Lamb wave signal frequency dispersion compensation method and system based on sparse matching and reconstruction

Abstract

The invention discloses a Lamb wave signal frequency dispersion compensation method and system based on sparse matching and reconstruction, which are applied to the technical field of structural health monitoring signal processing, and the method comprises the steps: collecting a damaged Lamb wave frequency domain excitation signal of a carbon fiber composite material, carrying out the frequency dispersion processing, and constructing a frequency dispersion dictionary; according to the frequency dispersion dictionary and the actually acquired Lamb wave frequency dispersion signals, an L1 norm sparse representation model is constructed, and according to the sparse representation model, a sparse solution containing frequency dispersion signal wave packet position and size information is calculated; performing excitation signal processing on the frequency domain excitation signal to construct a non-frequency dispersion dictionary; and based on a sparse solution and the non-dispersion dictionary, reconstructing a non-dispersion Lamb wave signal, and completing compensation of a dispersion wave packet. According to the Lamb wave signal frequency dispersion compensation method, the sparse matching and reconstruction method is used for processing, the time domain width of a wave packet is effectively reduced, deformation of the wave packet is reduced, and then frequency dispersion compensation of the Lamb wave signal is achieved.

Description

Technical Field

[0001] The present disclosure relates to the technical field of structural health monitoring signal processing, and in particular to a method and system for compensating for Lamb wave signal dispersion based on sparse matching and reconstruction. Background Art

[0002] During the service life of major equipment in the fields of aerospace, rail transit, wind power generation, etc., the structures will inevitably suffer from damage such as cracks and holes due to various factors. When the damage reaches a certain extent, it will cause the structure to break and cause serious safety accidents. Therefore, real-time health monitoring of the structure is required to evaluate the structural health status in real time and detect damage in time.

[0003] Structural health monitoring technology is a technology that can monitor the health of structures in real time and online. It obtains damage information by stimulating and collecting signals through sensors arranged on the surface of the structure or integrated into the structure. In the field of structural health monitoring, Lamb wave signals are widely used in structural health monitoring technology due to their advantages of long propagation distance and sensitivity to damage, and are good information carriers. However, due to the inherent dispersion characteristics of Lamb wave signals, the signal packet width will expand and the waveform will be distorted during the propagation process, which will affect the subsequent signal processing and damage identification. Therefore, dispersion compensation of Lamb wave signals is required.

[0004] Among the existing dispersion compensation methods, the time reversal method can compensate for the dispersion of the signal by inverting the signal, but the Lamb wave signal processed by this method will lose the propagation time, which is not conducive to the subsequent damage monitoring. In addition to the time reversal method, the time domain-distance mapping method and the linear mapping method can also compensate for the dispersion in the signal, but the interpolation process in the two methods will affect the signal wave packet, and there is often a large distortion in the wave packet, making it difficult to effectively compensate the wave packet, which will also affect the subsequent damage monitoring.

[0005] Therefore, providing a method that can effectively realize dispersion compensation of Lamb wave signals is of great significance for damage monitoring. Summary of the invention

[0006] The present invention provides a method and system for compensating for Lamb wave signal dispersion based on sparse matching and reconstruction, which matches the wave packet in the actual Lamb wave dispersion signal through the Lamb wave dispersion signal, and at least solves the technical problem that the prior art cannot achieve effective compensation for Lamb waves in the process of component damage monitoring.

[0007] According to a first aspect of the present disclosure, a method for compensating for dispersion of Lamb wave signals based on sparse matching and reconstruction is provided, comprising the following steps:

[0008] Collect the frequency domain excitation signal of Lamb wave of carbon fiber composite material damage, perform dispersion processing, and construct a dispersion dictionary;

[0009] According to the dispersion dictionary and the Lamb wave dispersion signal actually collected, an L1 norm sparse representation model is constructed, and a sparse solution containing the position and size information of the dispersion signal wave packet is calculated according to the sparse representation model;

[0010] Performing excitation signal processing on the frequency domain excitation signal to construct a non-dispersive dictionary;

[0011] Based on the sparse solution and the non-dispersive dictionary, a non-dispersive Lamb wave signal is reconstructed to complete the compensation of the dispersive wave packet.

