JP6751567B2 - Electronic component inspection method, electronic component mounting method, and electronic component mounting device - Google Patents

Description

The present invention relates to an electronic component inspection method, an electronic component mounting method, and an electronic component mounting device.

In the manufacturing process of an electronic device, an electronic component mounting device for mounting an electronic component on a substrate, for example, as disclosed in Patent Document 1, is used.

Japanese Unexamined Patent Publication No. 2012-039096

In the electronic component mounting process, the position or orientation of the electronic component held in the nozzle of the electronic component mounting device is inspected, and whether or not the electronic component after mounting on the board is correctly mounted in the mounting area on the surface of the board is checked. It may be inspected. In the inspection, an image of the electronic component held in the nozzle or an image of the electronic component after being mounted on the substrate is acquired, and the electronic component is detected by using a template matching method. In the inspection method based on the template matching method, a process of searching for an electronic component by moving a template to a sample image including an electronic component mounted on a substrate and inquiring the image of the electronic component and the template is performed. Will be done. For example, when the background portion around the electronic component or the surface of the substrate is dirty or foreign matter is attached to the surface of the substrate, the dirt or foreign matter becomes a noise component. If the template moves to a noise region in which a noise component exists in the sample image, the image in the noise region may be erroneously recognized as an image of an electronic component. As a result, the inspection accuracy may decrease. If the inspection accuracy is lowered, the desired electronic device is not manufactured, and the productivity may be lowered.

An object of the present invention is to provide an electronic component inspection method in which a decrease in inspection accuracy is suppressed. Another object of the present invention is to provide an electronic component mounting method and an electronic component mounting device in which a decrease in productivity is suppressed.

According to the first aspect of the present invention, a sample image showing an image of a sample region including an electronic component is acquired by an imaging device, and the sample image acquired by the imaging device is divided into a plurality of grid regions. That is, the coordinates of the first class grid area in which the pixels having the density value equal to or higher than the threshold value exist among the plurality of the grid areas are acquired, and the estimation statistical processing is performed based on the coordinates of the first class grid area. To calculate a reliable region in which the center position of the electronic component may exist in the sample image, and to specify a search region including the reliable region and smaller than the sample region in the sample image. Provided is an electronic component inspection method including moving a template to the search area and searching for the electronic component based on a correlation value between a part of image data in the search area and the template. To.

In the first aspect of the present invention, it is preferable that the electronic component has an electrode and the reliable region is calculated with the coordinates of the first class grid region including the electrode as a feature region.

In the first aspect of the present invention, the sample image has a plurality of coordinates defined in the first axial direction of a predetermined surface parallel to the sample region, and a second of the predetermined surface orthogonal to the first axial direction. It is divided by the grid area associated with each of the plurality of coordinates defined in the axial direction, and for each of the plurality of grid areas, it is determined whether or not a pixel having a density value equal to or higher than the threshold value exists in the grid area. To obtain the frequency of the coordinates of the first class grid area among the plurality of grid areas in the second axis direction for each coordinate in the first axis direction, and for each coordinate in the second axis direction. In addition, the coordinates of the coordinates of the first class grid area among the plurality of grid areas in the first axis direction are acquired, and the coordinates of the first class grid area acquired for each of the coordinates in the first axis direction. Based on the calculation of the range of the confidence region in the first axis direction and the coordinates of the coordinates of the first class grid region acquired for each coordinate in the second axis direction, the said It is preferable to include calculating the range of the confidence region in the second axis direction.

In the first aspect of the present invention, the calculation of the range of the confidence interval in the first axis direction is performed by using the coordinates of the first class grid region acquired for each coordinate in the first axis direction as a sample and averaging the sample. The calculation of the range of the confidence region in the second axis direction includes calculating and estimating the population average of the concentration value in the first axis direction in a confidence interval of a predetermined percentage, and the calculation of the range of the confidence region in the second axis direction is performed in the second axis direction. Includes calculating the sample average using the coordinates of the first class grid region acquired for each of the coordinates of the above as a sample, and estimating the population average of the density values in the second axis direction with a confidence interval of a predetermined percentage. The range of the confidence region is preferably defined by the confidence space in the first axial direction and the confidence interval in the second axial direction.

In the first aspect of the present invention, it is preferable that the appearance of the electronic component is substantially axisymmetric in each of the first axial direction and the second axial direction of a predetermined surface parallel to the sample region.

In the first aspect of the present invention, the grid region includes a plurality of pixels of the image pickup device of the image pickup apparatus, and the density value of at least one of the plurality of pixels included in the grid region is the density value. When it is equal to or more than the threshold value, it is preferable that the density value in the grid region is determined to be equal to or more than the threshold value.

According to the second aspect of the present invention, there is provided an electronic component mounting method including inspecting the electronic component by the electronic component inspection method of the second aspect.

According to the third aspect of the present invention, a mounting head having a nozzle for holding an electronic component and capable of mounting the electronic component on a substrate, and a sample image showing an image of a sample region including the electronic component are acquired. A first-class grid area in which an image pickup device, a grid area setting unit that divides the sample image acquired by the image pickup device into a plurality of grid areas, and pixels having a density value equal to or higher than a threshold value among the plurality of the grid areas are present. A density value acquisition unit that acquires the coordinates of the electronic component, and an estimation statistical processing unit that calculates a reliable region in which the center position of the electronic component may exist in the sample image based on the coordinates of the first class grid region. In the sample image, a search area setting unit that includes the trust area and specifies a search area smaller than the sample area, a storage unit that stores a template indicating the electronic component, and a storage unit that stores a template indicating the electronic component, and a template are moved with respect to the search area. Then, an electronic component mounting device including a template matching unit that searches for the electronic component based on a correlation value between a part of the image data in the search region and the template is provided.

In the third aspect of the present invention, the grid area setting unit sets the sample image at a plurality of coordinates defined in the first axial direction of a predetermined surface parallel to the sample area, and is orthogonal to the first axial direction. The grid area is divided into the grid areas associated with the plurality of coordinates defined in the second axis direction of the predetermined surface, and for each of the plurality of grid areas, pixels having a density value equal to or higher than the threshold value are formed in the grid area. The concentration value acquisition unit includes a determination unit for determining whether or not it exists, and the density value acquisition unit includes coordinates of the first class grid area among a plurality of grid areas in the second axis direction for each coordinate in the first axis direction. And for each coordinate in the second axis direction, the frequency of the coordinates of the first class grid area among the plurality of grid areas in the first axis direction is acquired, and the estimation statistical processing unit uses the above. Based on the frequency of the coordinates of the first class grid area acquired for each coordinate in the first axis direction, the range of the confidence area in the first axis direction is calculated and acquired for each coordinate in the second axis direction. It is preferable to calculate the range of the reliable region in the second axis direction based on the frequency of the coordinates of the first class grid region.

