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CN114994176A - Hole defect accurate measurement method based on ultrasonic threshold imaging - Google Patents

Hole defect accurate measurement method based on ultrasonic threshold imaging Download PDF

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CN114994176A
CN114994176A CN202210577710.5A CN202210577710A CN114994176A CN 114994176 A CN114994176 A CN 114994176A CN 202210577710 A CN202210577710 A CN 202210577710A CN 114994176 A CN114994176 A CN 114994176A
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李正光
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Guanggu Dalian Technology Development Co ltd
Dalian University Of Foreign Languages
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Guanggu Dalian Technology Development Co ltd
Dalian University Of Foreign Languages
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Abstract

The invention discloses a hole defect accurate measurement method based on ultrasonic threshold imaging, which comprises the steps of setting ultrasonic acquisition parameters and detecting equipment to be detected according to ultrasonic equipment; collecting ultrasonic signals by using a data acquisition card and a transceiver; ultrasonic threshold imaging, namely drawing a scanning image by utilizing gate information and a maximum peak algorithm; binarizing the scanned image; searching for a defect block in the image based on a depth-first search algorithm; calculating the total area of the defect according to the pixels of the defect block; designing a square matrix according to standard holes, constructing a matrix according to defect blocks, dividing the matrix transversely and longitudinally, calculating a matching result of the square matrix and a sub-matrix based on convolution matching, and judging whether the hole defects exist according to the matching result; and judging the equipment to be detected according to the judgment standard, if the threshold condition is not met, determining that the equipment is not qualified, and otherwise, determining that the equipment is qualified. The defect of the equipment to be detected can be accurately detected according to different standard holes, and the detection accuracy is improved.

