Ultrasonic array imaging method for defects in steel ingot based on phase shift migration

Abstract

The invention discloses a phase shift migration-based ultrasonic array imaging method for defects in a steel ingot, which comprises the following steps of: performing two-dimensional Fourier transform on full-matrix time domain data obtained by ultrasonic array detection of the steel ingot to obtain a two-dimensional frequency spectrum of the full-matrix data, and establishing a relationship between a transmitting sound field and a receiving sound field; and gradually extrapolating the sound field through a phase shift factor in the depth direction, recovering a time domain sound field signal through two-dimensional inverse Fourier transform, and obtaining a focusing imaging result in the steel ingot according to the correlation between the transmitted sound field and the received sound field. The method has the characteristics that the image resolution is improved, the method adapts to sound velocity change in a complex medium, complex calculation is not needed, and the calculation efficiency is high.

Description

Technical Field

[0001] The invention relates to an imaging detection method, in particular to an ultrasonic array imaging method for defects in steel ingots based on phase shift migration. Background Art

[0002] As core components of major equipment, large forgings are widely used in industries such as petrochemicals, machinery manufacturing, and nuclear power. They are made by rolling or forging steel ingots. During the ingot forming process, a polycrystalline structure consisting of equiaxed and columnar crystals is formed. The microstructural characteristics of the ingot indicate that it is a typical coarse-grained material. Because the quality of the ingot directly affects subsequent processing and even the quality of the finished product, inspection of the surface and internal quality of the ingot is crucial. Ingots are typically tested through chemical composition testing, surface quality testing, ultrasonic testing, magnetic particle testing, and low-magnification testing to ensure their inherent quality.

[0003] The microscopic grain structure of steel ingots affects the imaging accuracy and sensitivity of ultrasonic defect detection. The presence of columnar crystals in polycrystalline media alters the grain orientation, causing deviations in the ultrasonic velocity. Furthermore, the anisotropic grain structure can cause distortion, separation, and curved propagation of the sound waves. Once the ultrasonic propagation direction deviates from the energy propagation direction, the acoustic beam distorts, reducing the amplitude of the defect echo and increasing attenuation. This reduces the signal-to-noise ratio of the ultrasonic detection signal, impacting the imaging accuracy of the defect and the identification of the defect location during ultrasonic imaging.

[0004] Domestic and foreign scholars have conducted relevant research on methods to improve the accuracy of defect imaging. The ray tracing method selects the path with the shortest propagation time as the propagation path of the ultrasonic wave based on the Fermat principle, calculates the group velocity through the incident direction and grain orientation to obtain the propagation time of the ultrasonic wave, and obtains the defect positioning result through the time-delay superposition imaging method; however, the ray tracing method requires repeated iterations to calculate the refraction point during the calculation process, and the calculation efficiency is low. The root mean square velocity method equates the ultrasonic wave propagation process at the refractive interface to the ultrasonic wave propagating along a straight line at the root mean square velocity in a homogeneous medium. Hu Hongwei et al. obtained the propagation time of the ultrasonic wave in the multilayer medium based on the root mean square velocity, and obtained the actual position of the defect in the water-immersed steel block through the synthetic aperture focusing method; however, the root mean square velocity method is only applicable to detection situations with small sound velocity differences, and is not applicable to situations with large sound velocity differences. The virtual sound source method simulates the sound source through virtual focusing, distinguishing different structures into single-layer media, thereby achieving media imaging. Chang et al. used a focused probe to perform water immersion defect detection on epoxy resin and aluminum specimens. The experimental results showed that the defect imaging results obtained by the virtual sound source method significantly improved the imaging signal-to-noise ratio; however, the virtual sound source method has high requirements for the focus point position, which affects the imaging resolution of the defect.

