A composite material detection method based on ultrasonic lamb wave filtered back-projection imaging

Abstract

The application relates to the field of nondestructive testing of aerospace composites, 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 passing through a composite material; denoising the Lamb wave signal to obtain an optimized Lamb wave signal; continuously wavelet transforming the optimized Lamb wave signal to acquire a time-of-flight parameter of the optimized Lamb wave signal in the composite material; and based on the time-of-flight parameter, combining a filtering back-projection method reconstruction algorithm to acquire an internal image of the composite material, so as to detect internal defects of the composite material. The application utilizes the Lamb wave signal, the continuous wavelet transform and the filtering back-projection method to acquire a high-quality composite material internal damage image with few artifacts without the assistance of a baseline signal, and can effectively, quickly and accurately perform nondestructive testing on a plate-shaped composite material.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of non-destructive testing and diagnosis of aerospace composites, and particularly relates to a composite material detection method based on ultrasonic Lamb wave filtered back-projection imaging. BACKGROUND

[0002] In the aerospace industry and other industries, damage occurring on key components and structures can lead to catastrophic failure without prior notice or timely discovery, endangering equipment and personal safety. Therefore, quality inspection, especially non-destructive testing and imaging inspection of the internal components, is necessary at various stages of design, production and service. Therefore, non-destructive testing technology for the internal components, especially the internal composite materials, is very important. In the prior art, non-destructive testing of the internal structure of the composite material is generally achieved by thermal imaging method, ray detection method, magnetic powder detection method and eddy current detection method. However, the detection precision and detection range of the traditional detection method are limited, and only larger damage can be detected, and the requirements for the detection environment are relatively harsh, and the detection can only be carried out periodically during the life cycle of the composite material, and real-time detection of the internal composite material cannot be achieved, which is difficult to meet the requirements of high efficiency and accuracy in actual engineering environment.

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

[0004] In view of the deficiencies of the prior art, the purpose of the present application is to provide a composite material detection method based on ultrasonic Lamb wave filtered back-projection imaging, which aims to solve the problem that the traditional composite material non-destructive testing method in the prior art cannot achieve efficient and accurate detection of the composite material.

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

[0006] obtaining a Lamb wave signal passing through the composite material;

[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 the time-of-flight parameter of the optimized Lamb wave signal in the composite material;

[0009] 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.

[0010] In an embodiment, the Lamb wave signal passing through the composite material is acquired, specifically comprising:

[0011] A circular ultrasonic sensor array is arranged at an equiangular fixed interval around the composite material;

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

[0013] The scanning is sequentially performed in the manner of the circular ultrasonic sensor array, and after all the ultrasonic sensors have acted as transmission sources, all the Lamb wave signals received by the ultrasonic sensors are acquired and sequentially arranged.

[0014] In an embodiment, the Lamb wave signal is denoised to obtain an optimized Lamb wave signal, specifically comprising:

[0015] All extreme points of the Lamb wave signal are determined;

[0016] An average envelope function of the Lamb wave signal is acquired according to the extreme points;

[0017] An intrinsic modal function of the Lamb wave signal is determined based on the average envelope function;

[0018] The Lamb wave signal is reconstructed based on the intrinsic modal function to obtain the optimized Lamb wave signal.

[0019] In an embodiment, the Lamb wave signal is reconstructed based on the intrinsic modal function to obtain the optimized Lamb wave signal, specifically comprising:

[0020] Components corresponding to noise parts in the intrinsic modal function are screened out, and the Lamb wave signal is denoised;

[0021] The denoised Lamb wave signal is mapped to a wavelet function space for decomposition;

[0022] After the denoised Lamb wave signal is decomposed for several times based on a preset threshold, an optimal reconstruction signal is obtained;

[0023] The optimized Lamb wave signal is reconstructed based on the optimal reconstruction signal.

[0024] In an embodiment, a continuous wavelet transform is performed on the optimized Lamb wave signal to acquire a time-of-flight parameter of the optimized Lamb wave signal in the composite material, specifically comprising:

[0025] determining a continuous wavelet transform coefficient of the optimized Lamb wave signal and a corresponding kernel function;

[0026] determining an energy signal of the optimized Lamb wave signal based on the continuous wavelet transform coefficient;

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

[0028] determining a time-of-flight parameter of the optimized Lamb wave signal in the composite material in combination with the energy signal, the center frequency and the bandwidth.

