Method for extracting wave number in a variable thickness structure

Abstract

This invention relates to a method for extracting guided wavenumbers in variable thickness structures, belonging to the field of nondestructive testing technology. It utilizes an excitation signal to generate guided wave signals on the surface of the object under test. Based on a set window function and a set window length, the two-dimensional wavefield signal obtained by sampling the guided wave signal is divided into multiple local wavefield signals. A short-space Fourier transform is then performed on each local wavefield signal to obtain the amplitude-frequency-wavenumber array corresponding to each local space. A frequency range is then selected by summing the amplitude-frequency-wavenumber arrays of each local space, using the center frequency of the excitation signal as the midpoint. The weighted average wavenumber of each frequency point within the selected frequency range is calculated using the amplitude corresponding to the wavenumber sequence at each frequency point as the weight. The mean of the sum of the weighted average wavenumbers at each frequency point is then used as the wavenumber corresponding to the center position of each local signal space, and these values ​​are sequentially spliced ​​to obtain the wavenumber curve of the guided wave signal. This method solves the problem in existing technologies where the obtained guided wavenumbers cannot accurately reflect the thickness changes of variable thickness structures.

Description

Technical Field

[0001] This invention relates to the field of nondestructive testing technology, and in particular to a method for extracting guided wavenumbers in structures with varying thickness. Background Technology

[0002] For potential damage to a workpiece structure, a common approach is to place an excitation source on the workpiece and perform non-destructive testing on the guided waves generated by the vibration of the excitation source on the workpiece surface. Wave number is an inherent property of guided waves and is related to the excitation frequency, structural material, and geometric dimensions. In particular, it exhibits a certain non-linear transformation relationship with the structural thickness. Therefore, changes in wave number reflect changes in structural dimensions to some extent. The industry commonly uses the relationship between wave number and workpiece structural thickness for non-destructive testing of structural damage.

[0003] However, in the existing technology, there is no clear derivation relationship between the plane slope change angle of the variable thickness structure and the variable thickness dispersion for the plane stress change of the variable thickness structure. This makes it impossible to obtain a quantitative relationship with the thickness change of the variable thickness structure through the waveguide characteristic parameters. Therefore, the existing technology generally integrates the wave values ​​corresponding to the single-point frequency-thickness product extracted from the dispersion curves of multiple equal-thickness structures to approximate the variable thickness structure. However, the wave number obtained by this method cannot accurately reflect the continuity of the thickness change of the variable thickness structure, and the calculation process is complicated and the amount of calculation is huge. Summary of the Invention

[0004] Based on the above analysis, the embodiments of the present invention aim to provide a method for extracting guided wavenumbers in variable thickness structures, so as to solve the problem that the guided wavenumbers obtained in the prior art cannot accurately reflect the thickness changes of the variable thickness structure.

[0005] On one hand, embodiments of the present invention provide a method for extracting guided wavenumbers in a variable thickness structure, the method specifically including:

[0006] The method specifically includes:

[0007] An excitation signal is applied to induce guided wave signals in the object under test;

[0008] A two-dimensional wave field signal is obtained by sampling the guided wave signal on the surface of the object under test;

[0009] The two-dimensional wave field signal is divided into multiple local wave field signals based on a set window function and a set window length;

[0010] The amplitude-frequency-wavenumber array corresponding to each local wavefield signal is obtained by performing a short-space Fourier transform on each local wavefield signal.

[0011] Using the center frequency of the excitation signal as the midpoint, select frequency ranges in each local spatial amplitude-frequency-wavenumber array, and calculate the weighted average wavenumber of each frequency point within the selected frequency range in each local space.

[0012] The mean of the sum of the weighted average wavenumbers of each frequency point within the selected frequency range of each local space is taken as the wavenumber corresponding to each local signal space.

[0013] The wavenumber curve of the guided wave signal is obtained by sequentially splicing the corresponding wavenumbers of each local space.

[0014] Based on a further improvement of the above method, the excitation signal adopts an A0 mode narrowband signal.

