A fully focused phased array three-dimensional ultrasonic imaging method and system based on the Grey Wolf algorithm

Abstract

The present invention discloses a fully focused phased array three-dimensional ultrasonic imaging method and system based on the Gray Wolf algorithm, which relates to the technical field of three-dimensional ultrasonic imaging, and includes the steps of: using the Gray Wolf algorithm to optimize the array arrangement of the ultrasonic phased array sparse matrix of the ultrasonic probe, and obtaining a method for capturing the designed sparse matrix; constructing a three-dimensional coordinate system of the object to be measured, and based on the three-dimensional coordinate system of the object, using the method of capturing the designed sparse matrix to collect ultrasonic data of the target area of ​​the object to be measured using set sampling parameters and set sampling intervals, wherein each set sampling interval collects a corresponding ultrasonic data group; using the Gray Wolf algorithm to convert each ultrasonic data group into a binary image, and reconstructing a three-dimensional imaging image through multiple binary images. The method of the present invention solves the technical problem of slow convergence and low efficiency of the sparse matrix array design method of phased array ultrasonic imaging in the prior art.

Description

Technical Field

[0001] The present invention relates to the technical field of three-dimensional ultrasonic imaging, and in particular to a fully focused phased array three-dimensional ultrasonic imaging method and system based on a Grey Wolf algorithm. Background Art

[0002] Ultrasonic phased array imaging technology is one of the most representative non-destructive testing technologies. In recent years, it has been widely used in aviation, nuclear power, chemical industry and other industries. This technology transmits high-frequency ultrasonic waves to the object to be tested to achieve internal structure imaging detection of metal, non-metal and composite material components in various types of equipment. Ultrasonic phased array technology is designed based on the Huygens principle. By applying different time delay rules to different units of the transducer array when transmitting or receiving sound waves, ultrasonic imaging detection technology with functions such as ultrasonic sound velocity movement, deflection and focusing is realized. The ultrasonic phased array transducer is composed of multiple independent piezoelectric chips in a linear or circular array. According to certain rules and timing, each chip is excited by electronic control delay. The ultrasonic waves emitted by each chip are superimposed to form an overall wavefront. Through different delay rules, the control of ultrasonic angle, focus depth and focus size is achieved. Compared with traditional ultrasonic testing, ultrasonic phased array testing has the advantages of fast detection speed, high sensitivity, good flexibility and intuitive detection results.

[0003] Fully focused phased array ultrasonic imaging technology is an ultrasonic array processing technology that reconstructs imaging results based on full matrix capture of ultrasonic signal data. During the detection process, all array elements in the phased array transducer are used to complete the excitation and reception of ultrasonic waves, thereby achieving the effect of full-range dynamic focusing on the object under test. This technology reconstructs fully focused image results by combining the ultrasonic signals collected by all array elements. It has high imaging resolution and a wide detection range, and can intuitively feedback the internal structure or defect information of the object under test. However, due to the large computing resources required by the full matrix, this technology has the disadvantages of large signal data volume, long computing time, and complex algorithms, making it difficult to be further applied in the field of industrial real-time detection.

[0004] Sparse fully focused phased array ultrasound imaging technology can effectively solve the problem of huge computing resources in the process of full matrix acquisition and processing of ultrasound signals. This method reduces the amount of sampled signal data without increasing the number of phased array elements by expanding the aperture of the matrix array, thereby achieving high-resolution ultrasound imaging. The design of sparse phased array is one of the key difficulties of sparse fully focused phased array ultrasound imaging technology. The current design method has the problems of slow convergence and low efficiency.

[0005] In view of this, it is necessary to propose a fully focused phased array three-dimensional ultrasonic imaging method and system based on the Grey Wolf algorithm to solve or at least partially solve the above technical problems. Summary of the invention

[0006] The main purpose of the present invention is to provide a fully focused phased array three-dimensional ultrasonic imaging method and system based on the Grey Wolf algorithm, aiming to solve the technical problems of slow convergence and low efficiency of sparse matrix array design methods for phased array ultrasonic imaging in the prior art.

