Composite material damage imaging method based on time-space cross-correlation of ultrasonic guided wave field

Abstract

The invention relates to the technical field of nondestructive testing, and provides a composite material damage imaging method based on time-space cross correlation of an ultrasonic guided wave field, which comprises the following steps: S1, acquiring a wave field signal of a detected plate; s2, narrow-band signal extraction is carried out on the wave field signal; s3, filtering the wave field signal after the narrow-band signal extraction; s4, moving the wave field signals to obtain wave field signal cross-correlation characteristics; and S5, obtaining a damage imaging result by using a convex hull algorithm. According to the method, the difference coefficient between the wave field signals is creatively extracted to serve as a damage positioning basis, a new thought is provided for a feature extraction algorithm based on the time-frequency domain, automatic judgment of composite material layering damage positioning is achieved, and the method is sensitive to damage to the surface and the interior of a structure.

Description

Technical Field

[0001] The invention relates to the technical field of nondestructive testing, and in particular to a composite material damage imaging method based on time-space cross-correlation of ultrasonic guided wave fields. Background Art

[0002] Composite materials are a new type of material that is obtained by fusing several types of materials such as metals, polymers, and inorganic non-metals in different ways. They not only inherit the main functions of the raw materials, but also have incomparable excellent properties of the raw materials, such as light weight, corrosion resistance, and fatigue resistance. Advanced composite materials meet the needs of the aviation field for lightweight, high reliability, and long life. Therefore, they are widely used in the aviation field, and their usage has gradually become an important symbol of the advancement of aircraft. However, during the use and manufacturing process of composite materials, damages such as delamination, scratches, cracks, pitting, pits, and degumming will occur. The structural damage is highly concealed and difficult to detect. In order to ensure the safe use of the equipment, it is necessary to conduct quality inspections and structural safety monitoring of composite parts through various means to promptly detect defects in equipment operation.

[0003] Nondestructive evaluation (NDE) technology aims to evaluate the quality of materials by measuring a certain performance parameter without destroying the composite material structure. Guided waves are a type of ultrasonic wave. They are waves generated by the boundary of the medium and propagate along the waveguide structure. Guided waves can propagate in different waveguide structures, such as plates, rods, pipes, and multilayer structures. Among them, guided waves propagating in plates are called Lamb waves. When guided waves propagate in the medium, damage and defects will change the propagation mechanism of guided wave signals. Guided wave detection technology is based on this principle to achieve damage detection. In the past decade, with the development of scanning laser Doppler vibrometry (SLVD) technology, algorithms for measuring the full wavefield of elastic waves in thin-walled structures and locating damage have begun to emerge, providing many new solutions for intuitively displaying damage morphology. Compared with other damage detection technologies such as ultrasonic testing and acoustic emission testing, the advantages of SLVD technology are non-contact measurement and high measurement accuracy. It avoids problems such as friction, heat transfer or mechanical interference that may be caused by contact, thereby ensuring the accuracy and reliability of measurement. It can achieve extremely high displacement and velocity resolution and reach an amplitude resolution of picometers, providing strong support for the precise analysis of guided wave full-wavefield signals.

[0004] The information contained in the full wave field signal collected by the vibrometer is very complex. It is difficult to intuitively determine the information from the damage only from the evolution of the time domain wave field. Therefore, it is necessary to build a damage identification algorithm to extract damage features. In signal analysis, cross-correlation measures the similarity between two groups of signals. During the data acquisition process, if there is no structural change between two adjacent scanning points, the signals of these two points will have a high similarity due to the small scanning step size. On the contrary, the signal characteristics of the two scanning points at the damage boundary will have a large difference due to the change in structure. Based on this feature, the location of the damage and the expression of the damage boundary can be achieved. Summary of the invention

[0005] The purpose of the present invention is to provide a detection method that can realize rapid assessment of composite material delamination damage in a complex field working environment, which can more accurately obtain the quality characteristics of the composite material structure to be tested, while greatly reducing the complexity of the test process, and can conveniently and quickly realize defect detection of the test piece.