[0005] Therefore, the existing steel ingot defect imaging method has low image accuracy and resolution, low computational efficiency, and is not suitable for situations with large differences in sound speed. Summary of the Invention

[0006] The present invention aims to provide a method for ultrasonic array imaging of defects in steel ingots based on phase shift migration. The present invention has the characteristics of improving image resolution, adapting to changes in sound velocity in complex media, and requiring no complex calculations, resulting in high computational efficiency.

[0007] The technical solution of the present invention is: a method for ultrasonic array imaging of defects in steel ingots based on phase shift migration, comprising: using the full matrix time domain data obtained from the ultrasonic array detection of the steel ingot to obtain a two-dimensional spectrum of the full matrix data through a two-dimensional Fourier transform, establishing a relationship between the transmitted sound field and the received sound field, and gradually extrapolating the sound field in the depth direction through a phase shift factor, restoring the time domain sound field signal through a two-dimensional inverse Fourier transform, and obtaining a focused imaging result inside the steel ingot based on the correlation between the transmitted sound field and the received sound field.

[0008] The aforementioned method for ultrasonic array imaging of defects in steel ingots based on phase shift migration specifically includes the following steps: S1. Acquisition of full-matrix time-domain data: The steel ingot is tested by an ultrasonic array, and the full-matrix mode is used to acquire the time-domain data of the steel ingot; S2. Determine the boundary conditions of the transmitting and receiving sound fields; S3. 2D Fourier Transform: Perform a 2D Fourier transform on the acquired time-domain data to obtain frequency-wavenumber domain data. S4. Calculate the wavenumber vector: Calculate the depth-direction wavenumber component based on the dispersion equation from the frequency-wavenumber domain data. S5. Constructing a phase shift factor: Generate a phase shift factor based on the depth-direction wavenumber component and the target depth. S6. Extrapolation of the transmitted and received sound fields: Multiply the frequency domain data of the transmitted and received sound fields by the phase shift factor, and extrapolate to the target depth to obtain the extrapolated sound field. S7. Inverse Fourier Transform: Perform a two-dimensional inverse Fourier transform on the extrapolated sound field to recover the time-domain sound field signal. S8. Dynamic Focus Imaging: Perform coherent superposition of the time-domain acoustic field data of the transmitted and received acoustic fields of all array elements to generate focused imaging results of the steel ingot detection area.

[0009] In the aforementioned method for ultrasonic array imaging of defects in steel ingots based on phase shift migration, in step S2, the boundary conditions include sound velocity, density, and boundary sound source excitation mode.

[0010] In the aforementioned ultrasonic array imaging method for defects in steel ingots based on phase shift migration, in step S3, the frequency domain-wave number domain data is ,in k x for x Axial transverse wave number component, z is the target depth, ω is the angular frequency.

[0011] In the aforementioned method for ultrasonic array imaging of defects in steel ingots based on phase shift migration, in step S4, the calculation formula for the wave number component in the depth direction is: , where c Indicates the propagation speed of sound waves in the steel ingot.

[0012] In the aforementioned method for ultrasonic array imaging of defects in steel ingots based on phase shift migration, in step S5, the calculation formula of the phase shift factor is: , where Represents the wave propagating upward along the depth direction; and introduces the sound velocity gradient correction term into the phase shift factor .

[0013] In the aforementioned ultrasonic array imaging method for defects in steel ingots based on phase shift migration, in step S6, the amplitude of the phase shift factor is always 1, and the extrapolation depth step Δ z Satisfy the stability condition Δ z ≤λ / 2, where λ is the wavelength of ultrasound.

[0014] In the aforementioned method for ultrasonic array imaging of defects in steel ingots based on phase shift migration, in step S8, the calculation formula for the focused imaging result is: , where p tri To transmit the sound field, p i To receive the sound field, * indicates the convolution operation.

