An ultrasonic guided wave quantitative imaging method and system using initial value estimation iteration

Abstract

The application belongs to the technical field of ultrasonic nondestructive testing, and discloses an ultrasonic guided wave quantitative imaging method and system for iteratively solving initial values, wherein the method comprises the following steps: building a sensor array to collect ultrasonic signals, extracting ultrasonic propagation time information, calculating the group velocity distribution of a detection area, converting the group velocity distribution into a phase velocity distribution, using the phase velocity distribution of the ultrasonic waves to build an initial value of a calculation target function, using the initial value of the target function to calculate a theoretical scattering field, then calculating the difference between the theoretical scattering field and an actual scattering field, using an iterative optimization algorithm to update the target function, until the difference between the theoretical scattering field and the actual scattering field is less than a preset value, obtaining a final target function, building a mapping relationship between the final target function and the thickness of a measured object, and outputting a quantitative imaging result. The application has high accuracy in defect shape recognition, small size measurement error, small thickness reconstruction error, and significantly improves the precision and stability of ultrasonic guided wave imaging.

Description

Technical Field

[0001] This invention belongs to the field of ultrasonic nondestructive testing technology, and relates to a quantitative ultrasonic imaging method, specifically a quantitative ultrasonic guided wave imaging method and system for iterative solution of estimated initial values. Background Technology

[0002] Structural health monitoring technology is crucial for ensuring the safety and reliability of large plate and shell structures in service, such as aircraft skins and ship decks, and large-diameter pipelines such as oil and gas pipelines. Among numerous non-destructive testing methods, ultrasonic guided wave technology, especially Lamb waves, has shown significant advantages due to its long propagation distance, high detection efficiency, and ability to perform large-scale rapid scanning of structures, making it a research and application hotspot in this field.

[0003] By deploying a sensor array to acquire and process ultrasonic guided wave signals, damage can be visualized, located, and assessed in two-dimensional space. Existing ultrasonic guided wave imaging methods mainly include traditional methods such as time-delay superposition. The time-delay superposition method calculates the time delay of different propagation paths and superimposes the signal energy of each path onto a spatial grid to form an imaging result. This method is simple to implement, computationally efficient, and has certain advantages in damage localization.

[0004] However, the imaging of the time-delay stacking method is essentially the spatial distribution of wave packet energy, and its resolution is limited by the diffraction limit. This physical limitation leads to problems such as blurring, numerous artifacts, and insufficient positioning accuracy in the imaging results. Specifically, this manifests as: unclear defect boundaries, making it difficult to accurately determine the actual shape of the defect; the presence of false response points in the imaging area, interfering with defect identification; and significant errors in defect location, failing to meet the requirements for accurate assessment. More importantly, the time-delay stacking method struggles to obtain quantitative parameters of defects, such as precise shape and size, and the degree of thickness reduction; it can only achieve qualitative identification of damage and cannot support accurate quantitative assessment.

[0005] To overcome the aforementioned shortcomings, researchers have proposed an ultrasonic guided wave imaging method based on inversion theory. This type of method establishes a forward model and uses iterative algorithms to solve the objective function, achieving quantitative reconstruction of defect parameters. Typical iterative inversion methods include Born approximation iteration and modified Born iteration. While these methods can theoretically achieve high-precision quantitative imaging, they face challenges in computational efficiency in practical applications. Traditional iterative inversion methods typically start iterating from zero or random initial values. Because the initial values ​​differ significantly from the true solution, a large number of iterations are required to converge to satisfactory accuracy, resulting in long computation times and high computational resource consumption, making it difficult to meet the real-time requirements of engineering applications. Summary of the Invention

[0006] To address the aforementioned issues, this invention provides a quantitative ultrasonic guided wave imaging method and system based on iterative solution of initial values. This method utilizes a ring-shaped acquisition array and ultrasonic transducers to acquire guided wave signals from different paths. By first estimating the initial values ​​and then iteratively optimizing, it continuously approximates the true results, thereby achieving thickness imaging of the detection area and enabling quantitative evaluation of flat plate structures.

