JP5582806B2 - Granule size measurement system and program - Google Patents

Description

  The present invention relates to a granular material particle size measurement system and program, and more particularly to a system and program for simply measuring the particle size of a granular material supplied from a specific collection site or crushing apparatus.

  When constructing civil engineering structures such as dams, embankments, road bodies, roadbeds, roadbeds, concrete, pavements, planting bases, etc. In some cases, a method using a ground material or raw material procured on the ground, or a rock-crushing material obtained by crushing a rough stone with a crushing device or the like, or other granular material S (a civil engineering material in which granular materials having different particle diameters are mixed) may be employed. CSG (Cemented Sand and Gravel) method of Patent Document 1). For example, in the CSG method, from the viewpoint of material rationalization, water and cement are mixed with the procured granular material S (CSG material) to make the structure material (CSG) as it is, thus ensuring the quality (particularly strength) of the structure. In order to do this, it is necessary to confirm and manage whether or not the particle size of the granular material S is within the specified range.

  FIG. 11 shows an example of a strength management method for civil engineering structures constructed by the CSG method (see rhombus theory, Non-Patent Document 1). First, a number of particle size tests are performed on the particle size of the granular material S (CSG material), and the sample Tr having the coarsest particle size (the sample having the largest content of the large-diameter granular material. Hereinafter, it may be referred to as the most coarse particle sample). And the sample Ts having the finest particle size (the sample having the largest content of the small-diameter granular material, hereinafter sometimes referred to as the finest sample). Next, a strength test is performed on the CSG using the granular material S within the range of the coarsest grain sample Tr and the finest grain sample Ts while changing the unit water amount, and a lower limit value that is insufficient in strength and an upper limit value that is unsuitable for construction are obtained. To detect. In addition, when the CSG is manufactured or placed, the particle size and unit water amount of the CSG are determined according to the particle size-strength curve (dotted line in the figure) of the coarsest specimen Tr and the particle size-intensity curve of the finest specimen Ts (solid line in the figure). ) And two vertical lines indicating the permissible unit water amount range, and manage them so that they are within the specified range of “diamonds” (shaded area). The lowest strength within the specified range of the rhombus in the illustrated example is referred to as CSG strength. By using CSG within the range of the rhombus, strength higher than the CSG strength can be secured in the structure.

  In general, the particle size of the granular material S is such that the particle diameter d of each mixed granular material is the horizontal axis (logarithmic axis), and the mass percentage P (d) (the particle diameter d FIG. 10 shows a semi-logarithmic graph with the vertical axis (linear axis) as the vertical axis (linear axis), that is, the total mass of the granular material having a smaller diameter than the granular material / the total mass of the entire granular material × 100. It is represented by such a particle size accumulation curve P (d). Therefore, as shown in FIG. 10, the particle size accumulation curve Pr (d) of the coarsest sample Tr of the granular material S and the particle size accumulation curve Ps (d) of the finest sample Ts are obtained in advance. A range surrounded by the particle size accumulation curve Pr (d) and the particle size accumulation curve Ps (d) by obtaining the particle size accumulation curve P (d) of the continuously supplied granular material S (specified range) ), It is possible to realize quality control with granularity based on the rhombus theory of FIG.

  However, in order to create the particle size accumulation curve P of the granular material S in which granular materials with various particle diameters d are mixed, for example, in civil engineering work such as dams, a large amount of several hundred kg per time It is necessary to screen the granular material S many times, and to calculate the passing rate (passing mass) for each sieving (each screen size), and at the present stage, all these are performed manually. Because it is necessary, there is a problem that requires a lot of labor and time. In the quality control of the CSG method, it is required to check the particle size of the granular material S used at the beginning of the construction as frequently as possible (for example, once per hour) (see Non-Patent Document 1). Frequent repetition of the work of creating a radial product curve requires a great deal of labor.

