A precise measurement method for hole defects based on ultrasonic threshold imaging

Abstract

The invention discloses a precise hole defect measurement method based on ultrasonic threshold imaging, including setting ultrasonic acquisition parameters, detecting the equipment to be inspected according to ultrasonic equipment; collecting ultrasonic signals by using a data acquisition card and a transceiver; ultrasonic threshold imaging, drawing a scanned image by using gate information and a maximum peak algorithm; binarizing the scanned image; finding defect blocks in the image based on a depth-first search algorithm; calculating the total defect area according to the pixels of the defect block; designing a square matrix according to a standard hole, constructing a matrix according to the defect block, dividing the matrix horizontally and vertically, calculating the matching results of the square matrix and the submatrix based on convolution matching, judging whether it is a hole defect according to the matching results; judging the equipment to be inspected according to the evaluation criteria, if the threshold condition is not met, it is unqualified, otherwise it is qualified. The defects of the equipment to be inspected can be accurately detected according to different standard holes, and the accuracy of the detection is improved.

Description

Technical Field

[0001] The present invention relates to the field of nondestructive testing based on ultrasonic imaging, and in particular to a method for accurately measuring hole defects based on ultrasonic threshold imaging. Background Art

[0002] The nondestructive testing technology based on ultrasonic imaging is widely used, such as aircraft engine blades, aircraft composite materials, and brazing weld defects. The identification of defects and the measurement of defect area and shape are two very important technical directions in nondestructive testing. Defect detection can be automatically identified by manual recognition and artificial intelligence technology. However, the measurement of the area of ​​the defect block and whether the defect block can contain a circular hole is a difficult problem in defect measurement. The defect block in the image drawn based on the ultrasonic threshold is irregular in shape, such as Figure 2 As shown in the figure, how to accurately determine whether a defect block can contain a hole defect of a specified size to meet the defect identification standards of process engineers is a difficult problem that must be solved in defect measurement. Specific problems include:

[0003] (1) For the determination of defective blocks, current methods are mainly based on edge detection technology, convex polygon and irregular polygon calculation methods.

[0004] (2) Regarding the measurement of whether the hole defect can be contained, the method for determining the defect block determines the boundary of the defect block. Most of them are based on the center (center of gravity) of the defect area, and then draw a circle to see if it can collide with the boundary. If there is no collision, it can be contained, otherwise it cannot.

[0005] The existing methods will inevitably cause the defect block to expand and the defect area to increase in the calculation of defect area; hole defect measurement may cause misjudgment and missed judgment. For example, the measurement of the centroid of a convex polygon may cause misjudgment (because the shape itself is concave), while the concave shape may cause missed judgment, such as Figure 3 The shape can accommodate a 1cm hole defect. Therefore, the existing method will expand the defect area, resulting in multiple inspections and missed inspections of hole defects. Multiple inspections of defects will lead to a decrease in the qualified rate of products and waste of raw materials; missed inspections of defects will result in an inflated product qualified rate. The final delivered product may be damaged in the hands of the user, which may cause financial losses or serious accidents. For example, composite materials in aerospace may cause plane crashes and rocket explosions. Therefore, defects must be accurately measured to avoid excessive waste of raw materials, avoid missed inspections, reduce accidents, improve user experience, and ensure safety. Summary of the invention

[0006] The present invention provides a method for accurately measuring hole defects based on ultrasonic threshold imaging to overcome the above technical problems.

