1. The defect quantification method based on the super-resolution ultrasonic image is characterized by comprising the following steps of:

performing time domain preprocessing on full matrix acquisition data formed by all ultrasonic echo signals of a measured object, and extracting related scattering signals of an extended target in the measured object, wherein the extended target is a linear defect with a certain length and angle in the measured object;

performing super-resolution imaging according to the relevant scattering signal of the extended target to obtain a super-resolution ultrasonic image of the extended target;

and carrying out image characteristic analysis and expansion target parameter evaluation on the super-resolution ultrasonic image to obtain the length and the angle of an expansion target.

2. The method for quantifying defects based on super-resolution ultrasound images as claimed in claim 1, wherein the time domain preprocessing is performed on the full matrix acquisition data formed by all the ultrasound echo signals of the object to be measured to extract the related scattering signals of the extended target in the object to be measured, comprising the steps of:

acquiring original ultrasonic images of the tested object according to full-matrix acquisition data formed by all ultrasonic echo signals of the tested object;

judging the area where the extended target appears in the obtained original ultrasonic image, and setting a rectangular frame to cover the area to form an extended target area;

calculating and defining a time domain window function according to the array element position of the linear array sensor and the extended target area and by combining the propagation speed of the ultrasonic wave in the measured object;

and performing time domain preprocessing on all ultrasonic echo signals of the tested object by using the time domain window function, and extracting the related scattering signals of the extended target.

3. The method for quantifying defects based on a super-resolution ultrasound image of claim 2, wherein the step of obtaining an original ultrasound image of the object to be measured from the full-matrix acquisition data formed by all the ultrasound echo signals of the object to be measured comprises:

and processing all ultrasonic echo signals of the measured object by using a delay superposition method to obtain an original ultrasonic image of the measured object.

4. The method for quantifying defects based on super-resolution ultrasound images of claim 2, wherein the time domain preprocessing is performed on the full matrix acquisition data formed by all the ultrasound echo signals of the object to be measured to extract the related scattering signals of the extended target in the object to be measured, and further comprising the steps of:

directly coupling a linear array sensor with the measured object, wherein the measured object internally comprises an extended target as an imaging object;

selecting any pair of array element combinations of the linear array transducer as an exciting array element and a receiving array element respectively to obtain ultrasonic echo signals;

and sequentially executing the steps until all array element combinations of the linear array sensor acquire ultrasonic echo signals, and forming all acquired ultrasonic echo signals into full-matrix acquisition data.

5. The method for defect quantification based on super-resolution ultrasound images of claim 1, wherein the super-resolution imaging is performed according to the relevant scattering signal of the extended target to obtain the super-resolution ultrasound image of the extended target, comprising the steps of:

performing time domain-frequency domain conversion on the related scattering signals of the extended target, constructing an array response matrix in a given frequency bandwidth range, and performing singular value decomposition on the array response matrix to obtain singular values and corresponding singular vectors;

dividing singular vectors into a signal subspace and a noise subspace based on a distribution rule of singular values in a given frequency bandwidth range;

defining a direction vector, and giving a PC-MUSIC imaging function based on the signal subspace and the direction vector to obtain a super-resolution ultrasonic image of the extended target.

6. The method for quantifying defects based on a super-resolution ultrasound image according to claim 1, wherein the method for quantifying defects based on a super-resolution ultrasound image comprises the steps of performing image feature analysis and expansion target parameter evaluation on the super-resolution ultrasound image to obtain the length and the angle of an expansion target:

setting an intensity threshold, searching a pixel point set with the intensity greater than or equal to the threshold in the super-resolution ultrasonic image, and acquiring coordinates corresponding to each pixel point in the set;

drawing a super-resolution image intensity contour map according to the pixel point set and coordinates corresponding to all pixel points in the set;

searching pixel points corresponding to the maximum intensity value of the left end and the maximum intensity value of the right end in the contour map, and respectively defining the coordinates of the two pixel points as evaluation coordinates of the positions of the two ends of the extended target;

and calculating the length and the angle of the extension target based on the evaluation coordinates of the positions of the two ends of the extension target.

7. The method for quantifying defects based on super-resolution ultrasound images of claim 6, wherein the super-resolution ultrasound images are subjected to image feature analysis and expansion target parameter evaluation to obtain the length and angle of an expansion target, further comprising the steps of:

and obtaining a calculated length error and a calculated angle error of the extended target according to the calculated length and the calculated angle of the extended target and the actual length and the actual angle obtained by actual measurement of the extended target.