  On the other hand, as disclosed in Patent Documents 1 and 2, a method for obtaining the particle size of the granular material S using an image analysis technique has been proposed. For example, Patent Document 1 specifies the outline of each granular material in the material by performing image processing on the whole or a part of the image of the crushed material, and each granular material has a simple solid (with the equivalent diameter of the same area as the outline). Spheres or cubes), and a method of creating a particle size distribution curve by calculating the mass by multiplying the volume of the simple solid model by the specific gravity of the crushed material (raw stone) is proposed. Further, Patent Document 2 captures a plurality of images with different shadow positions while irradiating an observation area where gravel is accumulated with a plurality of illuminations in different directions, and synthesizes images with different shadow positions, thereby combining individual images in the observation area. In addition to separating and identifying pebbles, we propose a method to measure the particle size (radius) of each gravel and analyze its distribution. If the particle size of the granular material S can be managed using image analysis techniques such as Patent Documents 1 and 2, the quality control of the civil engineering structure can be simplified and the accuracy can be improved as compared with the conventional sieving method.

JP 2003-010726 A JP 2006-078234 A Japanese Patent Laid-Open No. 61-061623 JP 2009-036533 A

Jyuji Yanagawa “New technology in dam business-trapezoidal CSG dam” published by Construction Industry Research Committee, Base Design Material, No. 136 Civil Engineering, published on March 20, 2008, Internet (URL: http://www.kenkocho.co.jp/html/136/sa_136.html) Yasuhiko Okano “Crushing / Crushing / Sieving (Part 2)” Aggregate Resources, Volume No. 122, 1999

  However, the methods of Patent Documents 1 and 2 only determine the particle size distribution of each granular material in a range in which the contour can be detected from the image of the granular material S, and the ratio of each granular material in which the contour is detected to the entire granular material S, That is, there is a problem that the cumulative passage rate cannot be obtained. As described above with reference to FIG. 10, in order to manage the particle size of the granular material S used in the CSG method or the like, the cumulative passage rate P (d) is obtained for each particle size d in the granular material S. Then, a particle size accumulation curve P (d) is created, and the particle size accumulation curve P (d) is obtained by adding the particle size accumulation curve Pr (d) of the coarsest sample specimen Tr and the particle size addition curve of the finest sample Ts. Although the particle size quality must be confirmed in comparison with the specified range surrounded by the product curve Ps (d), the image analysis methods of Patent Documents 1 and 2 have limitations on the particle size of the granular material that can detect the contour. It is difficult to grasp the accumulated passing amount P of the granular material whose contour is detected in consideration of the granular material whose contour cannot be detected. In order to apply the image analysis method to the particle size management of the granular material S, the accumulation pass rate P for the entire granular material is grasped from the image of the granular material S, and the coarsest sample Tr and the finest sample Ts are obtained. A comparable technology is needed.

  Therefore, an object of the present invention is to provide a system and program capable of creating a particle size accumulation curve from an image of a granular material.

  The inventor of the present invention has a cumulative passage rate P (d) with respect to the entire granular material having a particle diameter d or less in the granular material S and an area ratio with respect to the entire granular material having a particle diameter d or more in the image G of the granular material S. I paid attention to the relationship. For example, it is difficult to detect all the granular materials having a specific particle size di (for example, 10 mm) or less from the image G of the granular material S as shown in FIG. All the granular materials (for example, 10 mm) or more can be detected relatively easily, and the area ratio Σe / E () of the sum (Σe) of the area e of the granular materials having a particle diameter di or more with respect to the entire area E of the image G Hereinafter, the granularity index Ii may be calculated. FIG. 5 shows a plurality of granular materials S collected from the same ground, and a cumulative passage rate P (di of granular materials having a particle size of di = 10 mm, 20 mm, 30 mm, 40 mm or less by a conventional method such as sieving work, respectively. ) And the particle size index Ii of the granular material having a particle size of di = 10 mm, 20 mm, 30 mm, 40 mm or more is calculated from the rolled-out image G, and the result is obtained as a secondary plane (additional passage rate P (d ) On the vertical axis and the area ratio (Σe / E) on the horizontal axis).