[0029] In an embodiment, the determining a time-of-flight parameter of the optimized Lamb wave signal in the composite material in combination with the energy signal, the center frequency and the bandwidth specifically comprises:

[0030] determining a time-of-flight of each of the Lamb wave signals corresponding to a sensing path based on the Lamb wave signals acquired by the ultrasonic sensor;

[0031] calculating a time delay caused by a scattering or a reflected wave due to a damage in combination with the energy signal, the center frequency and the bandwidth;

[0032] determining a time-of-flight parameter of the optimized Lamb wave signal in the composite material based on the time-of-flight and the time delay.

[0033] In an embodiment, the 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 an internal defect of the composite material specifically comprises:

[0034] 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 time-of-flight parameter of the optimized Lamb wave signal and the sequentially arranged Lamb wave signals;

[0035] determining a Fourier transform value on a straight line, interpolating the Fourier transform value to a two-dimensional Fourier domain based on a Fourier center slice theorem, and reconstructing an internal image of the composite material in combination with the projection value and the projection angle.

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

[0037] The second aspect of the present application discloses an intelligent terminal, comprising a memory and a processor, the memory stores a computer program, and the processor implements the steps of the composite material detection method based on ultrasonic Lamb wave filtered back-projection imaging according to any one of the above when executing the computer program.

[0038] The third aspect of the present application discloses a computer readable storage medium for storing computer instructions, which are executed by a processor to implement the steps of the composite material detection method based on ultrasonic Lamb wave filtered back-projection imaging according to any one of the above.

[0039] The present application provides a composite material detection method based on ultrasonic Lamb wave filtered back-projection imaging, comprising the steps of: transmitting a Lamb wave signal to a composite material using an ultrasonic sensor and acquiring a Lamb wave signal passing through the composite material; denoising the Lamb wave signal to obtain an optimized Lamb wave signal; performing continuous wavelet transform on the optimized Lamb wave signal to obtain the time-of-flight parameter of the optimized Lamb wave signal in the composite material; and based on the time-of-flight parameter, combining a filtered back-projection reconstruction algorithm to obtain an internal image of the composite material to detect internal defects of the composite material. The present application uses Lamb wave signals combined with continuous wavelet transform and filtered back-projection method, without the need for baseline signal assisted imaging, to obtain high-quality and few-artifact composite material internal damage images, which can effectively, quickly and accurately perform non-destructive testing on the composite material. BRIEF DESCRIPTION OF DRAWINGS

[0040] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed in the embodiments or prior art description will be briefly introduced below. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative labor.

[0041] Figure 1 Flowchart of the composite material detection method based on ultrasonic Lamb wave filtered back-projection imaging of the present application;

[0042] Figure 2 One embodiment of the sensor relative to the composite material in the composite material detection method based on ultrasonic Lamb wave filtered back-projection imaging of the present application;

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

[0044] Figure 4Another embodiment of the sensor relative to the composite material in the composite material detection method based on ultrasonic Lamb wave filtered back-projection imaging of the application;

[0045] Figure 5 The initial waveform graph of the Lamb wave signal in the composite material detection method based on ultrasonic Lamb wave filtered back-projection imaging of the application;

[0046] Figure 6 The waveform graph of the Lamb wave signal after noise reduction reconstruction in the composite material detection method based on ultrasonic Lamb wave filtered back-projection imaging of the application;

[0047] Figure 7 The schematic diagram of the intelligent terminal of the application. DETAILED DESCRIPTION

[0048] The application provides a composite material detection method based on ultrasonic Lamb wave filtered back-projection imaging, in order to make the purpose, technical scheme and effect of the application more clear and definite, the application will be further described in detail. It should be understood that the specific embodiments described herein are only used to explain the application and not to limit the application.