8. A defect quantification apparatus based on a super-resolution ultrasound image, comprising:

the device comprises a scattering signal extraction module, a data acquisition module and a data acquisition module, wherein the scattering signal extraction module is used for performing time domain preprocessing on full matrix acquisition data formed by all ultrasonic echo signals of a measured object and extracting related scattering signals of an extended target in the measured object, and the extended target is a linear defect with a certain length and angle in the measured object;

the super-resolution imaging module is used for performing super-resolution imaging according to the relevant scattering signal of the extended target to obtain a super-resolution ultrasonic image of the extended target;

and the extended target parameter evaluation module is used for carrying out image feature analysis and extended target parameter evaluation on the super-resolution ultrasonic image to obtain the length and the angle of an extended target.

9. An electronic device comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, the processor when executing the program implementing the method of defect quantification based on super resolution ultrasound images according to any of claims 1 to 7.

10. A storage medium comprising a stored program which, when executed, controls a device on which the storage medium is located to perform the method for defect quantification based on super-resolution ultrasound images according to any one of claims 1 to 7.

Background

In the field of ultrasonic nondestructive testing, the imaging testing of a tested object by utilizing an ultrasonic phased array is a main development direction, and the ultrasonic phased array is researched and applied in the fields of aerospace, nuclear power stations, railways, infrastructure and the like, so that obvious social and economic benefits are generated. And evaluating the internal condition of the object to be tested based on the ultrasonic image, finding defects in time, accurately extracting key information such as the size, the direction and the like of the defect, and making scientific countermeasures. The high-quality ultrasonic image is the basis for accurately evaluating the defects, the resolution is an important technical index for evaluating the quality of the ultrasonic image, and the higher the resolution is, the better the quality of the ultrasonic image is.

The conventional ultrasonic imaging method is limited by the diffraction of the acoustic waves, and the resolution of the conventional ultrasonic imaging method complies with the Rayleigh criterion, namely, the obtained ultrasonic image cannot identify defect detail information, so that misjudgment is easily caused, and serious results are caused. The phase coherent multi-signal classification method PC-MUSIC based on the ultrasonic time reversal theory is a typical super-resolution imaging method, can overcome the diffraction limit of sound waves, breaks the Rayleigh criterion, and has great application prospect. However, in the field of practical application, when an imaging object is an extended target with a certain size and angle, such as a straight line, the size of the imaging object is larger than the wavelength of the ultrasonic wave, and the imaging object cannot be regarded as an ideal point scatterer, and the existing super-resolution imaging method is not applied to accurately evaluating the length, the angle and the like of the extended target.

Disclosure of Invention

The method comprises the steps of obtaining a super-resolution image, obtaining a defect image by using a super-resolution imaging method, and carrying out quantitative evaluation on an extended target with a certain size and angle by using a super-resolution imaging method.

The application adopts the following technical scheme:

a defect quantification method based on a super-resolution ultrasonic image comprises the following steps:

performing time domain preprocessing on full matrix acquisition data formed by all ultrasonic echo signals of a measured object, and extracting related scattering signals of an extended target in the measured object, wherein the extended target is a linear defect with a certain length and angle in the measured object;

performing super-resolution imaging according to the relevant scattering signal of the extended target to obtain a super-resolution ultrasonic image of the extended target;

and carrying out image characteristic analysis and expansion target parameter evaluation on the super-resolution ultrasonic image to obtain the length and the angle of an expansion target.

Further, the time domain preprocessing is performed on the full matrix acquisition data formed by all the ultrasonic echo signals of the measured object, and the relevant scattering signals of the extended target in the measured object are extracted, including the steps of:

acquiring original ultrasonic images of the tested object according to full-matrix acquisition data formed by all ultrasonic echo signals of the tested object;

judging the area where the extended target appears in the obtained original ultrasonic image, and setting a rectangular frame to cover the area to form an extended target area;

calculating and defining a time domain window function according to the array element position of the linear array sensor and the extended target area and by combining the propagation speed of the ultrasonic wave in the measured object;

and performing time domain preprocessing on all ultrasonic echo signals of the tested object by using the time domain window function, and extracting the related scattering signals of the extended target.

