CN115343365A - Test piece integrity detection method based on ultrasonic C scanning digital image processing - Google Patents
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- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N29/00—Investigating or analysing materials by the use of ultrasonic, sonic or infrasonic waves; Visualisation of the interior of objects by transmitting ultrasonic or sonic waves through the object
- G01N29/04—Analysing solids
- G01N29/06—Visualisation of the interior, e.g. acoustic microscopy
- G01N29/0654—Imaging
- G01N29/069—Defect imaging, localisation and sizing using, e.g. time of flight diffraction [TOFD], synthetic aperture focusing technique [SAFT], Amplituden-Laufzeit-Ortskurven [ALOK] technique
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N29/00—Investigating or analysing materials by the use of ultrasonic, sonic or infrasonic waves; Visualisation of the interior of objects by transmitting ultrasonic or sonic waves through the object
- G01N29/44—Processing the detected response signal, e.g. electronic circuits specially adapted therefor
- G01N29/4463—Signal correction, e.g. distance amplitude correction [DAC], distance gain size [DGS], noise filtering
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- G—PHYSICS
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- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
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- G01N2291/02—Indexing codes associated with the analysed material
- G01N2291/028—Material parameters
- G01N2291/0289—Internal structure, e.g. defects, grain size, texture
Abstract
The invention relates to a test piece integrity detection method based on ultrasonic C scanning digital image processing, which comprises the following steps: reading and processing image data of a tested piece to obtain two-dimensional amplitude data corresponding to the tested piece; step two: preprocessing and correcting two-dimensional amplitude data of a tested piece; step three: judging whether the structural characteristics of the tested piece are detected or not, and obtaining the completeness of the tested piece. The method for analyzing the test piece completeness can be used for analyzing the defects of the test piece with or without structural characteristics and calculating the completeness of the tested test piece, has the characteristics of high accuracy and wide applicability, and provides an effective solution for image defect analysis.
Description
Technical Field
The application relates to the field of nondestructive testing of materials, in particular to a test piece integrity detection method based on ultrasonic C scanning digital image processing.
Background
The ultrasonic C scanning imaging detection technology is an important nondestructive detection means for ensuring the product quality, and is widely applied to the key fields of aviation, aerospace, nuclear industry and the like. In the ultrasonic C-scan detection process, the defect analysis based on the digitized image is a key process for judging whether the detected object meets the acceptance condition.
With the continuous emergence of new materials, new processes and new structures, the defects and acceptance conditions of the novel materials and the novel structures present new characteristics. Taking the superplastic forming diffusion bonding and composite material parts as examples, due to the reasons of complex manufacturing process, many influencing factors and the like, poor welding area defects are easy to occur inside the superplastic forming diffusion bonding, the shapes of the defects are often irregular, and the sizes, the number and the positions of the defects are not obviously regular; due to the complex manufacturing process, special material and structure and the like, the composite material part is easy to have area defects such as layering, debonding and the like. In contrast to conventional equivalent weight evaluation methods, superplastic forming diffusion bonding and composite articles are concerned more with the area of defects or the fraction of defects in the overall article.
Most of software parts of the existing ultrasonic C scanning detection system have a length measurement function and are suitable for size measurement of regular shape features, and few pieces of software have a defect area analysis function based on an amplitude threshold value. However, for a workpiece with complex internal structural features, defects and structural features in the C-scan image are difficult to distinguish from the amplitude; during ultrasonic C-scan detection, system software cannot often perform defect analysis processing on other detection images, and the use requirements cannot be met.
Reference CN201510290015.0 sets two different detection sensitivities to perform ultrasonic C scanning detection, and obtains a simulated complete debonding defect scanning image and an actual debonding defect scanning image of the to-be-detected surface of the to-be-detected product respectively, and uses phtoshop software to count total pixels of the to-be-detected surface and pixels of a debonding region of the to-be-detected product, and uses the ratio of the total pixels of the debonding region to the total area of the to-be-detected surface of the to-be-detected product. This method is time consuming due to the need to test the same product under test twice. The reference file 201810322575.3 is used for obtaining pixels contained in each defect by using a binary ultrasonic C scanning image of a composite material product, and further calculating the defect area, and the two reference files consider the influence of structural features on defect area calculation.
Different from the method, the test piece integrity rate analysis method based on ultrasonic C scanning digital image processing can be used for defect analysis of test pieces with or without structural features and calculating the integrity rate of the tested test piece, and has the advantages of high accuracy, flexibility in operation and wide applicability. Meanwhile, the effectiveness of the method in defect analysis is proved by analyzing and processing a large number of typical tested piece ultrasonic C-scan images.
Disclosure of Invention
In order to overcome the defects of the prior art, the method obtains defect information by ultrasonic C scanning of a tested piece, divides the tested piece into two states of undetected structural characteristics and detected structural characteristics through amplitude data of the tested piece, divides the tested piece with the structural characteristics into a key area and a non-key area, further determines a test piece integrity rate detection mode according to the structural characteristics of the tested piece, and completes the calculation of the integrity rate; the method calculates the completeness of the tested piece, and has the characteristics of high accuracy, flexible operation and wide applicability.