According to the aspect of the present invention, there is provided an electronic component inspection method in which a decrease in inspection accuracy is suppressed. Further, according to the aspect of the present invention, there is provided an electronic component mounting method and an electronic component mounting device in which a decrease in productivity is suppressed.

FIG. 1 is a perspective view showing an example of an electronic component mounting device according to the present embodiment. FIG. 2 is a perspective view showing an example of the transfer head according to the present embodiment. FIG. 3 is a front view showing an example of the image pickup apparatus according to the present embodiment. FIG. 4 is a diagram showing an example of the operation of the electronic component mounting device according to the present embodiment. FIG. 5 is a diagram showing an example of the operation of the electronic component mounting device according to the present embodiment. FIG. 6 is a functional block diagram showing an example of a control system for the electronic component mounting device according to the present embodiment. FIG. 7 is a flowchart showing an example of the electronic component inspection method according to the present embodiment. FIG. 8 is a schematic diagram for explaining the electronic component inspection method according to the present embodiment. FIG. 9 is a schematic diagram for explaining the electronic component inspection method according to the present embodiment. FIG. 10 is a schematic diagram for explaining the electronic component inspection method according to the present embodiment. FIG. 11 is a schematic diagram for explaining the electronic component inspection method according to the present embodiment. FIG. 12 is a schematic diagram for explaining the electronic component inspection method according to the present embodiment. FIG. 13 is a schematic diagram for explaining the electronic component inspection method according to the present embodiment. FIG. 14 is a schematic diagram for explaining a problem of the prior art. FIG. 15 is a diagram showing an example of an electronic component according to the present embodiment.

Hereinafter, embodiments according to the present invention will be described with reference to the drawings, but the present invention is not limited thereto. The constituent elements of the embodiments described below can be appropriately combined. In addition, some components may not be used. The constituent elements in the embodiments described below include those that can be easily conceived by those skilled in the art, those that are substantially the same, and those that are in the so-called equivalent range.

In the following description, the XYZ Cartesian coordinate system is set, and the positional relationship of each part will be described with reference to the XYZ Cartesian coordinate system. The direction parallel to the first axis of the predetermined surface is the X-axis direction, and the direction parallel to the second axis of the predetermined surface orthogonal to the first axis is the Y-axis direction, and is orthogonal to each of the first axis and the second axis. The direction parallel to the third axis is the Z-axis direction. The predetermined plane is an XY plane, and in the present embodiment, it is a horizontal plane. The first axis is the X axis, the second axis is the Y axis, and the third axis is the Z axis. The Z axis and the XY plane are orthogonal to each other. Further, the rotation or tilt direction centered on the X axis is defined as the θX direction, the rotation or tilt direction centered on the Y axis is defined as the θY direction, and the rotation or tilt direction centered on the Z axis is defined as the θZ direction.

FIG. 1 is a perspective view showing an example of the electronic component mounting device 100 according to the present embodiment. The electronic component mounting device 100 mounts the electronic component C on the substrate P. The electronic component mounting device 100 includes a board transfer device 2 for transporting the substrate P, an electronic component supply device 4 for supplying the electronic component C, and a nozzle 10 for detachably holding the electronic component C. A mounting head 7 for mounting the electronic components C supplied from the above on the board P, a drive system 3 for moving the nozzle 10 and the mounting head 7, and a base 1 for supporting at least a part of the board transfer device 2 and the drive system 3. And.

In the present embodiment, the electronic component C is a chip-type electronic component (mounting-type electronic component) having no lead, and is mounted on the substrate P by being mounted on the substrate P.

Further, the electronic component mounting device 100 mounts the electronic component C on the substrate P and the image pickup device 9 including the image pickup element arranged in the moving path of the mounting head 7 and acquiring the image data of the electronic component C held by the nozzle 10. The present invention includes an image pickup device 14 including an image pickup element that acquires image data of at least a part of the electronic component C and the substrate P.

The substrate transfer device 2 has a transfer path 2R extending in the X-axis direction and in which the substrate P moves, and a substrate holding portion that holds and positions the substrate P in the transfer path 2R. The electronic component supply device 4 supplies the electronic component C mounted on the substrate P. In the present embodiment, the electronic component supply devices 4 are arranged on both sides of the transport path 2R in the Y-axis direction. The electronic component supply device 4 has a plurality of component feeders 5 arranged in the X-axis direction. The parts feeder 5 stores the carrier tapes held by the plurality of electronic components C, and sends out the carrier tapes to sequentially supply the electronic components C.

The drive system 3 includes an X-axis drive device 6 that moves the mounting head 7 in the X-axis direction, a Y-axis drive device 8 that moves the mounting head 7 in the Y-axis direction, and a Z-axis that moves the nozzle 10 in the Z-axis direction. It has a drive device and a θZ drive device that rotates the nozzle 10 in the θZ direction.

The X-axis drive device 6 includes a guide member 6G that guides the mounting head 7 in the X-axis direction, and an actuator that generates power for moving the mounting head 7 in the X-axis direction. The Y-axis drive device 8 includes a guide member 8G that guides the X-axis drive device 6 in the Y-axis direction, and an actuator that generates power for moving the X-axis drive device 6 in the Y-axis direction. When the X-axis drive device 6 moves in the Y-axis direction by the Y-axis drive device 8, the mounting head 7 supported by the X-axis drive device 6 moves in the Y-axis direction together with the X-axis drive device 6.

The image pickup device 9 includes an optical system and an image pickup element, and photographs the electronic component C held by the nozzle 10 from below. The image pickup device 9 is arranged in the movement path of the mounting head 7 between the transport path 2R and the electronic component supply device 4, and can acquire image data of the electronic component C held by the nozzle 10. By acquiring the image data of the electronic component C held by the nozzle 10, the electronic component C is identified and the position is detected.

The image pickup apparatus 14 includes an optical system and an image pickup element, and photographs at least a part of the substrate P and the electronic component C mounted on the substrate P from above. The image pickup apparatus 14 is provided on the mounting head 7, and can move together with the mounting head 7 to acquire image data of the electronic component C mounted on the substrate P. By acquiring the image data of the electronic component C mounted on the substrate P, the misalignment of the electronic component C with respect to the substrate P is detected.

FIG. 2 is a perspective view showing an example of the mounting head 7 according to the present embodiment. The mounting head 7 includes a nozzle 10 that detachably holds the electronic component C, a nozzle shaft 11 that supports the nozzle 10, a holder 17 that holds the nozzle shaft 11, a base member 16 that supports the holder 17, and a base member. A Z-axis drive device 13 that is supported by 16 and moves the nozzle 10 in the Z-axis direction by moving the holder 17, and a nozzle 10 that is supported by the holder 17 and rotates the nozzle shaft 11 in the θZ direction to rotate the nozzle 10 in the θZ direction. The θZ drive device 12 is provided.