[0012] According to the above aspects and any possible implementation, an implementation is further provided, wherein the process of collecting the frequency domain excitation signal of the damaged Lamb wave of the carbon fiber composite material and performing dispersion processing to construct a dispersion dictionary is as follows:

[0013] Obtain the frequency domain excitation signal of Lamb wave of carbon fiber composite material damage and discretize the propagation distance of Lamb wave;

[0014] Solve the theoretical Lamb wave dispersion signal under discrete propagation distance based on the wave number-frequency relationship;

[0015] The theoretical Lamb wave dispersion signals after discretization are combined in columns to construct a dispersion dictionary.

[0016] According to the above aspects and any possible implementation, an implementation is further provided, in which the propagation distance of the discrete Lamb wave is calculated as follows:

[0017]

[0018] Where j is the discrete number, ranging from 1≤j≤M; ω c is the center frequency; c g (ω c ) is the group velocity of the center frequency; f s is the sampling frequency, its reciprocal is the sampling period, d j is the propagation distance of discrete Lamb waves.

[0019] According to the above aspects and any possible implementation, an implementation is further provided, wherein the calculation method for solving the theoretical Lamb wave dispersion signal under discrete propagation distance based on the wave number-frequency relationship is:

[0020]

[0021] Where t is time, ω is angular frequency, U(ω) is the frequency domain excitation signal, k(ω) is the wave number, and v j is the theoretical Lamb wave dispersion signal.

[0022] According to the above aspects and any possible implementation, an implementation is further provided, wherein the calculation method of obtaining the sparse solution containing the position and size information of the dispersion signal wave packet according to the sparse representation model is:

[0023]

[0024] in, is the optimal solution of the sparse coefficient a, which is solved by the basis pursuit denoising algorithm; ‖a‖ 1 is the L1 norm of the sparse coefficient a, y is the actual collected Lamb wave dispersion signal, v is the dispersion dictionary, σ 2 is the regularization parameter.

[0025] According to the above aspects and any possible implementation manner, an implementation manner is further provided, wherein the process of performing excitation signal processing on the frequency domain excitation signal to construct a non-dispersive dictionary is:

[0026] Based on the frequency excitation signal, calculating the time-shifted Lamb wave excitation signal corresponding to the j-th discrete propagation distance;

[0027] The time-shifted Lamb wave excitation signals are combined in columns to construct a non-dispersive dictionary.

[0028] According to the above aspects and any possible implementation, an implementation is further provided, wherein the calculation method of calculating the time-shifted Lamb wave excitation signal corresponding to the j-th discrete propagation distance based on the frequency excitation signal is:

[0029]

[0030] Among them, v′ j This is equal to the excitation signal shifted by t in the time domain. j The signal after will not contain the dispersion signal wave packet, u(t) is the time domain excitation signal, u(tt j ) means u(t) is shifted by t in the time domain j After the signal.

[0031] According to the above aspects and any possible implementation, an implementation is further provided, wherein the calculation method of reconstructing a non-dispersive Lamb wave signal based on a sparse solution and a time-shifted Lamb wave excitation signal to complete the compensation of the dispersive wave packet is:

[0032]

[0033] in, is the reconstructed non-dispersive Lamb wave signal, and v′ is the non-dispersive dictionary.

[0034] According to a second aspect of the present disclosure, a Lamb wave signal dispersion compensation system based on sparse matching and reconstruction is provided, which is used to implement a Lamb wave signal dispersion compensation method based on sparse matching and reconstruction as described in the first aspect, and the system includes: a dispersion dictionary construction module, a Lamb wave signal sparse solution calculation module, a non-dispersion dictionary construction module and a dispersion wave packet compensation module;

[0035] The dispersion dictionary building module is used to collect frequency domain excitation signals of Lamb waves of carbon fiber composite material damage, and perform dispersion processing to build a dispersion dictionary;

[0036] The Lamb wave signal sparse solution calculation module is used to construct an L1 norm sparse representation model according to the dispersion dictionary and the Lamb wave dispersion signal actually collected, and calculate a sparse solution containing the position and size information of the dispersion signal wave packet according to the sparse representation model;

[0037] The non-dispersive dictionary construction module is used to perform excitation signal processing on the frequency domain excitation signal to construct a non-dispersive dictionary;

[0038] The dispersion wave packet compensation module is used to reconstruct a non-dispersive Lamb wave signal based on a sparse solution and a time-shifted Lamb wave excitation signal, thereby completing compensation for the dispersion wave packet.