[0007] To achieve the above-mentioned object, the present invention provides a fully focused phased array three-dimensional ultrasonic imaging method based on the Grey Wolf algorithm, comprising S10, using the Grey Wolf algorithm to optimize the array arrangement of the ultrasonic phased array sparse matrix of the ultrasonic probe to obtain a capture method of the designed sparse matrix;

[0008] Specifically, it includes: S11, setting the ultrasonic phased array parameters of the ultrasonic probe, the ultrasonic probe adopts a uniform linear array, and the array of the ultrasonic probe is uniformly distributed with array elements, set the state function of each array element It is expressed as:

[0009]

[0010] Set the normalized pattern function of the array element sparse matrix It is expressed as:

[0011]

[0012] in, is the maximum pointing angle of the ultrasonic beam, is the beam pointing angle, is the distance between adjacent array elements of the ultrasonic probe, is the wavelength;

[0013] Set the main lobe width of the pattern Side lobe peak level The normalized pattern function It is expressed as:

[0014]

[0015]

[0016] Among them, max represents the maximum value function, and S is the sidelobe interval of the pattern;

[0017] S12, determining algorithm parameters of the grey wolf algorithm for designing an array arrangement of an ultrasonic phased array sparse matrix, the algorithm parameters including the maximum number of iterations of the design , the position vector of individuals in the gray wolf population 、The number of gray wolf populations And the evaluation function , the position vector is the distribution state of the array elements in the uniform linear array. Initially, the size of the randomly generated 0 and 1 values ​​is Binary matrix, evaluation function The expression is:

[0018]

[0019] S13, perform iterative calculation, when the evaluation function Update the position vector of individuals in the gray wolf population as it grows ; or when the preset maximum number of iterations is reached Output the position vector of the individual in the gray wolf population ;

[0020] S20, constructing a three-dimensional coordinate system of the object to be measured, and based on the three-dimensional coordinate system of the object, using a sparse matrix capture method to collect ultrasonic data of a target area of ​​the object to be measured by using set sampling parameters and set sampling intervals, wherein each set sampling interval has a corresponding ultrasonic data group;

[0021] S30, using the Grey Wolf algorithm to convert each ultrasound data set into a binary image, and reconstructing a three-dimensional imaging image through multiple binary images.

[0022] Furthermore, step S20 specifically includes: constructing a three-dimensional coordinate system of the object to be measured, wherein the three intersecting coordinate axes of the object three-dimensional coordinate system are the x-axis, the y-axis and the z-axis respectively; placing the ultrasonic probe on the xy plane of the object to be measured, and arranging the center line of the probe array element parallel to and opposite to the y-axis symmetry line of the object to be measured, moving the ultrasonic probe along the y-axis and sampling according to the set sampling interval, and during sampling, moving the ultrasonic probe at equal distances from top to bottom according to the set sampling interval to collect line scan images on the xz plane; setting sampling parameters including pulse width, pulse voltage, sampling frequency, number of sampling points, and amplifier gain.

[0023] Furthermore, the sampling interval is set to any value between 0.3 mm and 0.9 mm.

[0024] Furthermore, each ultrasound data set is segmented in turn using the Gray Wolf Algorithm. The maximum number of segmentation times is first set. and the gray wolf position vector , the gray wolf position vector The position vector is a random integer between [1, 255]; composite exponential entropy is used As the discriminant of the Grey Wolf Algorithm, , , Represent the gray wolf position vector Two partial index entropies obtained when segmenting the ultrasound data set to be segmented;

[0025]

[0026] in, are integers in the position vector, is the probability of the gray value i appearing in the gray image to be segmented for the ultrasonic data set collected by the object under test, 255 is the maximum gray value, , Respectively represent the weight parameters in the position component; in each iteration, the gray wolf position vector is calculated For the composite exponential entropy of the grayscale image to be segmented, when the composite exponential entropy value increases, the current maximum composite exponential entropy is recorded and the gray wolf position vector is updated synchronously. , when the number of iterations reaches the maximum number of segmentation When , get the gray wolf position vector corresponding to the value of the maximum composite exponential entropy As the grayscale image segmentation threshold; use the grayscale image segmentation threshold to perform binary segmentation on the corresponding ultrasound data group to obtain the corresponding binary image ; Repeat the above steps to obtain multiple binary images ; For all binary images Perform linear interpolation calculation and output the final three-dimensional image reconstruction result.