[0007] The technical solution of the present invention is as follows: A quantitative imaging method for ultrasonic guided waves, based on iterative solution of initial values, is used for thickness measurement of an object by ultrasonic waves. The method includes the following steps: S1. Build a sensor array to collect ultrasonic signals, extract ultrasonic propagation time information, calculate the group velocity distribution in the detection area, and convert the group velocity distribution into a phase velocity distribution. S2, using the phase velocity distribution of ultrasound to construct the initial value of the objective function for calculation; S3, calculate the theoretical scattering field using the initial value of the objective function, and then calculate the difference between the theoretical scattering field and the actual scattering field; S4. Update the objective function using an iterative optimization algorithm until the difference between the theoretical scattering field and the actual scattering field is less than a preset value, and obtain the final objective function. S5. Construct the mapping relationship between the final objective function and the thickness of the measured object, and output the quantitative imaging results.

[0008] Furthermore, in S1, the sensor array is a ring-shaped ultrasonic sensor array.

[0009] Furthermore, in S1, the extracted ultrasonic propagation time information is the arrival time T of each direct wave in the ultrasonic wave. i Let i represent the propagation path; divide the area to be detected into N grids, and calculate the length L of the segment between each propagation path and the grid. j j is the grid number; Using a single-layer neural network algorithm, the group velocity distribution in the detection region is quickly calculated. Then use the dispersion curve to Converted to phase velocity distribution .

[0010] Furthermore, in S2, the method for calculating the initial value of the objective function using the phase velocity distribution is specifically as follows: the wave number k at grid j is... j Considered as being related to the internal refractive index n j Related functions, define related functions as ,in It is the phase velocity of the ultrasonic guided wave propagation in the defect-free region; the initial objective function O0 is calculated from nj: , where k0 is the wavenumber of the defect-free region.

[0011] Furthermore, in S3, the method for calculating the scattered field is as follows: P (s) =DOP (t) Among them, P (s) Let P be the scattered field, D be the result of the Green's function integral including the defect, and P be the result of the scattered field. (t) The total field is O; O is the objective function; substituting the initial objective function O0, the theoretical scattering field P0 is obtained. (s) =DO0P (t) ; The actual scattered field is obtained by acquiring signals using ultrasonic guided waves: In the time domain, the incident field signal excluding the defect is subtracted from the full-field signal including the defect to obtain the time-domain scattered field signal. A fast Fourier transform is performed on the time-domain scattered field signal, and the frequency domain result at the center frequency is extracted to obtain the actual scattered field result P. real (s) ; Calculate the difference between the theoretical and actual scattered fields .

[0012] Furthermore, in S4, the iterative optimization algorithm is a modified Born iterative method.

[0013] Furthermore, in S4, the modified Born iteration method is as follows: in each iteration, the objective function O is recalculated. k and the Green's function integral D containing defects k Where the subscript k represents the iteration number; D k The calculation formula is D k =D(IO k C) -1 Where I is the identity matrix and C is the Green's function integral matrix without defects; the theoretical scattering field result obtained in the k-th iteration is P. k (s) =D k O k P k (t) P k (t) For the entire field in the k-th iteration; P k (t) =(I-CO k ) -1 P (in) P (in) The incident field is given; finally, the difference between the theoretical and actual scattered fields is calculated: P k (s) =P real (s) -P k(s) .

[0014] An ultrasonic guided wave quantitative imaging system based on iterative solution of initial value estimation is disclosed. This system, used for performing the aforementioned ultrasonic guided wave quantitative imaging based on iterative solution of initial value estimation, includes a sensor array acquisition module, a signal processing module, an objective function calculation module, a scattered field calculation module, an iterative optimization module, and an imaging module. The signal processing module is electrically connected to the sensor array acquisition module and is used to extract propagation time information, calculate the group velocity distribution of the detection area, and convert it into a phase velocity distribution. The objective function calculation module is electrically connected to the signal processing module and is used to construct the initial value of the objective function using the velocity information. The scattered field calculation module is electrically connected to both the objective function calculation module and the signal processing module and is used to calculate the deviation between the theoretical scattered field and the measured scattered field. The iterative optimization module is electrically connected to both the scattered field calculation module and the objective function calculation module and is used to optimize the objective function using an iterative algorithm. The imaging module is electrically connected to the iterative optimization module and is used to establish the mapping relationship between the objective function and the thickness of the measured object, and output the quantitative imaging results.