Graph in Figure 5 shows that expressed in different particle sizes di in pressurized product passage rates P (di) respectively, multidimensional regression model granularity index ^{_{Ii (y = Σa n · x}} n) of each particulate material S ing. Although the figure is intended for a plurality of granular materials S collected from a specific ground, the present inventor also conducted a further experiment on the granular materials S collected from other grounds. By using an appropriate regression model every time, between the accumulation passage rate P (d) at different particle diameters di of the granular material S collected from the natural ground and the particle size index of the granular material having the particle diameters di or larger. We found that the relational expression can be set. If a relational expression (for example, a multidimensional regression model) as shown in FIG. 5 is used, the accumulated passage rate P (d) of a plurality of particle diameters d can be estimated from the image G of the granular material S. The particle diameter accumulation curve P (d) of the granular material S can be created using the passage rate P (d). The present invention has been completed as a result of research and development based on this finding.

Referring to the block diagram of FIG. 1, the granular material quality control system according to the present invention is a spear image G of a granular material S supplied from a predetermined sampling site 1 or a crushing device 2 (see FIG. 6A). An image pickup device 5 for detecting the contour of each granular material in the image G, a particle diameter d and an area e from the contour of each granular material, and a granular material in the image G for a plurality of particle diameters di The calculating means 18 for calculating the area ratio (= Σe / E) of the granular material with the particle size di or more with respect to the total area E of S as the particle size index Ii, the particle size index of each particle size di obtained from the sample T of the granular material S Storage means 16 for storing a relational expression K (see FIG. 5) between Ii and a cumulative passage rate P (di) which is a mass ratio of a granular material having a particle size di or less in the sample T to the total mass of the sample T; In addition, the calculated particle size of each particle size di Made comprise creating means 20 for creating a particle size accumulation curve P (d) converting the dexfenfluramine Ii by equation K a pressurized volume passage rate is the mass fraction of the full weight of the particulate material S P (di) It is.

1 and 2, the granular material particle size measurement program according to the present invention includes a computer 10 for measuring the particle size of the granular material S supplied from the predetermined sampling site 1 or the crushing device 2, The input means 14 for inputting the rolled-out image G (see FIG. 6A) of the granular material S, the detecting means 17 for detecting the contour of each granular material in the image G, the particle diameter d and the area from the contour of each granular material calculating means 18 for obtaining e and calculating an area ratio (= Σe / E) of a granular material having a particle diameter di or larger with respect to the total area E of the granular material S in the image G for a plurality of particle diameters di as a particle size index Ii; The particle size index Ii of each particle size di obtained from the sample T of the granular material S and the cumulative passage rate P (di) which is the mass ratio of the granular material having a particle size di or less in the sample T to the total mass of the sample T Equation K (see Fig. 5) ) Is converted to a mass ratio to the total mass of pressurized product passage rates P of the particulate material S by equation K granularity index Ii of each particle size di storing unit 16, and calculates and stores (di) a particle径加It functions as the creation means 20 for creating the product curve P (d).

  Preferably, as shown in FIG. 1, a separation device 6 for separating a fine granular material having a particle diameter less than a predetermined particle size D from the granular material S is provided, and the fine granular material having a particle diameter less than the predetermined particle diameter D is separated in the input means 14 of the computer 10. The squeezed image G of the granular material S is input, and the storage unit 16 stores a relational expression K between the particle size index Ii obtained from the granular material sample T after separation of the fine granular material and the accumulated passage rate P (di). Then, the creation means 20 creates a particle size accumulation curve P (d ≧ D) having a predetermined particle size D or more.