[0007] A method for accurately measuring hole defects based on ultrasonic threshold imaging, comprising:

[0008] Step 1: Set the ultrasonic acquisition parameters of the ultrasonic device, use the ultrasonic device to collect the ultrasonic signal of the device to be inspected, and draw an image C based on the ultrasonic signal;

[0009] Step 2: Binarize image C, set the pixel values ​​of pixels above the threshold in image C to 255, set the pixel values ​​of the remaining pixels to 0, and store the pixel values ​​of image C in matrix F mn In which, m is the number of rows containing pixels in image C, and n is the number of columns containing pixels in image C;

[0010] Step 3: For the matrix F mn , when F mn When it is 255, it is regarded as a defective pixel and the matrix F is traversed in turn. mn For each row of , if the adjacent pixels are defective pixels, they are merged, and the merged defective pixel set is regarded as a vertex, denoted as Q ip,iq , where ip represents the i-th row and p-th column, iq represents the i-th row and q-th column, p is the starting column label of the vertex, and q is the ending column label of the vertex;

[0011] Step 4: From the matrix F mn Traverse upward from the last row of . If the two vertices in the i-th row and the j-th row satisfy the condition that the end column index q+1 of the i-th row is greater than or equal to the start column index p of the j-th row, and the start column index -1 of the i-th row is less than or equal to the end column index of the j-th row, then connect the two vertices and represent them as an edge, where j = i+1.

[0012] Step 5: construct an adjacency matrix based on vertices and edges, traverse the adjacency matrix based on the depth-first search algorithm, obtain the searched vertex path sets, and regard each vertex path set as a defective block;

[0013] Step 6: For each defective block, obtain the vertices of the defective block, calculate the area of ​​the defective block according to the defective pixel point set corresponding to the vertex, and calculate the total area A2 of all defective blocks according to the area of ​​each defective block;

[0014] Step 7: Define the defect block size based on different requirements, design standard holes according to the defect block size, construct a square matrix, initialize the value of the square matrix to 0, calculate the number of rows and columns of the square matrix according to the standard holes, and update the value of the square matrix;

[0015] Step 8. Obtain the maximum row mark, minimum row mark, maximum column mark, and minimum column mark of the defective block according to the vertices of the defective block, and construct a matrix. The matrix size is: (maximum row mark - minimum row mark + 1) * (maximum column mark - minimum column mark + 1). The value of the matrix is ​​initialized to 0, and the matrix is ​​updated according to the location of the defective pixel point of the current defective block.

[0016] The updating of the matrix according to the position of the defective pixel of the current defective block refers to obtaining the subscript values ​​s and t of each defective block pixel, where s is the row value and t is the column value, and updating the value of the position where the row value in the matrix is ​​set to s-the minimum row index and the column value is set to t-the minimum column index to 1;

[0017] Step 9: When the number of rows or columns of the matrix is ​​less than the number of rows of the square matrix, the defect block represented by the matrix is ​​marked as a non-hole defect. Otherwise, the matrix is ​​divided according to the size of the square matrix. The matrix division refers to dividing the matrix horizontally and vertically with the size of the square matrix as a unit. The horizontal direction is the direction along the columns, and the vertical direction is the direction along the rows. The part that is not divided into a square matrix is ​​padded to form a complete square matrix. The value of the padded part is 0. The sub-matrix after division is convoluted and matched with the square matrix according to formula (1). When the matching result is less than or equal to the threshold, the defect block represented by the matrix is ​​a hole defect. The area A1 of the defect block containing the hole defect is calculated according to step 6.

[0018]

[0019] Among them, V represents the sum of the square matrix and the submatrix after XOR, M T represents a square matrix, represents the i-th sub-matrix,

[0020] Step 10: Execute steps 8 and 9 for all defective blocks, calculate the area A1 of all hole defects, and calculate the quality inspection parameters F1 and F2 according to formulas (2) and (3). When the quality inspection parameters F1 and F2 and the quality inspection qualified thresholds Thresh_F1 and Thresh_F2 satisfy formula (4), it means that the equipment to be inspected is qualified, otherwise it is unqualified.

[0021]

[0022]

[0023] F1 ≥ Thresh_F1 and F2 ≥ Thresh_F2 (4)

[0024] Where A0 represents the theoretical welding area.

[0025] Preferably, the binarization processing of the image C refers to binarization processing of the image C based on a pixel histogram.

