Quality inspection method and quality inspection device

Abstract

A controller (13) performs computer tomography of a cylinder block (21) in an orthogonal coordinate system that has an x axis, a y axis, and a z axis and acquires a plurality of CT images of the xy plane along the z-axis direction. The controller (13) superimposes the plurality of CT images to generate one stacked image and averages the grayscale values px of the pixels in the stacked image in the y-axis direction to acquire an average grayscale value μ. The controller (13) determines whether there is a defect in the cylinder block (21) in accordance with the average grayscale value μ.

Description

Quality inspection method and quality inspection device

[0001] The present invention relates to a quality inspection method and a quality inspection device.

[0002] As disclosed in Patent Document 1, it is known to use CT images taken with X-rays to determine whether defects such as cavities (shrinkage cavities, blowholes) have occurred in a component to be inspected.

[0003] Japanese Unexamined Patent Publication No. 7-12759

[0004] In an engine cylinder block, thermal stress during test runs can cause multiple cavities scattered throughout the block to merge, potentially leading to coolant leaks. While CT images can be used to assess the number, size, and distribution of cavities, assessing the risk of cavities merging requires experience and skill, making it difficult to perform a consistent assessment. The objective of this invention is to provide a consistent assessment of the risk of cavities merging during quality inspections.

[0005] According to one aspect of the present invention, a controller performs computed tomography of an inspection target part in an orthogonal coordinate system of x-, y-, and z-axes, and acquires multiple CT images of the xy plane along the z-axis direction. The controller then overlays the multiple CT images to generate a layered image, averages the grayscale values ​​of each pixel in the layered image in at least one of the x-axis and y-axis directions to acquire an average grayscale value, and determines whether the inspection target part has a defect based on the average grayscale value.

[0006] According to the present invention, the risk of cavities being combined can be evaluated in a uniform manner.

[0007] FIG. 1 is a block diagram showing a quality inspection device; FIG. 2 is a flowchart showing a control process; FIG. 3 is a diagram showing a cylinder block; FIG. 4 is a diagram showing a plurality of CT images; FIG. 5 is a diagram showing a stacked image; FIG. 6 is an enlarged view of a cavity in the stacked image; FIG. 7 is a diagram showing a graph of μ=f(x); FIG. 8 is a diagram showing a flowchart of the control process; FIG. 9 is a diagram showing an integral value;

[0008] Hereinafter, embodiments of the present invention will be described with reference to the drawings. Note that the drawings are schematic and may differ from the actual product. Furthermore, the following embodiments exemplify devices and methods for embodying the technical concept of the present invention, and are not intended to limit the configuration to those described below. In other words, the technical concept of the present invention can be modified in various ways within the technical scope described in the claims.

[0009] First Embodiment Configuration FIG. 1 is a block diagram showing a quality inspection device. The quality inspection device 11 inspects a target part, such as a cylinder block of an engine, which is a cast product, for defects such as cavities (shrinkage cavities, blowholes). Specifically, the quality inspection device 11 diagnoses whether or not thermal stress during a test run could cause multiple scattered cavities to connect and lead to cooling water leakage. The target part is not limited to a cast product, and may be any part that is susceptible to defects such as cavities. The quality inspection device 11 includes a CT device 12 and a controller 13. The CT device 12 performs computed tomography (CT) on the target object and outputs a CT image. That is, X-rays are irradiated onto the target object, and the X-rays that pass through the target object are received by a detector. The image is analyzed and reconstructed to output a two-dimensional CT image.

[0010] The controller 13 is, for example, a microcomputer, and includes a CT image acquisition unit 14, a layered image generation unit 15, an average gray value acquisition unit 16, and a defect determination unit 17, and executes the control processing described below. The CT image acquisition unit 14 performs computed tomography of the inspection target part in an orthogonal coordinate system of the x-axis, y-axis, and z-axis, and acquires multiple CT images of the xy plane along the z-axis direction. The inspection target part is, for example, an engine cylinder block. The layered image generation unit 15 overlays multiple CT images to generate a single layered image. The average gray value acquisition unit 16 averages the gray values ​​px of each pixel in the layered image in the y-axis direction to acquire an average gray value μ. The defect determination unit 17 determines whether the inspection target part has a defect based on the average gray value μ.