[0015] In the aforementioned method for ultrasonic array imaging of defects in steel ingots based on phase shift migration, in step S8, dynamic focus imaging is specifically achieved by the following steps: S801. Time domain inversion of the transmitted sound field of each transmitting array element; S802. Perform point-by-point convolution on the inverted transmitted sound field and the corresponding received sound field, applying a window function to the full matrix data in the frequency domain. ; S803. For all array elements i The convolution results are adaptively weighted and summed. The weight coefficient is dynamically generated according to the medium sound velocity distribution and defect scattering characteristics, and the imaginary attenuation term is introduced into the phase shift factor. k 'z , k ' z = k z + i ·α(ω)· sgn ( z ); where α(ω) is the frequency-dependent attenuation coefficient, sgn ( z ) is a sign function that ensures that the attenuation only acts in the forward propagation direction.

[0016] The aforementioned method for ultrasonic array imaging of defects in steel ingots based on phase shift migration further includes step S9 of imaging the multi-layer material of the steel ingot: establishing a sound velocity distribution model according to the multi-layer structural characteristics of the steel ingot: ,in is the initial sound speed, is the sound velocity gradient constant; in the process of wavelength extrapolation, it is updated in real time , calculate the depth direction wave number component , to achieve imaging of multi-layer materials of steel ingots.

[0017] Compared with the prior art, the present invention has the following beneficial effects: The present invention utilizes depth adaptive focusing technology to automatically adjust the focusing depth and position according to changes in sound speed, and can adapt to complex media; it associates the transmitted sound field with the received sound field, uses dynamic focusing to achieve signal coherent superposition, and improves the resolution of imaging; it eliminates the need to calculate the iterative time of ultrasonic wave propagation and refraction points, reduces the amount of calculation, and has high imaging efficiency; and it utilizes phase coherence to effectively suppress noise and multiple scattering interference, improve the signal-to-noise ratio, and enhance imaging quality.

[0018] Therefore, the present invention adopts the frequency domain dynamic phase migration mechanism and the phase migration algorithm to migrate and superimpose the echo signals in the frequency domain, reconstruct high-resolution images, adapt to the changes in sound speed in complex media, and effectively suppress noise and multiple scattering interference without calculating the sound wave propagation path. It is significantly superior to traditional ultrasonic imaging methods in terms of computational efficiency, imaging resolution, and anti-interference ability, and is particularly suitable for the high-precision, real-time detection needs of coarse-grained structural defects inside metal materials such as steel ingots. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Figure 1 It is a flow chart of the present invention.

[0020] Figure 2 This is the imaging result of 4140 continuous casting billet with a center frequency of 1.5 MHz. DETAILED DESCRIPTION

[0021] The present invention will be further described below with reference to the examples, but they are not intended to limit the present invention.

[0022] like Figure 1 As shown in the figure, the phase shift migration method mainly uses the full matrix time domain data obtained by the ultrasonic array detection of the detection object to obtain the two-dimensional spectrum of the full matrix data through two-dimensional Fourier transform, establishes the relationship between the transmitted sound field and the received sound field, and gradually extrapolates the sound field in the depth direction through the phase shift factor. The time domain sound field signal is restored through the two-dimensional Fourier inverse transform, and the focused imaging result inside the steel ingot is obtained according to the correlation between the transmitted sound field and the received sound field.

[0023] When the beam propagates in the two-dimensional plane xz, at time t, let p(x,z,t) be the time-varying sound field signal of the coordinate point (x,z), satisfying the following wave formula: (1); in, c Represents the speed of sound waves in a material.

[0024] Performing a two-dimensional Fourier transform on equation 1 yields: (2); in k x With k z are the wave number components along the x-axis and z-axis respectively; for Sound field in the frequency domain; ω is the angular frequency.

[0025] when When , according to the dispersion equation, we can obtain z Axial wave number component, its formula is: (3); According to the two-dimensional Fourier transform, when x and t When used as an independent variable, Formula 1 is expressed as: (4); Combining Formula 3 and Formula 4, the frequency domain-wavenumber domain expression is obtained: (5); when k x When ω is a fixed value, formula 5 is z The general solution of the second-order ordinary differential equation is: (6); in and represent the waves propagating upward and downward in the depth direction, and The boundary conditions are The amplitude coefficient of .

