Composite material detection method based on ultrasonic lamb wave filtering back projection imaging

Abstract

The invention relates to the field of non-destructive testing of aerospace composite materials, and provides a composite material detection method based on ultrasonic lamb wave filtering back projection imaging, which comprises the following steps: acquiring a lamb wave signal penetrating through a composite material; performing noise reduction on the Lamb wave signal to obtain an optimized Lamb wave signal; performing continuous wavelet transform on the optimized lamb wave signal to obtain a flight time parameter of the optimized lamb wave signal in the composite material; and based on the flight time parameter, in combination with a filtering back projection method reconstruction algorithm, obtaining an internal image of the composite material so as to detect the internal defect of the composite material. According to the method, the Lamb wave signal is combined with the continuous wavelet transform and the filtering back projection method, a high-quality composite material internal damage image with few artifacts can be obtained without baseline signal auxiliary imaging, and nondestructive testing can be effectively, rapidly and accurately carried out on the plate-shaped composite material.

Description

Technical Field

[0001] The invention relates to the field of nondestructive testing and diagnosis of aerospace composite materials, and in particular to a composite material testing method based on ultrasonic Lamb wave filtering back-projection imaging. Background Art

[0002] In industries such as aerospace, damage to key components and structures can lead to catastrophic damage without prior notice or timely discovery, endangering equipment and personal safety. Therefore, quality inspection, especially non-destructive testing and imaging inspection of the interior of components, is necessary at all stages of design, production and service. Therefore, non-destructive testing technology for the interior of components, especially the interior of composite materials, is very important. In the prior art, non-destructive testing of the internal structure of composite materials is generally achieved by thermal imaging, X-ray detection, magnetic particle detection and eddy current detection. However, the detection accuracy and detection range of traditional detection methods of this type are limited, and can only detect larger damage. In addition, the requirements for the detection environment are relatively harsh, and they can often only be carried out regularly during the life cycle of the composite material. It is impossible to achieve real-time detection of the interior of the composite material, and it is difficult to meet the requirements of efficiency and accuracy in the actual engineering environment.

[0003] Therefore, the prior art still needs to be improved and developed. Summary of the invention

[0004] In view of the above-mentioned deficiencies in the prior art, the object of the present invention is to provide a composite material detection method based on ultrasonic Lamb wave filtering back projection imaging, aiming to solve the problem that traditional composite material nondestructive testing methods in the prior art are difficult to achieve efficient and accurate detection of composite materials.

[0005] The first aspect of the present invention provides a composite material detection method based on ultrasonic Lamb wave filtering back projection imaging, comprising the steps of:

[0006] Acquire Lamb wave signals passing through composite materials;

[0007] De-noising the Lamb wave signal to obtain an optimized Lamb wave signal;

[0008] Performing continuous wavelet transform on the optimized Lamb wave signal to obtain an energy signal corresponding to the excitation frequency in the optimized Lamb wave signal, and further calculating a flight time parameter of the optimized Lamb wave signal in the composite material;

[0009] Based on the time-of-flight parameters and in combination with a filtered back-projection reconstruction algorithm, an internal image of the composite material is acquired to detect internal defects of the composite material.

[0010] In one embodiment, obtaining a Lamb wave signal passing through a composite material specifically includes:

[0011] Surrounding the composite material, a circular ultrasonic sensor array is arranged at equal angles and fixed intervals;

[0012] Selecting an ultrasonic sensor as an initial sensor, starting from the initial sensor, each of the ultrasonic sensors sequentially acts as a transmitting source to transmit a Lamb wave signal into the composite material, and when each ultrasonic sensor acts as a transmitting source, the remaining ultrasonic sensors receive the Lamb wave signal;

[0013] Scanning is performed in sequence in a circular ultrasonic sensor array manner. After all the ultrasonic sensors have served as transmitting sources, all Lamb wave signals received by the ultrasonic sensors are acquired and arranged in sequence.

[0014] In one implementation, the Lamb wave signal is subjected to noise reduction to obtain an optimized Lamb wave signal, specifically comprising:

[0015] Determine all extreme points of the Lamb wave signal;

[0016] According to the extreme value point, obtaining an average envelope function of the Lamb wave signal;

[0017] Determining an intrinsic mode function of the Lamb wave signal based on the average envelope function;

[0018] Based on the intrinsic mode function, the Lamb wave signal is reconstructed to obtain the optimized Lamb wave signal.

[0019] In one implementation, based on the intrinsic mode function, reconstructing the Lamb wave signal to obtain the optimized Lamb wave signal specifically includes:

[0020] Screening out the component corresponding to the noise part in the intrinsic mode function to reduce the noise of the Lamb wave signal;

[0021] Map the denoised Lamb wave signal to the wavelet function space for decomposition;

[0022] Based on a preset threshold, the denoised Lamb wave signal is decomposed several times to obtain an optimal reconstructed signal;

[0023] Based on the best reconstructed signal, the optimized Lamb wave signal is reconstructed.