[0027] Furthermore, using the formula For binary images Perform linear interpolation calculation, where and are two binary images segmented after the adjacent ultrasound data set, is the distance parameter, and its expression is ,in for and The distance between for and The distance between.

[0028] The present invention also provides a fully focused phased array three-dimensional ultrasonic imaging system based on the Grey Wolf algorithm, comprising:

[0029] An ultrasonic probe, used for storing the array arrangement of the ultrasonic phased array sparse matrix and receiving the sound pressure and echo signals during the ultrasonic wave propagation process;

[0030] An initialization program unit is used for initializing the gray wolf algorithm, and determining the arrangement of the ultrasound probe array through the gray wolf algorithm initialization; determining the maximum number of iterations in the gray image segmentation process and the gray wolf position vector in the gray wolf population through the gray wolf algorithm initialization;

[0031] An evaluation function calculation program unit is used to calculate the evaluation function value corresponding to the position vector of an individual in the gray wolf population during the arrangement of the ultrasonic probe array;

[0032] The exponential entropy calculation program unit is used to calculate the composite exponential entropy of the gray wolf position vector for the gray image to be segmented during the image segmentation process, and save the gray wolf position vector corresponding to the maximum composite exponential entropy;

[0033] An iteration judgment program unit is used to determine the number of iterations and judge whether the number of iterations in the process of ultrasonic probe array arrangement and grayscale image segmentation has reached the maximum number of iterations. In the process of ultrasonic probe array arrangement, if the maximum number of iterations has been reached, the data is stored in the sparse fully focused phased array ultrasonic probe; in the process of grayscale image segmentation, if the maximum number of iterations has been reached, the image segmentation program unit is called;

[0034] Ultrasonic signal processing unit: converts the received ultrasonic signal into a grayscale image;

[0035] Image segmentation program unit: used to access the gray wolf position vector corresponding to the maximum exponential entropy in the exponential entropy calculation program unit, read the grayscale image in the ultrasonic signal processing unit, use this position vector as a pre-threshold segmentation for the grayscale image, obtain a binary image, and use it to reconstruct a three-dimensional imaging image through multiple binary images.

[0036] Compared with the prior art, the fully focused phased array three-dimensional ultrasonic imaging method based on the Grey Wolf algorithm provided by the present invention has the following beneficial effects:

[0037] The present invention provides a method for three-dimensional ultrasonic imaging of a fully focused phased array based on the Grey Wolf algorithm, which uses the Grey Wolf algorithm to obtain a design sparse matrix capture method, and uses an evaluation function The value of is used to calculate the position vector of the individual in the gray wolf population during the arrangement of the ultrasonic probe array. During the arrangement of the ultrasonic probe array, if the maximum number of iterations is reached, the data is stored in the ultrasonic probe so that the ultrasonic probe has a corresponding array arrangement mode. Based on the three-dimensional coordinate system of the object, a sparse matrix capture method is designed to collect ultrasonic data from the target area of ​​the object under test using set sampling parameters and set sampling intervals, wherein each starting point of the set sampling interval has a corresponding ultrasonic data group. The grayscale image is threshold-segmented to obtain a binary image. Finally, a three-dimensional imaging image is reconstructed through multiple binary images to solve the technical problems of slow convergence and low efficiency of the sparse matrix array design method of phased array ultrasonic imaging in the prior art. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on the structures shown in these drawings without paying creative work.

[0039] Figure 1 It is a flow chart of the fully focused phased array three-dimensional ultrasonic imaging method based on the Grey Wolf algorithm of the present invention;

[0040] Figure 2 This is one of the schematic diagrams of the three-dimensional fully focused phased array ultrasonic imaging detection model in the method of the present invention;

[0041] Figure 3 This is the second schematic diagram of the three-dimensional fully focused phased array ultrasonic imaging detection model in the method;

[0042] Figure 4 are three single-view fitting images obtained in a specific implementation method of the present invention; wherein, Figure 4 a is the front view fitting diagram, Figure 4 b is the side view fitting diagram, Figure 4 c is the top view fitting diagram;

[0043] Figure 5 It is a schematic diagram of the three-dimensional structure fitting obtained in a specific implementation method of the present invention.