  More preferably, measuring instruments 7 and 8 for measuring the weight M and moisture content Z of the granular material S before and after separating the fine granular material are provided, and the granular material before and after separating the fine granular material in the input means 14 of the computer 10. The computer 10 is provided with a calculation means 25 for inputting the weight M and moisture content Z of S and calculating the accumulated passage rate P (D) of the fine granular material in the granular material S from the measured values of the weight M and moisture content Z. From the accumulated passage rate P (di) of each particle size di of the granular material S after separation of the fine granular material by the creating means 20 and the accumulated passage rate P (D) of the fine granular material in the granular material S. A particle size accumulation curve P (d) is created.

  Alternatively, the particle size accumulation curve P (d ≦ D) of the fine granular material having a particle diameter less than the predetermined particle diameter D obtained from the sample T of the granular material S is stored in the storage means 16 of the computer 10 and the fine granular material in the sample T is added. The product passing rate P (D) is stored as functions U and R, and the particle size addition of the fine granular material is performed by the functions U and R from the accumulated passing rate P (D) of the fine granular material in the granular material S in the computer 10. Estimating means 27 for estimating the curve P (d ≦ D) is provided, and by the creating means 20, the particle size accumulation curve P (d ≧ D) of the granular material S after separation of the fine granular material and the fine granular material of the granular material The particle size accumulation curve P (d) may be created by combining the particle size accumulation curve P (d ≦ D).

Desirably, the storage means 16 of the computer 10 stores the particle size accumulation curves Pr and Ps of the coarsest grain sample Tr and the finest grain sample Ts of the granular material S, and the computer 10 stores the particle diameter accumulation of the granular material S. A determination unit 24 is provided for comparing the curve P (d) with the particle size accumulation curves Pr (d) and Ps (d) of the coarsest sample Tr and the finest sample Ts to determine the particle quality. Alternatively or in addition, the particle size index I or the particle size accumulation curve P (d) created from the granular material S continuously supplied to the storage means 16 of the computer 16 is accumulated and stored. the particle size variation in the particle size index I _t or grain size accumulation curve P (d) _t and particle size index I _t-1 or grain size accumulation curve P (d) is compared with the _t-1 particulate material S previous feed A determination means 24 for determining the above may be provided.

The granular material quality control system and program according to the present invention detects the outline of each granular material from the rolled-out image G of the granular material S by the detecting means 17, and the calculating means 18 detects the outline of each granular material from the outline of each granular material. The particle size d and the area e are obtained, and the ratio (= Σe / E) of the granular material equal to or larger than the particle size di to the total area E of the granular material S in the rolled-out image G is obtained for the particle size di. And the accumulated passage rate which is the mass ratio of the granular material having a particle size di or less in the sample T to the total mass of the sample T and the particle size index Ii of each particle size di previously calculated from the sample T of the granular material S P based on the relationship K between the (di), the particle size converted at creating unit 20 to the pressurized product passage rates P (di) is the mass fraction of the full mass of the particle size index Ii particulate material S for each particle size di Since creating a product curve P (d), it exhibits the following advantageous effects.

(A) Since the particle size accumulation curve P (d) can be easily created from the image of the granular material S in a short time and does not require sieving work requiring labor or time, for example, the CSG method or the like When applied to construction work using granular material S (construction work such as fill dams), the quality control of granular material S is facilitated and the creation frequency of the particle size accumulation curve is increased, resulting in high quality control. Can be achieved.
(B) If the particle diameter accumulation curves Pr and Ps of the coarsest grain sample Tr and the finest grain specimen Ts of the granular material S are obtained in advance, the created particle diameter accumulation curve P (d) is the diameter thereof. By comparing the accumulation curves Pr (d) and Ps (d), the particle quality of the granular material S can be easily determined.
(C) Furthermore, if the particle size index I or the particle size accumulation curve P (d) of the granular material S that is continuously supplied is stored in a cumulative manner, the particle size of the granular material S can be determined from the fluctuation of the index I or the curve P. Can be quickly grasped, and can contribute to further improvement of quality control in construction work using a granular material S such as CSG method.
(D) Even if the granular material S contains a fine granular material whose contour cannot be detected from the image, the granularity index Ii and the cumulative passage rate P are obtained from the sample T of the granular material S from which the fine granular material has been separated in advance. If the relational expression K with (di) is obtained, a particle size accumulation curve P (d ≧ D) equal to or larger than the particle size D of the fine granular material is obtained from the rolled-out image G of the granular material S obtained by separating the fine granular material. Can be created.