[0049] Non-destructive testing and diagnosis is a prerequisite for ensuring production quality, especially in the field of aerospace, real-time monitoring and fault diagnosis of key components and structures can detect and identify possible abnormalities and faults in the structure as soon as possible, through data analysis and algorithm processing, flexible control and management are realized, performance degradation and economic cost are minimized, and dangerous situations for equipment and personnel are avoided. At present, there have been a large number of related researches on the damage detection method of plate structure, the traditional methods include thermal imaging method, ray detection method, magnetic powder detection method, eddy current detection method, etc. The detection accuracy and detection range of these methods are limited, and they can only detect larger damage or metal plate structure; and the detection range of the traditional method is relatively small, which cannot be well applied to the damage detection of large range of composite material plate; in particular, for example, the thermal imaging method has high requirements on environmental temperature change, the ray detection method has special requirements on the size and transmission direction of the test piece, the magnetic powder detection method and the eddy current detection method are not suitable for composite materials and are not sensitive to internal damage of plate materials. And, most of the non-destructive testing techniques can only be carried out periodically in the engineering structure and asset life cycle, and the damage condition of the structure cannot be understood in real time and efficiently, the information about the structural integrity provided by most non-destructive testing methods is very limited. And the equipment of the traditional detection method is often large, the operation is relatively complex, the cost is high, and it is difficult to be directly used in actual engineering environment.

[0050] Compared to 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 within composite materials. This invention utilizes Lamb wave signals to scan the interior of composite materials, employs EMD (empirical mode decomposition) and wavelet transform to denoise and reconstruct the Lamb wave signals, and then uses CWT (continuous wavelet transform) to extract the time-of-flight parameters of the Lamb wave signals within the composite material under test. Finally, a Radon transform is performed using a filtered back-projection algorithm to reconstruct the internal image of the composite material. The resulting image of the internal damage of the composite material has high imaging quality, few artifacts, and requires no baseline signal for auxiliary imaging. This enables the detection, localization, evaluation, and imaging of the structural integrity and damage information of plate-like materials.

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

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

[0053] Lamb wave-based nondestructive testing (NDT) techniques are highly sensitive to damage on material surfaces and embedded structures, enabling the detection of internal damage within materials. Leveraging the characteristics of Lamb waves—high penetration, long propagation distance, low attenuation, low cost, and sensitivity to various defects—Lamb wave signals can be applied to detect various types of damage (delamination, debonding, cracks, voids, etc.). This results in high detection speed and high accuracy, enabling rapid detection and evaluation of the internal structure of composite materials.

[0054] Specifically, step S100 includes:

[0055] S110. A circular ultrasonic sensor array is arranged around the composite material at fixed intervals at equal angles.

[0056] S120. Select an ultrasonic sensor as the initial sensor. Starting from the initial sensor, each of the ultrasonic sensors sequentially acts as a source to emit Lamb wave signals into the interior of the composite material. When each ultrasonic sensor acts as a source, the remaining ultrasonic sensors receive the Lamb wave signals.

[0057] S130. Scanning is performed sequentially according to the circular ultrasonic sensor array. After all the ultrasonic sensors have acted as emission 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 uniformly and achieve a larger effective coverage area, how to set the relative position relationship between the emission source and the receiving source of the Lamb wave signal and the composite material is the key.

[0059] As shown in Figure 2 , a single-pass setting in which ultrasonic sensors are arranged in parallel on both sides of the composite material as the emission source and the receiving source respectively, wherein the gray circles are ultrasonic sensors, and the lines between the ultrasonic sensors inside the square are the projection paths of the Lamb wave signal emission. It can be seen that this setting method can only detect the composite material in a small range, and the path direction of the Lamb wave signal is single, with obvious sparse and dense differences; as shown in Figure 3 , ultrasonic sensors are arranged as the emission source and the receiving source respectively, wherein the gray circles are ultrasonic sensors, and the lines between the ultrasonic sensors inside the square are the projection paths of the Lamb wave signal emission. The double-pass setting is arranged in a rectangular shape to surround the composite material. It can be seen that this setting method is more uniform than the single-pass setting, but there are still dead angles in the four corners, and there are obvious sparse and dense differences in the path of the Lamb wave signal passing through the center position and the position close to the ultrasonic sensor; as shown in Figure 4 , an equidistant fan beam structure setting, that is, ultrasonic sensors form a circular ultrasonic sensor array around the composite material, wherein the gray circles are ultrasonic sensors, and the lines between the ultrasonic sensors inside the circular ultrasonic sensor array structure are the projection paths of the Lamb wave signal emission. It can be seen that in this setting method, the path of the Lamb wave signal is uniformly distributed and has the largest effective coverage area, basically no dead angle, and higher scanning accuracy, which is conducive to the comprehensive detection of the composite material. Therefore, preferably, the ultrasonic sensor setting method as shown in Figure 4 is adopted.