[0044] The purpose, features and advantages of the present invention will be further described with reference to the accompanying drawings in conjunction with the embodiments. DETAILED DESCRIPTION

[0045] It should be understood that the specific embodiments described herein are only used to explain the present invention, and are not used to limit the present invention.

[0046] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0047] It should be noted that all directional indications (such as up, down, left, right, front, back, etc.) in the embodiments of the present invention are only used to explain the relative position relationship, movement status, etc. between the components under a certain specific posture (as shown in the accompanying drawings). If the specific posture changes, the directional indication will also change accordingly.

[0048] In addition, the descriptions of "first", "second", etc. in the present invention are only used for descriptive purposes and cannot be understood as indicating or implying their relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined as "first" and "second" may explicitly or implicitly include at least one of the features. In addition, the technical solutions between the various embodiments can be combined with each other, but they must be based on the ability of ordinary technicians in the field to implement them. When the combination of technical solutions is contradictory or cannot be implemented, it should be deemed that such a combination of technical solutions does not exist and is not within the scope of protection required by the present invention.

[0049] Please refer to Figure 1 and Figure 2 The present invention provides a fully focused phased array three-dimensional ultrasonic imaging method based on the Grey Wolf algorithm, comprising the steps of:

[0050] S10, using the Grey Wolf algorithm to optimize the array arrangement of the ultrasonic phased array sparse matrix of the ultrasonic probe, and obtaining a method for capturing the designed sparse matrix.

[0051] Optionally, the ultrasonic probe may be an ultrasonic phased array probe with 32 array elements, or may be an ultrasonic phased array probe with 16 array elements, 64 array elements, or other array elements.

[0052] In the present invention, the array arrangement of the sparse matrix of the ultrasonic phased array is optimized and designed using the Grey Wolf Algorithm, which specifically includes:

[0053] S11, setting the ultrasonic phased array parameters of the ultrasonic probe. The ultrasonic probe adopts a uniform linear array, and the array of the ultrasonic probe is evenly distributed with array elements, set the state function of each array element It is expressed as:

[0054]

[0055] Set the normalized pattern function of the array element sparse matrix It is expressed as:

[0056]

[0057] in, is the maximum pointing angle of the ultrasonic beam, is the beam pointing angle, is the distance between adjacent array elements of the ultrasonic probe, is the wavelength;

[0058] Set the main lobe width of the pattern Side lobe peak level The normalized pattern function It is expressed as:

[0059]

[0060]

[0061] Among them, max represents the maximum value function, and S is the sidelobe interval of the radiation pattern.

[0062] As can be understood, j refers to an imaginary number, e is an exponential function, To find the maximum value of the F function in the S interval.

[0063] S12, determining algorithm parameters of the grey wolf algorithm for designing an array arrangement of an ultrasonic phased array sparse matrix, the algorithm parameters including the maximum number of iterations of the design , the position vector of individuals in the gray wolf population (individual position vector) 、The number of gray wolf populations And the evaluation function , the position vector is the distribution state of the array elements in the uniform linear array. Initially, the size of the randomly generated 0 and 1 values ​​is Binary matrix, evaluation function The expression is:

[0064]

[0065] S13, perform iterative calculation, when the evaluation function Update the position vector of individuals in the gray wolf population as it grows ; or when the preset maximum number of iterations is reached Output the position vector of the individual in the gray wolf population .

[0066] Preferably, the ultrasonic phased array probe is set to use a uniform linear array of 32 elements, and the maximum directional angle of the ultrasonic beam is , beam pointing angle , the spacing between adjacent array elements , ultrasonic wavelength ; Design maximum number of iterations The number of gray wolf populations is , the position vector of individuals in the gray wolf population The size for randomly generating 0 and 1 values ​​is Binary matrix.

[0067] Further, S20, a three-dimensional coordinate system of the object to be measured is constructed, and ultrasonic data of a target area of ​​the object to be measured is collected using set sampling parameters and a set sampling interval based on the object three-dimensional coordinate system, wherein each set sampling interval has a corresponding ultrasonic data group (i.e., a grayscale image).

