Component inspection method and component inspection device

Abstract

In this component inspection method, first, a region including an ignition coil (3) and a fuel tube (4) is scanned from outside by a three-dimensional laser scanner (5) to gradually acquire measurement data that includes a portion of the outer surface of the ignition coil (3) and the fuel tube (4). Thereafter, the region including the ignition coil (3) and the fuel tube (4) in design data, and the region including the ignition coil (3) and the fuel tube (4) in measurement data are aligned, and scanning progress is calculated on the basis of this alignment. When the progress has exceeded a progress threshold value, information is presented to a display (8) indicated that the progress threshold value has been exceeded.

Description

[Technical Field]

[0001] The present invention relates to a component inspection method and a component inspection device for inspecting the spatial arrangement of at least one component in an assembly formed by assembling a plurality of components. [Background technology]

[0002] Patent Document 1 discloses a part inspection method for inspecting a part by determining the outer shape of the part based on measurement data of the part measured by a 3D laser scanner and design data of the part. In this method, when acquiring shape data using the 3D laser scanner, it is necessary to irradiate the entire outer surface of the part with laser light.

[0003] The component inspection device of Patent Document 1 has a problem in that it takes a long time to inspect a component because the entire outer surface of the component is irradiated with laser light.

[0004] Furthermore, in recent years, in assemblies made up of multiple parts, the laser light is not sufficiently irradiated onto the outer surface of the target part due to reasons such as the laser light being blocked by other parts, and the time required for part inspection tends to be longer.

[0005] The present invention has been made in light of such problems, and provides a component inspection method and component inspection device that can shorten the inspection time for target components in an assembly by scanning from the outside. [Prior art documents] [Patent documents]

[0006] [Patent Document 1] Patent No. 6792927 Summary of the Invention

[0007] The present invention is a component inspection method for performing inspection related to the spatial arrangement state of at least one target component in an assembly formed by assembling a plurality of components, by scanning an area including the target component from the outside with a three-dimensional sensor to gradually obtain measurement data including a portion of the outer surface of the target component, obtaining design data including the outer shape of the target component and its positional relationship within the assembly, aligning the area including the target component in the design data with the area including the target component in the measurement data, calculating a progress level indicating the degree to which scanning has progressed based on the alignment, comparing the progress level with a predetermined threshold, and presenting information that the threshold has been exceeded when the progress level exceeds the threshold.

[0008] The present invention allows for reduced inspection time of target parts in an assembly by scanning from the outside. [Brief explanation of the drawings]

[0009] [Figure 1] FIG. 2 is an explanatory diagram showing various components in an engine compartment of the embodiment as viewed from above. [Figure 2] 1 is a schematic diagram of a gap inspection device according to an embodiment of the present invention. [Figure 3] This is point cloud data of the engine room and its internal parts scanned using a 3D laser scanner. [Figure 4] Point cloud data of the engine bay and its internal components showing 40% progress. [Figure 5] FIG. 10 is an explanatory diagram of reliability. [Figure 6] FIG. 10 is an explanatory diagram showing an indication of the displacement amount of the fuel tube on the display. [Figure 7] 1 is a flowchart showing a gap inspection method according to the present embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0010] An embodiment of the present invention will now be described with reference to the drawings. In this embodiment, the present invention is applied to a gap inspection process in which the spatial arrangement of two parts in an engine compartment is identified and the minimum gap between them is calculated during the inspection process of a completed automobile.

