Particle size distribution measuring apparatus and particle size distribution measuring method

Abstract

To accurately measure a particle size distribution even if an aggregate contains objects of various shapes.SOLUTION: A particle size distribution measurement device (MD) according to the present disclosure includes an image capturing unit (10) that captures an image of a bone material (200) falling from a conveying device (CD), a projection unit (20) that projects a two dimensional pattern in a range captured by the image capturing unit (10), a three dimensional information acquisition unit (310) that acquires three dimensional information from the image captured by the image capturing unit (10), and a particle size distribution calculation unit (320) that calculates a particle size distribution of the bone material (200) from the three dimensional information, in which the two dimensional pattern includes a plurality of dot patterns whose positions on the image can be uniquely specified.SELECTED DRAWING: Figure 3

Description

[Technical Field]

[0001] The present disclosure relates to a particle size distribution measuring device and a particle size distribution measuring method. [Background technology]

[0002] When constructing civil engineering structures such as dams, materials obtained from quarry mines are often used as aggregate. For example, the CSG (Cemented Sand and Gravel) method uses locally-sourced materials mixed with cement and water (CSG material) to construct structures. This method allows for the effective use of locally-sourced materials, eliminating the need for classification, grading, or cleaning, and simply removing and crushing oversized objects. While the CSG method offers advantages such as material rationalization, low cost, and environmental conservation, it also requires inspection to ensure that the materials meet the required quality. Quality control of CSG material involves sieving tests performed approximately once per hour to ensure that the CSG material's grain size is within a specified range. However, manual sieving tests are labor-intensive and time-consuming, and because they involve random sampling, the test results do not necessarily represent the grain size distribution of the entire CSG material. Therefore, the following methods have been proposed to simply monitor the grain size of CSG material.

[0003] Patent Document 1 discloses a method of binarizing an image to identify its contour, converting it into a sphere or cube based on the contour, calculating the mass by multiplying the volume of the sphere or cube by its specific gravity, and creating a particle size distribution. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] Japanese Patent Application Laid-Open No. 2003-10726 Summary of the Invention [Problem to be solved by the invention]

[0005] However, the method described in Patent Document 1 estimates the volume using the outline of the aggregate on the image plane. Therefore, the length in the depth direction is not taken into consideration, and there is a problem that the accuracy of measuring the particle size distribution deteriorates when the aggregate includes objects of various shapes.

[0006] The present disclosure has been made in consideration of the above-mentioned problems, and aims to accurately measure particle size distribution even when aggregate contains objects of various shapes. [Means for solving the problem]

[0007] In order to solve the above problems, a particle size distribution measuring device according to one embodiment of the present disclosure includes an imaging unit that captures an image of aggregates falling from a conveying device, a projection unit that projects a two-dimensional pattern into the area captured by the imaging unit, a three-dimensional information acquisition unit that acquires three-dimensional information from the image captured by the imaging unit, and a particle size distribution calculation unit that calculates the particle size distribution of the aggregates from the three-dimensional information, and the two-dimensional pattern is configured to be composed of a plurality of dot patterns that can uniquely identify a position on the image.

[0008] In order to solve the above-mentioned problems, a particle size distribution measuring method according to one embodiment of the present disclosure is a method including an imaging step of imaging aggregates falling from a conveying device, a projection step of projecting a two-dimensional pattern onto the area imaged in the imaging step, a three-dimensional information acquisition step of acquiring three-dimensional information from the image captured in the imaging step, and a particle size distribution calculation step of calculating the particle size distribution of the aggregates from the three-dimensional information, wherein the two-dimensional pattern is composed of a plurality of dot patterns that can uniquely identify a position on the image. [Effects of the Invention]

[0009] According to one aspect of the present disclosure, the particle size distribution can be accurately measured even if the aggregate contains objects of various shapes. [Brief explanation of the drawings]

[0010] [Figure 1] 1 shows an example of the configuration of a particle size distribution measuring system according to a first embodiment of the present disclosure. [Figure 2] 2 shows an example of the placement of the first imaging unit shown in FIG. 1. [Figure 3] FIG. 2 is a functional block diagram showing in more detail the configuration of the particle size distribution measuring device shown in FIG. [Figure 4] 2 shows an example of a two-dimensional pattern projected by the projection unit shown in FIG. [Figure 5] An example of the configuration of the multiple dot patterns shown in FIG. 4 is shown. [Figure 6] An example of variations of the multiple dot patterns shown in FIG. 4 is shown below. [Figure 7] An example of processing by the three-dimensional information acquisition unit shown in FIG. 3 will be described below. [Figure 8] An example of a method for calculating the distance in the depth direction from the first imaging unit to the dot pattern on the aggregate will be described. [Figure 9] 10 shows an example of coordinates of a dot pattern on a first image. [Figure 10] An example of coordinates on the aggregate of a dot pattern is shown. [Figure 11] 10 shows an example of a method for calculating the coordinate components in the width direction of the dot pattern on the aggregate relative to the first imaging unit. [Figure 12] An example of processing by the particle size distribution calculation unit shown in FIG. 3 will be described below. [Figure 13] 1 shows an example of object occlusion. [Figure 14] An example of particle size distribution display is shown below. [Figure 15] The process flow of the particle size distribution measurement system shown in FIG. 1 is shown below. [Figure 16] An example of detecting impurities is shown below. [Figure 17] FIG. 10 is a functional block diagram showing an example of the configuration of a particle size distribution measuring system according to a second embodiment of the present disclosure. [Figure 18] An example of processing by the three-dimensional information acquisition unit shown in FIG. 17 will be described below. [Figure 19] 10 shows an example of the configuration of a particle size distribution measuring system according to a third embodiment of the present disclosure. [Figure 20]FIG. 20 is a functional block diagram showing in more detail the configuration of the particle size distribution measuring device MD shown in FIG. 19. [Figure 21] 19 shows line height information acquired by the line height information acquisition unit shown in FIG. [Figure 22] 10 shows an example of the total volume on the conveying device based on line height information and the sum of the volumes for each particle size. [Figure 23] An example of processing by the particle size distribution calculation unit shown in FIG. 20 will be described below. [Figure 24] An example of particle size distribution display is shown below. [Figure 25] 20 shows a process flow of the particle size distribution measuring system shown in FIG. 19. DETAILED DESCRIPTION OF THE INVENTION

[0011] [Embodiment 1] (Configuration of particle size distribution measurement system) FIG. 1 shows an example of the configuration of a particle size distribution measuring system according to a first embodiment of the present disclosure. As shown in FIG. 1, the particle size distribution measuring system MS according to the first embodiment includes a particle size distribution measuring device MD and an output device OU. The particle size distribution measuring device MD includes a first imaging unit 10 (imaging unit), a projection unit 20, and a calculation device 30. As the output device OU, a display device 101, a speaker 102, a signal light 103, and the like are connected to the particle size distribution measuring device MD as needed. The output device OU is not limited to being externally attached to the particle size distribution measuring device MD, but may also be built into the particle size distribution measuring device MD. Note that the scales of parts, structures, and the like in the drawings accompanying this disclosure are for clarity and may differ from the actual scales.

[0012] The particle size distribution measurement system MS is installed in association with a conveying device CD that conveys the aggregate. The conveying device CD may be a belt conveyor. The conveying device CD is included in the aggregate production system PS, for example, and is controlled by a control device CU.