A plurality of nozzle shafts 11 and a plurality of nozzle shafts 11 for supporting the nozzle 10 are provided. In this embodiment, four nozzles 10 and four nozzle shafts 11 are provided. A single nozzle 10 and a single nozzle shaft 11 may be provided. The nozzle 10 is a suction nozzle that sucks the electronic component C, and is arranged at the lower end of the nozzle shaft 11. A suction hole for sucking gas is provided at the lower end of the nozzle 10. The nozzle 10 holds the electronic component C by sucking gas from the suction hole in a state where the lower end portion of the nozzle 10 and the electronic component C are in contact with each other. Further, the electronic component C is released from the nozzle 10 by stopping the suction of the gas from the suction hole.

The θZ drive device 12 is connected to the upper end of the nozzle shaft 11. The θZ drive device 12 includes a servomotor and rotates the nozzle shaft 11 in the θZ direction. When the nozzle shaft 11 rotates in the θZ direction, the nozzle 10 supported by the nozzle shaft 11 rotates in the θZ direction together with the nozzle shaft 11. The Z-axis drive device 13 is connected to the holder 17 via a ball screw 18. The Z drive device 13 includes a servomotor and drives the ball screw 18 to move the holder 17 in the Z-axis direction. When the holder 17 moves in the Z-axis direction, the nozzle shaft 11 and the nozzle 10 held by the holder 17 move in the Z-axis direction together with the holder 17.

In the present embodiment, the holder 17, the θZ drive device 12, and the Z-axis drive device 13 are arranged for each of the plurality of nozzles 10 and the nozzle shaft 11. The plurality of nozzles 10 can be individually moved in the Z-axis direction and the θZ direction by the operation of the θZ drive device 12 and the Z-axis drive device 13.

Due to the operation of the drive system 3 including the X-axis drive device 6, the Y-axis drive device 8, the Z-axis drive device 13, and the θZ drive device 12, the nozzle 10 has four nozzles, X-axis, Y-axis, Z-axis, and θZ. It is movable in the direction.

FIG. 3 is a front view showing an example of the image pickup apparatus 14 according to the present embodiment. The image pickup apparatus 14 includes a plurality of cameras 15. Each of the plurality of cameras 15 has an optical system and an image sensor. The image pickup apparatus 14 acquires at least a part of image data of the substrate P when the electronic component C is mounted on the substrate P. In the present embodiment, the image pickup apparatus 14 images the substrate P from diagonally above. In addition, only one camera 15 may be provided for one nozzle 10, or only one may be provided for a plurality of nozzles 10.

Further, in the present embodiment, the image pickup device 14 includes a lighting device that illuminates the substrate P to be imaged by the image pickup device 14. The lighting device emits illumination light to illuminate at least a part of the electronic component C and the substrate P, which are the subjects of the image pickup device 14. The image pickup apparatus 14 acquires image data of at least a part of the electronic component C and the substrate P illuminated by the illumination apparatus.

Next, an example of the operation of the electronic component mounting device 100 according to the present embodiment will be described. FIG. 4 is a diagram showing a state before the electronic component C is mounted on the substrate P. The electronic component C held by the nozzle 10 is mounted on the mounting area MA on the surface of the substrate P. The solder paste HP is provided in the mounting area MA of the substrate P.

The image pickup apparatus 14 acquires image data including the mounting area MA of the substrate P and the peripheral region SA of the substrate P around the mounting region MA before the electronic component C is mounted on the mounting region MA of the substrate P. ..

After the image data of the mounting area MA and the peripheral area SA on the surface of the substrate P are acquired, the nozzle 10 holding the electronic component C is lowered, and the electronic component C is mounted on the mounting area MA of the substrate P. The electronic component C is connected to the solder paste HP provided on the substrate P. The electronic component C has a body Ca and electrodes Cb provided at both ends of the body Ca. At least a part of the electrode Cb and the solder paste HP are connected.

FIG. 5 is a diagram showing a state after the electronic component C is mounted on the substrate P. After the electronic component C is mounted on the substrate P, the nozzle 10 rises and separates from the substrate P and the electronic component C.

After the electronic component C is mounted on the mounting area MA of the substrate P, the image pickup apparatus 14 acquires the image data of the electronic component C and the image data of the surface of the substrate P arranged around the electronic component C. .. The image data on the surface of the substrate P arranged around the electronic component C includes the image data of the peripheral region SA.

In the following description, the image of the sample region including the electronic component C acquired by at least one of the image pickup device 9 and the image pickup device 14 is appropriately referred to as a sample image. The sample image shows an image of the sample region including the electronic component C and the objects around the electronic component C.

The sample image acquired by the image pickup apparatus 9 shows an image of the sample region including the electronic component C held by the nozzle 10 and the objects around the electronic component C. Objects around the electronic component C include, for example, a part of the nozzle 10 or a part of the mounting head 7. The sample region of the image pickup apparatus 9 corresponds to the visual field region of the optical system of the image pickup apparatus 9.

The sample image acquired by the image pickup apparatus 14 shows an image of an electronic component C mounted on the substrate P and an image of a sample region including the surface of the substrate P arranged around the electronic component C. The sample region of the imaging device 14 corresponds to the visual field region of the optical system of the imaging device 14.

The sample region is a region parallel to the XY plane. The sample image is two-dimensional image data parallel to the XY plane.

FIG. 6 is a functional block diagram showing an example of the control system 200 of the electronic component mounting device 100 according to the present embodiment. As shown in FIG. 6, the control system 200 includes a control device 20 including a computer system. The control device 20 is connected to the mounting head 7, the drive system 3, the image pickup device 9, and the image pickup device 14.

The control device 20 has a processor such as a CPU (Central Processing Unit), an internal memory such as a ROM (Read Only Memory) or a RAM (Random Access Memory), and an external memory such as a hard disk device.

The control device 20 includes a mounting control unit 21 that outputs a control signal to the mounting head 7 and the drive system 3, an image data acquisition unit 22 that acquires a sample image acquired by at least one of the image pickup device 9 and the image pickup device 14. A grid area setting unit 23 that sets a plurality of grid areas in a sample image acquired by at least one of the image pickup device 9 and the image pickup device 14, and a first class in which pixels having a density value equal to or higher than a threshold value are present in the plurality of grid areas. A density value acquisition unit 24 that acquires the coordinates of the grid area, a determination unit 25 that determines whether or not a pixel having a density value equal to or higher than the threshold value exists in the grid area for each of a plurality of grid areas, and a first-class grid. An estimation statistical processing unit 26 that calculates a reliable area in which the center position of the electronic component C may exist based on the coordinates of the area, a search area setting unit 27 that specifies the search area, and a template showing the electronic component C. A storage unit 28 for storing, a template matching unit 29 for moving a template with respect to a search area and searching for an electronic component C based on a correlation value between a part of image data in the search area and the template, and an input / output unit. 30 and.