[0026] In ultrasonic array detection applications, only the array element receives the ultrasonic wave propagating upward from the defect. At this time, the amplitude coefficient of the wave propagating downward along the depth direction is is 0, so we can get: (7); From the above analysis, we can know that the phase shift migration method only needs to change the initial plane, that is, z =0 multiplying the signal spectrum by the phase shift factor can obtain the sound field in any depth direction. .

[0027] when k x When ω is the independent variable, Do the inverse Fourier transform and use t = 0 as the boundary condition for imaging, the imaging result of the interior of the specimen by wave field extrapolation can be obtained: (8); Among them, when t =0, .

[0028] The acoustic field is divided into two parts: the transmitting acoustic field and the receiving acoustic field. The receiving acoustic field is the process of considering the array element receiving the ultrasonic wave radiated upward from the defect. i exist t =0 when ultrasonic wave is emitted, and after time t i The ultrasonic wave propagates to the defect, and the ultrasonic wave propagating upward from the defect has not yet diverged. Imaging at this time can obtain better imaging results, so t i as imaging conditions.

[0029] for i The acoustic field formed by the array element transmission and reception by all array elements can be extrapolated to any depth through the phase shift migration method based on the above analysis and can be expressed as: (9); in is the phase shift factor, which is obtained through inverse Fourier transform. t i The imaging results can be obtained by collecting data at each moment.

[0030] By using the above phase shift migration principle, the transmitted sound field of all array elements can also be extrapolated to any depth of the detection object, and the first i When the array element excites the ultrasonic wave, the other array elements are not excited. i The transmitted wave field of each array element relative to other array elements is 0, and the transmitted sound field of the array propagates downward, which can be expressed as: (10); Establish the relationship between the transmitted sound field and the received sound field in the form of convolution in the time domain: (11); Finally, the imaging results of all array elements are obtained, which can be expressed as: (12); Example 1: A method for ultrasonic array imaging of defects in steel ingots based on phase shift migration comprises the following steps: Different layer sizes in the ingot and corresponding wave velocities in a two-dimensional plane x - z spread in t time, is the coordinate point A sound field signal that changes over time.

[0031] S1. Collect full matrix time domain data: The steel ingot is tested by an ultrasonic array, and the full matrix mode is used to collect the time domain data of the steel ingot.

[0032] S2. Determine the boundary conditions of the transmitting and receiving sound fields: Determine the boundary conditions of the transmitting and receiving sound fields based on the geometric shape and material acoustic properties of the component to be tested. The boundary conditions include sound speed, density, boundary sound source excitation mode, etc.

[0033] S3. Two-dimensional Fourier transform: Perform two-dimensional Fourier transform on the full matrix time domain data of the collected steel ingot to convert it into two-dimensional spectrum data, that is, frequency domain-wave number domain data ,in k x for x Axial transverse wave number component, z is the target depth, ω is the angular frequency.

[0034] S4. Calculate the wave number vector: Based on the frequency domain-wave number domain data, calculate the depth direction wave number component according to formula (3) k z .

[0035] S5. Constructing phase shift factor: Based on the wave number component in the depth direction k z and target depthz , generating the phase shift factor : (13); in Represents the wave propagating upward along the depth direction, considering the array element i Receive the upward propagating ultrasonic waves radiated from the defect.

[0036] And introduce the sound velocity gradient correction term into the phase shift factor , achieving depth adaptive focusing.

[0037] S6. Extrapolation of the transmitted and received sound fields: Multiply the frequency domain data of the transmitted and received sound fields by the phase shift factor, and extrapolate to the target depth to obtain the extrapolated sound field in the depth direction. .

[0038] The amplitude of the phase shift factor is always 1, that is, ; Extrapolation depth step Δ z Satisfy the stability condition Δ z ≤λ / 2, where λ is the wavelength of ultrasound.