[0024] In one embodiment, performing continuous wavelet transform on the optimized Lamb wave signal to obtain the flight time parameter of the optimized Lamb wave signal in the composite material specifically includes:

[0025] Determining the continuous wavelet transform coefficients and the corresponding kernel function of the optimized Lamb wave signal;

[0026] Based on the continuous wavelet transform coefficients, determining an energy signal of the optimized Lamb wave signal;

[0027] Based on the kernel function, separating the optimized Lamb wave signal amplitude and phase, and measuring the center frequency and bandwidth of the optimized Lamb wave signal;

[0028] The flight time parameter of the optimized Lamb wave signal in the composite material is determined by combining the energy signal, the center frequency and the bandwidth.

[0029] In one embodiment, combining the energy signal, the center frequency and the bandwidth to determine the flight time parameter of the optimized Lamb wave signal in the composite material specifically includes:

[0030] Based on the Lamb wave signals acquired by the ultrasonic sensor, determining the flight time of each Lamb wave signal corresponding to the sensing path;

[0031] Calculate the time delay caused by the scattered or reflected waves caused by the damage by combining the energy signal, the center frequency and the bandwidth;

[0032] Based on the flight time and the time delay, a flight time parameter of the optimized Lamb wave signal within the composite material is determined.

[0033] In one embodiment, obtaining an internal image of the composite material based on the time-of-flight parameter combined with a filtered back-projection reconstruction algorithm to detect internal defects of the composite material specifically includes:

[0034] Based on the flight time parameters of the optimized Lamb wave signals and the Lamb wave signals arranged in sequence, determining the projection value and projection angle of each of the optimized Lamb wave signals on the internal projection path of the composite material;

[0035] The Fourier transform value on the straight line is determined, and based on the Fourier center slice theorem, the Fourier transform value is interpolated into a two-dimensional Fourier domain, and the internal image of the composite material is reconstructed by combining the projection value and the projection angle.

[0036] In one embodiment, the projection value is the line integral of the inverse of the propagation speed of the optimized Lamb wave signal in the plate, and the flight time parameter is brought into the filtered back projection reconstruction algorithm as the projection value.

[0037] The second aspect of the present invention discloses an intelligent terminal, including a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the steps of the composite material detection method based on ultrasonic Lamb wave filtering back projection imaging as described in any of the above items are implemented.

[0038] A third aspect of the present invention discloses a computer-readable storage medium for storing computer instructions, which, when executed by a processor, implement the steps of the composite material detection method based on ultrasonic Lamb wave filtering back projection imaging as described in any of the above items.

[0039] The present invention provides a composite material detection method based on ultrasonic Lamb wave filtered back projection imaging, comprising the steps of: using an ultrasonic sensor to transmit a Lamb wave signal to a composite material, and obtaining the Lamb wave signal passing through the composite material; performing noise reduction on the Lamb wave signal to obtain an optimized Lamb wave signal; performing continuous wavelet transform on the optimized Lamb wave signal to obtain the flight time parameter of the optimized Lamb wave signal in the composite material; based on the flight time parameter, combined with a filtered back projection reconstruction algorithm, obtaining an internal image of the composite material to detect internal defects of the composite material. The present invention utilizes Lamb wave signals combined with continuous wavelet transform and filtered back projection method, and can obtain high-quality composite material internal damage images with few artifacts without the need for baseline signal auxiliary imaging, and can effectively, quickly and accurately perform non-destructive testing on camouflage materials. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0041] Figure 1 It is a flow chart of the composite material detection method based on ultrasonic Lamb wave filtering back projection imaging of the present invention;

[0042] Figure 2 An implementation method of setting a sensor relative to a composite material in a composite material detection method based on ultrasonic Lamb wave filtering back projection imaging of the present invention;

[0043] Figure 3 Another embodiment of the arrangement of the sensor relative to the composite material in the composite material detection method based on ultrasonic Lamb wave filtering back projection imaging of the present invention;

[0044] Figure 4It is another embodiment of the arrangement of the sensor relative to the composite material in the composite material detection method based on ultrasonic Lamb wave filtering back projection imaging of the present invention;

[0045] Figure 5 It is an initial waveform diagram of the Lamb wave signal in the composite material detection method based on ultrasonic Lamb wave filtering back projection imaging of the present invention;

[0046] Figure 6 It is a waveform diagram of the Lamb wave signal after noise reduction and reconstruction in the composite material detection method based on ultrasonic Lamb wave filtering back projection imaging of the present invention;

[0047] Figure 7 Schematic diagram of the intelligent terminal of the present invention. DETAILED DESCRIPTION