In order to achieve the purpose, the solution adopted by the invention is as follows:
a test piece integrity detection method based on ultrasonic C scanning digital image processing comprises the following steps:
step 1: reading and processing image data of a tested piece to obtain two-dimensional amplitude data corresponding to the tested piece;
putting a tested piece into an ultrasonic C for scanning to obtain an RGB format two-dimensional scanning image Pic (x, y) and a two-dimensional color band Col (m, n) thereof; converting RGB format two-dimensional scanning image Pic (x, y) into RGB mode IIIDimension image array Pic RGB (x, y, i), i =1,2,3; converting RGB format two-dimensional scanning color band Col (m, n) into RGB mode three-dimensional color band array Col RGB (m,n,i)，i＝1,2,3；
Three-dimensional image array Pic with RGB mode RGB In each layer (x, y, i), the x-th row and the y-th column data Pic RGB (x,y,1)、Pic RGB (x, y, 2) and Pic RGB (x, y, 3) and color bar data Col RGB (m, n, i) m-th row and 1-th column data Col in each layer RGB (m,1,1)、Col RGB (m, 1, 2) and Col RGB (m, 1, 3) comparison to find Col RGB (m, 1, i) with Pic RGB The corresponding row number M when the (x, y, i) values are the same i (i =1,2,3), the calculation procedure is as follows:
in the formula: m 1 、M 2 And M 3 Respectively representing the corresponding line numbers when the image array and the color bar array in the 1 st, the 2 nd and the 3 rd layers have the same numerical value, and each M i The number of middle row numbers is at least 1; pic RGB (x, y, i) represents the pixel values of the x row and the y column of the ith layer in the three-dimensional image array; col (Col) RGB (m, 1, i) represents the pixel value of the mth layer in the three-dimensional color bar array; x and y respectively represent the row number and the column number of the image array; find represents a lookup function that assigns a row number in the array that satisfies the condition value listed in parentheses to M to the left of the equal sign i (ii) a i represents the number of the layer number in the three-dimensional image array; m represents the pixel number in the three-dimensional color band array;
three-dimensional image data Pic RGB The two-dimensional amplitude data corresponding to the (x, y, i) th row and y column data is as follows:
a(x,y)＝Amp(M)；
in the formula: a (x, y) represents two-dimensional amplitude data of the three-dimensional image data in the x-th row and the y-th column; amp denotes color bar array Col RGB The amplitude value corresponding to each row value in (m, 1, i) is in the value range of [0,100]](ii) a M represents three-dimensional color bar array Col RGB RGB data of (m, 1, i) anddimension image array Pic RGB The row number corresponding to the same RGB data of the (x, y, i) x-th row and the y-th column is represented by M 1 、M 2 And M 3 Obtaining an intersection;
processing three-dimensional image array Pic RGB For each x-th row and y-th column data of each layer in (x, y, i), the three-dimensional image array Pic is subjected to RGB Carrying out amplitude conversion on the data in the (x, y, i) to obtain corresponding two-dimensional amplitude data a (x, y);
step 2: preprocessing and correcting two-dimensional amplitude data of a tested piece;
acquiring the two-dimensional amplitude data obtained in the step (1), and processing the imported two-dimensional amplitude data a (x, y) by adopting two-dimensional median filtering of a 5 multiplied by 5 neighborhood block, so as to reduce speckle noise and salt and pepper noise in image data and realize preprocessing operation; rotating the image according to the following formula, correcting the image to obtain corrected two-dimensional amplitude data A (x) θ ,y θ ) The calculation process is as follows:
in the formula: θ represents a correction angle of the image; x is the number of θ And y θ Respectively represent two-dimensional amplitude data A (x) θ ,y θ ) The row and column numbers of (a); a (x) θ ,y θ ) Representing two-dimensional amplitude data at x-th θ Line, y θ Amplitude of the column;
and step 3: judging whether the structural characteristics of the tested piece are detected or not, and obtaining the completeness rate of the tested piece;
when the structural features are not detected, the structural feature-free completeness calculation is executed, and the two-dimensional amplitude data A (x) is counted by setting a defect amplitude threshold value θ ,y θ ) The number of defective pixels and the number of pixels in the whole area within the threshold range of the defect amplitude are calculated, and the ratio of the number of defective pixels and the number of pixels in the whole area is used as the perfectness ratio alpha of the tested piece without structural characteristics 1 (ii) a When the structural characteristics exist in the detected image, the corrected image is superposed with the design parameters of the tested piece, and the structural characteristics of the design parameters of the tested piece are determined according to the structural characteristicsCoordinates in critical, critical and non-critical regions, can be in two-dimensional amplitude data A (x) θ ,y θ ) Automatically acquiring the boundary of the relevant area so as to calculate the perfectness ratio alpha of the key area c Perfection ratio alpha of non-critical area nc And the integrity factor alpha of the tested piece with structural characteristics 2 And finally obtaining the completeness of the tested piece.
Preferably, the two-dimensional scan image Pic (x, y) and the two-dimensional color band Col (m, n) thereof in step 1 are specifically:
the two-dimensional scanning image Pic (x, y) represents the pixel color of the x-th row and the y-th column of the ultrasonic C scanning image; the two-dimensional color bar Col (m, n) represents the colors of the pixels in the m-th row and the n-th column in the color bar, and the amplitude Amp ranges from [0,100] for different colors in the color bar.
Preferably, the three-dimensional image array and the three-dimensional color band array in the RGB mode in step 1 are obtained by:
reading in an ultrasonic C scanning image Pic (x, y), wherein the read-in data is a three-dimensional image array Pic in an RGB mode RGB (x,y,i)，i＝1,2,3；Pic RGB (x, y, i) denotes the value of the x-th row and y-th column of the i-th layer; layer 1 data Pic RGB (x, y, 1) is the value of R, layer 2 data Pic RGB (x, y, 2) is the value of G, layer 3 data Pic RGB (x, y, 3) is the number of B;
reading in color bands Col (m, n) of the ultrasonic C scanning image, wherein the read data is a three-dimensional color band array Col in an RGB mode RGB (m,n,i)，i＝1,2,3；Col RGB (m, n, i) denotes the value of the m-th row and n-th column of the i-th layer; col of layer 1 data RGB (m, n, 1) is the value of R, the layer 2 data Col RGB (m, n, 2) is the value of G, and the layer 3 data Col RGB (m, n, 3) is the number of B; cause data Col RGB (m, n, i) the same column number in all layers is the same, only the 1 st column number Col in each layer is taken RGB (m,1,i)。
It is preferable that M is subjected to the treatment in step 1 1 、M 2 And M 3 Taking intersection, as follows:
M＝M 1 ∩M 2 ∩M 3 ；
in the formula: m represents three-dimensional color bar array Col RGB (m, 1, i) RGB data and three-dimensional image array Pic RGB (x, y, i) the row number corresponding to the same RGB data of the x-th row and the y-th column.
Preferably, when the structural feature is not detected in step 3, the non-structural-feature completeness calculation is performed, specifically:
two-dimensional amplitude data A (x) θ ,y θ ) The value of (A) is set to be 1, and the obtained values are 1, dimension and A (x) θ ,y θ ) The same two-dimensional data A' (x) θ ,y θ ) Counting the number of the whole pixels N, as shown in the following formula:
N＝∑A′(x θ ,y θ )；
in the formula: n represents the overall pixel number; a' (x) θ ,y θ ) Represents A (x) θ ,y θ ) Setting the numerical value of the data to be 1 to obtain two-dimensional data;
threshold range phi corresponding to defect amplitude F Two-dimensional amplitude data A (x) θ ,y θ ) The medium amplitude being in the threshold range phi F Built-in '1', the amplitude of wave is in the threshold range phi F The outer "0" is shown as follows:
in the formula:
representing a defect binarization matrix; phi F Representing a threshold range corresponding to the amplitude of the defect;
counting the number of defective pixels N F As follows:
in the formula: n is a radical of hydrogen F Indicating the number of defective pixels;
perfectness ratio alpha of tested piece without structural characteristics 1 The expression of (a) is:
in the formula: alpha (alpha) ("alpha") 1 And the completeness of the tested piece without structural characteristics is shown.
