Directional shear wave excitation method based on three-dimensional elastomer

Abstract

The invention discloses a directional shear wave excitation method based on a three-dimensional elastomer, and belongs to the field of directional shear wave excitation, and the method comprises the following steps: S1, determining a material attribute and a coordinate system of a detected three-dimensional elastomer; s2, longitudinal waves and shear waves are calculated in combination with material attributes, and the wave velocities are determined; s3, solving a control equation of the isotropic infinite three-dimensional elastomer basic model to obtain displacement field distribution; s4, optimizing parameters of the exciter structure based on the displacement field; and S5, after arrangement according to parameters of the optimized exciter structure, applying multi-excitation, performing coherence enhancement on shear waves in a target direction by utilizing multi-excitation interference, and outputting directional shear waves. By adopting the directional shear wave excitation method based on the three-dimensional elastomer, phased array vertical excitation is implemented on the three-dimensional elastic half-space surface, the generation of a directional shear wave beam is realized, and a surface adhesive is not needed, so that the inherent shear / friction artifact problem in the traditional transducer design is avoided.

Description

Technical Field

[0001] The present invention relates to the technical field of directional shear wave excitation, and in particular to a directional shear wave excitation method based on a three-dimensional elastic body. Background Art

[0002] In modern industry and scientific research, non-destructive testing technology is a key means of ensuring product quality and structural safety, and its importance is self-evident. However, existing non-destructive testing technology has the following insurmountable shortcomings when dealing with three-dimensional elastomers: 1. Limitations in Detection Accuracy and Range: Current mainstream nondestructive testing relies heavily on longitudinal waves. The propagation characteristics of longitudinal waves limit their ability to discern the internal structure of the test object. This is particularly true for complex three-dimensional elastomeric structures. The accuracy of detecting tiny defects (such as cracks or holes) falls short of meeting the requirements of high-precision industries such as aerospace and microelectronics manufacturing. Furthermore, the attenuation characteristics of longitudinal waves limit the detection range. For large or thick-walled three-dimensional elastomeric structures, the detection depth often falls short of expectations.

[0003] 2. High Cost of 3D Solid Inspection: Existing nondestructive testing research primarily focuses on 2D plate and pipe structures, which are relatively regular and relatively easy to inspect. However, for truly complex 3D solid structures, there is a lack of targeted and efficient computational methods. Traditional computational methods such as finite element method (FEM) require extremely fine meshing when processing 3D solids, which not only consumes significant computing resources (such as memory and computation time) but also places extremely high demands on hardware, significantly increasing inspection costs. Furthermore, designing inspection equipment and processes suitable for 3D solids presents numerous challenges, further increasing inspection costs.

[0004] 3. Detection equipment performance needs urgent improvement: Existing detection equipment performs poorly in terms of energy utilization. Most of the energy is lost during transmission, unable to effectively act on the detection object, resulting in weak detection signals and poor anti-interference capabilities. In actual detection environments, such as the complex electromagnetic environment of industrial sites or the noisy environment of construction sites, detection signals are extremely susceptible to interference, resulting in misjudgments and missed detections.

[0005] 4. Inherent defects of shear wave excitation: In traditional shear wave excitation methods, although adhesive transducers can excite shear waves to a certain extent, a coupling agent is required to ensure good contact between the transducer and the test object. The use of coupling agents not only increases the complexity of detection and reduces detection efficiency, but also in certain special environments (such as high temperature, high pressure, and high humidity), the performance of the coupling agent may be affected, thereby affecting the accuracy of the test results. In addition, residual coupling agents may cause contamination or corrosion to the test object. Non-contact excitation methods, such as laser and magnetostriction, avoid the coupling agent problem, but due to low energy conversion efficiency, the excited shear wave energy is weak, which makes it difficult to meet the requirements of detection depth and accuracy in actual detection. Summary of the Invention

[0006] The purpose of the present invention is to provide a directional shear wave excitation method based on a three-dimensional elastic body to solve the above technical problems.