[0039] S7. Inverse Fourier transform: the extrapolated sound field in the depth direction Perform two-dimensional inverse Fourier transform to restore the time domain sound field signal .

[0040] S8. Dynamic Focus Imaging: Coherently superimpose the time-domain acoustic field data of the transmitted and received acoustic fields of all array elements to generate a focused imaging result of the detection area. I ( x , z ), its expression formula is: (14); in p tri To transmit the sound field, p i To receive the sound field, * indicates the convolution operation.

[0041] The dynamic focus imaging in step S8 is specifically implemented by the following steps: S801. For each transmitting array element i The emission sound field Perform time domain inversion; S802. The inverted transmitted sound field and the corresponding received sound field Perform point-by-point convolution operations; It also suppresses noise and multiple scattering interference by frequency domain phase compensation and applies a window function to the full matrix data in the frequency domain. , to suppress high-frequency noise and non-physical modes; S803. For all array elements i The convolution results are adaptively weighted and summed, and the weight coefficient is dynamically generated according to the medium sound velocity distribution and defect scattering characteristics.

[0042] In order to suppress high-frequency noise and multiple scattering effects, an imaginary attenuation term is introduced into the phase shift factor. k ' z , the expression is: k ' z = k z + i ·α(ω)· sgn ( z ); where α(ω) is the frequency-dependent attenuation coefficient, sgn ( z ) is a sign function that ensures that the attenuation only acts in the forward propagation direction ( z >0). That is, during the forward propagation of the sound wave, z =0 There is no attenuation at the interface, which improves the imaging contrast.

[0043] S9. Multi-layer material imaging of steel ingots: According to the multi-layer structural characteristics of the steel ingot, a sound velocity distribution model is established, and different speeds are set for different depths. The local sound velocity of the sound velocity distribution model Expressed as: , where is the initial sound velocity and is the sound velocity gradient constant; in the process of wavelength extrapolation, the local sound velocity is updated in real time. , calculate the depth direction wave number component , to achieve imaging of multi-layer materials of steel ingots.

[0044] Example 2: The detection instrument in this embodiment is a Multi2000 series phased array device, which includes an ultrasonic excitation / receiving module, an acquisition module, and a phased array linear array transducer. The center frequency of the linear array transducer used in the experiment is f =1.5MHz, total number of array elements N=32, single array element width a =0.5mm, the center distance between two adjacent array elements p=0.6mm, the propagation speed of the sound wave in the test piece c =5900m / s, then the wavelength. The test object is 4140 continuous casting steel ingot, whose size is 390×380×55mm. Table 1 shows the defect location and size of the steel ingot specimen.

[0045] Table 1. Ingot size and defect information The present invention proposes a method for ultrasonic array imaging of defects in steel ingots based on phase shift migration, comprising the following steps: S1. Acquisition of full matrix time domain data: Ultrasonic testing experiments on steel ingots were performed using Multi2000, and time domain data was acquired using full matrix mode. f (i)j ( t )( i =1, 2, 3,…,32, j =1,2,3,…,32), where the subscript ( i ) represents the first i Array element incentive, j Indicates the first j Array element receiving.

[0046] S2. Determine the boundary conditions for the transmitted and received sound fields. Based on the component to be inspected and the inspection environment (as shown in Table 1), determine the boundary conditions for the transmitted and received sound fields. Determining boundary conditions is crucial for accurate sound field simulation and primarily includes boundary shape, acoustic properties of the boundary material (such as speed and density), and the excitation method for the boundary sound source.

[0047] S3. Two-dimensional Fourier transform: Perform a two-dimensional Fourier transform on the collected full-matrix time-domain data and convert it into two-dimensional spectrum data. This will provide a two-dimensional spectrum representation of the full-matrix time-domain data, which will provide a basis for establishing the relationship between the emitted acoustic field and the defect extrapolation field. The frequency domain-wavenumber domain data is: (15); among them k x For the x The wave number component of the axis, z is the target depth, ω is the angular frequency.