Preferably, when the structural feature is detected in step 3, the structural feature completeness calculation is performed, specifically:
according to the structural characteristics, the coordinate system corresponding to the boundary of the key area and the non-key area in the design parameters of the tested piece, two-dimensional amplitude data A (x) θ ,y θ ) Extracting structural feature region (x) As ,y As ) Critical area (x) Ac ,y Ac ) And non-critical area (x) Anc ,y Anc )；
To be obtained (x) As ,y As )、(x Ac ,y Ac )、(x Anc ,y Anc ) The data is stored, and the stored data can be used for automatically importing the structural characteristics, the key areas and the non-key areas of the tested pieces in the same batch; two-dimensional amplitude data A (x) θ ,y θ ) The numerical value of (A) is set to be 1, and the numerical values of (A), (B) and (X) are all 1 θ ,y θ ) The same two-dimensional data A' (x) θ ,y θ ) (ii) a Respectively counting the pixel number N of the key area and the non-key area c 、N nc The calculation method is as follows:
in the formula: n is a radical of c Indicating the number of pixels in the key area; n is a radical of nc Representing the number of pixels in the non-critical area; omega c Indicates the boundary (x) Ac ,y Ac ) A region enclosed; omega nc Indicates the boundary (x) Anc ,y Anc ) A region enclosed;
two-dimensional amplitude data A (x) θ ,y θ ) Middle by boundary (x) As ,y As ) Enclose into region omega s The value of (c) is set to "0", and the dimension and A (x) are obtained θ ,y θ ) The same two-dimensional data A' (x) θ ,y θ ) Eliminating the influence of the structural characteristics on the statistical result of the defect area; on the basis, setting a threshold value range phi corresponding to the defect amplitude F Two-dimensional data A' (x) θ ,y θ ) The medium amplitude being in the threshold range phi F Built-in '1', the amplitude of wave is in the threshold range phi F The outer "0" is shown as follows:
in the formula: a' (x) θ ,y θ ) Representing the two-dimensional data after the structural features are removed;
respectively counting the number N of the defective pixels in the key area and the non-key area Fc And N Fnc The calculation method is as follows:
in the formula: n is a radical of Fc Indicating the number of pixels defective in the critical area; n is a radical of Fnc Indicating the number of pixels defective in the non-critical area;
respectively calculating the integrity rates alpha of the key area, the non-key area and the tested piece with the structural characteristics c 、α nc And alpha 2 As follows:
in the formula: alpha (alpha) ("alpha") c And alpha nc Respectively representing the completeness of the test piece in a key area and a non-key area; alpha is alpha 2 Indicating the completeness of the piece under test with structural features.
Preferably, the amplitude data A (x) in two dimensions θ ,y θ ) Extracting structural feature region (x) As ,y As ) Key region (x) Ac ,y Ac ) And non-critical area (x) Anc ,y Anc ) The method specifically comprises the following steps:
according to the structural characteristics in the design parameters of the tested piece, the coordinate system corresponding to the boundary of the key area and the non-key area, the two-dimensional amplitude data A (x) θ ,y θ ) Extracting structural features, key areas and non-key areas;
the method for acquiring the coordinate corresponding to the structural feature region boundary is as follows:
in the formula: x is a radical of a fluorine atom s And y s Respectively representing the corresponding abscissa and ordinate of the structural feature region boundary in the design parameters; x is the number of As And y As Respectively represent two-dimensional amplitude data A (x) θ ,y θ ) The middle structure characteristic region boundary corresponds to a horizontal coordinate and a vertical coordinate; l and W are the length and width, respectively, of the design parameter; p and Q are two-dimensional amplitude data A (x), respectively θ ,y θ ) A total number of rows and a total number of columns;
the coordinate acquisition method corresponding to the key area boundary is as follows:
in the formula: x is the number of c And y c Respectively representing the abscissa and the ordinate corresponding to the key area boundary in the design parameters; x is a radical of a fluorine atom Ac And y Ac Respectively represent two-dimensional amplitude data A (x) θ ,y θ ) The middle key area boundary corresponds to a horizontal coordinate and a vertical coordinate;
the coordinate acquisition method corresponding to the non-key area boundary is as follows:
in the formula: x is the number of nc And y nc Respectively representing the corresponding coordinates of the non-key area boundary in the design parameters; x is a radical of a fluorine atom Anc And y Anc Respectively representing two-dimensional amplitude data A (x) θ ,y θ ) The middle non-key area boundary corresponds to coordinates.
Compared with the prior art, the invention has the beneficial effects that:
(1) The method obtains defect detailed information by ultrasonic C scanning of a tested piece, divides the tested piece into two states of undetected structural characteristics and detected structural characteristics through amplitude data of the tested piece, divides the tested piece with the structural characteristics into a key area and a non-key area, further determines a scientific test piece completeness rate detection mode according to the structural characteristics of the tested piece, and completes the computation of completeness rate;
(2) The test piece completeness analysis method provided by the method can be used for carrying out defect analysis on the test piece with or without structural characteristics, calculating the completeness of the tested test piece, has high accuracy, flexible operation and wide applicability, and provides an effective solution for defect analysis of ultrasonic C scanning images.
Drawings
FIG. 1 is a control block diagram of a test piece integrity analysis method based on ultrasonic C-scan digital image processing according to an embodiment of the present invention;
FIG. 2 is a flowchart of a specimen integrity analysis method based on ultrasonic C-scan digital image processing according to an embodiment of the present invention;
FIG. 3 is an ultrasonic C-scan image of a defect-free superplastic forming diffusion bonding test part according to an embodiment of the present invention;
FIG. 4 is an ultrasonic C-scan image of a defective superplastic forming diffusion bonding test piece in accordance with an embodiment of the present invention;
FIG. 5 is a picture import of a process of analyzing an ultrasonic C-scan image of a superplastic forming diffusion bonded test piece according to an embodiment of the present invention;
FIG. 6 shows the result of selecting the structural parameters, the key regions and the non-key regions after the image correction of the process of analyzing the ultrasonic C-scan image of the superplastic forming diffusion bonding test piece according to the embodiment of the invention;
FIG. 7 shows the defect threshold input and technical result of a defect-free superplastic forming diffusion bonding test piece in the process of analyzing an ultrasonic C-scan image of a superplastic forming diffusion bonding test piece according to the embodiment of the present invention;
FIG. 8 shows the defect threshold input and technical result of a superplastic forming diffusion bonded test piece in the process of analyzing an ultrasonic C-scan image of the superplastic forming diffusion bonded test piece according to the embodiment of the present invention;
FIG. 9 is a C-scan image of a carbon fiber composite impact test piece according to an embodiment of the present invention;
fig. 10 is an analysis result of the carbon fiber composite impact test piece according to the embodiment of the present invention.