[0015] Based on a further improvement of the above method, the step of sampling the guided wave signal on the surface of the object under test to obtain a two-dimensional wave field signal specifically includes: setting multiple sampling positions at equal intervals along the one-dimensional propagation direction on the surface of the object under test, and performing multiple time-domain samplings on each sampling position to obtain the time-domain signals at all sampling positions to form the two-dimensional wave field signal.

[0016] Based on a further improvement of the above method, the two-dimensional wave field signal is specifically represented by the following expression:

[0017] In the formula,

[0018] k(f) is the wavenumber at the sampling point. Let A(f) be the initial phase of the guided wave signal, f be the sampling point amplitude, f be the sampling point frequency, u(x,t) be the two-dimensional wave field signal, t be the sampling point time, (x,t) be the sampling point position, and i be the imaginary part of the signal phase.

[0019] Based on a further improvement of the above method, the set window length is not less than twice the maximum wavelength of the guided wave signal.

[0020] Based on a further improvement of the above method, the short-space Fourier transform is specifically expressed as follows:

[0021] S(x n ,k,f)=∫∫u(x,t)W * (xx n ,t)exp[-i(ft-kx)]dxdt, where,

[0022] x n For window spatial location index, W(xx) n ,t) is the set window function, S(x) n, k, f) is the amplitude-frequency-wavenumber array obtained after the short-space Fourier transform, * denotes complex conjugate, dx is the spatial position integral within the window, dt is the time integral within the window, and n is the window number.

[0023] Based on a further improvement of the above method, the weighted average wavenumber of each frequency point within the selected frequency range of each local space is calculated through the following steps, the specific steps of which include:

[0024] S71: For each amplitude-frequency-wavenumber array corresponding to all sampling positions in each local space, calculate the product of each amplitude and the corresponding wavenumber at each frequency point;

[0025] S72: Sum the products of each amplitude and its corresponding wavenumber at the same frequency point to obtain the first summation result; sum the products of each amplitude at the same frequency point to obtain the second summation result;

[0026] S73: Divide the first summation result corresponding to each frequency point by the second summation result to obtain the weighted average wavenumber of each frequency point.

[0027] Based on a further improvement of the above method, the mean value of the weighted average wavenumber of each frequency point within the selected frequency range is calculated by dividing the sum of the weighted average wavenumbers of each frequency point within the selected frequency range by the number of frequency points within the selected frequency range.

[0028] On the other hand, embodiments of the present invention provide a device for extracting guided wavenumbers in a variable thickness structure. The device includes an excitation source, a scanning module, a processing module, and a display module.

[0029] The excitation source is disposed on the object under test and is used to generate an A0 mode narrowband excitation signal that causes the object under test to generate a corresponding guided wave signal.

[0030] The scanning module is used to sample the guided wave signal on the surface of the object under test to obtain a two-dimensional wave field signal and output it.

[0031] The processing module is used to divide the two-dimensional wave field signal into multiple local wave field signals based on a set window function and a set window length, and output them. Then, it performs a short-space Fourier transform on each local wave field signal to obtain the amplitude-frequency-wavenumber array corresponding to each local space and outputs it. Then, it selects a frequency range in each local space amplitude-frequency-wavenumber array with the center frequency of the excitation signal as the midpoint, calculates the weighted average wavenumber of each frequency point within the selected frequency range of each local space, and then takes the mean of the sum of the weighted average wavenumbers of each frequency point within the selected frequency range of each local space as the wavenumber corresponding to each local signal space. Finally, it splices the wavenumbers corresponding to each local space according to the sampling time sequence to obtain the wavenumber curve of the guided wave signal and outputs it.

[0032] The display module is used to generate and display corresponding images based on the outputs of the scanning module and the processing module.

[0033] Based on further improvements to the above system, the excitation source being set on the object under test specifically includes: the excitation source includes two identical excitation sensors, which are correspondingly set on the front and back surfaces of the object under test at preset positions.

[0034] Compared with the prior art, the present invention can achieve at least one of the following beneficial effects:

[0035] 1. Based on the set window function and set window length, the two-dimensional wave field signal is divided into multiple local wave field signals, which preserves the local position of the signal. This facilitates the subsequent acquisition of wave number changes that can reflect changes in spatial position, and helps to correlate wave number changes with changes in structural geometric dimensions, thereby reflecting changes in structural thickness through wave number changes.