[0048] The present invention provides a composite material detection method based on ultrasonic Lamb wave filtering back projection imaging. In order to make the purpose, technical solution and effect of the present invention clearer and more specific, the present invention is further described in detail below. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0049] Nondestructive testing and diagnosis are prerequisites for ensuring production quality, especially in the aerospace field. Real-time monitoring and fault diagnosis of key components and structures can detect and identify possible anomalies and faults in the structure as early as possible. Through data analysis and algorithm processing, flexible control and management can be achieved to minimize performance degradation and economic costs and avoid dangerous situations for equipment and personnel. At present, there have been a lot of related research on damage detection methods for plate structures. Traditional methods include thermal imaging, X-ray detection, magnetic particle detection, eddy current detection, etc. These methods have limited detection accuracy and detection range, and can often only detect larger damage or metal plate components; and the detection range of traditional methods is relatively small, which cannot be well applied to damage detection of a wide range of composite panels; in particular, for example, thermal imaging has high requirements for ambient temperature changes, X-ray detection has special requirements for the size and transmission direction of the test piece, and magnetic particle detection and eddy current detection are not suitable for composite materials and are not sensitive to internal damage of plate materials. Moreover, most non-destructive testing technologies can usually only be performed periodically during the life cycle of engineering structures and assets, and cannot provide real-time and efficient information on structural damage. Most non-destructive testing methods provide very limited information on structural integrity. In addition, the equipment of traditional testing methods is often large, complex to operate, and expensive, and it is difficult to directly apply them in actual engineering environments.

[0050] Compared with traditional nondestructive testing methods, Lamb waves have broad application prospects in the field of material damage detection due to their high penetration, long propagation distance, low attenuation, low cost and sensitivity to various defects in composite materials. The present invention uses Lamb wave signals to scan the inside of the composite material, uses the EMD (empirical mode decomposition) method and wavelet transform (wavelet transform) to reduce noise and reconstruct the Lamb wave signal, and then uses CWT (continues wavelet transform, continuous wavelet transform) to extract the flight time parameters of the Lamb wave signal in the composite material to be detected, and then uses the filtered back projection algorithm to perform Radon transform reconstruction to obtain the internal image of the composite material. The final composite material internal damage image has high imaging quality and few artifacts, and does not require baseline signals for auxiliary imaging, which can realize the detection, positioning, evaluation and imaging of the structural integrity and damage information of plate-like materials.

[0051] Specifically, Figure 1 As shown, the composite material detection method based on ultrasonic Lamb wave filtering back projection imaging of the present invention comprises the following steps:

[0052] S100. Acquire a Lamb wave signal passing through the composite material.

[0053] Nondestructive testing technology based on Lamb wave propagation is highly sensitive to damage on the surface of materials and embedded structures, and can detect damage inside materials. Taking advantage of the characteristics of Lamb waves, such as high penetration, long propagation distance, low attenuation, low cost, and sensitivity to various defects, Lamb wave signals can be used to detect various types of damage (delamination, debonding, cracks, holes, etc.), with high detection speed and high result accuracy, and can achieve rapid detection and evaluation of the interior of composite materials.

[0054] Specifically, step S100 includes:

[0055] S110, surrounding the composite material, a circular ultrasonic sensor array is arranged at equal angles and fixed intervals;

[0056] S120, selecting an ultrasonic sensor as an initial sensor, starting from the initial sensor, each of the ultrasonic sensors sequentially acts as a transmitting source to transmit a Lamb wave signal into the composite material, and when each ultrasonic sensor acts as a transmitting source, the remaining ultrasonic sensors receive the Lamb wave signal;

[0057] S130, scanning is performed in sequence in a circular ultrasonic sensor array manner, and after all the ultrasonic sensors have served as transmitting sources, all Lamb wave signals received by the ultrasonic sensors are acquired and arranged in sequence.

[0058] In order to ensure that the Lamb wave signal emitted to the composite material can pass through the interior of the composite material more evenly and achieve a larger effective coverage area, how to set the relative position relationship between the transmitting source and receiving source of the Lamb wave signal and the composite material is the key.

