JP2024099202A - Inspection Systems - Google Patents

Abstract

[Problem] The adhesion of foreign matter to a bead in a welded portion is judged as an abnormality. [Solution] An inspection system is provided for inspecting a workpiece including a columnar portion having a welded portion. The inspection system includes an image acquisition unit that acquires an image of the appearance of the bead in the welded portion as an inspection image, a first inspection unit that judges the presence or absence of a void on the bead in the inspection image, a second inspection unit that judges the presence or absence of a foreign matter on the bead in the inspection image by detecting edges included in the inspection image, and a judgment unit that judges that there is an abnormality in the workpiece when at least one of a void and a foreign matter is included in the inspection image. [Selected Figure] Figure 1

Description

This disclosure relates to an inspection system.

Technology for detecting abnormalities in weld beads is known (for example, see Patent Document 1). Patent Document 1 discloses detecting incomplete fusion in a weld bead based on the variation in brightness values in an image of the weld bead.

JP 2017-148841 A

Foreign matter can adhere to beads. Until now, there has been no specific consideration of determining whether the adhesion of foreign matter to beads is an abnormality.

This disclosure can be realized in the following forms:

(1) According to one aspect of the present disclosure, there is provided an inspection system for inspecting a workpiece including a columnar portion having a welded portion, the inspection system including: an image acquisition unit that acquires an image of an appearance of a bead in the welded portion as an inspection image; a first inspection unit that determines the presence or absence of a void on the bead in the inspection image; a second inspection unit that determines the presence or absence of a foreign matter on the bead in the inspection image by detecting an edge included in the inspection image; and a determination unit that determines that the workpiece is abnormal when at least one of the void and the foreign matter is included in the inspection image.
In this embodiment, the first inspection unit can determine the presence or absence of voids in the inspection image, and the second inspection unit can determine the presence or absence of foreign matter based on edges contained in the inspection image. Then, if the learning image contains either voids or foreign matter, it is determined that there is an abnormality in the workpiece. Therefore, in addition to voids, adhesion of foreign matter to the bead can be determined as an abnormality.
(2) In the above embodiment, the first inspection unit may determine the presence or absence of the void using a machine learning model that has been trained using a plurality of learning images of the appearance of the bead, the machine learning model being for determining whether or not the void is included in an image input to the machine learning model. In this embodiment, the first inspection unit can determine the presence or absence of the void using the machine learning model.
(3) In the above embodiment, a first camera that captures a part of the appearance of the bead and a second camera that captures the part of the bead at an angle different from the angle at which the first camera captures the part are provided, and the machine learning model may have been trained using an image of the appearance of the bead captured by the first camera and an image of the appearance of the bead captured by the second camera as the training images. In this embodiment, for example, a shortage of training images can be suppressed compared to a case where only images captured by the first camera or only images captured by the second camera are used for machine learning.
(4) In the above embodiment, the image acquisition unit may acquire, as the inspection images, a first image in which the appearance of the bead of the welded portion to be inspected is captured by the first camera, and a second image in which the appearance of the bead of the welded portion to be inspected is captured by the second camera, and the determination unit may determine that the workpiece has an abnormality when at least one of the first image and the second image contains at least one of the void and the foreign matter. According to this embodiment, the workpiece can be inspected more precisely than, for example, when determining the presence or absence of a void or a foreign matter based on only one of the image captured by the first camera and the image captured by the second camera.
(5) In the above embodiment, the second inspection unit may determine the presence or absence of the foreign matter in the inspection image based on at least one of the angle of an edge, the coordinates of an edge, the spacing between edges, and the strength of an edge in the inspection image.

In addition to the above-mentioned inspection system, the present disclosure can be realized in various forms, such as a workpiece inspection method.

FIG. 1 is an explanatory diagram showing a schematic configuration of an inspection system. FIG. 2 is an explanatory diagram showing how a workpiece is manufactured. FIG. 1 is a first explanatory diagram showing an example of a captured image. FIG. 2 is a second explanatory diagram showing an example of a captured image. FIG. 11 is a third explanatory diagram showing an example of a captured image. 13 is a flowchart of an inspection process.

A. First embodiment:
1 is an explanatory diagram showing a schematic configuration of an inspection system 100. The inspection system 100 inspects a workpiece W including a columnar portion CP having a welded portion WP. The inspection system 100 of this embodiment includes a photographing unit 110, a storage device 130, a control device 140, an inspection device 150, and an alarm unit 160. In this specification, the meaning of "columnar" includes not only a solid columnar shape but also a hollow columnar shape.