[0036] 2. Selecting a frequency range in each local spatial amplitude-frequency-wavenumber array with the excitation signal center frequency as the center helps to reduce the amount of computation. Since the energy distribution of the guided wave signal gradually decays from the center frequency to both sides, analyzing the signal characteristics of a certain frequency range with the excitation signal center frequency as the center helps to obtain results that are closer to the real situation and have analytical value.

[0037] 3. Calculating the weighted average wavenumber of each frequency point within the selected frequency range of each local space involves multiplying the amplitude of each sampling point at the current frequency point in each local space by the wavenumber of the sampling point, and then summing the weighted average wavenumber of the current frequency point based on the sum of the amplitudes of each sampling point in the local space. This process of summing the weighted average wavenumbers of each frequency point within the selected frequency range of each local space helps to reflect the wavenumber energy distribution characteristics in the local spatial signal, reduces the influence of outliers, and more accurately obtains the wavenumber corresponding to the spatial location.

[0038] In this invention, the above-described technical solutions can be combined with each other to achieve more preferred combinations. Other features and advantages of this invention will be set forth in the following description, and some advantages may become apparent from the description or be learned by practicing the invention. The objects and other advantages of this invention can be realized and obtained from what is particularly pointed out in the description and drawings. Attached Figure Description

[0039] The accompanying drawings are for illustrative purposes only and are not intended to limit the invention. Throughout the drawings, the same reference numerals denote the same parts.

[0040] Figure 1This is a flowchart of the method in Embodiment 1 of the present invention.

[0041] Figure 2 This is a schematic diagram of the sampling location points in Embodiment 1 of the present invention.

[0042] Figure 3 This is a schematic diagram of the narrowband excitation signal in Embodiment 1 of the present invention.

[0043] Figure 4 This is a schematic diagram of the sliding window analysis process of a two-dimensional wave field signal in Embodiment 1 of the present invention.

[0044] Figure 5 This is a schematic diagram of the amplitude-frequency-wavenumber spectrum of a local wavefield signal in Embodiment 1 of the present invention.

[0045] Figure 6 This is a schematic diagram comparing the wavenumber curves obtained in Embodiment 1 of the present invention with those obtained in the prior art. Detailed Implementation

[0046] Preferred embodiments of the present invention will now be described in detail with reference to the accompanying drawings, which form part of this application and are used together with the embodiments of the present invention to illustrate the principles of the present invention, but are not intended to limit the scope of the present invention.

[0047] Example 1:

[0048] A specific embodiment of the present invention discloses a method for extracting guided wavenumbers in a variable thickness structure, such as... Figure 1 As shown.

[0049] The method specifically includes:

[0050] An excitation signal is applied to induce guided wave signals in the object under test;

[0051] A two-dimensional wave field signal is obtained by sampling the guided wave signal on the surface of the object under test;

[0052] The two-dimensional wave field signal is divided into multiple local wave field signals based on a set window function and a set window length;

[0053] The amplitude-frequency-wavenumber array corresponding to each local wavefield signal is obtained by performing a short-space Fourier transform on each local wavefield signal.

[0054] Using the center frequency of the excitation signal as the midpoint, select frequency ranges in each local spatial amplitude-frequency-wavenumber array, and calculate the weighted average wavenumber of each frequency point within the selected frequency range in each local space.

[0055] The mean of the sum of the weighted average wavenumbers of each frequency point within the selected frequency range of each local space is taken as the wavenumber corresponding to each local signal space.

[0056] The wavenumber curve of the guided wave signal is obtained by sequentially splicing the corresponding wavenumbers of each local space.

[0057] Step 1: Apply an excitation signal to generate a guided wave signal on the object under test.

[0058] Generally, non-destructive testing of structures with varying thickness involves setting an excitation sensor on the object being tested. The excitation sensor generates an excitation vibration signal, which causes the object to vibrate and generate guided waves on its surface. The testing instrument then detects the guided waves on the surface of the object.

[0059] Specifically, a lead zirconate titanate piezoelectric ceramic sheet is preferably set on the surface of the object being tested as an excitation sensor, and a Cartesian coordinate system is established with the location of the excitation sensor as the origin in order to identify and record the sampling point position.