[0015] Furthermore, the sensor array acquisition module contains 64 ultrasonic transducers, which are arranged at equal angles on the circumference and use a one-to-many method to acquire ultrasonic signals.

[0016] The advantages of this invention are as follows: 1. A technological leap from qualitative to quantitative analysis has been achieved. The initial value of the group velocity distribution is estimated by converting it into the phase velocity distribution, and then the modified Born iterative algorithm is used for optimization and solution. For the equilateral triangle thinning defect with a side length of 80mm, the defect shape recognition accuracy reaches 100%, the size measurement error is less than 3%, and the thickness reconstruction error is less than 5%, which significantly improves the accuracy and stability of ultrasonic guided wave imaging.

[0017] 2. The computational efficiency has been optimized. Due to the accurate prediction of the initial value, the number of iterations is reduced by about 55% compared with the traditional method. The single imaging time is shortened from about 18 minutes to about 9 minutes, and the consumption of computing resources is reduced by about 40%, saving a lot of computing resources and time costs, and improving the feasibility of engineering applications.

[0018] 3. The modified Born iterative method, by correcting the Green's function in each round, reduces the inversion error of strong scattering defects with a thickness reduction of more than 50% from 15-20% in the traditional Born approximation to less than 5%, thereby improving the inversion accuracy of strong scattering defects and significantly improving the stability and repeatability of imaging results.

[0019] 4. This invention is applicable to the quantitative testing of various large plate and shell structures and has broad application prospects in aerospace, shipbuilding, petrochemical and other fields. It can reliably achieve quantitative assessment and provide accurate basis for structural safety evaluation and maintenance decisions. Attached Figure Description

[0020] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. The drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0021] Figure 1 This is a circular array diagram for acquiring ultrasonic guided wave signals according to the present invention.

[0022] Figure 2 This is a schematic diagram of the steps of the method of the present invention.

[0023] Figure 3 This is a diagram showing the actual defect distribution of the aluminum plate detected by the present invention.

[0024] Figure 4 The images are the initial and final imaging results based on the estimated values ​​of this invention. Detailed Implementation

[0025] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0026] The features and illustrative embodiments of various aspects of the present invention will now be described in detail. Numerous specific details are set forth in the following detailed description to provide a thorough understanding of the invention. However, it will be apparent to those skilled in the art that the invention may be practiced without requiring some of these specific details. The following description of embodiments is merely intended to provide a better understanding of the invention by illustrating examples of the invention. The invention is by no means limited to any specific setups and methods set forth below, but covers any improvements, substitutions, and modifications to structures, methods, and devices without departing from the spirit of the invention. Well-known structures and techniques are not shown in the drawings and the following description to avoid unnecessarily obscuring the invention.

[0027] In the description of this invention, it should be noted that the directions or positional relationships indicated by terms such as "center," "upper," "lower," "left," "right," "vertical," "horizontal," "inner," and "outer" are based on the directions or positional relationships shown in the accompanying drawings and are only for the convenience of describing and simplifying the invention, and should not be construed as limiting the invention. Furthermore, the use of ordinal numbers (e.g., "first and second," etc.) is for distinguishing objects and is not limited to this order, and should not be construed as indicating or implying relative importance.

[0028] In the description of this invention, it should be noted that, unless otherwise explicitly specified and limited, the terms "installation," "connection," and "linking" should be interpreted broadly, encompassing both direct connection and indirect connection via an intermediate medium. Those skilled in the art can understand the specific meaning of these terms in this invention based on the specific circumstances.

[0029] It should be noted that, unless otherwise specified, the embodiments of the present invention and the features thereof can be combined with each other, and the various embodiments can be referenced and cited in each other. The present invention will now be described in detail with reference to the accompanying drawings and embodiments.