[0006] The present invention proposes a composite material damage imaging method based on the temporal and spatial cross-correlation of ultrasonic guided wave fields, which comprises the following steps:

[0007] Step 1: Obtain the wave field signal W(x,y,n) of the composite plate under test;

[0008] The guided wave propagates in the composite plate under test, and the scanning laser Doppler vibrometer obtains the wave field signal W(x, y, n) of the composite plate under test, where x = 0, 1, 2, ..., M-1, y = 0, 1, 2, ..., N-1, respectively representing the coordinates of two directions in the two-dimensional coordinate system, M and N are the image pixel values ​​of the row and column respectively, n is the signal length, n = 1, 2, ..., T, and M, N, T are all positive integers;

[0009] Step 2: Extract narrowband signals from wave field signals;

[0010] Firstly, the time domain expression of wave field signal, the time domain expression of broadband excitation signal and the time domain expression of narrowband excitation signal are respectively obtained by Fourier transform to obtain the frequency domain expression of wave field signal, the frequency domain expression of broadband excitation signal and the frequency domain expression of narrowband excitation signal;

[0011] Then, the frequency domain expression of the wavefield signal after narrowband signal extraction is obtained using formula (1). The specific formula is as follows:

[0012]

[0013] Where ω is the frequency, R b (ω) is the frequency domain expression of the wavefield signal after narrowband signal extraction, R c (ω) is the frequency expression of the wave field signal, S c(ω) is the frequency domain expression of broadband excitation signal, S b (ω) is the frequency domain expression of the narrowband excitation signal;

[0014] Finally, the frequency domain expression of the wave field signal after narrowband signal extraction is R b (ω) The time domain expression W of the wave field signal after narrowband signal extraction is obtained through inverse Fourier transform b (x,y,n).

[0015] Step 3: Filtering the wave field signal after narrowband signal extraction;

[0016] First, the time domain expression of the wave field signal after narrowband signal extraction is expressed in W b The slice on the (x, y, n) time axis is divided into T parts, then W b (x,y,n) is converted to two-dimensional f n (x, y), n = 1, 2, ..., T;

[0017] Then, the sliced ​​wave field signal f n (x,y) is transformed from the spatial domain to the wave number domain F n (u,v), by F n f represented by (u,v) n The two-dimensional discrete Fourier transform of (x,y) is given by:

[0018]

[0019] Among them, u and v are two variables in the frequency domain, corresponding to the frequency components of the two spatial dimensions x and y of the signal respectively;

[0020] Secondly, the frequency wavenumber domain filtering algorithm is used to selectively suppress the wavenumber component of the reflected wave in the frequency wavenumber domain;

[0021] Finally, the filtered spectrum is inverse Fourier transformed to convert the signal back to the time domain. The inverse discrete Fourier transform is in the form of:

[0022]

[0023] Finally, by filtering the wave field signal of each time slice f n The data of (x, y) are accumulated to obtain the filtered wave field signal W c (x,y,n);

[0024] Step 4: Move the wave field signal to obtain the cross-correlation characteristics of the wave field signal;

[0025] Select a wavefield signal W from multiple filtered wavefield signals c(x, y, n), moving the wave field signal in different directions to solve the cross-correlation characteristics of the signal between adjacent scanning points in different directions;

[0026] When the x and y values ​​are determined, according to the filtered wave field signal W c (x, y, n) to obtain a single scanning point signal f(t), the cross-correlation feature solution formula of adjacent scanning point signals f(t) and g(t) is as follows:

[0027]

[0028] Wherein, f(t) and g(t) are both single scan point signals based on time t, τ is the integral variable; f(t) and g(t) are adjacent scan point signals;

[0029] Step 5: Use the convex hull algorithm to obtain the damage imaging results;

[0030] The results of cross-correlation solutions at different center frequencies and in different directions are superimposed, and the convex envelope of discrete edge points is calculated using the convex hull algorithm to obtain the damage range of the tested composite plate.

