A rapid ultrasonic guided wave damage imaging method for aviation composite materials

Abstract

The invention discloses a rapid ultrasonic guided wave damage imaging method for aviation composite materials, which relates to the field of non-destructive testing. The method comprises the following steps: calculating the dispersion curve of a carbon fiber composite material plate according to its material parameters and obtaining the optimal ultrasonic excitation angle and ultrasonic guided wave propagation mode, sequentially scanning and collecting ultrasonic guided wave signals in two groups of orthogonal directions; decomposing the guided wave signal and extracting the target component according to the size of the energy entropy value to obtain a reconstructed ultrasonic guided wave signal; calculating the time-frequency information and energy of the signal and estimating the damage probability in the scanning path in combination with the damage index; embedding a dilated kernel convolution and a dual probability distribution function into the damage index curve to respectively achieve the enhancement of the damage index and the sharpening of the edge; expanding the damage index curves in the two groups of orthogonal directions into a two-dimensional damage matrix and performing imaging according to a composite path cross imaging method, thereby finally achieving damage location imaging of the carbon fiber composite material plate.

Description

[0001] Methodology

[0002] The present invention relates to the field of nondestructive testing, and in particular to a method for rapid ultrasonic guided wave damage imaging of aviation composite materials.

[0003] Background Methods

[0004] Carbon fiber composites are widely used in many fields such as aircraft fuselages, high-speed trains, and subway bodies due to their advantages such as light weight, high specific strength, high temperature resistance, corrosion resistance, and excellent design flexibility. However, due to the uncertainty in the complex preparation process and the external impact or fatigue loads suffered in extreme service environments, carbon fiber composites inevitably suffer from defects such as delamination, porosity, fiber breakage, fiber buckling, and fatigue cracks, which affect their mechanical properties and bring safety hazards. Therefore, it is particularly important to carry out research on health monitoring and damage detection technology of carbon fiber composite structures.

[0005] Ultrasonic guided waves, as elastic waves, have the characteristics of long propagation distance, low amplitude loss, and high damage sensitivity. Compared with the point-by-point scanning mode of traditional transmission and reflection methods, ultrasonic guided waves have higher detection efficiency for large-scale carbon fiber composite structural components. At the same time, the imaging of defects is often more intuitive than ultrasonic wave shape parameters. Therefore, ultrasonic guided wave defect imaging has emerged. Among them, probabilistic damage imaging methods have attracted widespread attention due to their simple calculation method and independence from prior knowledge of the structure. However, the existing technology has been greatly limited by the need for manual selection of damage index calibration, the need for densely arranged sensor arrays for signal acquisition, and poor imaging effect of multiple defects.

[0006] Therefore, a rapid ultrasonic guided wave damage imaging method for aviation composite materials is provided to solve the above problems. Summary of the Invention

[0007] The purpose of the present invention is to provide a rapid ultrasonic guided wave damage imaging method for aviation composite materials, overcome the shortcomings of existing probabilistic damage imaging algorithms, and achieve accurate positioning and imaging of delamination damage in carbon fiber composite laminates.

[0008] To achieve the above objectives, the present invention provides a method for rapid imaging of damage in aviation composite materials using ultrasonic guided waves, comprising the following steps:

[0009] S1: Calculate the dispersion curve of the carbon fiber composite material plate according to the material parameters of the carbon fiber composite material plate, and calculate the optimal ultrasonic excitation angle and ultrasonic propagation mode according to the dispersion curve;

[0010] S2: Determine the scanning area, set up four scanning paths with different ultrasonic propagation directions, and scan and collect ultrasonic guided wave signals along the four scanning paths respectively;

[0011] S3: Decomposing the ultrasonic guided wave signal by fully adaptive noise set empirical mode decomposition (EMD) to obtain several ultrasonic guided wave signal components, calculating the energy entropy of the ultrasonic guided wave signal components, and optimally reconstructing the ultrasonic guided wave signal components according to the energy entropy to obtain a reconstructed signal;