[0013] (Arrangement of the first imaging unit and the projection unit) Fig. 2 shows an example of the installation of the first imaging unit shown in Fig. 1. As shown in Fig. 2, the first imaging unit 10 is installed at a position where it can capture an image of the aggregate 200 falling from the conveying device CD. It is preferable that the first imaging unit 10 is positioned approximately directly opposite the falling surface (parallel to the ZY plane in Fig. 2) described by the falling aggregate 200. Specifically, it is preferable that the optical axis of the first imaging unit 10 passes through or near the center of the width direction (Y direction in Fig. 2) of the falling surface and is approximately perpendicular to the falling surface.

[0014] The projection unit 20 is installed in a position where it projects a two-dimensional pattern onto the imaging range R1 of the first imaging unit 10 (or onto the aggregates 200 passing through). It is preferable that the projection unit 20 also faces approximately directly toward the falling surface of the falling aggregates 200. The relative position of the projection unit 20 with respect to the first imaging unit 10 is measured in advance. The projection unit 20 may be a projector that modulates light emitted from a light source according to image information and projects the modulated light onto a projection surface to display an image. The projection range of the projection unit 20 only needs to at least partially overlap with the imaging range R1 of the first imaging unit 10.

[0015] (Configuration of particle size distribution measuring device) Fig. 3 is a functional block diagram showing in more detail the configuration of the particle size distribution measuring device shown in Fig. 1. As shown in Fig. 3, the particle size distribution measuring device MD according to the first embodiment of the present disclosure includes a first imaging unit 10 that captures an image of aggregate 200 falling from a conveying device CD, a projection unit 20 that projects a two-dimensional pattern into an imaging range R1 captured by the first imaging unit 10, a three-dimensional information acquisition unit 310 that acquires three-dimensional information from the first image captured by the first imaging unit 10, and a particle size distribution calculation unit 320 that calculates the particle size distribution of the aggregate 200 from the acquired three-dimensional information.

[0016] (2D pattern configuration) Fig. 4 shows an example of a two-dimensional pattern projected by the projection unit shown in Fig. 1. As shown in Fig. 4, the projected two-dimensional pattern 400 is made up of a plurality of dot patterns 410(0) to 410(M) that can uniquely identify positions on the two-dimensional pattern 400. Here, M is an integer equal to or greater than 1. The first image is an image obtained by capturing the two-dimensional pattern 400 projected onto the aggregate 200. Therefore, the two-dimensional pattern 400 is made up of a plurality of dot patterns 410(1) to 410(M) that can uniquely identify positions on the first image.

[0017] One dot pattern 410 may have a size of 3×3 pixels or more, and may be set so that the color combination of the pixels that make up the dot pattern 410 is unique within the two-dimensional pattern 400. In other words, the multiple dot patterns 410 that make up the two-dimensional pattern 400 may all be designed to be different from one another.

[0018] Fig. 5 shows an example of the configuration of the multiple dot patterns shown in Fig. 4. As shown in Fig. 5, each of the dot patterns 410(1) to 410(M) is made up of 3 blocks x 3 blocks, and includes eight blocks A0 to A7 that are either red, green, or blue, and a white block A8 that is surrounded by the blocks A0 to A7. One block may correspond to one pixel, or may correspond to multiple adjacent pixels.

[0019] FIG. 6 shows an example of a variation of the multiple dot patterns shown in FIG. 4. In FIG. 6, white is represented by "W," red by "R," green by "G," and blue by "B." Dot patterns 410(0) through 410(M) can be distinguished by the color combinations of blocks A0 through A7. This color combination can be interpreted as a ternary numerical value. For example, block A0 is the least significant digit, block A7 is the most significant digit, and red is considered to be 0, green is considered to be 1, and blue is considered to be 2. Dot patterns 410(0) through 410(3) represent 0 through 3 in decimal notation. For example, in two-dimensional pattern 400, dot pattern 410(0), which represents 0, is placed in the upper left corner, and dot patterns 410(2) through 410(M) are placed from left to right (in the +Y direction in FIG. 4) so ​​that the numerical value represented by dot pattern 410 increases by 1. Using any integer m between 0 and M, the numerical value indicated by dot pattern 410(m) is unique in two-dimensional pattern 400. Therefore, the position of dot pattern 410(m) in two-dimensional pattern 400 that corresponds to dot pattern 410(m) in the first image can be easily found.

[0020] (Processing by arithmetic unit) 3 again, the first imaging unit 10 captures a first image of the aggregate 200 and the two-dimensional pattern 400 projected onto the surface of the aggregate 200 and sends it to the calculation device 30. Then, the calculation device 30 estimates the particle size distribution from the first image.

[0021] The functions of the arithmetic device 30 can be realized by a program for causing a computer to function as the device, and a program for causing a computer to function as each block of the device (for example, a three-dimensional information acquisition unit 310, a particle size distribution calculation unit 320, and first to fourth warning units 331 to 334).

[0022] In this case, the arithmetic device 30 includes a computer having at least one processing device and at least one storage device as hardware for executing the program. This processing device may be configured as a CPU (Central Processing Unit), a GPU (Graphic Processing Unit), an NPU (Nural network Processing Unit), or a combination thereof. By executing the program using this processing device and storage device, each function described in this embodiment and the following embodiments is realized.

[0023] The program may be non-transitory and may be recorded on one or more computer-readable recording media. The recording media may or may not be included in the device. In the latter case, the program may be supplied to the device via any wired or wireless transmission medium.

[0024] In addition, some or all of the functions of each of the above blocks can be realized by logic circuits. For example, integrated circuits in which logic circuits that function as each of the above blocks are formed are also included in the scope of the present disclosure. In addition, the functions of each of the above control blocks can also be realized by, for example, a quantum computer.

[0025] (Processing by 3D information acquisition unit) Fig. 7 shows an example of processing by the three-dimensional information acquisition unit shown in Fig. 3. Referring to Fig. 3, three-dimensional information acquisition unit 310 may include a first search unit 312 and a coordinate calculation unit 314. As shown in Fig. 7, first search unit 312 searches for each dot pattern 410 so as to identify the position of that dot pattern 410 on the first image (step S100).

[0026] In step S100, the first search unit 312 detects the dot pattern 410 from the first image and obtains its position (step S110). Specifically, the first search unit 312 detects a feature common to the multiple dot patterns 410, namely, the white block A8. The first search unit 312 also obtains the center coordinates of the white block A8 in the first image and sets these center coordinates as the position of the dot pattern 410 on the first image.

[0027] Next, first search unit 312 determines the numerical value indicated by detected dot pattern 410 (step S120). Specifically, for each detected block A8, the area of ​​the first image corresponding to each of blocks A0 to A7 surrounding block A8 is scanned, and the color that occupies the largest area in each area (red, green, and blue) is determined as the color of the block corresponding to that area. Then, as described above with reference to FIG. 6, the numerical value indicated by dot pattern 410 is determined based on the color combination of blocks A0 to A7.

[0028] Next, for each dot pattern 410 whose position on the first image has been identified, the coordinate calculation unit 314 calculates the three-dimensional coordinates of the position of the dot pattern 410 on the aggregate 200 based on the position of the dot pattern 410 on the first screen, the position of the dot pattern 410 on the two-dimensional pattern 400, and the position of the projection unit 20 relative to the first imaging unit 10 (step S200).

