Defect detection device and defect detection method

Abstract

To provide a defect detection device and a defect detection method for detecting a defect of a spherical component without using an image of a normal component.SOLUTION: An X-ray camera 20 captures an image of X-rays emitted from an X-ray irradiator 10 and passing through spherical components 40a and 40b. An image input unit 31 accepts input of an X-ray image from the X-ray camera 20. A gravity center detection unit 32 detects the center of gravity of the spherical components from the X-ray image. A spherical surface approximation unit 33 obtains the center and radius of a sphere by spherically approximating the spherical components. A defect detection unit 34 detects a radius (volume) defect of the spherical components based on whether or not the radius of the approximate sphere is out of the range of a predetermined value, obtains the sum of the absolute values of the differences between the radius of the approximate sphere subjected to the spherical approximation and a distance from the circle center to the luminance value, and detects a defect including a shape defect and a cavity defect based on whether or not the sum of the absolute values of the differences is equal to or greater than a predetermined threshold value.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The present invention relates to a defect detection device and a defect detection method. [Background technology]

[0002] In welding, there are welded parts that are formed into a roughly spherical shape by welding. Defects in these welded parts include defects such as cavities inside due to the inclusion of impurities, defects due to an excess or deficiency of the specified welding amount (volume), and defects where the weld shape is not as specified. Therefore, after welding, it is necessary to check whether the welded parts are properly welded, i.e., to detect defects.

[0003] For example, Patent Document 1 discloses a technique for detecting solder defects in IC terminals, which detects anomalies by focusing on the fact that the amount of X-ray transmission is greater in X-ray images of insufficient solder than in images of normal solder. Patent Document 2 also discloses a technique for obtaining an X-ray image through simulation based on information on the shape and material of the object to be inspected, and then detecting defects by comparing this simulated image with an X-ray image obtained by inspection. Patent Document 3 also discloses a technique for detecting defects by comparing with a defect-free transmitted image. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] Japanese Patent Application Publication No. 04-330761 [Patent Document 2] Japanese Patent Application Laid-Open No. 2014-016239 [Patent Document 3] Japanese Patent Application Laid-Open No. 2006-105794 Summary of the Invention [Problem to be solved by the invention]

[0005] In all of the above-mentioned Patent Documents 1 to 3, defects in welded parts are detected by comparing a normal X-ray image with an inspection image, which requires that a normal X-ray image be prepared in advance, making the work complicated.

[0006] Therefore, an object of the present invention is to provide a defect detection device and a defect detection method that can detect defects in spherical parts without using images of normal parts. [Means for solving the problem]

[0007] In order to solve the above problems, the present invention employs the following means. That is, the defect detection device according to the first invention is characterized by comprising an imaging unit that captures X-rays that have passed through a spherical part as an X-ray image, a spherical approximation unit that spherically approximates the spherical part from the X-ray image, and a defect detection unit that determines a defect when the radius of the spherically approximated sphere exceeds a predetermined range, calculates the sum of the absolute values ​​of the differences between the radius of the spherically approximated sphere and the distance from the center of the circle to the brightness value, and determines a defect when the sum of the absolute values ​​of the differences is equal to or greater than a first threshold value.

[0008] In addition, a defect detection device according to a second aspect of the present invention is characterized by comprising an imaging unit that captures X-rays that have passed through a spherical part as an X-ray image, a horizontal line brightness extraction unit that extracts the brightness of one horizontal line from the X-ray image, an arc approximation unit that approximates the spherical part to an arc from the brightness of the one horizontal line, and a defect detection unit that determines a defect if the radius of the approximated arc exceeds a predetermined range, calculates the sum of the absolute values ​​of the differences between the radius of the approximated arc and the distance from the center of the circle to the brightness value, and determines a defect if the sum of the absolute values ​​of the differences is equal to or greater than a first threshold value.

[0009] Furthermore, a defect detection device according to a third invention is the defect detection device according to the first invention, characterized in that the defect detection unit further calculates the positive sum of the differences between the radius of the approximation sphere and the distance from the center of the circle to the brightness value, and if the positive sum of the differences is equal to or greater than a second threshold value, determines that the spherical part is defective due to the formation of an internal cavity.