[0059] like Figure 2 As shown in the figure, it is a single-through setting in which ultrasonic sensors are set in parallel on both sides of the composite material as the transmitting source and the receiving source respectively. The gray circle is the ultrasonic sensor, and the line between the ultrasonic sensors inside the box is the projection path of the Lamb wave signal emission. It can be seen that this setting method can only detect composite materials within a small range, and the path direction of the Lamb wave signal is single, with obvious density differences; Figure 3 As shown in the figure, the ultrasonic sensors are used as the transmitting source and the receiving source respectively, where the gray circle is the ultrasonic sensor, and the line between the ultrasonic sensors inside the box is the projection path of the Lamb wave signal emission, which is arranged as a double-penetration setting of a rectangular surrounding composite material. It can be seen that this setting method has more uniform coverage than the single-penetration setting, but there are also dead spots in the four corners, and the path of the Lamb wave signal has obvious density differences in the center and the position close to the ultrasonic sensor; Figure 4 As shown, it is an equidistant fan-shaped beam structure setting, that is, the ultrasonic sensor surrounds the composite material to form a circular ultrasonic sensor array, where the gray circle is the ultrasonic sensor, and the connection between the ultrasonic sensors inside the circular ultrasonic sensor array structure is the projection path of the Lamb wave signal emission. It can be seen that in this setting, the path of the Lamb wave signal is evenly distributed and the effective coverage area is the largest, there is basically no dead angle, and the scanning accuracy is also higher, which is conducive to the comprehensive detection of the composite material. Therefore, preferably, the present invention adopts Figure 4 The ultrasonic sensor setup is shown.

[0060] Furthermore, when transmitting Lamb wave signals, the present invention first sets an ultrasonic sensor as an initial sensor, and the initial sensor is used as a transmitting source to transmit an ultrasonic signal as a Lamb wave signal, and the remaining ultrasonic sensors are used as receiving sources to receive signals in a clockwise direction; after all ultrasonic sensors have received the Lamb wave signals, the next ultrasonic sensor in the clockwise direction of the initial sensor is used as a transmitting source to transmit an ultrasonic signal, and the remaining ultrasonic sensors including the initial sensor are used as receiving sources to receive signals in a clockwise direction. In this way, after all ultrasonic sensors have successively acted as transmitting sources and have all transmitted ultrasonic signals, the scanning of the composite material is completed, which can ensure that the ray distribution of the Lamb wave signal is more uniform, the effective coverage area is wider, and higher scanning accuracy is provided.

[0061] Furthermore, if Figure 1 As shown, after step S100, the composite material detection method based on ultrasonic Lamb wave filtering back projection imaging of the present invention further includes:

[0062] S200: De-noise the Lamb wave signal to obtain an optimized Lamb wave signal.

[0063] The present invention combines EMD and wavelet transform to remove high-frequency noise in the signal, thereby reconstructing an optimized Lamb wave signal. Among them, EMD decomposes the complex Lamb signal in the time domain according to the orthogonality of the signal and the single intrinsic component obtained after the recursive process, and identifies all intrinsic oscillation modes in the complex motion, and finally extracts a single component with a relatively pure signal; while DB filtering is based on the db mother wavelet basis to perform discrete wavelet transform and signal reconstruction, and obtains the low-frequency part of the signal and reconstructs the signal by discretely decomposing the signal to filter out a large amount of high-frequency noise. In this way, an optimized Lamb wave signal with a high signal-to-noise ratio and low noise is obtained, which is helpful for the subsequent more accurate determination of the flight time (TOF, Time of Flight) of the Lamb wave signal in the composite material, and reduces the artifacts and burrs after image reconstruction, so that the final damage image is more accurate and clean.

[0064] Specifically, step S200 includes:

[0065] S210, determining all extreme points of the Lamb wave signal;

[0066] S220, acquiring an average envelope function of the Lamb wave signal according to the extreme value point;

[0067] S230, determining an intrinsic mode function of the Lamb wave signal based on the average envelope function;

[0068] S240. Reconstruct the Lamb wave signal based on the intrinsic mode function to obtain the optimized Lamb wave signal.

[0069] The EMD method involves orthogonality and a single intrinsic component obtained after a recursive process. It decomposes the complex signal according to its time domain and identifies all the intrinsic oscillation modes in the complex motion. In general, any signal is composed of different intrinsic mode functions (IMFs). The linear or nonlinear model of the extreme value and zero crossing of each point is the same. Any continuous crossing point has only one extreme value. Each mode should be independent of other modes. The complex signal can be decomposed into a finite number of IMF signals through EMD. Each component contains the characteristics of the original signal at different time scales. The IMF must meet two conditions: first, the number of local extreme value points and zero crossing points must be equal or at most one difference over the entire time range of the function. Second, the local IMF values ​​are symmetrical and have a mean of zero. The essence of the EMD method is to decompose the complex signal into a finite number of IMFs, and the IMF components are obtained by forcing a stable signal. For the Lamb wave signal X(t), after finding all the extreme points, the spline difference function e is used to extract the local extreme value points and zero crossing points. min (t) and e max (t) Calculate the average envelope function:

[0070] m(t)=(e max (t)+e min (t)) / 2.

[0071] The Lamb wave signal X(t) minus the average envelope function m(t) is the characteristic mode function IMF i (t), if the characteristic mode function cannot be successfully obtained, repeat the above steps to obtain:

[0072]

[0073] Where R(t) is the residual component, that is, the part that needs to be filtered out. In this way, the high-frequency noise in the Lamb wave signal can be effectively filtered out through EMD, thereby improving the accuracy of the signal and ensuring that the subsequent reconstruction of the internal damage image of the composite material is more accurate and clear.