Further, acquiring an original ultrasound image of the object to be measured according to full-matrix acquisition data formed by all the ultrasound echo signals of the object to be measured, specifically including:

and processing all ultrasonic echo signals of the measured object by using a delay superposition method to obtain an original ultrasonic image of the measured object.

Further, the time domain preprocessing is performed on the full matrix acquisition data formed by all the ultrasonic echo signals of the measured object, and the relevant scattering signals of the extended target in the measured object are extracted, and the method further comprises the following steps:

directly coupling a linear array sensor with the measured object, wherein the measured object internally comprises an extended target as an imaging object;

selecting any pair of array element combinations of the linear array transducer as an exciting array element and a receiving array element respectively to obtain ultrasonic echo signals;

and sequentially executing the steps until all array element combinations of the linear array sensor acquire ultrasonic echo signals, and forming all acquired ultrasonic echo signals into full-matrix acquisition data.

Further, performing super-resolution imaging according to the relevant scattering signal of the extended target to obtain a super-resolution ultrasound image of the extended target, comprising the steps of:

performing time domain-frequency domain conversion on the related scattering signals of the extended target, constructing an array response matrix in a given frequency bandwidth range, and performing singular value decomposition on the array response matrix to obtain singular values and corresponding singular vectors;

dividing singular vectors into a signal subspace and a noise subspace based on a distribution rule of singular values in a given frequency bandwidth range;

defining a direction vector, and giving a PC-MUSIC imaging function based on the signal subspace and the direction vector to obtain a super-resolution ultrasonic image of the extended target.

Further, image feature analysis and expansion target parameter evaluation are carried out on the super-resolution ultrasonic image, and the length and the angle of an expansion target are obtained, and the method comprises the following steps:

setting an intensity threshold, searching a pixel point set with the intensity greater than or equal to the threshold in the super-resolution ultrasonic image, and acquiring coordinates corresponding to each pixel point in the set;

drawing a super-resolution image intensity contour map according to the pixel point set and coordinates corresponding to all pixel points in the set;

searching pixel points corresponding to the maximum intensity value of the left end and the maximum intensity value of the right end in the contour map, and respectively defining the coordinates of the two pixel points as evaluation coordinates of the positions of the two ends of the extended target;

and calculating the length and the angle of the extension target based on the evaluation coordinates of the positions of the two ends of the extension target.

Further, the method comprises the steps of performing image feature analysis and expansion target parameter evaluation on the super-resolution ultrasonic image to obtain the length and the angle of an expansion target, and further comprises the following steps:

and obtaining a calculated length error and a calculated angle error of the extended target according to the calculated length and the calculated angle of the extended target and the actual length and the actual angle obtained by actual measurement of the extended target.

Another aspect of the present application further provides a defect quantification apparatus based on a super-resolution ultrasound image, including:

the device comprises a scattering signal extraction module, a data acquisition module and a data acquisition module, wherein the scattering signal extraction module is used for performing time domain preprocessing on full matrix acquisition data formed by all ultrasonic echo signals of a measured object and extracting related scattering signals of an extended target in the measured object, and the extended target is a linear defect with a certain length and angle in the measured object;

the super-resolution imaging module is used for performing super-resolution imaging according to the relevant scattering signal of the extended target to obtain a super-resolution ultrasonic image of the extended target;

and the extended target parameter evaluation module is used for carrying out image feature analysis and extended target parameter evaluation on the super-resolution ultrasonic image to obtain the length and the angle of an extended target.

The application also provides an electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor implements the method for defect quantification based on super-resolution ultrasound images when executing the program.

The present application also provides a storage medium including a stored program, and when the program runs, the apparatus on which the storage medium is located is controlled to execute the defect quantification method based on the super-resolution ultrasound image.

Compared with the prior art, the method has the following beneficial effects:

the method comprises the steps of firstly, carrying out time domain preprocessing on full matrix acquisition data formed by all ultrasonic echo signals of a measured object, and extracting related scattering signals of an extended target in the measured object; then, performing super-resolution imaging according to the relevant scattering signal of the extended target to obtain a super-resolution ultrasonic image of the extended target; and finally, carrying out image characteristic analysis and expansion target parameter evaluation on the super-resolution ultrasonic image to obtain the length and the angle of the expansion target. The method and the device can quantitatively detect the extended target with a certain size (the size is larger than the wavelength of the ultrasonic wave) and angle, such as a straight line, and accurately estimate the length and the angle of the extended target by analyzing the super-resolution ultrasonic image, so that the quantitative estimation of the extended target is realized, the related parameters of the extended target are accurately mastered, and the defects are more comprehensively detected and estimated during ultrasonic nondestructive detection.