[0039] Compared with the prior art, the present invention has the following technical effects:

[0040] The present invention utilizes theoretical Lamb wave dispersion signals at different propagation distances to match wave packets in actual Lamb wave dispersion signals, obtains the position and size information of the wave packets, and then reconstructs corresponding excitation wave packets at corresponding positions in combination with excitation signals at different propagation distances, thereby reducing the time domain width of the wave packets to make them more similar to the wave packets of the Lamb wave excitation signal, thereby achieving effective compensation for the Lamb wave dispersion signals.

[0041] It should be understood that the contents described in the summary of the invention are not intended to limit the key or important features of the embodiments of the present disclosure, nor are they intended to limit the scope of the present disclosure. Other features of the present disclosure will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] The above and other features, advantages and aspects of the embodiments of the present disclosure will become more apparent with reference to the following detailed description in conjunction with the accompanying drawings. The accompanying drawings are used to better understand the present solution and do not constitute a limitation of the present disclosure. In the accompanying drawings, the same or similar reference numerals represent the same or similar elements, among which:

[0043] Figure 1 A schematic flow chart of a method for compensating frequency dispersion of Lamb wave signals based on sparse matching and reconstruction according to an embodiment of the present disclosure is shown;

[0044] Figure 2 A schematic diagram of the structure of a Lamb wave signal dispersion compensation system based on sparse matching and reconstruction according to an embodiment of the present disclosure is shown;

[0045] Figure 3 A physical picture of a carbon fiber composite material plate according to an embodiment of a Lamb wave signal dispersion compensation method based on sparse matching and reconstruction according to an embodiment of the present disclosure is shown;

[0046] Figure 4 A time domain diagram of an excitation signal of an embodiment of a Lamb wave signal dispersion compensation method based on sparse matching and reconstruction according to an embodiment of the present disclosure is shown;

[0047] Figure 5 A schematic diagram of a rectangular coordinate system of a carbon fiber composite material plate constructed according to an embodiment of a Lamb wave signal dispersion compensation method based on sparse matching and reconstruction according to an embodiment of the present disclosure is shown;

[0048] Figure 6 A single-wave packet Lamb wave signal before and after dispersion compensation is shown in an embodiment of a Lamb wave signal dispersion compensation method based on sparse matching and reconstruction according to an embodiment of the present disclosure;

[0049] Figure 7 A dual-wave packet Lamb wave signal before and after dispersion compensation according to an embodiment of a Lamb wave signal dispersion compensation method based on sparse matching and reconstruction according to an embodiment of the present disclosure is shown. DETAILED DESCRIPTION

[0050] In order to make the purpose, technical solution and advantages of the embodiments of the present disclosure clearer, the technical solution in the embodiments of the present disclosure will be clearly and completely described below in conjunction with the drawings in the embodiments of the present disclosure. Obviously, the described embodiments are part of the embodiments of the present disclosure, not all of the embodiments. Based on the embodiments in the present disclosure, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present disclosure.

[0051] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the present invention is further described in detail below with reference to the accompanying drawings and specific embodiments.

[0052] Reference Figure 1 As shown, this embodiment provides a Lamb wave signal dispersion compensation method based on sparse matching and reconstruction, comprising the following steps:

[0053] S101, collecting frequency domain excitation signals of Lamb waves of carbon fiber composite material damage, performing dispersion processing, and constructing a dispersion dictionary.

[0054] In this embodiment, dispersion compensation is performed on the Lamb wave monitoring signal of the carbon fiber composite material damage. The specific process is as follows:

[0055] Obtain the frequency domain excitation signal of Lamb wave of carbon fiber composite material damage and discretize the propagation distance of Lamb wave;

[0056] Solve the theoretical Lamb wave dispersion signal under discrete propagation distance based on the wave number-frequency relationship;

[0057] The discretized Lamb wave dispersion signals are combined by columns to construct a dispersion dictionary.

[0058] Specifically, the calculation method of the j-th discrete propagation distance dj is as follows:

[0059]

[0060] Where j is the discrete number, ranging from 1≤j≤M; ω c is the center frequency; c g (ω c ) is the group velocity of the center frequency; f s is the sampling frequency, and its reciprocal is the sampling period.