[0029] In step S200, the coordinate calculation unit 314 sets m=0 (step S210) and determines whether the position on the first image of the dot pattern 410(m) indicating the numerical value m has been identified (step S220). If the position on the first image has been identified (Yes in step S220), the coordinate calculation unit 314 calculates the three-dimensional coordinates of the position on the aggregate 200 of the dot pattern 410(m) indicating the numerical value m (step S230). This calculation will be described in detail later.

[0030] If the position on the first image has not been identified (No in step S220), the coordinate calculation unit 314 leaves it as is, or if the position on the first image has been identified (Yes in step S220), after executing step S230, increments the numerical value m by 1 (step S240). If the numerical value m is equal to or less than the maximum numerical value M that can be represented by the dot pattern 410 (No in step S250), the process returns to step S220. On the other hand, if the numerical value m exceeds the maximum numerical value M (Yes in step S250), the coordinate calculation unit 314 sends three-dimensional information including the three-dimensional coordinates on the aggregate of each dot pattern 410 whose position on the first image has been identified to the particle-size distribution calculation unit 320 (step S260).

[0031] (Calculation of 3D coordinates of dot pattern on aggregate) FIG. 8 shows an example of a method for calculating the depth direction distance from the first imaging unit to a dot pattern on an aggregate. As shown in FIG. 8, based on the position of a certain dot pattern 410(m) on the first screen and the position of the projection unit 20 relative to the first imaging unit 10, an angle α can be calculated between the line connecting the dot pattern 410(m) and the first imaging unit 10 and the line connecting the projection unit 20 and the first imaging unit. Similarly, based on the position of the dot pattern 410(m) on the two-dimensional pattern 400 and the position of the projection unit 20 relative to the first imaging unit 10, an angle β can be calculated between the line connecting the dot pattern 410(m) and the projection unit 20 and the line connecting the projection unit 20 and the first imaging unit. Then, based on the position of the projection unit 20 relative to the first imaging unit 10, the linear distance connecting the first imaging unit 10 and the projection unit 20 can be calculated.

[0032] Based on the angle α, the angle β, and the linear distance, that is, by triangulation, the distance |Dx| in the depth direction (X direction in FIG. 8) from the first imaging unit 10 to the dot pattern 410(m) can be calculated, where |Dx| represents the absolute value of the value Dx.

[0033] 9 shows an example of the coordinates of the dot pattern on the first image. As shown in FIG. 9, the position of the dot pattern 410 on the first image is expressed in an image coordinate system with a corner of the first image as the origin. The image coordinate system may be a YZ Cartesian coordinate system. The position of the dot pattern 410 on the first image in the image coordinate system is represented by coordinates (u, v), and the width and height of the first image are represented by w and h.

[0034] Fig. 10 shows an example of coordinates of a dot pattern on an aggregate. As shown in Fig. 10, the position of the dot pattern 410 on the aggregate 200 is expressed in a camera coordinate system with the optical center of the lens unit of the first imaging unit 10 as the origin. The camera coordinate system may be an XYZ Cartesian coordinate system. The position of the dot pattern 410 on the aggregate 200 in the camera coordinate system is defined as coordinates (Dx, Dy, Dz). The absolute value of the coordinate component Dx in the depth direction (X direction) is the distance |Dx| calculated by triangulation. The positive and negative values ​​of the coordinate components Dx, Dy, Dz in each direction depend on the orientation of the XYZ axes in the camera coordinate system.

[0035] FIG. 11 shows an example of a method for calculating the width direction coordinate components of the dot pattern on the aggregate relative to the first imaging unit. For simplicity, an example will be described in which the optical axis of the lens unit 11 is a line parallel to the X direction passing through the center of the first image, the Y direction of the image coordinate system is parallel to the Y direction of the lens coordinate system, and the Z direction of the image coordinate system is parallel to the Z direction of the lens coordinate system. As shown in FIG. 11, the first imaging unit 10 includes the lens unit 11 and an imaging element 12. The focal length f of the first imaging unit 10 corresponds to the distance in the depth direction (the X direction in FIG. 11) between the optical center of the lens unit 11 and the imaging surface of the imaging element 12. The lens unit 11 may include one or more lenses, and may also include a prism and a mirror as appropriate. A first image is projected onto the imaging surface of the imaging element 12.

[0036] FIG. 11 shows two triangles. One is a right-angled triangle whose hypotenuse is a line segment connecting the optical center of the lens unit 11 and the position of the dot pattern 410(m) on the aggregate 200. The other is a right-angled triangle whose hypotenuse is a line segment connecting the optical center of the lens unit 11 and the position of the dot pattern 410(m) on the first image. These two triangles are similar. Therefore, the position of the dot pattern 410 on the first image is related to the position of the dot pattern 410 on the aggregate 200 through the similarity of the triangles. Specifically, with respect to the coordinate component Dy in the width direction (Y direction in FIG. 2, etc.) of the dot pattern 410(m) on the aggregate 200 relative to the first imaging unit 10, the following equation (1) holds, and equation (2) is derived. Note that the positive and negative values ​​may change depending on the orientation of the coordinate axes.

[0037]

number

[0038]

number

[0039] (Processing by particle size distribution calculation unit) Fig. 12 shows an example of processing by the particle size distribution calculation unit shown in Fig. 3. As shown in Fig. 12, particle size distribution calculation unit 320 calculates the particle size distribution of aggregate 200 based on the three-dimensional information provided from three-dimensional information acquisition unit 310. This three-dimensional information includes three-dimensional coordinates indicating the position on the aggregate of each dot pattern 410 whose position on the first image has been identified.

[0040] The particle size distribution calculation unit 320 first labels the three-dimensional coordinates of the positions of the dot patterns 410 on the aggregate 200 (step S300). In step S300, a labeling process is performed such that the same label is assigned to the coordinates of the dot patterns 410 projected onto the same object among the multiple objects 210 included in the aggregate 200, and different labels are assigned to the coordinates of the dot patterns 410 projected onto different objects. For such a labeling process, it is preferable that the multiple objects included in the aggregate 200 are separated from each other. Compared to the aggregate 200 flowing on the conveying device CD, it can be expected that the objects 210 included in the falling aggregate 200 are separated from each other.

[0041] Next, the particle size distribution calculation unit 320 determines the volume and particle size of each of the plurality of objects 210 contained in the aggregate 200 (step S400).

[0042] As an example of step S400, the particle size distribution calculation unit 320 sets one of the labels assigned to the coordinates as a target label (step S410), and creates a convex hull of the set of three-dimensional coordinates to which the target label has been assigned (step S420). The convex hull is the smallest convex set that includes the set of three-dimensional coordinates to which the same label has been assigned. The convex hull can be created by an algorithm using the Quickhull method, for example. Then, the particle size distribution calculation unit 320 calculates the volume of the convex hull (step S422). The convex hull created by the algorithm using the Quickhull method is composed of a plurality of tetrahedrons. The sum of the volumes of these tetrahedrons is calculated as the volume of the entire convex hull.