In addition to the objects, features and advantages described above, other objects, features and advantages will be apparent from the present application. The present application will now be described in further detail with reference to the accompanying drawings.

Drawings

The accompanying drawings, which are incorporated in and constitute a part of this application, illustrate embodiments of the application and, together with the description, serve to explain the application and are not intended to limit the application. In the drawings:

fig. 1 is a flowchart illustrating a defect quantification method based on a super-resolution ultrasound image according to a preferred embodiment of the present application.

Fig. 2 is a schematic representation of the object of the present application, which is an extension of the present application (straight-line grooving).

Fig. 3 is a flow chart illustrating the detailed sub-steps of step S1 in the preferred embodiment of the present application.

FIG. 4 is a schematic diagram of the original ultrasound image and the extended target area obtained in the preferred embodiment of the present application.

Fig. 5 is a schematic diagram of the ultrasonic echo signal and the extended target-related scattering signal obtained in the preferred embodiment of the present application.

Fig. 6 is a flow chart illustrating the detailed sub-steps of step S1 in another preferred embodiment of the present application.

Fig. 7 is a schematic view of the linear array sensor coupled to the measured object in the preferred embodiment of the present application.

Fig. 8 is a flow chart illustrating the detailed substeps of step S2 in the preferred embodiment of the present application.

FIG. 9 is a diagram of a singular value distribution curve in a preferred embodiment of the present application.

Fig. 10 is a flow chart illustrating the detailed substeps of step S3 in the preferred embodiment of the present application.

FIG. 11 is a super-resolution ultrasound image obtained in the preferred embodiment of the present application.

Figure 12 is a line contour plot of the intensities obtained in the preferred embodiment of the present application.

Fig. 13 is a flow chart illustrating the detailed substeps of step S3 in another preferred embodiment of the present application.

FIG. 14 is a block diagram of a defect quantification apparatus based on super-resolution ultrasound images according to a preferred embodiment of the present application.

Fig. 15 is a schematic block diagram of an electronic device entity according to a preferred embodiment of the present application.

Fig. 16 is an internal structural view of a computer device according to a preferred embodiment of the present application.

In the figure: 1. a linear array sensor; 2. a measured object; 3. and (4) expanding the target.

Detailed Description

It should be noted that the embodiments and features of the embodiments in the present application may be combined with each other without conflict. The present application will be described in detail below with reference to the embodiments with reference to the attached drawings.

As shown in fig. 1, a preferred embodiment of the present application provides a defect quantification method based on a super-resolution ultrasound image, including the steps of:

s1, performing time domain preprocessing on the full matrix acquisition data formed by all ultrasonic echo signals of the measured object, and extracting related scattering signals of an extended target in the measured object, wherein the extended target is a linear defect with a certain length and angle in the measured object;

s2, performing super-resolution imaging according to the relevant scattering signal of the extended target to obtain a super-resolution ultrasonic image of the extended target;

s3, performing image feature analysis and expansion target parameter evaluation on the super-resolution ultrasonic image, and acquiring the length and angle of an expansion target.

The phase coherent multi-signal classification method PC-MUSIC based on the ultrasonic time reversal theory is a typical super-resolution imaging method, the existing research focuses on the positioning of ideal point scatterers by the PC-MUSIC method, the size of the ultrasonic wave is smaller than the wavelength of the ultrasonic wave, however, in the practical application field, the imaging object is an extended target with a certain size and angle, the size of the scattering body is larger than the wavelength of the ultrasonic wave, and the scattering body can not be regarded as an ideal point scattering body, such as the notch shown in figure 2, through actual measurement, the actual length L of the super-resolution image is 5mm, the actual included angle theta between the super-resolution image and the x axis is 45 degrees, aiming at the extension target (linear grooving), the super-resolution image obtained by the super-resolution imaging method PC-MUSIC can not directly obtain the actual length L and the actual included angle theta, therefore, it is necessary to analyze image features and propose a quantization method to accurately quantize the parameters of the notch.