[0031] Preferably, in step 1, the waveguide is generated in the following manner:

[0032] The composite plate is fixed on the bracket as the composite plate to be tested. A reflective film is pasted on the surface of the composite plate to enhance the energy reflected to the scanning head. The PZT piezoelectric piece is pasted on the upper left corner of the reflective film. The signal generator generates a broadband frequency modulation signal, which is then amplified by the power amplifier to obtain a broadband excitation signal. The broadband excitation signal is transmitted to the PZT piezoelectric piece, and the PZT piezoelectric piece converts the electrical signal into a mechanical signal to cause the composite plate to vibrate and generate guided waves.

[0033] Preferably, in step 2, the broadband excitation signal is a broadband chirp signal, and the frequency band of the broadband chirp signal is 5-500kHz.

[0034] Preferably, in step 2, the narrowband excitation signal is a sinusoidal signal modulated by a Hanning window, and the time domain expression of the narrowband excitation signal is as follows:

[0035]

[0036] In the formula, f c is the center frequency of the sinusoidal signal modulated by the Hanning window.

[0037] Preferably, in step three, the frequency wavenumber domain filtering algorithm preferably adopts a filtering method of setting the reflected wave to zero.

[0038] Preferably, in step 4, the wave field signal is moved in different directions, preferably in four directions of 0°, 45°, 90° and 135°.

[0039] Preferably, the convex hull algorithm is used in step 5 to calculate the convex hull of discrete edge points as follows:

[0040] Let S = {p1, p2, ..., p s} is a set of points in a plane or space, S is a point set, p j is a point in S. The convex hull is defined as the set of convex combinations of all these points. The convex combination of points in the point set S refers to points that satisfy the following form:

[0041]

[0042] Among them, λ j is the coefficient, λ j ≥0, and satisfies x is the convex combination of points in the point set S;

[0043] For s edge points, the convex hull Conv(S) is given by:

[0044]

[0045] The damage range of the composite plate is obtained according to formula (6).

[0046] Compared with the prior art, the present invention has the following beneficial effects:

[0047] 1. The present invention takes guided wave detection as its theoretical basis, and has the advantages of rich modal information, sensitivity to damage on the surface and inside of the structure, and flexible guided wave generation.

[0048] 2. The present invention avoids the limitation of searching for damage features by manual comparison, gets rid of the dependence on engineering experience, and can realize the automatic identification of composite material delamination damage location.

[0049] 3. The present invention innovatively extracts the difference coefficient between wave field signals as the basis for damage location, providing a new idea for the feature extraction algorithm based on the time-frequency domain. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] Figure 1 A test system for realizing a composite material damage imaging method based on time-space cross-correlation of ultrasonic guided wave fields according to the present invention;

[0051] Figure 2 It is a schematic diagram of the process of the composite material damage imaging method based on the time-space cross-correlation of the ultrasonic guided wave field of the present invention;

[0052] Figure 3AIt is an image of the one-dimensional wave field in the frequency wave number domain of the present invention without removing the reflected wave front;

[0053] Figure 3B It is an image after removing the reflected wave from the one-dimensional wave field in the frequency wave number domain of the present invention;

[0054] Figure 4A It is a result diagram of the cross-correlation characteristics of the wave field signal after filtering and the wave field signal obtained after moving in the 0° direction according to the present invention;

[0055] Figure 4B This is a cross-correlation characteristic result diagram of the wave field signal after filtering and the wave field signal obtained after moving in the 45° direction according to the present invention;

[0056] Figure 4C This is a cross-correlation characteristic result diagram of the wave field signal after filtering and the wave field signal obtained after moving in a 90° direction according to the present invention;

[0057] Figure 5 The damage imaging result diagram is obtained according to the convex hull algorithm of the present invention;

[0058] Figure 6 It is a schematic diagram of generating the wave field signal of the present invention. DETAILED DESCRIPTION

[0059] In order to better understand the technical solution of the present invention, the specific implementation of the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. The same reference numerals in the accompanying drawings represent elements with the same or similar functions. Although various aspects of the embodiments are shown in the accompanying drawings, the drawings need not be drawn to scale unless otherwise specified.