Description

Hole defect accurate measurement method based on ultrasonic threshold imaging
Technical Field
The invention relates to the field of nondestructive testing based on ultrasonic imaging, in particular to a hole defect accurate measurement method based on ultrasonic threshold imaging.
Background
Nondestructive testing technology based on ultrasonic imaging is widely applied to defects of aircraft engine blades, aircraft composite materials and brazing welding seams. The identification of the defect and the measurement of the area and the shape of the defect in the nondestructive detection are two important technical directions. Defect detection can be automatically identified using manual identification and artificial intelligence techniques, however measurement of the area of a defective block and whether a defective block can contain a circular hole is a difficult problem in defect measurement. Based on the irregular shape of the defect block in the image drawn by the ultrasonic threshold, as shown in fig. 2, how to accurately judge that the defect block can contain a hole defect with a specified size so as to meet the qualification standard of the process engineer for the defect is a difficult problem to be solved in defect measurement. Specific problems include the fact that,
(1) for the determination of the defect block, the current method is mainly based on an edge detection technology, a convex polygon and an irregular polygon calculation method.
(2) For the measurement of whether the hole defect can be contained or not, the boundary of the defect block is determined by the determination method of the defect block, and whether the circle can collide with the boundary or not based on the center (gravity center) of the defect area is mostly adopted, and the hole defect can be contained if no collision exists, otherwise, the hole defect cannot be contained.
The existing method inevitably causes the enlargement of the defect blocks and the increase of the defect area when calculating the defect area; hole defect measurements may cause false positives and false negatives. Such as convex polygon center of gravity measurements, may cause false positives (because the shape itself is concave) while concave shapes may cause false negatives, such as the shape of fig. 3, which can accommodate 1cm hole defects. Therefore, the existing method can enlarge the defect area, and lead to the multi-detection and the omission of the hole defects. The defects are detected more, so that the qualification rate of the product is reduced, and raw materials are wasted; the defects are missed and the product percent of pass is high. The final delivered product may cause damage in the hands of the user, with less loss of money and more serious accidents, such as aerospace composites, which may lead to the loss of the aircraft and the explosion of the rocket. Therefore, the defects must be accurately measured, waste of excessive raw materials is avoided, missing detection is avoided, accidents are reduced, user experience is improved, and safety is guaranteed.
Disclosure of Invention
The invention provides an accurate hole defect measuring method based on ultrasonic threshold imaging, which aims to overcome the technical problems.
A hole defect accurate measurement method based on ultrasonic threshold imaging comprises the following steps,
setting ultrasonic acquisition parameters of ultrasonic equipment, acquiring an ultrasonic signal of equipment to be detected by using the ultrasonic equipment, and drawing an image C according to the ultrasonic signal;
step two, carrying out binarization processing on the image C, setting the pixel value of the pixel point higher than the threshold value in the image C to be 255, setting the pixel values of the rest pixel points to be 0, and storing the pixel value of the image C in a matrix F mn Wherein m is the number of rows of pixel points in the image C, and n is the number of columns of pixel points in the image C;
step three, for the matrix F mn When F is mn When the number is 255, the pixel points are regarded as defective pixel points, and the matrix F is traversed in sequence mn If the adjacent pixel points are all defect pixel points, merging is carried out, and the merged defect pixel point set is regarded as a vertex and is expressed as Q ip,iq Wherein ip represents the ith row and the pth column, iq represents the ith row and the pth column, p is a starting column mark of a vertex, and q is an ending column mark of the vertex;
step four, the slave matrix F mn Is the most important ofTraversing the subsequent row upwards, if two vertexes of the ith row and the jth row are simultaneously satisfied, connecting the two vertexes to represent as an edge, wherein j is i +1, an end column mark q +1 of the ith row is greater than or equal to a start column mark p of the jth row, and a start column mark-1 of the ith row is less than or equal to an end column mark of the jth row;
constructing an adjacency matrix according to the vertexes and the edges, traversing the adjacency matrix based on a depth-first search algorithm, acquiring each searched vertex path set, and regarding each vertex path set as a defect block;
step six, acquiring the vertex of each defect block, calculating the area of each defect block according to the defect pixel point set corresponding to the vertex, and calculating the total area A2 of all defect blocks according to the area of each defect block;
defining the size of a defect block based on different requirements, designing a standard hole according to the size of the defect block, constructing a square matrix, initializing the value of the square matrix to be 0, calculating the number of rows and columns of the square matrix according to the standard hole, and updating the value of the square matrix;
step eight, acquiring a maximum row mark, a minimum row mark, a maximum column mark and a minimum column mark of the defect block according to the vertex of the defect block, and constructing a matrix, wherein the size of the matrix is as follows: (maximum row mark-minimum row mark +1) × (maximum column mark-minimum column mark +1), initializing the value of the matrix to 0, and updating the matrix according to the position of the defective pixel point of the current defective block;