[0060] Further, when emitting the Lamb wave signal, the present application first sets an ultrasonic sensor as an initial sensor, emits ultrasonic signals as the Lamb wave signal from the initial sensor as the emission source, and the remaining ultrasonic sensors as the receiving source, and receives signals in the clockwise direction; after all ultrasonic sensors receive the Lamb wave signal, the next ultrasonic sensor in the clockwise direction of the initial sensor is set as the emission source to emit ultrasonic signals, and the remaining ultrasonic sensors including the initial sensor are set as the receiving source to receive signals in the clockwise direction. In this way, after all ultrasonic sensors sequentially emit ultrasonic signals as the emission source, 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] Further, as shown in Figure 1 , after step S100, the composite material detection method based on ultrasonic Lamb wave filtered back-projection imaging of the present application further comprises:

[0062] S200, denoising the Lamb wave signal to obtain an optimized Lamb wave signal.

[0063] The present application combines EMD and wavelet transform to remove high-frequency noise in the signal, thereby reconstructing the 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, identifies all intrinsic oscillation modes in the complex motion, and finally extracts the single component of the signal. The pure signal; and DB filtering is based on db mother wavelet basis for discrete wavelet transform and signal reconstruction, through the discrete decomposition of the signal, the low frequency part of the signal is obtained and the signal is reconstructed to filter out a large amount of high frequency noise. In this way, the optimized Lamb wave signal with high signal-to-noise ratio and low noise is obtained, which helps to more accurately determine the time of flight (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 obtained 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, obtaining an average envelope function of the Lamb wave signal according to the extreme points;

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

[0068] S240, reconstructing 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 a complex signal in the time domain and identifies all the intrinsic oscillation modes in the complex motion. In general, any signal is composed of different intrinsic mode functions (IMF). The linear or nonlinear model of each point of the extreme value and zero crossing is the same. There is only one extreme value for any continuous crossing point. Each mode should be independent of other modes. Through EMD, a complex signal can be decomposed into a finite number of IMF signals. 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 points and zero-crossing points must be equal throughout the time range of the function, or at most one difference. Second, the local IMF value is symmetric and the mean is zero. The essence of the EMD method is to decompose a complex signal into a finite number of IMFs, and the IMF component is obtained by forcing a stable signal. For a Lamb wave signal X(t), after finding all the extreme points, the average envelope function m(t) is calculated using the spline difference functions e min (t) and e max (t):

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

[0071] And the characteristic mode function IMF i (t) is obtained by subtracting the average envelope function m(t) from the Lamb wave signal X(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, i.e. 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, screening out the components corresponding to the noise part of the intrinsic mode function, and denoising 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, obtaining a best reconstruction signal after decomposing the denoised Lamb wave signal several times;

[0078] S244. Based on the optimal reconstructed signal, the optimized Lamb wave signal is reconstructed.

[0079] After determining the residual components and characteristic mode functions corresponding to high-frequency noise in the original Lamb wave signal using EMD, the corresponding components are filtered out to denoise the Lamb wave signal. Then, wavelet transform maps the EMD-denoised Lamb wave signal to the wavelet function space, decomposing the signal into two parts: a large-scale approximation and a detailed representation. The large-scale approximation part is further decomposed according to the definition to obtain a larger-scale approximation and finer detail resolution. By iterating through multiple segments and selecting the appropriate requirements for the transform part, the optimal reconstructed signal can be obtained. Optionally, wavelet transform can reduce the autocorrelation of the signal, and then threshold analysis is performed on the decomposed wavelet coefficients, adjusting the wavelet coefficients within a preset threshold to obtain the optimal reconstructed signal. Figure 5 The image shows the original Lamb wave signal, revealing a poor signal resolution. However, after using "db8" with six-level wavelet decomposition, as shown... Figure 6 As shown, the obtained Lamb wave signal is very smooth, and both low-frequency and high-frequency noise are filtered out. Thus, the final optimized Lamb wave signal has a high signal-to-noise ratio and low noise, which helps to extract the flight time of the optimized Lamb wave signal more accurately, and reduces artifacts and spikes after image reconstruction, making the damaged reconstructed image more accurate and clear.