[0030] First embodiment: A quantitative imaging method for ultrasonic guided waves, based on iterative solution of initial values, is used for thickness measurement of an object by ultrasonic waves. The method includes the following steps: S1. Build a sensor array to collect ultrasonic signals, extract ultrasonic propagation time information, calculate the group velocity distribution in the detection area, and convert the group velocity distribution into a phase velocity distribution. S2, using the phase velocity distribution of ultrasound to construct the initial value of the objective function for calculation; S3, calculate the theoretical scattering field using the initial value of the objective function, and then calculate the difference between the theoretical scattering field and the actual scattering field; S4. Update the objective function using an iterative optimization algorithm until the difference between the theoretical scattering field and the actual scattering field is less than a preset value, and obtain the final objective function. S5. Construct the mapping relationship between the final objective function and the thickness of the measured object, and output the quantitative imaging results.

[0031] In S1, the sensor array is a ring-shaped ultrasonic sensor array.

[0032] In S1, the extracted ultrasonic propagation time information is the arrival time T of each direct wave in the ultrasonic wave. i Let i represent the propagation path; divide the area to be detected into N grids, and calculate the length L of the segment between each propagation path and the grid. j j is the grid number; Using a single-layer neural network algorithm, the group velocity distribution in the detection region is quickly calculated. Then use the dispersion curve to Converted to phase velocity distribution .

[0033] In S2, the method for calculating the initial value of the objective function using the phase velocity distribution is as follows: the wave number k at grid j is... j Considered as being related to the internal refractive index n j Related functions, define related functions as ,in It is the phase velocity of the ultrasonic guided wave propagation in the defect-free region; the initial objective function O0 is calculated from nj: , where k0 is the wavenumber of the defect-free region.

[0034] In S3, the method for calculating the scattered field is as follows: P (s) =DOP (t) Among them, P (s) Let P be the scattered field, D be the result of the Green's function integral including the defect, and P be the result of the scattered field. (t) The total field is O; O is the objective function; substituting the initial objective function O0, the theoretical scattering field P0 is obtained. (s) =DO0P (t) ; The actual scattered field is obtained by acquiring signals using ultrasonic guided waves: In the time domain, the incident field signal excluding the defect is subtracted from the full-field signal including the defect to obtain the time-domain scattered field signal. A fast Fourier transform is performed on the time-domain scattered field signal, and the frequency domain result at the center frequency is extracted to obtain the actual scattered field result P. real (s) ; Calculate the difference between the theoretical and actual scattered fields .

[0035] In S4, the iterative optimization algorithm is a modified Born iterative method.

[0036] In S4, the modified Born iteration method is as follows: in each iteration, the objective function O is recalculated. k and the Green's function integral D containing defects k Where the subscript k represents the iteration number; D k The calculation formula is D k =D(IO k C) -1 Where I is the identity matrix and C is the Green's function integral matrix without defects; the theoretical scattering field result obtained in the k-th iteration is P. k (s) =D k O k P k (t) P k(t) For the entire field in the k-th iteration; P k (t) =(I-CO k ) -1 P (in) P (in) The incident field is given; finally, the difference between the theoretical and actual scattered fields is calculated: P k (s) =P real (s) -P k (s) .

[0037] An ultrasonic guided wave quantitative imaging system based on iterative solution of initial value estimation is disclosed. This system, used for performing the aforementioned ultrasonic guided wave quantitative imaging based on iterative solution of initial value estimation, includes a sensor array acquisition module, a signal processing module, an objective function calculation module, a scattered field calculation module, an iterative optimization module, and an imaging module. The signal processing module is electrically connected to the sensor array acquisition module and is used to extract propagation time information, calculate the group velocity distribution of the detection area, and convert it into a phase velocity distribution. The objective function calculation module is electrically connected to the signal processing module and is used to construct the initial value of the objective function using the velocity information. The scattered field calculation module is electrically connected to both the objective function calculation module and the signal processing module and is used to calculate the deviation between the theoretical scattered field and the measured scattered field. The iterative optimization module is electrically connected to both the scattered field calculation module and the objective function calculation module and is used to optimize the objective function using an iterative algorithm. The imaging module is electrically connected to the iterative optimization module and is used to establish the mapping relationship between the objective function and the thickness of the measured object, and output the quantitative imaging results.