the updating of the matrix according to the positions of the defective pixel points of the current defective block means that subscript values s and t of the pixel points of each defective block are obtained, wherein s is a row value, t is a column value, and the values of the row values in the matrix are set to be s-minimum row marks and the column values are set to be t-minimum column mark positions and are updated to be 1;
step nine, when the number of rows or columns of the matrix is less than the number of rows of the square matrix, marking the defect block represented by the matrix as a non-hole defect, otherwise, dividing the matrix according to the size of the square matrix, wherein dividing the matrix by taking the size of the square matrix as a unit respectively along the transverse direction and the longitudinal direction, the transverse direction is along the column direction, the longitudinal direction is along the row direction, complementing the part which is not sufficiently divided into the square matrix into a complete square matrix, the value of the complemented part is 0, performing convolution matching on the divided sub-matrix and the square matrix according to a formula (1), when the matching result is less than or equal to a threshold value, taking the defect block represented by the matrix as a hole defect, and calculating the area A1 of the defect block containing the hole defect according to the step six,
Figure BDA0003661014230000031
where V represents the sum of the exclusive OR of the square matrix and the submatrix, M T The square matrix is represented by a matrix table,
Figure BDA0003661014230000032
it represents the i-th sub-matrix,
step ten, executing steps eight and nine on all the defect blocks, calculating the area A1 of all the hole defects, calculating the quality inspection parameters F1 and F2 according to the formulas (2) and (3), when the quality inspection parameters F1 and F2 and the quality inspection qualified thresholds Thresh _ F1 and Thresh _ F2 meet the formula (4), indicating that the equipment to be inspected is qualified, otherwise indicating that the equipment to be inspected is unqualified,
Figure BDA0003661014230000033
Figure BDA0003661014230000034
f1 ≧ Thresh _ F1 and F2 ≧ Thresh _ F2 (4)
Where a0 represents the theoretical weld area.
Preferably, the binarizing process on the image C refers to binarizing the image C based on a pixel histogram.
Preferably, the calculating the area of the defect block includes obtaining the actual area of the region to be detected of the device to be detected, the number of pixels of the scanned image obtained by the ultrasonic device, calculating the ratio between the area of the region to be detected and the number of pixels of the image, obtaining the number of pixels in the pixel set, and taking the product of the number of the pixels and the ratio as the area of the defect block.
The invention provides a hole defect accurate measurement method based on ultrasonic threshold imaging, which can accurately detect the defects of a part to be detected according to different standard holes and improve the detection accuracy.
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In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings needed to be used in the description of the embodiments or the prior art will be briefly introduced below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to these drawings without creative efforts.
FIG. 1 is a flow chart of the method of the present invention;
FIG. 2 is an exemplary diagram of the present invention containing irregular defect blocks;
FIG. 3 is a hole defect of the present invention capable of accommodating a 1cm hole;
FIG. 4 is a diagram of a convex hull partition visualization result of the present invention;
FIG. 5 is a diagram of a polygon partitioning visualization of the present invention;
FIG. 6 is a graph of the convolution matching partition visualization result of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, but not all, embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Fig. 1 is a flowchart of the method of the present invention, and as shown in fig. 1, the method of the present embodiment may include:
a hole defect accurate measurement method based on ultrasonic threshold imaging comprises,
setting ultrasonic acquisition parameters of ultrasonic equipment, wherein the parameters comprise sampling length, frequency, gate length, threshold value and start time; collecting an ultrasonic signal of equipment to be detected by using ultrasonic equipment, collecting the ultrasonic signal by using a data acquisition card and a transceiver, and drawing a drawing image C according to gate information and a maximum peak algorithm of the ultrasonic signal;
step two, carrying out binarization processing on the image C based on a pixel histogram, setting the pixel value of a pixel point higher than a threshold value in the image C to be 255, setting the pixel values of the rest pixel points to be 0, and storing the pixel value of the image C in a matrix F mn Wherein m is the number of rows of pixel points in the image C, and n is the number of columns of pixel points in the image C;
step three, for the matrix F mn When F is ij When the number of the pixels is 255, the pixels are regarded as defective pixels, each row of the matrix F is traversed in sequence, if the adjacent pixels are all defective pixels, merging is carried out, a set of the merged defective pixels is regarded as a vertex and is represented as Q ip,iq Wherein ip represents the ith row and the pth column, iq represents the ith row and the pth column, p is a starting column mark of a vertex, and q is an ending column mark of the vertex;
step four, the slave matrix F mn Traversing upwards, if two vertexes of the ith row and the jth row are simultaneously satisfied, connecting the two vertexes to represent an edge, wherein j is i +1, and the end column mark q +1 of the ith row is greater than or equal to the start column mark p of the jth row and the start column mark-1 of the ith row is less than or equal to the end column mark p of the jth row;