[0068] In the specific implementation, a three-dimensional coordinate system of the object to be measured is constructed, and the three intersecting coordinate axes of the object three-dimensional coordinate system are respectively the x-axis, the y-axis and the z-axis; the ultrasonic probe is placed on the xy plane of the object to be measured, and the center line of the probe array element is arranged parallel to and opposite to the y-axis symmetry line of the object to be measured, the ultrasonic probe is moved along the y-axis and sampling is performed according to the set sampling interval, and the ultrasonic probe is moved from top to bottom at equal distances according to the set sampling interval to collect line scan images on the xz plane during sampling; the sampling parameters are set including pulse width, pulse voltage, sampling frequency, number of sampling points, and amplifier gain.

[0069] Optionally, the x-axis and the z-axis are both horizontal axes, and the y-axis is a vertical axis. The ultrasonic probe is placed on the xy plane of the object to be measured and moves upward or downward along the y-axis. The center line of the probe array element is parallel to the y-axis symmetry line of the workpiece. During sampling, a line scan image on the xz plane is collected every 6 mm from top to bottom, and a total of 20 line scan images are collected; the sampling parameters are set to include pulse width, pulse voltage, sampling frequency, number of sampling points, and amplifier gain, as shown in Table 1 (Setting Sampling Parameters Table):

[0070] Table 1

[0071]

[0072] Furthermore, the sampling interval is set to any value between 0.3 mm and 0.9 mm.

[0073] Further, S30, each ultrasound data set is converted into a binary image using the Grey Wolf algorithm, and a three-dimensional imaging image is reconstructed through multiple binary images.

[0074] In the specific implementation, each ultrasound data group is segmented in turn by the Gray Wolf Algorithm. When segmenting, the maximum number of segmentation times is first set. and the gray wolf position vector , the gray wolf position vector A position vector that randomly selects integers between [1, 255];

[0075] Compound exponential entropy As the discriminant of the Grey Wolf Algorithm, , , Represent the gray wolf position vector Two partial index entropies obtained when segmenting the ultrasound data set to be segmented;

[0076]

[0077] in, are integers in the position vector, is the probability of the gray value i appearing in the gray image to be segmented for the ultrasonic data set collected by the object under test, 255 is the maximum gray value, , Respectively represent the weight parameters in the position component;

[0078] In each iteration, the gray wolf position vector is calculated For the composite exponential entropy of the grayscale image to be segmented, when the composite exponential entropy value increases, the current maximum composite exponential entropy is recorded and the gray wolf position vector is updated synchronously. , when the number of iterations reaches the maximum number of segmentation When , get the gray wolf position vector corresponding to the value of the maximum composite exponential entropy As the grayscale image segmentation threshold;

[0079] Using formula For binary images Perform linear interpolation calculation, where and are two binary images segmented after the adjacent ultrasound data set, is the distance parameter, and its expression is ,in for and The distance between for and The distance between

[0080] Repeat the above steps to obtain multiple binary images ;

[0081] For all binary images Perform linear interpolation calculation and output the final three-dimensional image reconstruction result.

[0082] The present invention provides a method for three-dimensional ultrasonic imaging of a fully focused phased array based on the Grey Wolf algorithm, which uses the Grey Wolf algorithm to obtain a design sparse matrix capture method, and uses an evaluation function The value of is used to calculate the position vector of the individual in the gray wolf population during the arrangement of the ultrasonic probe array. During the arrangement of the ultrasonic probe array, if the maximum number of iterations is reached, the data is stored in the ultrasonic probe so that the ultrasonic probe has a corresponding array arrangement mode. Based on the three-dimensional coordinate system of the object, a sparse matrix capture method is designed to collect ultrasonic data from the target area of ​​the object under test using set sampling parameters and set sampling intervals, wherein each starting point of the set sampling interval has a corresponding ultrasonic data group. The gray wolf algorithm is used to obtain the maximum number of iterations in the gray image segmentation process and the gray wolf position vector in the gray wolf population. During the gray image segmentation process, if the maximum number of segmentations is reached, the corresponding gray wolf position vector is calculated according to the maximum composite exponential entropy, and the position vector is used as the gray image segmentation threshold to perform threshold segmentation on the gray image to obtain a binary image. Finally, a three-dimensional imaging image is reconstructed through multiple binary images to solve the technical problems of slow convergence and low efficiency of the sparse matrix array design method of phased array ultrasonic imaging in the prior art.