[0038] The sensor array acquisition module contains 64 ultrasonic transducers, which are arranged at equal angles on the circumference and use a one-to-many method to acquire ultrasonic signals.

[0039] Second embodiment: A quantitative imaging method for ultrasonic guided waves using iterative initial value estimation includes the following steps: deploying a sensor array to acquire ultrasonic guided wave signals, extracting ultrasonic guided wave propagation time information, calculating the wave velocity distribution in the area to be detected, and converting the wave velocity distribution into a physical quantity suitable for inversion; constructing an initial value for the inversion objective function using the velocity information; calculating the theoretical field based on the initial value, and calculating the deviation between the theoretical value and the measured value; optimizing the objective function using an iterative algorithm, setting an iteration termination condition, and stopping the iteration when the deviation reaches a preset accuracy; establishing a mapping between the objective function and the physical quantity, and outputting the quantitative detection result.

[0040] The arrival time of each propagation path is extracted using wavelet transform. The area to be detected is divided into multiple grids. The length of the intercept segment between each propagation path and the grid is calculated. The group velocity distribution is calculated using a single-layer neural network algorithm and then converted into a phase velocity distribution.

[0041] The phase velocity distribution is converted into refractive index, which is defined as the ratio of the phase velocity in the defect-free region to the phase velocity at the grid. The initial value of the objective function is calculated using the refractive index, which is the product of the square of the wavenumber in the defect-free region and the square of the refractive index minus 1.

[0042] The theoretical field is obtained through Green's function integration, matrix operations of the objective function and the entire field. The measured value is obtained by subtracting the incident field signal without defects from the full-field signal containing defects to obtain the time-domain scattered field signal, and then performing a fast Fourier transform on the time-domain scattered field signal and extracting the frequency domain result at the center frequency.

[0043] The iterative algorithm is a modified Born iterative algorithm, in which the objective function and the Green's function integral including the defect are recalculated in each iteration. The Green's function integral including the defect is obtained by multiplying the Green's function integral matrix and the identity matrix by the inverse of the product of the objective function and the Green's function integral matrix without the defect.

[0044] The objective function increment is solved using the modified Born iterative algorithm, and the objective function is updated using the objective function increment to establish a mapping relationship between phase velocity and objective function. The phase velocity is then converted into thickness using the dispersion curve.

[0045] This invention also provides a quantitative imaging system for ultrasonic guided waves, comprising: a sensor array acquisition module containing multiple ultrasonic sensors for acquiring ultrasonic guided wave signals; a signal processing module electrically connected to the sensor array acquisition module for extracting propagation time information, calculating wave velocity distribution, and converting it into physical quantities suitable for inversion; an objective function calculation module electrically connected to the signal processing module for constructing initial values ​​of the inverted objective function using velocity information; a scattered field calculation module electrically connected to the objective function calculation module and the sensor array acquisition module for calculating the deviation between theoretical and measured values; an iterative optimization module electrically connected to the scattered field calculation module and the objective function calculation module for optimizing the objective function using an iterative algorithm; and an imaging module electrically connected to the iterative optimization module for establishing a mapping between the objective function and physical quantities and outputting quantitative detection results.

[0046] Third embodiment: This invention relates to a quantitative imaging method for ultrasonic guided waves using iterative solutions of estimated initial values. The method includes: constructing an ultrasonic guided wave acquisition test platform; the test specimen includes a 600mm*600mm*3mm aluminum plate; the detection area is 400mm*400mm*3mm; 64 transducers are arranged at equal angles on a 400mm diameter circle; and data is acquired using a one-transmitter-multiple-receiver method. Figure 1 As shown. After one ultrasonic guided wave excitation was completed, the excitation probe was changed and the data was collected again. A total of 64*63 sets of data were collected. A boundary absorption layer was arranged around the aluminum plate to suppress the reflected wave signal.