[0026] Preferably, the calculation of the area of ​​the defect block includes obtaining the actual area of ​​the inspected area of ​​the device to be inspected, the number of pixels of the scanned image obtained by the ultrasonic device, calculating the ratio between the area of ​​the inspected area and the number of pixels in the 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.

[0027] The present invention provides a method for accurately measuring hole defects based on ultrasonic threshold imaging, which can accurately detect defects of a component to be inspected according to different standard holes, thereby improving the accuracy of detection. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0029] Figure 1 is a flow chart of the method of the present invention;

[0030] Figure 2 This is an example diagram of the present invention containing irregular defect blocks;

[0031] Figure 3 The present invention can accommodate hole defects of 1 cm holes;

[0032] Figure 4 This is a visualization result diagram of the convex hull partitioning of the present invention;

[0033] Figure 5 This is a visualization result diagram of polygon partitioning of the present invention;

[0034] Figure 6 This is a visualization result diagram of the convolution matching partitioning of the present invention. DETAILED DESCRIPTION

[0035] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are 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.

[0036] Figure 1 It is a flow chart of the method of the present invention, such as Figure 1 As shown, the method of this embodiment may include:

[0037] A method for accurately measuring hole defects based on ultrasonic threshold imaging, comprising:

[0038] Step 1, setting the ultrasonic acquisition parameters of the ultrasonic device, including the sampling length, frequency, gate length, threshold, and start time; using the ultrasonic device to collect the ultrasonic signal of the device to be inspected, using the data acquisition card and the transceiver to collect the ultrasonic signal, and drawing the image C according to the gate information of the ultrasonic signal and the maximum peak algorithm;

[0039] Step 2: Binarize image C based on the pixel histogram, set the pixel values ​​of pixels above the threshold in image C to 255, set the pixel values ​​of the remaining pixels to 0, and store the pixel values ​​of image C in the matrix F. mn In which, m is the number of rows containing pixels in image C, and n is the number of columns containing pixels in image C;

[0040] Step 3: For the matrix F mn , when F ij When it is 255, it is regarded as a defective pixel. Each row of the matrix F is traversed in turn. If the adjacent pixels are all defective pixels, they are merged. The merged defective pixel set is regarded as a vertex, which is represented by Q ip,iq , where ip represents the i-th row and p-th column, iq represents the i-th row and q-th column, p is the starting column label of the vertex, and q is the ending column label of the vertex;

[0041] Step 4: From the matrix F mn Traverse upward from the last row of . If the two vertices in the i-th row and the j-th row satisfy the condition that the end column index q+1 of the i-th row is greater than or equal to the start column index p of the j-th row, and the start column index -1 of the i-th row is less than or equal to the end column index of the j-th row, then connect the two vertices and represent them as an edge, where j = i+1.

[0042] Step 5: construct an adjacency matrix based on vertices and edges, traverse the adjacency matrix based on the depth-first search algorithm (DFS), obtain the searched vertex path sets, and regard each vertex path set as a defective block;

[0043] Step 6: For each defective block, obtain the vertices of the defective block, calculate the area of ​​the defective block according to the defective pixel point set corresponding to the vertex, and calculate the total area A2 of all defective blocks according to the area of ​​each defective block;

[0044] The calculating the area of ​​the defect block includes obtaining the actual area of ​​the inspected region of the inspected device, the number of pixels of the scanned image obtained by the ultrasonic device, calculating the ratio between the area of ​​the inspected region 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 pixels and the ratio as the area of ​​the defect block;

[0045] Step 7: Define the size of the defect block based on different requirements. For example, define the defect block as a hole defect containing a diameter of d (0.5 mm) according to the requirements. Design a standard hole according to the size of the defect block, construct a square matrix, initialize the value of the square matrix to 0, calculate the number of rows and columns of the square matrix according to the standard hole, and update the value of the square matrix.