[0011] FIG. 1 is a top view of some of the various components in an automobile engine compartment 1, which is an assembly of one embodiment, showing the area near the engine intake manifold 2. An ignition coil 3, which is part of the engine's ignition system, is located below the intake manifold 2. A fuel tube 4, which supplies fuel to the engine, is located to the side of the intake manifold 2. The fuel tube 4 is made of a metal tube that is oil-resistant and fire-resistant, and has a circular cross section along its radial direction. As shown in FIG. 1, the fuel tube 4 has a straight portion 4a that extends generally linearly along the side of the intake manifold 2 and an inclined portion 4b that slopes from one end of the straight portion 4a toward the ignition coil 3. The fuel tube 4, made of a metal tube, undergoes some deformation during installation and is therefore considered a non-rigid component. On the other hand, the ignition coil 3 is considered a rigid component whose external shape does not change. The minimum spatial distance (minimum gap) between the ignition coil 3 and the fuel tube 4 is regulated by law, and therefore inspection of this minimum gap is required during the finished vehicle inspection process. In many cases, the design minimum distance between the ignition coil 3 and the fuel tube 4 is regulated at a position on the outer surface of at least one of the ignition coil 3 or the fuel tube 4 that is not visible from the outside, and it is generally difficult for an inspector to measure using a ruler. In this embodiment, the gap between these two components is determined by external measurement using a three-dimensional sensor and calculation processing.

[0012] Furthermore, in addition to the intake manifold 2, the ignition coil 3, and the fuel tube 4, multiple other parts are provided in the engine compartment 1. In the completed vehicle inspection process of this embodiment, the distance between the ignition coil 3 and the fuel tube 4 is inspected in an automobile that is assembled from multiple parts including the ignition coil 3, which is a rigid part, and the fuel tube 4, which is a non-rigid part that takes into account deformation of its shape.

[0013] As shown in Figure 2, one embodiment of a gap inspection device used in the finished vehicle inspection process is mainly composed of a three-dimensional sensor, such as a three-dimensional laser scanner 5, a database 6, a control device 7, and one or more displays (devices) 8. In the finished vehicle inspection process, a large number of inspections are carried out sequentially in a predetermined order. The gap inspection device of one embodiment is configured as part of the inspection equipment in the finished vehicle inspection process.

[0014] The 3D laser scanner 5 can obtain the 3D coordinates of the surface shape of the measurement target by irradiating the measurement target with a laser and measuring the reflection time. By performing measurements at a high speed of approximately tens of thousands of points per second, high-density point cloud data can be obtained. While various sizes and types of 3D laser scanners are known, one embodiment uses a type that can be held by an operator and used to scan the measurement target. The target area is measured by manually scanning the area including the ignition coil 3, the fuel tube 4, and other components from the outside. Scanning with this 3D laser scanner 5 obtains point cloud data for the entire area including a portion of the outer surface of the ignition coil 3 and the fuel tube 4, as shown in FIG. 3 .

[0015] Although point cloud data is actually acquired as time-series data for each frame by scanning, point cloud data for the entire area can be acquired by overlaying the data. It is also desirable to perform noise reduction processing on the acquired point cloud data to remove noise caused by dust or other particles that may have been introduced during scanning. The 3D laser scanner may also require markers to serve as references for identifying the shape and position of the target part during scanning.

[0016] Here, "scanning" in the present invention is a concept that includes either or both of the planar scanning function of the 3D sensor (e.g., 3D laser scanner 5) itself and the movement of the 3D sensor by, for example, an operator. In one embodiment, scanning is performed by using a 3D laser scanner 5 with a planar scanning function and further moving this 3D laser scanner 5. Depending on the size and shape of the target area to be measured or the type of 3D sensor, it is also possible, for example, to arrange multiple 3D sensors fixedly at appropriate positions in space and acquire point cloud data of the target area using the scanning function of each 3D sensor.

[0017] The database 6 stores all design data for the automobile to be inspected. Therefore, shape data for the ignition coil 3 and the fuel tube 4, which are the targets of the gap inspection, are stored as design data along with data indicating their spatial relationship. The database 6 also stores shape data and positional relationship data for other parts present within the area. The design data is stored in the database 6 in the form of CAD data that constitutes a mesh. During the gap inspection, the necessary design data is read from the database 6 to the control device 7. After the design data is read into the control device 7, known hidden surface removal may be performed on areas other than those involved in the gap between the ignition coil 3 and the fuel tube 4 to reduce the data size.