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

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

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

[0083] Specifically, step S300 includes:

[0084] S310. Determine the continuous wavelet transform coefficients and corresponding kernel functions of the optimized Lamb wave signal;

[0085] S320. Based on the continuous wavelet transform coefficients, determine the energy signal of the optimized Lamb wave signal;

[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 time of flight parameter of the optimized Lamb wave signal in the composite material in combination with the energy signal, the center frequency and the bandwidth.

[0088] Wherein, the continuous wavelet transform (CWT) realizes scaling and translation with two parameters respectively, so the CWT form of the Lamb wave signal is:

[0089]

[0090]

[0091] Wherein, CWT (a, b) is the continuous wavelet transform coefficient, a is used for scaling, b is used for translating the mother wavelet function ψ (t), L s (t) represents the collected time sequence Lamb wave signal, * represents complex conjugate, ψ (a，b) (t) is the kernel function corresponding to the continuous wavelet transform coefficient CWT (a, b), t is time. Optionally, the amplitude and phase of the Lamb wave signal are separated by using the complex Morlet wavelet, and the instantaneous frequency and the range of time are measured, and the complex Morlet wavelet is defined as:

[0092]

[0093] Wherein, j is an imaginary number, f c represents the center frequency, f b represents the bandwidth, which 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 Morlet wavelet and constructing the energy-time envelope. For the continuous wavelet transform, the square modulus represents the energy density distribution in the time domain, which reveals the most concentrated energy corresponding to the instantaneous frequency of the low-frequency signal received by the receiver, so that the coefficient in the CWT energy signal reaches the maximum value at the instantaneous frequency, which corresponds to the center frequency of the analyzed Lamb wave signal at the current time. Wherein, the scalar form of the CWT energy concentration is:

[0095]

[0096] According to the complex Morlet wavelet analysis of the energy distribution of the Lamb wave signal, the relationship between each frequency and scale parameter can be defined as:

[0097]

[0098] wherein f is the scattered signal, f c is the center frequency of the wavelet (take 1 to get 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 of the time domain and the frequency domain.

[0099] After the continuous wavelet transform of the optimized Lamb wave signal, the time of flight 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 subsequent reconstruction of the internal image of the composite material. Optionally, the time of flight parameter is the time of flight (TOF) of the optimized Lamb wave signal in the composite material.

[0100] Specifically, step S340 comprises:

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

[0102] S342, combining the energy signal, the center frequency and the bandwidth, calculating the time delay caused by the scattering or reflection wave caused by the damage;

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

[0104] The time difference between the transmission and reception of the Lamb wave signal by different ultrasonic sensors is used to determine the time of flight of each sensing path corresponding to the Lamb wave signal. 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 when passing through the damage site, and the time of arrival of the scattered or reflected wave at the corresponding ultrasonic sensor will be longer. At this time, the time of flight is greater than the time of flight of the Lamb wave signal moving in a straight line, and the actual sensing path does not match the expected sensing path. The more accurate time of flight can be obtained by subtracting the time corresponding to the peak value from the time of the excitation signal after obtaining the Lamb wave energy information by continuous wavelet transform. In this way, the energy signal, the center frequency and the bandwidth are obtained by continuous wavelet transform, and the time delay caused by the scattering or reflection wave caused by the damage is calculated. Finally, based on the time of flight and the time delay, the time of flight parameter of the optimized Lamb wave signal in the composite material is determined to ensure that the internal image of the composite material is reconstructed to match the actual damage situation.

[0105] Further, as Figure 1As shown, after step S300, the composite material detection method based on the ultrasonic Lamb wave filtered back-projection imaging method further comprises:

[0106] S400, based on the time-of-flight parameter, combining the filtered back-projection method reconstruction algorithm, obtaining the internal image of the composite material to detect the internal defects of the composite material.

[0107] The filtered back-projection transformation is to bring the time-of-flight of the Lamb wave in the composite material as the projection value on the projection path of the detection area into the Radon transformation, and to realize the reconstruction of the image according to the Fourier central slice theorem. First, the equidistant sector beam structure is used to set a circular ultrasonic sensor array to complete the scanning of the composite material. According to the group velocity dispersion curve of the Lamb wave, the wave velocity changes 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 a straight line length, increasing the time-of-flight, i.e. the actual propagation path of the Lamb wave signal is lengthened, which is equivalent to reducing the propagation speed. Therefore, the projection value (TOF data of the Lamb wave) of the detection area on the projection path increases, resulting in 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 detected.