[0047] The testing instruments for the ultrasonic guided wave acquisition experimental platform include: an NI data acquisition card, a power amplifier, a transducer, a signal generator, and a PC containing testing software. The signal generator produces a 5-cycle Hanning window modulated sinusoidal signal with a center frequency of 200kHz. This signal is amplified by the power amplifier and then transmitted to the transducer to generate ultrasonic guided waves. After receiving the signal, the transducer transmits it to the data acquisition card for analog-to-digital conversion. The final received guided wave signal is acquired and saved by the host computer software.

[0048] After the ultrasonic guided wave signal acquisition is completed, the imaging method provided by this invention patent includes the following steps, such as... Figure 2 As shown: S1. Construct a ring array to acquire ultrasonic guided wave signals, extract the direct wave time, calculate the group velocity distribution of the area to be detected, and convert it into a phase velocity distribution. S2. Calculate the initial value of the objective function using the phase velocity distribution; S3. Calculate the theoretical scattering field using the initial value of the objective function, and calculate the difference between the theoretical scattering field and the actual scattering field; S4. Update the objective function using the modified Born iterative method, and stop iterating when the difference in the scattered field reaches a certain accuracy. S5. Obtain the final objective function, construct the mapping relationship between the objective function and the thickness, and realize quantitative imaging.

[0049] In step S1, a ring array is constructed to acquire ultrasonic guided wave signals, and wavelet transform is used to extract the arrival time T of each direct wave. i Let i represent each path. Divide the region to be detected into N grids, and calculate the length L of the segment between each propagation path and the grid. j j=1,2,...,N represents the grid number. Using the formula... Using a single-layer neural network algorithm, the group velocity distribution can be calculated quickly. The dispersion curve is then converted into a phase velocity distribution. .

[0050] The method for calculating the initial value of the objective function using the phase velocity distribution in step S2 is as follows: When dealing with guided wave tomography-related problems, the area to be detected containing defects is usually considered as a non-uniform medium, and the wave number k at grid j is... j It can be regarded as related to the internal refractive index n j The relevant function is defined as follows: ,in It is the phase velocity of the ultrasonic guided wave propagating in the defect-free region. The initial objective function O0 is given by n. j The calculation yields the following formula: , where k0 is the wavenumber of the defect-free region.

[0051] In step S3, the formula for calculating the theoretical scattering field is: , where P (s) Let P be the scattered field, D be the result of the Green's function integral including the defect, and P be the result of the scattered field. (t) For the entire field. The initial objective function O0 can be derived from n j The theoretical scattering field P0 can be calculated from this. (s) =DO0P (t) 。 The actual scattered field is obtained by acquiring signals using ultrasonic guided waves. The calculation method involves subtracting the incident field signal excluding the defect from the full-field signal including the defect in the time domain to obtain the time-domain scattered field signal. Performing a Fast Fourier Transform on the time-domain scattered field signal and extracting the frequency domain result at the center frequency yields the actual scattered field result P. real (s) Calculate the difference between the theoretical and actual scattered field. .

[0052] Step S4, the modified Born iteration method, is an improved method based on the Born approximation. In each iteration, it recalculates the objective function O. k and the Green's function integral D containing defects k , where the subscript k represents the iteration number. D k The calculation formula is D k =D(IO k C) -1, Where I is the identity matrix, and C is the Green's function integral matrix without defects. The theoretical scattering field result obtained in the k-th iteration is P. k (s) =D k O k P k (t) , P k (t) The total field for the k-th iteration is calculated using the formula P. k (t)=(I-CO k ) -1 P (in) ,P (in) The incident field is defined. Finally, the difference between the theoretical and actual scattered field is calculated. P k (s) =P real (s) -P k (s) .

[0053] In step S5, the final objective function is obtained after iteration to a certain precision. The specific calculation method is as follows: the increment of the objective function is solved using a modified Born iterative algorithm. ,in The objective function O is updated using this formula. k= O k-1 + O k The iteration stops once a certain level of accuracy is achieved, yielding the final objective function O. k。 No. k The mapping relationship between phase velocity and objective function after the next iteration is as follows: ,in It is the phase velocity of the ultrasonic guided wave propagation in a defect-free region. The phase velocity distribution obtained after the kth iteration is the final phase velocity distribution. The phase velocity can be directly converted into thickness using the dispersion curve. Therefore, the mapping relationship between the final objective function and the thickness can be established to realize the quantitative imaging of ultrasonic guided waves.