In this embodiment, the workpiece W is made of a resin material and is configured as a liner of a tank for storing hydrogen. The liner is a hollow container for storing hydrogen gas or the like inside, and has a body P1 having a substantially cylindrical shape and a pair of dome portions P2 connected to both ends of the body P1. In this embodiment, the columnar portion CP is configured by the entire body P1 and a part of the dome portion P2. Each dome portion P2 has a substantially hemispherical shape that is convex toward the outside of the workpiece W in the axial direction along the axis AX, which is the central axis of the columnar portion CP. An opening is formed at the apex of each dome portion P2, and a nozzle M is fitted into the opening. The hollow portion in the workpiece W is connected to the outside via the nozzle M. In this embodiment, the central axis of the body P1 and the central axis of each dome portion P2 are substantially aligned with the axis AX. Therefore, the central axis of the workpiece W is aligned with the axis AX.

In this embodiment, the workpiece W is connected to a rotating device (not shown) and rotates around the axis AX by driving the rotating device. The rotating device has, for example, a motor that generates a rotational driving force that is applied to the workpiece W, and is driven under the control of the control device 140.

2 is an explanatory diagram showing how the workpiece W is manufactured in this embodiment. As shown in FIG. 2, the workpiece W is manufactured by joining the body P1 and each dome P2 to each other by infrared welding. More specifically, first, a cylindrical member P1a and two dome members P2a are prepared. The cylindrical member P1a is a member that will later constitute the body P1. The dome members P2a are members that will later constitute each dome P2. Next, as shown in the upper part of FIG. 2, both ends of the body P1 and the ends of each dome member P2a on the cylindrical member P1a side are heated by infrared lamps L. Next, as shown in the middle part of FIG. 2, the cylindrical member P1a and each dome member P2a are brought into contact with each other so that each end of the cylindrical member P1a and the ends of each dome member P2a on the cylindrical member P1a side are in close contact with each other. Then, as shown in the lower part of Figure 2, each dome member P2a is pressed against the cylindrical member P1a from the outside, thereby joining the cylindrical member P1a and each dome member P2a by welding.

The above welding forms a columnar portion CP having a welded portion WP. More specifically, a welded portion WP is formed between the body portion P1 and each dome portion P2, connecting the body portion P1 and each dome portion P2 and extending along the circumferential direction of the workpiece W. Each welded portion WP has a bead Bd. The bead Bd is a welding mark that extends along the circumferential direction. The bead Bd is raised higher than the surrounding areas, and has an inner portion Bp1 that protrudes toward the inside of the workpiece W, and an outer portion Bp2 that protrudes toward the outside.

The photographing unit 110 has a photographing section 111 and a camera controller 116. The photographing section 111 photographs the welded portion WP to photograph the external appearance of the bead Bd of the welded portion WP. More specifically, in this embodiment, the photographing section 111 photographs the external appearance of the inner portion Bp1 of the bead Bd. In other embodiments, the photographing section 111 may photograph the outer portion Bp2 in addition to or instead of the inner portion Bp1.

The photographing unit 111 has a first camera 112, a second camera 113, and a shaft portion 114. The shaft portion 114 has an axis shape and is inserted into the workpiece W via a nozzle M. The first camera 112 and the second camera 113 are each fixed to the shaft portion 114, and are inserted into the workpiece W together with the shaft portion 114. The first camera 112 and the second camera 113 may be configured as an endoscopic camera such as a fiberscope or a borescope, for example.

The first camera 112 and the second camera 113 capture a portion of the exterior of the bead Bd. The second camera 113 captures the portion of the bead Bd captured by the first camera 112 at an angle different from the angle at which the first camera 112 captures that portion.