[0043] FIG. 13 shows an example of object occlusion. As shown in FIG. 13, when an object 210 included in an aggregate 200 is photographed, occlusion by the object 210 itself occurs. A front section 212 of the object 210, which is closer to the first image capture unit 10, exactly hides a rear section 214 of the object 210, which is farther from the first image capture unit 10. The volume of the front section 212 of the object 210 corresponding to the target label corresponds to the volume of the convex hull. The orientation of the object 210 in the falling aggregate 200 is assumed to be random, and the expected value of the volume of the rear section 214 is the volume of the front section 212 multiplied by a given coefficient.

[0044] 12 again, the particle size distribution calculation unit 320 therefore calculates the volume of the corresponding object 210 based on the volume of the convex hull (step S424). In step S424, for example, the volume of the convex hull is set to the volume of the front section 212, the volume of the back section 214 is set to the value obtained by multiplying the volume of the convex hull by a given coefficient, and the sum of the volumes of the front section 212 and the back section 214 is calculated as the volume of the object 210. The particle size distribution calculation unit 320 may calculate the volume of the object 210 corresponding to the target label using other methods. For example, the three-dimensional information may be converted into voxels, and the volume may be calculated from the voxels.

[0045] The particle size distribution calculation unit 320 also determines the particle size in parallel with, or before or after, the calculation of the volume. The particle size distribution calculation unit 320 determines a circumscribing rectangle of the set of three-dimensional coordinates to which the target label has been assigned (step S430). The circumscribing rectangle is the smallest rectangular parallelepiped that includes the set of three-dimensional coordinates to which the same label has been assigned, and each side is parallel to one of the X, Y, and Z axes.

[0046] Referring again to FIG. 13 , the front section 212 is located inside the circumscribing rectangle 1300 and is in contact with the circumscribing rectangle 1300. Therefore, the lengths of the front section 212 in the X, Y, and Z directions are equal to the lengths Lx, Ly, and Lz of the circumscribing rectangle 1300 in the X, Y, and Z directions, respectively. The rear section 214 is completely hidden by the front section 212. Therefore, the lengths of the rear section 214 in the width direction (Y direction) and the gravity direction (Z direction) are equal to the lengths of the front section 212 in the width direction and the gravity direction. If it is understood that the orientation of the object 210 in the falling aggregate 200 is random, the expected value of the length of the rear section 214 in the depth direction (X direction) is the length of the front section 212 in the depth direction multiplied by a given coefficient.

[0047] 12 again, the particle size distribution calculation unit 320 calculates the lengths in the X, Y, and Z directions of the object 210 corresponding to the target label based on the circumscribing rectangle 1300 (steps S432, S434, and S436). In step S432, the length Lx of the depth direction side of the circumscribing rectangle 1300 is set to the length of the front section 212 in the depth direction, and the value obtained by multiplying the length Lx of the depth direction side of the circumscribing rectangle 1300 by a given coefficient is set to the length of the rear section 214 in the depth direction, and the sum of the lengths of the front section 212 and the rear section 214 in the depth direction is calculated as the length of the object 210 in the depth direction. In step S434, the length Ly of the width direction side of the circumscribing rectangle 1300 is calculated as the length of the object 210 in the width direction. In step S436, the length Lz of the gravity direction side of the circumscribing rectangle 1300 is calculated as the length of the object 210 in the gravity direction.

[0048] The particle size distribution calculation unit 320 compares the three calculated lengths, and determines the maximum length as the "major diameter," the minimum length as the "minor diameter," and the intermediate length as the "medium diameter." The unit then determines the medium diameter as the particle size of the object 210 corresponding to the target label (step S438). After calculating the volume and determining the particle size, the particle size distribution calculation unit 320 checks whether all labels have been set as target labels (step S450). If there are any unset labels among the target labels (No in step S450), the process returns to step S410, sets the unset labels as target labels, and repeats the calculation of the volume and the determination of the particle size. On the other hand, if all labels have been set as target labels (Yes in step S540), the sum of the volumes for each particle size is calculated (step S510). In step S510, the objects 210 contained in the aggregate 200 may be classified based on particle size, and the sum of the volumes of the objects 210 belonging to each class may be calculated for each class.

[0049] The particle size distribution calculation unit 320 then calculates the sum of masses for each particle size (step S520). In step S520, the sum of volumes is multiplied by a given surface dry density to convert the sum of volumes into the sum of masses. The surface dry density is a value stored in advance in a recording medium built into or external to the calculation device 30, and is, for example, 2.5 g / cm. 3 etc. Then, the particle size distribution calculation unit 320 calculates the sum of the masses of all particle sizes (step S530) and calculates the passing mass percentage (step S540). The passing mass percentage is the ratio of the mass of objects 210 that are equal to or smaller than a particle size category to the total mass. For example, the mass percentages of particle sizes of 0.6 mm or smaller, 1.0 mm or smaller, 2.0 mm or smaller, etc. are calculated.

[0050] The particle size distribution calculation unit 320 further creates a graph or table of the particle size distribution of the aggregate 200 from the particle size and the passing mass percentage (step S550), and sends the graph or table to the output device OU (step S560). The particle size distribution is the passing mass percentage relative to the particle size.

[0051] As described above, the configuration according to the present disclosure obtains three-dimensional information including depth information from the image captured by the imaging unit 10, and measures the particle size distribution of the aggregate 200 based on this three-dimensional information. As a result, compared to a configuration that measures particle size distribution based on two-dimensional information that does not include depth information (for example, the configuration disclosed in Japanese Patent Application Laid-Open No. 2003-10726), the configuration according to the present disclosure has the advantage of being able to accurately calculate the particle size distribution even if the shapes of the objects 210 in the aggregate 200 are diverse.

[0052] (display of particle size distribution) Fig. 14 shows an example of a particle size distribution display. As shown in Fig. 14, the particle size distribution calculation unit 320 may create a graph to display the calculated particle size distribution 1401 together with a specified value. Here, the specified value has a lower limit of the coarsest particle size distribution 1402 and an upper limit of the finest particle size distribution 1403. If the calculated particle size distribution 1401 deviates from the specified value, the particle size distribution calculation unit 320 may output a warning via an output device.

[0053] (Processing flow of particle size distribution measurement system) Fig. 15 shows the flow of processing in the particle size distribution measuring system shown in Fig. 1. As shown in Fig. 15, the projection unit 20 projects a two-dimensional pattern 400 onto the aggregate 200 dropping from the conveying device CD (step S600, projection step), and the first imaging unit 10 captures an image of the aggregate 200 onto which the two-dimensional pattern 400 is projected (step S602, imaging step). The first imaging unit 10 sends the first image to the calculation device 30.

[0054] In the calculation device 30, the three-dimensional information acquisition unit 310 detects the dot pattern 410 on the first image, calculates the distance to the dot pattern 410 on the aggregate 200 based on triangulation from the positional relationship between the first imaging unit 10, the projection unit 20, and the dot pattern 410, and further calculates three-dimensional information of the dot pattern 410 (step S604, three-dimensional information acquisition step). The three-dimensional information acquisition unit 310 sends the three-dimensional information to the particle-size distribution calculation unit 320.

[0055] The particle size distribution calculation unit 320 calculates the volume for each particle size from the received three-dimensional information, multiplies the volume by the surface dry density to convert it to mass, and calculates the passing mass percentage for each particle size range (step S606, particle size distribution calculation step). The particle size distribution calculation unit 320 sends the particle size distribution, or a table or graph of the particle size distribution, to the output device OU.