[0083] Please refer to Figure 3 , Figure 4 and Figure 5 When the fully focused phased array three-dimensional ultrasonic imaging method based on the Grey Wolf algorithm of the present invention is used, it can be used to detect the surface of the transformer to reconstruct the three-dimensional imaging image of the winding inside the transformer and determine whether the winding is deformed. Please refer to the figure. The test workpiece consists of test block 1, test block 2 and test block 3, wherein test block 1 and test block 3 are arranged at intervals and parallel to each other along the height (y-axis) direction, and test block 2 is arranged between test block 1 and test block 3. Test block 1 and test block 2 are placed in a T-shape, with the upper height of the T-shaped surface being 20 mm and the lower width being 10 mm. The total width of the test workpiece is 40 mm, and the sampling interval is set to 6 mm. In the specific operation, the gray wolf algorithm is used to obtain the method of designing sparse matrix capture; based on the three-dimensional coordinate system of the object, the method of designing sparse matrix capture is used to collect ultrasonic data of the target area of ​​the object under test using set sampling parameters and set sampling intervals, wherein each set sampling interval collects a corresponding ultrasonic data group (i.e., grayscale image); the gray wolf algorithm is used to perform image segmentation to obtain binary images (binary images of three single-view angles for each measuring point); all binary images of each view angle are fused to obtain three single-view angle views; three-dimensional imaging image reconstruction based on the three single-view angle views is performed by scanning using the full-focus phased array three-dimensional ultrasonic imaging method based on the gray wolf algorithm to obtain each single-view angle image, wherein, Figure 4 a is the front view fitting diagram, Figure 4 b is the side view fitting diagram, Figure 4 c is a top view fitting diagram; after 3D reconstruction, a local 3D image of the test workpiece is obtained, such as Figure 5 shown.

[0084] The present invention also provides a fully focused phased array three-dimensional ultrasonic imaging system based on the gray wolf algorithm, comprising: an ultrasonic probe, used to store the array arrangement of the ultrasonic phased array sparse matrix and to receive the sound pressure and echo signals during ultrasonic propagation; an initialization program unit, used to initialize the gray wolf algorithm, and to determine the arrangement of the ultrasonic probe array through the gray wolf algorithm initialization; to determine the maximum number of iterations in the gray image segmentation process and the gray wolf position vector in the gray wolf population through the gray wolf algorithm initialization; an evaluation function calculation program unit, used to calculate the evaluation function value corresponding to the position vector of the individual in the gray wolf population during the arrangement of the ultrasonic probe array; an exponential entropy calculation program unit, used to calculate the composite exponential entropy of the gray wolf position vector for the gray image to be segmented during the image segmentation process, and to save the gray wolf position vector corresponding to the maximum composite exponential entropy. Vector; an iteration judgment program unit, used to determine the number of iterations, judge whether the number of iterations in the process of ultrasonic probe array arrangement and grayscale image segmentation reaches the maximum number of iterations. In the process of ultrasonic probe array arrangement, if the maximum number of iterations is reached, the data is stored in the sparse fully focused phased array ultrasonic probe; in the process of grayscale image segmentation, if the maximum number of iterations is reached, the image segmentation program unit is called; an ultrasonic signal processing unit: converts the received ultrasonic signal into a grayscale image; an image segmentation program unit: used to access the gray wolf position vector corresponding to the maximum exponential entropy in the exponential entropy calculation program unit, read the grayscale image in the ultrasonic signal processing unit, use this position vector as a prefabricated threshold segmentation on the grayscale image, obtain a binary image, and use it to reconstruct a three-dimensional imaging image through multiple binary images.

[0085] The above embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the present application. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the attached claims.