[0046] The designing of the standard hole according to the size of the defect block refers to specifying a hole defect of a fixed size to be included in the defect block, and calculating the number of pixels of the standard hole based on the size and proportion of the hole defect;

[0047] Calculating the number of rows and columns of the square matrix according to the standard hole means calculating the number of rows and columns of the square matrix according to the number of pixels, and updating the value in the square matrix to 1;

[0048] Step 8. Obtain the maximum row mark, minimum row mark, maximum column mark, and minimum column mark of the defective block according to the vertices of the defective block, and construct a matrix. The matrix size is: (maximum row mark - minimum row mark + 1) * (maximum column mark - minimum column mark + 1). The value of the matrix is ​​initialized to 0, and the matrix is ​​updated according to the location of the defective pixel point of the current defective block.

[0049] The updating of the matrix according to the position of the defective pixel of the current defective block refers to obtaining the subscript values ​​s and t of each defective block pixel, where s is the row value and t is the column value, and updating the value of the position where the row value in the matrix is ​​set to s-the minimum row index and the column value is set to t-the minimum column index to 1;

[0050] Step 9: When the number of rows or columns of the matrix is ​​less than the number of rows of the square matrix, the defect block represented by the matrix is ​​marked as a non-hole defect. Otherwise, the matrix is ​​divided according to the size of the square matrix. The matrix division refers to dividing the matrix horizontally and vertically with the size of the square matrix as a unit. The horizontal direction is the direction along the column, and the vertical direction is the direction along the row. The part that is not divided into a square matrix is ​​padded to form a complete square matrix. The value of the padded part is 0. The divided sub-matrix is ​​convoluted with the square matrix according to formula (1). When the matching result is less than or equal to the threshold, the defect block represented by the matrix is ​​a hole defect. The area A1 of the defect block containing the hole defect is calculated according to step 6.

[0051]

[0052] Among them, V represents the sum of the square matrix and the submatrix after XOR, M T represents a square matrix, represents the i-th sub-matrix,

[0053] Step 10: Execute steps 8 and 9 for all defective blocks, calculate the area A1 of all hole defects, and calculate the quality inspection parameters F1 and F2 according to formulas (2) and (3). When the quality inspection parameters F1 and F2 and the quality inspection qualified thresholds Thresh_F1 and Thresh_F2 satisfy formula (4), it means that the equipment to be inspected is qualified, otherwise it is unqualified.

[0054]

[0055]

[0056] F1 ≥ Thresh_F1 and F2 ≥ Thresh_F2 (4)

[0057] Where A0 represents the theoretical welding area.

[0058] Defective block detection is performed using convex hull partitioning, polygon partitioning, and convolution matching-based partitioning. The visualization results are shown in the figure. Figure 4 , 5 , 6, the results of detecting the 8 regions are shown in Table 1.

[0059] Table 1 Detection results of different division methods

[0060]

[0061] Overall beneficial effects: The present invention provides a method for accurately measuring hole defects based on ultrasonic threshold imaging, which can accurately detect defects of components to be inspected according to different standard holes, thereby improving the accuracy of detection.