[0007] To achieve the above object, the present invention provides a directional shear wave excitation method based on a three-dimensional elastic body, comprising the following steps: S1. Construct a basic model of a three-dimensional elastic body: Use simulation software and the three-dimensional elastic half-space theory to determine the material properties and coordinate system of the three-dimensional elastic body; S2. Analyze the propagation of waves in three-dimensional elastic bodies: By establishing the governing equations for the basic model of an isotropic infinite three-dimensional elastic body and correlating the material properties with the Lame constant, calculate the longitudinal and shear waves and determine their wave velocities; S3. Based on the Lamb problem theory, finite element simulation is combined with machine learning to solve the governing equations of the isotropic infinite three-dimensional elastic body basic model and obtain the displacement field distribution; S4. Optimizing the parameters of the actuator structure based on the displacement field obtained in step S3; S5. After arranging the parameters of the optimized exciter structure, multiple excitations are applied, and the shear wave is coherently enhanced in the target direction by using the multi-excitation interference, and the longitudinal wave and surface wave are coherently canceled, and a directional shear wave is output.

[0008] Preferably, step S1 specifically includes the following steps: S11. Determination of material mechanical parameters: Obtaining the elastic modulus of a three-dimensional elastomer through material testing , Poisson's ratio and density , and calculate the first Lamé constant and the second Lamé constant : (1); (2); S12. Establish a cylindrical coordinate system: randomly select a point on the surface of the three-dimensional elastic body as the origin, and define the radial , circumferential ,depth Coordinates, determine the solution domain.

[0009] Preferably, step S2 specifically includes the following steps: S21. Establish the governing equations for an isotropic infinite three-dimensional elastic body: (3); Where, represents the gradient operator; represents vector displacement; Indicates time; S22. Using the Helmholtz decomposition formula (3), we can obtain: (4); Where, represents the divergence vector; represents a scalar; S23. Substitute formula (4) into formula (3) to obtain: (5); (6); Where, represents the longitudinal wave velocity, and ; represents the shear wave velocity .

[0010] Preferably, step S3 specifically includes the following steps: S31. Solve the displacement field under single vertical excitation; S311. Set circular vertical excitation to excite elastic waves in the isotropic infinite three-dimensional elastic body base model, and set the boundary conditions in the cylindrical coordinate system as follows: (7); Where, represents the normal stress in the z direction; represents the vertical excitation force; represents the excitation radius; and represent the shear stress in the zx direction and the shear stress in the zy direction respectively; S312. Using a single point of surface vertical force as the coordinate origin, where the wave field is uniformly distributed in all directions, the three-dimensional Lamb problem is simplified to a two-dimensional axisymmetric model. Pre-trained machine learning is used as a semi-analytical model to obtain the displacement solution for any point in the two-dimensional axisymmetric model. S313. Based on rotational symmetry, the axisymmetric plane displacement is expanded to three-dimensional spatial displacement, and the consistency between the output value of the machine learning model and the theoretical value is verified; S32, solve the displacement field step under multiple excitations; S321. Construct multi-excitation control equations: (8); Where, represents a linear operator; represents the displacement component in the z direction; S322, add Boundary conditions for vertical excitation: (9); Where, Indicates the The vertical excitation boundary, and ; Indicates the A vertical excitation at the corresponding boundary Axial displacement on S323. Introducing different excitation coefficients, rewriting formula (8) yields: (10); Where, Indicates the The excitation coefficient of the vertical excitation; S324. Using the mapping relationship between the coordinates and displacement values ​​of the axisymmetric plane, a mapping relationship between the coordinate values ​​and the corresponding displacement values ​​of the three-dimensional elastic body is established: (11); S33. Solve formula (11) to obtain the excitation coefficient , and using the interference and superposition principle of waves, multiple single vertical excitation displacement fields are combined according to the corresponding excitation coefficients to obtain the vertical displacement solution of the multi-excitation combination.