[0012] S4: Obtain the time-frequency information of the reconstructed signal through Hilbert transform, obtain the marginal spectrum by integrating the amplitude in the time-frequency information, calculate the damage index in the scanning path, and evaluate the degree of damage impact on the scanning path based on the damage index;

[0013] S5: Use the dilation kernel and probability distribution function to perform convolution operation on the damage index in the scanning path, enhance the defect area of ​​the damage index curve, and sharpen the defect edge area of ​​the damage index curve;

[0014] S6: Expand the damage index curves of the four scanning paths into two-dimensional image matrices respectively, process the two-dimensional image matrices to obtain damage imaging image matrices, and fuse the damage imaging image matrices to obtain the final imaging result.

[0015] Preferably, in step S2, the ultrasonic propagation directions of the four scanning paths adopt two sets of orthogonal angles, and the two sets of orthogonal angles are 0° and 90°, and 45° and 135° respectively.

[0016] Preferably, in step S3, the ultrasonic guided wave signal is decomposed by fully adaptive noise set empirical mode decomposition (EMD) to obtain several ultrasonic guided wave signal components, which specifically includes the following steps:

[0017] Step 1: Merge Gaussian white noise into the ultrasonic guided wave signal to obtain the signal to be processed x i (t), x i (t) is expressed as:

[0018] x i (t) = x(t) + μc i (t)

[0019] Where x(t) represents the ultrasonic guided wave signal, μ represents the amplitude of Gaussian white noise, and c i (t) represents the Gaussian white noise of group i;

[0020] Step 2: Decompose the signal x by EMD i (t), we get the first component IMF1 of each group, IMF1 is expressed as:

[0021]

[0022] Where T represents the EMD decomposition period. The first component IMF1 of each group in the ultrasonic guided wave signal x(t) is removed to obtain the residual component r1(t) of the first stage. r1(t) is expressed as:

[0023] r1(t)=x(t)-IMF1;

[0024] Step 3: Add i groups of Gaussian white noise with amplitude μ to the residual component r1(t) of the first stage to obtain a new signal Expressed as:

[0025]

[0026] For new signals Perform EMD decomposition to obtain the first component IMF2 of the new signal and the residual component r2(t) of the second stage. IMF2 is expressed as:

[0027]

[0028] r2(t) is expressed as:

[0029] r2(t)=r1(t)-IMF2;

[0030] Step 4: Repeat steps 1 to 3 until the residual can no longer be decomposed. At this time, the ultrasonic guided wave signal x(t) is expressed as:

[0031]

[0032] Preferably, in step S3, the energy entropy of the ultrasonic guided wave signal component is calculated, and the ultrasonic guided wave signal component is optimally reconstructed according to the energy entropy to obtain a reconstructed signal, which specifically includes the following steps:

[0033] S31: The energy entropy H(x) of the ultrasonic guided wave signal component is expressed as:

[0034]

[0035] Where P(x) is the probability density function, which represents the proportion of the energy of a single ultrasonic guided wave signal component to the total energy;

[0036] S32: Sort the energy entropy H(x) in descending order, and select the ultrasonic guided wave signal components corresponding to the first five energy entropies H(x) for reconstruction. At this time, the ultrasonic guided wave signal x(t) is expressed as:

[0037]

[0038] IMF′ i are the first five selected ultrasonic guided wave signal components.