[0060] Furthermore, the excitation signal adopts an A0 mode narrowband signal.

[0061] Specifically, in this embodiment, the A0 mode Toneburst narrowband signal is used as the excitation signal. The A0 mode narrowband signal is more sensitive to thin-walled structures in variable thickness structures, making it easier to extract significant wavenumber characteristics and thus reveal potential anomalies in the structure. Preferably, the center frequency of the A0 mode Toneburst narrowband signal is 150 kHz, and each excitation cycle consists of 5 periods.

[0062] Step 2: Sample the guided wave signal on the surface of the object under test to obtain a two-dimensional wave field signal.

[0063] Furthermore, the step of sampling the guided wave signal on the surface of the object under test to obtain a two-dimensional wave field signal specifically includes: setting multiple sampling positions at equal intervals along the one-dimensional propagation direction on the surface of the object under test, performing multiple samplings at each sampling position simultaneously, and forming the two-dimensional wave field signal from the signals obtained by multiple samplings at each sampling position.

[0064] Specifically, when the object being tested generates guided waves on its surface due to continuous excitation of an excitation signal, a Doppler vibration meter is used, with the origin of the constructed Cartesian coordinate system as the starting point, and the points are set along the horizontal axis as follows: Figure 2 The multiple sampling locations shown are as follows: Figure 2 The midpoints are labeled as x1, x2, ..., x M Where M is the maximum number of sampling locations, and the distance between each adjacent sampling location is the same. Multiple sampling points are obtained by simultaneously sampling each location multiple times at equal time intervals. The sampling points at each location have the characteristics of identical spatial location and uniform temporal distribution. According to the Nyquist theorem, the sampling frequency must be at least twice the center frequency of the Toneburst narrowband signal in mode A0, i.e., the sampling frequency ≥ 300 kHz. Figure 3This is a schematic diagram of a narrowband excitation signal. The two-dimensional wave field signal obtained by waveguide sampling at each location point includes spatial (i.e., position) information, temporal information, and amplitude information. Here, two dimensions refer to the two dimensions of space and time.

[0065] Furthermore, the two-dimensional wave field signal is specifically represented by the following expression:

[0066] In the formula,

[0067] k(f) is the wavenumber at the sampling point. Let A(f) be the initial phase of the guided wave signal, f be the sampling point amplitude, f be the sampling point frequency, u(x,t) be the two-dimensional wave field signal, t be the sampling point time, (x,t) be the sampling point position, and i be the imaginary part of the signal phase.

[0068] Step 3: Divide the two-dimensional wave field signal into multiple local wave field signals based on the set window function and set window length.

[0069] The next step is typically to extract frequency domain features using a Fourier transform of the two-dimensional wavefield signal. While a two-dimensional Fourier transform can extract the signal's frequency-wavenumber spectrum, directly performing a two-dimensional Fourier transform on the entire signal results in the loss of local spatial features, making it impossible to correlate wavenumber variations with the spatial location of guided wave propagation, thus hindering the determination of wavenumber anomalies. Therefore, this embodiment proposes applying a short spatial Fourier transform to the two-dimensional wavefield signal to decompose it into local signals of appropriate length before extracting frequency and wavenumber features. This approach preserves the spatial variation characteristics of the local signals while obtaining the corresponding frequency and wavenumber feature information.

[0070] In theory, the frequency-thickness product can be obtained based on the thickness of the object being tested at the corresponding sampling point and the center frequency of the excitation signal. The propagation speed of the A0 mode Toneburst narrowband excitation signal under this frequency-thickness product can be obtained through the dispersion curve, and the maximum wavelength can be calculated.

[0071] Furthermore, the set window length is not less than twice the maximum wavelength of the guided wave signal.

[0072] Based on the Nyquist theorem, the window length is preferably set to be one times the maximum wavelength. In this embodiment, the maximum wavelength covers 10 consecutive sampling points, so the window length is set to 20 sampling points. At the same time, by selecting a suitable window function, the spectral energy leakage of the corresponding local wave field signal within each window is minimized to avoid distortion of the results. In this embodiment, the Hanning window is preferred as the set window function. Based on the characteristic that the amplitude decreases at both ends of the Hanning window and remains unchanged at the center, a spectrum similar to a normal distribution is obtained, which helps to reduce the spectral leakage of the signal within the window. The signal features used for subsequent analysis gradually concentrate at the center of the window, making it easier to obtain wavenumber energy distribution results that are closer to the center of the window.