The mounting control unit 21 generates a control signal for controlling the mounting head 7 and the drive system 3. The mounting control unit 21 outputs a control signal to the mounting head 7 and the driving system 3 via the input / output unit 30 to control the mounting head 7 and the driving system 3.

The image data acquisition unit 22 acquires a sample image acquired by at least one of the image pickup device 9 and the image pickup device 14 via the input / output unit 30.

The grid area setting unit 23 divides the sample image acquired by at least one of the image pickup device 9 and the image pickup device 14 into a plurality of grid areas. The grid area setting unit 23 divides the sample image into a plurality of X-coordinates defined in the X-axis direction and a grid area associated with each of the plurality of Y-coordinates defined in the Y-axis direction.

In the present embodiment, the grid region includes a plurality of pixels of the image pickup device 9 of the image pickup device 9 or the image pickup device of the image pickup device 14. That is, one grid area is an aggregate of a plurality of pixels. In addition, one grid area may be composed of one pixel.

The density value acquisition unit 24 acquires the coordinates of the first-class grid region in which pixels having a density value equal to or higher than the threshold value exist among the plurality of grid regions. The pixel density value is a value indicating the brightness of the image corresponding to the pixel. When the image of the pixel is bright, the density value becomes large. When the image of the pixel is dark, the density value becomes small. A bright pixel image indicates that the color of the pixel image is close to white. The darkness of the pixel image indicates that the color of the pixel image is close to black. The density value acquisition unit 24 determines the density value of the pixels included in the grid area, and acquires the coordinates of the first class grid area in which the pixels having the density value equal to or higher than the threshold value exist.

The determination unit 25 determines for each of the plurality of grid areas whether or not there are pixels having a density value equal to or higher than the threshold value in the grid area. In the present embodiment, the maximum value and the minimum value of the concentration value are defined. The threshold value for the concentration value is set to the median value between the maximum value and the minimum value, or a value obtained by a threshold value calculation method such as a discriminant analysis method.

The concentration value is classified into a plurality of stages between the maximum value and the minimum value. In the present embodiment, the density value is represented by 8 bits and is classified into 256 steps (256 gradations). The threshold value for the density value is set to the half value of 256 gradations, that is, 128 when the median value of the maximum value and the minimum value is used.

In the present embodiment, the determination unit 25 has a plurality of grid areas, a grid area in which pixels having a density value equal to or higher than the threshold value exist, and pixels having a density value lower than the threshold value, and pixels having a density value equal to or higher than the threshold value. Not classified as a grid area. That is, the plurality of grid areas are classified into two types of grid areas based on the density values of the pixels included in the grid area. In the following description, a grid area in which pixels having a density value equal to or higher than the threshold value are present is appropriately referred to as a first-class grid area, and a grid area in which a density value below the threshold value is present and pixels with a density value higher than the threshold value are not present. Is appropriately referred to as a second-class grid area.

As described above, in the present embodiment, the grid region includes a plurality of pixels of the image pickup device of the image pickup device 14. When the density value of at least one pixel among the plurality of pixels included in one grid area is equal to or greater than the threshold value, the determination unit 25 determines that the grid area is the first class grid area. For example, when one grid area consists of (5 × 5) pixels, if the density value of at least one pixel is 128 or more, even if the density value of the other pixel is less than 128, the grid area Is determined to be the first class grid area.

In the present embodiment, the density value acquisition unit 24 acquires the frequency (number of data) of the coordinates of the first class grid area among the plurality of grid areas set in the Y-axis direction for each of the plurality of X coordinates. Further, the density value acquisition unit 24 acquires the frequency (number of data) of the coordinates of the first class grid area among the plurality of grid areas set in the X-axis direction for each of the plurality of Y coordinates.

The inference statistical processing unit 26 calculates a reliable region in which the center position of the electronic component C may exist in the sample image based on the coordinates of the first class grid region. The density value acquisition unit 24 acquires the frequency of the coordinates of the first class grid area among the plurality of grid areas arranged in the Y-axis direction for each of the plurality of X-coordinates, and acquires the frequency of the coordinates of the first-class grid area for each of the plurality of Y-coordinates in the X-axis direction. Of the plurality of grid areas arranged in, the frequency of the coordinates of the first class grid area is acquired. The inference statistical processing unit 26 calculates the range of the trust region in the X-axis direction based on the frequency of the coordinates of the first class grid region acquired for each of the plurality of X coordinates. In addition, the inference statistics processing unit 26 calculates the range of the trust region in the Y-axis direction based on the frequency of the coordinates of the first class grid region acquired for each of the plurality of Y coordinates.

The search area setting unit 27 specifies a search area in the sample image. The search area is smaller than the sample area. Further, the search area is an area including the entire trust area, and is larger than the trust area.

The template matching unit 29 moves the template with respect to the search area, and searches for the electronic component C based on the correlation value between the image data of a part of the search area and the template. That is, the template matching unit 29 searches for the electronic component C from the search region based on the density-based or shape-based template matching method. A template showing the electronic component C is defined in advance and is stored in the storage unit 28.

Next, an example of the electronic component inspection method according to the present embodiment will be described. FIG. 7 is a flowchart showing an example of the electronic component inspection method according to the present embodiment. In the following description, an example of an electronic component inspection method using the image pickup apparatus 14 will be described. That is, in the following description, as described with reference to FIG. 5, after the electronic component C is mounted on the substrate P, whether or not the electronic component C is correctly mounted in the mounting area MA on the surface of the substrate P. An example of inspecting the component will be described.

As shown in FIG. 7, in the electronic component inspection method according to the present embodiment, a step (step S10) of acquiring a sample image showing an image of a sample region including the electronic component C by the imaging device 14 and acquisition by the imaging device 14 A step of dividing the sample image into a plurality of grid regions (step S20) and a step of acquiring the coordinates of a first-class grid region in which pixels having a density value equal to or higher than a threshold value are present among the plurality of grid regions (step S30). ), And a step (step S40) of calculating a reliable region in which the center position of the electronic component C may exist in the sample image by performing estimation statistical processing based on the coordinates of the first class grid region, and a sample. In the image, the step of designating the search area including the trust area and smaller than the sample area (step S50), and moving the template to the search area to set the correlation value between the image data of a part of the search area and the template. A step (step S60) of searching for the electronic component C based on the electronic component C is included.