constructing an adjacency matrix according to the vertexes and the edges, traversing the adjacency matrix based on a Depth First Search (DFS) algorithm, acquiring each searched vertex path set, and regarding each vertex path set as a defect block;
step six, acquiring the vertex of each defect block, calculating the area of each defect block according to the defect pixel point set corresponding to the vertex, and calculating the total area A2 of all defect blocks according to the area of each defect block;
calculating the area of the defect block comprises the steps of obtaining the actual area of the area to be detected of the equipment to be detected, obtaining the number of pixels of the scanned image through ultrasonic equipment, calculating the proportion between the area of the area to be detected and the number of pixels of the scanned image, obtaining the number of pixels in a pixel set, and taking the product of the number of the pixels and the proportion as the area of the defect block;
step seven, defining the size of the defect block based on different requirements, for example, defining the defect block as a hole defect with the diameter d (0.5mm) according to the requirements, designing a standard hole according to the size of the defect block, constructing a square matrix, initializing the value of the square matrix to 0, calculating the number of rows and columns of the square matrix according to the standard hole, and updating the value of the square matrix;
designing a standard hole according to the size of the defect block refers to appointing that the defect block contains a hole defect with a fixed size, and calculating the number of pixel points of the standard hole based on the size and the proportion of the hole defect;
the step of calculating the number of rows and columns of the square matrix according to the standard holes is to calculate the number of rows and columns of the square matrix according to the number of the pixel points, and update the value in the square matrix to 1;
step eight, acquiring a maximum row mark, a minimum row mark, a maximum column mark and a minimum column mark of the defect block according to the vertex of the defect block, and constructing a matrix, wherein the size of the matrix is as follows: (maximum row mark-minimum row mark +1) ((maximum column mark-minimum column mark + 1)), initializing the value of the matrix to be 0, and updating the matrix according to the position of the defective pixel point of the current defective block;
the updating of the matrix according to the positions of the defective pixel points of the current defective block means that subscript values s and t of the pixel points of each defective block are obtained, wherein s is a row value, t is a column value, and the values of the row values in the matrix are set to be s-minimum row marks and the column values are set to be t-minimum column mark positions and are updated to be 1;
step nine, when the number of rows or columns of the matrix is less than the number of rows of the square matrix, marking the defect block represented by the matrix as a non-hole defect, otherwise, dividing the matrix according to the size of the square matrix, wherein dividing the matrix by taking the size of the square matrix as a unit respectively along the transverse direction and the longitudinal direction, the transverse direction is along the column direction, the longitudinal direction is along the row direction, complementing the part which is not sufficiently divided into the square matrix into a complete square matrix, the value of the complemented part is 0, performing convolution matching on the divided sub-matrix and the square matrix according to a formula (1), when the matching result is less than or equal to a threshold value, the defect block represented by the matrix is a hole defect, and calculating the area A1 of the defect block containing the hole defect according to the step six,
Figure BDA0003661014230000061
where V represents the sum of the exclusive OR of the square matrix and the submatrix, M T The square matrix is represented by a matrix table,
Figure BDA0003661014230000062
it represents the i-th sub-matrix,
step ten, executing steps eight and nine on all the defect blocks, calculating the area A1 of all the hole defects, calculating the quality inspection parameters F1 and F2 according to the formulas (2) and (3), when the quality inspection parameters F1 and F2 and the quality inspection qualified thresholds Thresh _ F1 and Thresh _ F2 meet the formula (4), indicating that the equipment to be inspected is qualified, otherwise indicating that the equipment to be inspected is unqualified,
Figure BDA0003661014230000063
Figure BDA0003661014230000064
f1 ≧ Thresh _ F1 and F2 ≧ Thresh _ F2 (4)
Where a0 represents the theoretical weld area.
The detection of the defect blocks is performed by using convex hull division, polygon division and convolution matching based division, the visualization results are shown in fig. 4, 5 and 6, and the results of the detection of 8 regions are shown in table 1.
TABLE 1 test results of different partitioning methods
Figure BDA0003661014230000065
The beneficial effects of the whole are as follows: the invention provides a hole defect accurate measurement method based on ultrasonic threshold imaging, which can accurately detect the defects of a part to be detected according to different standard holes and improve the detection accuracy.
Finally, it should be noted that: the above embodiments are only used to illustrate the technical solution of the present invention, and not to limit the same; while the invention has been described in detail and with reference to the foregoing embodiments, it will be understood by those skilled in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some or all of the technical features may be equivalently replaced; and these modifications or substitutions do not depart from the spirit of the corresponding technical solutions of the embodiments of the present invention.