[0060] like Figure 2 As shown, a composite material damage imaging method based on the temporal and spatial cross-correlation of ultrasonic guided wave fields specifically includes the following steps:

[0061] Step 1: Obtain the wave field signal W(x,y,n) of the plate under test.

[0062] Taking the actual test system as an example, the entire test system includes a composite plate 1, a signal generator 2, a power amplifier 3 and a scanning laser Doppler vibrometer 4. Figure 1As shown. Composite plate 1 is fixed on the bracket as the composite plate to be tested. In this embodiment, composite plate 1 has been prefabricated with delamination damage. A reflective film is pasted on the surface of composite plate 1 to enhance the energy reflected to the scanning head. PZT (lead zirconate titanate) piezoelectric sheet is pasted on the upper left corner of the reflective film. Signal generator 2 generates a broadband frequency modulation signal with a frequency range of 5-500KHz, which is then amplified by power amplifier 3 to obtain a broadband excitation signal. The broadband excitation signal is transmitted to the PZT piezoelectric sheet, which converts the electrical signal into a mechanical signal to cause the plate to vibrate and generate guided waves. When the guided wave propagates to the scanning area, the scanning laser Doppler vibrometer 4 obtains the wave field signal W(x, y, n) of the composite plate 1 under test, where x = 0, 1, 2, ..., M-1, y = 0, 1, 2, ..., N-1, respectively representing the coordinates of the two directions in the two-dimensional coordinate system, M and N are the image pixel values ​​of the row and column respectively, n is the signal length, n = 1, 2, ..., T, and M, N, T are all positive integers. At this time, the wave field signal W(x, y, n) is the signal time domain expression, and the generation of the wave field signal is as follows: Figure 6 shown.

[0063] Step 2: Extract narrowband signals from wavefield signals.

[0064] The signal generator uses a broadband chirp signal as a broadband frequency modulation signal. The frequency band of the broadband chirp signal is 5-500kHz, and the signal components are complex, which leads to complex components of the obtained wave field signal. Therefore, in order to improve the efficiency of damage feature recognition, it is necessary to use a narrowband excitation signal to extract the narrowband signal of the wave field signal obtained in step one.

[0065] Firstly, the time domain expression of wavefield signal, the time domain expression of broadband excitation signal and the time domain expression of narrowband excitation signal are respectively obtained by Fourier transform to obtain the frequency domain expression of wavefield signal, the frequency domain expression of broadband excitation signal and the frequency domain expression of narrowband excitation signal.

[0066] Then, the frequency domain expression of the wavefield signal after narrowband signal extraction is obtained using formula (1). The specific formula is as follows:

[0067]

[0068] Where ω is the frequency, R b (ω) is the frequency domain expression of the wavefield signal after narrowband signal extraction, R c (ω) is the frequency expression of the wave field signal, S c (ω) is the frequency domain expression of broadband excitation signal, S b (ω) is the frequency domain expression of the narrowband excitation signal. The narrowband excitation signal is a sinusoidal signal modulated by the Hanning window. The time domain expression of the narrowband excitation signal is as follows:

[0069]

[0070] In the formula, f c is the center frequency of the sinusoidal signal modulated by the Hanning window.

[0071] Finally, the frequency domain expression of the wave field signal after narrowband signal extraction is R b (ω) The time domain expression W of the wave field signal after narrowband signal extraction is obtained through inverse Fourier transform b (x,y,n).

[0072] Step 3: Filter the wavefield signal after narrowband signal extraction.

[0073] In order to remove the influence of boundary reflection on the similarity of wavefield signals and only retain the differences in wavefield signals caused by structural changes, it is necessary to filter the wavefield signals, and the filtering process is implemented in the frequency and wavenumber domain.

[0074] First, the time domain expression of the wave field signal after narrowband signal extraction is expressed in W b The slice on the (x, y, n) time axis is divided into T parts, then W b (x,y,n) is converted to two-dimensional f n (x,y)(n=1,2,…,T).