[0011] Preferably, in step S312, the machine learning model includes an input layer, three hidden layers and an output layer arranged in sequence, the mean square error is set as the loss function, the learning rate is 0.001, and the displacement field under a single vertical excitation is simulated by finite element method to extract the coordinates of the observation point. and displacement components, and the observation point coordinates The coordinates and displacement components are input into the machine learning model to learn the mapping relationship between the coordinates and the displacement components until the fitting degree reaches the set threshold to obtain a pre-trained machine learning model.

[0012] Preferably, step S4 specifically includes the following steps: S41. Define the wave transmittance calculation method: Calculate the transmittance of longitudinal waves, shear waves, and surface waves: (12); (13); (14); Where, 、 and represent the transmittance of longitudinal waves, shear waves, and surface waves respectively; Represents the solution area of ​​the entire three-dimensional elastic body; for The three-dimensional elastic region, represents the wavelength of the longitudinal wave, ; Indicates that the entire three-dimensional elastic body Areas outside Represents the displacement vector Vector in unit direction The projected scalar of , represents the displacement vector, , Represents the displacement vector The projected scalar in the xy plane of the cylindrical coordinate system, , represents the displacement projection angle, , represents the radial plane coordinates in the cylindrical coordinate system, represents the unit direction vector, , represents the direction vector angle, ; represents the in-plane shear wave, and , represents a unit vector, ; represents the out-of-plane shear wave, and ; S42. Optimize the actuator structure parameters; design an actuator structure consisting of multiple stacked PZT-5H piezoelectric columns, and the multiple stacked PZT-5H piezoelectric columns are arranged in a rectangular ring array, a square ring array, or a circular ring array, and optimize the spacing ratio in a simulation environment. , Indicates the distance between two adjacent PZT-5H piezoelectric columns, represents the wavelength of the shear wave, and , until the shear wave transmittance is the highest, determine the distance between two adjacent PZT-5H piezoelectric pillars ; S43. Determine the excitation angle: Determine the distance between two adjacent PZT-5H piezoelectric columns Based on the simulation results from multiple angles, .

[0013] Preferably, in step S42, when a plurality of stacked PZT-5H piezoelectric columns are arranged in a rectangular ring array, , shear wave transmittance is the highest; When multiple stacked PZT-5H piezoelectric pillars are arranged in a square ring array, , shear wave transmittance is the highest; When multiple stacked PZT-5H piezoelectric pillars are arranged in a circular ring array, , the shear wave transmittance is the highest.

[0014] Preferably, the constitutive equation of the PZT-5H piezoelectric column in step S42 is as follows: (15); in, (16); (17); (18); Where, and denote the stress tensor and strain tensor respectively; and and represent electric displacement and electric field intensity respectively; represents the elastic stiffness parameter matrix under constant electric potential; represents the piezoelectric constant tensor; represents the dielectric constant under constant strain; represents the strain tensor component; Represents the radial displacement component Coordinates The first partial derivative of ; Represents the radial displacement component Coordinates The first partial derivative of ; Indicates the electric field strength at Directional component; Indicates the electric potential Directional component.

[0015] Therefore, the present invention adopts the above-mentioned directional shear wave excitation method based on a three-dimensional elastic body, which has the following beneficial effects: 1. To address the complexity of solving displacement fields in three-dimensional elastic media, a machine learning-assisted semi-analytical framework was constructed. This hybrid model efficiently solves wave field distributions under single-source and multi-source excitation. The trained neural network combines the principles of wave interference and superposition to achieve predictions for multiple excitation scenarios. 2. By using axisymmetric simplification combined with rotational symmetry expansion, complex three-dimensional problems can be reduced to two dimensions for solution and then restored to three dimensions, greatly improving computational efficiency.