Detailed Description
Embodiments of the present invention will be described below with reference to the drawings.
According to the embodiment of the invention, the detailed information of the test piece is obtained by ultrasonically C-scanning a typical superplastic forming diffusion connection test piece and a carbon fiber composite material impact test piece, the test piece is divided into two states of undetected structural characteristics and detected structural characteristics through amplitude data of the test piece, the test piece with the structural characteristics is divided into a key area and a non-key area, a completeness detection mode of the tested piece is further determined according to the structural characteristics of the test piece, and the completeness calculation is completed. In the present invention, the integrity ratio of the tested object is the proportion of non-defective areas in a specific area of the tested object, where the specific area is a part of the integrity ratio calculation formula, and the specific area is different for different objects. For example, in a first test piece, the specific area includes a critical area, a non-critical area and the whole area of the test piece; in the second type of test piece, the specific area is the entire area of the test piece. Further, the specific region may be a clear region defined according to specific detection requirements. The test piece completeness analysis method provided by the embodiment of the invention can be used for carrying out defect analysis on the test piece with or without structural characteristics, and the completeness of the test piece calculated by the method can be proved through data comparison and analysis of settlement results, so that the method has the characteristic of high accuracy; the method is flexible to operate and high in applicability, and an effective solving way is provided for the defect analysis of the ultrasonic C scanning image. Fig. 1 is a control block diagram of a specimen integrity rate analysis method based on ultrasonic C-scan digital image processing according to an embodiment of the present invention.
The embodiment of the invention provides a test piece integrity rate detection method based on ultrasonic C scanning digital image processing, and as shown in FIG. 2, the invention provides a flow chart of a test piece integrity rate analysis method; to demonstrate the applicability of the invention, it is applied to the examples, comprising in particular the following steps:
s1: reading and processing image data of a tested piece to obtain two-dimensional amplitude data corresponding to the tested piece;
putting a tested piece into an ultrasonic C for scanning to obtain an RGB format two-dimensional scanning image Pic (x, y) and a two-dimensional color band Col (m, n) thereof; converting RGB format two-dimensional scanning image Pic (x, y) into RGB mode three-dimensional image array Pic RGB (x, y, i), i =1,2,3; converting RGB format two-dimensional scanning color band Col (m, n) into RGB mode three-dimensional color band array Col RGB (m,n,i)，i＝1,2,3；
The two-dimensional scanning image Pic (x, y) represents the pixel color of the x-th row and the y-th column of the ultrasonic C scanning image; the two-dimensional color bar Col (m, n) represents the pixel colors of the m-th row and the n-th column in the color bar, and the amplitude Amp ranges from 0,100 for different colors in the color bar. FIG. 3 is an ultrasonic C-scan image of a defect-free superplastic forming diffusion bonded test part according to an embodiment of the present invention; FIG. 4 shows an ultrasonic C-scan image of a defective superplastic forming diffusion bonded test piece according to an embodiment of the present invention.
Reading in an ultrasonic C scanning image Pic (x, y), wherein the read-in data is a three-dimensional image array Pic in an RGB mode RGB (x,y,i)，i＝1,2,3；Pic RGB (x, y, i) denotes the value of the x-th row and y-th column of the i-th layer; layer 1 data Pic RGB (x, y, 1) is the value of R, layer 2 data Pic RGB (x, y, 2) is the value of G, layer 3 data Pic RGB (x, y, 3) is the number of B;
reading in color bands Col (m, n) of the ultrasonic C scanning image, wherein the read data is a three-dimensional color band array Col in an RGB mode RGB (m,n,i)，i＝1,2,3；Col RGB (m, n, i) denotes the value of the m-th row and n-th column of the i-th layer; layer 1 data Col RGB (m, n, 1) is the value of R, the layer 2 data Col RGB (m, n, 2) is the value of G, and the layer 3 data Col RGB (m, n, 3) is the number of B; cause data Col RGB (m, n, i) the same column number is the same in all layers, and only the 1 st column number Col in each layer is taken RGB (m, 1, i). Fig. 5 shows the introduction of the image of the flow for analyzing the ultrasonic C-scan image of the superplastic forming diffusion bonding test piece according to the embodiment of the present invention.
Three-dimensional image array Pic of RGB mode RGB The x-th row and y-th column data Pic in each layer (x, y, i) RGB (x,y,1)、Pic RGB (x, y, 2) and Pic RGB (x, y, 3) and color bar data Col, respectively RGB (m, n, i) m-th row and 1-th column data Col in each layer RGB (m,1,1)、Col RGB (m, 1, 2) and Col RGB (m, 1, 3) comparing and searching Col RGB (m, 1, i) with Pic RGB The corresponding line number M when the (x, y, i) values are the same i (i =1,2,3), the calculation procedure is as follows:
in the formula: m is a group of 1 、M 2 And M 3 Respectively representing the corresponding line numbers when the image array and the color band array in the 1 st, the 2 nd and the 3 rd layers have the same numerical value, wherein each M is i The number of middle row numbers is at least 1; pic RGB (x, y, i) represents the pixel values of the x row and the y column of the ith layer in the three-dimensional image array; col (Col) RGB (m, 1, i) represents the pixel value of the mth layer in the three-dimensional color bar array; x and y respectively represent the row number and the column number of the image array; find represents a lookup function that assigns a row number in the array that satisfies the condition value listed in parentheses to M to the left of the equal sign i (ii) a i represents the number of layers in the three-dimensional image array; m represents the pixel number in the three-dimensional color band array;
to M is aligned with 1 、M 2 And M 3 Taking intersection as follows:
M＝M 1 ∩M 2 ∩M 3 ；
in the formula: m representsThree-dimensional color band array Col RGB (m, 1, i) RGB data and three-dimensional image array Pic RGB (x, y, i) the row number corresponding to the same RGB data of the x-th row and the y-th column.