The embodiment provides a defect quantification method based on a super-resolution ultrasonic image, which comprises the steps of firstly, carrying out time domain preprocessing on full matrix acquisition data formed by all ultrasonic echo signals of a measured object, and extracting related scattering signals of an extended target in the measured object; then, performing super-resolution imaging according to the relevant scattering signal of the extended target to obtain a super-resolution ultrasonic image of the extended target; and finally, carrying out image characteristic analysis and expansion target parameter evaluation on the super-resolution ultrasonic image to obtain the length and the angle of the expansion target. The embodiment can quantitatively detect the extended target with a certain size (the size is larger than the wavelength of the ultrasonic wave) and a certain angle, such as linear grooving and the like, and accurately estimate the length and the angle of the extended target by analyzing the super-resolution ultrasonic image to realize quantitative estimation of the extended target, so that the related parameters of the extended target are accurately mastered, and more comprehensive detection and estimation of defects are realized during ultrasonic nondestructive detection. The embodiment realizes the quantitative evaluation of the extended target based on the PC-MUSIC method, fully exerts the maximum advantage of the PC-MUSIC method and realizes the automation of defect detection in the future.

In one possible implementation manner, as shown in fig. 3, the performing time domain preprocessing on the full matrix acquired data formed by all the ultrasonic echo signals of the measured object to extract the relevant scattering signals of the extended target in the measured object includes the steps of:

s11, acquiring an original ultrasonic image of the measured object according to the full-matrix acquisition data formed by all the ultrasonic echo signals of the measured object (as shown in figure 4);

s12, judging the area where the expansion target appears in the obtained original ultrasonic image, and setting a rectangular frame to cover the area to form an expansion target area A (shown as a dashed line frame A in FIG. 4);

s13, calculating and defining a time domain window function according to the array element position of the linear array sensor and the extended target area A by combining the propagation speed c of the ultrasonic wave in the measured object, wherein the specific calculation process can refer to journal articles (Chengguang FAN et al, Preprocessing of the full matrix capture data for time-reversed-based super-resolution imaging), and is not described herein again;

s14, performing time domain preprocessing on all ultrasonic echo signals of the tested object by using the time domain window function, and extracting an extended target related scattering signal S (t):

s(t)＝h(t)w(t) (1)

wherein w (t) is a time domain window function, and h (t) is an ultrasonic echo signal, as shown in fig. 5.

In one possible implementation manner, acquiring an original ultrasound image of a measured object according to full-matrix acquisition data formed by all ultrasound echo signals of the measured object specifically includes:

all ultrasonic echo signals of the measured object are processed by a delay and sun (DAS) method to obtain an original ultrasonic image of the measured object. Compared with other methods, the delay and sun (DAS) method has the advantages of simple execution process and high imaging speed, and can scan the whole imaging area in a short time to judge the area where the extended target may appear.

In one possible implementation manner, as shown in fig. 6, the performing time domain preprocessing on the full matrix acquired data formed by all the ultrasonic echo signals of the measured object to extract the relevant scattering signals of the extended target in the measured object includes the steps of:

s11, directly coupling the linear array sensor 1 with the measured object 2, wherein the measured object contains the extended target 3 as an imaging object (as shown in fig. 7);

s12, selecting any pair of array element combinations of the linear array transducer as an exciting array element and a receiving array element respectively, and acquiring ultrasonic echo signals;

s13, sequentially executing the steps until all array element combinations of the linear array sensor acquire ultrasonic echo signals, and enabling all the acquired ultrasonic echo signals to form full-matrix acquisition data;

s14, acquiring an original ultrasonic image of the measured object according to the full-matrix acquisition data formed by all the ultrasonic echo signals of the measured object (as shown in figure 4);

s15, judging the area where the expansion target appears in the obtained original ultrasonic image, and setting a rectangular frame to cover the area to form an expansion target area A (shown as a dashed line frame A in FIG. 4);

s16, calculating and defining a time domain window function according to the array element position of the linear array sensor and the extended target area A by combining the propagation speed c of the ultrasonic wave in the measured object, wherein the specific calculation process can refer to journal articles (Chengguang FAN et al, Preprocessing of the full matrix capture data for time-reversed-based super-resolution imaging), and is not described herein again;

s17, performing time domain preprocessing on all ultrasonic echo signals of the tested object by using the time domain window function, and extracting an extended target related scattering signal S (t):

s(t)＝h(t)w(t) (1)

wherein w (t) is a time domain window function, and h (t) is an ultrasonic echo signal, as shown in fig. 5.