DESCRIPTION OF EMBODIMENTS Hereinafter, embodiments and examples for carrying out the present invention will be described with reference to the accompanying drawings.
It is a block diagram of one Example of the particle size measurement system of this invention. It is an example of the flowchart of the particle size measurement program of this invention. It is an example of the detailed flowchart of the calculation method (step S108 of FIG. 2) of the accumulation passage rate of a minute granular material. It is explanatory drawing of an example of the method of calculating an area from the outline of each granular material of the rolled-out image of a granular material. It is an example of the graph which shows the relational expression between the particle size index Ii of each particle size di of granular material, and the accumulation passage rate P (di) of the granular material below the particle size di in the granular material. It is explanatory drawing of an example of the method of detecting the outline of each granular material from the rolled-out image of a granular material. It is an example of the graph which shows the particle size accumulation curve of the granular material produced with the system of this invention. It is another example of the graph which shows the particle size accumulation curve of the granular material produced with the system of this invention. It is a further example of the graph which shows the particle size accumulation curve of the granular material produced with the system of this invention. It is an example of the graph which shows the particle size accumulation curve Pr and Ps of the coarsest grain sample Tr and the finest grain sample Ts of a granular material. It is explanatory drawing of an example of the particle size management method in the conventional CSG construction method.

  FIG. 1 shows a block diagram of the particle size measurement system of the present invention. The system of the illustrated example includes an imaging device 5 that captures a rolled-out image G of the granular material S, and a computer 10 that inputs the rolled-out image G and creates a particle size accumulation curve P (d) of the granular material S. Have For example, when a civil engineering structure is constructed by the CSG method, the ground material, etc. that is procured at a predetermined collection site (ground and geological layer) 1 near the site and continuously supplied to the construction site by a transporting machine 3 such as a dump truck Is used as a granular material S for quality control, and its particle size accumulation curve P (d) is created for each transport unit to manage the particle quality of the granular material S. When the material conveyed by the transporting machine 3 can be regarded as homogeneous, it is sufficient that a part of the transporting machine 3 is the granular material S to be managed. Note that the application target of the present invention is not limited to the ground material procured from the ground, etc., but the type and origin, for example, the rock material that is continuously supplied by crushing the raw stone with the predetermined crushing device 2 Accordingly, the present invention can be widely applied to the granular material S that can be approximated by substantially the same particle size accumulation curve (particle size distribution).

  The imaging device 5 in the illustrated example captures an image G (see FIG. 6A) by thinly rolling out the granular material S on, for example, a sheet laid on the ground surface. As will be described later, in order to make it possible to detect the outline of the granular material having a predetermined particle diameter D (for example, 5 mm) or more from the rolled-out image G, the granular material S is spread to a thickness that does not bury the granular material having the predetermined particle diameter D or larger. It is desirable to shoot out. In addition, since the particle size index Ii calculated by the calculation means 18 described later can vary depending on the thickness and width (area) of the start, it is desirable that the granular material S is always started in the same manner (thickness and width). Instead of the method of rolling out on the sheet, the granular material S thinly placed on the mobile conveyance machine 3 such as a belt conveyor may be imaged to form a rolled-out image G. In addition, it is desirable to include a lighting device (not shown) in the imaging device 5 and take a plurality of rolled-out images G of the granular material S while changing the lighting direction by the lighting device. Expected to improve the accuracy of detecting the contour of the granular material by avoiding the influence of the shadow when detecting the contour of the granular material from the image G by using a plurality of squeezed images G having different shadows by changing the illumination direction it can.