[0018] The control device 7 first aligns the design data of the ignition coil 3 as a rigid body with the position of the measurement data of the ignition coil 3 to generate the outer shape of the ignition coil 3 including the hidden outer surface portion, and then aligns the design data of the fuel tube 4 as a non-rigid body with the position of the measurement data of the fuel tube 4 to perform various processes to generate the outer shape of the fuel tube 4 including the hidden outer surface portion.The control device 7 then calculates the distance between any point on the ignition coil 3 and any point on the fuel tube 4 based on the generated outer shapes of the ignition coil 3 and the fuel tube 4. Each component of the control device 7 will be described in detail later.

[0019] If the minimum distance calculated by the control device 7 is less than a threshold value prescribed by law, the display 8 displays the displacement (movement) amount required for the fuel tube 4 and the location thereof.

[0020] Next, we will explain each component of the control device 7. As shown in Fig. 2, the control device 7 has a first alignment unit 7a, a progress calculation unit 7b, a second alignment unit 7c, a third alignment unit 7d, a reliability calculation unit 7e, a first interpolation unit 7f, a second interpolation unit 7g, a distance calculation unit 7h, and a displacement calculation unit 7i.

[0021] The first alignment unit 7a roughly aligns the entire target area (the so-called target area in alignment) including the ignition coil 3, the fuel tube 4, and other components in the measurement data acquired by the 3D laser scanner 5 with the entire area (the so-called reference area in alignment) including the ignition coil 3, the fuel tube 4, and other components in the design data stored in the database 6. More specifically, the first alignment unit 7a uses the FPFH algorithm to search for keypoints in the point cloud data of the entire target area and describes the characteristics of these keypoints, such as the normal vectors of the keypoints and the relative angles of the surroundings. Furthermore, the first alignment unit 7a converts the design data of the entire reference area into point cloud data using a well-known conversion method, and then similarly uses the FPFH algorithm to search for keypoints and describe the characteristics of these keypoints, such as the normal vectors of the keypoints and the relative angles of the surroundings. The first alignment unit 7a then compares the normal vectors between the target keypoints and the reference keypoints and their relative angles with the surrounding point clouds to search for a pair of keypoints whose normal vectors and relative angles approximately match, and then roughly aligns the point cloud data of the reference with the point cloud data of the target using the pair of keypoints. During this rough alignment, the non-rigid fuel tube 4 is considered to be a rigid body, and as a result, for example, an average alignment is performed within the length of the fuel tube 4. The rough alignment of the target region by the first alignment unit 7a is performed in parallel with the progress of scanning the target region. The first alignment unit 7a may also perform rough alignment of the target region using a known algorithm other than the FPFH algorithm.

[0022] The progress calculation unit 7b calculates the progress of the scanning required in the target area after the rough alignment by the first alignment unit 7a and before the detailed alignment of the ignition coil 3 and the fuel tube 4 (described later). That is, the progress calculation unit 7b calculates the progress of the scanning (degree of progress) from the ratio between the number of points in the point cloud data of the target area based on the reference design data and the number of points matched between the reference and the target by the rough alignment by the first alignment unit 7a. Furthermore, the progress calculation unit 7b compares the calculated progress with a predetermined progress threshold (e.g., 40% in this embodiment) and determines in real time whether the progress, which gradually increases as the scanning progresses, has exceeded the progress threshold. For example, information on the current progress and whether the progress has exceeded the progress threshold is displayed on the display 8 via an information output unit (not shown). The operator then continues scanning using the 3D laser scanner 5 according to this display. In other words, scanning by the 3D laser scanner 5 (generation of point cloud data), rough alignment, and progress calculation are repeated in real time until a predetermined progress threshold is exceeded. For example, the area surrounded by the dashed line in Figure 4 corresponds to a progress of 40%.

[0023] In addition to the ratio of the number of data points as described above, the progress may also be evaluated based on the distance scanned by the 3D laser scanner 5, the number of viewpoints passed by the 3D laser scanner 5, the number of key points used in rough alignment, etc.

