JP6553412B2 - Inspection system - Google Patents

Description

  Embodiments of the present invention relate to inspection systems.

  Conventionally, there has been proposed a technique for irradiating an object to be inspected, imaging reflected light from the surface of the object to be inspected as image data, and detecting an abnormality of the object to be inspected based on a change in luminance of the image data. It is done.

  At that time, a technique has been proposed in which the intensity of light to be irradiated to the inspection object is periodically changed, and an abnormality is detected based on a change in luminance of captured image data.

JP 2014-2125 A

  In this type of inspection system, inspection may be performed on the basis of an image obtained by dividing the inspection surface a plurality of times. It is not preferable that it takes time and effort to perform multiple times of imaging.

  Therefore, one of the problems of the present invention is to obtain an inspection system capable of imaging a plurality of imaging regions (inspection regions) more smoothly, for example.

The inspection system according to the embodiment includes, for example, an intensity signal of reflected light from an inspection surface of an inspection object, and light intensity based on a spatial change according to the passage of time of the intensity of light provided on the inspection surface. A temporal correlation image generation unit that generates a temporal correlation image by an imaging system that multiplies a reference signal that changes periodically in response to a temporal change, and a space corresponding to continuous time lapse of light on the inspection surface According to the planar illumination unit that continuously and periodically changes temporally and spatially the intensity of light within one exposure time of the imaging system by changing the pattern periodically, and the temporal correlation image, An arithmetic processing unit that calculates a feature that detects an abnormality based on at least one of the difference from the surrounding area and the difference from the reference surface, the feature corresponding to the distribution of the normal vector of the inspection plane; Set to Is more like the imaging of the imaging area is performed with, and a moving mechanism for moving at least one of the inspection object and the imaging system, the locus of movement of the imaging area on the test surface, the A section that moves around the center of gravity of the inspection object is included.

FIG. 1 is a diagram showing a configuration example of an inspection system including the calibration system of the embodiment. FIG. 2 is a block diagram illustrating a configuration of the time correlation camera of the embodiment. FIG. 3 is a conceptual diagram showing frames accumulated in chronological order by the temporal correlation camera of the embodiment. FIG. 4: is the figure which showed an example of the fringe pattern which the illuminating device of embodiment irradiates. FIG. 5 is a diagram showing a first example of detection of an abnormality of an object under test by the time correlation camera of the embodiment. FIG. 6 is a diagram showing an example of the amplitude of light which changes in response to an abnormality shown in FIG. 5 when the object under test has the abnormality. FIG. 7 is a diagram showing a second example of detection of an abnormality of the object under inspection by the time correlation camera of the embodiment. FIG. 8 is a diagram showing a third example of detection of an abnormality of the object under inspection by the time correlation camera of the embodiment. FIG. 9 is a diagram illustrating an example of a fringe pattern output to the lighting device by the light emission control unit of the embodiment. FIG. 10 is a diagram illustrating an example of a wave shape representing a stripe pattern after passing through the screen of the embodiment. FIG. 11 is a flowchart illustrating a procedure of abnormality detection processing based on amplitude in the abnormality detection processing unit of the embodiment. FIG. 12 is a flowchart illustrating a procedure of an abnormality detection process based on a phase in the abnormality detection processing unit of the embodiment. FIG. 13 is a flowchart illustrating a procedure of abnormality detection processing based on amplitude and intensity in the abnormality detection processing unit of the embodiment. FIG. 14 is a flowchart showing the procedure of the inspection process of the inspection object in the inspection system of the embodiment. FIG. 15 is a diagram illustrating an example of switching the fringe pattern output by the light emission control unit of the second modification. FIG. 16 is a diagram illustrating an example in which the light emission control unit of Modification 2 irradiates the surface including the abnormality (defect) with a stripe pattern. FIG. 17 is a diagram showing the relationship between the abnormality (defect) and the stripe pattern on the screen when the stripe pattern is changed in the y direction. FIG. 18 is a diagram illustrating an example of a fringe pattern output from the light emission control unit of Modification 3 to the illumination device. FIG. 19 is an exemplary schematic diagram illustrating a plurality of imaging regions set on the inspection surface and the imaging order (inspection order) in the inspection system of the embodiment. FIG. 20 is an exemplary flowchart of misregistration correction in the inspection system of the embodiment. FIG. 21 is a graph showing an example of the correlation between the rotation angle around the reference axis of the inspection surface and the luminance value of the first reference point by the inspection system of the embodiment. FIG. 22 is a graph showing an example of the correlation between the rotation angle around the reference axis of the inspection surface and the luminance value of the second reference point by the inspection system of the embodiment. FIG. 23 is a graph showing another example of the correlation between the rotation angle around the reference axis of the inspection surface by the inspection system of the embodiment and the luminance value of the first reference point. FIG. 24 is a graph showing another example of the correlation between the rotation angle about the reference axis of the inspection surface by the inspection system of the embodiment and the luminance value of the first reference point.

<Basic configuration of time correlation camera>
The inspection system of this embodiment will be described. Inspection system 1 of an embodiment is provided with various composition in order to inspect a to-be-inspected object. FIG. 1 is a view showing a configuration example of an inspection system of the present embodiment. As shown in FIG. 1, the inspection system of the present embodiment includes a PC 100, a time correlation camera 110, a lighting device 120, a screen 130, and a moving mechanism 140. The time correlation camera 110 is an example of an imaging unit.

  The moving mechanism 140 is used to fix the inspection object 150 and changes the position and orientation of the surface of the inspection object 150 that can be imaged by the time correlation camera 110 according to control from the PC 100.

  The illumination device 120 is a device that irradiates light to the inspection object 150, and can control the intensity of the light to be irradiated in area units in accordance with the stripe pattern from the PC 100. Furthermore, the lighting device 120 can control the intensity of light in the area unit according to the periodic time transition. In other words, the lighting device 120 can give a periodic temporal change and a spatial change of the light intensity. A specific light intensity control method will be described later.

  The screen 130 diffuses the light output from the illuminating device 120 and then irradiates the test object 150 with light in a plane. The screen 130 according to the present embodiment irradiates the object 150 in a surface with the light input from the illumination device 120 and subjected to periodic time change and space change. In addition, optical system components (not shown), such as a Fresnel lens for condensing, may be provided between the illuminating device 120 and the screen 130.

  In addition, although this embodiment demonstrates the example which comprises the planar irradiation part which combines the illuminating device 120 and the screen 130, and gives the periodic time change and spatial change of light intensity, such a combination is demonstrated. For example, the illumination unit may be configured by arranging LEDs in a plane.

  The time correlation camera 110 includes an optical system 210, an image sensor 220, a data buffer 230, a control unit 240, and a reference signal output unit 250. FIG. 2 is a block diagram showing the configuration of the time correlation camera 110 according to the present embodiment.

  The optical system 210 includes a photographing lens and the like, transmits a light flux from a subject (including a subject to be inspected) outside the time correlation camera 110, and forms an optical image of the subject formed by the light flux.

  The image sensor 220 is a sensor that can output the intensity of light incident through the optical system 210 as a light intensity signal at high speed for each pixel.

  The light intensity signal of the present embodiment is a signal obtained by the illumination device 120 of the inspection system irradiating a subject (including an object to be inspected) with light and the image sensor 220 receiving reflected light from the subject.

