Inspection Equipment

Abstract

To provide an inspection apparatus which can classify a type of solder on the basis of a difference in the shape (texture) of a solidification structure appearing on a solder surface of an inspection object.SOLUTION: An inspection apparatus 10 comprises: an imaging unit 20 which images an inspection object 12; and a control unit 30. The control unit 30 acquires image data by imaging a solder portion on an inspection object 12 by the imaging unit 20, extracts a feature amount of the shape of a solidification structure appearing on a surface of the solder portion from the image data, and classifies the type of solder used for the solder portion on the basis of the feature amount.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The present invention relates to an inspection device. [Background technology]

[0002] Inspection devices that inspect the appearance of a board on which electronic components or the like are mounted as test objects inspect the state of soldering on the board (see, for example, Patent Document 1). Furthermore, in recent years, many solders with low lead content have been developed. Therefore, solders with different performances due to differences in composition have been developed (see, for example, Patent Document 2). [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Application Laid-Open No. 2012-053015 [Patent Document 2] Japanese Patent Application Publication No. 2019-206032 Summary of the Invention [Problem to be solved by the invention]

[0004] As mentioned above, many solders with low lead content have been developed in recent years, but the type of solder used for each board is specified from the perspective of quality assurance, etc. However, there are cases where a different type of solder than the specified solder is used due to a mistake or other reason. In such cases, there is a problem that current inspection devices are unable to classify the type of solder used on the board.

[0005] The present invention has been made in consideration of these problems, and aims to provide an inspection device that can classify solder types based on differences in the shape (texture) of the solidified structure that appears on the solder surface of the inspected object. [Means for solving the problem]

[0006] In order to solve the above problems, the inspection device according to the present invention comprises: a plurality of light sources that irradiate the object under inspection with illumination light at different angles; The inspection apparatus includes an imaging unit that images an object to be inspected, and a control unit, irradiating the object under inspection with illumination light from each of the plurality of light sources; The imaging unit captures an image of the solder portion on the object to be inspected. , corresponding to each of the plurality of light sources Acquire image data The first step to , a second step of generating RGB image data by converting the luminance value of each pixel corresponding to the same location on the object to be inspected in the image data corresponding to each of the plurality of light sources into color information corresponding to the inclination state of the location on the object to be inspected from the luminance value of the pixel; a third step of converting the color information into information consisting of hue, saturation, and lightness for each pixel of the RGB image data; The solidification structure that appears on the surface of the solder part Microstructure (texture) and classifying the type of solder used in the soldered portion based on the feature amount. Step 4: Execute . [Effects of the Invention]

[0007] According to the inspection device of the present invention, it is possible to classify the type of solder based on the difference in the shape (texture) of the solidified structure that appears on the solder surface of the inspected object. [Brief explanation of the drawings]

[0008] [Figure 1] FIG. 2 is an explanatory diagram for explaining the configuration of an inspection device. [Figure 2] 10A and 10B are explanatory diagrams for explaining the projection angle of the lighting unit and the detection of its reflected light, where FIG. 10A shows the projection angle of each illumination source of the lighting unit, and FIG. 10B shows an example of the state of the inspection surface of the object under inspection. [Figure 3] 10 is an explanatory diagram for explaining the correspondence between the hue in the HSV color system and the projection angle of the illumination source of the lighting unit. FIG. [Figure 4] 10 is a flowchart showing the flow of image synthesis processing. [Figure 5] 10 is a flowchart showing the flow of a solder type classification process. [Figure 6] FIG. 10 is an explanatory diagram illustrating an example of a feature amount map. [Figure 7] 10 is a flowchart showing the flow of a first inspection method. [Figure 8] 10 is a flowchart showing the flow of a second inspection method. [Figure 9] 10 is a flowchart showing the flow of a third inspection method. [Figure 10]10 is a flowchart showing the flow of a fourth inspection method. [Figure 11] 10 is a flowchart showing the flow of a fifth inspection method. DETAILED DESCRIPTION OF THE INVENTION

[0009] A preferred embodiment of the present invention will be described below with reference to the drawings. First, the configuration of an inspection device 10 according to this embodiment will be described with reference to FIG. 1. This inspection device 10 is a device that inspects an object 12 under inspection using object image data obtained by imaging the object 12 under inspection. The object 12 under inspection is, for example, an electronic circuit board on which a large number of electronic components are mounted. The inspection device 10 determines whether the electronic components are properly mounted based on the object image data. This inspection is usually performed on each component for multiple inspection items. An inspection item is an item that requires determination of whether the component is good or bad. The inspection items include, for example, inspection items related to component placement, such as missing components, misalignment, and polarity inversion, as well as inspection items related to the soldering condition and the connection between the component and the board, such as loose lead pins.

[0010] The inspection device 10 includes an inspection table 14 for holding the object under inspection 12, an imaging unit 20 for illuminating and imaging the object under inspection 12, an XY stage 16 for moving the imaging unit 20 relative to the inspection table 14, and a control unit 30 for controlling the imaging unit 20 and the XY stage 16. For ease of explanation, as shown in Fig. 1, the surface of the inspection table 14 on which the object under inspection is placed is defined as the XY plane, and the direction perpendicular to the surface (i.e., the imaging direction by the imaging unit 20 (the optical axis direction of the optical system of the camera unit 21)) is defined as the Z direction.

[0011] The imaging unit 20 is attached to a moving table (not shown) of the XY stage 16 and can be moved in both the X and Y directions by the XY stage 16. The XY stage 16 is, for example, a so-called H-shaped XY stage. The XY stage 16 thus includes a Y linear motor that moves the moving table in the Y direction along a Y-direction guide extending in the Y direction, two X-direction guides that support the Y-direction guide at both ends and are configured to move the moving table and the Y-direction guide in the X direction, and an X linear motor. The XY stage 16 may further include a Z-movement mechanism that moves the imaging unit 20 in the Z direction, or a rotation mechanism that rotates the imaging unit 20. The inspection apparatus 10 may further include an XY stage that can move the inspection table 14. In this case, the XY stage 16 that moves the imaging unit 20 may be omitted.

[0012] The imaging unit 20 includes a camera unit 21, a half mirror 22, an illumination unit 23, and a projection unit 24. In the inspection device 10 according to this embodiment, the camera unit 21, the half mirror 22, the illumination unit 23, and the projection unit 24 may be configured as an integrated imaging unit 20. In this integrated imaging unit 20, the relative positions of the camera unit 21, the half mirror 22, the illumination unit 23, and the projection unit 24 may be fixed, or each unit may be configured to be relatively movable. Alternatively, the camera unit 21, the half mirror 22, the illumination unit 23, and the projection unit 24 may be separate and configured to be independently movable. In the following description, a case will be described in which the inspection object 12 is illuminated using the half mirror 22, but the half mirror 22 may be omitted.

[0013] The camera unit 21 includes an imaging element that generates two-dimensional image data of the object, and an optical system (e.g., a lens) for forming an image on the imaging element. The camera unit 21 is, for example, a CCD camera. The maximum field of view of the camera unit 21 may be smaller than the area on the inspection table 14 where the object under test is placed. In this case, the camera unit 21 captures an image of the entire object under test 12 by dividing it into multiple partial images. The control unit 30 controls the XY stage 16 so that the camera unit 21 moves to the next imaging position each time the camera unit 21 captures a partial image and outputs partial image data. The control unit 30 combines the partial image data to generate overall image data of the object under test 12.