[0108] Specifically, step S400 comprises:

[0109] S410, based on the time-of-flight parameter of the optimized Lamb wave signal and the sequentially arranged Lamb wave signal, determining the projection value and projection angle of each optimized Lamb wave signal on the internal projection path of the composite material;

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

[0111] The Radon transformation is an integral transform function that projects a two-dimensional planar image along a certain direction to a one-dimensional profile image, and the expression is:

[0112]

[0113] Wherein, t is the projection line corresponding to xcosθ+ysinθ, and θ is the projection angle. The Radon transform is realized by the filtered back projection (FBP) method, and a better reconstructed image can be formed in a shorter calculation time. The filtered back projection method estimates the target image slice to reconstruct the image by a group of projections. The Fourier slice theorem is needed for a two-dimensional object, which provides the Fourier transform value on a straight line. If other projections are assumed to be zero and the Fourier transform value is correctly interpolated to the two-dimensional Fourier domain, the image reconstruction can be carried out to obtain the damage information inside the composite material. The filtered back projection reconstruction algorithm is expressed as:

[0114]

[0115] Wherein, the filtered projection Qθ(ω) is derived from The reconstructed image f(x, y) is estimated by different angles in N represents the number of sensors, and θ i represents the projection angle.

[0116] Therefore, after the Fourier transform value is interpolated to 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 flight time parameter is taken as the projection value into the filtered back projection reconstruction algorithm, wherein the slowness is the derivative of the propagation speed of the Lamb wave signal, and therefore the projection value is defined as:

[0117]

[0118] Wherein, s represents the transmission path, and v(s) represents the current propagation speed of the Lamb wave.

[0119] Therefore, when the Lamb wave signal passes through the defect inside the composite material, the propagation of the Lamb wave will bypass the fault, thereby causing the length of the projection path to be greater than the length of the straight line, increasing the flight time, i.e. the actual propagation path of the Lamb wave signal is lengthened, which is equivalent to reducing the propagation speed. The projection value of the detection area on the projection path increases, resulting in a defect area corresponding to the actual damage in the composite material image 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 effectively, quickly and accurately performing nondestructive testing on the plate-shaped material.

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

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

[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 method in the embodiments of the present application. The processor executes the software programs, instructions or modules stored in the memory, thereby performing functional applications and data processing, that is, implementing the method in the above embodiments.

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

[0124] In addition, the specific process of the processor loading and executing the plurality of instructions in the above storage medium and the terminal device has been described in detail in the above method, and will not be described one by one here.

[0125] In summary, the application discloses a composite material detection method based on ultrasonic Lamb wave filtering back-projection imaging, comprising the following steps: an ultrasonic sensor is used to emit a Lamb wave signal to a composite material, and a Lamb wave signal passing through the composite material is acquired; noise reduction is performed on the Lamb wave signal to obtain an optimized Lamb wave signal; continuous wavelet transform is performed on the optimized Lamb wave signal to acquire a time-of-flight parameter of the optimized Lamb wave signal in the composite material; based on the time-of-flight parameter, a filtering back-projection reconstruction algorithm is combined to acquire an internal image of the composite material, so as to detect internal defects of the composite material. The application uses a Lamb wave signal in combination with continuous wavelet transform and a filtering back-projection method, and can acquire a high-quality composite material internal damage image with few artifacts without the assistance of a baseline signal for imaging, and can effectively, quickly and accurately perform nondestructive testing on the composite material.

[0126] The above-described embodiments are only used to illustrate the technical solutions of the present application, rather than limit them; although the present application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand; the technical solutions recorded in the foregoing embodiments can be modified, or some technical features can be replaced by equivalents; and these modifications or replacements do not deviate from the spirit and scope of the corresponding technical solutions, and should be included in the protection scope of the present application.