[0073] By aligning the set window function with the starting point of the two-dimensional wave field signal, and then sliding the two-dimensional wave field signal along the horizontal axis with a set window length, multiple local wave field signals can be obtained. Figure 4 The diagram illustrates the sliding window analysis process of a two-dimensional wave field signal based on a set window function and a set window length. The vertical axis represents the spatial location, the horizontal axis represents the time series, and the right side uses different colors to indicate the changes in the amplitude of the wave field signal.

[0074] Step 4: Obtain the amplitude-frequency-wavenumber array corresponding to each local wave field signal by performing a short-space Fourier transform on each local wave field signal.

[0075] Furthermore, the short-space Fourier transform is specifically expressed as follows:

[0076] S(x n ,k,f)=∫∫u(x,t)W * (xx n ,t)exp[-i(ft-kx)]dxdt, where,

[0077] x n For window spatial location index, W(xx) n ,t) is the set window function, S(x) n , k, f) is the amplitude-frequency-wavenumber array obtained after the short-space Fourier transform, * denotes complex conjugate, dx is the spatial position integral within the window, dt is the time integral within the window, and n is the window number.

[0078] Specifically, the short-space Fourier transform (SFT) is based on the short-time Fourier transform (SFT) approach. It uses a sliding window to extract amplitude-frequency-wavenumber arrays from the spatial distribution of the signal, obtaining local spatial signals within each window. The processing object of the SFT is the local spatial signal within a window obtained by sliding the window with a set window function and length, using the midpoint x within the window space as an example. nEach window is identified, where n is the window number; the amplitude of each local spatial signal obtained by sliding window is obtained by short space Fourier transform, where each amplitude corresponds to frequency and wavenumber, thus obtaining the amplitude-frequency-wavenumber spectrum of the local spatial signal.

[0079] Step 5: Using the center frequency of the excitation signal as the midpoint, select frequency ranges in each local spatial amplitude-frequency-wavenumber array, and calculate the weighted average wavenumber of each frequency point within the selected frequency range in each local space.

[0080] Specifically, after obtaining the amplitude-frequency-wavenumber array of each local spatial signal, a frequency range is selected for each local spatial signal with the center frequency of the excitation signal as the midpoint. The purpose of selecting the frequency range for analysis for each local spatial signal with the center frequency of the excitation signal as the midpoint is to ensure that the guided wave signal energy is the greatest at the center frequency of the excitation signal, and the signal gradually attenuates on both sides of the center frequency. In order to make the analysis results more accurate, preferably, about 30% of the frequency range on both sides of the center frequency is selected as the analysis frequency range. In this embodiment, the center frequency of the excitation signal is 150KHz, and 100KHz-200KHz is selected as the frequency range of each local spatial signal. Figure 5 The diagram shows the amplitude-frequency-wavenumber spectrum of the local wavefield signal obtained by short-space Fourier transform.

[0081] Furthermore, the weighted average wavenumber of each frequency point within the selected local spatial frequency range is calculated through the following steps, specifically including:

[0082] S71: For each amplitude-frequency-wavenumber array corresponding to all sampling positions in each local space, calculate the product of each amplitude and the corresponding wavenumber at each frequency point;

[0083] S72: Sum the products of each amplitude and its corresponding wavenumber at the same frequency point to obtain the first summation result; sum the products of each amplitude at the same frequency point to obtain the second summation result;

[0084] S73: Divide the first summation result corresponding to each frequency point by the second summation result to obtain the weighted average wavenumber of each frequency point.