1 shows the first camera 112 and the second camera 113 photographing the first portion Pt1 of the bead Bd. The first portion Pt1 is a part of the bead Bd in the circumferential direction. As shown in FIG. 1, in this embodiment, the first camera 112 and the second camera 113 are arranged in a position in the axial direction to sandwich the bead Bd, which is the subject of the photograph, between them when photographing the bead Bd. More specifically, the first camera 112 and the second camera 113 are arranged to be approximately symmetrical in the axial direction with the bead Bd, which is the subject of the photograph, sandwiched between them. The first camera 112 is arranged to face the first direction d1, and photographs the inner portion Bp1 of the bead Bd from one side in the axial direction. The second camera 113 is arranged to face the second direction d2, and photographs the inner portion Bp1 of the bead Bd from the other side in the axial direction together with the first camera 112. The first direction d1 and the second direction d2 are opposite to each other in the axial direction, and are substantially the same on a plane perpendicular to the axial direction. More specifically, the first direction d1 is a direction from the first camera 112 to the second camera 113, and from the center of the columnar part CP to the outer periphery. The second direction d2 is a direction from the second camera 113 to the first camera 112, and from the center of the columnar part CP to the outer periphery. Hereinafter, an image of the appearance of the bead Bd is also referred to as a captured image Pi. Also, the captured image Pi captured by the first camera 112 is also referred to as a first captured image, and the captured image Pi captured by the second camera 113 is also referred to as a second captured image.

In this embodiment, an illumination device 115 that illuminates the bead Bd, which is the subject of the image, is fixed to the shaft portion 114. The illumination device 115 in this embodiment is disposed between the first camera 112 and the second camera 113 in the axial direction, and illuminates the bead Bd by irradiating light onto the bead Bd in a direction perpendicular to the axial direction.

Note that FIG. 1 shows the image capturing unit 111 capturing an image of one of the two beads Bd. Although not shown, in this embodiment, the image capturing unit 111 is configured to be able to capture an image of the other bead Bd as well. More specifically, in this embodiment, the insertion positions of the first camera 112 and the second camera 113 are configured to be changeable under the control of the control device 140, and when the subject to be captured is changed, the insertion positions of the first camera 112 and the second camera 113 are changed to correspond to the position of the bead Bd to be captured.

The camera controller 116 is configured, for example, as a circuit or computer for controlling each camera provided in the photographing unit 111, and is connected to each camera. The camera controller 116, for example, transmits a photographing trigger signal to each camera and receives photographed images Pi photographed by each camera. The photographed images Pi received by the camera controller 116 are transmitted to the storage device 130 and stored in the storage device 130. In this embodiment, the storage device 130 is a NAS (Network Attached Storage) connected to the inspection device 150 via a network.

3 to 5 are explanatory diagrams showing examples of captured images Pi. Image Pi1 shown in FIG. 3 is an example of a captured image Pi including a bead Bd that does not include voids Vd and foreign matter Fs on its surface. Image Pi2 shown in FIG. 4 is an example of a captured image Pi including voids Vd and no foreign matter Fs. Image Pi3 shown in FIG. 5 is an example of a captured image Pi including foreign matter Fs and no voids Vd. In FIG. 3 to FIG. 5, the bead Bd is hatched. More specifically, the part of the bead Bd where whiteout HL occurs is hatched with an upward slope to the right. The part of the bead Bd where voids Vd occur is hatched vertically. The part of the bead Bd where whiteout HL and voids Vd do not occur is hatched with a dot pattern. In this embodiment, as shown in Figures 3 to 5, the captured image Pi is captured so that the bead Bd crosses the center of the captured image Pi in the vertical direction.

As shown in Figures 4 and 5, voids Vd may form on the bead Bd, or foreign matter Fs may adhere to the bead Bd. The voids Vd shown in Figure 4 are hole-shaped defects on the surface of the bead Bd, and are formed, for example, when moisture contained in the cylindrical member P1a or the dome member P2a evaporates during welding. The foreign matter Fs shown in Figure 5 is a linear foreign matter, such as a fiber or a hair. In this embodiment, such foreign matter Fs adheres to the surface of the bead Bd due to, for example, static electricity. Note that blown-out highlights HL occur when the brightness in the captured image Pi increases due to, for example, the reflection of light irradiated from the lighting device 115 onto the bead Bd.

The control device 140 is configured as a computer including a CPU 141, a storage unit 142, and an input/output interface. The CPU 141 executes a program stored in the storage unit 142 to cause the control device 140 to realize various functions including the function of the inspection control unit 143. The inspection control unit 143 executes the inspection process described below. Note that in other embodiments, the control device 140 may be configured, for example, by a PLC (Programmable Logic Controller). The functions of the control device 140 may also be realized by a circuit.