A sample image of the electronic component C after being mounted on the substrate P is acquired by the image pickup apparatus 14 (step S10). FIG. 8 is a diagram schematically showing an example of a sample image acquired by the image pickup apparatus 14. As shown in FIG. 8, a sample image including the electronic component C mounted on the mounting region MA and the peripheral region SA of the substrate P existing around the electronic component C is acquired.

The sample image shows an image of a sample region including the electronic component C. The sample region corresponds to the visual field region of the optical system of the imaging device 14. As shown in FIG. 8, the sample region is a region parallel to the XY plane.

As shown in FIG. 8, the outer shape of the electronic component C in the XY plane is substantially a quadrangle. Further, in the present embodiment, the appearance of the electronic component C in the XY plane is substantially axisymmetric in each of the X-axis direction and the Y-axis direction. The appearance of the electronic component C is substantially axisymmetric with respect to the reference line Ly that passes through the center position AX of the electronic component C in the XY plane and is parallel to the Y axis. Similarly, the appearance of the electronic component C is substantially axisymmetric with respect to the reference line Lx passing through the center position AX and parallel to the X axis. In the present embodiment, the electrodes Cb are arranged at the + X side end portion and the −X side end portion of the body Ca of the electronic component C, respectively. The outer shape and dimensions of the electrode Cb arranged at the + X side end of the body Ca and the outer shape and dimensions of the electrode Cb arranged at the −X side end of the body Ca are substantially equal. Further, the distance between the reference line Ly and the electrode Cb arranged at the + X side end of the body Ca and the distance between the reference line Ly and the electrode Cb arranged at the −X side end of the body Ca. Are substantially equal.

The surface of the electrode Cb is made of metal, and the surface of the body Ca is made of synthetic resin. When the electronic component C is illuminated by the illumination device of the image pickup device 14, the reflectance of the electrode Cb is higher than the reflectance of the body Ca. In the sample image acquired by the image pickup apparatus 14, the brightness of the image data of the electrode Cb is brighter than the brightness of the image data of the body Ca. That is, in the sample image, the density value of the image data of the electrode Cb is higher than the density value of the image data of the body Ca.

Next, the sample image is divided into a plurality of grid areas (step S20). FIG. 9 is a diagram schematically showing an example of a sample image divided by a plurality of grid regions. In the XY plane, the outer shape of the grid area is a quadrangle. The outer shape and dimensions of the plurality of grid areas are the same.

The X coordinate xi and the Y coordinate yi are given to each of the plurality of grid areas. In the present embodiment, 19 grid regions are set in the X-axis direction and 18 grid regions are set in the Y-axis direction. The sample image is divided into a plurality of grid regions associated with each of the plurality of X coordinates x1 to x19 defined in the X-axis direction and the plurality of Y coordinates y1 to y18 defined in the Y-axis direction.

As schematically shown in FIG. 9, in the present embodiment, one grid region includes a plurality of pixels of the image sensor of the image pickup device 14. In the present embodiment, in one grid area, five pixels are arranged in the X-axis direction and five pixels are arranged in the Y-axis direction.

Next, the density values of each of the plurality of pixels are acquired, and the coordinates of the first class grid region are acquired (step S30). As described above, the density value is a value indicating the brightness of the image. The density value of the pixel in which the electrode Cb is present is high. The density value of the pixel in which the electrode Cb does not exist is low. The density value of the pixel in which the electrode Cb is present is equal to or higher than the threshold value, and the density value of the pixel in which the electrode Cb is not present is less than the threshold value.

For example, when the surface of the substrate P around the electronic component C is dirty or foreign matter is attached to the surface of the substrate P, the dirt or foreign matter becomes a noise component. As shown in FIGS. 8 and 9, the reflectance of the noise region in which the noise component exists in the sample image may be high. In that case, the density value of the pixel in which the noise region exists becomes high.

The density value acquisition unit 24 acquires pixel density values for each of a total of 342 (19 × 18) grid areas, which are set to 19 in the X-axis direction and 18 in the Y-axis direction. Further, in the present embodiment, one grid area includes a total of 25 (5 × 5) pixels, which are set to 5 in the X-axis direction and 5 in the Y-axis direction.

Next, for each of the plurality of (342) grid regions, it is determined whether or not there are pixels having a density value equal to or higher than the threshold value in the grid region. The density value is represented by a specified number of gradations, and the threshold value is a half value of the maximum value represented by the number of gradations, or a value obtained by a threshold calculation method such as a discriminant analysis method. As described above, in the present embodiment, the density value is represented by 256 gradations, and the threshold value is 128, which is a half value of the maximum value of 256 gradations. The determination unit 25 determines for each of the plurality of grid areas whether or not there are pixels having a density value equal to or higher than the threshold value in the grid area, and has pixels having a density value equal to or higher than the threshold value in the plurality of grid areas. It is classified into a first-class grid area and a second grid area in which a density value below the threshold value exists and a pixel having a density value above the threshold value does not exist.

In the present embodiment, when the density value of at least one pixel among the plurality (25) pixels included in one grid area is equal to or more than the threshold value, the grid area is the first class grid area. Judge that there is. That is, if the density value of at least one image among the density values of 25 pixels included in one grid area is 128 or more, the grid area even if the density value of the other pixels is less than 128. Is determined to be the first class grid area. By specifying the first class grid area, the coordinates of the first class grid area are specified. The density value acquisition unit 24 acquires the coordinates of the first class grid area (step S30).

Next, the density value acquisition unit 24 acquires the frequency of the coordinates of the first class grid area among the plurality of grid areas arranged in the Y-axis direction for each of the plurality of X coordinates. Further, the density value acquisition unit 24 acquires the frequency of the coordinates of the first class grid area among the plurality of grid areas arranged in the X-axis direction for each of the plurality of Y coordinates.

FIG. 10 is a diagram showing a histogram of the frequencies of the coordinates of the first class grid area. A plurality of (18) grid areas arranged in the Y-axis direction are set for each of the plurality of X coordinates xi. For example, 18 grid areas arranged in the Y-axis direction are set in the X coordinate x1, and 18 grid areas arranged in the Y-axis direction are set in the X coordinate x2. In the present embodiment, the frequency of the coordinates of the first class grid area is derived for each of the plurality of X coordinates, and a histogram showing the frequency distribution in the X axis direction of the first class grid area is created. In the example shown in FIG. 10, there is no first class grid region at the X coordinates x1 to x5 (the frequency is zero). At the X coordinate x6, one of the 18 grid areas arranged in the Y-axis direction is a first-class grid area. At the X coordinate x7, there are two first-class grid areas out of the 18 grid areas arranged in the Y-axis direction. At the X coordinate x8, there are five first-class grid areas out of the 18 grid areas arranged in the Y-axis direction. At the X coordinate x9, there are three first-class grid areas out of the 18 grid areas arranged in the Y-axis direction. At the X coordinate x10, there are two first-class grid areas out of the 18 grid areas arranged in the Y-axis direction. At the X coordinate x11, there is one first class grid area out of the 18 grid areas arranged in the Y-axis direction. At the X coordinate x12, there are four first-class grid areas out of the 18 grid areas arranged in the Y-axis direction. There is no first class grid area at the X coordinate x13. At the X coordinate x14, one of the 18 grid areas arranged in the Y-axis direction is a first-class grid area. There is no first class grid area at the X coordinates x15 to x19.