[0014] The camera unit 21 may include an imaging element that generates a one-dimensional image instead of the two-dimensional imaging element. In this case, the entire image of the inspection object 12 can be acquired by scanning the inspection object 12 with the camera unit 21.

[0015] The illumination unit 23 is configured to project illumination light onto the surface of the inspection object 12 for imaging by the camera unit 21. The illumination unit 23 includes one or more light sources that emit light of a wavelength or wavelength range selected from the wavelength range detectable by the imaging element of the camera unit 21. The illumination light is not limited to visible light, and ultraviolet light, X-rays, etc. may also be used. When multiple light sources are provided, each light source is configured to project light of a different wavelength (e.g., red, blue, and green) onto the surface of the inspection object 12 at a different projection angle.

[0016] In the inspection device 10 according to this embodiment, the illumination unit 23 includes an epi-illumination source 23a that projects illumination light perpendicularly onto the inspection surface of the object under inspection 12 (i.e., the surface (XY plane) facing the imaging unit 20), and a side illumination source (comprising an upper light source 23b, a middle light source 23c, and a lower light source 23d in this embodiment) that projects illumination light obliquely onto the inspection surface of the object under inspection 12. A half mirror 22 is disposed on the optical axis of the optical system of the camera unit 21, and a portion of the illumination light emitted from the epi-illumination source 23a is reflected by the half mirror 22 and projected onto the object under inspection 12 along the optical axis. A half prism may be used instead of the half mirror 22. In the inspection device 10 according to this embodiment, the side illumination sources 23b, 23c, and 23d are each a ring illumination source that surrounds the optical axis of the camera unit 21 and projects illumination light obliquely onto the inspection surface of the object under inspection 12. Each of these side illumination sources 23b, 23c, and 23d may be configured by arranging multiple light sources in a circular pattern. The side illumination sources, upper light source 23b, middle light source 23c, and lower light source 23d, are configured to project illumination light at different angles relative to the inspection surface.

[0017] Furthermore, each of the upper light source 23b, the middle light source 23c, and the lower light source 23d, which are the side illumination sources, may be configured as a single ring illumination source or may include multiple ring illumination sources. For example, the epi-illumination source 23a may be attached to the side of the camera unit 21, and among the side illumination sources, the upper light source 23b may be configured as a single ring illumination unit, and the middle light source 23c and the lower light source 23d may be integrated into a single ring illumination unit. In this embodiment, the epi-illumination source 23a is a red illumination source, among the side illumination sources, the upper light source 23b and the lower light source 23d are red illumination sources, and among the side illumination sources, the middle light source 23c is configured as a green illumination source, a blue illumination source, and a red illumination source.

[0018] As described above, in the description of this embodiment, a case where four types of light sources that irradiate the inspection object 12 with illumination light from different angles is described, but the types (number) of light sources are not limited to four, and it may be only the incident illumination source 23a, or a combination of the incident illumination source 23a and any of the side illumination sources 23b to 23d, or only the side illumination sources 23b to 23d or some of these. Also, it may be any one of the light sources 23a to 23d, in which case it may be configured to acquire a monochrome image using a single color light source.

[0019] 1, for reference, dashed arrows indicate the light beams projected from the incident illumination source 23a, reflected by the inspection surface of the object under inspection 12, and projected onto the camera unit 21. Here, the light reflected by the inspection surface of the object under inspection 12 is incident on the half mirror 22, and a portion of the light is transmitted and incident onto the camera unit 21. In addition, the projections from the side illumination sources 23b, 23c, and 23d and the projection unit 24 are similarly indicated by dashed arrows, and as an example, the light beams projected from the upper light source 23b, reflected by the inspection surface of the object under inspection 12, and incident onto the camera unit 21 are also shown. Here, for convenience of explanation, the surface of the object under inspection 12 is illustrated as a flat surface, but in reality, like a general object under inspection, there are slopes and heights depending on the location.

[0020] The projection unit 24 projects a pattern onto the inspection surface of the inspection object 12. The inspection object 12 onto which the pattern is projected is imaged by the camera unit 21. In the illustrated embodiment, the projection unit 24 is provided between the upper light source 23b and the middle light source 23c, but the arrangement of the projection unit 24 is not limited to this, and the projection unit 24 may be provided outside the lower light source 23d, for example.

[0021] The inspection device 10 creates a height map of the inspection surface of the object under test 12 based on pattern image data of the object under test 12 captured with the pattern projected from the projection unit 24. The control unit 30 detects a local mismatch between the pattern image and the projected pattern, and calculates the height of that portion based on the local mismatch. In other words, a change in the captured pattern (the pattern projected onto the object under test 12 and captured by the camera unit 21) relative to the projected pattern (the pattern projected onto the object under test 12 from the projection unit 24) corresponds to a change in height on the inspection surface.

[0022] Here, the projection pattern is preferably a one-dimensional stripe pattern in which bright and dark lines alternate and repeat periodically. The projection unit 24 is arranged to project the stripe pattern obliquely onto the inspection surface of the inspection object 12. Discontinuities in height on the inspection surface of the inspection object 12 appear as pattern shifts in the stripe pattern image. Therefore, the height difference can be determined from the amount of pattern shift. In the inspection device 10 according to this embodiment, the control unit 30 creates a height map using the PMP (Phase Measurement Profilometry) method, which uses a stripe pattern whose brightness changes according to a sine curve. In the PMP method, the amount of shift in the stripe pattern corresponds to the phase difference of the sine curve.

[0023] The projection unit 24 includes a pattern forming device, a light source for illuminating the pattern forming device, and an optical system for projecting the pattern onto the inspection surface of the object under test 12. The pattern forming device may be, for example, a variable patterning device capable of dynamically generating a desired pattern, such as a liquid crystal display, or a fixed patterning device in which a pattern is fixedly formed on a substrate, such as a glass plate. When the pattern forming device is a fixed patterning device, it is preferable to provide a movement mechanism for moving the fixed patterning device or an adjustment mechanism in the optical system for pattern projection, thereby making the projection position of the pattern variable. Furthermore, the projection unit 24 may be configured to be able to switch between multiple fixed patterning devices having different patterns.

[0024] A plurality of projection units 24 may be provided around the camera unit 21. The plurality of projection units 24 are arranged so as to project patterns onto the inspection object 12 from different projection directions. In this way, it is possible to reduce the area on the inspection surface where the pattern is not projected due to a shadow caused by a difference in height.

[0025] 1, which controls the entire device, is realized as hardware by the CPU, memory, and other LSIs of any computer, and as software by programs loaded into memory, but the diagram shows functional blocks realized by the cooperation of these. Therefore, it will be understood by those skilled in the art that these functional blocks can be realized in various ways by hardware alone, software alone, or a combination of both.