The inspection device 150 is configured as a computer including a CPU 151, a memory unit 152, and an input/output interface. In this embodiment, the memory unit 152 stores a machine learning model 200 (described later) and an edge detection program 205.

The inspection device 150 has a first inspection unit 155, a second inspection unit 156, an image acquisition unit 157, and a judgment unit 158. In this embodiment, the first inspection unit 155, the second inspection unit 156, the image acquisition unit 157, and the judgment unit 158 are each functional units that are realized by the CPU 151 executing a program stored in the memory unit 152.

The image acquisition unit 157 acquires the captured image Pi as an inspection image Di. In this embodiment, the image acquisition unit 157 acquires the first captured image and the second captured image stored in the storage device 130 as the inspection image Di. More specifically, the image acquisition unit 157 acquires the first image and the second image. The first image refers to the first captured image captured by the first camera 112 of the appearance of the bead Bd of the welded part WP, which is the inspection target. The second image refers to the second captured image captured by the second camera 113 of the appearance of the bead Bd of the welded part WP, which is also the inspection target.

The first inspection unit 155 judges the presence or absence of a void Vd on the bead Bd based on the inspection image Di acquired by the image acquisition unit 157. In this embodiment, the first inspection unit 155 judges the presence or absence of a void Vd using the machine learning model 200 and the inspection image Di. The machine learning model 200 is a learning model for judging whether or not a void Vd is included in an input image to the machine learning model 200, which has been trained using a plurality of learning images in which the appearance of the bead Bd is captured. In this embodiment, the learning images include a first captured image and a second captured image captured in the past. In addition, the machine learning model 200 in this embodiment is a convolutional neural network that has been trained regarding whether or not a void Vd is included in the bead Bd by supervised learning using training data. This training data is composed of a data set in which each learning image is associated with a label indicating the presence or absence of a void Vd.

The shooting angle of the bead Bd in the inspection image Di may be different from the shooting angle of the bead Bd in the learning image. For example, the shooting angle of the bead Bd in the first image may be different from the shooting angle of the bead Bd in the first and second captured images used as learning images. Similarly, the shooting angle of the bead Bd in the second image may be different from the shooting angle of the bead Bd in the first and second captured images used as learning images.

The second inspection unit 156 executes the edge detection program 205 to detect edges contained in the inspection image Di, thereby determining the presence or absence of a foreign matter Fs on the bead Bd. The edge detection program 205 is a program for detecting edges contained in the inspection image Di using an edge detection algorithm.

In this embodiment, the second inspection unit 156 judges the presence or absence of a foreign substance Fs based on the angle of the edge, the coordinates of the edge, the interval between the edges, and the strength of the edges in the inspection image Di. More specifically, the second inspection unit 156 judges the presence or absence of a foreign substance Fs in the inspection image Di by detecting an edge different from the edge representing the bead Bd and different from the edge representing the blown-out HL based on the above. Note that the strength of the edge refers to the magnitude of the change in the luminance of the pixel. For example, in this embodiment, as shown in FIG. 3 to FIG. 5, the edges representing the bead Bd and the blown-out HL are along the horizontal axis in the captured image Pi as a whole, are detected in the center of the captured image Pi in the vertical direction, are relatively wide apart, and have relatively small strength. Therefore, in this embodiment, the second inspection unit 156 detects an edge that satisfies the following judgment condition as an edge different from the edge representing the bead Bd and the blown-out HL. The judgment conditions are that the magnitude of the inclination of the edge relative to the horizontal axis in the test image Di is greater than a predetermined inclination threshold, the vertical coordinate of the edge is outside the predetermined central coordinate, the distance between adjacent edges is narrower than a predetermined distance threshold, and the strength of the edge is stronger than a predetermined strength threshold.

The judgment unit 158 judges that there is an abnormality in the workpiece W when the inspection image Di contains at least one of a void Vd and a foreign matter Fs. In other words, the judgment unit 158 judges that there is an abnormality in the workpiece W both when the first inspection unit 155 judges that there is a void Vd and when the second inspection unit 156 judges that there is a foreign matter Fs.

The notification unit 160, under the control of the control device 140, notifies the user of various information, for example, related to the inspection system 100 and the workpiece W. In this embodiment, the notification unit 160 is configured as a display device that displays visual information under the control of the control device 140. The notification unit 160 may, for example, have a speaker for outputting audio information in addition to or instead of such a display device.