Further, a plurality of (19) grid areas arranged in the X-axis direction are set for each of the plurality of Y coordinates yi. For example, 19 grid areas arranged in the X-axis direction are set in the Y coordinate y1, and 19 grid areas arranged in the X-axis direction are set in the Y coordinate y2. In the present embodiment, the coordinates of the coordinates of the first class grid area are derived for each of the plurality of Y coordinates, and a histogram showing the frequency distribution in the Y axis direction of the first class grid area is created. In the example shown in FIG. 10, the first class grid region does not exist at the Y coordinates y1 and y2. At the Y coordinate y3, one of the 19 grid areas arranged in the X-axis direction is a first-class grid area. At the Y coordinate y4, there is one first class grid area out of 19 grid areas arranged in the X-axis direction. At the Y coordinate y5, there are two first-class grid areas out of the 19 grid areas arranged in the X-axis direction. At the Y coordinate y6, there are two first-class grid areas out of the 19 grid areas arranged in the X-axis direction. At the Y coordinate y7, there are two first-class grid areas out of the 19 grid areas arranged in the X-axis direction. At the Y coordinate y8, there are three first-class grid areas out of the 19 grid areas arranged in the X-axis direction. At the Y coordinate y9, there are three first-class grid areas out of the 19 grid areas arranged in the X-axis direction. At the Y coordinate y10, there are three first-class grid areas out of the 19 grid areas arranged in the X-axis direction. At the Y coordinate y11, there is one first class grid area out of 19 grid areas arranged in the X-axis direction. At the Y coordinate y12, one of the 19 grid areas arranged in the X-axis direction is a first-class grid area. At the Y coordinate y13, one of the 19 grid areas arranged in the X-axis direction is a first-class grid area. The first class grid region does not exist at the Y coordinates y14 to y18.

As a result, as shown in FIG. 10, a histogram showing the frequency distribution of the first class grid region is created.

Next, inference statistical processing is performed based on the coordinates of the acquired first-class grid region, and a reliable region in which the center position AX of the electronic component C is likely to exist is calculated in the sample image (step S40). ..

In the present embodiment, the inference statistical processing unit 26 calculates the range of the trust region in the X-axis direction based on the frequency of the coordinates of the first class grid region acquired for each of the plurality of X coordinates xi (x1 to x19). To do. Further, the inference statistics processing unit 26 calculates the range of the trust region in the Y-axis direction based on the frequency of the coordinates of the first class grid region acquired for each of the plurality of Y coordinates yi (y1 to y18).

In the present embodiment, the range of the confidence region in the X-axis direction is calculated by calculating the average from the frequencies of the center coordinates of the first class grid region acquired for each of a plurality of X coordinates and using it as the sample average to estimate the X-axis. It includes estimating the population average in the X-axis direction from the sample average with a 95% confidence interval, with the center position of the electronic component in the direction as the population average. In the present embodiment, the range of the confidence region in the X-axis direction is defined by the 95 percent confidence interval when the interval is estimated. That is, the 95% confidence interval when the interval is estimated is the range of the confidence region in the X-axis direction.

Similarly, in the present embodiment, the calculation of the range of the confidence region in the Y-axis direction is estimated by calculating the average from the frequencies of the center coordinates of the first class grid region acquired for each of a plurality of Y coordinates and using it as the sample average. The center position of the electronic component in the Y-axis direction is used as the population average, and the population average in the Y-axis direction is estimated from the sample average with a 95% confidence interval. In the present embodiment, the range of the confidence region in the Y-axis direction is defined by the 95 percent confidence interval when the interval is estimated. That is, the 95% confidence interval when the interval is estimated is the range of the confidence region in the Y-axis direction.

Hereinafter, the calculation of the range of the trust region in the X-axis direction will be described. First, the sample average of the coordinates of the coordinates of the first class grid region acquired for each of the plurality of X coordinates is calculated. In this embodiment, the weighted average is calculated as the sample average. As described above, in the present embodiment, there is one first class grid region at the X coordinate x6, two at the X coordinate x7, five at the X coordinate x8, and three at the X coordinate x9. There are two, two at the X coordinate x10, one at the X coordinate x11, four at the X coordinate x12, and one at the X coordinate x14. Therefore, the total number of first-class grid areas is 19 (1 + 2 + 5 + 3 + 2 + 1 + 4 + 1).

When the frequency of the first class grid area existing in the X coordinate xi is mi and the total number of the first class grid areas is N, the inference statistical processing unit 26 performs the calculation of the following equation (1). The center of the frequency distribution of the first class grid region in the X-axis direction is calculated.

In this example, the center of the frequency distribution of the first class grid region in the X-axis direction is calculated by performing the calculation of Eq. (2).

The solution of equation (2) is 9.47. Therefore, the X coordinate of the center of the frequency distribution in the first class grid region in the X-axis direction is x9.47. In the present embodiment, the X coordinate x 9.47 of the center of the frequency distribution is used as the sample average of the frequency distribution of the center coordinates of the first class grid region in the X axis direction.

In the present embodiment, based on the X coordinate x 9.47, the population average of the X coordinate of the first class grid region in the X axis direction is interval-estimated with a 95% confidence interval. When the frequency distribution of the first class grid region follows a normal distribution, the 95% confidence interval of the population mean is generally expressed by Eq. (3).

Equation (3) is an equation for deriving a 95% confidence interval when the population standard deviation σ (population variance σ ² ) is known. When the population standard deviation σ (population variance σ ² ) is unknown and the population mean is estimated over a confidence interval of a predetermined percentage, the general formula shown by the following equation (4) is used.

k is a parameter that determines a predetermined percentage of the confidence interval. When estimating the confidence interval at 95 percent, the value of k is 1.96. When estimating the confidence interval at 80 percent, the value of k is less than 1.96.

The confidence interval of the population average calculated as described above is the range of the confidence region in the X-axis direction.