[0074] Specifically, step S240 includes:

[0075] S241, filtering out the component corresponding to the noise part in the intrinsic mode function, and performing noise reduction on the Lamb wave signal;

[0076] S242, mapping the denoised Lamb wave signal to a wavelet function space for decomposition;

[0077] S243, based on a preset threshold, decomposing the denoised Lamb wave signal several times to obtain an optimal reconstructed signal;

[0078] S244: reconstruct the optimized Lamb wave signal based on the best reconstructed signal.

[0079] After determining the residual components and characteristic mode functions corresponding to the high-frequency noise in the original Lamb wave signal through EMD, the corresponding components are screened out and the Lamb wave signal is denoised. The wavelet transform then maps the Lamb wave signal after EMD denoising to the wavelet function space, and decomposes the signal into two parts: large-scale approximation and detailed representation. The large-scale approximation part is further decomposed according to the definition to obtain a larger-scale approximation and finer detail resolution. In this way, the best reconstructed signal can be obtained by iterating multiple segmentations and selecting the corresponding requirements of the transform part. Optionally, the wavelet transform can reduce the autocorrelation of the signal, and then perform threshold analysis on the decomposed wavelet coefficients, adjust the wavelet coefficients within the preset threshold, and thus obtain the best reconstructed signal. Figure 5 The original Lamb wave signal is shown in Figure 1. It can be seen that the resolution of the signal is poor. After using "db8" to decompose the six-layer wavelet, as shown in Figure 1. Figure 6 As shown, the obtained Lamb wave signal is very smooth, and both low-frequency noise and high-frequency noise are screened out, so that the optimized Lamb wave signal finally obtained has a high signal-to-noise ratio and low noise, which helps to more accurately extract the flight time of the optimized Lamb wave signal and reduce artifacts and glitches after image reconstruction, making the damaged reconstructed image more accurate and clear.

[0080] Furthermore, if Figure 1 As shown, after step S200, the composite material detection method based on ultrasonic Lamb wave filtering back projection imaging of the present invention further includes:

[0081] S300, performing continuous wavelet transform on the optimized Lamb wave signal to obtain an energy signal corresponding to the excitation frequency in the optimized Lamb wave signal, and further calculating to obtain a flight time parameter of the optimized Lamb wave signal in the composite material.

[0082] The flight time calculation method of CWT continuous wavelet transform is combined with complex Morlet wavelet transform to obtain the energy-time spectrum of the signal at the excitation frequency, and determine the local peak energy of the low-frequency signal to provide relevant data for the subsequent reconstruction of the internal image of the composite material.

[0083] Specifically, step S300 includes:

[0084] S310, determining the continuous wavelet transform coefficients of the optimized Lamb wave signal and the corresponding kernel function;

[0085] S320, determining an energy signal of the optimized Lamb wave signal based on the continuous wavelet transform coefficient;

[0086] S330, separating the optimized Lamb wave signal amplitude and phase based on the kernel function, and measuring the center frequency and bandwidth of the optimized Lamb wave signal;

[0087] S340, determining the flight time parameter of the optimized Lamb wave signal in the composite material by combining the energy signal, the center frequency and the bandwidth.

[0088] Among them, the continuous wavelet transform (CWT) uses two parameters to achieve scaling and translation respectively, so the CWT form of the Lamb wave signal is:

[0089]

[0090]

[0091] Among them, CWT (a, b) is the continuous wavelet transform coefficient, where a is used for scaling and b is used for translating the mother wavelet function ψ (t), L s (t) represents the collected time series Lamb wave signal, * represents the complex conjugate, ψ (a，b) (t) is the kernel function corresponding to the continuous wavelet transform coefficient CWT (a, b), and t is time. Optionally, the complex Morlet wavelet is used to separate the amplitude and phase of the Lamb wave signal and measure the range of instantaneous frequency and time. The complex Morlet wavelet is defined as:

[0092]

[0093] Among them, j is an imaginary number, f c represents the center frequency, f b Represents the bandwidth and controls the shape of the mother wavelet.

[0094] Therefore, the local peak energy corresponding to the Lamb wave excitation frequency can be determined by using the complex Mollet wavelet and constructing the energy-time envelope. For the continuous wavelet transform, its square modulus represents the energy density distribution in the time domain, revealing the most concentrated energy corresponding to the instantaneous frequency of the low-frequency signal received by the receiver, so that the coefficients in the CWT energy signal reach the maximum value at the instantaneous frequency, corresponding to the center frequency of the Lamb wave signal analyzed at the current moment. Among them, the scalar form of the CWT energy concentration is:

[0095]

[0096] When analyzing the energy distribution of Lamb wave signals based on complex Mollet wavelet, the relationship between each frequency and scale parameter can be defined as:

[0097]

[0098] Where f is the scattered signal, f c is the center frequency of the wavelet (take 1 to obtain the energy information corresponding to the excitation frequency), f s is the sampling frequency of the Lamb wave signal, and a is the scale parameter, which controls the resolution in the time domain and frequency domain.