[0056] The output device OU includes the display device 101, which displays the particle size distribution (step S608).

[0057] As described above, the particle size distribution measurement method according to the present disclosure includes an imaging process of photographing aggregate 200 falling from conveying device CD, a projection process of projecting a two-dimensional pattern 400 onto the range R1 photographed in the imaging process, a three-dimensional information acquisition process of acquiring three-dimensional information from the first image photographed in the projection process, and a particle size distribution calculation process of calculating the particle size distribution of aggregate 200 from the three-dimensional information acquired in the three-dimensional information acquisition process, and the two-dimensional pattern 400 is composed of a plurality of dot patterns that can uniquely identify a position on the image.

[0058] Because the two-dimensional pattern 400 is composed of a plurality of dot patterns 410 whose positions can be uniquely identified, it is easy to associate the dot patterns 410 in the first image captured by the first imaging unit 10 with the dot patterns 410 in the two-dimensional pattern 400 projected by the projection unit 20. By performing the series of processes shown in Fig. 15, it is possible to associate the first image with the two-dimensional pattern 400 and acquire three-dimensional information about the aggregate 200 at high speed and with high density. Furthermore, even if the aggregate 200 includes objects 210 of various shapes, it is possible to measure the particle size distribution.

[0059] The particle size distribution measurement system may repeatedly execute the series of processes shown in FIG. 15. In this process, the projection unit 20 continuously projects the two-dimensional pattern 400 onto the aggregate 200, and the first imaging unit 10 continuously captures the aggregate 200. Continuously capturing images means capturing first images at a given time interval. For example, by setting the time interval between captures longer than the time it takes for the object 210 to pass through the capture range R1, the first images can be captured with minimal overlap. Minimal overlap between first images means that the proportion of the object 210 captured in one first image that is also captured in another first image is small or zero. Reducing the overlap between first images can reduce the need to capture and measure the same object 210 multiple times. The time interval between captures may be irregular, and capturing may be paused after capturing one first image.

[0060] (Warning part) Referring again to FIG. 3, the particle size distribution measuring device MD may be provided with various warning units.

[0061] For example, the particle size distribution measuring device MD further includes a first warning unit 331. The first warning unit 331 counts the number of dot patterns 410 detected from the first image by the first search unit 312, and outputs a warning via the output device OU when the counted number is equal to or less than a first threshold. This warning is useful because it can notify the user that there has been a change in the projection environment of the projection unit 20.

[0062] For example, the particle size distribution measuring device MD further includes a second warning unit 332 (warning unit). As described above, the particle size distribution calculation unit 320 calculates the length of each of the plurality of objects 210 included in the aggregate 200 from the three-dimensional information. The second warning unit 332 outputs a warning via the output device OU when the length of one or more of the plurality of objects 210 is equal to or greater than a second threshold (threshold). This warning is useful because it can notify the user that impurities have been mixed into the aggregate 200. As an example, there are foreign objects, such as pipes and vinyl sheets, that have lengths greater than the range of lengths that objects 210 typically included in the aggregate 200 can assume. The length monitored by the second warning unit 332 may be one or more of the minor diameter, middle diameter, and major diameter of the object 210.

[0063] For example, the particle size distribution measuring device MD further includes a third warning unit 333. As described above, the particle size distribution calculation unit 320 calculates the volume of each of the plurality of objects 210 contained in the aggregate 200 from the three-dimensional information. The third warning unit 333 outputs a warning via the output device OU when the volume of one or more of the plurality of objects 210 is equal to or greater than a third threshold. This warning is useful because it can notify the user that impurities have been mixed into the aggregate 200. As an example, there are foreign objects, such as pipes and vinyl sheets, that have a volume larger than the range of volumes that the objects 210 normally contained in the aggregate 200 can take.

[0064] For example, the particle size distribution measuring device MD further includes a fourth warning unit 334. The particle size distribution calculation unit 320 may calculate the area of ​​each of the plurality of objects 210 contained in the aggregate 200 that appears in the first image from the three-dimensional information. This area is the apparent area on the first image. The fourth warning unit 334 outputs a warning via the output device OU when the area of ​​one or more of the plurality of objects 210 is equal to or greater than a fourth threshold. This warning is useful because it can notify the user that impurities have been mixed into the aggregate 200. As an example, there are foreign objects, such as pipes and vinyl sheets, that appear with an area larger than the range of possible areas of the objects 210 normally contained in the aggregate 200.

[0065] An example of detecting impurities is shown in Figure 16. As shown in Figure 16, foreign objects such as a pipe 1601 and a vinyl sheet 1602 that have a length, volume, or area larger than the object 210 normally contained in the aggregate 200 may be detected.

[0066] (Variation 1) In the above example, dot pattern 410 is composed of nine blocks, but the scope of the present disclosure is not limited to this. Dot pattern 410 may be composed of multiple blocks, such as two to eight blocks, or ten or more blocks.

[0067] (Variation 2) In the above example, the central coordinates of the central block are used as the coordinates of the dot pattern 410, but the scope of the present disclosure is not limited to this. The central coordinates of any one or more of the blocks constituting the dot pattern 410 may also be used. For example, with reference to FIG. 5, the central coordinates of each of the blocks A0 to A7 may be calculated. This is advantageous because it increases the density of the three-dimensional information compared to calculating the central coordinates of only the block A8.

[0068] (Variation 3) In the above example, the blocks constituting the dot pattern 410 are four colors: red, blue, green, and white. However, the scope of the present disclosure is not limited to this. The number of colors in the dot pattern 410 may be two, three, five, or more.

[0069] (Variation 4) In the above example, the dot patterns 410 are laid out tightly in the two-dimensional pattern 400, but the scope of the present disclosure is not limited to this. There may be a gap of one pixel or more between the dot patterns 410. For example, if the dot pattern 410 is expressed using four colors, red, blue, green, and white, the dot patterns 410 may be separated by black pixels. The black pixels can reduce color bleeding or color mixing in the dot pattern 410.

[0070] (Variation 5) In the above example, the blocks are laid out tightly in the dot pattern 410, but the scope of the present disclosure is not limited to this. There may be a gap of one pixel or more between the blocks constituting the dot pattern 410. For example, if the dot pattern 410 is expressed using four colors (red, blue, green, and white), the blocks may be separated by black pixels. There may also be a gap of one pixel or more between both the dot patterns 410 and the blocks.

[0071] (Variation 6) In the above example, the particle size distribution is calculated once, but the scope of the present disclosure is not limited to this. The series of processes shown in FIG. 15 may be executed repeatedly. The first imaging unit 10 captures images of the aggregate 200 multiple times, and the calculation device 30 calculates the particle size distribution multiple times. In this case, it is useful to adjust the time interval between images captured by the first imaging unit 10 according to the conveying speed of the conveying device CD so that there is little overlap between the first images.