[0011] Next, the control processing executed by the controller 13 will be described. FIG. 2 is a flowchart showing the control processing. In step S101, a plurality of CT images are acquired by the CT device 12. FIG. 3 is a diagram showing the cylinder block 21. Here, the cylinder block 21 of a V6 engine will be described as an example. (a) in the figure shows the external appearance of the cylinder block 21. A plurality of cylinders 22 are formed in the cylinder block 21, and the z-axis is set in the direction of arrangement of the cylinders 22, which is parallel to the rotational axis of the engine.

[0012] (b) in the figure shows a cross section on one side of the cylinder block 21, passing through the center of one cylinder 22 and perpendicular to the z-axis. The y-axis is set along the axial direction of the cylinder 22, and the x-axis is set along the radial direction of the cylinder 22. A water jacket 23 is formed on the cylinder block 21 radially outside the cylinder 22. The water jacket 23 is formed along the inner circumferential surface of the cylinder 22 and serves as a passage for cooling water. An open-deck type water jacket, whose mating surface with the cylinder head is open, is shown here as an example. A recess 24, which is a recessed portion of the outer circumferential surface and has a reduced thickness, is formed on the outer circumferential surface of the cylinder block 21, closer to the crankshaft than the water jacket 23 in the y-axis direction. The area of ​​the water jacket 23 from the opposite side of the cylinder head to the recess 24 may lead to cooling water leakage, and is therefore designated as a region of interest 25.

[0013] Therefore, in a Cartesian coordinate system of the x-, y-, and z-axes, multiple CT images of the xy plane in the region of interest 25 are acquired along the z-axis direction. FIG. 4 shows multiple CT images. The CT images are expressed in 256 8-bit gradations for each of the RGB colors, with cavities displayed in black and solids displayed in gray. Note that the gradation is not limited to 8-bit gradations, and 10-, 12-, or 16-bit gradations may also be used. Multiple cavities are scattered below the water jacket 23 in the cylinder block 21. Return to FIG. 2 . In the following step S102, each CT image is converted to a 256-level grayscale and the gray value px is binarized to either 0 or 255. The threshold value is set to 127, with gray values ​​px of 127 or less being set to 0 and gray values ​​px of 128 or more being set to 256.

[0014] In the next step S103, multiple CT images are superimposed, and the grayscale values ​​px of each pixel are averaged in the z-axis direction to generate a single stacked image. FIG. 5 shows the stacked image. By convolving the images, the binarized grayscale values ​​px are averaged in the z-axis direction to generate a grayscale stacked image. FIG. 6 shows an enlarged view of cavities in the stacked image. In this way, it is possible to represent not only the distribution of cavities in the xy plane, but also the distribution of cavities in the z-axis direction.

[0015] Returning to FIG. 2 , in the following step S104, the grayscale values ​​px of each pixel in the stacked image are averaged along the y-axis to obtain an average grayscale value μ. That is, the average of all grayscale values ​​px aligned along the y-axis for each x-coordinate is calculated. If the average grayscale value μ is the minimum of 0, it is black, indicating a hollow area. If the average grayscale value μ is the maximum of 255, it is white, indicating a solid area. Here, the average is calculated along the y-axis as an example, but this is not limiting. The score for the entire image may be expressed as a single value by averaging along both the x-axis and y-axis. In the following step S105, it is determined whether there is an x-coordinate where the average grayscale value μ is equal to or less than a predetermined threshold value th. The threshold value th varies depending on the vehicle model and the location of the region of interest 25, and here is set to 100 as an example. If there is no x-coordinate where the average grayscale value μ is equal to or less than the threshold value th, the process proceeds to step S106. On the other hand, if there is an x-coordinate where the average grayscale value μ is equal to or less than the threshold value th, the process proceeds to step S107.

[0016] In step S106, it is determined that there is no possibility that multiple cavities may be connected and cause cooling water leakage, and the process returns to the predetermined main program. In step S107, it is determined that there is a possibility that multiple cavities may be connected and cause cooling water leakage, and the process returns to the predetermined main program. FIG. 7 is a graph of μ = f(x). Here, the graph of μ = f(x) is shown in a Cartesian coordinate system with an x ​​axis and a μ axis. The thick solid line indicates the cylinder block 21 where there is no x coordinate where the average gradation value μ is equal to or less than the threshold value th, and the thick dotted line indicates the cylinder block 21 where there is an x ​​coordinate where the average gradation value μ is equal to or less than the threshold value th. M indicates the maximum value of the gradation (=255). The above is the control process executed by the controller 13 of the first embodiment. Among these, the processing of step S101 corresponds to the CT image acquisition unit 14, the processing of step S103 corresponds to the stacked image generation unit 15, the processing of step S104 corresponds to the average gray value acquisition unit 16, and the processing of steps S105 to S107 corresponds to the defect judgment unit 17.