[0010] Furthermore, a defect detection device according to a fourth invention is the defect detection device according to the second invention, characterized in that the defect detection unit further calculates the positive sum of the differences between the radius of the approximate arc and the distance from the center of the circle to the brightness value, and if the positive sum of the differences is equal to or greater than a second threshold value, determines that the spherical part is defective due to the formation of an internal cavity.

[0011] In addition, a defect detection method according to a fifth invention is a defect detection method for detecting defects in a spherical part, characterized in that it includes capturing an X-ray image of X-rays that have passed through the spherical part, spherically approximating the spherical part from the X-ray image, determining a defect if the radius of the spherically approximated sphere exceeds a predetermined range, calculating the sum of the absolute values ​​of the differences between the radius of the spherically approximated sphere and the distance from the center of the circle to the brightness value, and determining a defect if the sum of the absolute values ​​of the differences is equal to or greater than a first threshold value.

[0012] In addition, a defect detection method according to a sixth aspect of the present invention is a defect detection method for detecting defects in spherical parts, comprising the steps of capturing an X-ray image of X-rays that have passed through the spherical part, extracting the brightness of one horizontal line from the X-ray image, approximating the spherical part to an arc from the brightness of the one horizontal line, determining a defect if the radius of the approximated arc exceeds a predetermined range, calculating the sum of the absolute values ​​of the differences between the radius of the approximated arc and the distance from the center of the circle to the brightness value, and determining a defect if the sum of the absolute values ​​of the differences is equal to or greater than a first threshold value.

[0013] Furthermore, a defect detection method according to a seventh invention is characterized in that, in the defect detection method according to the fifth invention, detecting the defect further includes calculating the positive sum of the differences between the radius of the approximation sphere and the distance from the center of the circle to the brightness value, and if the positive sum of the differences is equal to or greater than a second threshold value, determining that the spherical part is defective due to the formation of an internal cavity.

[0014] Furthermore, a defect detection method according to an eighth aspect of the present invention is characterized in that, in the defect detection method according to the sixth aspect of the present invention, detecting the defect further includes calculating the positive sum of the differences between the radius of the approximate arc and the distance from the center of the circle to the brightness value, and if the positive sum of the differences is equal to or greater than a second threshold value, determining that the spherical part is defective due to the formation of an internal cavity. [Effects of the Invention]

[0015] According to the present invention, defects in spherical parts can be detected without using images of normal parts. [Brief explanation of the drawings]

[0016] [Figure 1] 1 is a block diagram showing a configuration of a defect detection device according to a first embodiment of the present invention. [Figure 2] 5 is a flowchart for explaining the operation of the defect detection device according to the first embodiment. [Figure 3] 3 is a schematic diagram showing an example of an X-ray image captured by the defect detection device of the first embodiment. FIG. [Figure 4] 3 is a schematic diagram for explaining spherical approximation by the defect detection device of the first embodiment. FIG. [Figure 5] 3 is a schematic diagram for explaining a three-dimensional sphere obtained by spherical approximation by the defect detection device of the first embodiment. FIG. [Figure 6] FIG. 2 is a schematic diagram showing a two-dimensional (cross-section) representation of a three-dimensional sphere obtained by spherical approximation using the defect detection device of the first embodiment. [Figure 7] FIG. 10 is a block diagram showing the configuration of a defect detection device according to a second embodiment of the present invention. [Figure 8] 10A and 10B are schematic diagrams for explaining arc approximation by the defect detection device of the second embodiment. [Figure 9] 10 is a flowchart for explaining the operation of the defect detection device according to the second embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0017] Hereinafter, an embodiment of the present invention will be described with reference to the accompanying drawings. A. First embodiment 1 is a block diagram showing the configuration of a defect detection device according to a first embodiment of the present invention. The defect detection device 1 includes an X-ray irradiation device 10, an X-ray camera (imaging unit) 20, and an image processing device 30. Spherical components 40a and 40b to be inspected are arranged between the X-ray irradiation device 10 and the X-ray camera 20. In the illustrated example, two spherical components 40a and 40b are arranged, but the number of spherical components is not limited.