[0085] Specifically, for each frequency point within the selected frequency range in each local space, based on the short-space Fourier transform results, the amplitude corresponding to each wavenumber at the current frequency point in that local space can be obtained. In step S71, the amplitude is used as a weight, considering not only the magnitude of each "wavenumber" but also the "amplitude" or "energy" corresponding to each "wavenumber." The amplitude and wavenumber at the current frequency point are multiplied to obtain the weighted wavenumber. Using the amplitude as a weight can reflect the wavenumber energy distribution characteristics in the local spatial signal, reducing the influence of outliers and making the signal more accurate. First, obtain the wavenumber amplitude corresponding to the spatial location. Next, in step S72, multiply all amplitudes in the local space at the current frequency point by the corresponding wavenumber to obtain their respective weighted wavenumbers, and then sum them to obtain the first summation result. Then, sum all amplitudes in the local space at the current frequency point to obtain the second summation result. Finally, in step S73, divide the first summation result by the second summation result to obtain the weighted average wavenumber at the current frequency point. Perform steps S71-S73 for each frequency point within the selected frequency range to obtain the weighted average wavenumber of each frequency point.

[0086] Step 6: Take the average of the sum of the weighted average wavenumbers of each frequency point within the selected frequency range of each local space as the wavenumber corresponding to each local signal space.

[0087] Furthermore, the mean value of the weighted average wavenumber of each frequency point within the selected frequency range is calculated by dividing the sum of the weighted average wavenumbers of each frequency point within the selected frequency range by the number of frequency points within the selected frequency range.

[0088] Step 7: Sequentially stitch together the corresponding wavenumbers of each local space to obtain, as shown below. Figure 6 The wavenumber curve of the guided wave signal is shown.

[0089] Depend on Figure 6 As can be seen, the wavenumber extracted from the simulation results in this embodiment is largely consistent with the theoretical wavenumber values ​​in the structure, and can reflect the thickness variation of the structure in different spaces. Therefore, when used for non-destructive testing of structures with varying thickness, wavenumber variation is more effective in reflecting the thickness variation of the structure.

[0090] The wavenumber extraction method for variable thickness structures disclosed in this embodiment utilizes an excitation signal to generate a waveguide signal on the surface of the object under test. Based on a set window function and a set window length, the two-dimensional wavefield signal obtained by sampling the waveguide signal from the surface of the object under test is divided into multiple local wavefield signals. By using an optimized Hanning window function and a window length of twice the maximum wavelength, the obtained multiple local wavefield signals reduce spectral leakage. Then, a short-space Fourier transform is performed on each local wavefield signal to obtain the amplitude-frequency-wavenumber array corresponding to each local space. The short-space Fourier transform avoids the loss of time-domain and spatial characteristics caused by the Fourier transform, which would otherwise fail to reflect the wavenumber at different sampling points. The changes in amplitude, frequency, and wavenumber are summarized in the amplitude-frequency-wavenumber array of each local space, with the center frequency of the excitation signal as the midpoint. The weighted average wavenumber of each frequency point within the selected frequency range of each local space is calculated. The amplitude is used as the weight to reflect the wavenumber characteristics of high energy in the local space. The mean of the sum of the weighted average wavenumbers of each frequency point within the selected frequency range of each local space is taken as the wavenumber corresponding to each local signal space. The wavenumbers corresponding to each local space are then spliced ​​together to obtain the wavenumber curve of the guided wave signal. Compared with the existing technology, no complicated processing is required, and a wavenumber curve that truly reflects the changes in structural thickness can be extracted.

[0091] Example 2:

[0092] A second specific embodiment of the present invention discloses a device for extracting guided wavenumbers in a variable thickness structure. The device includes an excitation source, a scanning module, a processing module, and a display module.

[0093] The excitation source is disposed on the object under test and is used to generate an A0 mode narrowband excitation signal that causes the object under test to generate a corresponding guided wave signal.

[0094] The scanning module is used to sample the guided wave signal on the surface of the object under test to obtain a two-dimensional wave field signal and output it.

[0095] The processing module is used to divide the two-dimensional wave field signal into multiple local wave field signals based on a set window function and a set window length, and output them. Then, it performs a short-space Fourier transform on each local wave field signal to obtain the amplitude-frequency-wavenumber array corresponding to each local space and outputs it. Then, it selects a frequency range in each local space amplitude-frequency-wavenumber array with the center frequency of the excitation signal as the midpoint, calculates the weighted average wavenumber of each frequency point within the selected frequency range of each local space, and then takes the mean of the sum of the weighted average wavenumbers of each frequency point within the selected frequency range of each local space as the wavenumber corresponding to each local signal space. Finally, it splices the wavenumbers corresponding to each local space according to the sampling time sequence to obtain the wavenumber curve of the guided wave signal and outputs it.