[0048] S4. Calculate the wave number vector: Based on the frequency domain-wave number domain data after Fourier transformation, combined with the physical properties of the acoustic wave and the boundary conditions, calculate the wave number component in the depth direction according to formula (3): k z The wave number vector contains the propagation information of the sound wave in different directions and is one of the key parameters in the phase shift migration method. It is used to describe the spatial phase change law of the sound wave.

[0049] S5. Construct phase shift factor: Construct phase shift factor based on wave number vector and target depth , in order to realize the spatial extrapolation of the sound field. z = 0) is used as the reference, and the distance extending inward is the extrapolated distance. The extrapolated distance is the coverage range of sound wave propagation, that is, the ultrasonic detection range, which is a preset parameter.

[0050] The phase shift factor is used to adjust the phase of the sound field and extrapolate the sound field from the reference plane to the target depth plane. Its construction needs to consider the wave equation of the sound wave and the boundary condition constraints to ensure the accuracy and rationality of the extrapolation results.

[0051] S6. Extrapolation of the transmitted and received sound fields: Using the constructed phase shift factors, phase adjustment and extrapolation processing are performed on the frequency domain data of the transmitted and received sound fields to obtain the spatial distribution of the transmitted and received sound fields within the target imaging area. , providing the necessary acoustic field information for further ingot imaging processing.

[0052] S7. Inverse Fourier transform: Extrapolating the sound field Perform an inverse Fourier transform to convert it back to a time-domain sound field signal. This step restores the sound field information in the frequency domain to a sound field signal in the time domain, making the imaging result consistent with actual physical meaning and observation habits.

[0053] S8. Dynamic Focusing for Imaging Results: Based on the inverse Fourier transform of the time-domain acoustic field signal, the coherent superposition method is used to process and fuse the time-domain acoustic field data of the transmitting and receiving fields, generating an intuitive and clear acoustic image.

[0054] Different imaging methods were used to image the 4140 continuous casting steel ingot with a center frequency of 1.5 MHz. The imaging results are shown in Figure 2 As shown. Figure 2 The imaging results show that in the conventional full focus and weighted full focus imaging results, the defect imaging position deviates from the actual defect position coordinates, but the weighted full focus method improves the resolution of defect imaging compared to the conventional full focus imaging method. Compared with the above two imaging methods, the phase shift migration imaging results of the present invention have significantly improved the defect imaging accuracy and further improved the lateral resolution of the defect. Compared with conventional full focus and weighted full focus, the phase shift migration imaging method can distinguish adjacent defects and improve the imaging resolution of defects in the steel ingot.

[0055] From the above cases, we can see that the ultrasonic array imaging method based on phase shift migration can achieve high-precision detection of internal defects in coarse-grained structures such as steel ingots through frequency domain processing and dynamic phase migration mechanism. It also has the characteristics of high computational efficiency, high imaging resolution, and strong anti-interference ability.

[0056] It should be understood that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Those skilled in the art may modify the technical solutions described in the above embodiments, or make equivalent replacements for some of the technical features therein; and all these modifications and replacements should fall within the scope of protection of the claims attached to the present invention.

Claims

1. A method for ultrasonic array imaging of defects in steel ingots based on phase shift migration, characterized by: The method includes using the full-matrix time domain data obtained from the ultrasonic array detection of the steel ingot to obtain the two-dimensional spectrum of the full-matrix data through two-dimensional Fourier transform, establishing the relationship between the transmitted sound field and the received sound field, and gradually extrapolating the sound field in the depth direction through the phase shift factor. The time domain sound field signal is restored through the two-dimensional inverse Fourier transform, and the focused imaging result inside the steel ingot is obtained based on the correlation between the transmitted sound field and the received sound field.