  The image sensor 220 is, for example, a sensor that can be read out at a higher speed than a conventional sensor, and has a two-dimensional planar shape in which pixels are arranged in two kinds of directions: a row direction (x direction) and a column direction (y direction). It shall be constructed. Each pixel of the image sensor 220 is defined as a pixel P (1,1),..., P (i, j),..., P (X, Y) (Note that the image size in this embodiment is X X Y.). Note that the reading speed of the image sensor 220 is not limited, and may be the same as that in the related art.

  The image sensor 220 receives a light beam from a subject (including an object to be inspected) transmitted by the optical system 210 and photoelectrically converts the light intensity signal (photographing) indicating the intensity of light reflected from the subject. And generates a two-dimensional planar frame, which is output to the control unit 240. The image sensor 220 of the present embodiment outputs the frame for each readable unit time.

  The control unit 240 according to the present embodiment includes, for example, a CPU, a ROM, and a RAM, and executes the inspection program stored in the ROM to transfer the transfer unit 241, the reading unit 242, and the intensity image superimposing unit 243. And a first multiplier 244, a first correlation image superimposing unit 245, a second multiplier 246, a second correlation image superimposing unit 247, and an image output unit 248. Note that the present invention is not limited to being realized by a CPU or the like, and may be realized by an FPGA or an ASIC.

  The transfer unit 241 stores, in the data buffer 230, the frames composed of the light intensity signal, which are output from the image sensor 220, in chronological order.

  The data buffer 230 accumulates frames composed of light intensity signals output from the image sensor 220 in time series.

  FIG. 3 is a conceptual diagram showing frames accumulated in time series order by the time correlation camera 110 of the present embodiment. As shown in FIG. 3, the data buffer 230 of the present embodiment stores a plurality of light intensity signals G (1, 1, t), every time t (t = t0, t1, t2,..., Tn). ..., G (i, j, t), ..., G (X, Y, t) composed of a plurality of frames Fk (k = 1, 2, ..., n) are in chronological order It is accumulated. Note that one frame created at time t is a light intensity signal G (1, 1, t),..., G (i, j, t), ..., G (X, Y, t). Configured

  A light intensity signal (imaging signal) G (1,1, t),..., G (i, j, t),. Each pixel P (1,1),..., P (i, j),..., P (X, Y) constituting k = 1, 2,.

  The frame output from the image sensor 220 includes only a light intensity signal, in other words, it can be considered as monochrome image data. In this embodiment, an example in which the image sensor 220 generates monochrome image data in consideration of resolution, sensitivity, cost, and the like will be described. However, the image sensor 220 is not limited to a monochrome image sensor. Alternatively, a color image sensor may be used.

  Returning to FIG. 2, the reading unit 242 of the present embodiment receives the light intensity signals G (1,1, t),..., G (i, j, t),. Y, t) are read out in frame-by-frame order and output to the first multiplier 244, the second multiplier 246, and the intensity image superimposing unit 243.

  The time correlation camera 110 of the present embodiment generates image data for each output destination of the reading unit 242. In other words, the time phase camera 110 creates three types of image data.

  The time correlation camera 110 of this embodiment generates intensity image data and two types of time correlation image data as three types of image data. Note that the present embodiment is not limited to generating three types of image data, and it may be possible to generate no intensity image data or to generate one or more types of time-correlated image data. . The temporal correlation camera 110 is an example of a temporal correlation image generation unit.

  As described above, the image sensor 220 of the present embodiment outputs a frame composed of a light intensity signal every unit time. However, in order to generate normal image data, a light intensity signal corresponding to the exposure time necessary for photographing is required. Therefore, in the present embodiment, the intensity image superimposing unit 243 generates intensity image data by superimposing a plurality of frames for an exposure time necessary for photographing. In addition, each pixel value (value representing the light intensity) G (x, y) of the intensity image data can be derived from the equation (1) shown below. The exposure time is the time difference between t0 and tn.

  Thereby, the intensity image data in which the subject (including the object to be inspected) is photographed is generated in the same manner as the conventional camera photographing. Then, the intensity image superimposing unit 243 outputs the generated intensity image data to the image output unit 248.

  Temporally correlated image data is image data indicating changes in light intensity depending on time transition. That is, in the present embodiment, for each frame in time series order, the light intensity signal included in the frame is multiplied by the reference signal indicating the time transition, and the reference signal, the light intensity signal, and the time that is the multiplication result Temporal correlation image data is generated by generating a temporal correlation value frame composed of correlation values and superimposing a plurality of temporal correlation value frames.

  By the way, in order to detect abnormality of the object to be inspected using the time correlation image data, it is necessary to change the light intensity signal input to the image sensor 220 in synchronization with the reference signal. For this purpose, as described above, the illumination device 120 performs planar light irradiation that periodically gives temporal changes and spatial movement of the stripes via the screen 130.

In the present embodiment, two types of time correlation image data are generated. The reference signal may be a signal representing time transition, but in the present embodiment, a complex sine wave e ^−jωt is used. It is assumed that the angular frequency is ω and the time is t. The angular frequency ω is such that the complex sine wave e ^−jωt representing the reference signal correlates with one period of the above-described exposure time (in other words, the time required to generate the intensity image data and the time correlation image). It shall be set. In other words, the planar and dynamic light formed by the illumination unit 120 and the illumination unit such as the screen 130 is in a first period (time period) at each position on the surface (reflection surface) of the inspection object 150. And a distribution of increase or decrease in spatial irradiation intensity in a second period (spatial period) along at least one direction along the surface. When this planar light is reflected by the surface, it is complex-modulated according to the specifications of the surface (normal vector distribution, etc.). The time correlation camera 110 receives the light complex-modulated on the surface and performs quadrature detection (orthogonal demodulation) using the reference signal of the first period, thereby obtaining time correlation image data as a complex signal. By modulation / demodulation based on such complex time correlation image data, it is possible to detect features corresponding to the surface normal vector distribution.

The complex sine wave e ^−jωt can also be expressed as e ^−jωt = cos (ωt) −j · sin (ωt). Accordingly, each pixel value C (x, y) of the time correlation image data can be derived from the following equation (2).

  In this embodiment, in equation (2), two kinds of time correlation image data are divided into a pixel value C1 (x, y) representing a real part and a pixel value C 2 (x, y) representing an imaginary part. Generate

Therefore, the reference signal output unit 250 generates and outputs different reference signals to the first multiplier 244 and the second multiplier 246, respectively. Reference signal output section 250 of this embodiment outputs the first reference signal cosωt corresponding to the real part of the complex sine wave e ^-Jeiomegati the first multiplier 244, the imaginary part of the complex sine wave e ^-Jeiomegati The corresponding second reference signal sin ωt is output to the second multiplier 246. As described above, the reference signal output unit 250 according to the present embodiment describes an example in which two types of reference signals expressed as time functions of a sine wave and a cosine wave that form a Hilbert transform pair are described. It may be a reference signal that changes according to time transition such as a function.

Then, the first multiplier 244 ^calculates the real part cosωt of the complex sine wave e ^−jωt input from the reference signal output unit 250 for each light intensity signal of the frame in units of frames input from the reading unit 242. Multiply.

  The first correlation image superimposing unit 245 performs a process of superimposing the multiplication result of the first multiplier 244 on a pixel-by-pixel basis for a plurality of frames for an exposure time necessary for photographing. Thereby, each pixel value C1 (x, y) of the first time correlation image data is derived from the following equation (3).