[0099] After the optimized Lamb wave signal is subjected to continuous wavelet transform, the flight time parameter of the optimized Lamb wave signal in the composite material can be determined by combining the energy signal, the center frequency, the sampling frequency and the bandwidth, thereby providing relevant data for the subsequent reconstruction of the internal image of the composite material. Optionally, the flight time parameter is the flight time (TOF) of the optimized Lamb wave signal in the composite material.

[0100] Specifically, step S340 includes:

[0101] S341, determining the flight time of each Lamb wave signal corresponding to a sensing path based on the Lamb wave signal acquired by the ultrasonic sensor;

[0102] S342, calculating the time delay caused by the scattered or reflected waves caused by the damage by combining the energy signal, the center frequency and the bandwidth;

[0103] S343. Determine a flight time parameter of the optimized Lamb wave signal in the composite material based on the flight time and the time delay.

[0104] The flight time of the corresponding sensing path of each Lamb wave signal is determined by the time difference between the emission and reception of Lamb wave signals between different ultrasonic sensors. When there is no damage inside the composite material, the sensing path of each Lamb wave signal is the line between the two ultrasonic sensors, and the actual sensing path matches the expected sensing path; when there is damage inside the composite material, the Lamb wave signal will be scattered and reflected after passing through the damaged part, and the time for the scattered or reflected wave to actually reach the corresponding ultrasonic sensor becomes longer. At this time, the flight time is greater than the flight time of the Lamb wave signal along the straight line, and the actual sensing path does not match the expected sensing path. The Lamb wave energy information is obtained by continuous wavelet transform, and then the time corresponding to the peak value is subtracted from the time of the excitation signal to obtain a more accurate flight time. In this way, the energy signal, the center frequency and the bandwidth are obtained by continuous wavelet transform, so as to calculate the time delay caused by the scattered or reflected wave caused by the damage. Finally, based on the flight time and the time delay, the flight time parameters of the optimized Lamb wave signal in the composite material are determined to ensure that the actual damage is matched when reconstructing the internal image of the composite material.

[0105] Furthermore, if Figure 1As shown, after step S300, the composite material detection method based on ultrasonic Lamb wave filtering back projection imaging of the present invention further includes:

[0106] S400 , acquiring an internal image of the composite material based on the time-of-flight parameter in combination with a filtered back-projection reconstruction algorithm to detect internal defects of the composite material.

[0107] The filtered back-projection transform is to bring the flight time of the Lamb wave inside the composite material as the projection value on the projection path of the detection area into the Radon transform, and realize the image reconstruction according to the Fourier center slice theorem. First, a circular ultrasonic sensor array is set up using an equidistant fan-shaped beam structure to complete the scanning of the composite material. According to the group velocity dispersion curve of the Lamb wave, the wave velocity varies with the plate thickness. When the Lamb wave encounters a strong scattering defect, the propagation of the Lamb wave will bypass the fault, resulting in a path length greater than the straight line length, which increases the flight time, that is, the actual propagation path of the Lamb wave signal becomes longer, which is equivalent to reducing the propagation speed. Then, the projection value (TOF data of the Lamb wave) of the detection area on the projection path increases, resulting in the appearance of a defect area corresponding to the actual damage in the internal image of the composite material reconstructed by the filtered back-projection method. The coordinates and shape of the defect area are consistent with the position and size of the actual defect point, so that the plate-shaped material can be effectively, quickly and accurately non-destructively tested.

[0108] Specifically, step S400 includes:

[0109] S410, determining a projection value and a projection angle of each of the optimized Lamb wave signals on an internal projection path of the composite material based on the flight time parameters of the optimized Lamb wave signals and the Lamb wave signals arranged in sequence;

[0110] S420, determining the Fourier transform value on the straight line, interpolating the Fourier transform value into a two-dimensional Fourier domain based on the Fourier center slice theorem, combining the projection value and the projection angle, and reconstructing an internal image of the composite material.

[0111] Radon transform is an integral transformation function that projects a two-dimensional plane image onto a one-dimensional contour image along a certain direction. The expression is:

[0112]

[0113] Wherein, t is the projection line corresponding to xcosθ+ysinθ, and θ is the projection angle. The present invention realizes Radon transform through filtered back projection (FBP), which can form a better reconstructed image in a shorter computing time. The filtered back projection method reconstructs the image by estimating the target image slices through a set of projections. Among them, the two-dimensional object requires the Fourier slice theorem, which provides the Fourier transform values ​​on the straight line. If the other projections are assumed to be zero and the Fourier transform values ​​are correctly interpolated into the two-dimensional Fourier domain, the image can be reconstructed to obtain the damage information inside the composite material. The reconstruction algorithm of the filtered back projection method is expressed as:

[0114]

[0115] where is derived from the filtered projection Qθ(ω) Depend on To estimate the reconstructed image f(x, y), N represents the number of sensors, θ i represents the projection angle.