[0039] Preferably, in step S4, the calculation is performed by Hilbert transform, which specifically includes the following steps:

[0040] S41: Perform Hilbert transform on the optimal IMF component of the ultrasonic guided wave signal to obtain the principal value integral y(t), which is expressed as:

[0041]

[0042] Where P is a slowly increasing distribution;

[0043] S42: Construct an analytical signal Z(t), and obtain an instantaneous frequency spectrum curve of the optimal IMF component of the ultrasonic guided wave signal based on the analytical signal Z(t). Z(t) is expressed as:

[0044]

[0045] Where a(t) is the instantaneous amplitude, θ(t) is the instantaneous phase, ω(t) is the instantaneous frequency, and a j (t,ω j ) is the instantaneous amplitude of the j-th order IMF component at time t and frequency j;

[0046] S43: The instantaneous amplitudes are combined in the time domain to obtain the Hilbert spectrum H(t,ω), which is expressed as:

[0047]

[0048] S44: Integrate the Hilbert spectrum on the time axis to obtain the Hilbert marginal spectrum h(t,ω), which is expressed as:

[0049]

[0050] S45: The damage index DI under each scanning path is obtained according to the Hilbert spectrum. DI is expressed as:

[0051]

[0052] Among them E r is the average value of the marginal spectrum energy, and E is the value of the marginal spectrum energy in a single scan step.

[0053] Preferably, in step S5, the probability distribution function P(d) is expressed as:

[0054]

[0055] Where d is the distance from the scanning path to the center line of the scanning area, σ is the parameter that controls the discrete degree of the damage probability, μ is the center position of the normal distribution, D is the diameter of the ultrasonic transducer, and when σ is 2.4 and μ is +2, the probability distribution function is P L (d) When σ is 2.4 and μ is -2, the probability distribution function is P R (d).

[0056] Preferably, step S5 specifically includes the following steps:

[0057] S51: convolution operation is performed on the damage index curve using a one-dimensional dilation kernel with a size of 1, a length of 11, and a dilation rate of 4;

[0058] S52: When entering the damaged area, the high-weight area is biased toward the front of the scanning area, and the probability distribution function P is used to calculate the damage area. L (d) Convolution operation is performed on the damage index curve, and the operation direction is set from left to right;

[0059] S53: When leaving the damaged area, the high-weight area is biased toward the trailing edge of the scan area, and the probability distribution function P is used to calculate the R (d) Convolution operation is performed on the damage index curve, and the operation direction is set from left to right.

[0060] Preferably, in step S6, the two-dimensional image is filled with a number of zero values ​​around it, and the two-dimensional image matrix is ​​a two-dimensional image matrix with equal rows and columns. The damage imaging image matrix M is expressed as:

[0061] M=(M0+M 90 )×(M 45 +M 135 )

[0062] Among them, M0, M 45 、M 90 and M 135 Represents the damage index distribution matrix under the scanning directions of 0°, 45°, 90° and 135° respectively.

[0063] Therefore, the present invention adopts the above-mentioned ultrasonic guided wave damage rapid imaging method for aviation composite materials, which has the following beneficial effects:

[0064] (1) The damage index calculation method adopted does not require the selection of artificial thresholds, which reduces the uncertainty when testing different samples and can effectively improve the robustness of damage detection;

[0065] (2) Introducing the energy entropy of the signal as the basis for selecting the optimal signal component when calculating the Hilbert spectrum can effectively reduce the interference of noise signals and improve the image signal-to-noise ratio;

[0066] (3) Preprocessing the damage index curve using a dilation kernel can effectively increase the damage area index and improve the contrast between damaged and undamaged areas;

[0067] (4) Using a double probability function to sharpen the damage edge can reduce the problem of damage edge expansion caused by factors such as probe width and improve the accuracy of damage imaging;

[0068] (5) The present invention adopts orthogonal image matrix fusion, which can further increase the difference between damaged areas and undamaged areas and improve imaging quality;

[0069] (6) A composite path cross-imaging method is proposed, which can identify multiple damages in flat specimens, avoid the generation of artifacts, and improve detection accuracy and efficiency.

