signal processing and positioning unit is used for dual-index defect identification and judgment.

Claims

1. A method for detecting layup defects in carbon fiber prepreg based on nonlinear guided waves, characterized in that, Includes the following steps: Step 1, Sensor array arrangement: On the inner and outer sides of the carbon fiber prepreg area to be detected, excitation sensor array and receiving sensor array are arranged in a parallel linear array form respectively. Step 2, Excitation Signal Transmission and Pseudo-Nonlinearity Suppression: The excitation center frequency f is transmitted through the excitation sensor array. c The Hanning window modulated sine wave signal, wherein the f c The value range is set to 100kHz to 500kHz; simultaneously, the number of cycles of the Hanning window modulated sine wave signal is set to 10 to 30 cycles; an acoustic metamaterial layer is disposed on the surface of the detection region between the excitation sensor array and the receiving sensor array, and the bandwidth of the acoustic metamaterial layer is designed to cover the excitation center frequency f. c The second harmonic frequency 2f c The frequency range in which it is located; Step 3, Array Partitioning and Dynamic Beam Focusing: The excitation sensor array is dynamically divided into a first array element and a second array element; the transmission frequency of the first array element is... A continuous sinusoidal signal, the transmission frequency of the second array element is The transient sinusoidal signal modulated by the Hanning window; by controlling the phase of the transmitted signals of each element in the first array group and the second array group respectively, the two beams can be synchronously focused and interact at any specified position in the detection area; Step 4, Recursive Layup Inspection and Benchmark Update: After laying the first layer of prepreg on the substrate as the metamaterial matrix, its health status is first verified using X-ray or infrared non-destructive testing methods, and the ultrasonic guided wave signal of this status is collected as the initial benchmark signal. Based on this, during subsequent layup processes, the current signal is collected as the test signal after each new layup is completed, and compared with the benchmark signal of the previous layup to evaluate the quality of the new layup. If the quality is qualified, the current signal is updated as the new benchmark for subsequent inspections. In addition, after establishing the initial benchmark, known artificial simulated damage needs to be introduced into the first layer of prepreg and the subsequent identification process is executed. Step 5, Dual-index Defect Identification: Perform normalized time-frequency analysis on the reference signal and the signal under test to extract the second harmonic component and sideband frequency components; calculate the relative change ΔA1 of the second harmonic amplitude of the signal under test relative to the reference signal, and the relative change ΔA2 of the sideband frequency amplitude. Based on thresholds statistically determined on defect-free samples, a defect is identified when both ΔA1 and ΔA2 exceed the threshold, and a suspected defect is identified when either indicator exceeds the threshold.

2. The method for detecting carbon fiber prepreg layup defects based on nonlinear guided waves according to claim 1, characterized in that, In step 1, the arrangement direction of the excitation sensor array and the receiving sensor array is configured to be consistent with the direction of the main fiber of the currently detected layup, so as to excite modally pure and damage-sensitive guided waves in the layup; the element spacing of the excitation sensor array and the receiving sensor array is set to one-half to one guided wave wavelength.

3. The method for detecting carbon fiber prepreg layup defects based on nonlinear guided waves according to claim 1, characterized in that, In step 3, the center frequency of the Hanning window modulated sine wave signal is f. c The frequency of the continuous sinusoidal signal is f. s ; where f s with f c All are within the range of 100kHz to 500kHz, and f s The value of f is less than c .

4. The method for detecting carbon fiber prepreg layup defects based on nonlinear guided waves according to claim 3, characterized in that, The f c f s 2 times.

5. The method for detecting carbon fiber prepreg layup defects based on nonlinear guided waves according to claim 1, characterized in that, In step 2, the acoustic metamaterial layer is composed of multiple periodically arranged acoustic metamaterial cells; the bandgap center frequency of the acoustic metamaterial cells is designed to cover the excitation center frequency f selected in step 3. c The second harmonic frequency 2f c .

6. The method for detecting carbon fiber prepreg layup defects based on nonlinear guided waves according to claim 4, characterized in that, The acoustic metamaterial cell has a three-layer cylindrical structure, consisting of a matrix layer, an intermediate layer, and a top layer stacked sequentially from bottom to top. The matrix layer is the substrate. The length and width of the matrix layer are equal, both being lattice constants, and the thickness of the matrix layer is equal to the thickness of the substrate. The length and width of the intermediate layer and the top layer are equal, and these lengths and widths are smaller than the lattice constants. The matrix layer and the intermediate layer are made of the same metallic material, and the material density of the top layer is greater than that of the matrix layer and the intermediate layer. When designing the material density and geometry of the top layer, the required band gap is first determined in advance based on the range of second harmonic frequencies to be suppressed, and then the material density and geometry of the top layer are designed accordingly to achieve targeted absorption of specific second harmonic frequencies by the acoustic metamaterial layer.

7. The method for detecting carbon fiber prepreg layup defects based on nonlinear guided waves according to claim 4 or 5, characterized in that, The bandgap center frequency and bandwidth of the acoustic metamaterial cell are determined by the equivalent mass of the top layer. By replacing the top layer with one of different size or density, the bandgap characteristics of the acoustic metamaterial layer can be adjusted.

8. The method for detecting carbon fiber prepreg layup defects based on nonlinear guided waves according to claim 6, characterized in that, The relationship between the equivalent mass of the top layer and the center frequency and bandwidth of the bandgap is as follows: as the equivalent mass increases, the center frequency of the bandgap decreases and the bandwidth increases; conversely, as the equivalent mass decreases, the center frequency of the bandgap increases and the bandwidth decreases.

9. The method for detecting carbon fiber prepreg layup defects based on nonlinear guided waves according to claim 5, characterized in that, The lattice constant of the acoustic metamaterial cell is less than the transverse wave wavelength for detecting ultrasonic guided waves.

10. A carbon fiber prepreg layup defect detection system based on nonlinear guided waves, characterized in that, include: The area of ​​carbon fiber prepreg to be inspected; An excitation sensor array and a receiving sensor array are arranged in a parallel linear array on the inner and outer sides of the carbon fiber prepreg area to be detected. An acoustic metamaterial layer is disposed around the detection area; A signal generator and amplifier, connected to an excitation sensor array, for generating and amplifying the dual-frequency excitation signal; A data acquisition device, which is connected to a receiving sensor array, is used to acquire signals from the receiving sensor array. The signal processing and positioning unit is used for dual-index defect identification and judgment.

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