[0018] An X-ray irradiator 10 irradiates X-rays toward spherical components 40a and 40b. An X-ray camera 20 captures an image of X-rays irradiated from the X-ray irradiator 10 and passing through the spherical components 40a and 40b, and inputs the captured X-ray image to an image input unit 31 of an image processing device 30. The image input unit 31 inputs the X-ray image from the X-ray camera 20 and supplies it to a center of gravity detection unit 32. The center of gravity detection unit 32 applies a general image processing center of gravity detection method to the X-ray image to detect the centers of gravity of the spherical components 40a and 40b, and cuts out an image (hereinafter referred to as a rectangular image) with a rectangle ("cut rectangle") corresponding to a radius r from the center of gravity of the spherical components. The radius r is the radius of a known good product.

[0019] The spherical approximation unit 33 takes the 3D point cloud (x, y, z) of the cropped rectangular image plotted against coordinates x, y and brightness z as input and performs spherical approximation using a standard least-squares method or the like to determine the center and radius rs of the approximating sphere. Since the spherical radius of a non-defective part is known, spherical approximation with a fixed radius may be used to improve approximation accuracy. Furthermore, while the image positions x, y are coordinate values, brightness z has a different value range, such as an 8-bit value or a 16-bit value. Therefore, x, y, and z are normalized before spherical approximation. This aligns the coordinates of the brightness distribution obtained from the X-ray image with the coordinates of the approximated sphere. The defect detection unit 34 detects defects in spherical parts based on the brightness distribution of the spherical part obtained from the X-ray image and the coordinate values ​​on the approximated sphere. Defects include radius (volume) defects where the radius rs of the approximation sphere exceeds a predetermined range (radius r of a non-defective part ± tolerance), shape defects where a protrusion appears from a spherical part, cavity defects where a cavity is formed inside a spherical part, etc. The defect detection unit 34 first detects volume defects of spherical parts, and then detects shape defects (including cavity defects).

[0020] FIG. 2 is a flowchart illustrating the operation of the defect detection device according to the first embodiment. In the image processing device 30, the image input unit 31 inputs an X-ray image from the X-ray camera 20 (step S10) and supplies it to the center of gravity detection unit 32. For example, as shown in FIG. 3, the X-ray image 21 is an image having brightness values ​​according to the X-ray penetration. The brightness is high (bright / white) in parts that do not block X-rays relatively well (thin parts), and low (dark / black) in parts that block X-rays relatively well (thick parts). FIG. 3 shows an example image in which there is no defect in the spherical part 40b, but there is a defect (high brightness part; gray circle) approximately near the center of the spherical part 40a.

[0021] Next, the center of gravity detection unit 32 applies a general image processing method such as center of gravity detection to the X-ray image to detect the center of gravity of the spherical part, and cuts out a rectangular image 22 from the center of gravity of the spherical part by a cutout rectangle corresponding to radius r, as shown in Fig. 4 (step S12). The spherical approximation unit 33 receives as input a 3D point cloud (x, y, z) plotted with coordinates x, y and brightness z of the cut-out rectangular image 22, and performs spherical approximation using a general least squares method or the like to determine the center of the sphere and its radius (step S14). Fig. 5 shows the 3D point cloud (x, y, z) plotted with coordinates x, y and brightness z of the obtained image.

[0022] The defect detection unit 34 detects radius (volume) defects of the spherical part based on whether the radius rs of the approximating sphere is outside a predetermined range, and also detects shape defects (including void defects) of the spherical part other than radius (volume) defects based on the brightness distribution of the spherical part obtained from the X-ray image and the coordinate values ​​on the approximated sphere (3D point cloud (x, y, z)) (step S16). The defect detection unit 34 first detects that the radius (volume) of the spherical part is too large if the radius rs of the approximating sphere is equal to or greater than a predetermined value (upper limit), and that the radius (volume) of the spherical part is too small if the radius rs of the approximating sphere is equal to or less than a predetermined value (lower limit). Next, the defect detection unit 34 detects shape defects (including void defects) other than volume defects as follows. For ease of understanding, the following description will be given using a 2D cross-sectional graph shown in FIG. 6 instead of a 3D point cloud. In FIG. 6, the horizontal axis represents the horizontal coordinate and the vertical axis represents the brightness value. The dotted line is a semicircle corresponding to the approximation sphere, and the solid line is the brightness of the spherical part. As shown in Equation 1, the radius r of the approximation sphere θ ^ and the distance r from the center of the circle to the brightness value θ Difference with R θ The sum SAD of the absolute values ​​of the above is calculated. If the sum SAD is equal to or greater than a predetermined threshold TH1 (first threshold) (SAD≧TH1), it is determined to be a shape defect (including a cavity defect).