There is one grid region of the first class in the Y-axis direction at the Y coordinate y3, one at the Y coordinate y4, two at the Y coordinate y5, two at the Y coordinate y6, and Y. There are two at coordinate y7, three at Y8, three at Y9, three at Y10, one at Y11, and one at Y12. It exists, and there is one at the Y coordinate y13. Therefore, the total number of first-class grid regions in the Y-axis direction is 20 (1 + 1 + 2 + 2 + 2 + 3 + 3 + 3 + 1 + 1 + 1). From equation (1), the center of the frequency distribution in the first class grid region in the Y-axis direction is 8.00. Therefore, the Y coordinate of the center of the frequency distribution in the first class grid region in the Y-axis direction is y8.00. The Y coordinate y8.00 at the center of this frequency distribution is the sample average of the frequency distribution at the center coordinate of the grid region of the first class in the Y-axis direction. Based on the Y coordinate y8.00, the population average of the Y coordinate of the first class grid region in the Y axis direction is interval-estimated with a 95% confidence interval. Since the method for deriving the range of the trust region in the Y-axis direction is the same as the method for deriving the range of the trust region in the X-axis direction, the description thereof will be omitted.

From the above, as shown in FIG. 11, the confidence interval of the population average in the X-axis direction and the confidence interval of the population average in the Y-axis direction are calculated. The range of the confidence region is defined by the confidence space of the population mean in the X-axis direction and the confidence interval of the population mean in the Y-axis direction.

After the trust region is calculated, as shown in FIG. 12, a search region including the trust region and smaller than the sample region is designated in the sample image (step S50).

The dimensions of the search area in the X-axis direction are defined as, for example, the dimensions in which the center of the template is movable in the X-axis direction in the trust region, and the dimensions of the search area in the Y-axis direction are, for example, the center of the template in the trust region. It is defined as a dimension that can be moved in the Y-axis direction.

The search area is specified so that the template center position is arranged in the rectangular area where the trust area in the X-axis direction and the trust area in the Y-axis direction overlap in the XY plane.

After the search area is specified, as shown in FIG. 13, a template that moves the template with respect to the search area and searches for the electronic component C based on the correlation value between the image data of a part of the search area and the template. Matching is performed (step S60).

In the present embodiment, before the detection of the electronic component C based on the above-mentioned template matching method, the position of the mounting area MA of the substrate P before the electronic component C is mounted on the substrate P is detected by the template matching method. .. Based on the position data of the mounting area MA before the electronic component C is mounted on the board P and the position data of the electronic component C after being mounted on the board P, the electronic component C is mounted on the surface of the board P. It is determined whether or not it is correctly mounted on the MA.

As described above, according to the present embodiment, when the sample image is divided into a plurality of grid regions and there are pixels equal to or larger than the threshold value in each of the plurality of grid regions, the center coordinates thereof are acquired and the first axis thereof is acquired. By performing inference statistical processing based on the frequency for each coordinate in the direction and the second axis direction, a reliable region in which the center position AX of the electronic component C may exist is calculated, and a sample is calculated based on the reliable region. A search area smaller than the area is specified, and template matching is performed in the search area. As a result, even if a noise region exists in the sample image, the possibility that the noise region exists inside the search region can be reduced. Therefore, the possibility that the template moves in the noise area is reduced. Therefore, it is possible to prevent the image in the noise region from being erroneously recognized as an image of the electronic component, and to search for the electronic component C with high accuracy based on the template matching method. Therefore, a decrease in inspection accuracy is suppressed.

FIG. 14 is a diagram schematically showing a state in which the template moves the entire sample area. As shown in FIG. 14, when template matching is performed on a wide range of areas, if there is a noise area around the electronic component C, when the template moves in the noise area, the noise area is the electronic component C. It may be misrecognized.

According to the present embodiment, since the minimum required search area can be determined by inference statistical processing, even if a noise area exists, the template is suppressed from moving with respect to the noise area. ..

Further, in the present embodiment, the electronic component C has an electrode Cb showing a high density value in the image data. The confidence region is calculated with the coordinates of the first class grid region including the electrode Cb as the feature region. As a result, the reliable region in which the central position AX of the electronic component C is likely to exist can be estimated with high accuracy.

Further, in the present embodiment, the frequency distribution of the first class grid region is calculated for each of the X-axis direction and the Y-axis direction. The trust region can be calculated with high accuracy based on the frequency distribution.

Further, in the present embodiment, the population average is estimated in a confidence interval of a predetermined percentage, the confidence interval is calculated based on the confidence interval, a search area larger than the confidence area and smaller than the sample area is specified, and the search is performed. Since template matching is performed only inside the region, even if a noise region exists in the sample image, the noise region is not mistakenly recognized as an electronic component, and the electronic component C is based on the template matching method. Can be searched for.

Further, in the present embodiment, the appearance of the electronic component C is line-symmetrical in each of the X-axis direction and the Y-axis direction. Therefore, the center position AX can be accurately detected with the two electrodes Cb arranged line-symmetrically as feature points.

Further, in the present embodiment, the grid area is set to include a plurality of pixels, and when the density value of at least one pixel among the plurality of pixels included in one grid area is equal to or more than a threshold value, the grid is used. The area is determined to be the first class grid area. Therefore, it is easy to determine whether or not it is the first class grid area, and the load of arithmetic processing such as frequency distribution calculation and section estimation is reduced.

In the above-described embodiment, the image of the electronic component C after being mounted on the substrate P is imaged by the imaging device 14, and it is inspected whether or not the electronic component C is correctly mounted in the mounting area MA. explained. When the image pickup device 9 captures an image of the electronic component C held by the nozzle 10 and before being mounted on the substrate P and the identification or position of the electronic component C is detected, the electronic component described in the above-described embodiment is described. The inspection of the electronic component C may be carried out based on the inspection method. The imaging device 9 images the electronic component C held by the nozzle 10 from below. In that case, a part of the nozzle 10 around the electronic component C may be reflected, or a part of the mounting head 7 may be reflected. A part of the nozzle 10 or a part of the mounting head 7 becomes a noise component, and there is a possibility that the noise component is erroneously recognized as an electronic component C. By inspecting the electronic component C before being mounted on the substrate P by using the image pickup apparatus 9 based on the electronic component inspection method described in the above-described embodiment, the deterioration of the inspection accuracy is suppressed.

In the above-described embodiment, the chip-type electronic component in which the electronic component C does not have a lead is inspected. A lead-type electronic component (insertion-type electronic component) having a lead as shown in FIG. 15 may be inspected. The lead type electronic component is mounted on the substrate P by inserting the lead into the opening of the substrate P. The electronic component C2 shown in FIG. 15 has a body Ca2 and an electrode Cb2, similarly to the electronic component C described in the above-described embodiment. The appearance of the electronic component C2 in the XY plane is substantially axisymmetric in each of the X-axis direction and the Y-axis direction. The appearance of the electronic component C2 is substantially axisymmetric with respect to the reference line Ly that passes through the center position AX of the electronic component C in the XY plane and is parallel to the Y axis. Similarly, the appearance of the electronic component C2 is substantially axisymmetric with respect to the reference line Lx passing through the center position AX and parallel to the X axis. The electronic component C2 as shown in FIG. 15 is also inspected with high inspection accuracy by the electronic component inspection method according to the above-described embodiment.