In one possible implementation, as shown in fig. 8, performing super-resolution imaging according to the relevant scattering signal of the extended target to obtain a super-resolution ultrasound image of the extended target includes the steps of:

s21, performing time-frequency domain conversion on the spread target-related scattering signal S (t), constructing an array response matrix K (ω) within a given frequency bandwidth Δ ω, and performing singular value decomposition SVD on the array response matrix K (ω) to obtain singular values and corresponding singular vectors, as shown in formula (2):

K(ω)＝U(ω)∑(ω)V^H(ω) (2)

wherein U (omega) and V (omega) are matrixes formed by singular vectors, sigma (omega) is a matrix formed by singular values, and superscript H represents the conjugate transpose of a complex matrix;

s22, dividing the singular vector into signal subspaces U based on the distribution rule of singular values in the given frequency bandwidth range (as shown in figure 9)_S(omega) and V_S(ω), noise subspace U_N(omega) and V_N(ω)：

S23, defining a direction vector g (r, omega), giving out a PC-MUSIC imaging function based on the signal subspace and the direction vector, and acquiring a super-resolution ultrasonic image of an extended target:

wherein N is_ωIndicating the number of frequency points used for imaging and the superscript T indicates the conjugate of the complex matrix.

In one possible implementation manner, as shown in fig. 10, performing image feature analysis and expansion target parameter evaluation on the super-resolution ultrasound image to obtain the length and angle of an expansion target, includes the steps of:

s31, settingConstant intensity threshold I_σFinding the intensity in the super-resolution ultrasonic image which satisfies that I is more than or equal to I_σThe coordinates corresponding to each pixel point in the set are obtained, and the step sets an intensity threshold value I_σThe purpose of filtering the pixel points in the super-resolution ultrasonic image is to remove interference, and only a pixel set (such as a dark black area in fig. 11) related to the defect is reserved, so that the subsequent calculation amount can be greatly reduced, and the subsequent calculation accuracy is improved;

s32, drawing a super-resolution image intensity contour map (as shown in fig. 12) according to the pixel point set and the coordinates corresponding to each pixel point in the set, comparing fig. 2 and fig. 12, wherein the contour map is identical to the actual extension target, and the result shows that the residual pixel point set after filtering can accurately reflect the actual length and angle of the actual extension target;

s33, searching pixel points corresponding to the maximum value of the left-end intensity and the maximum value of the right-end intensity in the contour map, respectively defining the coordinates of the two pixel points as the evaluation coordinates of the positions of the two ends of the extended target, and in the ultrasonic imaging field, the maximum intensity value coordinate generally corresponds to the key point, such as an end point, of the extended target, so that the maximum value (x) of the left-end intensity in the contour map is searched_l，z_l) And right intensity maximum (x)_r，z_r) Can be defined as the position D of two end points of the extended target_lAnd D_rRespectively is (x)_l，z_l)、(x_r，z_r)；

S34, calculating the calculated length L of the extended target based on the estimated coordinates of the positions of the two ends of the extended target_aAnd calculating the angle theta_a：

θ_a＝sin^-1(|z_l-z_r|/L_a) (6)

From the coordinate positions in fig. 12, L is calculated_a＝4.9529mm，θ_a＝41.3166°。

In one possible implementation manner, as shown in fig. 13, performing image feature analysis and extended target parameter evaluation on the super-resolution ultrasound image to obtain the length and angle of the extended target, further includes the steps of:

s35, obtaining the calculated length error epsilon of the extended target according to the calculated length and the calculated angle of the extended target and the actual length and the actual angle of the extended target obtained by actual measurement_LAnd calculating the angle error ε_θ：

ε_L＝|L_a-L|/L×100％ (7)

ε_θ＝|θ_a-θ|/θ×100％ (8)

Calculate the length L as described above_aAnd calculating the angle theta_aAnd the actual length and the actual angle are substituted into formulas (7) and (8), and the following can be obtained through calculation: epsilon_L＝0.94％，ε_θ8.19%, the error is within an acceptable range. For the extended target quantization evaluation method based on the ultrasonic image, the smaller the error is, the higher the reliability of the result is.

The above embodiment selects the rule extension target reason as follows: the rule extension target has a certain size and angle, so that parametric evaluation is convenient to carry out, which is a conventional method for researching ultrasonic imaging and defect quantification methods; the irregular defects in the actual field can be regarded as superposition of a rule extension target in a certain form, and a quantitative evaluation method for researching the rule extension target is a precondition and a necessary stage of final actual application.