[0017] <<Functions and Effects>> Next, the main functions and effects of the first embodiment will be described. (1) In the quality inspection method, the controller 13 performs computed tomography (CT) of the cylinder block 21 in a Cartesian coordinate system of the x-, y-, and z-axes, and acquires multiple CT images of the xy plane along the z-axis direction (S101). The controller 13 then overlays the multiple CT images to generate a single stacked image (S103), and averages the grayscale values ​​px of each pixel in the stacked image along the y-axis direction to acquire an average grayscale value μ (S104). The controller 13 determines whether or not there is a defect in the cylinder block 21 based on the average grayscale value μ (S105 to S107). In this way, by using the average grayscale value μ obtained by averaging the grayscale values ​​px of each pixel in the stacked image along the y-axis direction, the risk of voids merging can be uniformly evaluated.

[0018] (2) The controller 13 determines that the cylinder block 21 has a defect when the average gray value μ is equal to or less than a predetermined threshold value th. This allows for a simple determination of whether the cylinder block 21 has a defect. (3) The gray value px is a 256-level grayscale, and the controller 13 binarizes the gray value px to either 0 or 255. This prevents an increase in the computational load. (4) The controller 13 overlays multiple CT images and averages the gray values ​​px of each pixel in the z-axis direction to generate a single layered image. This allows for a grasp of not only the distribution of cavities in the xy plane, but also the distribution of cavities in the z-axis direction.

[0019] (5) The y-axis is set along the axial direction of the cylinders 22 in the cylinder block 21. The z-axis is set along the arrangement direction of the cylinders 22. This makes it easy to set up a Cartesian coordinate system. (6) The cylinder block 21 is formed with a water jacket 23 through which cooling water flows and a recessed portion 24 formed on the outer circumferential surface. The controller 13 generates a stacked image of the region in the xy plane from the end of the water jacket 23 opposite the cylinder head to the recessed portion 24. This allows areas prone to cooling water leakage to be targeted for inspection. (7) The controller 13 determines whether multiple cavities in the cylinder block 21 may be connected to each other, leading to cooling water leakage. This makes it possible to identify cylinder blocks 21 in which multiple scattered cavities may be connected to each other due to thermal stress during test operation, leading to cooling water leakage.

[0020] (8) The quality inspection device 11 includes a controller 13. The controller 13 performs computed tomography (CT) of the cylinder block 21 in a Cartesian coordinate system of the x-, y-, and z-axes, and acquires multiple CT images of the xy plane along the z-axis direction (S101). The controller 13 then overlays the multiple CT images to generate a single stacked image (S103), and averages the grayscale values ​​px of each pixel in the stacked image along the y-axis direction to acquire an average grayscale value μ (S104). The controller 13 determines whether or not the cylinder block 21 has a defect based on the average grayscale value μ (S105 to S107). In this way, the risk of void formation can be uniformly evaluated by using the average grayscale value μ obtained by averaging the grayscale values ​​px of each pixel in the stacked image along the y-axis direction.

[0021] Here, a comparative example will be described. Until now, X-ray CT images have been used to determine whether defects such as cavities (shrinkage cavities, casting cavities) have occurred in parts to be inspected. However, in the cylinder block 21 of an engine, thermal stress during test runs can cause multiple cavities scattered throughout the block to join together, potentially leading to cooling water leakage. While the number, size, and distribution of cavities can be evaluated from CT images, assessing the risk of cavities joining together requires experience and proficiency, making it difficult to perform a uniform evaluation.

[0022] Second Embodiment Configuration The second embodiment adds a condition for determining that a defect exists, but other configurations are the same as those of the first embodiment described above, so detailed descriptions of common parts will be omitted. Figure 8 is a flowchart of the control process. Here, a new process of step S201 is added between step S105 and step S107.

[0023] In step S201, it is determined whether there are two or more consecutive x-coordinates in the x-axis direction where the average gray value μ is equal to or less than the threshold value th. If there are not two or more consecutive x-coordinates in the x-axis direction where the average gray value μ is equal to or less than the threshold value th, the process proceeds to step S106. On the other hand, if there are two or more consecutive x-coordinates in the x-axis direction where the average gray value μ is equal to or less than the threshold value th, the process proceeds to step S107. Here, as an example, it is determined whether there are two or more consecutive x-coordinates in the x-axis direction where the average gray value μ is equal to or less than the threshold value th, but this is not limiting. In other words, three or more thresholds may be used to determine continuity. The above is the control process executed by the controller 13 of the second embodiment. Among these, steps S105 to S107 and S201 correspond to the defect determination unit 17.