[0016] The technical solution of the present invention is further described in detail below through the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 This is a flow chart of a directional shear wave excitation method based on a three-dimensional elastic body according to the present invention; Figure 2 This is an axisymmetric model diagram of the elastic half-space described in the simulation experiment of the present invention; Figure 3 This is a comparison diagram of the displacement solutions described in the simulation experiment of the present invention, where (a) is the displacement solution obtained by finite element analysis. Displacement solution diagram, (b) is obtained by the machine learning model Displacement solution diagram, (c) is obtained by finite element Displacement solution diagram, (d) is obtained by the machine learning model Displacement solution diagram; Figure 4 This is a schematic diagram showing the principle of obtaining three-dimensional displacement values ​​under single-point excitation as described in the simulation experiment of the present invention; Figure 5 Schematic diagram of elastic half-plane propagation characteristics described in the simulation experiment of the present invention; Figure 6 The rectangular ring array arrangement and transmittance results of the simulation experiment of the present invention are shown in FIG. 1 , where (a) is the rectangular ring array arrangement diagram, and (b) is the rectangular ring array transmittance result diagram; Figure 7 The diagrams of the square ring array arrangement and transmittance results described in the simulation experiment of the present invention are shown, wherein (a) is the square ring array arrangement diagram, and (b) is the square ring array transmittance result diagram; Figure 8 Graphs showing the arrangement of the circular ring array and transmittance results of the simulation experiment of the present invention, wherein (a) is the arrangement diagram of the circular ring array, and (b) is the transmittance result diagram of the circular ring array; Figure 9 Figures 1 and 2 show the simulation results of the rectangular ring array arrangement described in the simulation experiment of the present invention, where (a) is the SV wave field diagram simulated by the finite element method (FEM), and (b) is the SV wave field diagram predicted by the machine learning model; Figure 10Figures 1 and 2 show the simulation results of the square ring array arrangement described in the simulation experiment of the present invention, where (a) is the SV wave field diagram simulated by the finite element method (FEM), and (b) is the SV wave field diagram predicted by the machine learning model; Figure 11 Figures 2 and 3 show the simulation results of the circular ring array arrangement described in the simulation experiment of the present invention, where (a) is the SV wave field diagram simulated by the finite element method (FEM), and (b) is the SV wave field diagram predicted by the machine learning model; Figure 12 This is a comparison diagram of the time-history response of the elastic wave excitation and detection signals described in the simulation experiment of the present invention. DETAILED DESCRIPTION

[0018] In order to make the purposes, technical solutions and advantages disclosed in the embodiments of the present invention clearer, the embodiments of the present invention are further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the embodiments of the present invention and are not intended to limit the embodiments of the present invention. Based on the embodiments in the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of this application. Examples of the embodiments are shown in the accompanying drawings, where the same or similar numbers throughout represent the same or similar elements or elements with the same or similar functions.

[0019] It should be noted that the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product or server that includes a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or are inherent to these processes, methods, products or devices.

[0020] The embodiments of the present invention will be described in detail below with reference to the accompanying drawings.

[0021] like Figure 1 As shown, a directional shear wave excitation method based on a three-dimensional elastic body includes the following steps: S1. Constructing a basic model of a three-dimensional elastic body: Determine the material properties and coordinate system of the three-dimensional elastic body to be inspected based on the object to be inspected; Step S1 specifically includes the following steps: S11. Determination of material mechanical parameters: Obtaining the elastic modulus of a three-dimensional elastomer through material testing , Poisson's ratio and density , and calculate the first Lamé constant and the second Lamé constant : (1); (2); S12. Establish a cylindrical coordinate system: randomly select a point on the surface of the three-dimensional elastic body as the origin, and define the radial , circumferential ,depth Coordinates, determine the solution domain.

[0022] S2. Analyze the propagation of waves in three-dimensional elastic bodies: By establishing the governing equations for the basic model of an isotropic infinite three-dimensional elastic body and correlating the material properties with the Lame constant, calculate the longitudinal and shear waves and determine their wave velocities; Step S2 specifically includes the following steps: S21. Establish the governing equations for an isotropic infinite three-dimensional elastic body: (3); Where, represents the gradient operator; represents vector displacement; Indicates time; S22. Using the Helmholtz decomposition formula (3), we can obtain: (4); Where, represents the divergence vector; represents a scalar; S23. Substitute formula (4) into formula (3) to obtain: (5); (6); Where, represents the longitudinal wave velocity, and ; represents the shear wave velocity .