[0072] 3, for example, the particle size distribution measuring device MD may further include an image capture adjustment unit that adjusts the time interval between images captured by the first image capture unit 10 based on the conveying speed of the conveying device CD. The image capture adjustment unit 40 determines the time interval between images captured by the first image capture unit 10 so that the faster the conveying speed received from the control device CU is, the shorter the time interval between images captured by the first image capture unit 10 is, and the slower the conveying speed is, the longer the time interval is. The image capture adjustment unit 40 may be built into a camera having the first image capture unit 10, or may be realized by an application program on the computing device 30.

[0073] (Variation 7) In the above example, one particle size distribution is calculated from one first image, but the scope of the present disclosure is not limited thereto. One particle size distribution may be calculated from multiple first images. Referring to FIG. 15 , in step S602, the first imaging unit 10 may capture images of the aggregate 200 multiple times, and in step S604, the 3D information acquisition unit 310 may acquire 3D information from each of the multiple first images. Then, in step S606, the particle size distribution calculation unit 320 integrates the multiple pieces of 3D information and calculates the particle size distribution from the integrated 3D information. In this case, too, it is beneficial to adjust the time interval between images captured by the first imaging unit 10 in accordance with the conveying speed of the conveying device CD so as to minimize overlap between the first images.

[0074] [Embodiment 2] Other embodiments of the present invention will be described below. For ease of explanation, the same reference numerals will be used to designate components having the same functions as those described in the above embodiment, and the description thereof will not be repeated.

[0075] (Configuration of particle size distribution measurement system) Fig. 17 is a functional block diagram showing an example of the configuration of a particle size distribution measuring system according to embodiment 2 of the present disclosure. As shown in Fig. 17, the particle size distribution measuring device MD according to embodiment 2 further includes a second imaging unit 1710 that captures images of aggregates 200 within a range R1 captured by the first imaging unit 10. The second imaging unit 1710 is synchronized with the first imaging unit 10 so as to capture images simultaneously with the first imaging unit 10.

[0076] It is preferable that the second imaging unit 1710 is positioned approximately directly opposite the falling surface of the falling aggregate, similar to the first imaging unit 10. The relative position of the second imaging unit 1710 with respect to the first imaging unit 10 is measured in advance.

[0077] (Processing by 3D information acquisition unit) Fig. 18 shows an example of processing by the three-dimensional information acquisition unit shown in Fig. 17. Referring to Fig. 17, three-dimensional information acquisition unit 310 may include first search unit 312, second search unit 1720, and coordinate calculation unit 314. As shown in Fig. 18, first search unit 312 executes step S100. Similar to step S100, second search unit 1720 searches for each dot pattern 410 so as to identify the position of that dot pattern 410 on the second image captured by second imaging unit 1710 (step S700).

[0078] Next, as in step S200, for each dot pattern 410 whose position on both the first image and the second image has been identified, the coordinate calculation unit 314 calculates the three-dimensional coordinates of the position of the dot pattern 410 on the aggregate 200 based on the position of the dot pattern 410 on the first screen, the position of the dot pattern 410 on the second image, and the position of the second imaging unit 1710 relative to the first imaging unit 10 (step S800).

[0079] In the second embodiment, a stereo camera may be used that has a first imaging unit 10 and a second imaging unit 1710. Since the position of the second imaging unit 1710 relative to the first imaging unit 10 is fixed, it is not necessary to measure the position of the second imaging unit 1710 relative to the first imaging unit 10.

[0080] In the second embodiment, the position of the projection unit 20 is not used to calculate the three-dimensional coordinates of the dot pattern 410. Therefore, it is not necessary to measure the position of the projection unit 20 relative to the first imaging unit 10. Also, it is easy to change the position of the projection unit 20 relative to the first imaging unit 10.

[0081] [Embodiment 3] (Configuration of particle size distribution measurement system) Fig. 19 shows an example of the configuration of a particle size distribution measuring system according to embodiment 3 of the present disclosure. Fig. 20 is a functional block diagram showing in more detail the configuration of the particle size distribution measuring device MD shown in Fig. 19. As shown in Figs. 19 and 20, the particle size distribution measuring system MS according to embodiment 2 further includes a line height information acquiring unit 50 that acquires line height information of the aggregate 200 flowing on the conveying device CD along a measurement line 1900 (line). The measurement line 1900 is a virtual line extending along the width direction (Y direction) on the conveying surface of the conveying device CD.

[0082] The line height information acquisition unit 50 acquires line height information of the aggregate 200 on the measurement line 1900 in a single measurement. The line height information acquisition unit 50 has a resolution capable of measuring an object 210 with a particle size smaller than the lower measurement limit of the three-dimensional information acquisition unit 310. The line height information acquisition unit 50 is installed facing downward so that its optical axis is approximately perpendicular to the conveyance surface of the conveyance device CD. The line height information acquisition unit 50 is composed of, for example, a camera and a line laser, and can acquire line height information using a light-section method. The line height information acquisition unit 50 can, for example, perform laser scanning and acquire line height information from the laser scanning signal. By narrowing the measurement range to the measurement line 1900, the resolution in the height direction can be improved, allowing objects 210 with small particle sizes to be measured. In the light-section method, a line laser is irradiated toward the measurement line 1900, the position of the line laser is acquired from an image captured by a camera, and the height is calculated from the difference between the reference position and the position of the line laser. The reference position is the conveying surface, and is obtained in advance by manually or by irradiating a line laser onto a conveying surface where no aggregate is present.

[0083] (Line height information and volume) Fig. 21 shows line height information acquired by the line height information acquisition unit shown in Fig. 19. As shown in Fig. 21, line height information 2010 relative to a reference line 2000 is calculated at frame intervals d nThe reference line 2000 corresponds to the measurement line 1900. The area Sn enclosed by the reference line 2000 and the line height information 2010 of the nth frame corresponds to the cross-sectional area of ​​the aggregate 200 in a cross section passing through the measurement line 1900 and perpendicular to the conveying direction (X direction in FIG. 19 ) at the moment when the line height information acquisition unit 50 captured the nth frame. Therefore, the total volume V of the aggregate 200 flowing on the conveying device CD can be calculated by numerically integrating the line height information 2010. For example, as shown in the following equation (5), the total volume V can be calculated from the sum of the volumes multiplied by the frame interval dn corresponding to the area Sn. The frame interval dn can be obtained by multiplying the time interval from when the line height information acquisition unit 50 acquires the line height information 2010 of the nth frame to when the line height information 2010 of the (n+1)th frame is acquired by the conveying speed of the conveying device CD.

[0084]

number

[0085] In the present disclosure, the total volume of the aggregate 200 calculated based on the three-dimensional information provided by the three-dimensional information acquisition unit 310 is referred to as the "first volume." On the other hand, the total volume of the aggregate 200 calculated based on the line height information 2010 provided by the line height information acquisition unit 50 is referred to as the "second volume."

[0086] The time difference between the first and second points in time can be calculated from the conveying speed of the conveying device CD, the distance from the measurement line 1900 to the fall line 1906 where the aggregate 200 falls from the conveying device CD, the acceleration of gravity, and the distance from the fall line 1906 to the bottom line 1904. Similarly, the time difference between the first and third points in time can be calculated from the conveying speed of the conveying device CD, the distance from the measurement line 1900 to the fall line 1906, the acceleration of gravity, and the distance from the fall line 1906 to the top line 1902. Each time difference may be measured in advance.