[0024] <<Functions and Effects>> Next, the main functions and effects of the second embodiment will be described. (1) The controller 13 determines that there is a defect in the cylinder block 21 when the average gray value μ equal to or less than the threshold value th is continuous in the x-axis direction (S105 to S107, S201). This eliminates the influence of noise and makes it possible to determine with higher accuracy whether or not there is a defect. Other functions and effects brought about by the common configuration are the same as those of the first embodiment described above.

[0025] Third Embodiment Configuration The third embodiment adds a condition for determining that a defect exists, but the configuration is otherwise the same as that of the first embodiment, so detailed description of the common parts will be omitted. Figure 9 is a flowchart of the control process. Here, a new process of step S301 is added between step S105 and step S107.

[0026] In step S301, it is determined whether the x-coordinate where the average gradation value μ is equal to or less than the threshold value th is in contact with the circumferential surface of the cylinder block 21. The circumferential surface of the cylinder block 21 refers to the inner circumferential surface of the water jacket 23 or the outer circumferential surface of the recess 24. If the x-coordinate where the average gradation value μ is equal to or less than the threshold value th is not in contact with the circumferential surface of the cylinder block 21, the process proceeds to step S106. On the other hand, if the x-coordinate where the average gradation value μ is equal to or less than the threshold value th is in contact with the circumferential surface of the cylinder block 21, the process proceeds to step S107. The above is the control process executed by the controller 13 of the third embodiment. Among these, the processes of steps S105 to S107 and S301 correspond to the defect determination unit 17.

[0027] <<Functions and Effects>> Next, the main functions and effects of the third embodiment will be described. (1) The controller 13 determines that the inspected part has a defect when the portion of the cylinder block 21 where the average gray value μ is equal to or less than the threshold value th starts from the circumferential surface of the cylinder block 21 (S105 to S107, S301). This makes it possible to determine with higher accuracy whether or not there is a defect. Other functions and effects brought about by the common configuration are the same as those of the first embodiment described above.

[0028] Fourth Embodiment Configuration The fourth embodiment changes the conditions for determining that a defect exists, but other configurations are the same as those of the first embodiment described above, so detailed descriptions of common parts will be omitted. Figure 10 is a flowchart of the control process. Here, new processes of steps S401 and S402 have been added in place of step S105.

[0029] In step S401, the average gray value μ is integrated in a plane coordinate system with the x-axis and the average gray value μ to obtain the integrated value ∫. FIG. 11 is a diagram showing the integrated value ∫. Here, in a Cartesian coordinate system with the x-axis and μ-axis, the area of ​​the region surrounded by the graph of μ = f(x) and the line μ = M is obtained as the integrated value ∫. In the following step S402, it is determined whether the integrated value ∫ is equal to or greater than a predetermined threshold. The threshold varies depending on the vehicle model and the location of the region of interest 25. If the integrated value ∫ is less than the threshold, the process proceeds to step S106. On the other hand, if the integrated value ∫ is equal to or greater than the threshold, the process proceeds to step S107. The above is the control process executed by the controller 13 of the fourth embodiment. Among these, the processes of steps S401, S402, S106, and S107 correspond to the defect determination unit 17.

[0030] <<Functions and Effects>> Next, the main functions and effects of the fourth embodiment will be described. (1) The controller 13 integrates the average gradation value μ in a plane coordinate system defined by the x-axis and the average gradation value μ to obtain an integral value ∫, and determines whether or not the cylinder block 21 has a defect based on the integral value ∫. This makes it easy to determine whether or not the cylinder block 21 has a defect. (2) The average gradation value is μ, and the maximum value of gradation is M. In a rectangular coordinate system defined by the x-axis and μ-axis, the controller 13 obtains the area of ​​the region surrounded by the graph of μ = f(x) and the line μ = M as the integral value ∫. If the integral value ∫ is equal to or greater than a predetermined threshold, the controller 13 determines that the cylinder block 21 has a defect. This makes it easy to determine whether or not the cylinder block 21 has a defect. Other functions and effects provided by the common configuration are the same as those of the first embodiment described above.