[0023] S3. Based on the Lamb problem theory, boundary conditions are added and finite element simulation is combined with machine learning to solve the governing equations of the isotropic infinite three-dimensional elastic body basic model to obtain the displacement field distribution. Step S3 specifically includes the following steps: S31. Solve the displacement field under single vertical excitation; S311. Set circular vertical excitation to excite elastic waves in the isotropic infinite three-dimensional elastic body base model, and set the boundary conditions in the cylindrical coordinate system as follows: (7); Where, represents the normal stress in the z direction; represents the vertical excitation force; represents the excitation radius; and represent the shear stress in the zx direction and the shear stress in the zy direction respectively; S312. Using a single point of surface vertical force as the coordinate origin, where the wave field is uniformly distributed in all directions, the three-dimensional Lamb problem is simplified to a two-dimensional axisymmetric model. Pre-trained machine learning is used as a semi-analytical model to obtain the displacement solution for any point in the two-dimensional axisymmetric model. In step S312, the machine learning model includes an input layer, three hidden layers, and an output layer, and the mean square error is set as the loss function, the learning rate is 0.001, and the displacement field under a single vertical excitation is simulated by finite element method to extract the coordinates of the observation point. and displacement components, and the observation point coordinates The coordinates and displacement components are input into the machine learning model to learn the mapping relationship between the coordinates and the displacement components until the fitting degree reaches the set threshold to obtain a pre-trained machine learning model.

[0024] S313. Based on rotational symmetry, the axisymmetric plane displacement is expanded to three-dimensional spatial displacement, and the consistency between the output value of the machine learning model and the theoretical value is verified; S32, solve the displacement field step under multiple excitations; S321. Construct multi-excitation control equations: (8); Where, represents a linear operator; represents the displacement component in the z direction; S322, add Boundary conditions for vertical excitation: (9); Where, Indicates the The vertical excitation boundary, and ; Indicates the A vertical excitation at the corresponding boundary Axial displacement on S323. Introducing different excitation coefficients, rewriting formula (8) yields: (10); Where, Indicates the The excitation coefficient of the vertical excitation; S324. Using the mapping relationship between the coordinates and displacement values ​​of the axisymmetric plane, a mapping relationship between the coordinate values ​​and the corresponding displacement values ​​of the three-dimensional elastic body is established: (11); S33. Solve formula (11) to obtain the excitation coefficient , and using the interference and superposition principle of waves, multiple single vertical excitation displacement fields are combined according to the corresponding excitation coefficients to obtain the vertical displacement solution of the multi-excitation combination.

[0025] S4. Optimizing the parameters of the actuator structure based on the displacement field obtained in step S3; Step S4 specifically includes the following steps: S41. Define the wave transmittance calculation method: Calculate the transmittance of longitudinal waves, shear waves, and surface waves: (12); (13); (14); Where, 、 and represent the transmittance of longitudinal waves, shear waves, and surface waves respectively; Represents the solution area of ​​the entire three-dimensional elastic body; for The three-dimensional elastic region, represents the wavelength of the longitudinal wave, ; Indicates that the entire three-dimensional elastic body Areas outside Represents the displacement vector Vector in unit direction The projected scalar of , represents the displacement vector, , Represents the displacement vector The projected scalar in the xy plane of the cylindrical coordinate system, , represents the displacement projection angle, , represents the radial plane coordinates in the cylindrical coordinate system, represents the unit direction vector, , represents the direction vector angle, ; represents the in-plane shear wave, and , represents a unit vector, ; represents the out-of-plane shear wave, and ; S42. Optimize the actuator structure parameters; design an actuator structure consisting of multiple stacked PZT-5H piezoelectric columns, and the multiple stacked PZT-5H piezoelectric columns are arranged in a rectangular ring array, a square ring array, or a circular ring array, and optimize the spacing ratio in a simulation environment. , Indicates the distance between two adjacent PZT-5H piezoelectric columns, represents the wavelength of the shear wave, and , until the shear wave transmittance is the highest, determine the distance between two adjacent PZT-5H piezoelectric pillars ; In step S42, when a plurality of stacked PZT-5H piezoelectric columns are arranged in a rectangular ring array, , shear wave transmittance is the highest; When multiple stacked PZT-5H piezoelectric pillars are arranged in a square ring array, , shear wave transmittance is the highest; When multiple stacked PZT-5H piezoelectric pillars are arranged in a circular ring array, , the shear wave transmittance is the highest.