2. The method for ultrasonic array imaging of defects in steel ingots based on phase shift migration according to claim 1, characterized in that: The specific steps include: S1. Acquisition of full-matrix time-domain data: The steel ingot is tested by an ultrasonic array, and the full-matrix mode is used to acquire the time-domain data of the steel ingot; S2. Determine the boundary conditions of the transmitting and receiving sound fields; S3. 2D Fourier Transform: Perform a 2D Fourier transform on the acquired time-domain data to obtain frequency-wavenumber domain data. S4. Calculate the wavenumber vector: Calculate the depth-direction wavenumber component based on the dispersion equation from the frequency-wavenumber domain data. S5. Constructing a phase shift factor: Generate a phase shift factor based on the depth-direction wavenumber component and the target depth. S6. Extrapolation of the transmitted and received sound fields: Multiply the frequency domain data of the transmitted and received sound fields by the phase shift factor, and extrapolate to the target depth to obtain the extrapolated sound field. S7. Inverse Fourier Transform: Perform a two-dimensional inverse Fourier transform on the extrapolated sound field to recover the time-domain sound field signal. S8. Dynamic Focus Imaging: Perform coherent superposition of the time-domain acoustic field data of the transmitted and received acoustic fields of all array elements to generate focused imaging results of the steel ingot detection area.

3. The method for ultrasonic array imaging of defects in steel ingots based on phase shift migration according to claim 2, characterized in that: In step S2, the boundary conditions include sound velocity, density, and boundary sound source excitation mode.

4. The method for ultrasonic array imaging of defects in steel ingots based on phase shift migration according to claim 2, characterized in that: In step S3, the frequency domain-wave number domain data is ,in k x for x Axial transverse wave number component, z is the target depth, ω is the angular frequency.

5. The method for ultrasonic array imaging of defects in steel ingots based on phase shift migration according to claim 2, characterized in that: In step S4, the calculation formula of the depth direction wavenumber component is: , where c Indicates the propagation speed of sound waves in the steel ingot.

6. The method for ultrasonic array imaging of defects in steel ingots based on phase shift migration according to claim 2, characterized in that: In step S5, the calculation formula of the phase shift factor is: , where Represents the wave propagating upward along the depth direction; and introduces the sound velocity gradient correction term into the phase shift factor .

7. The method for ultrasonic array imaging of defects in steel ingots based on phase shift migration according to claim 2, characterized in that: In step S6, the amplitude of the phase shift factor is always 1, and the extrapolation depth step Δ z Satisfy the stability condition Δ z ≤λ / 2, where λ is the wavelength of ultrasound.

8. The method for ultrasonic array imaging of defects in steel ingots based on phase shift migration according to claim 2, characterized in that: In step S8, the calculation formula for the focus imaging result is: , where p tri To transmit the sound field, p i To receive the sound field, * indicates the convolution operation.

9. The method for ultrasonic array imaging of defects in steel ingots based on phase shift migration according to claim 2, characterized in that: In step S8, dynamic focus imaging is specifically achieved by the following steps: S801. Time domain inversion of the transmitted sound field of each transmitting array element; S802. Perform point-by-point convolution on the inverted transmitted sound field and the corresponding received sound field, applying a window function to the full matrix data in the frequency domain. ; S803. For all array elements i The convolution results are adaptively weighted and summed. The weight coefficient is dynamically generated according to the medium sound velocity distribution and defect scattering characteristics, and the imaginary attenuation term is introduced into the phase shift factor. k ' z , k ' z = k z + i ·α(ω)· sgn ( z );Mode where α(ω) is the frequency-dependent attenuation coefficient, sgn ( z ) is a sign function that ensures that the attenuation only acts in the forward propagation direction.

10. The method for ultrasonic array imaging of defects in steel ingots based on phase shift migration according to claim 2, characterized in that: The step S9 also includes imaging of the multi-layered material of the steel ingot: establishing a sound velocity distribution model according to the multi-layered structural characteristics of the steel ingot: ,in is the initial sound speed, is the sound velocity gradient constant; in the process of wavelength extrapolation, it is updated in real time , calculate the depth direction wave number component , to achieve imaging of multi-layer materials of steel ingots.

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