[0026] FIG. 1 shows an example of the configuration of the control unit 30. The control unit 30 includes an inspection control unit 31 and a memory 35, which is a storage unit. The inspection control unit 31 includes a height measurement unit 32, an inspection data processing unit 33, and an inspection unit 34. The inspection device 10 also includes an input unit 36 ​​for receiving input from a user or another device, and an output unit 37 for outputting information related to the inspection. The input unit 36 ​​and the output unit 37 are each connected to the control unit 30. The input unit 36 ​​includes, for example, input means such as a mouse or keyboard for receiving input from a user, and communication means for communicating with other devices. The output unit 37 includes known output means such as a display or printer.

[0027] The inspection control unit 31 is configured to execute various control processes for inspection based on input from the input unit 36 ​​and inspection-related information stored in the memory 35. The inspection-related information includes two-dimensional image data of the object 12 under inspection, a height map of the object 12 under inspection, and substrate inspection data (inspection data). Prior to inspection, the inspection data processing unit 33 creates substrate inspection data using the two-dimensional image data and height map of the object 12 under inspection that is guaranteed to pass all inspection items. The inspection unit 34 executes inspection based on the created substrate inspection data and the two-dimensional image data and height map of the object 12 under inspection to be inspected.

[0028] Board inspection data is inspection data created for each type of board. Board inspection data is, so to speak, a collection of inspection data for each component mounted on the board. The inspection data for each component includes the inspection items required for that component, the inspection window, which is the inspection area on the image for each inspection item, and the inspection criteria that serve as the criteria for determining whether each inspection item is pass or fail. One or more inspection windows are set for each inspection item. For example, for an inspection item that determines whether a component's soldering is pass or fail, typically, the same number of inspection windows as the number of soldering areas on the component are set, with the arrangement corresponding to the arrangement of the soldering areas. Furthermore, for inspection items that use image data that has undergone a specified image processing on the image data of the object being inspected, the details of that image processing are also included in the inspection data.

[0029] The inspection data processing unit 33 sets each item of inspection data to suit the board in the board inspection data creation process. For example, the inspection data processing unit 33 automatically sets the position and size of each inspection window for each inspection item so that it matches the component layout of the board. The inspection data processing unit 33 may also accept user input for some items of the inspection data. For example, the inspection data processing unit 33 may also accept tuning of the inspection criteria by the user. The inspection criteria may also be set using height information.

[0030] The inspection control unit 31 performs imaging processing of the object under inspection 12 as preprocessing for creating substrate inspection data. The object under inspection 12 used must pass all inspection items. As described above, the imaging processing is performed by controlling the relative movement of the imaging unit 20 and the inspection table 14 while illuminating the object under inspection 12 with the illumination unit 23, sequentially capturing partial images of the object under inspection 12, and acquiring partial image data. Multiple pieces of partial image data are captured so that the entire object under inspection 12 is covered. The inspection control unit 31 combines these multiple pieces of partial image data to generate full-surface substrate image data that includes the entire inspection surface of the object under inspection 12. The inspection control unit 31 stores the full-surface substrate image data in memory 35.

[0031] Furthermore, as a preprocessing step for creating a height map, the inspection control unit 31 controls the relative movement of the imaging unit 20 and the inspection table 14 while projecting a pattern onto the inspection object 12 using the projection unit 24, divides the pattern image of the inspection object 12, sequentially captures the images, and acquires divided image data when the pattern is projected. The projected pattern is preferably a stripe pattern whose brightness changes according to a sine curve based on the PMP method. The inspection control unit 31 combines the divided image data obtained by capturing the images to generate pattern image data, which is image data of the entire inspection surface of the inspection object 12. The inspection control unit 31 stores the pattern image data in the memory 35. Note that pattern image data may be generated for only a portion of the inspection surface rather than the entire surface.

[0032] The height measurement unit 32 creates a height map of the entire inspection surface of the object under inspection 12 based on the captured pattern of the pattern image data. The height measurement unit 32 first calculates the local phase difference between the pattern image data and the reference pattern image data for the entire image, thereby calculating a phase difference map of the inspection surface of the object under inspection 12. The reference pattern image data is the pattern image projected by the projection unit 24 (i.e., image data generated by a pattern forming device built into the projection unit 24). The height measurement unit 32 creates the height map of the object under inspection 12 based on a reference plane serving as a reference for height measurement and the phase difference map. The reference plane is, for example, the surface of the electronic circuit board to be inspected. The reference plane does not necessarily have to be flat, and may be a curved surface that reflects deformation such as warpage of the board. The reference plane may be specified in advance by user input, or may be calculated for each individual board, for example, using a board surface height measurement method described below.

[0033] Specifically, the height measurement unit 32 calculates the phase difference of the stripe pattern between each pixel of the captured pattern image data and the corresponding pixel of the reference pattern image data. The height measurement unit 32 converts the phase difference into height. The conversion to height is performed using the local stripe width in the vicinity of the pixel. This is to compensate for the difference in stripe width depending on the location on the captured pattern image data. This is because the distance from the projection unit 24 varies depending on the position on the inspection surface, so even if the stripe width of the reference pattern is constant, the stripe width changes linearly from one end of the pattern projection area on the inspection surface to the other. The height measurement unit 32 calculates the height from the reference surface based on the converted height and the reference surface, and creates a height map of the inspection object 12.

[0034] The inspection control unit 31 may create inspection object image data having a height distribution by associating height information contained in a height map of the inspection object 12 with each pixel of a two-dimensional image of the inspection object 12. The inspection control unit 31 may also perform a three-dimensional modeling display of the inspection object 12 based on the inspection object image data with height distribution. The inspection control unit 31 may also superimpose the height distribution on the two-dimensional inspection object image data and display it on the output unit 37. For example, the inspection object image data may be displayed in different colors depending on the height distribution. Note that the inspection device 10 according to this embodiment does not necessarily have to implement the projection unit 24 and the height measurement process of the inspection object 12 performed by this projection unit 24.

[0035] Next, a method for processing image data captured using the illumination unit 23 will be described. As described above, in the inspection device 10 according to this embodiment, the light sources constituting the illumination unit 23 (the epi-illumination source 23a, and the upper light source 23b, the middle light source 23c, and the lower light source 23d, which are side illumination sources) are arranged so as to have different projection angles with respect to a reference plane of the object under inspection 12 (an inspection surface of the object under inspection 12, which is a surface substantially parallel to the installation surface of the inspection device 10), as shown in FIG. 2(a). Specifically, illumination light from the epi-illumination source 23a is projected along the optical axis L of the optical system of the camera unit 21, i.e., substantially perpendicular to the reference plane, and illumination light from the upper light source 23b, the middle light source 23c, and the lower light source 23d is projected in this order so that the projection angles approach the horizontal.