The second multiplier 246 multiplies the light intensity signal of the frame input from the reading unit 242 by the imaginary part sin ^ωt of the complex sine wave e ^−jωt input from the reference signal output unit 250.

  The second correlation image superimposing unit 247 performs a process of superimposing the multiplication result of the second multiplier 246 on a pixel-by-pixel basis for a plurality of frames corresponding to the exposure time necessary for photographing. Thereby, each pixel value C2 (x, y) of the second time correlation image data is derived from the following equation (4).

  By performing the processing described above, two types of time correlation image data, in other words, time correlation image data having two degrees of freedom can be generated.

Also, the present embodiment does not limit the type of reference signal. For example, in this embodiment, two types of time-correlated image data of the real part and the imaginary part of the complex sine wave e ^−jωt are created, but two types of image data based on the light amplitude and the light phase are generated. May be.

  Note that the time correlation camera 110 of the present embodiment can create a plurality of systems as time correlation image data. Thereby, for example, when light in which stripes having a plurality of types of widths are combined is irradiated, two types of time correlation image data based on the real part and the imaginary part described above can be created for each stripe width. For this purpose, the time correlation camera 110 includes a combination of two multipliers and two correlation image superimposing units for a plurality of systems, and the reference signal output unit 250 has an angular frequency suitable for each system. It is possible to output the reference signal by ω.

  Then, the image output unit 248 outputs the two types of time correlation image data and the intensity image data to the PC 100. As a result, the PC 100 detects an abnormality of the object to be inspected using the two types of time correlation image data and the intensity image data. For that purpose, it is necessary to irradiate light to the subject.

  The illuminating device 120 of this embodiment irradiates the fringe pattern which moves at high speed. FIG. 4 is a diagram illustrating an example of a fringe pattern irradiated by the illumination device 120 of the present embodiment. In the example shown in FIG. 4, the stripe pattern is scrolled (moved) in the x direction. White areas correspond to bright areas corresponding to stripes, and black areas correspond to spaced areas (dark areas) corresponding to stripes. In the present embodiment, the portion to be the bright region of the screen 130 is an example of the light emitting unit.

  In the present embodiment, the fringe pattern irradiated by the illuminating device 120 is moved by one cycle with the exposure time when the time correlation camera 110 captures the intensity image data and the time correlation image data. Thereby, the illuminating device 120 gives the time change of the light intensity periodically by the spatial movement of the stripe pattern of the light intensity. In the present embodiment, the time for which the fringe pattern in FIG. 4 moves by one cycle corresponds to the exposure time, so that each pixel of the time-correlated image data relates to at least an intensity signal of light for one cycle of the fringe pattern. Information is embedded.

  As shown in FIG. 4, in the present embodiment, an example in which the illumination device 120 irradiates a stripe pattern based on a rectangular wave will be described, but a device other than the rectangular wave may be used. In addition, the use of a diffusing member that diffuses illumination light makes it possible to blur the bright and dark boundary region of the rectangular wave. The screen 130 is an example of a diffusion member.

  In the present embodiment, a stripe pattern irradiated by the illumination device 120 is represented as A (1 + cos (ωt + kx), that is, the stripe pattern includes a plurality of stripes repeatedly (periodically). The intensity of the light applied to can be adjusted between 0 and 2 A, and is the light phase kx, where k is the wave number of the stripes, and x is the direction in which the phase changes.

  The fundamental frequency component of the light intensity signal f (x, y, t) of each pixel in the frame can be expressed as the following equation (5). As shown in equation (5), the light and dark of the stripes change in the x direction.

f (x, y, t) = A (1 + cos (ωt + kx))
= A + A / 2 {e ^{j (ωt + kx)} + e- ^{j (ωt + kx)} } (5)

  As shown in Expression (5), the intensity signal of the fringe pattern irradiated by the illumination device 120 can be considered as a complex number.

  Then, the light from the illumination device 120 is reflected and input to the image sensor 220 from the subject (including the object to be inspected).

  Therefore, the light intensity signal G (x, y, t) input to the image sensor 220 can be used as the light intensity signal f (x, y, t) of each pixel of the frame when the illumination device 120 is irradiated. Therefore, when Expression (5) is substituted into Expression (1) for deriving intensity image data, Expression (6) can be derived. It is assumed that the phase kx.

  From Expression (6), it can be confirmed that each pixel of the intensity image data is input with a value obtained by multiplying the exposure time T by the intermediate value A of the intensity of the light output from the illumination device 120. Further, when Expression (5) is substituted into Expression (2) for deriving time correlation image data, Expression (7) can be derived. Note that AT / 2 is an amplitude and kx is a phase.

  Thereby, the time correlation image data shown by the complex number shown by Formula (7) can be substituted with two types of time correlation image data mentioned above. That is, the temporal correlation image data composed of the real part and the imaginary part described above includes the phase change and the amplitude change in the light intensity change irradiated to the test object. In other words, the PC 100 according to the present embodiment can detect the phase change of the light emitted from the illumination device 120 and the light amplitude change based on the two types of time correlation image data. Therefore, the PC 100 according to the present embodiment, based on the time correlation image data and the intensity image data, amplitude image data representing the amplitude of light entering each pixel and phase image data representing the phase change of light entering each pixel. And generate.

  Furthermore, the PC 100 detects an abnormality of the subject based on the generated amplitude image data and phase image data.

  By the way, when the abnormality based on unevenness has arisen in the surface shape of a to-be-inspected object, the change corresponding to the abnormality has arisen in distribution of the normal line vector of the surface of a to-be-inspected object. Further, when an abnormality that absorbs light occurs on the surface of the object to be inspected, the intensity of the reflected light changes. A change in the normal vector distribution is detected as at least one of a phase change and an amplitude change of light. Thus, in the present embodiment, using the time correlation image data and the intensity image data, at least one of the light phase change and the amplitude change corresponding to the change in the normal vector distribution is detected. This makes it possible to detect surface shape anomalies. Next, the relationship between the abnormality of the inspected object, the normal vector, and the phase change or amplitude change of light will be described.

  FIG. 5 is a diagram illustrating a first detection example of abnormality of an object to be inspected by the time correlation camera 110 according to the embodiment. In the example shown in FIG. 5, it is assumed that the inspected object 500 has a projecting shape abnormality 501. In this situation, it can be confirmed that the normal vectors 521, 522 and 523 point in different directions in the vicinity of the point 502 of the abnormality 501. Then, when the normal vectors 521, 522, and 523 point in different directions, diffusion (for example, light 511, 512, and 513) occurs in the light reflected from the abnormality 501, and the image sensor 220 of the time correlation camera 110 The width 503 of the stripe pattern entering any pixel 531 of the

  FIG. 6 is a diagram showing an example of the amplitude of light that changes in accordance with the abnormality 501 shown in FIG. In the example shown in FIG. 6, the amplitude of light is divided into a real part (Re) and an imaginary part (Im) to be represented on a two-dimensional plane. In FIG. 6, the light amplitudes 611, 612, and 613 corresponding to the lights 511, 512, and 513 in FIG. The light amplitudes 611, 612, and 613 cancel each other, and light having an amplitude 621 is incident on the arbitrary pixel 531 of the image sensor 220.