[0024] Since the basic shape or configuration of the area to be scanned is known as design data obtained from the database 6, it is possible to estimate the spatial position of the 3D laser scanner 5 and its movement trajectory, including its movement trajectory, based on the point cloud data sequentially obtained from the 3D laser scanner 5. Then, the progress of scanning can be calculated based on how much of the distance scanned by the 3D laser scanner 5 is included in the length of this movement trajectory.

[0025] In addition, for the viewpoint at the position of the three-dimensional laser scanner 5, multiple representative viewpoints are predetermined, and the progress of scanning can be determined based on how many representative viewpoints the three-dimensional laser scanner 5 passes through before drawing a movement trajectory.

[0026] Furthermore, the maximum number of key points is determined based on the point cloud data converted from the design data, so the progress of scanning can be calculated by finding the ratio of key points based on the point cloud data converted from the measurement data to this maximum number of key points.

[0027] The second alignment unit 7c performs detailed spatial alignment for each component, provided that the progress rate exceeds 40%. Specifically, the second alignment unit 7c searches for paired points in the reference point cloud data for every point in the target point cloud data obtained by measuring the ignition coil 3 and the fuel tube 4, and performs detailed alignment of the reference point cloud data with the target point cloud data. The non-rigid fuel tube 4 is considered to be a rigid body here, and as a result, average alignment is performed within the length of the fuel tube 4. The detailed alignment in the second alignment unit 7c can be performed using an appropriate known algorithm.

[0028] After the detailed alignment by the second alignment unit 7c, the third alignment unit 7d performs so-called non-rigid alignment of non-rigid components (fuel tube 4 in this embodiment) taking deformation into account. Any known algorithm can be used here. For example, the third alignment unit 7d searches for nearest neighbor pairs from the reference point cloud data and target point cloud data, which have been previously aligned as rigid bodies, and calculates rotation, scaling, and translation parameters to bring the paired points closer to each other. For example, the outer shape of the fuel tube 4 is downsampled to form an outer surface composed of multiple triangles with vertices and edges. Using the vertices representing the point clouds (clusters) of each downsampled region, i.e., each region containing multiple adjacent triangles, the deformation of the cluster is decomposed into rotation, scaling, and translation parameters under the constraint that the edge length does not change (strictly speaking, the length change is minimized). The deformation of the entire fuel tube 4 is obtained as a collection of such cluster-based deformations. The third alignment unit 7d aligns the reference point cloud data for the fuel tube 4 with the target point cloud data in space while deforming the reference point cloud data for the fuel tube 4 using a non-rigid alignment method that takes such deformation into consideration.

[0029] The reliability calculation unit 7e calculates the reliability of the alignment of each target component (i.e., the ignition coil 3 and the fuel tube 4). In other words, the reliability calculation unit 7e calculates the reliability indicating how close the target point cloud data is to the aligned reference point cloud data for each of the ignition coil 3 and the fuel tube 4.

[0030] FIG. 5 is an explanatory diagram that schematically shows point cloud data of a fuel tube 4 after alignment to explain reliability. For simplicity, it is assumed here that the circular outer surface of a cross section of the fuel tube 4 is formed by 13 pieces of point cloud data. The 13 pieces of point cloud data Dr arranged in a circle are reference point cloud data based on design data, and the seven pieces of point cloud data Dt arranged in a semicircle are target point cloud data based on measurement data. For example, if scanning by the 3D laser scanner 5 is performed only from the top of the figure, the lower half will be an area that was not scanned (a missing area), and the target point cloud data Dt will be arranged in a semicircle.

[0031] The reliability is expressed, for example, as the ratio between the number of points in the reference point cloud data Dr and the number of points in the target point cloud data Dt that fall within a radius L from each point in the reference point cloud data Dr. In the figure, the range of radius L from the numerous points in the reference point cloud data Dr is represented by an outer circle C1 and an inner circle C2, each indicated by a dashed line. In the example shown in FIG. 5( a), four target point cloud data Dt are included within the range R of the circles C1 and C2, resulting in a reliability of 4 / 13. In the example shown in FIG. 5( b), two target point cloud data Dt are included within the range R of the circles C1 and C2, resulting in a reliability of 2 / 13. In the example shown in FIG. 5( c), all of the target points, i.e., seven point cloud data Dt, are included within the range R, resulting in a reliability of 7 / 13. Thus, the reliability is affected by both the accuracy of alignment and the size or proportion of missing areas in the measurement data.