[0023]

number

[0024] Next, the image processing device 30 determines whether there is a next centroid (step S18). If the centroid detection unit 32 detects multiple centroids (YES in step S18), the spherical approximation in step S14 and the defect detection in step S16 are repeated until the multiple centroids are replaced one by one in order. Then, when the processing for all centroids is completed (NO in step S18), the processing ends.

[0025] As described above, according to the first embodiment, by focusing on the fact that the inspection part is spherical, the spherical part in the captured X-ray image is approximated as a sphere, and defects are detected based on whether the radius rs of the approximated sphere is outside a predetermined range. Therefore, it is possible to detect radius (volume) defects of a spherical part without acquiring an image of a normal part in advance. Furthermore, according to the first embodiment, the radius r of the approximated sphere is θ ^ and the distance r from the center of the circle to the brightness value θ Difference with R θ Since defects are detected based on whether the sum of the absolute values ​​of SAD is equal to or greater than a predetermined threshold value TH1, it is possible to detect shape defects (including cavity defects) in spherical parts. Furthermore, according to the first embodiment, while the back surface of a part cannot be seen with a visible light camera, transmitted X-rays are used, and therefore the condition of the back surface of a spherical part is also integrated using brightness values, making it possible to detect defects on the back surface that cannot be seen with visible light.

[0026] B. Second embodiment The second embodiment is characterized in that defects are detected using "arc approximation" instead of the "spherical approximation" used in the first embodiment.

[0027] FIG. 7 is a block diagram showing the configuration of a defect detection device according to a second embodiment of the present invention. Note that the same components as those in FIG. 1 are designated by the same reference numerals, and their description will be omitted. As shown in FIG. 7, the defect detection device 100 of the second embodiment includes a horizontal line luminance extraction unit 35 and an arc approximation unit 36 ​​instead of the spherical approximation unit 33. The horizontal line luminance extraction unit 35 acquires the luminance of horizontal lines by shifting the rectangular image 23 shown in FIG. 8, acquired by the preceding centroid detection unit 32, downward by one horizontal line (one pixel) at a time from y=0, as indicated by the dotted line. The arc approximation unit 36 ​​receives as input a 2D point cloud (x, z) plotted by coordinate x and luminance z of the rectangular image, based on the luminance of the horizontal lines acquired by the horizontal line luminance extraction unit 35, and performs arc approximation using a general least squares method or the like to determine the center and radius of the arc.

[0028] 9 is a flowchart for explaining the operation of the defect detection device according to the second embodiment. In the image processing device 50, the image input unit 31 inputs an X-ray image from the X-ray camera 20 (step S20), and the center of gravity detection unit 32 applies a center of gravity detection method or the like to the X-ray image to detect the center of gravity of the spherical part, and cuts out a rectangular image 23 as shown in FIG. 8 (step S22). Next, the image processing device 50 resets a variable y for scanning horizontal lines to 0 (step S24).