[0075] Then, the wave field signal is transformed from the spatial domain to the wave number domain through the two-dimensional Fourier transform. n f represented by (u,v) n The two-dimensional discrete Fourier transform of (x,y) is given by:

[0076]

[0077] Among them, u and v are two variables in the frequency domain, corresponding to the frequency components of the two spatial dimensions x and y of the signal respectively.

[0078] Secondly, the wave number component of the reflected wave is selectively suppressed in the frequency wave number domain. When a signal is reflected in space, its wave number changes. In the frequency wave number domain, the wave number of the reflected wave is usually expressed as a negative wave number, so its position corresponds to quadrant 2 or 4 in the wave number domain. In this embodiment, the reflected wave is filtered by setting it to zero. Finally, the filtered spectrum is subjected to an inverse Fourier transform to convert the signal back to the time domain. The form of the inverse discrete Fourier transform is:

[0079]

[0080] Finally, by filtering each time slice f n The data of (x, y) (n = 1, 2, ..., T) are accumulated to obtain the filtered wave field signal Wc (x,y,n).

[0081] Because in step 2, narrowband excitation signals with different center frequencies are used to extract narrowband signals from wavefield signals, this step can obtain multiple filtered wavefield signals with different center frequencies. When the center frequency of the narrowband excitation signal is f c When , we get the filtered wave field signal W c (x,y,n).

[0082] For a more intuitive explanation, Figure 3A is the image of the one-dimensional wave field in the frequency-wavenumber domain without removing the reflected wavefront, Figure 3B This is the image after removing the reflected wave from the one-dimensional wave field in the frequency wavenumber domain. By comparison, it can be intuitively found that the imaging quality is improved.

[0083] Step 4: Move the wavefield signal to obtain the cross-correlation characteristics of the wavefield signal.

[0084] Select a wavefield signal W from multiple filtered wavefield signals c (x, y, n), move the wave field signal in multiple directions, including 0° (right), 45° (upper right), 90° (upper), and 135° (upper left), so as to solve the cross-correlation characteristics of the signal between adjacent scanning points in different directions.

[0085] When the x and y values ​​are determined, according to the filtered wave field signal W c (x, y, n) to obtain a single scanning point signal f(t), the cross-correlation feature solution formula of adjacent scanning point signals f(t) and g(t) is as follows:

[0086]

[0087] Wherein, f(t) and g(t) are both single scanning point signals based on time t, τ is the independent variable; f(t) and g(t) are adjacent scanning point signals.

[0088] Adjacent scanning point signals refer to the scanning point signals of the current wavefield signal and the scanning point signals of the wavefield signal after the movement. For example, the current wavefield signal is the filtered wavefield signal W obtained in step 3. c (x, y, n), when moving towards 0°, the wave field signal W is obtained c 0 (x,y,n), the filtered wavefield signal W c (x, y, n) and the wave field signal W after the shift c 0 (x, y, n) are adjacent wave field signals, and their corresponding scanning point signals are adjacent scanning point signals; then the wave field signal W cAfter (x, y, n) moves in the 90° direction, the wave field signal W c (x,y,n) and wave field signal W c 90 (x, y, n) is called an adjacent wave field signal. If it is a wave field signal W c 0 (x, y, n) moves in the 90° direction, then the wave field signal W c 0 (x,y,n) and wave field signal W c 90 (x, y, n) are called adjacent wave field signals, and their corresponding scanning point signals are adjacent scanning point signals.

[0089] In this embodiment, the filtered wave field signal W c The results of solving the wave field movement cross-correlation characteristics between adjacent scanning points (x, y, n) in three different directions of 0° (right shift), 45° (upper right), and 90° (upper) are as follows Figures 4A-4C As shown, Figure 4A is the wave field signal W after filtering c The cross-correlation characteristic result diagram of the wave field signal obtained after (x, y, n) moves in the 0° direction; Figure 4B is the wave field signal W after filtering c (x, y, n) and the wave field signal cross-correlation characteristic result diagram obtained after moving in the 45° direction; Figure 4C is the wave field signal W after filtering c The cross-correlation characteristic result diagram of the wave field signal obtained after (x, y, n) moves in the 90° direction.