[0116] Therefore, after the Fourier transform value is interpolated into the two-dimensional Fourier domain, the image corresponding to the internal damage of the composite material can be reconstructed by combining the projection value of the optimized Lamb wave signal on the projection path and the projection angle of the projection path. The projection value is the line integral of the slowness of the optimized Lamb wave signal on the projection path. The flight time parameter is used as the projection value to bring into the filtered back projection reconstruction algorithm, where the slowness is the derivative of the propagation speed of the Lamb wave signal, so the projection value is defined as:

[0117]

[0118] Among them, s represents the relay path, and v(s) represents the current propagation speed of the Lamb wave.

[0119] In this way, when the Lamb wave signal passes through the defects inside the composite material, the propagation of the Lamb wave will bypass the fault, resulting in the projection path length being greater than the straight line length, increasing the flight time, that is, the actual propagation path of the Lamb wave signal becomes longer, which is equivalent to reducing the propagation speed. The projection value of the detection area on the projection path increases, resulting in the appearance of a defect area corresponding to the actual damage in the internal image of the composite material reconstructed by the filtered back projection method. The coordinates and shape of the defect area are consistent with the position and size of the actual defect point, thereby enabling effective, rapid and accurate non-destructive testing of plate-like materials.

[0120] Based on the above composite material detection method based on ultrasonic Lamb wave filtering back projection imaging, the present invention also provides an intelligent terminal, such as Figure 7As shown, the intelligent terminal includes at least one processor, a display screen and a memory, and may also include a communication interface and a bus. The processor, the display screen, the memory and the communication interface can communicate with each other through the bus. The display screen is configured to display a preset user guide interface in the initial setting mode. The communication interface can transmit information. The processor can call the logic instructions in the memory 2 to execute the method in the above embodiment.

[0121] In addition, the logic instructions in the memory can be implemented in the form of software functional units and can be stored in a computer-readable storage medium when sold or used as an independent product.

[0122] The memory, as a computer-readable storage medium, can be configured to store software programs, computer executable programs, such as program instructions or modules corresponding to the methods in the embodiments of the present invention. The processor executes functional applications and data processing by running the software programs, instructions or modules stored in the memory, that is, implementing the methods in the above embodiments.

[0123] The memory may include a program storage area and a data storage area, wherein the program storage area may store an operating system and at least one application required for a function; the data storage area may store data created according to the use of the terminal device, etc. In addition, the memory may include a high-speed random access memory and may also include a non-volatile memory. For example, a variety of media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a disk or an optical disk, may also be a transient storage medium.

[0124] In addition, the specific process of loading and executing the multiple instruction processors in the above-mentioned storage medium and the terminal device has been described in detail in the above-mentioned method, and will not be described one by one here.

[0125] In summary, the present invention discloses a composite material detection method based on ultrasonic Lamb wave filtered back projection imaging, comprising the steps of: using an ultrasonic sensor to transmit a Lamb wave signal to a composite material, and obtaining a Lamb wave signal passing through the composite material; performing noise reduction on the Lamb wave signal to obtain an optimized Lamb wave signal; performing continuous wavelet transform on the optimized Lamb wave signal to obtain a flight time parameter of the optimized Lamb wave signal in the composite material; based on the flight time parameter, combined with a filtered back projection reconstruction algorithm, obtaining an internal image of the composite material to detect internal defects of the composite material. The present invention utilizes Lamb wave signals combined with continuous wavelet transform and filtered back projection method, and can obtain high-quality and artifact-free internal damage images of composite materials without the need for baseline signal auxiliary imaging, and can effectively, quickly and accurately perform non-destructive testing on camouflage materials.

[0126] The embodiments described above are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, it should be understood by those skilled in the art that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features therein may be replaced by equivalents. However, these modifications or replacements do not deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should be included in the protection scope of the present invention.

Claims

1. A composite material detection method based on ultrasonic Lamb wave filtering back projection imaging, characterized in that: Includes steps: Acquire Lamb wave signals passing through composite materials; De-noising the Lamb wave signal to obtain an optimized Lamb wave signal; Performing continuous wavelet transform on the optimized Lamb wave signal to obtain an energy signal corresponding to the excitation frequency in the optimized Lamb wave signal, and further calculating a flight time parameter of the optimized Lamb wave signal in the composite material; Based on the time-of-flight parameters and in combination with a filtered back-projection reconstruction algorithm, an internal image of the composite material is acquired to detect internal defects of the composite material.