[0061] The jth discrete propagation distance d j The theoretical Lamb wave dispersion signal v under j for:

[0062]

[0063] Where t is time, ω is angular frequency, U(ω) is the frequency domain excitation signal, and k(ω) is the wave number.

[0064] After the theoretical Lamb wave dispersion signal under each discrete propagation distance is calculated, it is combined by column to construct a dispersion dictionary in the following form:

[0065] v=[v 1 ,...,v j ,...,v M] (3)

[0066] Among them, v is the dispersion dictionary, and M is the total number of discrete propagation distances.

[0067] S102. According to the dispersion dictionary and the Lamb wave dispersion signal actually collected, an L1 norm sparse representation model is constructed, and a sparse solution containing the position and size information of the dispersion signal wave packet is calculated according to the sparse representation model.

[0068] Regularization is a general term for a class of methods in machine learning that introduces additional information and penalty terms to the original loss function in order to prevent overfitting and improve the generalization performance of the model. Specifically, in this embodiment, the sparse optimal solution is calculated by the L1 regularization function, and the specific process is:

[0069]

[0070] in, is the optimal solution of the sparse coefficient a, which is solved by the basis pursuit denoising algorithm; ‖a‖ 1 is the L1 norm of the sparse coefficient a, y is the actual collected Lamb wave dispersion signal, v is the dispersion dictionary, σ 2 is the regularization parameter.

[0071] S103, performing excitation signal processing on the frequency domain excitation signal to construct a non-dispersive dictionary.

[0072] In this embodiment, by calculating the time-shifted Lamb wave excitation signal corresponding to the j-th discrete propagation distance based on the frequency excitation signal, the following is obtained:

[0073]

[0074] Among them, v′ j This is equal to the excitation signal shifted by t in the time domain. j The signal after will not contain the dispersion signal wave packet, u(t) is the time domain excitation signal, u(tt j ) means u(t) is shifted by t in the time domain j After the signal.

[0075] After all the time-shifted Lamb wave excitation signals corresponding to the discrete propagation distances are calculated, they are combined by columns to construct a non-dispersive dictionary in the following form:

[0076] v′=[v 1 ′,...,v j ′,...,v′ M ] (6)

[0077] Where v′ is the non-dispersive dictionary and M is the total number of discrete propagation distances.

[0078] S104, reconstructing a non-dispersive Lamb wave signal based on the sparse solution and the time-shifted Lamb wave excitation signal, and completing the compensation of the dispersive wave packet.

[0079] Specifically, in this embodiment, the dispersion wave packet compensation process is as follows:

[0080]

[0081] in, is the reconstructed non-dispersive Lamb wave signal.

[0082] like Figure 2 As shown, this embodiment also provides a Lamb wave signal dispersion compensation system based on sparse matching and reconstruction, including: a dispersion dictionary construction module 1, a Lamb wave signal sparse solution calculation module 2, a non-dispersion dictionary construction module 3 and a dispersion wave packet compensation module 4;

[0083] The dispersion dictionary construction module 1 is used to collect the frequency domain excitation signal of Lamb wave of carbon fiber composite material damage, and perform dispersion processing to construct a dispersion dictionary;

[0084] The Lamb wave signal sparse solution calculation module 2 is used to construct an L1 norm sparse representation model based on the dispersion dictionary and the Lamb wave dispersion signal actually collected, and calculate the sparse solution containing the dispersion signal wave packet position and size information according to the sparse representation model;

[0085] The non-dispersive dictionary construction module 3 is used to perform excitation signal processing on the frequency domain excitation signal to construct a non-dispersive dictionary;

[0086] The dispersion wave packet compensation module 4 is used to reconstruct a non-dispersive Lamb wave signal based on the sparse solution and the time-shifted Lamb wave excitation signal, and complete the compensation of the dispersion wave packet.