[0032] The first interpolation unit 7f uses reference point cloud data to interpolate missing portions that have not been scanned in the measurement data of the ignition coil 3, i.e., the target point cloud data. In other words, the first interpolation unit 7f interpolates the outer surface portion of the back (lower) side of the ignition coil 3, which is hidden from view from above the engine compartment 1, using the reference point cloud data to generate point cloud data including the hidden portion. The first interpolation unit 7f then converts the generated point cloud data into mesh data that constitutes a surface using a well-known conversion method.

[0033] Similarly, the second interpolation unit 7g interpolates missing portions that have not been scanned in the measurement data of the fuel tube 4, i.e., the target point cloud data, using the reference point cloud data. In other words, the outer surface portion of the back side (lower side) of the fuel tube 4, which is hidden from view from above the engine compartment 1, is interpolated using the reference point cloud data to generate point cloud data of the fuel tube 4 including the hidden portion. Then, the second interpolation unit 7g converts the generated point cloud data into mesh data that constitutes a surface using a well-known conversion method.

[0034] The distance calculation unit 7h calculates the distance from each point on the surface of the ignition coil 3 to each point on the surface of the fuel tube 4 based on the mesh data of the ignition coil 3 acquired by the first interpolation unit 7f and the mesh data of the fuel tube 4 acquired by the second interpolation unit 7g. Furthermore, the distance calculation unit 7h obtains the minimum distance by comparing the calculated distances with each other. The distance calculation unit 7h may calculate the distance from each point on the ignition coil 3 to each point on the fuel tube 4 based on the point cloud data of the ignition coil 3 and the point cloud data of the fuel tube 4 without converting them into mesh data. The distance calculation unit 7h also compares the minimum distance with a predetermined threshold, and if the minimum distance is less than the threshold, displays information on the display 8 that the minimum distance is less than the threshold. When presenting information to a worker that the minimum distance is less than the threshold, in addition to the above-mentioned image presentation using the display, the information may be presented by sound using an audio device such as a speaker, or by vibration using a wearable device such as a scanner held by the worker or a watch worn by the worker. In the case of presenting information by vibration, whether the minimum distance is above or below the threshold may be presented using a predetermined vibration pattern.

[0035] When the minimum distance is less than a predetermined threshold, the displacement amount calculation unit 7i quantitatively calculates the amount of movement required for the fuel tube 4 at the point where the minimum distance is reached and for several representative points, that is, the amount of displacement of the fuel tube 4 required for the minimum distance to be equal to or greater than the threshold, and presents the information on the display 8.

[0036] The display 8 displays the minimum distance and location between the ignition coil 3 and the fuel tube 4, along with the displacement amount required for the fuel tube 4. The display 8 also shows the desired placement of the fuel tube 4 in the engine compartment 1 by the area between two curves W1 and W2 shown by dashed lines in Fig. 6, and if the minimum distance is less than the threshold, the worker displaces the fuel tube 4 based on the displacement amount (not shown) displayed on the display 8, thereby placing the fuel tube 4 in the area between the curves W1 and W2. The dark-colored portion adjacent to the side of the fuel tube 4 indicates a portion of the fuel tube 4 before the worker displaces it. 6, the displacement amount calculation unit 7i displays a displacement of 20 mm in a direction P away from the intake manifold 2 for a point on the straight portion 4a that extends linearly along the side of the intake manifold 2, and further displays a displacement of 10 mm in another direction Q away from the intake manifold 2 for a point on the inclined portion 4b that is inclined toward the ignition coil 3 (see FIG. 1). Note that while the minimum distance and the location of the minimum distance are not shown in FIG. 6, the location of the minimum distance is located between the ignition coil 3 (see FIG. 1) and a point on the inclined portion 4b that is diagonally downward and to the left of the point where the displacement amount in direction Q is applied.