[0070] The method scheme of the present invention is further described in detail below through the drawings and examples. BRIEF DESCRIPTION OF THE DRAWINGS

[0071] Figure 1 This is a flow chart of a method for rapid imaging of ultrasonic guided wave damage in aviation composite materials according to the present invention;

[0072] Figure 2 Graph showing phase velocity curves in all directions downward in an embodiment of the present invention;

[0073] Figure 3 Schematic diagram of dual-orthogonal scanning of a sample plate in an embodiment of the present invention;

[0074] Figure 4 This is a diagram showing the effect of the damage index enhancement of the damaged area by the expansion core in an embodiment of the present invention;

[0075] Figure 5 This is a diagram showing the optimization effect of the double probability distribution function on the damage index curve in an embodiment of the present invention;

[0076] Figure 6 This is an imaging effect diagram of a single lesion in an embodiment of the present invention;

[0077] Figure 7 This is an imaging effect diagram of multiple damages in an embodiment of the present invention. DETAILED DESCRIPTION

[0078] The method scheme of the present invention is further described below through the drawings and examples.

[0079] Unless otherwise defined, technical terms or scientific terms used in the present invention shall have the same meaning as commonly understood by one of ordinary skill in the art to which the present invention belongs.

[0080] The words “include” or “comprising” and similar words used in the present invention mean that the elements before the word include the elements listed after the word, and do not exclude the possibility of also including other elements. The orientation or position relationship indicated by the terms “inside”, “outside”, “upper”, “lower”, etc. is based on the orientation or position relationship shown in the accompanying drawings. It is only for the convenience of describing the present invention and simplifying the description, and does not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation. Therefore, it cannot be understood as a limitation of the present invention. When the absolute position of the described object changes, the relative position relationship may also change accordingly. In the present invention, unless otherwise clearly stipulated and limited, the terms such as “attachment” should be understood in a broad sense. For example, it can be a fixed connection, a detachable connection, or an integral whole; it can be directly connected or indirectly connected through an intermediate medium, and it can be the internal connection of two elements or the interaction relationship between two elements. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to the specific circumstances.

[0081] Example

[0082] In this embodiment, two carbon fiber composite material plates with different sizes and damage degrees are selected as sample plates. The first sample plate is set as a single-damage sample plate, the size is set to 600mm×300mm, the thickness is set to 2.4mm, and the diameter of the delamination damage is set to 10mm. The second sample plate is set as a multi-damage sample plate, the size is set to 400mm×400mm, the thickness is set to 2.4mm, and the diameters of the delamination damage are set to 10mm and 5mm respectively. During the experiment, the two delamination damages are scanned simultaneously.

[0083] like Figure 1 As shown, this embodiment provides a method for rapid imaging of ultrasonic guided wave damage in aviation composite materials, comprising the following steps:

[0084] S1: If Figure 2 As shown, the dispersion curve of the carbon fiber composite material plate is calculated according to the material parameters of the carbon fiber composite material plate, and the optimal ultrasonic excitation angle and ultrasonic propagation mode are calculated according to the dispersion curve. In this embodiment, the A0 mode with the largest out-of-plane displacement is used as the excitation target, and the appropriate probe frequency is selected and the optimal incident angle of the probe is calculated. The probes are placed symmetrically according to the optimal incident angle. In this embodiment, the probe frequency selected is 200 kHz, the optimal incident angle is 14.5°, and the probe spacing is 10 cm;

[0085] S2: If Figure 3As shown in the figure, the scanning area is determined, and four scanning paths with different ultrasonic propagation directions are set. The ultrasonic guided wave signals under the four scanning paths are scanned and collected respectively. When scanning different scanning paths, the scanning direction of the probe is always along the Y-axis direction. After the scanning in a single direction is completed, the carbon fiber composite material plate is rotated at a fixed angle to realize the collection of guided wave signals in different directions.

[0086] In step S2, the ultrasonic propagation directions of the four scanning paths adopt two sets of orthogonal angles, which are 0° and 90°, and 45° and 135° respectively. Scanning at orthogonal angles can accurately locate the damage position and eliminate misjudgment caused by multiple damage.