[0036] Of the light projected from each of the light sources 23a to 23d of the illumination unit 23 and reflected by the object under inspection 12, the intensity of the light other than the light reflected by the object under inspection 12 and directly incident on the camera unit 21 is ideally 0. In other words, the angle (inclination state) of the inspection surface of the object under inspection 12 with respect to the reference plane is Depending on, among the light sources 23a to 23d of the illumination unit 23, the intensity of the reflected light from the light source whose light reflected by this inspection surface directly enters the camera unit 21 increases, and the intensity of the reflected light from other light sources becomes 0. For example, when solder of the cross-section shown in Fig. 2(b) is formed on the inspection surface of the inspection object 12, according to the angle of the solder surface with respect to the reference surface, the intensity of the reflected light of the illumination light from each of the light sources 23a to 23d of the illumination unit 23 detected by the imaging element of the camera unit 21 changes. In the present embodiment, for the inclined surface with an angle of 0° to 15° with respect to the reference surface, the intensity of the reflected light from the incident illumination source 23a increases; for the inclined surface with an angle of 15° to 45°, the intensity of the reflected light from the upper light source 23b increases; for the inclined surface with an angle of 45° to 65°, the intensity of the reflected light from the middle light source 23c increases; for the inclined surface with an angle of 65° to 85°, the intensity of the reflected light from the lower light source 23d increases. The relationship between each of the light sources 23a to 23d of the illumination unit 23 and the angle of the inclined surface of the inspection object 12 is an example, and it is not limited to this configuration.

[0037] From the above, the intensity of each pixel of the image data obtained by lighting each of the light sources 23a to 23d of the illumination unit 23 and imaging with the camera unit 21 increases when it coincides with the angle of the inclined surface described above, and becomes a value close to 0 when it does not coincide.

[0038] Therefore, in the inspection apparatus 10 according to the present embodiment, an image of the R (red) component, G (green) component, and B (blue) component is generated from the image data obtained by projecting illumination light from each of the light sources 23a to 23d of the illumination unit 23 and imaging with the camera unit 21, and further, an RGB image (color image) is generated by synthesizing these three images, so as to represent the inclination state of the inspection surface of the inspection object 12.

[0039] As shown in FIG. 3, when a color is expressed by hue H, saturation S, and brightness V (when expressed in the HSV color system), the hue H is expressed as an angle of a circle, and the saturation S and brightness V are expressed as magnitudes in mutually orthogonal directions. In this hue H, R (red), G (green), and B (blue) are positioned 120° apart from each other. Therefore, image data obtained by the reflected light projected from the upper light source 23b, i.e., image data obtained by detecting the reflected light from a slanted surface at an angle of 15° to 45° in this embodiment (referred to as "Top" in FIG. 3), is assigned to R (red); image data obtained by the reflected light projected from the middle light source 23c, i.e., image data obtained by detecting the reflected light from a slanted surface at an angle of 45° to 65° in this embodiment (referred to as "Side" in FIG. 3), is assigned to G (green); and image data obtained by the reflected light projected from the lower light source 23d, i.e., image data obtained by detecting the reflected light from a slanted surface at an angle of 65° to 85° in this embodiment (referred to as "Side" in FIG. 3), is assigned to G (green). slope By assigning the image data (called "Low" in FIG. 3) detecting reflected light from the side illumination sources 23b-23d to B (blue), image data expressed in RGB according to the inclination state can be obtained from the RGB image data (color image data) obtained by combining these image data. Therefore, the inclination state of the inspection surface of the inspection object 12 can be grasped from the color of this image data. Furthermore, as described above, by associating the projection angles of the side illumination sources 23b-23d of the illumination unit 23 with the hue H, image data (called "Coaxis" in FIG. 3) detecting reflected light from an inclined surface of 0°-15°, which is smaller than the 15°-45° represented by R (red), can be displayed in a color (purple) intermediate between R (red) and B (blue). Therefore, even when four or more light sources with different projection angles are used as the illumination unit 23, the inclination state of the inspection surface of the inspection object 12 can be clearly expressed from the RGB image data (color image data). In other words, the condition of the solder shown in FIG. 2(b) can be determined from the RGB image (color image).

[0040] Note that the color of the illumination light emitted from each of the light sources 23a to 23d of the illumination unit 23 does not need to match the color (RGB) to which image data obtained by capturing the reflected light from each of these light sources 23a to 23d is assigned (because the hue H represents the inclination state (angle) of the inspection surface of the inspection object 12), so the image sensor of the camera unit 21 does not need to be color (it only needs to be able to detect the intensity of light). Note that in generating RGB image data (color image data), differences in intensity are expressed by saturation S or lightness V.

[0041] The light sources 23a to 23d may be turned on sequentially to capture an image of the inspection object 12 with the camera unit 21, or the camera unit 21 may be configured with a camera capable of acquiring color image data, and the light sources 23a to 23d may be turned on simultaneously to capture a single image of the inspection object 12. In this case, image data of the R (red) component, image data of the G (green) component, and image data of the B (blue) component can be acquired from one piece of color image data.

[0042] 4, the image synthesis process of the inspection control unit 31 of the control unit 30 will be described. As described above, the inspection control unit 31 controls the XY stage 16, and acquires image data of the inspection surface of the inspected object 12 illuminated by the epi-illumination source 23a (hereinafter referred to as the "Coaxis image"), image data of the inspection surface of the inspected object 12 illuminated by the upper light source 23b (hereinafter referred to as the "Top image"), image data of the inspection surface of the inspected object 12 illuminated by the middle light source 23c (hereinafter referred to as the "Side image"), and image data of the inspection surface of the inspected object 12 illuminated by the lower light source 23d (hereinafter referred to as the "Low image"), and stores the intensity of each pixel in the memory 35. In the following description, the image data (inspection object image data) captured on the inspection surface of the inspection object 12 is assumed to be composed of M × N pixels (M and N are positive integers). The storage area for the image data (Coaxis image) of the epi-illumination source 23a for pixel (i, j) is assumed to be Ac(i, j), the storage area for the image data (Top image) of the upper light source 23b is assumed to be At(i, j), the storage area for the image data (Side image) of the middle light source 23c is assumed to be As(i, j), and the storage area for the image data (Low image) of the lower light source 23d is assumed to be Al(i, j). The storage area for the image data of the R (red) component generated by the following processing is assumed to be Br(i, j), the storage area for the image data of the G (green) component is assumed to be Bg(i, j), and the storage area for the image data of the B (blue) component is assumed to be Bb(i, j). Note that i = 0···M-1 and j = 0···N-1.

[0043] When image data of the inspection surface of the inspection object 12 is captured by each of the light sources 23a to 23d of the illumination unit 23 by the above-mentioned process, the inspection control unit 31 of the control unit 30 clears the storage areas Br(i,j), Bg(i,j), and Bb(i,j) of the image data of the RGB components (step S100). Then, the control unit 31 sets 0 to a variable i that counts the pixel in the column direction of the image data (step S102) and sets 0 to a variable j that counts the pixel in the row direction of the image data (step S104). First, the control unit 31 compares the intensity (Ac(i,j)) of the Coaxis image at pixel (i,j) with the intensity (At(i,j)) of the Top image (step S106). If the intensity of the Coaxis image is greater than the intensity of the Top image, the control unit 31 stores the intensity value of the Coaxis image as the value of pixel (i,j) of the image data of the R component (sets the value of Ac(i,j) to Br(i,j)) (step S108). Then, the control unit 31 compares the intensity of the Top image with the intensity of the Coaxis image (step S109). End If so, the intensity value of the Top image is stored as the value of pixel (i, j) of the R component image data (the value of At(i, j) is set to Br(i, j)) (step S110).