[0096] The display module is used to generate and display corresponding images based on the outputs of the scanning module and the processing module.

[0097] This embodiment includes all the technical features of Embodiment 1.

[0098] Furthermore, the excitation source being set on the object under test specifically includes: the excitation source comprising two identical excitation sensors, which are correspondingly set on the front and back surfaces of the object under test at preset positions.

[0099] Specifically, the excitation source is preferably a lead zirconate titanate piezoelectric ceramic excitation sensor. The excitation source is set at a preset position on the surface of the object under test. The preset position can be set based on prior information or randomly selected. The setting method is to tightly attach the lead zirconate titanate piezoelectric ceramic excitation sensor to both the front and back of the selected excitation point on the object under test, thereby obtaining the A0 single-mode excitation signal.

[0100] The scanning module is aligned with the surface of the object under test, preferably with the excitation source set at the center of the scanning area of ​​the scanning module. When the excitation source begins to vibrate, the scanning module scans the guided wave signal generated on the surface of the object under test, selects multiple one-dimensional position points at fixed intervals, samples each position point multiple times to obtain a two-dimensional wave field signal, and outputs it synchronously to the processing module and the display module. The display module generates a display based on the two-dimensional wave field signal. Figure 4 The image shown is a two-dimensional wave field signal.

[0101] The processing module divides the two-dimensional wave field signal into multiple local wave field signals based on a set window function and a set window length, and outputs them to the display module. The processing procedure is as follows: Figure 4 As shown; the processing module performs a short-space Fourier transform on each local wavefield signal to obtain the amplitude-frequency-wavenumber array corresponding to each local space, and outputs it to the display module to generate the following: Figure 5 The local wavefield signal amplitude-frequency-wavenumber spectrum image is shown and displayed. The processing module selects a frequency range in each local spatial amplitude-frequency-wavenumber array with the center frequency of the excitation signal as the midpoint, calculates the weighted average wavenumber of each frequency point within the selected frequency range of each local space, and then takes the mean of the sum of the weighted average wavenumbers of each frequency point within the selected frequency range of each local space as the wavenumber corresponding to each local signal space. Finally, the wavenumbers corresponding to each local space are spliced ​​according to the sampling time sequence to obtain the wavenumber curve of the guided wave signal and output to the display module to generate and display the wavenumber curve corresponding to the guided wave.

[0102] This embodiment discloses a wavenumber extraction device for guided waves in a variable thickness structure. Compared with the prior art, it is not only easier to apply and can monitor the results of each step of the scanning and processing modules based on the display module, but also can obtain a wavenumber curve that is closer to reality.

[0103] Those skilled in the art will understand that all or part of the processes of the methods described in the above embodiments can be implemented by a computer program instructing related hardware, and the program can be stored in a computer-readable storage medium. The computer-readable storage medium may be a disk, optical disk, read-only memory, or random access memory, etc.

[0104] The above description is only a preferred embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any changes or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for extracting guided wavenumbers in a variable thickness structure, characterized in that, The method specifically includes: An excitation signal is applied to induce guided wave signals in the object under test; A two-dimensional wave field signal is obtained by sampling the guided wave signal on the surface of the object under test; The two-dimensional wave field signal is divided into multiple local wave field signals based on a set window function and a set window length; The amplitude-frequency-wavenumber array corresponding to each local wavefield signal is obtained by performing a short-space Fourier transform on each local wavefield signal. Using the center frequency of the excitation signal as the midpoint, select frequency ranges in each local spatial amplitude-frequency-wavenumber array, and calculate the weighted average wavenumber of each frequency point within the selected frequency range in each local space. The mean of the sum of the weighted average wavenumbers of each frequency point within the selected frequency range of each local space is taken as the wavenumber corresponding to each local signal space. The wavenumber curve of the guided wave signal is obtained by sequentially splicing the corresponding wavenumbers of each local space.

2. The method for extracting guided wavenumbers in a variable thickness structure according to claim 1, characterized in that, The excitation signal is an A0 mode narrowband signal.