[0026] In this embodiment, three layers of circular ring piezoelectric columns are provided, and the second layer is rotated 2 , the third layer rotation .

[0027] The constitutive equation of the PZT-5H piezoelectric column described in step S42 is as follows: (15); in, (16); (17); (18); Where, and denote the stress tensor and strain tensor respectively; and and represent electric displacement and electric field intensity respectively; represents the elastic stiffness parameter matrix under constant electric potential; represents the piezoelectric constant tensor; represents the dielectric constant under constant strain; represents the strain tensor component; Represents the radial displacement component Coordinates The first partial derivative of ; Represents the radial displacement component Coordinates The first partial derivative of ; Indicates the electric field strength at Directional component; Indicates the electric potential Directional component.

[0028] S43. Determine the excitation angle: Determine the distance between two adjacent PZT-5H piezoelectric columns Based on the simulation results from multiple angles, .

[0029] S5. After arranging the parameters of the optimized exciter structure, multiple excitations are applied, and the shear wave is coherently enhanced in the target direction by using the multi-excitation interference, and the longitudinal wave and surface wave are coherently canceled, and a directional shear wave is output.

[0030] Simulation experiment Using the elastic wave experimental system, COMSOL Multiphysics 6.0 was used to obtain the axisymmetric plane displacement components. and , and get Figure 2 The axisymmetric plane structure for establishing the elastic half-space is shown (l represents the radial length and h represents the depth).

[0031] Table 1 Parameters of three-dimensional elastic body made of aluminum ;

[0032] First, the elastic wave propagation characteristics verification experiment was carried out using the three-dimensional elasticity shown in Table 1. In this experiment, the signal receiving point was located on the side of the aluminum block, and the detection signal of the elastic wave propagation in the three-dimensional elasticity was collected. The output signal of the excitation end was recorded synchronously. The results are as follows: Figure 12 As shown in the figure, the wave velocity is derived from the distance-time relationship, and the approximate wave velocity of the beam is obtained as a shear wave, thereby verifying the propagation characteristics of elastic waves.

[0033] Taking the vertical displacement ±1 (equivalent vertical load) applied at the coordinate origin (0,0) on the surface of a three-dimensional elastic body as an example, the center of the circle is set at the coordinate origin, and the circular excitation radius is , the operating frequency is 100kHz; add symmetrical boundaries on the left and low absorption boundaries on the right and bottom to eliminate the influence of reflected waves. 260,000 coordinate points (R, Z) and corresponding displacement values ​​( , ) to form a data set, and divided it into training set, test set and validation set, which were input into the machine learning model respectively. The mean square error (MSE) loss function was used in the training process, and the learning rate was set to 0.001. After 1000 iterations, the training set fitting degree R was obtained. 2 =0.99999, validation set R 2=0.99998, test set R 2 =0.99981, indicating that the machine learning model has extremely high accuracy in predicting wavefield displacements, and the mapping relationship between coordinate axis values ​​and displacement values, i.e., the implicit expression, can be obtained, thereby proving the effectiveness of the machine learning model described in the present invention.

[0034] In order to further verify the reliability of the machine learning model, the finite element real part solution was compared with the deep learning real part solution, and the results were as follows: Figure 3 As shown in the figure, it can be seen that the two have good consistency, which further verifies the machine learning model. Therefore, the rotational symmetry can be used to obtain the two-dimensional axisymmetric displacement results predicted by machine learning, that is, Figure 4 The displacement in three-dimensional space is shown.