[0044] Next, the intensity of the Coaxis image (Ac(i,j)) at pixel (i,j) is compared with the intensity of the Low image (Al(i,j)) (step S112). If the intensity of the Coaxis image is greater than the intensity of the Low image, the intensity value of the Coaxis image is stored as the value of pixel (i,j) of the B component image data (the value of Ac(i,j) is set to Bb(i,j)) (step S114). The intensity of the Low image is then compared with the intensity of the Coaxis image. End If so, the intensity value of the Low image is stored as the value of pixel (i, j) of the B component image data (the value of Al(i, j) is set to Bb(i, j)) (step S116).

[0045] Furthermore, the intensity (As(i,j)) of the Side image at pixel (i,j) is stored as the value of pixel (i,j) of the G component image data (the value of As(i,j) is set to Bg(i,j)) (step S118).

[0046] Then, 1 is added to variable j (step S120), and it is determined whether the value of variable j is smaller than N (step S122). If it is smaller than N, the process returns to step S106 and repeats the above processing. If it is determined in step S122 that the value of variable j is equal to or greater than N, 1 is added to variable i (step S124), and it is determined whether the value of variable i is smaller than M (step S126). If it is smaller than M, the process returns to step S104 and repeats the above processing.

[0047] Finally, using the R component image data Br(i,j), B component image data Bb(i,j), and G component image data Bg(i,j) (i=0···M-1, j=0···N-1) generated for all M×N pixels in the above manner, the red component value is determined from the value of Br(i,j), the blue component value is determined from the value of Bb(i,j), and Bg(i,j) is calculated for each pixel (i,j). Value of The value of the green component is determined from the above, and the color image data (RGB image data) is synthesized and stored in the memory 35 (step S128).

[0048] Basically, the intensity of reflected light cannot be detected unless the projection angles of the light sources 23a to 23d of the illumination unit 23 and the tilt state of the inspection surface of the inspection object 12 are directly input to the camera unit 21. However, there are cases where light reflected from the inspection surface is reflected at another location on the inspection surface of the inspection object 12 (due to secondary reflection) and is incident on and detected by the camera unit 21. Also, as described with reference to Fig. 3, in this embodiment, of the hue H of the RGB image data that is finally generated, R (red) is assigned to Top (representing a tilt of 15° to 45°) and B (blue) is assigned to Low (representing a tilt of 65° to 85°). Therefore, at pixel (i, j), when the intensity of the Coaxis image (Ac(i, j)) is greater than the intensity of the Top image (At(i, j)) and the intensity of the Low image (Al(i, j)), by setting the intensity of this Coaxis image as the values ​​of the R image data and B image data (Br(i, j) and Bb(i, j)) at that pixel (i, j), it can be determined that the light is at the angle at which reflected light from the incident illumination source 23a enters the camera unit 21 (a tilted state of 0° to 15°), and the hue H can be expressed as purple. Furthermore, when the intensity of the Top image is equal to or greater than the intensity of the Coaxis image, it can be determined that the inspection surface corresponding to the pixel is at an angle at which reflected light from the upper light source 23b is directly incident on the camera unit 21 (a tilted state of 15° to 45°), and the hue H is represented in red.When the intensity of the Low image is equal to or greater than the intensity of the Coaxis image, it can be determined that the inspection surface for the pixel is at an angle at which reflected light from the lower light source 23d is directly incident on the camera unit 21 (a tilted state of 65° to 85°), and the hue H is represented in blue.

[0049] If the hue H of Coaxis is assigned to yellow, for example, the angle of the inspection surface will also be yellow when it is in a tilted state near the boundary between the tilted state corresponding to Side (45° to 65°) and the tilted state corresponding to Low (65° to 85°), making it impossible to distinguish the tilted state. However, by assigning the hue H corresponding to Coaxis to purple, which is halfway between R (red) and B (blue), which have the furthest range of tilt angles, the tilted state can be clearly distinguished. Similarly, by assigning purple, the influence of secondary reflections can also be eliminated.

[0050] As described above, by representing the tilt state (angle) of the inspection surface of the object under test 12 as RGB image data in correspondence with the angle of hue H in the HSV color system (see FIG. 3), changes in the angle of hue H (i.e., changes in color) correspond to changes in the angle of the inspection surface (for example, as the angle of the inspection surface changes from 0° to 30° to 55° to 75°, the color of the pixel at the corresponding location in the RGB image changes from purple to red to green to blue), allowing the user to intuitively understand the tilt state of the inspection surface. Note that in the above explanation, the Top, Side, and Low states are assigned to R (red), G (green), and B (blue), respectively (resulting in the Coaxis state being purple). However, if the Top state is assigned to yellow, for example, it is possible to address this by assigning colors shifted 120° in hue H from yellow to the Side and Low states in FIG. 3, and setting the Coaxis state to a hue H between the Top and Low states.

[0051] Furthermore, by using the above-described RGB image data, when the inclination state of the inspection surface of the inspection object 12 changes smoothly, the hue H changes according to the angle as described above, so when the change in hue H is not continuous or changes suddenly, it is possible to express the possibility that the inspection surface is abnormal (the height of the inspection surface is abnormal). Furthermore, by estimating the inclination state (angle) of the inspection surface from the change in hue H in the RGB image data, it can also be used as material for measuring the height of the inspection surface.

[0052] It should be noted that the object of inspection using such RGB image data is not limited to the solder surface described above, but can also be applied to the shape of the tip of an IC lead or the shape of a chip electrode.

[0053] Next, when the object under test 12 is an electronic circuit board or the like, the types of solder used to attach electronic components to this electronic circuit board and how to classify them will be explained.

[0054] Conventional solder is an alloy whose main components are lead and tin, and when the molten solder is heated and solidifies, a fine lamellar eutectic structure of lead and tin is formed, resulting in a smooth surface with little unevenness. On the other hand, in the case of so-called "lead-free solder," which uses silver, copper, or other metals instead of lead to reduce the lead content, primary crystals of large dendrites appear first during solidification, and the eutectic structure forms in the gaps between them. As a result, the surface of the solidified solder is formed with numerous irregularities on the order of several tens of micrometers, but the shape, size, and number of these irregularities vary depending on the metals and their proportions contained in the solder. From the above, it can be said that the shape of the solidification structure that appears on the solder surface (the shape (texture) of the solidified solder surface) Smooth and rough The type of solder used can be classified based on the shape, size, and number of the irregularities.

[0055] As described above, the inspection device of this embodiment is configured to irradiate the surface of the inspected object 12 with illumination light emitted from different angles, thereby obtaining RGB image data (color image data) that expresses the angle of the inspection surface with differences in color information, and to classify the type of solder used from the image data of the solder surface obtained using this RGB image data. The method for classifying solder types will be described below.

[0056] First, a method for classifying solder types will be described with reference to FIG. 5. When the solder type classification process begins, the control unit 30 reads RGB image data including solder portions from the memory 35 (step S200). As described above, the board inspection data includes information on the inspection window, which is the inspection area on the image for each inspection item, and from this information, the position of the solder portion on the inspected object 12 can be identified. Alternatively, the position of the solder can also be identified from the design data of the inspected object 12. The control unit 30 also converts the read RGB image data into HSV and outputs H( Hue ), S (saturation), and V (luminance) are obtained (step S202).