[0087] S3: Decomposing the ultrasonic guided wave signal by fully adaptive noise set empirical mode decomposition (EMD) to obtain several ultrasonic guided wave signal components, calculating the energy entropy of the ultrasonic guided wave signal components, and optimally reconstructing the ultrasonic guided wave signal components according to the energy entropy to obtain a reconstructed signal;

[0088] In step S3, the ultrasonic guided wave signal is decomposed by fully adaptive noise set empirical mode decomposition (EMD) to obtain several ultrasonic guided wave signal components, which specifically includes the following steps:

[0089] Step 1: Merge Gaussian white noise into the ultrasonic guided wave signal to obtain the signal to be processed x i (t), x i (t) is expressed as:

[0090] x i (t) = x(t) + μc i (t)

[0091] Where x(t) represents the ultrasonic guided wave signal, μ represents the amplitude of Gaussian white noise, and c i (t) represents the Gaussian white noise of group i;

[0092] Step 2: Decompose the signal x by EMD i (t), we get the first component IMF1 of each group, IMF1 is expressed as:

[0093]

[0094] Where T represents the EMD decomposition period. The first component IMF1 of each group in the ultrasonic guided wave signal x(t) is removed to obtain the residual component r1(t) of the first stage. r1(t) is expressed as:

[0095] r1(t)=x(t)-IMF1;

[0096] Step 3: Add i groups of Gaussian white noise with amplitude μ to the residual component r1(t) of the first stage to obtain a new signal Expressed as:

[0097]

[0098] For new signals Perform EMD decomposition to obtain the first component IMF2 of the new signal and the residual component r2(t) of the second stage. IMF2 is expressed as:

[0099]

[0100] r2(t) is expressed as:

[0101]

[0102] Step 4: Repeat steps 1 to 3 until the residual can no longer be decomposed. At this time, the ultrasonic guided wave signal x(t) is expressed as:

[0103]

[0104] In step S3, the energy entropy of the ultrasonic guided wave signal component is calculated, and the ultrasonic guided wave signal component is optimally reconstructed according to the energy entropy to obtain a reconstructed signal, which specifically includes the following steps:

[0105] S31: The energy entropy H(x) of the ultrasonic guided wave signal component is expressed as:

[0106]

[0107] Where P(x) is the probability density function, which represents the ratio of the energy of a single ultrasonic guided wave signal component to the total energy, thereby determining the energy size of the component and its proportion in the overall signal;

[0108] S32: Sort the energy entropy H(x) in descending order, and select the ultrasonic guided wave signal components corresponding to the first five energy entropies H(x) for reconstruction. At this time, the ultrasonic guided wave signal x(t) is expressed as:

[0109]

[0110] IMF′ i For the first five selected ultrasonic guided wave signal components, the energy entropy of each component is introduced to optimize the signal components, which can reduce the influence of noise in the guided wave signal.

[0111] S4: Obtain the time-frequency information of the reconstructed signal through Hilbert transform, obtain the marginal spectrum by integrating the amplitude in the time-frequency information, calculate the damage index in the scanning path, and evaluate the degree of damage impact on the scanning path based on the damage index;

[0112] In step S4, calculation is performed by Hilbert transform, which specifically includes the following steps:

[0113] S41: Perform Hilbert transform on the optimal IMF component of the ultrasonic guided wave signal to obtain the principal value integral y(t), which is expressed as:

[0114]

[0115] Where P is a slowly increasing distribution;

[0116] S42: Construct an analytical signal Z(t), and obtain an instantaneous frequency spectrum curve of the optimal IMF component of the ultrasonic guided wave signal based on the analytical signal Z(t). Z(t) is expressed as:

[0117]

[0118] Where a(t) is the instantaneous amplitude, θ(t) is the instantaneous phase, ω(t) is the instantaneous frequency, and a j (t,ω j ) is the instantaneous amplitude of the j-th order IMF component at time t and frequency j;

[0119] S43: The instantaneous amplitudes are combined in the time domain to obtain the Hilbert spectrum H(t,ω), which is expressed as:

[0120]

[0121] S44: Integrate the Hilbert spectrum on the time axis to obtain the Hilbert marginal spectrum h(t,ω), which is expressed as:

[0122]

[0123] S45: The damage index DI under each scanning path is obtained according to the Hilbert spectrum. DI is expressed as:

[0124]

[0125] Among them E r is the average value of the marginal spectral energy, and E is the value of the marginal spectral energy in a single scanning step. When calculating the damage index DI, there is no need to input a manually selected threshold. This calculation method can be applied to different scenarios.