[0054] Specifically, in the embodiments provided by this invention patent, the imaging area is divided into 1793 grids, i.e., N=1793. Figure 3 The aluminum plate contains an actual defect, which is an equilateral triangle with a side length of 80 mm and a remaining thickness of 1 mm. Imaging is performed according to the method provided in this invention, and the thickness distribution of the aluminum plate after estimating the initial value is as follows. Figure 4 As shown in (a), it can be seen that the initial value evaluation method can simply depict the outline of the defect, but it cannot delineate the complete morphology of the defect, and the thickness reconstruction is also inaccurate. Based on this, continuous iteration is performed, and the final imaging result is as follows: Figure 4 As shown in (b), the thickness distribution and shape of the defect have been reconstructed to be very close to the true value, achieving a relatively ideal effect. Therefore, this method can be applied to the field of industrial non-destructive testing to achieve the purpose of quantitative evaluation.

[0055] The present invention also provides an ultrasonic guided wave quantitative imaging system, as shown in this embodiment, the system comprising: The sensor array acquisition module contains 64 ultrasonic transducers, which are arranged at equal angles on a circle with a diameter of 400mm. It uses a one-to-many transmission method to acquire guided wave signals and is used to acquire ultrasonic guided wave signals.

[0056] The signal processing module, electrically connected to the sensor array acquisition module, includes a wavelet transform unit, a grid partitioning unit, and a single-layer neural network unit. The wavelet transform unit, electrically connected to the sensor array acquisition module, is used to extract propagation time information; the grid partitioning unit, electrically connected to the wavelet transform unit, is used to partition the detection area into a grid and calculate the length of the cut-off segment; the single-layer neural network unit, electrically connected to the grid partitioning unit, is used to calculate the group velocity distribution and convert it into a phase velocity distribution.

[0057] The objective function calculation module is electrically connected to the signal processing module and is used to construct the initial value of the inverted objective function using phase velocity information.

[0058] The scattering field calculation module is electrically connected to the objective function calculation module and the sensor array acquisition module, and is used to calculate the deviation between the theoretical scattering field and the actual scattering field.

[0059] The iterative optimization module, electrically connected to the scattering field calculation module and the objective function calculation module, is used to optimize the objective function using the modified Born iterative algorithm.

[0060] The imaging module, electrically connected to the iterative optimization module, is used to establish the mapping between the objective function and thickness and output quantitative detection results.

[0061] This system, through the coordinated operation of six functional modules, realizes the complete technical process of the method of this invention, providing hardware and software support for the quantitative detection of flat plate structures and pipeline structures.

[0062] The above detailed embodiments are a description of the present invention. It should not be considered that the specific embodiments of the present invention are limited to these descriptions. For those skilled in the art, several simple deductions and substitutions can be made without departing from the concept of the present invention, and all of these should be considered to fall within the protection scope of the present invention.

Claims

1. A quantitative imaging method for ultrasonic guided waves using iterative solution of estimated initial values, used for measuring the thickness of an object by ultrasonic waves, characterized in that, Includes the following steps: S1. Build a sensor array to collect ultrasonic signals, extract ultrasonic propagation time information, calculate the group velocity distribution in the detection area, and convert the group velocity distribution into a phase velocity distribution. S2, using the phase velocity distribution of ultrasound to construct the initial value of the objective function for calculation; S3, calculate the theoretical scattering field using the initial value of the objective function, and then calculate the difference between the theoretical scattering field and the actual scattering field; S4. Update the objective function using an iterative optimization algorithm until the difference between the theoretical scattering field and the actual scattering field is less than a preset value, and obtain the final objective function. S5. Construct the mapping relationship between the final objective function and the thickness of the measured object, and output the quantitative imaging results.

2. The ultrasonic guided wave quantitative imaging method based on iterative solution of estimated initial values ​​according to claim 1, used for ultrasonic thickness measurement of an object, characterized in that, In S1, the sensor array is a ring-shaped ultrasonic sensor array.