[0087] FIG. 22 shows an example of the total volume on the conveying device based on line height information and the sum of the volumes for each particle size. In FIG. 22, the values ​​in column C3 of the volume for each particle size are calculated by the 3D information acquisition unit 310 and the particle size distribution calculation unit 320 based on the first image. The total volume and the volume for each particle size on the conveying device CD, which are arranged horizontally in FIG. 22, coincide with the end of the integration interval for the total volume on the conveying device CD and the capture time of the first image. In the example shown in FIG. 22, line height information and the first image are acquired every second, and the lower measurement limit of the 3D information acquisition unit 310 is 1 mm, while the lower measurement limit of the line height information acquisition unit 50 is 0.6 mm. The time difference between the object 210 positioned on the measurement line 1900 and the object 210 reaching the upper end line 1902 is assumed to be 3 seconds.

[0088] As shown in Figure 22, the total volume [m 3 ] column C1 at time t [s] is extracted as the total volume of the aggregate 200. 3 ], the sum of the values ​​in column F3 at time (t+3) [s] is extracted as the coarse particle side volume of the aggregate 200. Then, the value obtained by subtracting the coarse particle side volume from the total volume is taken as the fine particle side volume of the aggregate 200, and the volume [m 3] and enter it in column F2 at time (t+3) [s] in column C2.

[0089] (Processing by particle size distribution calculation unit) Fig. 23 shows an example of processing by the particle size distribution calculation unit shown in Fig. 20. As shown in Fig. 23, following steps S300 and S400, the particle size distribution calculation unit 320 calculates the total volume (first volume) of the aggregate 200 based on the result of step S400 (step S900). In other words, the particle size distribution calculation unit 320 calculates the first volume from three-dimensional information acquired from the first image.

[0090] The particle size distribution calculation unit 320 calculates the total volume (second volume) of the aggregate 200 based on the line height information 2010 provided by the line height information acquisition unit 50, in parallel with or before or after the calculation of the first volume (step S910).

[0091] The particle size distribution calculation unit 320 calculates the difference between the first volume and the second volume (step S920) and executes step S510. In step S510, the particle size distribution calculation unit 320 uses the three-dimensional information for particle sizes equal to or larger than the lower measurement limit of the three-dimensional information acquisition unit 310, and uses the difference between the first volume and the second volume for particle sizes smaller than the lower measurement limit of the three-dimensional information acquisition unit 310 to calculate the total volume for each particle size.

[0092] The particle size distribution calculation unit 320 further executes steps S530, S540, S550, and S560. In step S530, the mass obtained by multiplying the second volume by a given surface-dry density is set as the sum of the masses of all particle sizes.

[0093] (display of particle size distribution) Fig. 24 shows an example of a particle size distribution display. As shown in Fig. 24, a calculated particle size distribution 1401 may be displayed so as to distinguish between a fine particle side range 2401 based on the difference between the first volume and the second volume and a coarse particle side range 2402. For example, the shape and / or color of the mark may be different between the fine particle side range 2401 and the coarse particle side range 2402. Fig. 24 uses white diamonds in the fine particle side range 2401 and black circles in the coarse particle side range 2402.

[0094] As described above, the configuration according to the third embodiment can measure objects 210 with smaller particle sizes. Therefore, the particle size distribution can be calculated even when the aggregate 200 contains small particles such as sand.

[0095] (Processing flow of particle size distribution measurement system) Fig. 25 shows the flow of processing of the particle size distribution measurement system shown in Fig. 19. As shown in Fig. 25, steps S600, S602, and S604 are executed, and the three-dimensional information acquisition unit 310 sends the three-dimensional information to the particle size distribution calculation unit 320.

[0096] The particle size distribution calculation unit 320 acquires line height information 2010 via the line height information acquisition unit 50 (step 1000). The particle size distribution calculation unit 320 calculates the volume of the fine particle side from the difference between the total volume (first volume) of the aggregate 200 calculated from the three-dimensional information and the total volume (second volume) of the aggregate 200 calculated from the line height information 2010, calculates the volume of each particle size of the coarse particle side from the three-dimensional information, multiplies the volume by the surface dry density to convert it to mass, and calculates the passing mass percentage for each particle size range (step S1010). The particle size distribution calculation unit 320 sends the particle size distribution, or a table or graph of the particle size distribution, to the output device OU, and step S608 is executed.

[0097] (Warning part) Referring to FIG. 20, the particle size distribution measuring device MD may include various warning units.

[0098] For example, the particle size distribution measuring device MD includes one or more of the first to fourth warning units 331 to 334.

[0099] For example, the particle size distribution measuring device MD includes a fifth warning unit 335. The fifth warning unit 335 outputs a warning via the output device OU when the first volume based on the three-dimensional information is larger than the second volume based on the line height information 2010. This warning is useful because it can notify the user that an abnormality may have occurred between the line height information acquisition unit 50 and the calculation device 30, or that the line height information acquisition unit 50 and the first imaging unit 10 may be out of synchronization.

[0100] The line height information acquisition unit 50 according to the third embodiment may be combined with the configuration according to the second embodiment described above.

[0101] 〔summary〕 A particle size distribution measuring device according to a first aspect of the present disclosure includes a first imaging unit that captures an image of aggregates falling from a conveying device, a projection unit that projects a two-dimensional pattern onto the area captured by the first imaging unit, a three-dimensional information acquisition unit that acquires three-dimensional information from the first image captured by the first imaging unit, and a particle size distribution calculation unit that calculates the particle size distribution of the aggregates from the three-dimensional information, wherein the two-dimensional pattern is configured to be a plurality of dot patterns that can uniquely identify a position on the first image.

[0102] A particle size distribution measuring device according to a second aspect of the present disclosure may have the configuration according to the first aspect described above, further including a line height information acquisition unit that acquires line height information of the aggregate flowing on the conveying device, and the particle size distribution calculation unit calculates a first volume from the three-dimensional information, calculates a second volume from the line height information, and calculates the particle size distribution using the three-dimensional information for particle sizes equal to or larger than a lower limit measurable by the three-dimensional information acquisition unit, and using the difference between the first volume and the second volume for particle sizes smaller than the lower limit measurable by the three-dimensional information acquisition unit.

[0103] A particle size distribution measuring device according to aspect 3 of the present disclosure may have the configuration according to aspect 1 or 2 described above, wherein the three-dimensional information acquisition unit includes a first search unit that searches for each dot pattern to identify its position on the first image, and a coordinate calculation unit that calculates, for each dot pattern whose position on the first image has been identified, the three-dimensional coordinates of the position of the dot pattern on the aggregate based on the position of the dot pattern on the first screen, the position of the dot pattern on the two-dimensional pattern, and the position of the projection unit relative to the first imaging unit.

[0104] A particle size distribution measuring device according to aspect 4 of the present disclosure may have the configuration according to aspect 1 or 2 described above, further including a second imaging unit that images the aggregate within a range imaged by the first imaging unit, and the three-dimensional information acquisition unit may include a first search unit that searches for each dot pattern to identify its position on the first image, a second search unit that searches for each dot pattern to identify its position on the second image imaged by the second imaging unit, and a coordinate calculation unit that calculates, for each dot pattern whose position on both the first image and the second image has been identified, the three-dimensional coordinates of the position of the dot pattern on the aggregate based on the position of the dot pattern on the first image, the position of the dot pattern on the second image, and the position of the second imaging unit relative to the first imaging unit.