[0037] Next, the gap inspection method of this embodiment will be described with reference to the flowchart of FIG.

[0038] First, in step S1, an operator operates the 3D laser scanner 5 to scan a predetermined area in the engine compartment 1 from the outside, including the target components, the ignition coil 3 and the fuel tube 4, to obtain point cloud data including a portion of the outer surface of each component. This scanning and generation of point cloud data progresses gradually as the scanning operation proceeds.

[0039] Next, in step S2, CAD data of the target components, ignition coil 3 and fuel tube 4, and other peripheral components are obtained from database 6, along with CAD data indicating their spatial positional relationships.

[0040] Then, in step S3, the CAD data is converted into point cloud data using a known appropriate conversion method.

[0041] Next, in step S4, the first alignment unit 7a performs rough alignment between the entire target area and the entire reference area. As described above, rough alignment is performed by aligning the point cloud data of the entire area including the ignition coil 3, the fuel tube 4, and other components with the point cloud data of the entire area including the ignition coil, the fuel tube, and other components in the design data stored in the database 6 by searching for key points and combining paired key points.

[0042] After the rough alignment in step S4, in step S5, the progress calculation unit 7b calculates the progress of scanning from the ratio between the number of points in the point cloud data of the reference area and the number of matching points in the point cloud data of the scanned area.

[0043] Then, in step S6, it is determined whether this progress rate exceeds a predetermined progress rate threshold (40% in this embodiment, but the threshold is not limited to this). If the progress rate is 40% or less, the process proceeds to step S7, where the progress rate is displayed on the display 8 and the worker continues scanning. In other words, the process from step S1 onwards is repeated.

[0044] Furthermore, if the progress rate exceeds 40% in step S6, the process proceeds to step S8, where the target components, the ignition coil 3 and the fuel tube 4, are extracted from the point cloud data of the measurement data and the point cloud data of the design data, respectively. The point cloud data extracted from the measurement data becomes the so-called target, and the point cloud data extracted from the design data becomes the so-called reference. The point cloud data of the target components that serve as the reference may be generated from CAD data of the individual components.

[0045] Next, in step S9, the second alignment unit 7c uses a known appropriate algorithm to perform detailed alignment of the ignition coil 3 and the fuel tube 4. Here, the fuel tube 4 is considered to be a rigid body. For example, as described above, paired points are searched for between the point cloud data of the target that has undergone rough alignment and the point cloud data of the reference, and detailed alignment is performed so that the reference approaches the target.

[0046] Next, in step S10, the third alignment unit 7d described above downsamples the data of the fuel tube 4 in order to perform non-rigid alignment of the fuel tube 4, which is a non-rigid body. Then, in step S11, non-rigid alignment is performed taking into account the deformation of the fuel tube 4. That is, the reference point cloud data is aligned with the target position while being deformed. In this non-rigid alignment, the nearest pair is searched for from the reference point cloud data and target point cloud data, which have been aligned assuming a rigid body as described above, and rotation, enlargement, and translation are calculated as parameters for bringing them closer to each other.

[0047] Next, the process proceeds to step S12, where the reliability of the alignment is calculated for each of the ignition coil 3 and the fuel tube 4. The reliability is expressed, for example, as the ratio between the number of points in the reference point cloud data and the number of points in the target point cloud data that are included within a predetermined radius from each point in the reference point cloud data.

[0048] Then, in step S13, it is determined whether or not the reliability of the ignition coil 3 and the reliability of the fuel tube 4 each satisfy a predetermined reliability. If both reliability levels satisfy the predetermined reliability, it is determined that alignment is complete and the process proceeds to step S14.

[0049] In step S14, the first interpolation unit 7f and the second interpolation unit 7g interpolate unscanned portions of the target point cloud data of the ignition coil 3 and the fuel tube 4 with reference point cloud data aligned with the targets. As a result, point cloud data of the ignition coil 3 and the fuel tube 4 including unscanned portions (i.e., hidden portions) is generated at the positions of each target.