[0035] By using the interference theory of waves and combining the single excitation 1 / -1 numerical solution of machine learning, the displacement solution under vertical multi-excitation is obtained. In order to design a high energy density shear wave super exciter, the following is given: Figure 5 The propagation characteristics of longitudinal waves (P waves), shear waves (S waves) and surface waves (R waves) are shown in Figure 1. Based on the propagation characteristics, the following designs are used: Figure 6-Figure 8 The exciter structure shown in the figure is obtained as Figures 9-11 The spacing ratio and angle of the rectangular ring array, square ring array or circular ring array shown in the simulation experiment are as follows: They are 34°, 32° and 34° respectively.

[0036] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit the same. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that they can still modify or replace the technical solutions of the present invention with equivalents, and these modifications or equivalent replacements cannot cause the modified technical solutions to deviate from the spirit and scope of the technical solutions of the present invention.

Claims

1. A directional shear wave excitation method based on a three-dimensional elastic body, characterized by: The following steps are involved: S1. Constructing a basic model of a three-dimensional elastic body: Determine the material properties and coordinate system of the three-dimensional elastic body to be inspected based on the object to be inspected; S2. Analyze the propagation of waves in three-dimensional elastic bodies: By establishing the governing equations for the basic model of an isotropic infinite three-dimensional elastic body and correlating the material properties with the Lame constant, calculate the longitudinal and shear waves and determine their wave velocities; S3. Based on the Lamb problem theory, finite element simulation is combined with machine learning to solve the governing equations of the isotropic infinite three-dimensional elastic body basic model and obtain the displacement field distribution; S4. Optimizing the parameters of the actuator structure based on the displacement field obtained in step S3; S5. After arranging the parameters of the optimized exciter structure, multiple excitations are applied, and the shear wave is coherently enhanced in the target direction by using the multi-excitation interference, and the longitudinal wave and surface wave are coherently canceled, and a directional shear wave is output.

2. The method for directional shear wave excitation based on a three-dimensional elastic body according to claim 1, characterized in that: Step S1 specifically includes the following steps: S11. Determination of material mechanical parameters: Obtaining the elastic modulus of a three-dimensional elastomer through material testing , Poisson's ratio and density , and calculate the first Lamé constant and the second Lamé constant : （1）； （2）； S12. Establish a cylindrical coordinate system: randomly select a point on the surface of the three-dimensional elastic body as the origin, and define the radial , circumferential ,depth Coordinates, determine the solution domain.

3. The method for directional shear wave excitation based on a three-dimensional elastic body according to claim 2, characterized in that: Step S2 specifically includes the following steps: S21. Establish the governing equations for an isotropic infinite three-dimensional elastic body: （3）； Where, represents the gradient operator; represents vector displacement; Indicates time; S22. Using the Helmholtz decomposition formula (3), we can obtain: （4）； Where, represents the divergence vector; represents a scalar; S23. Substitute formula (4) into formula (3) to obtain: （5）； （6）； Where, represents the longitudinal wave velocity, and ; represents the shear wave velocity .

4. The method for directional shear wave excitation based on a three-dimensional elastic body according to claim 3, characterized in that: Step S3 specifically includes the following steps: S31. Solve the displacement field under single vertical excitation; S311. Set circular vertical excitation to excite elastic waves in the isotropic infinite three-dimensional elastic body base model, and set the boundary conditions in the cylindrical coordinate system as follows: （7）； Where, represents the normal stress in the z direction; represents the vertical excitation force; represents the excitation radius; and represent the shear stress in the zx direction and the shear stress in the zy direction respectively; S312. Using a single point of surface vertical force as the coordinate origin, where the wave field is uniformly distributed in all directions, the three-dimensional Lamb problem is simplified to a two-dimensional axisymmetric model. Pre-trained machine learning is used as a semi-analytical model to obtain the displacement solution for any point in the two-dimensional axisymmetric model. S313. Based on rotational symmetry, the axisymmetric plane displacement is expanded to three-dimensional spatial displacement, and the consistency between the output value of the machine learning model and the theoretical value is verified; S32, solve the displacement field step under multiple excitations; S321. Construct multi-excitation control equations: （8）； Where, represents a linear operator; represents the displacement component in the z direction; S322, add Boundary conditions for vertical excitation: （9）； Where, Indicates the The vertical excitation boundary, and ; Indicates the A vertical excitation at the corresponding boundary Axial displacement on S323. Introducing different excitation coefficients, rewriting formula (8) yields: （10）； Where, Indicates the The excitation coefficient of the vertical excitation; S324. Using the mapping relationship between the coordinates and displacement values ​​of the axisymmetric plane, a mapping relationship between the coordinate values ​​and the corresponding displacement values ​​of the three-dimensional elastic body is established: （11）； S33. Solve formula (11) to obtain the excitation coefficient , and using the interference and superposition principle of waves, multiple single vertical excitation displacement fields are combined according to the corresponding excitation coefficients to obtain the vertical displacement solution of the multi-excitation combination.