  Therefore, in the situation shown in FIG. 6, it can be confirmed that the amplitude is small in the region where the abnormality 501 of the inspection object 500 is imaged. In other words, when there is an area that is darker than the surrounding area in the amplitude image data that shows the amplitude change, it can be inferred that the amplitudes of the light cancel each other out in the area. It can be determined that an abnormality 501 has occurred at the position of the corresponding inspection object 500.

  The inspection system 1 according to the present embodiment is not limited to the case where the inclination changes steeply like the abnormality 501 in FIG. FIG. 7 is a diagram illustrating a second detection example of the abnormality of the inspected object by the time correlation camera 110 according to the embodiment. In the example shown in FIG. 7, the surface of the object under inspection becomes flat (in other words, the normals are parallel) in the normal case, but a gentle slope 701 is generated in the object under inspection 700. In such a situation, the normal vectors 721, 722, and 723 on the gradient 701 also change gently. Therefore, the lights 711, 712, and 713 input to the image sensor 220 also gradually shift. In the example shown in FIG. 7, since the cancellation of the light amplitude does not occur due to the gentle slope 701, the light amplitude as shown in FIGS. 5 and 6 hardly changes. However, although the light originally projected from the illumination device 120 and the screen 130 should enter the image sensor as it is, the light projected from the illumination device 120 and the screen 130 is parallel because of the gentle gradient 701. A phase change occurs in the light because it does not enter the image sensor. Therefore, by detecting the difference between the phase change of the light and the surroundings, it is possible to detect an abnormality due to the gentle gradient 701 as shown in FIG.

  In addition, there may be an abnormality other than the surface shape of the inspection object (in other words, the distribution of the normal vector of the inspection object). FIG. 8 is a diagram illustrating a third example of detection of abnormality of an object to be inspected by the time correlation camera 110 according to the embodiment. In the example shown in FIG. 8, since the dirt 801 adheres to the inspection object 800, the light emitted from the illumination device 120 is absorbed or diffusely reflected, and the dirt 801 of the time correlation camera 110 is photographed. This shows an example in which light hardly changes in intensity in an arbitrary pixel region. In other words, in an arbitrary pixel area in which the dirt 801 is photographed, the light intensity is phase-cancelled, the vibration component is canceled, and an example in which the brightness is almost DC direct is shown.

  In such a case, in the pixel region where the dirt 801 is imaged, there is almost no light amplitude, and therefore when the amplitude image data is displayed, a region darker than the surroundings is generated. Therefore, it can be estimated that there is an abnormality 801 such as dirt at the position of the inspection object 800 corresponding to the region.

  As described above, in the present embodiment, it is possible to estimate that the object to be inspected is abnormal by detecting the change in the amplitude of the light and the change in the phase of the light based on the time correlation image data.

  Returning to FIG. 1, the PC 100 will be described. The PC 100 controls the entire detection system. The PC 100 includes a movement mechanism control unit 101, a light emission control unit 102, a control unit 103, and a storage unit 109. The storage unit 109 stores data used for arithmetic processing, arithmetic processing results, and the like.

  The movement mechanism control unit 101 controls the movement mechanism 140 in order to change the surface of the object 150 to be imaged by the time correlation camera 110. The moving mechanism 140 is, for example, a robot arm. In the present embodiment, in the PC 100, a plurality of surfaces to be imaged of the inspection object 150 are set. Then, each time the time correlation camera 110 finishes capturing the object 150, the moving mechanism control unit 101 can capture the surface on which the time correlation camera 110 is set according to the setting. The inspection body 150 is moved. In the present embodiment, the moving mechanism 140 is moved each time shooting is completed, and the present invention is not limited to repeating stopping before shooting starts, and the moving mechanism 140 may be driven continuously. . The moving mechanism 140 can also be referred to as a conveyance unit, a moving unit, a gripping unit, a position changing unit, a posture changing unit, and the like.

  The light emission control unit 102 outputs a fringe pattern irradiated by the illumination device 120 in order to inspect the inspection object 150. The light emission control unit 102 of the present embodiment transfers at least three or more stripe patterns to the illumination device 120 and instructs the illumination device 120 to switch and display the stripe patterns during the exposure time. The light emission control unit 102 may also be referred to as a lighting control unit.

  FIG. 9 is a diagram illustrating an example of a fringe pattern output from the light emission control unit 102 to the illumination device 120. In accordance with the rectangular wave shown in FIG. 9B, the light emission control unit 102 performs control so that the stripe pattern in which the black region and the white region shown in FIG. 9A are set is output.

  The interval of stripes for each stripe pattern to be irradiated in the present embodiment is set according to the size of the abnormality (defect) to be detected, and the detailed description is omitted here.

  In addition, the angular frequency ω of the rectangular wave for outputting the fringe pattern is set to the same value as the angular frequency ω of the reference signal.

  As shown in FIG. 9, the fringe pattern output from the light emission control unit 102 can be shown as a rectangular wave, but blurs the border area of the fringe pattern through the screen 130 (diffusing member). It is possible to approximate a sine wave by gradual (dulling) the change in the intensity of light at the boundary between the bright region (striped region) and the dark region (interval region) in the pattern. FIG. 10 is a view showing an example of the shape of a wave representing a stripe pattern after passing through the screen 130. As shown in FIG. As shown in FIG. 10, the measurement accuracy can be improved by the wave shape approaching a sine wave. Further, a gray region in which the brightness changes in multiple steps may be added to the stripe, or a gradation may be given. Further, a stripe pattern including color stripes may be used.

  Returning to FIG. 1, the control unit 103 includes an amplitude-phase image generation unit 104 and an abnormality detection processing unit 105, and by intensity image data input from the time correlation camera 110 and time correlation image data, A process for calculating a feature corresponding to the distribution of the normal vector on the inspection surface of the inspection object 150 and detecting an abnormality based on a difference from the surroundings is performed. In the present embodiment, in order to perform the inspection, two types of real number and imaginary part of complex number correlation image data are used instead of time correlation image data (referred to as complex time correlation image data) indicated by complex numbers. Time correlated image data from the time correlated camera 110. The amplitude-phase image generation unit 104 (control unit 103) is an example of an arithmetic processing unit. The abnormality detection processing unit 105 is an example of an abnormality determination unit.

  The amplitude-phase image generation unit 104 generates amplitude image data and phase image data based on the intensity image data input from the time correlation camera 110 and the time correlation image data.

  The amplitude image data is image data representing the amplitude of light entering each pixel. The phase image data is image data representing the phase of light entering each pixel.

  Although the present embodiment does not limit the calculation method of the amplitude image data, for example, the amplitude-phase image generation unit 104 has pixel values C1 (x, y) and C2 (x, From y), each pixel value F (x, y) of the amplitude image data can be derived using Equation (8).

  Then, in the present embodiment, it is possible to determine whether there is an area in which an abnormality has occurred, based on the pixel value (amplitude) of the amplitude image data and the pixel value of the intensity image data. For example, in a region where the value obtained by dividing the pixel value (AT) of the intensity image data by 2 and the amplitude of the amplitude image data (it becomes AT / 2 when no cancellation occurs), an abnormality occurs I can guess that it is not. On the other hand, it can be presumed that the amplitude cancellation occurs in the non-matching region. The specific method will be described later.

  Similarly, the amplitude-phase image generation unit 104 uses the pixel values C1 (x, y) and C2 (x, y) to calculate each pixel value P (x, y) of the phase image data using Equation (9). Can be derived.