[0057] As mentioned above, Hue This information represents the amount of inclination of the solder portion, which reflects the macro uneven surface shape of the solder portion. Therefore, the control unit 30 calculates the following using the three-axis values ​​obtained from the RGB image data: Hue By labeling the distribution of , the graininess feature (size, shape, number of irregularities (particles), etc.) is obtained (step S204). In addition, the saturation information is a continuous quantity that corresponds to the diffuse reflection of the surface of the solder part, and reflects the microscopic surface roughness of the solder part. Specifically, when there is a lot of diffuse reflection, the saturation is close to 0, and when there is a lot of total reflection or specular reflection, the saturation is 100%, reflecting the microscopic surface roughness. Therefore, the control unit 30 obtains the surface smoothness feature (smooth or rough) from the saturation using the three-axis values ​​obtained from the RGB image data (step S206).

[0058] Finally, the control unit 30 calculates the feature quantities obtained in steps S204 and S206 as shown in FIG. Feature map The solder type is classified based on the feature values ​​(step S208), and the solder type classification process is terminated. In Fig. 6, the solder type is classified based on the particle count, particle size, and surface smoothness as feature values.

[0059] Contour Match, an algorithm for inspecting specific regions within an image, can be used to classify solder types. Contour Match is a method for inspecting by enclosing the contours of contiguous pixels (regions) that meet certain conditions and measuring their number, area, and contour length. When binarizing an image and determining the area of ​​irregularities, the value is the same whether the target pixels are dispersed or clustered. Contour Match, however, can capture regions that are clusters of pixels, allowing for accurate representation of the shape (texture) of the solder surface. As described above, the solder type classification process according to this embodiment uses HSV-converted RGB image data, thereby improving the accuracy of the above-mentioned features. Note that solder can also be classified using original RGB image data without HSV conversion.

[0060] When the irregularities of the solidification structure are finer than the resolution of the camera unit 21 and are like a matte finish, diffuse reflected light is captured. In this case, the RGB values ​​according to the angle of illumination are not clearly separated as in specular reflection, and an image is captured in which the various illuminations appear to be mixed together. In this case, it is difficult to extract the granular contours themselves, but it is possible to obtain the characteristic that there are irregularities that are finer than the resolution of the camera unit 21.

[0061] Alternatively, as a method for classifying solder types, class classification can be performed using machine learning such as deep learning. Specifically, by creating an AI model by learning HSV-converted RGB image data for each solder type in a pre-selected image area, the solder type can be classified based on the image data of the solder part (image data obtained by converting RGB image data to HSV) during inspection based on this AI model. Using an AI model eliminates the need for parameter adjustment for classification processing. Note that classification can also be performed using the original RGB image data without HSV conversion.

[0062] The type of solder used in the test object 12 may not only be determined based on a single solder part, but may also be classified as the type of solder used in the test object 12 by performing the above-described classification process on multiple solder parts of the test object 12, and then classifying the most frequently classified type of solder as the type of solder used in the test object 12.

[0063] When acquiring HSV-converted RGB image data (specifically, image data in which the color corresponds to the angle of the solder portion) from image data acquired by irradiating the object under test 12 with illumination light from different angles, it is desirable for the classification of solder types that the camera unit 21 be positioned so that the optical axis of the lens of the camera unit 21 is as nearly perpendicular as possible to the solder surface. Therefore, in addition to the above-mentioned camera unit 21 (referred to as the "main camera"), a sub-camera may be provided that captures the object under test 12 from an angle different from that of the main camera, and the main camera and the sub-camera may each acquire RGB image data corresponding to the angle of the solder portion. This sub-camera may be positioned, for example, at the position of the projection unit 24 in FIG. 1. When generating HSV-converted RGB image data from image data acquired by the sub-camera, it is desirable to ensure that the relationship between the color of the RGB image data acquired by the main camera and the angle of the solder portion is the same. In other words, it is desirable that the RGB image data acquired by the main camera and the RGB image data acquired by the sub-camera have the same color when the angle of the solder portion is the same.

[0064] In this way, when RGB image data is acquired using the main camera and the sub-camera, the main camera may capture an image of solder with no component mounted thereon, and the sub-camera may capture an image of non-defective solder with an angle.

[0065] The inspection device 10 according to this embodiment requires a certain degree of field of view to inspect the soldering condition and component mounting condition, which results in a low resolution for the camera unit 21. However, as described above, by acquiring image data by irradiating the object under inspection 12 with illumination light from different angles and then generating RGB image data corresponding to the angle and color of the solder portion from this image data and using this data to classify the solder type, it is possible to accurately classify the solder type even with a low resolution for the camera unit 21. In other words, this solder type classification method does not require detailed capture of the shape of the solidified structure; the camera unit 21 only needs a resolution sufficient to capture general characteristics to a certain extent. For example, to capture a 20 μm structure, a resolution of 2 μm, or 1 / 10 of that, is generally required. However, according to the method of the present application, a resolution of 5 to 30 μm, which allows for general capture, is sufficient. Furthermore, by widening the field of view of the camera unit 21, the inspection speed of the object under inspection 12 can be improved.

[0066] Next, we will explain the process of inspecting the soldered portions of the object under test 12, which is executed by the inspection device 10 according to this embodiment. Note that the inspection of the object under test 12 by the inspection device 10 includes not only inspection of the soldered portions but also inspection of the quality of the mounting state of electronic components, but the following explanation will only cover the inspection of the soldered portions.

[0067] -First inspection method- First, a first solder inspection method will be described with reference to Figure 7. When inspection begins, the control unit 30 of the inspection device 10 carries the object under inspection 12, which has been handed over from an upstream process of the inspection device 10, into the inspection area (step S300). The control unit 30 also moves the imaging unit 20 using the XY stage 16 to capture an image of the recognition mark on the object under inspection 12 (step S301). The recognition mark makes it possible to accurately grasp the position of the board, and therefore to accurately identify the position of the solder in subsequent processing.

[0068] Next, the control unit 30 moves the imaging unit 20 using the XY stage 16 to capture an image of the solder portion on the object under test 12 to be used for classifying the type of solder (step S302). As described above, it is possible to identify the position of the solder from the design data and board inspection data of the object under test 12, and based on this information, it is possible to efficiently obtain an image of the solder portion.

[0069] When the image data of the soldered portion is acquired in step S302, the control unit 30 uses the image data to execute the solder type classification process described above and classify the type of solder used in the currently inspected object 12 (step S303). The control unit 30 compares the solder type classified in step S303 with the solder type specified in the design data and the board inspection data (step S304). If the control unit 30 determines that the type of solder used is correct (the same as the solder type specified in the design data and the board inspection data) (step S304: "Y"), the control unit 30 images other areas on the object 12 (step S305) and inspects the soldering condition in each area (step S306). When inspection of all soldered portions is completed, the object 12 is transported to the next process (step S307), and the process returns to step S300 to inspect the next object 12.