[0126] In step S5, the probability distribution function P(d) is expressed as:

[0127]

[0128] Where d is the distance from the scanning path to the center line of the scanning area, σ is the parameter that controls the discrete degree of the damage probability, μ is the center position of the normal distribution, D is the diameter of the ultrasonic transducer, and when σ is 2.4 and μ is +2, the probability distribution function is P L (d) When σ is 2.4 and μ is -2, the probability distribution function is P R (d) The introduction of the double probability function effectively solves the problem of damage edge expansion caused by probe size during the scanning process.

[0129] Combining fully adaptive noise set empirical mode decomposition (EMD) with Hilbert transform can solve the problem of modal aliasing in the decomposed signal.

[0130] S5: Use the dilation kernel and probability distribution function to perform convolution operation on the damage index in the scanning path, enhance the defect area of ​​the damage index curve, and sharpen the defect edge area of ​​the damage index curve;

[0131] Step S5 specifically includes the following steps:

[0132] S51: A convolution operation is performed on the damage index curve using a one-dimensional dilation kernel with a size of 1, a length of 11, and a dilation rate of 4. The introduction of the dilation kernel effectively increases the index of the damaged area in the damage index curve and reduces the index of the undamaged area. The effect of the dilation kernel on the damage index enhancement of the damaged area is shown in the figure below. Figure 4 As shown;

[0133] S52: When entering the damaged area, the high-weight area is biased toward the front of the scanning area, and the probability distribution function P is used to calculate the damage area. L (d) Convolution operation is performed on the damage index curve, and the operation direction is set from left to right;

[0134] S53: When leaving the damaged area, the high-weight area is biased toward the trailing edge of the scan area, and the probability distribution function P is used to calculate the R (d) Convolution operation is performed on the damage index curve, and the operation direction is set from left to right;

[0135] Probability distribution function P L (d) and P R (d) The optimization effect of the damage index curve is as follows Figure 5 shown.

[0136] S6: Expanding the damage index curves of the four scanning paths into two-dimensional image matrices respectively, processing the two-dimensional image matrices to obtain damage imaging image matrices, and fusing the damage imaging image matrices to obtain the final imaging result;

[0137] In step S6, the two-dimensional image is filled with a number of zero values ​​to ensure that no data is lost when the two-dimensional image is reversely rotated and restored according to the corresponding rotation angle;

[0138] The two-dimensional image matrix is ​​a two-dimensional image matrix with equal rows and columns;

[0139] The damage imaging image matrix M is expressed as:

[0140] M=(M0+M 90 )×(M 45 +M 135 )

[0141] Among them, M0, M 45 、M 90 and M 135 The damage index distribution matrices at scanning directions of 0°, 45°, 90°, and 135° are represented respectively. The two-dimensional image matrix is ​​restored by reverse rotation according to the ultrasonic propagation angle during scanning. The two-dimensional image matrices with mutually perpendicular rotation angles are added together to increase the weight of the damage location. The two added two-dimensional image matrices are then multiplied together to effectively expand the numerical value between the damaged and undamaged areas, eliminate artifacts, and obtain the final damage imaging image matrix, thereby realizing damage positioning imaging in carbon fiber composite panels and micro-curved surface structures.

[0142] like Figure 6 and Figure 7 As shown, the ultrasonic guided wave damage rapid imaging method for aviation composite materials provided in this embodiment can accurately locate both single damaged areas and multiple damaged areas.