3. In the quantitative imaging method for ultrasonic guided waves based on iterative solution of initial values ​​according to claim 2, in S1, the extracted ultrasonic wave propagation time information is the arrival time T of each direct wave in the ultrasonic wave. i Let i represent the propagation path; divide the area to be detected into N grids, and calculate the length L of the segment between each propagation path and the grid. j j is the grid number; Using a single-layer neural network algorithm, the group velocity distribution in the detection region is quickly calculated. Then use the dispersion curve to Converted to phase velocity distribution .

4. In the quantitative imaging method for ultrasonic guided waves based on iterative solution of initial values ​​according to claim 3, in S2, the method for calculating the initial value of the objective function using the phase velocity distribution specifically involves: calculating the wave number k at grid j... j Considered as being related to the internal refractive index n j Related functions, define related functions as ,in It is the phase velocity of the ultrasonic guided wave propagation in the defect-free region; the initial objective function O0 is calculated from nj: , where k0 is the wavenumber of the defect-free region.

5. In the quantitative imaging method for ultrasonic guided waves based on iterative solution of initial values ​​according to claim 4, in S3, the method for calculating the scattered field is as follows: P (s) =DOP (t) in, P (s) Let P be the scattered field, D be the result of the Green's function integral including the defect, and P be the result of the scattered field. (t) The total field is O; O is the objective function; substituting the initial objective function O0, the theoretical scattering field P0 is obtained. (s) =DO0P (t) ; The actual scattered field is obtained by acquiring signals using ultrasonic guided waves: In the time domain, the incident field signal excluding the defect is subtracted from the full-field signal including the defect to obtain the time-domain scattered field signal. A fast Fourier transform is performed on the time-domain scattered field signal, and the frequency domain result at the center frequency is extracted to obtain the actual scattered field result P. real (s) ; Calculate the difference between the theoretical and actual scattered fields. .

6. In the method for quantitative imaging of ultrasonic guided waves by iterative solution of estimated initial values ​​according to claim 5, in S4, the iterative optimization algorithm is a modified Born iterative method.

7. In the quantitative imaging method for ultrasonic guided waves based on iterative solution of initial value estimation according to claim 6, in S4, the modified Born iteration method is as follows: in each iteration, the objective function O is recalculated. k and the Green's function integral D containing defects k Where the subscript k represents the iteration number; D k The calculation formula is D k =D(IO k C) -1 Where I is the identity matrix and C is the Green's function integral matrix without defects; the theoretical scattering field result obtained in the k-th iteration is P. k (s) =D k O k P k (t) P k (t) For the entire field in the k-th iteration; P k (t) =(I-CO k ) -1 P (in) P (in) The incident field is given; finally, the difference between the theoretical and actual scattered fields is calculated: P k (s) =P real (s) -P k (s) 。 8. A quantitative ultrasonic guided wave imaging system for iterative solution of initial value estimation, used to run the quantitative ultrasonic guided wave imaging system for iterative solution of initial value estimation as described in claim 1, characterized in that, It includes a sensor array acquisition module, a signal processing module, an objective function calculation module, a scattered field calculation module, an iterative optimization module, and an imaging module. The signal processing module is electrically connected to the sensor array acquisition module and is used to extract propagation time information, calculate the group velocity distribution of the detection area, and convert it into a phase velocity distribution. The objective function calculation module is electrically connected to the signal processing module and is used to construct the initial value of the objective function using the velocity information. The scattering field calculation module is electrically connected to both the objective function calculation module and the signal processing module, and is used to calculate the deviation between the theoretical scattering field and the measured scattering field; the iterative optimization module is electrically connected to both the scattering field calculation module and the objective function calculation module, and is used to optimize the objective function using an iterative algorithm; the imaging module is electrically connected to the iterative optimization module, and is used to establish the mapping relationship between the objective function and the thickness of the measured object, and output quantitative imaging results.

9. The ultrasonic guided wave quantitative imaging system for iterative solution of estimated initial values ​​according to claim 8, characterized in that, The sensor array acquisition module contains 64 ultrasonic transducers, which are arranged at equal angles on the circumference and use a one-to-many method to acquire ultrasonic signals.

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