As shown in fig. 14, another aspect of the present application further provides a defect quantification apparatus based on a super-resolution ultrasound image, including:

the device comprises a scattering signal extraction module, a data acquisition module and a data acquisition module, wherein the scattering signal extraction module is used for performing time domain preprocessing on full matrix acquisition data formed by all ultrasonic echo signals of a measured object and extracting related scattering signals of an extended target in the measured object, and the extended target is a linear defect with a certain length and angle in the measured object;

the super-resolution imaging module is used for performing super-resolution imaging according to the relevant scattering signal of the extended target to obtain a super-resolution ultrasonic image of the extended target;

and the extended target parameter evaluation module is used for carrying out image feature analysis and extended target parameter evaluation on the super-resolution ultrasonic image to obtain the length and the angle of an extended target.

The modules in the simulation device can be wholly or partially realized by software, hardware and a combination thereof. The modules can be embedded in a hardware form or independent from a processor in the computer device, and can also be stored in a memory in the computer device in a software form, so that the processor can call and execute operations corresponding to the modules.

The embodiment provides a defect quantification device based on a super-resolution ultrasonic image, which first performs time domain preprocessing on full matrix acquisition data formed by all ultrasonic echo signals of a measured object, and extracts related scattering signals of an extended target in the measured object; then, performing super-resolution imaging according to the relevant scattering signal of the extended target to obtain a super-resolution ultrasonic image of the extended target; and finally, carrying out image characteristic analysis and expansion target parameter evaluation on the super-resolution ultrasonic image to obtain the length and the angle of the expansion target. The embodiment can quantitatively detect the extended target with a certain size (the size is larger than the wavelength of the ultrasonic wave) and a certain angle, such as linear grooving and the like, and accurately estimate the length and the angle of the extended target by analyzing the super-resolution ultrasonic image to realize quantitative estimation of the extended target, so that the related parameters of the extended target are accurately mastered, and more comprehensive detection and estimation of defects are realized during ultrasonic nondestructive detection. The embodiment realizes the quantitative evaluation of the extended target based on the PC-MUSIC method, fully exerts the maximum advantage of the PC-MUSIC method and realizes the automation of defect detection in the future.

As shown in fig. 15, the preferred embodiment of the present application further provides an electronic device, which includes a memory, a processor and a computer program stored in the memory and running on the processor, wherein the processor executes the program to implement the defect quantification method based on super-resolution ultrasound images in the above embodiments.

As shown in fig. 16, the preferred embodiment of the present application also provides a computer device, which may be a terminal or a biopsy server, and the internal structure thereof may be as shown in fig. 16. The computer device includes a processor, a memory, and a network interface connected by a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device comprises a nonvolatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of an operating system and computer programs in the non-volatile storage medium. The network interface of the computer device is used for communicating with other external computer devices through network connection. The computer program is executed by a processor to implement the above-described method for defect quantification based on super-resolution ultrasound images.

Those skilled in the art will appreciate that the configuration shown in fig. 16 is a block diagram of only a portion of the configuration associated with the embodiment, and does not constitute a limitation on the computer device to which the embodiment is applied, and a specific computer device may include more or less devices than those shown in the figure, or may combine some devices, or have a different arrangement of devices.

A preferred embodiment of the present application also provides a storage medium, which includes a stored program, and when the program runs, the storage medium controls a device on which the storage medium is located to execute the defect quantization method based on the super-resolution ultrasound image in the foregoing embodiment.

It should be noted that the steps illustrated in the flowcharts of the figures may be performed in a computer system such as a set of computer-executable instructions and that, although a logical order is illustrated in the flowcharts, in some cases, the steps illustrated or described may be performed in an order different than presented herein.

The functions of the method of the present embodiment, if implemented in the form of software functional units and sold or used as independent products, may be stored in one or more storage media readable by a computing device. Based on such understanding, part of the contribution to the prior art of the embodiments of the present application or part of the technical solution may be embodied in the form of a software product stored in a storage medium and including several instructions for causing a computing device (which may be a personal computer, a server, a mobile computing device or a network device) to execute all or part of the steps of the method described in the embodiments of the present application. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.

The above description is only a preferred embodiment of the present application and is not intended to limit the present application, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, improvement and the like made within the spirit and principle of the present application shall be included in the protection scope of the present application.