Figure 6 is a flowchart of the inspection process. In this embodiment, the inspection process is executed, for example, when the first camera 112 and the second camera 113 are placed in the workpiece W and a predetermined start operation is performed by the user on the control device 140. In this embodiment, steps S10 and S70 shown in Figure 6 are executed by the control device 140, and steps S20 to S60 are executed by the inspection device 150.

In step S10, the inspection control unit 143 uses the photographing unit 110 to photograph the appearance of the bead Bd of the welded portion WP to be inspected. In this embodiment, in step S10, the control device 140 alternately rotates the workpiece W around the axis AX by a predetermined unit angle, stops the rotation of the workpiece W, and photographs one bead Bd with the first camera 112 and the second camera 113 until the workpiece W rotates once around the axis AX. Thereafter, the inspection control unit 143 similarly photographs the other bead Bd. In this way, a plurality of first images and a plurality of second images of one bead Bd and a plurality of first images and a plurality of second images of the other bead Bd are obtained. The unit angle is preferably set to an angle small enough to photograph all parts of the bead Bd in the circumferential direction while the workpiece W is rotated once around the axis AX in step S10. Each captured image Pi is sent to the storage device 130.

In step S20, the image acquisition unit 157 acquires one of the captured images Pi captured in step S10 from the storage device 130 as the test image Di.

In step S30, the first inspection unit 155 determines whether or not there is a void Vd on the bead Bd in the inspection image Di acquired in step S20.

If it is determined in step S30 that the test image di contains a void Vd, the first inspection unit 155 records void information of the test image Di used in step S30 in step S32. The void information is information regarding the presence or absence of a void Vd in the test image Di. In step S32, the first inspection unit 155 records information indicating that the test image Di contains a void Vd in the storage device 130 as the void information of the test image Di used in step S30. Note that the void information may be recorded in, for example, the storage unit 142 or the storage unit 152. If it is determined in step S30 that the test image Di does not contain a void Vd, the first inspection unit 155 records information indicating that the test image Di does not contain a void Vd in step S34, in the same manner as in step S32.

In step S40, the second inspection unit 156 determines whether or not there is a foreign object Fs on the bead Bd in the inspection image Di acquired in step S30.

If it is determined in step S40 that the inspection image di contains a foreign matter Fs, the second inspection unit 156 records foreign matter information of the inspection image Di used in step S40 in step S42. Foreign matter information is information regarding the presence or absence of a foreign matter Fs in the inspection image Di. In step S42, information indicating that a foreign matter Fs is included is recorded as foreign matter information, similar to step S32. If it is determined in step S40 that a void Vd is not included, the second inspection unit 156 records information indicating that a foreign matter Fs is not included as foreign matter information of the inspection image Di in step S44, similar to step S42.

In step S50, the inspection device 150 determines whether all captured images Pi captured in step S10 have been acquired as test images Di. If there are any captured images Pi remaining that have not been acquired as test images Di, the inspection device 150 returns the process to step S20. In step S20, which is executed again, the captured images Pi previously acquired as test images Di are excluded from the acquisition targets.

If it is determined in step S50 that all the captured images Pi have been acquired as the inspection images Di, in step S60, the determination unit 158 determines whether or not there is an abnormality in the workpiece W. More specifically, in this embodiment, the determination unit 158 determines that there is an abnormality in the workpiece W when at least one of the first image and the second image acquired as the inspection image Di contains at least one of the void Vd and the foreign matter Fs. Furthermore, the determination unit 158 determines that there is an abnormality in the workpiece W even if the void Vd or the foreign matter Fs is included on any bead Bd. In step S60 in this embodiment, the determination unit 158 determines whether or not there is an abnormality in the workpiece W by referring to the recorded void information and foreign matter information. Note that in other embodiments, for example, the inspection image Di determined to contain the void Vd or the foreign matter Fs in the inspection process may be configured to be stored in a predetermined storage area such as a directory or folder in the storage device 130, the storage unit 142, or the storage unit 152. In this case, in step S60, the determination unit 158 determines whether or not the workpiece W has an abnormality by determining whether or not the inspection image Di is stored in this storage area.