[0070] On the other hand, in step S304, the control unit 30 determines that the type of solder being used is incorrect (the type of solder specified in the design data or the board inspection data is incorrect). Different from the type ) (step S304: "N"), the control unit 30 outputs a warning using the output unit 37 or the like (step S308), and temporarily ends the inspection process. When a warning is output, an operator or the like removes the inspected object 12 from the inspection device 10 and checks the type of solder, etc.

[0071] In this way, according to the first inspection method, the type of solder used in the object to be inspected 12 can be classified from the image of the solder portion, and a warning can be issued if the type of solder differs from that specified in the design data or board inspection data, making it possible to manage the type of solder used in the object to be inspected 12.

[0072] -Second inspection method- Next, a second solder inspection method will be explained using Figure 8. This second inspection method classifies the type of solder, reads inspection parameters set according to the type of solder used, and switches board inspection data based on these inspection parameters to inspect the soldering condition.

[0073] When the inspection starts, the control unit 30 carries the object under inspection 12, which has been delivered from an upstream process of the inspection device 10, into the inspection area (step S320). The control unit 30 also moves the imaging unit 20 using the XY stage 16 to capture an image of the recognition mark on the object under inspection 12 (step S321). The recognition mark allows the position of the board to be accurately determined, and the position of the solder can be accurately identified in the subsequent processing.

[0074] Next, the control unit 30 moves the imaging unit 20 using the XY stage 16 to capture an image of the solder portion on the object under test 12 to be used for classifying the type of solder (step S322). As with the first inspection method, it is possible to identify the position of the solder from the design data and board inspection data of the object under test 12, and based on this information, it is possible to efficiently obtain an image of the solder portion.

[0075] Once the image data of the solder portion is acquired in step S322, the control unit 30 uses the image data to execute the solder type classification process described above and classify the type of solder used in the currently inspected object 12 (step S323). Then, the control unit 30 loads inspection parameters corresponding to the classified solder type (step S324). Here, a specific example will be described in which one of two types of solder, A or B, is used (the number of solder types is not limited to two). When the control unit 30 determines that the solder type is "A" (step S324: "Type A"), it loads inspection parameters for solder type A from the memory 35 or the like (step S325). When the control unit 30 determines that the solder type is "B" (step S324: "Type B"), it loads inspection parameters for solder type B from the memory 35 or the like (step S326).

[0076] After reading the inspection parameters, the control unit 30 images other areas on the object to be inspected 12 (step S327), and inspects the soldering condition in each area using the inspection parameters read in step S325 or step S326 described above (step S328).When inspection of all soldered parts is completed, the object to be inspected 12 is transported to the next process (step S329), and the process returns to step S320 to inspect the next object to be inspected 12.

[0077] In this way, according to the second inspection method, the type of solder used in the inspected object 12 can be classified from the image of the solder portion, and inspection parameters for the soldering state can be read according to the classified type of solder, and the board inspection data can be switched based on these inspection parameters, so that an appropriate inspection can be performed depending on the type of solder used.

[0078] -Third inspection method- Next, a third solder inspection method will be explained using Figure 9. This third inspection method is a method in which solder types are classified, and board inspection data is generated according to the type of solder used to perform the inspection.

[0079] When the inspection starts, the control unit 30 reads from the memory 35 the design data of the object 12 to be inspected (step S340). The control unit 30 also carries the object 12 to be inspected, which has been delivered from an upstream process of the inspection device 10, into the inspection area (step S341). The control unit 30 also moves the imaging unit 20 using the XY stage 16 to capture an image of the recognition mark on the object 12 to be inspected (step S342). The recognition mark allows the position of the board to be accurately determined, and the position of the solder can be accurately identified in the subsequent processing.

[0080] Next, the control unit 30 moves the imaging unit 20 using the XY stage 16 to capture an image of the solder portion on the object under test 12 to be used for classifying the type of solder (step S343). As with the first and second inspection methods, the position of the solder can be identified from the design data and board inspection data of the object under test 12, and images of the solder portion can be efficiently obtained based on this information.

[0081] Once the image data of the solder portion is acquired in step S343, the control unit 30 uses the image data to execute the solder type classification process described above and classify the type of solder used in the currently inspected object 12 (step S344). Then, the control unit 30 loads the inspection library corresponding to the classified solder type (step S345). Here, a specific example will be described in which one of two types of solder, A or B, is used (the number of solder types is not limited to two). If the control unit 30 determines that the solder type is "A" (step S345: "Type A"), it loads the inspection library for solder type A from memory 35 or the like (step S346). If the control unit 30 determines that the solder type is "B" (step S345: "Type B"), it loads the inspection library for solder type B from memory 35 or the like (step S347).

[0082] After reading the inspection library, the control unit 30 images other areas on the object under test 12 (step S348), and uses the design data read in the above-mentioned step S340 and the inspection library read in step S346 or step S347 to deploy the inspection library for each mounted component based on the design data (step S349).The control unit 30 then inspects the soldering condition in each area using the deployed inspection library (step S350), and when inspection of all soldered portions is completed, the object under test 12 is carried out to the next process (step S351), and the process returns to step S340 to inspect the next object under test 12.

[0083] In this way, according to the third inspection method, it is possible to classify the type of solder used in the inspected object 12 from an image of the soldered portion, and then to develop an inspection library according to the classified solder type and perform inspections of the quality of the soldered state and the mounting state of electronic components based on this inspection library. Therefore, since inspection data can be generated according to the type of solder used in the inspected object 12, it is possible to perform appropriate inspections according to the type of solder used.

[0084] -Fourth inspection method- Next, a fourth solder inspection method will be described using Figure 10. In the third inspection method, an inspection library is developed according to the type of solder being used, but the fourth inspection method is configured in combination with the first inspection method so that the inspection process is stopped when the solder is classified as a type that is not intended to be used.

[0085] When the inspection starts, the control unit 30 reads from the memory 35 the design data of the object 12 to be inspected (step S360). The control unit 30 also carries the object 12 to be inspected, which has been delivered from an upstream process of the inspection device 10, into the inspection area (step S361). The control unit 30 then moves the imaging unit 20 using the XY stage 16 to capture an image of the recognition mark on the object 12 to be inspected (step S362). The recognition mark allows the position of the board to be accurately determined, and the position of the solder can be accurately identified in the subsequent processing.

[0086] Next, the control unit 30 moves the imaging unit 20 using the XY stage 16 to capture an image of the solder portion on the object under test 12 to be used for classifying the type of solder (step S363). As explained in the first inspection method, it is possible to identify the position of the solder from the design data and board inspection data of the object under test 12, and based on this information, it is possible to efficiently obtain an image of the solder portion.

[0087] When the image data of the solder portion is acquired in step S363, the control unit 30 uses the image data to execute the solder type classification process described above and classifies the type of solder used in the currently inspected device 12 (step S364). The control unit 30 also determines whether the solder type classified in step S364 is a known solder type (a solder type that may be set in the design data or board inspection data) (step S365). Specifically, if the control unit 30 determines that the type of solder used is known (step S365: "Y"), the control unit 30 reads an inspection library corresponding to the classified solder type from memory 35 (step S366), images other areas on the device 12 (step S367), and, using the design data read in step S360 and the inspection library read in step S366, deploys the inspection library for each mounted component based on the design data (step S368). Then, the control unit 30 inspects the soldering condition in each area based on the expanded inspection library (step S369), and when inspection of all solder parts is completed, it transports the object to be inspected 12 to the next process (step S370), and returns to step S360 to inspect the next object to be inspected 12.