[0090] Step 5: Use the convex hull algorithm to obtain the damage imaging results.

[0091] The results of cross-correlation solutions at different center frequencies and in different directions are superimposed, and the convex hull algorithm is introduced to calculate the convex envelope of discrete edge points. Let S = {p1, p2, ..., p s} is a set of points in a plane or space, S is a point set, p j is a point in S, and the convex hull can be defined as the set of convex combinations of all these points. A convex combination of points in the point set S is a point that satisfies the following form:

[0092]

[0093] Among them, λ j is the coefficient, λ j ≥0, and satisfies x is the convex combination of points in the point set S obtained.

[0094] For s edge points, the convex hull Conv(S) can be given by the following formula:

[0095]

[0096] The damage range is obtained according to formula (6).

[0097] Figure 5 This is a damage imaging result diagram obtained according to the convex hull algorithm in this embodiment. It can be seen that the damaged part is marked by a red frame line.

[0098] The present invention uses the full wave field signal collected by the scanning laser Doppler vibrometer as the analysis basis, explores the relationship between the guided wave signal and the damage in the composite material, and introduces the characteristic changes of the guided wave signal at the damage boundary. It aims to extract the signal characteristics of the scanning points in the wave field, explore the signal characteristic changes of the adjacent points of the wave field, and realize the damage location and damage boundary identification of the prefabricated damaged composite material plate.

[0099] Finally, it should be noted that the above-described embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the present invention. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some or all of the technical features thereof may be replaced by equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A composite material damage imaging method based on the temporal and spatial cross-correlation of ultrasonic guided wave fields, characterized in that: It includes the following steps: Step 1: Obtain the wave field signal W(x,y,n) of the composite plate under test; The guided wave propagates in the composite plate under test, and the scanning laser Doppler vibrometer obtains the wave field signal W(x, y, n) of the composite plate under test, where x = 0, 1, 2, ..., M-1, y = 0, 1, 2, ..., N-1, respectively representing the coordinates of two directions in the two-dimensional coordinate system, M and N are the image pixel values ​​of the row and column respectively, n is the signal length, n = 1, 2, ..., T, and M, N, T are all positive integers; Step 2: Extract narrowband signals from wave field signals; Firstly, the time domain expression of wave field signal, the time domain expression of broadband excitation signal and the time domain expression of narrowband excitation signal are respectively obtained by Fourier transform to obtain the frequency domain expression of wave field signal, the frequency domain expression of broadband excitation signal and the frequency domain expression of narrowband excitation signal; Then, the frequency domain expression of the wavefield signal after narrowband signal extraction is obtained using formula (1). The specific formula is as follows: Where ω is the frequency, R b (ω) is the frequency domain expression of the wavefield signal after narrowband signal extraction, R c (ω) is the frequency expression of the wave field signal, S c (ω) is the frequency domain expression of broadband excitation signal, S b (ω) is the frequency domain expression of the narrowband excitation signal; Finally, the frequency domain expression of the wave field signal after narrowband signal extraction is R b (ω) The time domain expression W of the wave field signal after narrowband signal extraction is obtained through inverse Fourier transform b (x,y,n); Step 3: Filtering the wave field signal after narrowband signal extraction; First, the time domain expression of the wave field signal after narrowband signal extraction is expressed in W b The slice on the (x, y, n) time axis is divided into T parts, then W b (x,y,n) is converted to two-dimensional f n (x, y), n = 1, 2, ..., T; Then, the sliced ​​wave field signal f is transformed into n (x,y) is transformed from the spatial domain to the wave number domain F n (u,v), by F n f represented by (u,v) n The two-dimensional discrete Fourier transform of (x,y) is given by: Among them, u and v are two variables in the frequency domain, corresponding to the frequency components of the two spatial dimensions x and y of the signal respectively; Secondly, the frequency wavenumber domain filtering algorithm is used to selectively suppress the wavenumber component of the reflected wave in the frequency wavenumber domain; Finally, the filtered spectrum is inverse Fourier transformed to convert the signal back to the time domain. The inverse discrete Fourier transform is in the form of: Finally, by filtering the wave field signal of each time slice f n The data of (x, y) are accumulated to obtain the filtered wave field signal W c (x,y,n); Step 4: Move the wave field signal to obtain the cross-correlation characteristics of the wave field signal; Select a wavefield signal W from multiple filtered wavefield signals c (x, y, n), moving the wave field signal in different directions to solve the cross-correlation characteristics of the signal between adjacent scanning points in different directions; When the x and y values ​​are determined, according to the filtered wave field signal W c (x, y, n) to obtain a single scanning point signal f(t), the cross-correlation feature solution formula of adjacent scanning point signals f(t) and g(t) is as follows: Wherein, f(t) and g(t) are both single scan point signals based on time t, τ is the integral variable; f(t) and g(t) are adjacent scan point signals; Step 5: Use the convex hull algorithm to obtain the damage imaging results; The results of cross-correlation solutions at different center frequencies and in different directions are superimposed, and the convex envelope of discrete edge points is calculated using the convex hull algorithm to obtain the damage range of the tested composite plate.