  The computer 10 in the illustrated example includes an input device 11 such as a keyboard, an output device 12 such as a display, and storage means 16 such as a primary or secondary storage device. The storage device 16 stores a relational expression K and other parameters for converting the particle size index Ii of the granular material S into a product passage rate P (di), as will be described later. Further, as the built-in program, an input unit 14 that inputs a rolled-out image G and other data from the imaging device 5 and the input device 11, and a detecting unit 17 that detects the contour of each granular material in the granular material S from the rolled-out image G. And calculating means 18 for calculating the particle size index Ii of the granular material S from the contour of each granular material, and converting the calculated particle size index Ii into a product passage rate P (di), and a particle size accumulation curve P (d) And an output means 13 for outputting the created particle size accumulation curve P (d) and the like to the output device 12. The computer 10 in the illustrated example has the relational expression setting means 26 for setting the relational expression K as a built-in program. However, as will be described later, in the present invention, if the relational expression K is stored in the storage means 16. The relational expression setting means 26 is not essential for the present invention.

  Preferably, as shown in the drawing, a separation device 6 for separating a fine granular material (silt, clay, etc.) having a predetermined particle size D (for example, 5 mm) from the granular material S is included in the particle size measurement system. A fine granular material is separated from the granular material S, and then a rolled-out image G is captured and input to the computer 10. For example, if the granular material S contains a large amount of fine granular material having a particle size less than D, which is difficult to detect the contour from the image G, the granular material having the particle size D or larger is buried in the fine granular material. Therefore, it becomes difficult for the detection means 17 to accurately detect the outline of the necessary granular material from the rolled-out image G. Further, when the fine granular material is agglomerated or stuck to a large particle, the detection means 17 may erroneously recognize the particle diameter of the granular material, and an error may occur in the particle size index Ii calculated by the calculation means 18. There is. By separating the fine granular material from the granular material S by the separating device 6 in advance, it is possible to improve the accuracy of detecting the contour of each granular material in the detecting means 17 and to improve the accuracy of calculating the particle size index Ii in the calculating means 18. it can. The separation device 6 to be used may differ depending on the state of the fine granular material in the granular material S. For example, when the fine granular material is dry, a sieving device is used, and the fine granular material is wetted to other granular material. If you are stuck, you can use a washing machine. However, the separation device 6 is not essential for the system of the present invention. For example, when the particulate material S has a small amount of fine particulate material, and the detection means 17 is less likely to misrecognize the particle size of the particulate material, The separating device 6 can be omitted.

  FIG. 2 shows a flow chart of a method for creating a particle size accumulation curve P (d) of the granular material S using the system of FIG. The system of FIG. 1 will be described below with reference to the flowchart of FIG. Steps S101 to S104 in FIG. 2 are performed by the relational expression setting means 26 of the computer 10 and the particle size index Ii of each particle size di of the granular material S and the accumulated passage rate P (di) of the granular material having the particle size di or less. An initial process for setting the relational expression K is shown. First, in step S101, the sample T of the granular material S is used. In the case of FIG. 1, the separation device 6 separates a minute granular material having a predetermined particle diameter D (for example, 5 mm) from the sample T, and the imaging device 5 then samples the sample. A rolled-out image G of T is captured and input to the computer 10. Further, with respect to the sample T after the separation of the fine granular material, the accumulation passage rate P (di) of the granular material having a plurality of particle diameters di (for example, 10 mm, 20 mm, 30 mm, and 40 mm shown in FIG. 5) in the sample T or less. Is obtained by sieving or other conventional methods, and the accumulated passing rate P (di) of each obtained particle diameter di is input from the input device 11 to the computer 10.