[0050] Then, in step S15, a known conversion method is used to convert the point cloud data including the unscanned portions of both the ignition coil 3 and the fuel tube 4 into mesh data that constitutes a surface.

[0051] Next, in step S16, distance calculation unit 7h calculates the minimum distance between ignition coil 3 and fuel tube 4 based on the mesh data of ignition coil 3 and the mesh data of fuel tube 4. That is, the distance between any two points on each surface is found, and the minimum value among these is set as the minimum distance.

[0052] Then, in step S17, it is determined whether the minimum distance is equal to or greater than the threshold value. If the minimum distance is equal to or greater than the threshold value, the process proceeds to step S18, where information that the minimum distance is equal to or greater than the threshold value is presented on the display 8.

[0053] If the minimum threshold is less than the threshold in step S17, the process proceeds to step S19, where the displacement amount calculation unit 7i calculates the displacement amount of the fuel tube 4 required to make the minimum distance equal to or greater than the threshold. The calculated displacement amount is displayed on the display 8.

[0054] If the reliability is less than the predetermined reliability in step S13, the process proceeds to step S20, where it is determined whether the scanned data is insufficient. If the data is insufficient, the process proceeds to step S21, where the operator is informed that scanning needs to be performed again using the 3D laser scanner 5, and the process returns to step S1.

[0055] If it is determined in step S20 that there is sufficient data, it is assumed that the reliability in step S13 was determined to be low due to excessive deformation of the fuel tube 4, and the process proceeds to step S18, where a message to that effect is displayed on the display 8.

[0056] As described above, in this embodiment, the 3D laser scanner 5 is manually operated to scan the area including the ignition coil 3 and the fuel tube 4 from the outside to obtain measurement data including portions of the outer surfaces of both components. The first alignment unit 7a roughly aligns the area including the ignition coil 3 and the fuel tube 4 in the design data with the area including the ignition coil 3 and the fuel tube 4 in the measurement data. Based on this rough alignment, the progress of scanning by the 3D laser scanner 5 is continuously calculated. When this progress exceeds a predetermined progress threshold, information indicating that the progress threshold has been exceeded is displayed on the display 8. Therefore, the system proceeds to the next stage of part inspection as soon as the progress threshold is exceeded, without waiting for scanning of the entire area to be completed. This reduces the time required for part inspection compared to proceeding to the next stage after scanning of the entire area is completed.

[0057] Furthermore, in this embodiment, after rough alignment by the first alignment unit 7a, the progress calculation unit 7b calculates the scanning progress from the ratio between the number of points in the point cloud data of the target area based on the reference design data and the number of matching points between the reference and the target through rough alignment by the first alignment unit 7a. Therefore, the scanning progress can be efficiently calculated by finding the ratio between the number of points in the point cloud data based on known design data and the number of matching points obtained through rough alignment.

[0058] Furthermore, in this embodiment, the degree of progress of scanning is calculated based on the distance scanned by the 3D laser scanner 5. As described above, the basic shape and the like of the area to be scanned are known from the database 6, so it is possible to estimate the movement trajectory of the 3D laser scanner 5 based on the point cloud data sequentially obtained from the 3D laser scanner 5. Then, the degree of progress of scanning can be calculated based on how much of the distance scanned by the 3D laser scanner 5 is included in the length of this movement trajectory.

[0059] Furthermore, in this embodiment, the degree of scanning progress is calculated based on the number of viewpoints passed by the 3D laser scanner 5. Therefore, the degree of scanning progress can be determined based on how many representative viewpoints the 3D laser scanner 5 passed before drawing a movement trajectory.

[0060] Furthermore, in this embodiment, the scanning progress is calculated based on the number of key points used in the rough alignment. As described above, the maximum number of key points is determined based on the point cloud data converted from the design data. Therefore, the scanning progress can be calculated by finding the ratio of the key points based on the point cloud data converted from the measurement data to this maximum number of key points.