  The abnormality detection processing unit 105 is a feature corresponding to the distribution of the normal vector on the inspection symmetry plane based on the amplitude image data and the phase image data generated by the amplitude-phase image generation unit 104, and is based on a difference from the surroundings. , Detects a feature related to the abnormality of the test object 150. In the present embodiment, an example in which the amplitude distribution of the complex time correlation image is used as the feature corresponding to the distribution of the normal vector will be described. The distribution of the amplitude of the complex time correlation image is data indicating the distribution of the amplitude of each pixel of the complex time correlation image, and corresponds to amplitude image data.

  Next, the abnormality detection processing based on the amplitude in the abnormality detection processing unit 105 of the present embodiment will be described. FIG. 11 is a flowchart showing the procedure of the process in the abnormality detection processing unit 105 of this embodiment.

  First, the abnormality detection processing unit 105 determines the average amplitude of the N × N region from the light amplitude value (representing pixel value) stored in each pixel of the amplitude image data, with the pixel as a reference (for example, the center). The values are subtracted (step S1101) to generate average difference image data of amplitude. The average difference image data of the amplitude corresponds to the gradient of the amplitude. The integer N is assumed to be set to an appropriate value according to the embodiment.

  Next, the abnormality detection processing unit 105 performs mask processing on the average difference image data of the amplitude generated by the subtraction using a predetermined threshold value of the amplitude (step S1102).

  Further, the abnormality detection processing unit 105 calculates a standard deviation for each pixel within the mask area of the average difference image data (step S1103). In the present embodiment, a method based on the standard deviation will be described. However, the method is not limited to the case where the standard deviation is used. For example, an average value or the like may be used.

  Then, the abnormality detection processing unit 105 detects a pixel whose amplitude pixel value obtained by subtracting the average is smaller than −4.5σ (σ: standard deviation) as a region having an abnormality (defect) (step S1104).

  By the processing procedure described above, an abnormality of the object to be inspected can be detected from the amplitude value of each pixel (in other words, the amplitude distribution). However, the present embodiment is not limited to the detection of an anomaly from the distribution of the amplitude of the complex time correlation image. The gradient of the distribution of the phase may be used as a feature corresponding to the distribution of the normal vector of the test symmetry plane. An example using the gradient of the phase distribution will be described next.

  Next, abnormality detection processing based on the phase in the abnormality detection processing unit 105 of the present embodiment will be described. FIG. 12 is a flowchart showing the procedure of the process in the abnormality detection processing unit 105 of this embodiment.

  First, the abnormality detection processing unit 105 subtracts the average phase value of the N × N region from the phase value of the light of each pixel of the phase image data (a pixel value representing the pixel value) using the pixel as a reference (for example, the center). (Step S1201), phase average difference image data is generated. The phase average difference image data corresponds to the phase gradient.

  Next, the abnormality detection processing unit 105 compares the magnitude (absolute value) of the average difference image data of the phase generated by the subtraction with a threshold value, and determines pixels whose average difference image data size is equal to or greater than the threshold value. Then, it is detected as an abnormal (defect) pixel (step S1202).

  Based on the detection result of S1202, the abnormality detection processing unit 105 can determine the unevenness based on the sign of the average difference image data, that is, the magnitude relationship between the phase value of the pixel and the average phase value (step S1203). Which of the pixel phase value and the average phase value is convex depends on the setting of each part, but the unevenness differs if the magnitude relationship is different.

  An abnormality can be detected from the gradient of the phase distribution obtained by another method. For example, as another method, the abnormality detection processing unit 105 determines whether the difference between the average vector of the N × N region of the normalized time correlation image data and the normalized vector of each pixel is a threshold value. If it is larger than that, it can be detected as a pixel having an abnormality (defect). Further, the abnormality of the object to be inspected may be detected based on information corresponding to the phase distribution, not limited to the gradient of the phase distribution.

  Next, abnormality detection processing based on the amplitude and the intensity in the abnormality detection processing unit 105 of the present embodiment will be described. FIG. 13 is a flowchart showing the procedure of the process in the abnormality detection processing unit 105 of this embodiment.

  First, the abnormality detection processing unit 105 uses the following equation (100) for each pixel from the time correlation image data and the intensity image data, and uses the following equation (100) to represent the amplitude (representing pixel value) C (x, y) (equation ( 7) Calculate a ratio R (x, y) between the reference (the reference) and the intensity (pixel value representing the reference) G (x, y) (see the equation (6)) (step S1301).

R (x, y) = C (x, y) / G (x, y) (100)

  Next, the abnormality detection processing unit 105 compares the ratio R (x, y) with a threshold value, and sets a pixel having a ratio R (x, y) value equal to or less than the corresponding threshold value to a pixel having an abnormality (defect). Is detected (step S1302). In addition, the abnormality detection processing unit 105 compares the ratio R (x, y) with a threshold value, and determines that a pixel whose ratio R (x, y) is equal to or greater than another corresponding threshold value is uneven (dirt or the like). It is detected as a certain pixel (step S1303). When the cancellation of the amplitude (attenuation) becomes noticeable due to the abnormal distribution of the normal vector, the amplitude is greatly reduced compared to the strength. On the other hand, although there is not so much abnormality in the normal vector distribution, when the light absorption becomes significant due to dirt on the surface of the object 150 to be inspected, the intensity is greatly reduced compared to the amplitude. Therefore, the abnormality detection processing unit 105 can detect the abnormality type in steps S1302 and S1303.

  Next, an inspection process for an object to be inspected in the inspection system of the present embodiment will be described. FIG. 14 is a flowchart showing the procedure of the above-described process in the inspection system of the present embodiment. It is assumed that the inspected object 150 is already fixed to the moving mechanism 140 and is disposed at the initial position of the inspection.

  The PC 100 of this embodiment outputs a fringe pattern for inspecting the object to be inspected to the illumination device 120 (step S1401).

  The lighting device 120 stores the fringe pattern input from the PC 100 (step S1421). And the illuminating device 120 displays the stored fringe pattern so that it may change according to a time transition (step S1422). Note that the conditions under which the illuminating device 120 starts display are not limited when the fringe pattern is stored, and may be, for example, when the inspector performs a start operation on the illuminating device 120.

  Then, the control unit 103 of the PC 100 transmits a shooting start instruction to the time correlation camera 110 (step S1402).

  Next, the time correlation camera 110 starts imaging for an area including the inspection object 150 in accordance with the transmitted imaging instruction (step S1411). Next, the control unit 240 of the time correlation camera 110 generates intensity image data and time correlation image data (step S1412). Then, the control unit 240 of the time correlation camera 110 outputs the intensity image data and the time correlation image data to the PC 100 (step S1413).

  The control unit 103 of the PC 100 receives the intensity image data and the time correlation image data (step S1403). Then, the amplitude-phase image generation unit 104 generates amplitude image data and phase image data from the received intensity image data and time correlation image data (step S1404).

  Then, the abnormality detection processing unit 105 performs abnormality detection control of the test object based on the amplitude image data and the phase image data (step S1405). Then, the abnormality detection processing unit 105 outputs the abnormality detection result to a display device (not shown) included in the PC 100 (step S1406).