[0029] The horizontal line luminance extraction unit 35 extracts the luminance of one horizontal line at coordinate y for the rectangular image 23 shown in Fig. 8 acquired by the preceding center of gravity detection unit 32, and increments y (step S26). Next, the arc approximation unit 36 ​​performs arc approximation using the 2D point cloud (x, z) plotted by the coordinate x and luminance z of the rectangular image based on the luminance of one horizontal line acquired by the horizontal line luminance extraction unit 35 (step S28). The defect detection unit 34 detects radius (volume) defects of the spherical part based on whether the radius ra of the approximated arc is outside a predetermined range, and detects shape defects (including cavity defects) based on the coordinate values ​​on the arc approximated to the luminance distribution of the spherical part obtained from the X-ray image and the 2D point cloud (x, z) (step S30). The defect detection unit 34 first detects that the radius (volume) of the spherical part is too large if the radius ra of the approximated arc is equal to or larger than a predetermined value (upper limit), or that the radius (volume) of the spherical part is too small if the radius ra of the approximated arc is equal to or smaller than a predetermined value (lower limit). Next, the defect detection unit 34 calculates the radius r of the approximated arc according to Equation 1, as in the first embodiment described above. θ ^ and the distance r from the center of the arc to the brightness value θ Difference with R θ The sum SAD of the absolute values ​​of the above is calculated, and if the sum SAD is out of a predetermined threshold TH1 (first threshold) (SAD≧TH1), it is determined to be a shape defect (including a cavity defect).

[0030] Next, image processing device 50 determines whether variable y for scanning horizontal lines has reached the end of the rectangular area (step S32), and if it has not reached the end of the rectangular area (NO in step S32), returns to step S26, shifts downward by one horizontal line (one pixel), and then repeats arc approximation in step S28 and defect detection in step S30 for the next horizontal line. Thereafter, steps S26 to S32 are repeated while incrementing variable y until the end of the rectangular area is reached, and defects are detected.

[0031] When the variable y for scanning the horizontal line reaches the end of the rectangular region (YES in step S32), the image processing device 50 determines whether there is a next centroid (step S34). When the centroid detection unit 32 detects multiple centroids (YES in step S34), the multiple centroids are swapped in order, and the process returns to step S24, where the extraction of brightness for one horizontal line in step S26, the arc approximation in step S28, and the defect detection in step S30 are repeated. When the process for all centroids has been completed (NO in step S34), the process ends.

[0032] According to the second embodiment, in addition to the effects of the first embodiment described above, defects are detected by approximating spherical parts in the captured X-ray image with an arc, so that even if the tip shape of a spherical part is not spherical (FIG. 4) but elliptical (FIG. 8), it is possible to detect the radius (volume) and shape defects (including cavity defects).

[0033] C. Third embodiment The third embodiment is characterized in that in "fault detection (volume fault, shape fault, cavity fault)" using spherical approximation, cavities formed inside a spherical part are identified as cavity faults. The fault detection device 1 according to this third embodiment has the same configuration as the first embodiment shown in FIG. 1, and operates according to the flowchart shown in FIG. 2. However, in this third embodiment, there is a difference in the processing of "fault detection (step S16)" in the fault detection unit 34. In addition to the above-mentioned formula 1, the fault detection unit 34 calculates the radius r of the approximation sphere according to the following formula 2. θ ^ and the distance r from the center of the circle to the brightness value θ The positive sum SPD of the difference between these is calculated, and if the sum SPD is equal to or greater than a predetermined threshold value TH2 (second threshold value) (SPD≧TH2), it is determined that the spherical part has a cavity defect.

[0034]

number

[0035] According to the third embodiment, in addition to the detection of defects according to the first embodiment, it is possible to identifiably detect cavity defects in which cavities are formed inside a component, which can only be seen in an X-ray image.

[0036] D. Fourth embodiment The fourth embodiment is characterized in that in "fault detection (volume fault, shape fault, cavity fault)" using arc approximation, cavities formed inside a spherical part are identified as cavity faults. The fault detection device 100 according to the fourth embodiment has the same configuration as the second embodiment shown in FIG. 7, and operates according to the flowchart shown in FIG. 9. However, in the fourth embodiment, there is a difference in the process of "fault detection (step S30)" in the fault detection unit 34. In addition to the above-mentioned formula 1, the fault detection unit 34 calculates the radius r of the approximate arc according to the above-mentioned formula 2. θ ^ and the distance r from the center of the circle to the brightness value θ The positive sum SPD of the difference between these is calculated, and if the sum SPD is equal to or greater than a predetermined threshold value TH2 (second threshold value) (SPD≧TH2), it is determined that the spherical part has a cavity defect.

[0037] According to the fourth embodiment, in addition to the detection of defects according to the second embodiment, it is possible to identifiably detect cavity defects in which cavities are formed inside a component, which can only be seen in an X-ray image.