[0061] Furthermore, in this embodiment, after the degree of progress exceeds the progress threshold, the design data for the ignition coil and the fuel tube are precisely aligned with the positions of the measurement data for the ignition coil 3 and the fuel tube 4. Therefore, it is sufficient to scan the area including the ignition coil 3 and the fuel tube 4 for only a relatively short time until the degree of progress exceeds the progress threshold, and therefore detailed alignment of only the target components, the ignition coil 3 and the fuel tube 4, can be performed early.

[0062] The above describes an embodiment in which the present invention is applied to measuring the gap between an automobile ignition coil 3 and a fuel tube 4, but the present invention is not limited to this application and can be widely applied to inspections related to the spatial arrangement of target parts in an assembly containing multiple parts. In the above embodiment, the distance between two parts is measured, but the present invention can also be applied to cases in which there is only one target part.

[0063] Furthermore, in this embodiment, an example of non-rigid positioning of the fuel tube 4 having a circular radial cross section has been described, but the present invention may also be applied to a pipe having a radial cross section other than a circle, for example, a rectangular cross section.

[0064] Furthermore, in the above embodiment, an example has been described in which the three-dimensional laser scanner 5 is held and operated by an operator, but the present invention can also be applied to cases in which scanning is performed by a robot using a three-dimensional sensor.

[0065] In addition, in this embodiment, a 3D laser scanner 5 has been described as a 3D sensor, but other types of 3D sensors, such as ToF types and triangulation types such as stereo cameras, can be widely applied.

Claims

1. 1. A part inspection method for performing inspection related to a spatial arrangement state of at least one target part in an assembly formed by assembling a plurality of parts, comprising: Scanning an area including the target part from the outside with a three-dimensional sensor to gradually acquire measurement data including a portion of the outer surface of the target part; acquiring design data including an outer shape of the target part and a positional relationship of the target part within the assembly; Aligning an area including the target component in the design data with an area including the target component in the measurement data; calculating a progress rate indicating a degree to which the scanning has progressed based on the alignment; comparing the progress to a predetermined threshold; When the progress rate exceeds the threshold, information indicating that the threshold has been exceeded is presented. Part inspection methods.

2. converting the measurement data and the design data into point cloud data; the aligning includes aligning a region including the target part in point cloud data based on the design data with a region including the target part in point cloud data based on the measurement data; 2. The part inspection method according to claim 1, wherein calculating the degree of progress includes calculating the degree of progress from a ratio between the number of points in point cloud data of a target area based on the design data and the number of matching points between the point cloud data based on the design data and the point cloud data based on the measurement data.

3. The component inspection method according to claim 1 , wherein calculating the degree of progress includes calculating the degree of progress based on a distance scanned by the three-dimensional sensor.

4. The component inspection method according to claim 1 , wherein calculating the degree of progress includes calculating the degree of progress based on the number of viewpoints passed by the three-dimensional sensor.

5. converting the measurement data and the design data into point cloud data; The method further includes searching for key points in each of the transformed point cloud data and describing features of the key points; the aligning includes comparing keypoint features of point cloud data of the design data with keypoint features of point cloud data of the metrology data; The method of claim 1 , wherein calculating the progress comprises calculating the progress based on a number of key points used in the alignment.

6. The part inspection method of claim 1 , further comprising aligning design data of the target part with a position of measurement data of the target part after the progress rate exceeds the threshold.

7. A part inspection device that performs an inspection related to the spatial arrangement state of at least one target part in an assembly formed by assembling a plurality of parts, a 3D sensor that scans an area including the target part from the outside and gradually acquires measurement data; a database that stores design data including an outer shape of the target part and a positional relationship of the target part within the assembly; an alignment unit that aligns the design data of the target part to a position of the measurement data of the target part; a progress calculation unit that calculates a progress level indicating a degree to which the scanning has progressed based on the alignment performed by the alignment unit; a device that, when the degree of progress exceeds a predetermined threshold, presents information that the threshold has been exceeded; A component inspection device equipped with the above.

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