5. The method for directional shear wave excitation based on a three-dimensional elastic body according to claim 4, characterized in that: In step S312, the machine learning model includes an input layer, three hidden layers, and an output layer, and the mean square error is set as the loss function, the learning rate is 0.001, and the displacement field under a single vertical excitation is simulated by finite element method to extract the coordinates of the observation point. and displacement components, and the observation point coordinates The coordinates and displacement components are input into the machine learning model to learn the mapping relationship between the coordinates and the displacement components until the fitting degree reaches the set threshold to obtain a pre-trained machine learning model.

6. The method for directional shear wave excitation based on a three-dimensional elastic body according to claim 4, characterized in that: Step S4 The specific steps include: S41. Define the wave transmittance calculation method: Calculate the transmittance of longitudinal waves, shear waves, and surface waves: （12）； （13）； （14）； Where, 、 and represent the transmittance of longitudinal waves, shear waves, and surface waves respectively; Represents the solution area of ​​the entire three-dimensional elastic body; for The three-dimensional elastic region, represents the wavelength of the longitudinal wave, ; Indicates that the entire three-dimensional elastic body Areas outside Represents the displacement vector Vector in unit direction The projected scalar of , represents the displacement vector, , Represents the displacement vector The projected scalar in the xy plane of the cylindrical coordinate system, , represents the displacement projection angle, , represents the radial plane coordinates in the cylindrical coordinate system, represents the unit direction vector, , represents the direction vector angle, ; represents the in-plane shear wave, and , represents a unit vector, ; represents the out-of-plane shear wave, and ; S42. Optimize the actuator structure parameters; design an actuator structure consisting of multiple stacked PZT-5H piezoelectric columns, and the multiple stacked PZT-5H piezoelectric columns are arranged in a rectangular ring array, a square ring array, or a circular ring array, and optimize the spacing ratio in a simulation environment. , Indicates the distance between two adjacent PZT-5H piezoelectric columns, represents the wavelength of the shear wave, and , until the shear wave transmittance is the highest, determine the distance between two adjacent PZT-5H piezoelectric pillars ; S43. Determine the excitation angle: Determine the distance between two adjacent PZT-5H piezoelectric columns Based on the simulation results from multiple angles, .

7. The method for directional shear wave excitation based on a three-dimensional elastic body according to claim 6, characterized in that: In step S42, when a plurality of stacked PZT-5H piezoelectric columns are arranged in a rectangular ring array, , shear wave transmittance is the highest; When multiple stacked PZT-5H piezoelectric pillars are arranged in a square ring array, , shear wave transmittance is the highest; When multiple stacked PZT-5H piezoelectric pillars are arranged in a circular ring array, , the shear wave transmittance is the highest.

8. The method for directional shear wave excitation based on a three-dimensional elastic body according to claim 6, characterized in that: The constitutive equation of the PZT-5H piezoelectric column described in step S42 is as follows: （15）； in, （16）； （17）； （18）； Where, and denote the stress tensor and strain tensor respectively; and and represent electric displacement and electric field intensity respectively; represents the elastic stiffness parameter matrix under constant electric potential; represents the piezoelectric constant tensor; represents the dielectric constant under constant strain; represents the strain tensor component; Represents the radial displacement component Coordinates The first partial derivative of ; Represents the radial displacement component Coordinates The first partial derivative of ; Indicates the electric field strength at Directional component; Indicates the electric potential Directional component.

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