If it is determined in step S60 that the workpiece W has an abnormality, in step S70 the inspection control unit 143 uses the notification unit 160 to notify the abnormality. The workpiece W determined to have an abnormality may, for example, be subjected to additional determination regarding the presence or absence of an abnormality, may be sent to a process for repairing the welded portion WP, or may be discarded. The workpiece W determined to have no abnormality in step S60 is sent to the next process for manufacturing a tank, for example. Note that in this embodiment, each captured image Pi captured in the inspection process, that is, each inspection image Di used in the inspection process, can be used, for example, to update the machine learning model 200 by re-learning, or to regenerate the machine learning model 200.

According to the inspection system 100 in the present embodiment described above, the inspection system 100 includes a first inspection unit 155 that determines the presence or absence of a void Vd on the bead Bd in the inspection image Di, a second inspection unit 156 that determines the presence or absence of a foreign matter Fs on the bead Bd in the inspection image Di by detecting edges included in the inspection image Di, and a determination unit 158 that determines that the workpiece W is abnormal when at least one of the void Vd and the foreign matter Fs is included in the inspection image Di. According to this embodiment, the first inspection unit 155 can determine the presence or absence of a void Vd based on the inspection image Di, and the second inspection unit 156 can determine the presence or absence of a foreign matter Fs based on edges included in the inspection image Di. Then, when either the void Vd or the foreign matter Fs is included in the inspection image Di, it is determined that the workpiece W is abnormal. Therefore, in addition to the void Vd, the adhesion of the foreign matter Fs to the bead Bd can be determined as an abnormality. Furthermore, for example, compared to a configuration in which both the presence or absence of voids Vd and the presence or absence of foreign matter Fs are determined by only the first inspection unit 155 and the second inspection unit 156, it is easier to specialize the second inspection unit 156 in determining the presence or absence of foreign matter Fs. This increases the likelihood that foreign matter Fs on the bead Bd can be accurately detected as an abnormality. In particular, if the foreign matter Fs is linear as in this embodiment, foreign matter Fs can be more effectively detected based on edges. Furthermore, since it is easier to specialize the first inspection unit 155 in determining the presence or absence of voids Vd, it is also possible to increase the likelihood that voids Vd can be accurately detected as an abnormality.

In addition, in this embodiment, the first inspection unit 155 determines the presence or absence of a void Vd using a machine learning model 200 that has been trained using a learning image that captures the appearance of the bead Bd. Therefore, the second inspection unit 156 can determine the presence or absence of a foreign body Fs based on the edge, and the first inspection unit 155 can determine the presence or absence of a void Vd using the machine learning model 200.

In addition, in this embodiment, the machine learning model 200 has already learned using the first captured image captured by the first camera 112 and the second captured image captured by the second camera 113 as training images. Therefore, for example, compared to a case where only one of the first captured image and the second captured image is used as a training image, it is possible to suppress a shortage of training images. In addition, since the second captured image can be captured by the second camera 113 at the same time as the first captured image is captured by the first camera 112, training images can be prepared more efficiently.

In addition, in this embodiment, the image acquisition unit 157 acquires the first image and the second image as the inspection image Di, respectively, and the judgment unit 158 judges that there is an abnormality in the workpiece W when at least one of the first image and the second image contains at least one of a void Vd and a foreign matter Fs. Therefore, the workpiece W can be inspected more precisely than when, for example, the presence or absence of a void Vd or a foreign matter Fs is judged based on only one of the first image and the second image. In addition, the presence or absence of a void Vd in the first captured image and the second captured image can be judged using a single machine learning model 200, and the first captured image and the second captured image used for the inspection can be used to update or regenerate the machine learning model 200.

B. Other embodiments:
(B1) In the above embodiment, the first captured image and the second captured image are used as learning images for learning the machine learning model 200, but the first captured image and the second captured image may not be used for learning the machine learning model 200. For example, only the first captured image may be used for learning the machine learning model 200, or only an image of the appearance of the bead Bd captured along a direction perpendicular to the axial direction may be used for learning the machine learning model 200. In this case, for example, the photographing unit 111 may not have two cameras, and may have only one camera. In addition, the image acquiring unit 157 acquires the first captured image and the second captured image as the inspection image Di, but similarly, the first captured image and the second captured image may not be acquired as the inspection image Di.

(B2) In the above embodiment, the photographing unit 111 may have three or more cameras. For example, in addition to the first camera 112 and the second camera 113, a third camera and a fourth camera may be provided so that multiple beads Bd can be photographed at the same time. Also, multiple cameras may be arranged so that one bead Bd can be photographed by three or more cameras.