1 Base 2 Board transport device 2R Transport path 3 Drive system 4 Electronic component supply device 5 Parts feeder 6 X-axis drive device 6G Guide member 7 Mounting head 8 Y-axis drive device 9 Imaging device 10 Nozzle 11 Nozzle shaft 12 θZ drive device 13 Z-axis drive device 14 Imaging device 15 Camera 16 Base member 17 Holder 18 Ball screw 20 Control device 21 Mounting control unit 22 Image data acquisition unit 23 Grid area setting unit 24 Concentration value acquisition unit 25 Judgment unit 26 Estimated statistical processing unit 27 Search area Setting unit 28 Storage unit 29 Template matching unit 30 Input / output unit 100 Electronic component mounting device 200 Control system AX Center position C, C2 Electronic component Ca, Ca2 Body Cb, Cb2 Electrode HP Solder paste MA Mounting area P Board SA Peripheral area

Claims (6)

Acquiring a sample image showing an image of a sample area including electronic components with an imaging device, and
Dividing the sample image acquired by the image pickup apparatus into a plurality of grid areas and
Acquiring the coordinates of the first-class grid area in which pixels having a density value equal to or higher than the threshold value exist among the plurality of grid areas,
Statistical inference processing is performed based on the coordinates of the first class grid region to calculate a reliable region in which the center position of the electronic component may exist in the sample image.
In the sample image, a search area including the trust area and smaller than the sample area is specified.
Move the template for the search area, seen including a and to explore the electronic component on the basis of the correlation value between the part of the image data and the template of the search area,
The sample image has a plurality of coordinates defined in the first axial direction of a predetermined surface parallel to the sample region, and a plurality of coordinates defined in the second axial direction of the predetermined surface orthogonal to the first axial direction. It is divided by the grid area associated with each of
For each of the plurality of grid areas, it is determined whether or not there are pixels having a density value equal to or higher than the threshold value in the grid area.
For each of the coordinates in the first axis direction, the frequency of the coordinates of the first class grid area among the plurality of grid areas in the second axis direction is acquired.
For each of the coordinates in the second axis direction, the frequency of the coordinates of the first class grid area among the plurality of grid areas in the first axis direction is acquired.
To calculate the range of the trust region in the first axis direction based on the frequency of the coordinates of the first class grid region acquired for each coordinate in the first axis direction.
Including calculating the range of the trust region in the second axis direction based on the frequency of the coordinates of the first class grid region acquired for each coordinate in the second axis direction.
The calculation of the range of the confidence region in the first axis direction is performed by calculating the sample average using the coordinates of the first class grid region acquired for each coordinate in the first axis direction as a sample and calculating the sample average in the first axis direction. Including the interval estimation of the population mean of the concentration values in the above with a confidence interval of a predetermined percentage.
The calculation of the range of the confidence region in the second axis direction is performed by calculating the sample average using the coordinates of the first class grid region acquired for each coordinate in the second axis direction as a sample and calculating the sample average in the second axis direction. Including the interval estimation of the population mean of the concentration values in the above with a confidence interval of a predetermined percentage.
The range of the confidence region is defined by the confidence interval in the first axial direction and the confidence interval in the second axial direction.
Electronic component inspection method. The electronic component has electrodes and
The confidence region is calculated with the coordinates of the first class grid region including the electrodes as a feature region.
The electronic component inspection method according to claim 1. The appearance of the electronic component is substantially axisymmetric in each of the first axial direction and the second axial direction of the predetermined surface parallel to the sample region.
The electronic component inspection method according to claim 1 or 2 . The grid region includes a plurality of pixels of the image pickup device of the image pickup apparatus.
When the density value of at least one pixel among the plurality of pixels included in one grid region is equal to or greater than the threshold value, it is determined that the density value of the grid region is equal to or greater than the threshold value.
Electronic component testing method according to any one of claims 1 to 3. A method for mounting an electronic component, which comprises inspecting the electronic component by the electronic component inspection method according to any one of claims 1 to 4 . A mounting head that has a nozzle for holding electronic components and can mount the electronic components on a substrate,
An imaging device that acquires a sample image showing an image of a sample region including the electronic component, and
A grid area setting unit that divides the sample image acquired by the image pickup apparatus into a plurality of grid areas, and
A density value acquisition unit that acquires coordinates of a first-class grid region in which pixels having a density value equal to or higher than a threshold value are present among the plurality of grid regions.
An inference statistical processing unit that calculates a reliable region in which the center position of the electronic component may exist in the sample image based on the coordinates of the first class grid region.
In the sample image, a search area setting unit that includes the trust area and specifies a search area smaller than the sample area.
A storage unit that stores a template indicating the electronic component,
A template matching unit that moves a template with respect to the search area and searches for the electronic component based on a correlation value between a part of image data in the search area and the template is provided .
The grid area setting unit sets the sample image on a plurality of coordinates defined in the first axial direction of a predetermined surface parallel to the sample area, and the second axial direction of the predetermined surface orthogonal to the first axial direction. Divide into the grid area associated with each of the plurality of coordinates specified in
For each of the plurality of grid areas, a determination unit for determining whether or not a pixel having a density value equal to or higher than a threshold value exists in the grid area is provided.
The density value acquisition unit acquires the frequency of the coordinates of the first class grid area among the plurality of grid areas in the second axis direction for each coordinate in the first axis direction, and the coordinates in the second axis direction. For each, the frequency of the coordinates of the first class grid area among the plurality of grid areas in the first axis direction is acquired.
The estimation statistical processing unit calculates the range of the trust region in the first axis direction based on the frequency of the coordinates of the first class grid region acquired for each coordinate in the first axis direction, and the first The range of the trust region in the second axis direction is calculated based on the frequency of the coordinates of the first class grid region acquired for each coordinate in the two axis directions.
The calculation of the range of the confidence region in the first axis direction is performed by calculating the sample average using the coordinates of the first class grid region acquired for each coordinate in the first axis direction as a sample and calculating the sample average in the first axis direction. Including the interval estimation of the population mean of the concentration values in the above with a confidence interval of a predetermined percentage.
The calculation of the range of the confidence region in the second axis direction is performed by calculating the sample average using the coordinates of the first class grid region acquired for each coordinate in the second axis direction as a sample and calculating the sample average in the second axis direction. Including the interval estimation of the population mean of the concentration values in the above with a confidence interval of a predetermined percentage.
The range of the confidence region is defined by the confidence interval in the first axial direction and the confidence interval in the second axial direction.
Electronic component mounting device.

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