  As an output example of the abnormality detection result, the intensity image data is displayed, and an area of the intensity image data corresponding to the area where the abnormality is detected based on the amplitude image data and the phase image data is displayed. It is conceivable to display decoration so that it can be recognized. Further, the output is not limited to visual output, and it may be output that an abnormality has been detected by voice or the like.

  The control unit 103 determines whether or not the inspection of the object to be inspected is completed (step S1407). If it is determined that the inspection has not been completed (step S1407: No), the moving mechanism control unit 101 captures the surface of the inspection object to be inspected with the time correlation camera 110 in accordance with a predetermined setting. Movement control of the arm is performed (step S1408). After the arm movement control is completed, the control unit 103 transmits an imaging start instruction to the time correlation camera 110 again (step S1402).

  On the other hand, if the control unit 103 determines that the inspection of the object to be inspected has ended (step S1407: Yes), the control unit 103 outputs an end instruction to the time correlation camera 110 (step S1409) and ends the process.

  Then, the time correlation camera 110 determines whether an end instruction has been received (step S1414). If an end instruction has not been received (step S1414: NO), the processing is performed again from step S1411. On the other hand, if the end instruction has been received (step S1414: YES), the process ends.

  Note that the inspecting process of the illumination device 120 may be performed by an inspector, or may be ended in accordance with an instruction from another configuration.

  Further, in the present embodiment, an example has been described in which intensity image data generated using the time correlation camera 110 and time correlation image data are generated. However, the present invention is not limited to the use of the time correlation camera 110 for generating the intensity image data and the time correlation image data, and a time correlation camera that can be realized by analog processing or an operation equivalent thereto. An imaging system may be used. For example, image data generated by a normal digital still camera is output, and the information processing apparatus superimposes a reference signal using the image data generated by the digital still camera as frame image data, thereby generating time-correlated image data. The time-correlated image data may be generated using a digital camera that may generate a reference signal in a light intensity signal in an image sensor.

(Modification 1)
In this embodiment, an example in which a feature related to an abnormality is detected based on a difference from the surroundings has been described, but the present invention is not limited to detecting the feature based on a difference from the surroundings. The feature may be detected based on the difference with data (reference data, for example, time correlation data, amplitude image data, phase image data, etc.). In this case, alignment and synchronization of spatial phase modulation illumination (fringe pattern) is required in the case of reference data.

  In this modification, the abnormality detection processing unit 105 stores the amplitude image data and phase image data obtained from the reference surface, the amplitude image data and phase image data of the inspected object 150, which are stored in the storage unit 109 in advance. Are compared to determine whether there is a difference greater than or equal to a predetermined standard for any one or more of the light amplitude and the light phase between the surface of the inspection object 150 and the reference surface.

  This modification is an example in which the inspection system having the same configuration as that of the embodiment is used and the surface of a normal inspection object is used as the reference surface.

  While the illumination device 120 irradiates a pattern via the screen 130, the time correlation camera 110 images the surface of a normal object to be inspected and generates time correlation image data. Then, the PC 100 receives the time correlation image data generated by the time correlation camera 110, generates amplitude image data and phase image data, and stores the amplitude image data and phase image data in the storage unit 109 of the PC 100. . Then, the time correlation camera 110 captures an object to be inspected for determining whether or not an abnormality has occurred, and generates time correlation image data. Then, the PC 100 generates the amplitude image data and the phase image data from the time correlation image data, and then compares the amplitude image data and the phase image data with the amplitude image data and the phase image data of the normal inspection object stored in the storage unit 109. At that time, the comparison result of the amplitude image data and phase image data of a normal inspection object and the amplitude image data and phase image data of the inspection object to be inspected is data indicating characteristics for detecting an abnormality. Output. Then, when the feature for detecting an abnormality is equal to or greater than the predetermined reference, it can be estimated that the inspection object 150 is abnormal.

  Thereby, in this modification, it can be determined whether there is a difference from the surface of the normal object to be inspected, in other words, whether there is an abnormality on the surface of the object to be inspected. In addition, since the comparison method of amplitude image data and phase image data may use what kind of method, description is abbreviate | omitted.

  Furthermore, in the present modification, an example of outputting data indicating a feature for detecting an abnormality based on the difference from the reference surface has been described. However, the difference from the reference surface and the difference from the surroundings shown in the embodiment , May be combined to calculate a feature for detecting an abnormality. The method to be combined may use any method, so the description will be omitted.

(Modification 2)
In the embodiment, an example has been described in which the stripe pattern is moved in the x direction to detect an abnormality (defect) of the inspection object. However, when an abnormality (defect) in which the distribution of the normal changes sharply in the y direction perpendicular to the x direction occurs in the inspection object, the stripe pattern is moved in the y direction rather than moving the stripe pattern in the x direction It may be easier to detect defects. Therefore, in the modification, an example in which the stripe pattern moving in the x direction and the stripe pattern moving in the y direction are alternately switched will be described.

  The light emission control unit 102 of this modification switches the fringe pattern output to the illumination device 120 at every predetermined time interval. Thereby, the illuminating device 120 outputs the several stripe pattern extended in the different direction with respect to one test | inspection surface.

  FIG. 15 is a diagram illustrating a switching example of the fringe pattern output from the light emission control unit 102 of the present modification. In FIG. 15A, the light emission control unit 102 causes the stripe pattern displayed by the illumination device 120 to transition in the x direction. Thereafter, as shown in (B), the light emission control unit 102 causes the stripe pattern displayed by the illumination device 120 to transition in the y direction.

  And the control part 103 of PC100 performed abnormality detection based on the time correlation image data obtained from the stripe pattern irradiation of FIG. 15 (A), and obtained from the stripe pattern irradiation of FIG. 15 (B). Abnormality detection is performed based on the time correlation image data.

  FIG. 16 is a diagram illustrating an example in which the light emission control unit 102 of the present modification irradiates the surface including the abnormality (defect) 1601 with a stripe pattern. In the example shown in FIG. 16, an abnormality (defect) 1601 extends in the x direction. In this case, the light emission control unit 102 sets the fringe pattern to move in the y direction that intersects the x direction, in other words, the direction that intersects the longitudinal direction of the abnormality (defect) 1601. With this setting, detection accuracy can be improved.

  FIG. 17 is a diagram showing the relationship between the abnormality (defect) 1701 and the stripe pattern on the illumination device 120 when the stripe pattern is changed in the y direction, in other words, in the direction orthogonal to the longitudinal direction of the defect 1701. . As shown in FIG. 17, when an abnormality (defect) 1701 having a narrow width in the y direction and a longitudinal direction in the x direction intersecting the y direction occurs, the light emitted from the illumination device 120 is In the y direction that intersects the x direction, the cancellation of the amplitude of light increases. Therefore, the PC 100 can detect the abnormality (defect) from the amplitude image data corresponding to the stripe pattern moved in the y direction.

  In the inspection system of this modification, when the longitudinal direction of the defect generated in the inspection object is random, the fringe pattern is displayed in a plurality of directions (for example, the x direction and the y direction crossing the x direction). Thus, the defect can be detected regardless of the shape of the defect, and the detection accuracy of the abnormality (defect) can be improved. Further, by projecting a fringe pattern that matches the shape of the abnormality, the abnormality detection accuracy can be improved.