[0062] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or replace some or all of the technical features therein with equivalents. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for accurate hole defect measurement based on ultrasonic threshold imaging, characterized in that: include, Step 1: Set the ultrasonic acquisition parameters of the ultrasonic device, use the ultrasonic device to collect the ultrasonic signal of the device to be inspected, and draw an image C based on the ultrasonic signal; Step 2: Binarize image C, set the pixel values ​​of pixels above the threshold in image C to 255, set the pixel values ​​of the remaining pixels to 0, and store the pixel values ​​of image C in matrix F mn In which, m is the number of rows containing pixels in image C, and n is the number of columns containing pixels in image C; Step 3: For the matrix F mn , when F mn When it is 255, it is regarded as a defective pixel and the matrix F is traversed in turn. mn For each row of , if the adjacent pixels are defective pixels, they are merged, and the merged defective pixel set is regarded as a vertex, denoted as Q ip,iq , where ip represents the i-th row and p-th column, iq represents the i-th row and q-th column, p is the starting column label of the vertex, and q is the ending column label of the vertex; Step 4: From the matrix F mn Traverse upward from the last row of . If the two vertices in the i-th row and the j-th row satisfy the condition that the end column index q+1 of the i-th row is greater than or equal to the start column index p of the j-th row, and the start column index -1 of the i-th row is less than or equal to the end column index of the j-th row, then connect the two vertices and represent them as an edge, where j = i+1. Step 5: construct an adjacency matrix based on vertices and edges, traverse the adjacency matrix based on the depth-first search algorithm, obtain the searched vertex path sets, and regard each vertex path set as a defective block; Step 6: For each defective block, obtain the vertices of the defective block, calculate the area of ​​the defective block according to the defective pixel point set corresponding to the vertex, and calculate the total area A2 of all defective blocks according to the area of ​​each defective block; Step 7: Define the defect block size based on different requirements, design standard holes according to the defect block size, construct a square matrix, initialize the value of the square matrix to 0, calculate the number of rows and columns of the square matrix according to the standard holes, and update the value of the square matrix; Step 8. Obtain the maximum row mark, minimum row mark, maximum column mark, and minimum column mark of the defective block according to the vertices of the defective block, and construct a matrix. The matrix size is: (maximum row mark - minimum row mark + 1) * (maximum column mark - minimum column mark + 1). The value of the matrix is ​​initialized to 0, and the matrix is ​​updated according to the location of the defective pixel point of the current defective block. The updating of the matrix according to the position of the defective pixel of the current defective block refers to obtaining the subscript values ​​s and t of each defective block pixel, where s is the row value and t is the column value, and updating the value of the position where the row value in the matrix is ​​set to s-the minimum row index and the column value is set to t-the minimum column index to 1; Step 9: When the number of rows or columns of the matrix is ​​less than the number of rows of the square matrix, the defect block represented by the matrix is ​​marked as a non-hole defect. Otherwise, the matrix is ​​divided according to the size of the square matrix. The matrix division refers to dividing the matrix horizontally and vertically with the size of the square matrix as a unit. The horizontal direction is the direction along the columns, and the vertical direction is the direction along the rows. The part that is not divided into a square matrix is ​​padded to form a complete square matrix. The value of the padded part is 0. The sub-matrix after division is convoluted and matched with the square matrix according to formula (1). When the matching result is less than or equal to the threshold, the defect block represented by the matrix is ​​a hole defect. The area A1 of the defect block containing the hole defect is calculated according to step 6. Among them, V represents the sum of the square matrix and the submatrix after XOR, M T represents a square matrix, represents the i-th sub-matrix, Step 10: Execute steps 8 and 9 for all defective blocks, calculate the area A1 of all hole defects, and calculate the quality inspection parameters F1 and F2 according to formulas (2) and (3). When the quality inspection parameters F1 and F2 and the quality inspection qualified thresholds Thresh_F1 and Thresh_F2 satisfy formula (4), it means that the equipment to be inspected is qualified, otherwise it is unqualified. F1 ≥ Thresh_F1 and F2 ≥ Thresh_F2 (4) Where A0 represents the theoretical welding area.

2. The method for accurate hole defect measurement based on ultrasonic threshold imaging according to claim 1, characterized in that: The binarization processing of the image C refers to binarization processing of the image C based on a pixel histogram.

3. The method for accurate hole defect measurement based on ultrasonic threshold imaging according to claim 1, characterized in that: The calculation of the area of ​​the defect block includes obtaining the actual area of ​​the inspected area of ​​the inspected device, the number of pixels of the scanned image obtained by the ultrasonic device, calculating the ratio between the area of ​​the inspected area and the number of pixels in the 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.

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