[0087] Example

[0088] This embodiment conducts a dispersion compensation experiment on the Lamb wave monitoring signal of carbon fiber composite material damage, and the data used is the Lamb wave monitoring signal data set of simulated damage of carbon fiber composite laminate provided by the Open Guided Waves open source platform. Figure 3 The figure shows the experimental carbon fiber composite material plate, which has a size of 500mm×500mm×2mm and a ply ratio of [45 / 0 / -45 / 90 / -45 / 0 / 45 / 90]s. Six circular thin-film piezoelectric sensors with a diameter of 10mm are arranged at the upper and lower ends of the plate for the excitation and reception of Lamb waves. The excitation signal is as follows: Figure 4 As shown in Figure 1, it is a five-peak sinusoidal modulation signal with a center frequency of 60kHz. The coordinate system is as follows: Figure 5 As shown, the lower left corner of the CFRP plate is the coordinate origin, the bottom boundary is the x-axis, the left boundary is the y-axis, the blue circles on the upper and lower sides represent the sensor positions, and the red circle in the middle represents the damage position. The damage response signal and the reference signal when there is no damage are collected respectively, and the damage monitoring signal is obtained by subtracting them. In this embodiment, the single wave packet and double wave packet damage Lamb wave monitoring signals are selected respectively, and the dispersion compensation signal is obtained according to the method of the present invention.

[0089] Figure 6 The figure shows the single-wave packet damaged Lamb wave monitoring signal before dispersion compensation and the signal after dispersion compensation using the present invention, wherein: Figure 6 (a) is the single-wave packet damaged Lamb wave monitoring signal before dispersion compensation. Figure 6 (b) in the figure is a single-wave packet damaged Lamb wave monitoring signal after dispersion compensation. It can be seen from the signal in the figure that compared with the excitation signal, the Lamb signal before dispersion compensation has a serious dispersion effect, the time domain width of the wave packet becomes wider, and the waveform is deformed. After the signal is subjected to dispersion compensation processing by the present invention, the signal wave packet width is compressed, and the wave packet waveform is more similar to the excitation signal waveform, indicating that the present invention effectively compensates for the dispersion of the single-wave packet Lamb wave monitoring signal.

[0090] Figure 7 The figure shows the double-wave packet damaged Lamb wave monitoring signal before dispersion compensation and the signal after dispersion compensation using the present invention, wherein: Figure 7 (a) is the double-wave packet damaged Lamb wave monitoring signal before dispersion compensation. Figure 7 (b) in the figure is the double-wave packet damaged Lamb wave monitoring signal after dispersion compensation. It can be seen from the signal in the figure that, like the single-wave packet damaged Lamb wave monitoring signal, the signal before dispersion compensation has a serious dispersion effect, and the waveforms of the two wave packets are distorted. After the signal is subjected to dispersion compensation processing by the present invention, the widths of the two wave packets in the signal are compressed, and the wave packet waveform is more similar to the excitation signal waveform, indicating that the present invention performs effective dispersion compensation on the double-wave packet damaged Lamb wave monitoring signal.

[0091] It should be noted that, for the aforementioned method embodiments, for the sake of simplicity, they are all described as a series of action combinations, but those skilled in the art should be aware that the present disclosure is not limited by the order of the actions described, because according to the present disclosure, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also be aware that the embodiments described in the specification are all optional embodiments, and the actions and modules involved are not necessarily required by the present disclosure.

[0092] It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps recorded in this disclosure can be executed in parallel, sequentially or in different orders, as long as the desired results of the technical solutions disclosed in this disclosure can be achieved, and this document does not limit this.

[0093] The above specific implementations do not constitute a limitation on the protection scope of the present disclosure. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modification, equivalent substitution and improvement made within the spirit and principle of the present disclosure shall be included in the protection scope of the present disclosure.

Claims

1. A Lamb wave signal dispersion compensation method based on sparse matching and reconstruction, characterized in that: The following steps are involved: Collect the frequency domain excitation signal of Lamb wave of carbon fiber composite material damage, perform dispersion processing, and construct a dispersion dictionary; According to the dispersion dictionary and the Lamb wave dispersion signal actually collected, an L1 norm sparse representation model is constructed, and a sparse solution containing the position and size information of the dispersion signal wave packet is calculated according to the sparse representation model; Performing excitation signal processing on the frequency domain excitation signal to construct a non-dispersive dictionary; Based on the sparse solution and the non-dispersive dictionary, a non-dispersive Lamb wave signal is reconstructed to complete the compensation of the dispersive wave packet.