Claims

1. A fully focused phased array three-dimensional ultrasonic imaging method based on the Grey Wolf algorithm, characterized in that: Includes steps: S10, using the Grey Wolf algorithm to optimize the array arrangement of the ultrasonic phased array sparse matrix of the ultrasonic probe, and obtaining a method for capturing the designed sparse matrix; Specifically include: S11, setting the ultrasonic phased array parameters of the ultrasonic probe, wherein the ultrasonic probe adopts a uniform linear array, and the array of the ultrasonic probe is uniformly distributed with array elements, set the state function of each array element It is expressed as: Set the normalized pattern function of the array element sparse matrix It is expressed as: in, is the maximum pointing angle of the ultrasonic beam, is the beam pointing angle, is the distance between adjacent array elements of the ultrasonic probe, is the wavelength; Set the main lobe width of the pattern Side lobe peak level The normalized pattern function It is expressed as: Among them, max represents the maximum value function, and S is the sidelobe interval of the pattern; S12, determining algorithm parameters of the grey wolf algorithm for designing the array arrangement of the ultrasonic phased array sparse matrix, wherein the algorithm parameters include designing a maximum number of iterations , the position vector of individuals in the gray wolf population 、The number of gray wolf populations And the evaluation function , the position vector is the distribution state of the array elements in the uniform linear array. Initially, the size of the randomly generated 0 and 1 values ​​is The binary matrix, the evaluation function The expression is: S13, performing iterative calculation, when the evaluation function Update the position vector of individuals in the gray wolf population as it grows ; or when the preset maximum number of iterations is reached Output the position vector of the individual in the gray wolf population ; S20, constructing a three-dimensional coordinate system of the object to be measured, and based on the three-dimensional coordinate system of the object, using a sparse matrix capture method to collect ultrasonic data of a target area of ​​the object to be measured by using set sampling parameters and set sampling intervals, wherein each set sampling interval collects a corresponding ultrasonic data group; Step S20 specifically includes: Constructing a three-dimensional coordinate system of the object to be measured, wherein three intersecting coordinate axes of the three-dimensional coordinate system of the object are respectively an x-axis, a y-axis and a z-axis; The ultrasonic probe is placed on the xy plane of the object to be measured, and the center line of the probe array is arranged parallel to the y-axis symmetry line of the object to be measured, and the ultrasonic probe is moved along the y-axis to perform sampling according to the set sampling interval. When sampling, the ultrasonic probe is moved from top to bottom at equal distances according to the set sampling interval to collect line scan images on the xz plane; The set sampling parameters include pulse width, pulse voltage, sampling frequency, number of sampling points, and amplifier gain; The sampling interval is set to any value between 0.3 mm and 0.9 mm; S30, using the Gray Wolf algorithm to convert each of the ultrasound data sets into a binary image, and reconstructing a three-dimensional imaging image using a plurality of the binary images; Each of the ultrasound data sets is segmented in turn by the Grey Wolf Algorithm. When segmenting, the maximum number of segmentation times is first set. and the gray wolf position vector , the gray wolf position vector A position vector that randomly selects integers between [1, 255]; Compound exponential entropy As the discriminant of the Grey Wolf Algorithm, , , Represent the gray wolf position vector Two partial index entropies obtained when segmenting the ultrasound data set to be segmented; in, are integers in the position vector, is the probability of the gray value i in the gray image to be segmented for the ultrasonic data set collected by the object under test, 255 is the maximum gray value, , Respectively represent the weight parameters in the position component; In each iteration, the gray wolf position vector is calculated For the composite exponential entropy of the grayscale image to be segmented, when the composite exponential entropy value increases, the current maximum composite exponential entropy is recorded and the gray wolf position vector is updated synchronously. , when the number of iterations reaches the maximum number of segmentation When , get the gray wolf position vector corresponding to the value of the maximum composite exponential entropy As the grayscale image segmentation threshold; The corresponding ultrasound data group is subjected to binary segmentation using the grayscale image segmentation threshold to obtain a corresponding binary image. ; Repeat the above steps to obtain multiple binary images ; For all the binary images Perform linear interpolation calculation and output the final three-dimensional image reconstruction result; Using formula For the binary image Perform linear interpolation calculation, where and are two binary images segmented after the adjacent ultrasound data set, is the distance parameter, and its expression is ,in for and The distance between for and The distance between.

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