2. The composite material detection method based on ultrasonic Lamb wave filtering back projection imaging according to claim 1 is characterized in that: Acquire Lamb wave signals through composite materials, including: Surrounding the composite material, a circular ultrasonic sensor array is arranged at equal angles and fixed intervals; Selecting an ultrasonic sensor as an initial sensor, starting from the initial sensor, each of the ultrasonic sensors sequentially acts as a transmitting source to transmit a Lamb wave signal into the composite material, and when each ultrasonic sensor acts as a transmitting source, the remaining ultrasonic sensors receive the Lamb wave signal; Scanning is performed in sequence in a circular ultrasonic sensor array manner. After all the ultrasonic sensors have served as transmitting sources, all Lamb wave signals received by the ultrasonic sensors are acquired and arranged in sequence.

3. The composite material detection method based on ultrasonic Lamb wave filtering back projection imaging according to claim 2 is characterized in that: Denoising the Lamb wave signal to obtain an optimized Lamb wave signal specifically includes: Determine all extreme points of the Lamb wave signal; According to the extreme value point, obtaining an average envelope function of the Lamb wave signal; Determining an intrinsic mode function of the Lamb wave signal based on the average envelope function; Based on the intrinsic mode function, the Lamb wave signal is reconstructed to obtain the optimized Lamb wave signal.

4. The composite material detection method based on ultrasonic Lamb wave filtering back projection imaging according to claim 3 is characterized in that: Based on the intrinsic mode function, reconstructing the Lamb wave signal to obtain the optimized Lamb wave signal specifically includes: Screening out the component corresponding to the noise part in the intrinsic mode function to reduce the noise of the Lamb wave signal; Map the denoised Lamb wave signal to the wavelet function space for decomposition; Based on a preset threshold, the denoised Lamb wave signal is decomposed several times to obtain an optimal reconstructed signal; Based on the best reconstructed signal, the optimized Lamb wave signal is reconstructed.

5. The composite material detection method based on ultrasonic Lamb wave filtering back projection imaging according to claim 2 is characterized in that: Performing continuous wavelet transform on the optimized Lamb wave signal to obtain the flight time parameter of the optimized Lamb wave signal in the composite material specifically includes: Determining the continuous wavelet transform coefficients and the corresponding kernel function of the optimized Lamb wave signal; Based on the continuous wavelet transform coefficients, determining an energy signal of the optimized Lamb wave signal; Based on the kernel function, separating the optimized Lamb wave signal amplitude and phase, and measuring the center frequency and bandwidth of the optimized Lamb wave signal; The flight time parameter of the optimized Lamb wave signal in the composite material is determined by combining the energy signal, the center frequency and the bandwidth.

6. The composite material detection method based on ultrasonic Lamb wave filtering back projection imaging according to claim 5 is characterized in that: Combining the energy signal, the center frequency and the bandwidth, determining the flight time parameter of the optimized Lamb wave signal in the composite material specifically includes: Based on the Lamb wave signals acquired by the ultrasonic sensor, determining the flight time of each Lamb wave signal corresponding to the sensing path; Calculate the time delay caused by the scattered or reflected waves caused by the damage by combining the energy signal, the center frequency and the bandwidth; Based on the flight time and the time delay, a flight time parameter of the optimized Lamb wave signal within the composite material is determined.

7. The composite material detection method based on ultrasonic Lamb wave filtering back projection imaging according to claim 2 is characterized in that: Based on the time-of-flight parameter combined with a filtered back-projection reconstruction algorithm, an internal image of the composite material is obtained to detect internal defects of the composite material, specifically including: Based on the flight time parameters of the optimized Lamb wave signals and the Lamb wave signals arranged in sequence, determining the projection value and projection angle of each of the optimized Lamb wave signals on the internal projection path of the composite material; The Fourier transform value on the straight line is determined, and based on the Fourier center slice theorem, the Fourier transform value is interpolated into a two-dimensional Fourier domain, and the internal image of the composite material is reconstructed by combining the projection value and the projection angle.

8. The composite material detection method based on ultrasonic Lamb wave filtering back projection imaging according to claim 7 is characterized in that: The projection value is the line integral of the inverse of the propagation speed of the optimized Lamb wave signal in the composite material, and the flight time parameter is brought into the filtered back-projection reconstruction algorithm as the projection value.

9. An intelligent terminal, comprising a memory and a processor, wherein the memory stores a computer program, characterized in that: When the processor executes the computer program, the steps of the composite material detection method based on ultrasonic Lamb wave filtering back projection imaging as described in any one of claims 1 to 8 are implemented.

10. A computer-readable storage medium for storing computer instructions, characterized in that: When the computer instructions are executed by the processor, the steps of the composite material detection method based on ultrasonic Lamb wave filtering back projection imaging as described in any one of claims 1 to 8 are implemented.

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