[0031] <<Modification>> In the fourth embodiment, the area of ​​the region surrounded by the graph of μ = f(x) and the line μ = M is obtained as the integral value ∫, and it is determined whether the integral value ∫ is equal to or greater than a predetermined threshold. However, the present invention is not limited to this. That is, it is also possible to obtain the area of ​​the region surrounded by the graph of μ = f(x) and the x-axis (the line μ = 0) as the integral value ∫, and determine whether the integral value ∫ is equal to or less than a predetermined threshold. In short, it is sufficient to obtain the integral value ∫ from the graph of μ = f(x) in a plane coordinate system with the x-axis and the average gradation value μ, and determine whether the cylinder block 21 has a defect based on the integral value ∫.

[0032] Although the present invention has been described above with reference to a limited number of embodiments, the scope of the invention is not limited thereto, and modifications of the embodiments based on the above disclosure will be obvious to those skilled in the art.

[0033] REFERENCE SIGNS LIST 11...quality inspection device, 12...CT device, 13...controller, 14...CT image acquisition unit, 15...laminated image generation unit, 16...average gray value acquisition unit, 17...defect determination unit, 21...cylinder block, 22...cylinder, 23...water jacket, 24...thinning portion, 25...area of ​​interest

Claims

1. In a Cartesian coordinate system of an x-axis, a y-axis, and a z-axis, perform computed tomography on a component to be inspected, and acquire a plurality of CT images in the xy plane along the z-axis direction; a process of generating one stacked image by overlapping the plurality of CT images; a process of obtaining an average gray value by averaging the gray values of each pixel in the stacked image in at least one of the x-axis direction or the y-axis direction; and a process of determining whether there is a defect in the component to be inspected according to the average gray value, and causing a controller to execute the processes. A quality inspection method characterized by this.

2. The quality inspection method according to claim 1, wherein the controller determines that there is a defect in the component to be inspected when the average gray value is less than or equal to a predetermined threshold value.

3. The quality inspection method according to claim 2, wherein the controller determines that there is a defect in the component to be inspected when the average gray value less than or equal to the threshold value is continuous in the x-axis direction.

4. The quality inspection method according to claim 2, wherein the controller determines that there is a defect in the component to be inspected when a portion of the component to be inspected where the average gray value is less than or equal to the threshold value starts from the circumferential surface of the component to be inspected.

5. In a plane coordinate system of the x-axis and the average gray value, cause the controller to execute a process of integrating the average gray value to obtain an integrated value, and the controller determines whether there is a defect in the component to be inspected according to the integrated value. A quality inspection method according to claim 1.

6. Let the average gray value be μ and the maximum value of the gradation be M. The controller obtains the area of the region surrounded by the graph of μ = f(x) and the straight line of μ = M as the integrated value in the orthogonal coordinate system of the x-axis and the μ-axis, and determines that there is a defect in the component to be inspected when the integrated value is greater than or equal to a predetermined threshold value. A quality inspection method according to claim 5.

7. The gray value is a 256-gradation gray scale, and the quality inspection method according to claim 1, wherein the controller binarizes the gray value to 0 or 255.

8. The quality inspection method according to claim 1, wherein the controller overlaps the plurality of CT images and averages the gray values of each pixel in the z-axis direction to generate one stacked image.

9. The component to be inspected is the cylinder block of an engine, the y-axis is set along the axial direction of the cylinders in the cylinder block, and the z-axis is set along the arrangement direction of the cylinders. The quality inspection method according to claim 1, characterized in that.

10. In the cylinder block, a water jacket through which cooling water flows and a core print with a recessed outer peripheral surface are formed. The controller generates the stacked image in a region from an end of the water jacket opposite to the cylinder head to the core print in the xy plane. The quality inspection method according to claim 9, characterized in that.

11. The controller determines whether a plurality of cavities in the cylinder block are connected and may cause leakage of the cooling water. The quality inspection method according to claim 10, characterized in that.

12. A quality inspection apparatus comprising a controller that performs a process of performing computed tomography on a component to be inspected in an orthogonal coordinate system of the x-axis, y-axis, and z-axis, and acquiring a plurality of CT images in the xy plane along the z-axis direction; a process of generating one stacked image by overlapping the plurality of CT images; a process of obtaining an average density value by averaging the density values of each pixel in the stacked image in at least one of the x-axis direction or the y-axis direction; and a process of determining whether there is a defect in the component to be inspected according to the average density value.

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