Three-dimensional image data Pic RGB The two-dimensional amplitude data corresponding to the (x, y, i) th row and y column data is as follows:
a(x,y)＝Amp(M)；
in the formula: a (x, y) represents two-dimensional amplitude data of the three-dimensional image data in the x-th row and the y-th column; amp denotes color bar array Col RGB The amplitude value corresponding to each row value in (m, 1, i) is in the value range of 0,100](ii) a M represents three-dimensional color bar array Col RGB (m, 1, i) RGB data and three-dimensional image array Pic RGB (x, y, i) the corresponding line number when the RGB data of the x-th line and the y-th line are the same;
processing three-dimensional image array Pic RGB For each x row and y column data of each layer in (x, y, i), for the three-dimensional image array Pic RGB Carrying out amplitude conversion on the data in the (x, y, i) to obtain corresponding two-dimensional amplitude data a (x, y);
s2: preprocessing and correcting two-dimensional amplitude data of a tested piece;
acquiring the two-dimensional amplitude data obtained in the S1, and processing the imported two-dimensional amplitude data a (x, y) by adopting two-dimensional median filtering of a 5 x 5 neighborhood block, so as to reduce speckle noise and salt and pepper noise in the image data and realize preprocessing operation; rotating the image according to the following formula, correcting the image to obtain corrected two-dimensional amplitude data A (x) θ ,y θ ) The calculation process is as follows:
in the formula: θ represents a correction angle of the image; x is the number of θ And y θ Respectively representing two-dimensional amplitude data A (x) θ ,y θ ) The row and column numbers of; a (x) θ ,y θ ) Representing two-dimensional amplitude data at x θ Line, y θ The amplitude of the column;
s3: judging whether the structural features of the tested piece are detected or not, and obtaining the completeness of the tested piece;
the structural characteristics of the invention mean that the amplitude and the depth in the ultrasonic C-scan image are displayed as same as the defects, and the other defects can not be distinguished through the adjustment of an amplitude threshold and a depth gate; the structural characteristics comprise that the amplitude and the depth of an ultrasonic C-scan image are the same as those of a defect; when the structural features are not detected, the structural feature-free completeness calculation is executed, and the two-dimensional amplitude data A (x) is counted by setting a defect amplitude threshold value θ ,y θ ) The number of defective pixels and the number of pixels in the whole area within the threshold range of the defect amplitude are calculated, and the ratio of the number of defective pixels and the number of pixels in the whole area is used as the perfectness ratio alpha of the tested piece without structural characteristics 1 ；
Two-dimensional amplitude data A (x) θ ,y θ ) The numerical value of (A) is set to be 1, and the numerical values of (A), (B) and (X) are all 1 θ ,y θ ) The same two-dimensional data A' (x) θ ,y θ ) And counting the number N of the integral pixels, as shown in the following formula:
N＝∑A′(x θ ,y θ )；
in the formula: n represents the overall number of pixels; a' (x) θ ,y θ ) Represents A (x) θ ,y θ ) Setting the numerical value of the data to be 1 to obtain two-dimensional data;
threshold range phi corresponding to defect amplitude F Two-dimensional amplitude data A (x) θ ,y θ ) The medium amplitude being in the threshold range phi F Built-in '1', the amplitude of wave is in the threshold range phi F The outer "0" is shown as follows:
in the formula:
representing a defect binarization matrix; phi F Representing a threshold range corresponding to the amplitude of the defect;
counting the number of defective pixels N F As followsShown in the figure:
in the formula: n is a radical of F Indicating the number of defective pixels;
perfectness alpha of tested piece without structural characteristics 1 The expression of (a) is:
in the formula: alpha (alpha) ("alpha") 1 Indicating the completeness of the piece under test without structural features.
When the structural feature exists in the detected image, the corrected image is superposed with the design parameter of the tested piece, and the two-dimensional amplitude data A (x) can be obtained according to the structural feature, the key area and the coordinates in the non-key area in the design parameter of the tested piece θ ,y θ ) Automatically acquiring the boundary of the relevant area so as to calculate the integrity rate alpha of the key area c Perfection ratio alpha of non-critical area nc And the integrity factor alpha of the tested piece with structural characteristics 2 And finally obtaining the completeness of the tested piece. Fig. 6 shows a result of selecting the structure parameters, the key regions, and the non-key regions after the image correction in the process of analyzing the ultrasonic C-scan image of the superplastic forming diffusion bonded test piece according to the embodiment of the present invention.
According to the structural characteristics in the design parameters of the tested piece, the coordinate system corresponding to the boundary of the key area and the non-key area, the two-dimensional amplitude data A (x) θ ,y θ ) Extracting structural feature region (x) As ,y As ) Key region (x) Ac ,y Ac ) And non-critical area (x) Anc ,y Anc )；
The method for acquiring the coordinates corresponding to the structural feature region boundary is as follows:
in the formula: x is the number of s And y s Respectively representing the corresponding abscissa and ordinate of the structural feature region boundary in the design parameters; x is a radical of a fluorine atom As And y As Respectively representing two-dimensional amplitude data A (x) θ ,y θ ) The middle structure characteristic region boundary corresponds to a horizontal coordinate and a vertical coordinate; l and W are the length and width, respectively, of the design parameter; p and Q are two-dimensional amplitude data A (x), respectively θ ,y θ ) A total number of rows and a total number of columns;
the coordinate acquisition method corresponding to the boundary of the key area is as follows:
in the formula: x is a radical of a fluorine atom c And y c Respectively representing the abscissa and the ordinate corresponding to the key area boundary in the design parameters; x is a radical of a fluorine atom Ac And y Ac Respectively representing two-dimensional amplitude data A (x) θ ,y θ ) The middle key area boundary corresponds to a horizontal coordinate and a vertical coordinate;
the coordinate acquisition method corresponding to the non-critical area boundary is as follows:
in the formula: x is a radical of a fluorine atom nc And y nc Respectively representing the corresponding coordinates of the non-key area boundary in the design parameters; x is the number of Anc And y Anc Respectively representing two-dimensional amplitude data A (x) θ ,y θ ) The middle non-critical area boundary corresponds to coordinates.