[0105] A particle size distribution measuring device according to aspect 5 of the present disclosure may have the configuration according to aspect 3 or 4 described above, and further include a first warning unit, wherein the first warning unit counts the number of dot patterns whose positions on the first image have been identified by the first search unit, and outputs a warning via an output device when the number is equal to or less than a first threshold.

[0106] A particle size distribution measuring device according to a sixth aspect of the present disclosure may have a configuration according to any one of the first to fifth aspects described above, wherein each dot pattern is composed of a plurality of blocks, and the three-dimensional coordinates of each dot pattern include the three-dimensional coordinates of one or more of the blocks.

[0107] A particle size distribution measuring device according to a seventh aspect of the present disclosure may have a configuration according to any one of the first to sixth aspects described above, wherein the dot pattern has a size of 3×3 pixels or more, and the color combination of the pixels constituting the dot pattern is set to be unique within the two-dimensional pattern.

[0108] A particle size distribution measuring device according to an eighth aspect of the present disclosure may have the configuration according to the seventh aspect described above, wherein there is a gap of one pixel or more between at least one of the dot patterns and the pixels constituting the dot patterns.

[0109] A particle size distribution measuring device according to a ninth aspect of the present disclosure may have the configuration according to any one of the first to eighth aspects described above, and further include a second warning unit, wherein the particle size distribution calculation unit calculates the length of each of a plurality of objects contained in the aggregate from the three-dimensional information, and the second warning unit outputs a warning via an output device when the length of one or more of the plurality of objects is equal to or greater than a second threshold value.

[0110] A particle size distribution measuring device according to aspect 10 of the present disclosure may have the configuration according to any one of aspects 1 to 9 described above, and further include a third warning unit, wherein the particle size distribution calculation unit calculates the volume of each of a plurality of objects contained in the aggregate from the three-dimensional information, and the warning unit outputs a warning via an output device when the volume of one or more of the plurality of objects is equal to or greater than a third threshold value.

[0111] A particle size distribution measuring device according to an eleventh aspect of the present disclosure may have the configuration according to any one of the above-described aspects 1 to 10, and further include a fourth warning unit, wherein the particle size distribution calculation unit calculates the area of ​​each of a plurality of objects contained in the aggregate that appears in the first image from the three-dimensional information, and the fourth warning unit outputs a warning via an output device when the area of ​​one or more of the plurality of objects is equal to or greater than a fourth threshold value.

[0112] A particle size distribution measuring device according to aspect 12 of the present disclosure may have the configuration according to the aforementioned aspect 2, and further include a fifth warning unit, which outputs a warning via an output device when the first volume is larger than the second volume.

[0113] A particle size distribution measuring device according to aspect 13 of the present disclosure may have a configuration according to any one of aspects 1 to 12 described above, wherein the first imaging unit photographs the aggregate multiple times and further includes an imaging adjustment unit that adjusts the time interval between images taken by the first imaging unit based on the conveying speed of the conveying device.

[0114] A particle size distribution measuring device according to aspect 14 of the present disclosure may have the configuration according to any one of aspects 1 to 13 described above, wherein the first imaging unit photographs the aggregate multiple times, the three-dimensional information acquisition unit acquires the three-dimensional information from each of the multiple first images, and the particle size distribution calculation unit integrates the multiple pieces of three-dimensional information and calculates the particle size distribution from the integrated three-dimensional information.

[0115] A particle size distribution measuring method according to aspect 15 of the present disclosure includes an imaging step of imaging aggregates falling from a conveying device, a projection step of projecting a two-dimensional pattern onto the area imaged in the imaging step, a three-dimensional information acquisition step of acquiring three-dimensional information from the image captured in the imaging step, and a particle size distribution calculation step of calculating the particle size distribution of the aggregates from the three-dimensional information, wherein the two-dimensional pattern is composed of a plurality of dot patterns that can uniquely identify a position on the image.

[0116] The three-dimensional information acquisition unit, particle size distribution calculation unit, first to fifth warning units, and photography adjustment unit according to each aspect of the present invention may be realized by a computer. In this case, a control program for the particle size distribution measuring device that causes the computer to operate as each unit (software element) of the particle size distribution measuring device, thereby realizing the particle size distribution measuring device on the computer, and a computer-readable recording medium on which the program is recorded, also fall within the scope of the present invention.

[0117] The present invention is not limited to the above-described embodiments, and various modifications are possible within the scope of the claims. Embodiments obtained by appropriately combining the technical means disclosed in different embodiments are also included in the technical scope of the present invention. Furthermore, new technical features can be formed by combining the technical means disclosed in each embodiment. [Explanation of symbols]

[0118] 10 First imaging unit (imaging unit) 20 Projection section 40 Shooting control section 50 Line height information acquisition unit 200 aggregate 210 Object 310 3D information acquisition section 320 Particle size distribution calculation section 332 2nd warning part (warning part) 400 2D patterns 410 dot pattern 1900 Measurement Line (Line) CD transport device MD particle size distribution measuring device R1 Range captured by the first imaging unit (imaging unit)

Claims

1. an imaging unit that captures an image of the aggregate falling from the conveying device; a projection unit that projects a two-dimensional pattern into a range captured by the imaging unit; a three-dimensional information acquisition unit that acquires three-dimensional information from the image captured by the imaging unit; a particle size distribution calculation unit that calculates a particle size distribution of the aggregate from the three-dimensional information, The two-dimensional pattern is composed of a plurality of dot patterns that can uniquely identify a position on the image.

2. a line height information acquisition unit that acquires line height information of the aggregate flowing on the conveying device; The particle size distribution calculation unit Calculating a first volume from the three-dimensional information; Calculating a second volume from the line height information; 2. The particle size distribution measuring device according to claim 1, wherein the particle size distribution is calculated using the three-dimensional information for particle sizes equal to or larger than a lower limit measurable by the three-dimensional information acquisition unit, and using the difference between the first volume and the second volume for particle sizes smaller than the lower limit measurable by the three-dimensional information acquisition unit.

3. 3. The particle size distribution measuring device according to claim 1, wherein the dot pattern has a size of 3×3 pixels or more, and the color combination of the pixels constituting the dot pattern is set to be unique within the two-dimensional pattern.

4. Further provided with a warning section, the particle size distribution calculation unit calculates a length of each of a plurality of objects included in the aggregate from the three-dimensional information; The particle size distribution measuring apparatus according to claim 1 , wherein the warning unit outputs a warning via an output device when the length of one or more of the plurality of objects is equal to or greater than a threshold value.

5. The imaging unit images the aggregate multiple times, 3. The particle size distribution measuring device according to claim 1, further comprising an image capturing adjustment unit that adjusts the time interval between images captured by the image capturing unit based on the transport speed of the transport device.

6. an imaging step of imaging the aggregate falling from the conveying device; a projection step of projecting a two-dimensional pattern onto the range photographed in the imaging step; a three-dimensional information acquisition step of acquiring three-dimensional information from the image captured in the imaging step; a particle size distribution calculation step of calculating a particle size distribution of the aggregate from the three-dimensional information, The particle size distribution measuring method, wherein the two-dimensional pattern is composed of a plurality of dot patterns that can uniquely identify positions on the image.

Images