(Modification 3)
Moreover, the modification 2 mentioned above does not restrict | limit to the method of switching a fringe pattern, when performing the abnormality detection of ax direction, and the abnormality detection of ay direction. Therefore, in the third modification, an example will be described in which the stripe pattern output to the illumination device 120 by the light emission control unit 102 is simultaneously moved in the x direction and the y direction.

  FIG. 18 is a diagram showing an example of a fringe pattern which the light emission control unit 102 of this modification outputs to the illumination device 120. As shown in FIG. In the example shown in FIG. 18, the light emission control unit 102 moves the stripe pattern in the direction 1801.

  The stripe pattern shown in FIG. 18 includes a stripe pattern with one period 1802 in the x direction and a stripe pattern with one period 1803 in the y direction. That is, the stripe pattern shown in FIG. 18 has a plurality of stripes extending in the cross direction different in width. In addition, it is necessary to make the width of the stripe pattern in the x direction different from the width of the stripe pattern in the y direction. Thereby, when generating the time correlation image data corresponding to the x direction and the time correlation image data corresponding to the y direction, the corresponding reference signals can be made different. In addition, since the period (frequency) of the change in the intensity of light due to the stripe pattern may be changed, the moving speed of the stripe pattern (stripe) may be changed instead of changing the width of the stripe.

  Then, the time correlation camera 110 generates time correlation image data corresponding to the stripe pattern in the x direction based on the reference signal corresponding to the stripe pattern in the x direction, and based on the reference signal corresponding to the stripe pattern in the y direction. Thus, time correlation image data corresponding to the stripe pattern in the y direction is generated. After that, the control unit 103 of the PC 100 detects an abnormality based on the time correlation image data corresponding to the stripe pattern in the x direction, and then detects an abnormality based on the time correlation image data corresponding to the stripe pattern in the y direction. I do. Thereby, in this modification, it becomes possible to detect regardless of the direction in which the defect occurs, and the detection accuracy of the abnormality (defect) can be improved.

<Multiple imaging areas and displacement correction>
In FIG. 19, a plurality of imaging regions P1 to P14 set on the inspection surface 150a of one inspection object 150 are illustrated. As described above, a plurality of imaging regions P1 to P14 can be set in one inspection surface 150a. The imaging areas P1 to P14 are respectively imaged and inspected by the inspection system 1. The moving mechanism 140 moves the inspected object 150 to a position and posture for performing any one of the plurality of imaging regions P1 to P14. The moving mechanism 140 moves the device under test 150 so that the imaging region P1, the imaging region P2, the imaging region P3,..., The imaging region P14 are switched in this order. The imaging regions P1 to P14 can also be referred to as inspection regions, inspection ranges, inspection positions, and the like. In the present embodiment, as an example, the imaging region is changed by moving the inspected object 150 by the moving mechanism 140, but the imaging system 1 (the time correlation camera 110, the illumination device 120, the screen 130, etc.) is moved. Thus, the imaging area may be changed, or the imaging area may be changed by moving both.

  As is clear from FIG. 19, the movement locus L of the imaging regions P <b> 1 to P <b> 14 moves spirally so as to go around the center of gravity C of the object 150 to be inspected. For this reason, when switching an imaging region, it becomes possible to move the to-be-inspected object 150 by the minimum moving amount (distance and angle) by the moving mechanism 140. Thus, according to the present embodiment, the time required for imaging the plurality of imaging regions P1 to P14 can be further shortened. The movement trajectory L of the imaging regions P1 to P14 does not have to be in a spiral shape around the center of gravity C over the entire section, and at least a part of the entire movement trajectory L is the center of gravity C The amount of movement can be reduced for the section if it is round or spiral. The movement locus L may include a section in which the imaging region moves in a zigzag manner (while reciprocating). The center of gravity C may be the center of gravity (center) on the viewing angle. The inspected object 150 can also be referred to as an inspection object or an inspection object.

  Further, as shown in FIG. 19, imaging regions P1 to P14 having different sizes and shapes are set on the inspection surface 150a. The imaging areas P1 to P14 are set so that, for example, the normal vector difference (angle difference) of the inspection surface 150a in each of the imaging areas P1 to P14 is a predetermined value (for example, within a few degrees). . By such setting, the accuracy of inspection is likely to be improved.

  Further, as illustrated in FIG. 1, the control unit 103 includes a deviation correction unit 106. The deviation correction unit 106 corrects the deviation of the position and posture (tilt and direction) of the inspection surface of the inspection object 150 (inspection object) based on the image captured by the imaging unit such as the time correlation camera 110.

  Further, as shown in FIG. 1, the PC 100 includes a storage unit 109. The storage unit 109 stores, for example, values of parameters necessary for the arithmetic processing in the deviation correction unit 106. The parameter is, for example, a numerical value, a table, a map, a function (function coefficient), or the like.

  Specifically, the shift correction unit 106 performs inspection by changing the luminance values at a plurality of (for example, two) reference points r1 and r2 illustrated in FIG. 19 when the angle of the inspection surface 150a is changed. The position and inclination of the surface 150a are corrected.

  FIG. 20 shows an example of a procedure of arithmetic processing related to deviation correction. First, at the correction timing (Yes in S11), the control unit 103 controls the time correlation camera 110 and the illumination device 120 to image the inspection surface 150a of the inspection object 150 (S12), and a result of imaging To obtain the luminance values of the reference points r1 and r2 (S13). These S12 and S13 are executed for a plurality of angles obtained by the control of the moving mechanism 140. In the example of FIG. 19, for example, S12 and S13 are performed for a plurality of angles around the Z axis.

  The reference points r1 and r2 are separated from each other in the X direction in which the stripe pattern moves. By the change in the angle of the inspection surface 150a around the Z axis, the positions of the reference points r1 and r2 change in the Y direction, and the direction of the normal vector at the reference points r1 and r2, that is, the reflection angle of light changes. Accordingly, the luminance values of the reference points r1 and r2 in the image (intensity image) captured by the time correlation camera 110 change according to the change in the angle of the inspection surface 150a around the Z axis.

  FIG. 21 shows an example of the correlation between the angle around the Z-axis of the inspection surface 150a at the reference point r1 and the luminance value in a series of measurements at a plurality of angles, and FIG. An example of the correlation between the angle around the Z axis of the inspection surface 150a at the reference point r2 and the luminance value is shown. As shown in FIG. 21, the luminance value of the reflected light at the reference point r1 exhibits a bell-shaped characteristic that peaks at an angle θr1. As shown in FIG. 22, the luminance value of the reflected light at the reference point r2 exhibits a bell-shaped characteristic that peaks at the angle θr2. As in the case of FIGS. 21 and 22, for the reference point r1, while the luminance value is maximized at an angle θr1 within a predetermined angle range Rr1, is the maximum value of the luminance value at the angle θr1 the same as the threshold value Th? Alternatively, for the reference point r2, the luminance value is maximized at the angle θr2 within the predetermined angle range Rr2, and the maximum value of the luminance value at the angle θr2 is equal to or larger than the threshold value Th In this case, the shift correction unit 106 does not perform shift correction assuming that the shift is within the allowable range. In this case, the deviation correction unit 106 calculates the correction amount as 0 (S14). In this case, the positional deviation correction of S15 is not executed. Alternatively, a positional deviation correction with a correction amount of 0 may be executed.