[0038] In addition to this, the present invention is not limited to the above-described embodiments and modified examples described with reference to the drawings, and it is possible to select and discard the configurations listed in the above-described embodiments and modified examples, or to change them to other configurations as appropriate, as long as this does not deviate from the gist of the present invention. [Explanation of symbols]

[0039] 1,100 Defect detection device 10 X-ray irradiation device 20 X-ray camera (imaging unit) 21 X-ray image 22, 23 Rectangular images 30, 50 Image processing device 31 Image input unit 32 Center of gravity detection unit 33 Spherical approximation part 34 Defect detection unit 35 Horizontal line luminance extraction section 36 Arc approximation 40a, 40b Spherical parts

Claims

1. an imaging unit that captures an X-ray image using X-rays that have passed through the spherical component; a spherical approximation unit that performs spherical approximation of the spherical part from the X-ray image; a defect detection unit that determines a defect when the radius of the spherically approximated approximation sphere exceeds a predetermined range, calculates the sum of the absolute values ​​of the differences between the radius of the spherically approximated approximation sphere and the distance from the circle center to the luminance value, and determines a defect when the sum of the absolute values ​​of the differences is equal to or greater than a first threshold.

2. an imaging unit that captures an X-ray image using X-rays that have passed through the spherical component; a horizontal line luminance extraction unit that extracts luminance for one horizontal line from the X-ray image; an arc approximation unit that performs arc approximation of the spherical component from the luminance of the one horizontal line; a defect detection unit that determines a defect when the radius of the approximated arc obtained by circular approximation exceeds a predetermined range, calculates the sum of the absolute values ​​of the differences between the radius of the approximated arc obtained by circular approximation and the distance from the center of the circle to the luminance value, and determines a defect when the sum of the absolute values ​​of the differences is equal to or greater than a first threshold value.

3. The defect detection unit further calculates a positive sum of differences between the radius of the approximation sphere and the distance from the center of the circle to a luminance value, and when the positive sum of differences is equal to or greater than a second threshold, determines that the spherical part is defective due to the formation of an internal cavity.

2. The defect detection device according to claim 1.

4. The defect detection unit further calculates a positive sum of differences between the radius of the approximate arc and the distance from the center of the circle to a luminance value, and when the positive sum of differences is equal to or greater than a second threshold, determines that the spherical part is defective due to the formation of an internal cavity.

3. The defect detection device according to claim 2.

5. A defect detection method for detecting defects in a spherical part, comprising: capturing an X-ray image using X-rays that have passed through the spherical component; approximating the spherical part from the X-ray image as a spherical surface; a defect detection method comprising determining a defect when the radius of the spherically approximated approximation sphere exceeds a predetermined range, calculating the sum of absolute values ​​of the differences between the radius of the spherically approximated approximation sphere and the distance from the circle center to the luminance value, and determining a defect when the sum of absolute values ​​of the differences is equal to or greater than a first threshold value.

6. A defect detection method for detecting defects in a spherical part, comprising: capturing an X-ray image using X-rays that have passed through the spherical component; Extracting the brightness of one horizontal line from the X-ray image; approximating the spherical component to an arc from the luminance of the horizontal line; a defect detection method comprising determining a defect when the radius of the approximated arc obtained by circular approximation exceeds a predetermined range, calculating the sum of the absolute values ​​of the differences between the radius of the approximated arc obtained by circular approximation and the distance from the center of the circle to the brightness value, and determining a defect when the sum of the absolute values ​​of the differences is equal to or greater than a first threshold value.

7. 6. The defect detection method according to claim 5, further comprising: calculating a positive sum of differences between the radius of the approximation sphere and the distance from the center of the circle to the brightness value; and determining that the spherical part is defective due to an internal cavity formed in the spherical part if the positive sum of differences is equal to or greater than a second threshold value.

8. 7. The defect detection method according to claim 6, further comprising: calculating a positive sum of differences between the radius of the approximate arc and the distance from the center of the circle to a brightness value; and determining that the spherical part is defective because an internal cavity has been formed in the spherical part if the positive sum of differences is equal to or greater than a second threshold value.

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