[0088] On the other hand, if the control unit 30 determines in step S365 that the type of solder being used is unknown (step S365: "N"), the control unit 30 outputs a warning using the output unit 37 or the like (step S371) and temporarily terminates the inspection process. When a warning is output, an operator or the like removes the inspected object 12 from the inspection device 10 and checks the type of solder, etc.

[0089] In this way, according to the fourth inspection method, it is possible to classify the type of solder used in the inspected object 12 from an image of the soldered portion, and to issue a warning if the solder type is not known, thereby making it possible to manage the type of solder used in the inspected object 12. Furthermore, since an inspection library can be set according to the type of solder, it is possible to perform an appropriate inspection according to the type of solder used.

[0090] -Fifth inspection method- Finally, a fifth inspection method for solder will be explained using Figure 11. In the second inspection method, inspection parameters are read in according to the type of solder being used, and the board data is switched based on these parameters to inspect the soldering condition, but the fifth inspection method is configured in combination with the first inspection method to suspend the inspection process when the solder type is classified as not intended to be used.

[0091] When the inspection starts, the control unit 30 carries the object under inspection 12, which has been delivered from an upstream process of the inspection device 10, into the inspection area (step S380). The control unit 30 also moves the imaging unit 20 using the XY stage 16 to capture an image of the recognition mark on the object under inspection 12 (step S381). The recognition mark allows the position of the board to be accurately determined, and the position of the solder can be accurately identified in the subsequent processing.

[0092] Next, the control unit 30 moves the imaging unit 20 using the XY stage 16 to capture an image of the solder portion on the object under test 12 to be used for classifying the type of solder (step S382). As with the first inspection method, it is possible to identify the position of the solder from the design data and board inspection data of the object under test 12, and based on this information, it is possible to efficiently obtain an image of the solder portion.

[0093] When the image data of the solder portion is acquired in step S382, the control unit 30 uses the image data to execute the solder type classification process described above and classifies the type of solder used in the currently inspected object 12 (step S383). After the solder type is classified, the control unit 30 determines whether the solder type classified in step S383 is a known solder type (a solder type that may be set in design data or board inspection data) (step S384). Specifically, when the control unit 30 determines that the type of solder used is known (step S384: "Y"), the control unit 30 reads inspection parameters corresponding to the classified solder type (step S385). Here, a specific description will be given of a case where one of two types of solder, A or B, is used (the number of solder types is not limited to two). When the control unit 30 determines that the solder type is "A" (step S385: "Type A"), it reads the inspection parameters for solder type A from the memory 35 or the like (step S386). When the control unit 30 determines that the solder type is "B" (step S385: "Type B"), it reads the inspection parameters for solder type B from the memory 35 or the like (step S387).

[0094] After reading the inspection parameters, the control unit 30 images other areas on the object to be inspected 12 (step S388), and inspects the soldering condition in each area using the inspection parameters read in step S386 or step S387 described above (step S389).When inspection of all soldered parts has been completed, the object to be inspected 12 is transported to the next process (step S390), and the process returns to step S380 to inspect the next object to be inspected 12.

[0095] On the other hand, if the control unit 30 determines in step S384 that the type of solder being used is unknown (step S384: "N"), the control unit 30 outputs a warning using the output unit 37 or the like (step S391) and temporarily terminates the inspection process. When a warning is output, an operator or the like removes the inspected object 12 from the inspection device 10 and checks the type of solder, etc.

[0096] In this way, according to the fifth inspection method, the type of solder used in the object 12 to be inspected can be classified from the image of the soldered portion, and a warning can be issued if the solder type is not a known one, making it possible to manage the type of solder used in the object 12 to be inspected. Also, depending on the classified solder type, inspection parameters for the soldering state can be read and the board inspection data can be switched based on these inspection parameters, making it possible to perform an appropriate inspection depending on the type of solder used. [Explanation of symbols]

[0097] 10 Inspection equipment 12 Test subject 20 Imaging unit (imaging section) 21 Camera unit 23 Lighting unit (light source) 30 Control unit (control section)

Claims

1. A plurality of light sources that irradiate illumination light onto an object to be inspected at different angles; an imaging unit that images the object to be inspected; a control unit; The control unit a first step of irradiating the object under inspection with illumination light from each of the plurality of light sources, capturing an image of the solder portion on the object under inspection by the imaging unit, and acquiring image data corresponding to each of the plurality of light sources; a second step of generating RGB image data by converting, for each pixel corresponding to the same location on the object under test in the image data corresponding to each of the plurality of light sources, the luminance value of the pixel into color information associated with the tilt state of the location on the object under test; a third step of converting the color information into information consisting of hue, saturation, and brightness for each pixel of the RGB image data; a fourth step of extracting feature quantities of the fine shape (texture) of the solidification structure appearing on the surface of the solder part from the information consisting of the hue, saturation, and brightness, and classifying the solder used in the solder part based on the feature quantities. Inspection equipment.

2. In the fourth step, the control unit: extracting a feature amount of graininess of the surface of the solder part from the hue; A feature of the surface smoothness of the surface of the solder part is extracted from the saturation. The inspection device according to claim 1 .

3. The control unit Based on the design data or inspection data of the object to be inspected, a position on the object to be inspected of a solder portion from which image data to be used for classifying the solder is acquired is identified.

3. The inspection device according to claim 1 or 2.

4. The control unit Inspecting the test object based on the classified solder.

3. The inspection device according to claim 1 or 2.

5. The control unit Inspection data is selected according to the classified solder, and the object to be inspected is inspected based on the selected inspection data.

3. The inspection device according to claim 1 or 2.

6. The control unit Inspection data is generated according to the classified solder, and the object to be inspected is inspected based on the generated inspection data.

3. The inspection device according to claim 1 or 2.

7. The feature amount is the size or number of irregularities on the surface of the solder part.

3. The inspection device according to claim 1 or 2.

8. The control unit The solder is classified based on an AI model generated by machine learning from the feature amount and the solder.

3. The inspection device according to claim 1 or 2.

9. the imaging unit has a plurality of camera units with different imaging angles relative to the object under inspection, The control unit The solder is classified using each of the image data of the object to be inspected captured by the plurality of camera units.

3. The inspection device according to claim 1 or 2.

10. The control unit Acquiring image data of a plurality of solder parts, and classifying the solder of the solder part corresponding to each image data according to the image data; The solder that is most frequently found among the classified solders is classified as the solder used in the test object.

3. The inspection device according to claim 1 or 2.

11. The control unit In addition to the above solder classification, The soldering condition of the soldered portion on the test object is inspected.

3. The inspection device according to claim 1 or 2.

12. The control unit The inspection is stopped depending on the classified solder.

3. An inspection device according to claim 1 or 2.

Images