To be obtained (x) As ,y As )、(x Ac ,y Ac )、(x Anc ,y Anc ) The data is stored, and the stored data can be used for automatically importing the structural characteristics, the key areas and the non-key areas of the tested pieces in the same batch; two-dimensional amplitude data A (x) θ ,y θ ) The numerical value of (A) is set to be 1, and the numerical values of (A), (B) and (X) are all 1 θ ,y θ ) The same two-dimensional data A' (x) θ ,y θ ) (ii) a Respectively counting the pixel number N of the key area and the non-key area c 、N nc The calculation method is as follows:
in the formula: n is a radical of c Indicating the number of pixels in the key area; n is a radical of nc Representing the number of pixels in the non-critical area; omega c Indicating a boundary (x) Ac ,y Ac ) A region enclosed; omega nc Indicating a boundary (x) Anc ,y Anc ) A region enclosed;
two-dimensional amplitude data A (x) θ ,y θ ) Middle band boundary (x) As ,y As ) Enclose into a region omega s The value of (c) is set to "0", and the dimension and A (x) are obtained θ ,y θ ) The same two-dimensional data A' (x) θ ,y θ ) Eliminating the influence of the structural characteristics on the statistical result of the defect area; on the basis, setting a threshold value range phi corresponding to the defect amplitude F Two-dimensional data A' (x) θ ,y θ ) The medium amplitude is in the threshold range phi F Built-in '1', the amplitude of wave is in the threshold range phi F The outer "0" is shown as follows:
in the formula: a' (x) θ ,y θ ) Representing the two-dimensional data after the structural features are removed;
respectively counting the number N of the defective pixels in the key area and the non-key area Fc And N Fnc The calculation method is as follows:
in the formula: n is a radical of hydrogen Fc Indicating the number of pixels defective in the critical area; n is a radical of Fnc Indicating the number of pixels defective in the non-critical area;
respectively calculating the integrity rates alpha of the key area, the non-key area and the tested piece with the structural characteristics c 、α nc And alpha 2 As follows:
in the formula: alpha (alpha) ("alpha") c And alpha nc Respectively representing the completeness of the test piece in a key area and a non-key area; alpha is alpha 2 Indicating the completeness of the piece under test with structural features.
Finally, the integrity of the tested piece is obtained. Fig. 7 shows the defect threshold input and the technical result of the defect-free superplastic forming diffusion bonding test piece in the process of analyzing the ultrasonic C-scan image of the superplastic forming diffusion bonding test piece according to the embodiment of the present invention; fig. 8 shows the defect threshold input and the technical result of the defect superplastic forming diffusion bonding test piece in the process of analyzing the ultrasonic C-scan image of the superplastic forming diffusion bonding test piece according to the embodiment of the present invention.
Setting the defect threshold range as [90,100], respectively counting the number of pixels of the critical area, the non-critical area, the whole tested piece and the defects therein, and respectively calculating the completeness of the critical area, the non-critical area and the whole. The results of calculations for the superplastic forming diffusion bonded specimens with no defects are shown in fig. 7 and 8, respectively. The critical area, the non-critical area and the overall integrity of the tested test piece of the defect-free superplastic forming diffusion bonding test piece are respectively 99.83 percent, 99.22 percent and 99.36 percent; the critical area, the non-critical area and the overall integrity of the tested test piece of the defective superplastic forming diffusion bonding test piece are respectively 99.73%, 96.20% and 96.90%.
The calculation procedure for the second test piece is as follows; FIG. 9 shows a C-scan image of an impact test piece of carbon fiber composite material according to an embodiment of the present invention; fig. 10 shows the analysis result of the impact test piece of the carbon fiber composite material according to the embodiment of the present invention. Set defect threshold range to 0,30]And respectively counting the whole tested piece and the number of the defective pixels in the tested piece, and calculating the perfectness ratio. The carbon fiber composite impact test piece perfection rate is 99.26%. When the temperature is higher than the set temperatureWhen the area of the area to be analyzed of the test piece is known, the defect area can be calculated according to the perfection rate of the test piece, for example, the area of the carbon fiber composite material impacting the test piece is 15000.00mm 2 Therefore, the impact damage area is calculated and known to be 111.00mm 2 。
Tables 1 and 2 show the data related to the calculation of the integrity of the first test piece and the second test piece, respectively, according to the present application. For comparison, the first and second test pieces were measured for the integrity by the length measuring function of the software part of the commercial ultrasonic C-scan test system, and the calculation results are shown in table 3. Comparing the table 1, the table 2 and the table 3 respectively, the defect area measured by using the commercial software length measuring function is larger due to irregular defect shape, so that the completeness rate of the tested piece is lower, and the calculation is inaccurate; in addition, for the first test piece, the influence of the structural features cannot be removed by using commercial software, and the perfectness ratios of the critical area and the non-critical area cannot be calculated separately.
TABLE 1 calculation results of the first defective test piece of the present application
TABLE 2 calculation results of the second test piece of the present application
| Number of integral pixels, N | Number of defective pixels, N F | Fraction of integrity of the test piece, alpha | |
| Second kind of test piece | 207074 | 1528 | 99.26％ |
TABLE 3 first and second test piece commercial software measurement results
In conclusion, the test piece integrity rate detection method based on ultrasonic C scanning digital image processing proves that the method has a good effect.
(1) According to the embodiment of the invention, the detailed information of the test piece is obtained by scanning the typical superplastic forming diffusion connection test piece and the carbon fiber composite material impact test piece through ultrasonic C, the test piece is divided into two states of undetected structural characteristics and detected structural characteristics through the amplitude data of the test piece, the test piece with the structural characteristics is divided into a key area and a non-key area, a scientific test piece completeness rate detection mode is further determined according to the structural characteristics of the test piece, and the completeness rate calculation is completed;
(2) The method for analyzing the test piece completeness can be used for analyzing the defects of the test piece with or without structural characteristics, and the completeness of the tested piece calculated by the method can be proved through data comparison and analysis of settlement results, so that the method has the characteristic of high accuracy; the method is flexible to operate and high in applicability, and an effective solving way is provided for defect analysis of the ultrasonic C scanning image.
The above-mentioned embodiments are merely illustrative of the preferred embodiments of the present invention, and do not limit the scope of the present invention, and various modifications and improvements of the technical solution of the present invention made by those skilled in the art without departing from the spirit of the present invention should fall within the protection scope defined by the claims of the present invention.