Claims

1. A method for detecting composite materials based on ultrasonic Lamb wave filtering back projection imaging, characterized in that, Including the following steps: Acquire Lamb wave signals passing through composite materials; The Lamb wave signal is denoised to obtain an optimized Lamb wave signal; The optimized Lamb wave signal is subjected to continuous wavelet transform to obtain the energy signal corresponding to the excitation frequency in the optimized Lamb wave signal, and the flight time parameter of the optimized Lamb wave signal in the composite material is further calculated. Based on the time-of-flight parameters, combined with a filtered back-projection reconstruction algorithm, an internal image of the composite material is obtained to detect internal defects in the composite material. Acquiring the Lamb wave signal passing through the composite material specifically includes: A circular ultrasonic sensor array is arranged around the composite material at fixed intervals at equal angles. An ultrasonic sensor is selected as the initial sensor. Starting from the initial sensor, each of the ultrasonic sensors sequentially acts as a source to emit Lamb wave signals into the interior of the composite material. When each ultrasonic sensor acts as a source, the remaining ultrasonic sensors receive the Lamb wave signals. The ultrasonic sensor array is scanned sequentially. After all the ultrasonic sensors have acted as emission sources, all Lamb wave signals received by the ultrasonic sensors are acquired and arranged in sequence. The Lamb wave signal is denoised to obtain an optimized Lamb wave signal, specifically including: Determine all extreme points of the Lamb wave signal; Based on the extreme points, obtain the average envelope function of the Lamb wave signal; Based on the average envelope function, the eigenmode functions of the Lamb wave signal are determined. Based on the intrinsic mode function, the Lamb wave signal is reconstructed to obtain the optimized Lamb wave signal; Performing continuous wavelet transform on the optimized Lamb wave signal to obtain the flight time parameters of the optimized Lamb wave signal within the composite material specifically includes: Determine the continuous wavelet transform coefficients and corresponding kernel functions of the optimized Lamb wave signal; Based on the continuous wavelet transform coefficients, the energy signal of the optimized Lamb wave signal is determined; Based on the kernel function, the amplitude and phase of the optimized Lamb wave signal are separated, and the center frequency and bandwidth of the optimized Lamb wave signal are measured. By combining the energy signal, the center frequency, and the bandwidth, the flight time parameters of the optimized Lamb wave signal within the composite material are determined.

2. The composite material detection method based on ultrasonic Lamb wave filtering back projection imaging according to claim 1, characterized in that, Based on the intrinsic mode function, the Lamb wave signal is reconstructed to obtain the optimized Lamb wave signal, specifically including: The Lamb wave signal is denoised by filtering out the noise components in the intrinsic mode function. The denoised Lamb wave signal is mapped to the wavelet function space and decomposed. Based on a preset threshold, the noise-reduced Lamb wave signal is decomposed several times to obtain the optimal reconstructed signal. Based on the optimal reconstructed signal, the optimized Lamb wave signal is reconstructed.

3. The composite material detection method based on ultrasonic Lamb wave filtering back projection imaging according to claim 1, characterized in that, The determination of the optimized Lamb wave signal's time-of-flight parameters within the composite material, based on the energy signal, the center frequency, and the bandwidth, specifically includes: Based on the Lamb wave signals acquired by the ultrasonic sensor, the flight time of the sensing path corresponding to each Lamb wave signal is determined. By combining the energy signal, the center frequency, and the bandwidth, the time delay caused by the scattered or reflected waves due to the damage is calculated; Based on the flight time and the time delay, the flight time parameters of the optimized Lamb wave signal within the composite material are determined.

4. The composite material detection method based on ultrasonic Lamb wave filtering back projection imaging according to claim 1, characterized in that, Based on the time-of-flight parameters and a filtered back-projection reconstruction algorithm, an internal image of the composite material is obtained to detect internal defects in the composite material, specifically including: Based on the flight time parameters of the optimized Lamb wave signals and the sequentially arranged Lamb wave signals, the projection value and projection angle of each optimized Lamb wave signal on the internal projection path of the composite material are determined. 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 the two-dimensional Fourier domain. Combined with the projection value and the projection angle, the internal image of the composite material is reconstructed.

5. The composite material detection method based on ultrasonic Lamb wave filtering back projection imaging according to claim 4, characterized in that, The projection value is the line integral of the reciprocal of the propagation speed of the optimized Lamb wave signal in the composite material, and the time-of-flight parameter is used as the projection value in the filtered back-projection reconstruction algorithm.

6. A smart terminal, comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the composite material detection method based on ultrasonic Lamb wave filter back projection imaging as described in any one of claims 1-5.

7. A computer-readable storage medium for storing computer instructions, characterized in that, When the computer instructions are executed by the processor, they implement the steps of the composite material detection method based on ultrasonic Lamb wave filter back projection imaging as described in any one of claims 1-5.

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