(B3) In the above embodiment, the machine learning model 200 has been trained by supervised learning. In contrast, the machine learning model 200 may be generated by a learning algorithm other than supervised learning. For example, the machine learning model 200 may be generated by unsupervised learning, and may be an autoencoder that has been trained using only images of beads Bd that include voids Vd or only images of beads Bd that do not include voids Vd as training images.

(B4) In the above embodiment, the first inspection unit 155 detects the voids Vd using the machine learning model 200. In contrast, the first inspection unit 155 does not need to use the machine learning model 200 to detect the voids Vd, and may detect the voids Vd based on, for example, brightness differences or brightness variations in the inspection image Di.

(B5) In the above embodiment, the second inspection unit 156 determines the presence or absence of a foreign object Fs based on the angle, coordinates, interval, and strength of the edge. In contrast, the second inspection unit 156 may determine the presence or absence of a foreign object Fs based on, for example, any one, two, or three of these.

(B6) In the above embodiment, in the inspection process, the second inspection unit 156 detects the presence or absence of a foreign body Fs after the first inspection unit 155 detects the presence or absence of a void Vd. In contrast, the detection of the presence or absence of a foreign body Fs may be performed before the detection of the presence or absence of a void Vd, or may be performed in parallel with the detection of the presence or absence of a void Vd.

(B7) In the above embodiment, the inspection system 100 is composed of the photographing unit 110, the storage device 130, the control device 140, the inspection device 150, and the notification unit 160. In contrast, in the inspection system 100, all of these may be configured as an integrated unit, or any two or more of them may be configured as an integrated unit. For example, the inspection device 150 may be incorporated into the control device 140, or the inspection device 150 may be incorporated into the control device 140.

The present disclosure is not limited to the above-described embodiments, and can be realized in various configurations without departing from the spirit of the present disclosure. For example, the technical features in the embodiments corresponding to the technical features in each form described in the Summary of the Invention column can be replaced or combined as appropriate to solve some or all of the above-described problems or to achieve some or all of the above-described effects. Furthermore, if a technical feature is not described as essential in this specification, it can be deleted as appropriate.

100...inspection system, 110...photography unit, 111...photography section, 112...first camera, 113...second camera, 114...axis section, 115...illumination device, 116...camera controller, 130...storage device, 140...control device, 141...CPU, 142...storage section, 143...inspection control section, 150...inspection device, 151...CPU, 152...storage section, 155...first inspection section, 156...second inspection section, 157...image acquisition section, 158...judgment section, 160...notification section, 200...machine learning model, 205...edge detection program

Claims (5)

An inspection system for inspecting a workpiece including a column having a weld, comprising:
an image acquisition unit that acquires an image of the appearance of the bead in the welded portion as an inspection image;
a first inspection unit that determines whether or not a void exists on the bead in the inspection image;
a second inspection unit that detects edges included in the inspection image to determine whether or not a foreign object is present on the bead in the inspection image;
An inspection system comprising: a judgment unit that judges that the workpiece has an abnormality when the inspection image contains at least one of the void and the foreign matter. 2. The inspection system of claim 1,
The first inspection unit is an inspection system that determines the presence or absence of the void using a machine learning model that has been trained using a plurality of training images of the appearance of the bead, and is for determining whether or not the void is contained in the image input to the machine learning model. 3. The inspection system of claim 2,
A first camera that captures an image of a part of the outer appearance of the bead;
a second camera that images the portion of the bead at an angle different from an angle at which the first camera images the portion,
An inspection system, wherein the machine learning model has been trained using an image of the bead's appearance captured by the first camera and an image of the bead's appearance captured by the second camera as the training images. 4. The inspection system of claim 3,
the image acquisition unit acquires, as the inspection images, a first image in which the appearance of the bead of the welded portion to be inspected is captured by the first camera, and a second image in which the appearance of the bead of the welded portion to be inspected is captured by the second camera,
An inspection system, wherein the judgment unit judges that the work has an abnormality when at least one of the first image and the second image contains at least one of the void and the foreign matter. 5. The inspection system according to claim 1 ,
An inspection system wherein the second inspection unit determines the presence or absence of the foreign matter in the inspection image based on at least one of an edge angle, an edge coordinate, an edge spacing, and an edge strength in the inspection image.

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