2. The method for compensating Lamb wave signal dispersion based on sparse matching and reconstruction according to claim 1, characterized in that: The process of collecting the frequency domain excitation signal of Lamb wave of carbon fiber composite material damage, performing dispersion processing, and constructing a dispersion dictionary is as follows: Obtain the frequency domain excitation signal of Lamb wave of carbon fiber composite material damage and discretize the propagation distance of Lamb wave; Solve the theoretical Lamb wave dispersion signal under discrete propagation distance based on the wave number-frequency relationship; The theoretical Lamb wave dispersion signals after discretization are combined in columns to construct a dispersion dictionary.

3. The method for compensating Lamb wave signal dispersion based on sparse matching and reconstruction according to claim 2, characterized in that: The propagation distance of the discrete Lamb wave is calculated as follows: Where j is the discrete number, ranging from 1≤j≤M; ω c is the center frequency; c g (ω c ) is the group velocity of the center frequency; f s is the sampling frequency, its reciprocal is the sampling period, d j is the propagation distance of discrete Lamb waves.

4. The method for compensating Lamb wave signal dispersion based on sparse matching and reconstruction according to claim 3, characterized in that: The calculation method for solving the theoretical Lamb wave dispersion signal under discrete propagation distance based on the wave number-frequency relationship is: Where t is time, ω is angular frequency, U(ω) is the frequency domain excitation signal, k(ω) is the wave number, and v j is the theoretical Lamb wave dispersion signal.

5. The method for compensating Lamb wave signal dispersion based on sparse matching and reconstruction according to claim 1, characterized in that: The calculation method of the sparse solution containing the position and size information of the dispersion signal wave packet calculated according to the sparse representation model is: in, is the optimal solution of the sparse coefficient a, which is solved by the basis pursuit denoising algorithm; ‖a‖1 is the L1 norm of the sparse coefficient a, y is the actual collected Lamb wave dispersion signal, v is the dispersion dictionary, σ 2 is the regularization parameter.

6. The method for compensating Lamb wave signal dispersion based on sparse matching and reconstruction according to claim 1, characterized in that: The process of performing excitation signal processing on the frequency domain excitation signal to construct a non-dispersive dictionary is as follows: Based on the frequency excitation signal, calculating the time-shifted Lamb wave excitation signal corresponding to the j-th discrete propagation distance; The time-shifted Lamb wave excitation signals are combined in columns to construct a non-dispersive dictionary.

7. The method for compensating Lamb wave signal dispersion based on sparse matching and reconstruction according to claim 6, characterized in that: The calculation method of calculating the time-shifted Lamb wave excitation signal corresponding to the j-th discrete propagation distance based on the frequency excitation signal is: Among them, v′ j This is equal to the excitation signal shifted by t in the time domain. j The signal after will not contain the dispersion signal wave packet, u(t) is the time domain excitation signal, u(tt j ) means u(t) is shifted by t in the time domain j After the signal.

8. The method for compensating Lamb wave signal dispersion based on sparse matching and reconstruction according to claim 1, characterized in that: The calculation method of reconstructing the non-dispersive Lamb wave signal based on the sparse solution and the time-shifted Lamb wave excitation signal to complete the compensation of the dispersive wave packet is: in, is the reconstructed non-dispersive Lamb wave signal, and v′ is the non-dispersive dictionary.

9. A Lamb wave signal dispersion compensation system based on sparse matching and reconstruction, used to implement the Lamb wave signal dispersion compensation method based on sparse matching and reconstruction as claimed in any one of claims 1 to 8, characterized in that: include: A dispersion dictionary construction module (1), a Lamb wave signal sparse solution calculation module (2), a non-dispersion dictionary construction module (3) and a dispersion wave packet compensation module (4); The dispersion dictionary construction module (1) is used to collect frequency domain excitation signals of Lamb waves of carbon fiber composite material damage, and perform dispersion processing to construct a dispersion dictionary; The Lamb wave signal sparse solution calculation module (2) is used to construct an L1 norm sparse representation model based on the dispersion dictionary and the Lamb wave dispersion signal actually collected, and calculate a sparse solution containing the dispersion signal wave packet position and size information based on the sparse representation model; The non-dispersive dictionary construction module (3) is used to perform excitation signal processing on the frequency domain excitation signal to construct a non-dispersive dictionary; The dispersion wave packet compensation module (4) is used to reconstruct a non-dispersive Lamb wave signal based on a sparse solution and a time-shifted Lamb wave excitation signal, thereby completing compensation for the dispersion wave packet.

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