3. The method for extracting guided wavenumbers in a variable thickness structure according to claim 2, characterized in that, The step of sampling the guided wave signal on the surface of the object under test to obtain a two-dimensional wave field signal specifically includes: setting multiple sampling positions at equal intervals along the one-dimensional propagation direction on the surface of the object under test, and performing multiple time-domain samplings on each sampling position to form the two-dimensional wave field signal from all the time-domain signals obtained.

4. The method for extracting guided wavenumbers in a variable thickness structure according to claim 3, characterized in that, The two-dimensional wave field signal is specifically represented by the following expression: In the formula, k(f) is the wavenumber at the sampling point. Let A(f) be the initial phase of the guided wave signal, f be the sampling point amplitude, f be the sampling point frequency, u(x,t) be the two-dimensional wave field signal, t be the sampling point time, (x,t) be the sampling point position, and i be the imaginary part of the signal phase.

5. The method for extracting guided wavenumbers in a variable thickness structure according to claim 4, characterized in that, The set window length is not less than twice the maximum wavelength of the guided wave signal.

6. The method for extracting guided wavenumbers in a variable thickness structure according to claim 4, characterized in that, The short-space Fourier transform is specifically expressed as follows: S(x n , k, f) = ∫∫u(x, y)W * (x - x n , t)exp[-i(ft - kx)]dxdt, where x n For window spatial location index, W(xx) n ,t) is the set window function, S(x) n , k, f) is the amplitude-frequency-wavenumber array obtained after the short-space Fourier transform, * denotes complex conjugate, dx is the spatial position integral within the window, dt is the time integral within the window, and n is the window number.

7. The method for extracting guided wavenumbers in a variable thickness structure according to claim 6, characterized in that, The weighted average wavenumber of each frequency point within the selected frequency range of each local space is calculated through the following steps, the specific steps of which include: S71: For each amplitude-frequency-wavenumber array corresponding to all sampling positions in each local space, calculate the product of each amplitude and the corresponding wavenumber at each frequency point; S72: Sum the products of each amplitude and its corresponding wavenumber at the same frequency point to obtain the first summation result; sum the products of each amplitude at the same frequency point to obtain the second summation result; S73: Divide the first summation result corresponding to each frequency point by the second summation result to obtain the weighted average wavenumber of each frequency point.

8. The method for extracting guided wavenumbers in a variable thickness structure according to claim 7, characterized in that, The mean value of the weighted average wavenumbers of each frequency point within the selected frequency range is obtained by dividing the sum of the weighted average wavenumbers of each frequency point within the selected frequency range by the number of frequency points within the selected frequency range.

9. A device for extracting guided wavenumbers in a variable thickness structure, characterized in that, The device includes an excitation source, a scanning module, a processing module, and a display module, wherein, The excitation source is disposed on the object under test and is used to generate an A0 mode narrowband excitation signal that causes the object under test to generate a corresponding guided wave signal. The scanning module is used to sample the guided wave signal on the surface of the object under test to obtain a two-dimensional wave field signal and output it. The processing module is used to divide the two-dimensional wave field signal into multiple local wave field signals based on a set window function and a set window length, and output them. Then, it performs a short-space Fourier transform on each local wave field signal to obtain the amplitude-frequency-wavenumber array corresponding to each local space and outputs it. Then, it selects a frequency range in each local space amplitude-frequency-wavenumber array with the center frequency of the excitation signal as the midpoint, calculates the weighted average wavenumber of each frequency point within the selected frequency range of each local space, and then takes the mean of the sum of the weighted average wavenumbers of each frequency point within the selected frequency range of each local space as the wavenumber corresponding to each local signal space. Finally, it splices the wavenumbers corresponding to each local space according to the sampling time sequence to obtain the wavenumber curve of the guided wave signal and outputs it. The display module is used to generate and display corresponding images based on the outputs of the scanning module and the processing module.

10. The wave number extraction device for a variable thickness structure according to claim 9, characterized in that, The excitation source being set on the object under test specifically includes: the excitation source includes two identical excitation sensors, which are correspondingly set on the front and back surfaces of the object under test at preset positions.

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