Claims (7)
1. A test piece integrity detection method based on ultrasonic C scanning digital image processing is characterized by comprising the following steps:
step 1: reading and processing image data of a tested piece to obtain two-dimensional amplitude data corresponding to the tested piece;
putting a tested piece into an ultrasonic C for scanning to obtain an RGB format two-dimensional scanning image Pic (x, y) and a two-dimensional color band Col (m, n) thereof; converting RGB format two-dimensional scanning image Pic (x, y) into RGB mode three-dimensional image array Pic RGB (x, y, i), i =1,2,3; converting RGB format two-dimensional scanning color band Col (m, n) into RGB mode three-dimensional color band array Col RGB (m,n,i)，i＝1,2,3；
Three-dimensional image array Pic with RGB mode RGB In each layer (x, y, i), the x-th row and the y-th column data Pic RGB (x,y,1)、Pic RGB (x, y, 2) and Pic RGB (x, y, 3) and color bar data Col RGB (m, n, i) m-th row and 1-th column data Col in each layer RGB (m,1,1)、Col RGB (m, 1, 2) and Col RGB (m, 1, 3) comparing and searching Col RGB (m, 1, i) with Pic RGB The corresponding row number M when the (x, y, i) values are the same i (i =1,2,3), the calculation procedure is as follows:
in the formula: m is a group of 1 、M 2 And M 3 Respectively representing the corresponding line numbers when the image array and the color bar array in the 1 st, the 2 nd and the 3 rd layers have the same numerical value, and each M i The number of middle row numbers is at least 1; pic RGB (x, y, i) represents the pixel values of the x row and the y column of the ith layer in the three-dimensional image array; col (Col) RGB (m, 1, i) represents the pixel value of the mth layer in the three-dimensional color bar array; x and y respectively represent the row number and the column number of the image array; find represents the lookup function, will be full in the arrayThe row number where the condition value listed in the bracket is located is assigned to M to the left of the equal sign i (ii) a i represents the number of layers in the three-dimensional image array; m represents the pixel number in the three-dimensional color band array;
three-dimensional image data Pic RGB The two-dimensional amplitude data corresponding to the (x, y, i) th row and y column data is as follows:
a(x,y)＝Amp(M)；
in the formula: a (x, y) represents two-dimensional amplitude data of the three-dimensional image data in the x-th row and the y-th column; amp represents the color bar array Col RGB The amplitude value corresponding to each row value in (m, 1, i) is in the value range of [0,100]](ii) a M represents three-dimensional color bar array Col RGB RGB data of (m, 1, i) and three-dimensional image array Pic RGB The row number corresponding to the same RGB data of the (x, y, i) x-th row and the y-th column is represented by M 1 、M 2 And M 3 Obtaining an intersection;
processing three-dimensional image array Pic RGB For each x row and y column data of each layer in (x, y, i), for the three-dimensional image array Pic RGB Carrying out amplitude conversion on the data in the (x, y, i) to obtain corresponding two-dimensional amplitude data a (x, y);
and 2, step: preprocessing and correcting two-dimensional amplitude data of a tested piece;
acquiring the two-dimensional amplitude data obtained in the step (1), and processing the imported two-dimensional amplitude data a (x, y) by adopting two-dimensional median filtering of a 5 x 5 neighborhood block, so as to reduce speckle noise and salt and pepper noise in image data and realize preprocessing operation; rotating the image according to the following formula, correcting the image to obtain corrected two-dimensional amplitude data A (x) θ ,y θ ) The calculation process is as follows:
in the formula: θ represents a correction angle of the image; x is a radical of a fluorine atom θ And y θ Respectively representing two-dimensional amplitude data A (x) θ ,y θ ) The row and column numbers of; a (x) θ ,y θ ) Representing two-dimensional amplitude data at x θ Line, y θ Amplitude of the column;
and 3, step 3: judging whether the structural features of the tested piece are detected or not, and obtaining the completeness of the tested piece;
when the structural feature is not detected, the structural feature-free integrity calculation is performed, and the two-dimensional amplitude data A (x) is counted by setting a defect amplitude threshold value θ ,y θ ) The number of defective pixels and the number of pixels in the whole area within the threshold range of the defect amplitude are calculated, and the ratio of the number of defective pixels and the number of pixels in the whole area is used as the perfectness ratio alpha of the tested piece without structural features 1 (ii) a When the structural feature exists in the detected image, the corrected image is superposed with the design parameter of the tested piece, and the two-dimensional amplitude data A (x) can be obtained according to the structural feature, the key area and the non-key area of the design parameter of the tested piece θ ,y θ ) Automatically acquiring the boundary of the relevant area so as to calculate the perfectness ratio alpha of the key area c Perfection ratio alpha of non-critical area nc And the fraction of integrity alpha of the tested piece with structural features 2 And finally obtaining the completeness of the tested piece.
2. The method for detecting the specimen integrity rate based on the ultrasonic C-scan digital image processing according to claim 1, wherein the two-dimensional scan image Pic (x, y) and the two-dimensional color bands Col (m, n) thereof in step 1 are specifically:
the two-dimensional scanning image Pic (x, y) represents the pixel color of the x-th row and the y-th column of the ultrasonic C scanning image; the two-dimensional color bar Col (m, n) represents the colors of the pixels in the m-th row and the n-th column in the color bar, and the amplitude Amp ranges from [0,100] for different colors in the color bar.
3. The method for detecting the specimen integrity rate based on the ultrasonic C-scan digital image processing according to claim 1, wherein the three-dimensional image array and the three-dimensional color band array in the RGB mode in step 1 are obtained by:
reading in an ultrasonic C scanning image Pic (x, y), wherein the read data is a three-dimensional image array Pic in an RGB mode RGB (x,y,i)，i＝1,2,3；Pic RGB (x, y, i) represents the ithThe value of the x-th row and y-th column of the layer; layer 1 data Pic RGB (x, y, 1) is the value of R, layer 2 data Pic RGB (x, y, 2) is the value of G, layer 3 data Pic RGB (x, y, 3) is the number of B;
reading in color bands Col (m, n) of the ultrasonic C scanning image, wherein the read data is a three-dimensional color band array Col in an RGB mode RGB (m,n,i)，i＝1,2,3；Col RGB (m, n, i) denotes the value of the m-th row and n-th column of the i-th layer; data Col in layer 1 RGB (m, n, 1) is the value of R, the layer 2 data Col RGB (m, n, 2) is the value of G, and the layer 3 data Col RGB (m, n, 3) is the number of B; cause data Col RGB (m, n, i) the same column number is the same in all layers, and only the 1 st column number Col in each layer is taken RGB (m,1,i)。
4. The method for detecting the test piece integrity rate based on ultrasonic C-scan digital image processing as claimed in claim 1, wherein M is measured in step 1 1 、M 2 And M 3 Taking intersection as follows:
M＝M 1 ∩M 2 ∩M 3 ；
in the formula: m represents three-dimensional color bar array Col RGB RGB data of (m, 1, i) and three-dimensional image array Pic RGB (x, y, i) the row number corresponding to the same RGB data of the x-th row and the y-th column.