Claims (3)

1. A hole defect accurate measurement method based on ultrasonic threshold imaging is characterized by comprising the following steps,
setting ultrasonic acquisition parameters of ultrasonic equipment, acquiring an ultrasonic signal of equipment to be detected by using the ultrasonic equipment, and drawing an image C according to the ultrasonic signal;
step two, carrying out binarization processing on the image C, setting the pixel value of the pixel point higher than the threshold value in the image C to be 255, setting the pixel values of the rest pixel points to be 0, and storing the pixel value of the image C in a matrix F mn Wherein m is the number of rows of pixel points in the image C, and n is the number of columns of pixel points in the image C;
step three, for the matrix F mn When F is mn When the number is 255, the pixel points are regarded as defective pixel points, and the matrix F is traversed in sequence mn If the adjacent pixel points are all defect pixel points, merging is carried out, and the merged defect pixel point set is regarded as a vertex and is expressed as Q ip,iq Wherein ip represents the ith row and the pth column, iq represents the ith row and the pth column, p is a starting column mark of a vertex, and q is an ending column mark of the vertex;
step four, the slave matrix F mn Go upward and go through if the two tops of the ith and jth linesIf the point satisfies that the ending column mark q +1 of the ith row is more than or equal to the starting column mark p of the jth row, and the starting column mark-1 of the ith row is less than or equal to the ending column mark of the jth row, connecting two vertexes and representing the two vertexes as edges, wherein j is i + 1;
constructing an adjacency matrix according to the vertexes and the edges, traversing the adjacency matrix based on a depth-first search algorithm, acquiring each searched vertex path set, and regarding each vertex path set as a defect block;
step six, acquiring the vertex of each defect block, calculating the area of each defect block according to the defect pixel point set corresponding to the vertex, and calculating the total area A2 of all defect blocks according to the area of each defect block;
defining the size of a defect block based on different requirements, designing a standard hole according to the size of the defect block, constructing a square matrix, initializing the value of the square matrix to be 0, calculating the number of rows and columns of the square matrix according to the standard hole, and updating the value of the square matrix;
step eight, acquiring a maximum row mark, a minimum row mark, a maximum column mark and a minimum column mark of the defect block according to the vertex of the defect block, and constructing a matrix, wherein the size of the matrix is as follows: (maximum row mark-minimum row mark +1) × (maximum column mark-minimum column mark +1), initializing the value of the matrix to 0, and updating the matrix according to the position of the defective pixel point of the current defective block;
the updating of the matrix according to the positions of the defective pixel points of the current defective block means that subscript values s and t of the pixel points of each defective block are obtained, wherein s is a row value, t is a column value, and the values of the row values in the matrix are set to be s-minimum row marks and the column values are set to be t-minimum column mark positions and are updated to be 1;
step nine, when the number of rows or columns of the matrix is less than the number of rows of the square matrix, marking the defect block represented by the matrix as a non-hole defect, otherwise, dividing the matrix according to the size of the square matrix, wherein dividing the matrix by taking the size of the square matrix as a unit respectively along the transverse direction and the longitudinal direction, the transverse direction is along the column direction, the longitudinal direction is along the row direction, complementing the part which is not sufficiently divided into the square matrix into a complete square matrix, the value of the complemented part is 0, performing convolution matching on the divided sub-matrix and the square matrix according to a formula (1), when the matching result is less than or equal to a threshold value, taking the defect block represented by the matrix as a hole defect, and calculating the area A1 of the defect block containing the hole defect according to the step six,
Figure FDA0003661014220000021
where V represents the sum of the exclusive OR of the square matrix and the submatrix, M T The square matrix is represented by a matrix table,
Figure FDA0003661014220000022
it represents the i-th sub-matrix,
step ten, executing steps eight and nine on all the defect blocks, calculating the area A1 of all the hole defects, calculating the quality inspection parameters F1 and F2 according to the formulas (2) and (3), when the quality inspection parameters F1 and F2 and the quality inspection qualified thresholds Thresh _ F1 and Thresh _ F2 meet the formula (4), indicating that the equipment to be inspected is qualified, otherwise indicating that the equipment to be inspected is unqualified,
Figure FDA0003661014220000023
Figure FDA0003661014220000024
f1 ≧ Thresh _ F1 and F2 ≧ Thresh _ F2 (4)
Where a0 represents the theoretical weld area.
2. The method for accurately measuring the hole defect based on the ultrasonic threshold imaging as claimed in claim 1, wherein the binarizing processing on the image C is performed on the image C based on a pixel histogram.
3. The method as claimed in claim 1, wherein the calculating the area of the defect block includes obtaining the actual area of the area to be inspected of the apparatus to be inspected, obtaining the number of pixels of the scanned image by the ultrasonic apparatus, calculating the ratio between the area of the area to be inspected and the number of pixels of the scanned image, obtaining the number of pixels in the pixel set, and taking the product of the number of pixels and the ratio as the area of the defect block.
CN202210577710.5A 2022-05-25 2022-05-25 Hole defect accurate measurement method based on ultrasonic threshold imaging Pending CN114994176A (en)

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Cited By (1)

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CN117252878A (en) * 2023-11-17 2023-12-19 青岛天仁微纳科技有限责任公司 Image defect detection method of nano-imprint mold

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN117252878A (en) * 2023-11-17 2023-12-19 青岛天仁微纳科技有限责任公司 Image defect detection method of nano-imprint mold
CN117252878B (en) * 2023-11-17 2024-02-02 青岛天仁微纳科技有限责任公司 Image defect detection method of nano-imprint mold

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