2. The composite material damage imaging method based on the temporal and spatial cross-correlation of ultrasonic guided wave fields according to claim 1 is characterized in that: In the step 1, the waveguide is generated in the following manner: The composite plate is fixed on the bracket as the composite plate to be tested. A reflective film is pasted on the surface of the composite plate to enhance the energy reflected to the scanning head. The PZT piezoelectric piece is pasted on the upper left corner of the reflective film. The signal generator generates a broadband frequency modulation signal, which is then amplified by the power amplifier to obtain a broadband excitation signal. The broadband excitation signal is transmitted to the PZT piezoelectric piece, and the PZT piezoelectric piece converts the electrical signal into a mechanical signal to cause the composite plate to vibrate and generate guided waves.

3. The composite material damage imaging method based on the temporal and spatial cross-correlation of ultrasonic guided wave fields according to claim 1 is characterized in that: In the step 2, The broadband excitation signal is a broadband chirp signal, and the frequency band of the broadband chirp signal is 5-500kHz.

4. The composite material damage imaging method based on the temporal and spatial cross-correlation of ultrasonic guided wave fields according to claim 1 is characterized in that: In the step 2, The narrowband excitation signal is a sinusoidal signal modulated by the Hanning window. The time domain expression of the narrowband excitation signal is as follows: In the formula, f c is the center frequency of the sinusoidal signal modulated by the Hanning window.

5. The composite material damage imaging method based on the temporal and spatial cross-correlation of ultrasonic guided wave fields according to claim 1, characterized in that: In the step three, The frequency wavenumber domain filtering algorithm preferably adopts a filtering method of setting the reflected wave to zero.

6. The composite material damage imaging method based on the temporal and spatial cross-correlation of ultrasonic guided wave fields according to claim 1, characterized in that: In the step 4, The wavefield signal is moved in different directions, preferably in four directions of 0°, 45°, 90°, and 135°.

7. The composite material damage imaging method based on the temporal and spatial cross-correlation of ultrasonic guided wave fields according to claim 1 is characterized in that: In step 5, the convex hull algorithm is used to calculate the convex hull of discrete edge points, specifically: Let S = {p1, p2, ..., p s } is a set of points in a plane or space, S is a point set, p j is a point in S. The convex hull is defined as the set of convex combinations of all these points. The convex combination of points in the point set S refers to points that satisfy the following form: Among them, λ j is the coefficient, λ j ≥0, and satisfies x is the convex combination of points in the point set S; For s edge points, the convex hull Conv(S) is given by: The damage range of the composite plate is obtained according to formula (6).

Images