5. The method for detecting the specimen integrity rate based on the ultrasonic C-scan digital image processing according to claim 1, wherein when the structural feature is not detected in the step 3, the calculation of the structural feature-free integrity rate is performed, specifically:
two-dimensional amplitude data A (x) θ ,y θ ) The numerical value of (A) is set to be 1, and the numerical values of (A), (B) and (X) are all 1 θ ,y θ ) The same two-dimensional data A' (x) θ ,y θ ) Counting the number of the whole pixels N, as shown in the following formula:
N＝∑A′(x θ ,y θ )；
in the formula: n denotes a whole pixelThe number of the components; a' (x) θ ,y θ ) Represents A (x) θ ,y θ ) Setting the numerical value of the data to be 1 to obtain two-dimensional data;
threshold range phi corresponding to defect amplitude F Two-dimensional amplitude data A (x) θ ,y θ ) The medium amplitude is in the threshold range phi F Built-in '1', the amplitude of wave is in the threshold range phi F The outer "0" is shown as follows:
in the formula:
representing a defect binarization matrix; phi F Representing a threshold range corresponding to the amplitude of the defect;
counting the number of defective pixels N F As follows:
in the formula: n is a radical of hydrogen F Indicating the number of defective pixels;
perfectness alpha of tested piece without structural characteristics 1 The expression of (a) is:
in the formula: alpha is alpha 1 Indicating the completeness of the piece under test without structural features.
6. The method for detecting the specimen integrity rate based on the ultrasonic C-scan digital image processing according to claim 1, wherein when the structural feature is detected in the step 3, the structural feature integrity rate calculation is performed, specifically:
designing parameters according to the tested pieceCounting the coordinate system corresponding to the structural feature, the key area and the non-key area boundary in the two-dimensional amplitude data A (x) θ ,y θ ) Extracting structural feature region (x) As ,y As ) Critical area (x) Ac ,y Ac ) And non-critical area (x) Anc ,y Anc )；
To be obtained (x) As ,y As )、(x Ac ,y Ac )、(x Anc ,y Anc ) The data is stored, and the stored data can be used for automatically importing the structural features, the key areas and the non-key areas of the tested pieces in the same batch; two-dimensional amplitude data A (x) θ ,y θ ) The numerical value of (A) is set to be 1, and the numerical values of (A), (B) and (X) are all 1 θ ,y θ ) The same two-dimensional data A' (x) θ ,y θ ) (ii) a Respectively counting the pixel number N of the key area and the non-key area c 、N nc The calculation method is as follows:
in the formula: n is a radical of hydrogen c Indicating the number of pixels in the key area; n is a radical of nc Representing the number of pixels in the non-critical area; omega c Indicating a boundary (x) Ac ,y Ac ) A region enclosed; omega nc Indicates the boundary (x) Anc ,y Anc ) A region enclosed;
two-dimensional amplitude data A (x) θ ,y θ ) Middle by boundary (x) As ,y As ) Enclose into region omega s The value of (c) is set to "0", and the dimension and A (x) are obtained θ ,y θ ) The same two-dimensional data A' (x) θ ,y θ ) Eliminating the influence of the structural characteristics on the statistical result of the defect area; on the basis, setting a threshold value range phi corresponding to the defect amplitude F Two-dimensional data A' (x) θ ,y θ ) The medium amplitude being in the threshold range phi F Built-in '1', the amplitude of wave is in the threshold range phi F The outer "0" is shown as follows:
in the formula: a' (x) θ ,y θ ) Representing the two-dimensional data after the structural features are removed;
respectively counting the number N of the defective pixels in the key area and the non-key area Fc And N Fnc The calculation method is as follows:
in the formula: n is a radical of Fc Indicating the number of pixels defective in the critical area; n is a radical of hydrogen Fnc Indicating the number of pixels defective in the non-critical area;
respectively calculating the integrity rate alpha of the tested piece when the key area, the non-key area and the structural feature exist c 、α nc And alpha 2 As follows:
in the formula: alpha is alpha c And alpha nc Respectively representing the completeness of the test piece in a key area and a non-key area; alpha (alpha) ("alpha") 2 And the completeness of the tested piece with the structural characteristics is shown.
7. The method for testing specimen integrity rate based on ultrasonic C-scan digital image processing as claimed in claim 6, wherein the two-dimensional amplitude data A (x) is obtained θ ,y θ ) Extracting structural feature region (x) As ,y As ) Key region (x) Ac ,y Ac ) And non-critical area (x) Anc ,y Anc ) The method specifically comprises the following steps:
according to the structural characteristics, the coordinate system corresponding to the boundary of the key area and the non-key area in the design parameters of the tested piece, two-dimensional amplitude data A (x) θ ,y θ ) Extracting structural features from the raw materials,Critical and non-critical areas;
the method for acquiring the coordinate corresponding to the structural feature region boundary is as follows:
in the formula: x is a radical of a fluorine atom s And y s Respectively representing the corresponding abscissa and ordinate of the structural feature region boundary in the design parameters; x is the number of As And y As Respectively representing two-dimensional amplitude data A (x) θ ,y θ ) The middle structure characteristic region boundary corresponds to a horizontal coordinate and a vertical coordinate; l and W are the length and width, respectively, of the design parameter; p and Q are two-dimensional amplitude data A (x), respectively θ ,y θ ) A total number of rows and a total number of columns;
the coordinate acquisition method corresponding to the key area boundary is as follows:
in the formula: x is the number of c And y c Respectively representing the abscissa and the ordinate corresponding to the key area boundary in the design parameters; x is the number of Ac And y Ac Respectively representing two-dimensional amplitude data A (x) θ ,y θ ) The middle key area boundary corresponds to a horizontal coordinate and a vertical coordinate;
the coordinate acquisition method corresponding to the non-key area boundary is as follows:
in the formula: x is the number of nc And y nc Respectively representing the corresponding coordinates of the non-key area boundary in the design parameters; x is a radical of a fluorine atom Anc And y Anc Respectively representing two-dimensional amplitude data A (x) θ ,y θ ) The middle non-critical area boundary corresponds to coordinates.
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