[0143] Therefore, the present invention adopts the above-mentioned ultrasonic guided wave rapid damage imaging method for aviation composite materials, which reduces the uncertainty when detecting different samples, effectively improves the robustness of damage detection, the image signal-to-noise ratio and the contrast between damaged areas and undamaged areas, reduces the interference of noise signals and the problem of damage edge expansion caused by reasons such as probe width, identifies multiple damages in flat specimens, avoids the generation of artifacts, and further improves the detection accuracy and efficiency of damage imaging.

[0144] Finally, it should be noted that the above embodiments are only used to illustrate the method scheme of the present invention and not to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, ordinary method personnel in this field should understand that they can still modify or replace the method scheme of the present invention with equivalents, and these modifications or equivalent replacements cannot cause the modified method scheme to deviate from the spirit and scope of the method scheme of the present invention.

Claims

1. A rapid ultrasonic guided wave damage imaging method for aviation composite materials, characterized by: The following steps are involved: S1: Calculate the dispersion curve of the carbon fiber composite material plate according to the material parameters of the carbon fiber composite material plate, and calculate the optimal ultrasonic excitation angle and ultrasonic propagation mode according to the dispersion curve; S2: Determine the scanning area, set up four scanning paths with different ultrasonic propagation directions, and scan and collect ultrasonic guided wave signals along the four scanning paths respectively; S3: Decomposing the ultrasonic guided wave signal by fully adaptive noise set empirical mode decomposition (EMD) to obtain several ultrasonic guided wave signal components, calculating the energy entropy of the ultrasonic guided wave signal components, and optimally reconstructing the ultrasonic guided wave signal components according to the energy entropy to obtain a reconstructed signal; S4: Obtain the time-frequency information of the reconstructed signal through Hilbert transform, obtain the marginal spectrum by integrating the amplitude in the time-frequency information, calculate the damage index in the scanning path, and evaluate the degree of damage impact on the scanning path based on the damage index; S5: Use the dilation kernel and probability distribution function to perform convolution operation on the damage index in the scanning path, enhance the defect area of ​​the damage index curve, and sharpen the defect edge area of ​​the damage index curve; S6: Expand the damage index curves of the four scanning paths into two-dimensional image matrices respectively, process the two-dimensional image matrices to obtain damage imaging image matrices, and fuse the damage imaging image matrices to obtain the final imaging result.

2. The method for rapid ultrasonic guided wave damage imaging of aviation composite materials according to claim 1, characterized in that: In step S2, the ultrasonic propagation directions of the four scanning paths adopt two sets of orthogonal angles, and the two sets of orthogonal angles are 0° and 90°, and 45° and 135° respectively.

3. The method for rapid ultrasonic guided wave damage imaging of aviation composite materials according to claim 1, characterized in that: In step S3, the ultrasonic guided wave signal is decomposed by fully adaptive noise set empirical mode decomposition (EMD) to obtain several ultrasonic guided wave signal components, which specifically includes the following steps: Step 1: Merge Gaussian white noise into the ultrasonic guided wave signal to obtain the signal to be processed x i (t), x i (t) is expressed as: x i (t)=x(t)+μc i (t) Where x(t) represents the ultrasonic guided wave signal, μ represents the amplitude of Gaussian white noise, and c i (t) represents the Gaussian white noise of group i; Step 2: Decompose the signal x by EMD i (t), we get the first component IMF1 of each group, IMF1 is expressed as: Where T represents the EMD decomposition period. The first component IMF1 of each group in the ultrasonic guided wave signal x(t) is removed to obtain the residual component r1(t) of the first stage. r1(t) is expressed as: r1(t)=x(t)-IMF1; Step 3: Add i groups of Gaussian white noise with amplitude μ to the residual component r1(t) of the first stage to obtain a new signal Expressed as: For new signals Perform EMD decomposition to obtain the first component IMF2 of the new signal and the residual component r2(t) of the second stage. IMF2 is expressed as: r2(t) is expressed as: r2(t)=r1(t)-IMF2; Step 4: Repeat steps 1 to 3 until the residual can no longer be decomposed. At this time, the ultrasonic guided wave signal x(t) is expressed as:

4. The method for rapid ultrasonic guided wave damage imaging of aviation composite materials according to claim 1, characterized in that: In step S3, the energy entropy of the ultrasonic guided wave signal component is calculated, and the ultrasonic guided wave signal component is optimally reconstructed according to the energy entropy to obtain a reconstructed signal, which specifically includes the following steps: S31: The energy entropy H(x) of the ultrasonic guided wave signal component is expressed as: Where P(x) is the probability density function, which represents the proportion of the energy of a single ultrasonic guided wave signal component to the total energy; S32: Sort the energy entropy H(x) in descending order, and select the ultrasonic guided wave signal components corresponding to the first five energy entropies H(x) for reconstruction. At this time, the ultrasonic guided wave signal x(t) is expressed as: IMF i ' are the first five selected ultrasonic guided wave signal components.

5. The method for rapid ultrasonic guided wave damage imaging of aviation composite materials according to claim 1, characterized in that: In step S4, calculation is performed by Hilbert transform, which specifically includes the following steps: S41: Perform Hilbert transform on the optimal IMF component of the ultrasonic guided wave signal to obtain the principal value integral y(t), which is expressed as: Where P is a slowly increasing distribution; S42: Construct an analytical signal Z(t), and obtain an instantaneous frequency spectrum curve of the optimal IMF component of the ultrasonic guided wave signal based on the analytical signal Z(t). Z(t) is expressed as: Where a(t) is the instantaneous amplitude, θ(t) is the instantaneous phase, ω(t) is the instantaneous frequency, and a j (t,ω j ) is the instantaneous amplitude of the j-th order IMF component at time t and frequency j; S43: The instantaneous amplitudes are combined in the time domain to obtain the Hilbert spectrum H(t,ω), which is expressed as: S44: Integrate the Hilbert spectrum on the time axis to obtain the Hilbert marginal spectrum h(t,ω), which is expressed as: S45: The damage index DI under each scanning path is obtained according to the Hilbert spectrum. DI is expressed as: Among them E r is the average value of the marginal spectrum energy, and E is the value of the marginal spectrum energy in a single scan step.

6. The method for rapid ultrasonic guided wave damage imaging of aviation composite materials according to claim 1, characterized in that: In step S5, the probability distribution function P(d) is expressed as: Where d is the distance from the scanning path to the center line of the scanning area, σ is the parameter that controls the discrete degree of the damage probability, μ is the center position of the normal distribution, D is the diameter of the ultrasonic transducer, and when σ is 2.4 and μ is +2, the probability distribution function is P L (d) When σ is 2.4 and μ is -2, the probability distribution function is P R (d).

7. The method for rapid ultrasonic guided wave damage imaging of aviation composite materials according to claim 6, characterized in that: Step S5 specifically includes the following steps: S51: convolution operation is performed on the damage index curve using a one-dimensional dilation kernel with a size of 1, a length of 11, and a dilation rate of 4; S52: When entering the damaged area, the high-weight area is biased toward the front of the scanning area, and the probability distribution function P is used to calculate the damage area. L (d) Convolution operation is performed on the damage index curve, and the operation direction is set from left to right; S53: When leaving the damaged area, the high-weight area is biased toward the trailing edge of the scan area, and the probability distribution function P is used to calculate the R (d) Convolution operation is performed on the damage index curve, and the operation direction is set from left to right.

8. The method for rapid ultrasonic guided wave damage imaging of aviation composite materials according to claim 1, characterized in that: In step S6, the two-dimensional image is filled with a number of zero values. The two-dimensional image matrix is ​​a two-dimensional image matrix with equal rows and columns. The damage imaging image matrix M is expressed as: M=(M0+M 90 )×(M 45 +M 135 ) Among them, M0, M 45 、M 90 and M 135 Represents the damage index distribution matrix under the scanning directions of 0°, 45°, 90° and 135° respectively.

Images