  FIG. 23 shows another correlation between the angle around the Z-axis of the inspection surface 150a at the reference point r1 and the luminance value in a series of measurements at a plurality of angles with a sample different from FIGS. An example is shown, and FIG. 24 shows an example of the correlation between the angle around the Z axis of the inspection surface 150a at the reference point r2 and the luminance value in the measurement. As shown in FIG. 23, the luminance value of the reflected light at the reference point r1 exhibits a bell-shaped characteristic that peaks at the angle θr1. As shown in FIG. 24, the luminance value of the reflected light at the reference point r2 exhibits a bell-shaped characteristic that peaks at the angle θr2. As in the case of FIGS. 23 and 24, for the reference point r1, although the luminance value is maximum at the angle θr1 within the predetermined angle range Rr1, the maximum value of the luminance value at the angle θr1 is obtained from the threshold value Th. Although the luminance value is maximum at an angle θr2 within the predetermined angle range Rr2 for the reference point r2 which is low or the maximum value of the luminance value at the angle θr2 is lower than the threshold value Th, The deviation correction unit 106 performs deviation correction assuming that the deviation exceeds the allowable range. In this case, the deviation correction unit 106 calculates a correction amount according to the luminance value of the reference point r1 and the luminance value of the reference point r2 (S14). The correction amount corresponding to the magnitude of the luminance values of the reference points r1 and r2 is experimentally acquired in advance, and stored in the storage unit 109 as numerical values, a table, a map, a function (function coefficient), and the like. Yes. Therefore, the shift correction unit 106 can acquire (calculate) a correction amount corresponding to the luminance values of the reference points r1 and r2 with reference to the storage unit 109. In this case, the movement mechanism control unit 101 moves the movement mechanism 140 according to the calculated correction amount, and corrects the positional deviation (S15).

  Here, if the posture is corrected so that the luminance value of the reflected light of only one reference point is increased, the allowable range of the luminance value of the reflected light at the one reference point is set. It can be considered that the object 150 is in a posture in which the luminance value of the reflected light does not increase at each point in the other region of the inspection surface 150a. In this respect, in the present embodiment, the positional deviation can be further reduced by correcting the posture of the object 150 so that the luminance values of the reflected light at the at least two reference points are within a predetermined range. Two or more reference points may be used. In the above example, only the correction of the positional deviation around the Z axis has been described. However, the correction can be similarly performed for other axes. For example, when correction based on the luminance values of the reflected light of two reference points is performed, while changing the rotational attitude of the inspection object 150 around the axis passing through the two reference points, You may correct | amend the position shift of the to-be-inspected object 150 so that the luminance value of reflected light may be in a predetermined range. If it carries out like this, the to-be-inspected object 150 can be positioned more accurately. In the above-described method, typically, for example, the fringe pattern extends along the Z direction, the fringe pattern moves in the direction orthogonal to the Z direction, and the two reference points move in the direction in which the fringe pattern moves. It is set to be separated.

  As described above, in the present embodiment, the movement trajectories L of the plurality of imaging regions P1 to P14 set on the inspection surface 150a move around the center of gravity C of the inspection object 150 (inspection object). Moving in a spiral. For this reason, when switching an imaging region, it becomes possible to move the to-be-inspected object 150 by the minimum moving amount (distance and angle) by the moving mechanism 140. Thus, according to the present embodiment, the time required for imaging the plurality of imaging regions P1 to P14 can be further shortened.

  Further, in the present embodiment, the imaging areas P1 to P14 include a plurality of imaging areas having different sizes and shapes. The imaging areas P1 to P14 are set so that, for example, the normal vector difference (angle difference) of the inspection surface 150a in each of the imaging areas P1 to P14 is a predetermined value (for example, within a few degrees). . Therefore, according to the present embodiment, the accuracy of inspection is easily improved.

  In the present embodiment, the shift correction unit 106 changes the luminance value at a plurality of (for example, two) reference points r1 and r2 illustrated in FIG. 19 when, for example, the angle of the inspection surface 150a is changed. Thus, the position and inclination deviation of the inspection surface 150a are corrected. Therefore, according to the present embodiment, the accuracy of inspection is easily improved. In addition, by correcting the deviation based on the change in the luminance value at the plurality of reference points r1 and r2, the accuracy of the inspection can be compared with the case of correcting the deviation based on the change in the luminance value at one reference point. Is easier to improve.

  The inspection program executed by the PC 100 according to the embodiment described above is a file in an installable format or an executable format, and is a computer such as a CD-ROM, a flexible disk (FD), a CD-R, or a DVD (Digital Versatile Disk). It is recorded on a readable recording medium and provided.

  Further, the inspection program executed by the PC 100 of the above-described embodiment may be provided by being stored on a computer connected to a network such as the Internet and downloaded via the network. Moreover, you may comprise so that the test | inspection program and calibration program which are performed with PC100 of embodiment mentioned above may be provided or distributed via networks, such as the internet.

  Although some embodiments and modifications of the present invention have been described, these embodiments and modifications are presented as examples and are not intended to limit the scope of the invention. These novel embodiments and modifications can be implemented in various other forms, and various omissions, replacements, and changes can be made without departing from the spirit of the invention. These embodiments and modifications thereof are included in the scope and gist of the invention, and are included in the invention described in the claims and equivalents thereof.

DESCRIPTION OF SYMBOLS 1 ... Inspection system, 104 ... Amplitude-phase image generation part (arithmetic processing part), 106 ... Deviation correction part, 110 ... Time correlation camera (imaging part, time correlation image generation part), 120 ... Illuminating device (illumination part), 130: screen (illumination unit, light emission unit), 140: movement mechanism, 150: inspection object (inspection object), 150a: inspection surface, C: center of gravity, L: movement locus (a section moving around the center of gravity, (Section moving spirally), P1 to P14... Imaging region, r1, r2.

Claims (5)

The intensity signal of the reflected light from the inspection surface of the inspection object and the temporal change of the light intensity periodically based on the spatial change according to the passage of time of the light intensity given on the inspection surface A time correlation image generation unit that generates a time correlation image by an imaging system that multiplies a reference signal that changes;
Continuous and periodic time variation of light intensity and space within one exposure time of the imaging system on the inspection surface by spatially changing the light according to continuous time progress on the inspection surface A surface lighting unit that gives change,
An arithmetic processing unit that calculates, from the time correlation image, a feature corresponding to the distribution of the normal vector of the inspection surface and detecting an abnormality by at least one of a difference from the surroundings and a difference from the reference surface When,
As the imaging of a plurality of imaging areas set on the test surface is performed, a moving mechanism for moving at least one of the inspection object and before SL imaging system,
Equipped with
The inspection system according to claim 1, wherein the movement trajectory of the imaging area on the inspection surface includes a section moving so as to turn around the center of gravity of the inspection object.   The inspection system according to claim 1, wherein the movement trajectory includes a section moving in a spiral manner.   The inspection system according to claim 1, wherein the plurality of imaging regions include a plurality of imaging regions having different sizes. In a plurality of images normal vector is captured by the pre-Symbol IMAGING system different orientation of the reference point on the test surface, on the basis of the intensity of light at the reference point, the displacement of the test surface The inspection system according to any one of claims 1 to 3, further comprising a shift correction unit for correcting. The deviation correcting unit, in the plurality of images picked up corresponding to the plurality of reference points, on the basis of the intensity of light at each of the reference points, to correct the deviation of the test surface, claim 4. The inspection system according to 4.

Images