  In step S102, the rolled-out image G is input to the detection means 17 of the computer 10, and the contours of the individual granular materials in the image G are detected as shown in FIG. For example, the image G is binarized based on the brightness of the pixels, and the contour of each particle is extracted from the binarized image using a technique such as labeling or pattern matching (see FIG. 6B). Preferably, an image G of a plurality of specimens T with different shadows photographed by the imaging device 5 is input, and a composite image in which the outline of the granular material is emphasized by synthesizing the plurality of images G by the detection means 17; The contour of each particle is extracted from the synthesized image. Even when it is difficult to detect the contours of all the granular materials in the image G, it is desirable to detect all the contours of the granular materials having a fine particle diameter D (for example, 5 mm) that is the limit that the contour can be detected, and at least step S101. All the contours of the granular material having the minimum particle diameter di (for example, 10 mm) for which the accumulated passage rate P (di) is obtained are detected.

  In step S103, the contour of each granular material in the sample T detected by the detecting means 17 is input to the calculating means 18, and the particle diameter di and area e of each granular material are obtained. For example, when the granular material can be regarded as a sphere as shown in FIG. 4A, the area equivalent diameter of the granular material is the particle diameter di, and the cross-sectional area of the sphere is the area e. Alternatively, as shown in FIG. 4B, an ellipse is fitted to the contour of each granular material (for example, by least square approximation) to obtain a major axis b and a minor axis a, and the minor axis a is determined as the grain size di of the granular material. (Sieving diameter), and the approximate elliptical area is defined as the area e of the granular material. Instead of elliptical approximation, a minimum rectangle circumscribing the contour of each granular material may be obtained, the short axis a of the minimum rectangle may be defined as the particle size di, and the area of the minimum rectangle may be defined as the area e of the granular material. Alternatively, the area e of each granular material can be calculated by converting the number of pixels inside the contour of each granular material into an area.

  In step S103, the particle diameter di and the area e of each granular material are obtained, and then a plurality of particle diameters di (for example, 10 mm, 20 mm, 30 mm, 40 mm, etc.) in the specimen T are respectively larger than each particle diameter di. The total area Σe of the material areas is obtained, and the area ratio (= Σe / E) of the granular material having a particle size di or larger with respect to the area E of the entire shooting region of the rolled-out image G is calculated as the particle size index Ii of each particle size di. Instead of the area E of the entire imaging region, the total E of the areas of all the granular materials having a fine particle diameter D (for example, 5 mm) of the contour detection limit in the rolled-out image G or more (a granular material whose contour in the image G cannot be detected) It is also possible to obtain the particle size index Ii of the particle diameter di by calculating the sum Σe of the areas of the granular materials having the particle diameters di or larger with respect to the total area E of all the granular materials.

  Next, in step S104, the particle size index Ii of the plurality of particle diameters di obtained by the calculation means 18 is input to the relational expression setting means 26, and the accumulated passage of each particle diameter di input in step S101 by the relational expression setting means 26 A relational expression K between the rate P (di) and the granularity index Ii obtained by the calculation means 18 is set. For example, as shown in FIG. 5, the product passage rate P (di) and the particle size index Ii of each particle size di in the sample T are plotted on a quadratic plane, and the product passage rate P (di) is set as an objective variable ( Set an appropriate regression model (for example, a granularity index polynomial (multidimensional regression model), logarithmic function, power function, exponential function, etc.) with the granularity index Ii as the explanatory variable (independent variable) as the dependent variable) and the relational expression K And the set relational expression K is stored in the storage means 16.

  Preferably, in step S101, a spread image G of a plurality of specimens T is imaged, and an accumulation passing rate P (di) is obtained from each of the plurality of specimens T, and the accumulated passage obtained from the plurality of specimens T in step S104. A relational expression K is set based on the rate P (di) and the granularity index Ii. As can be seen from FIG. 5, the accumulation passage rate P (di) and the particle size index Ii of each particle size di obtained from the sample T of the granular material S collected at the same collection site are approximately approximated. Therefore, by setting a relational expression K having a correlation coefficient r as large as possible based on a plurality of samples T, the accuracy of estimating the product passage rate P (di) from the granularity index Ii described later can be improved. Can be increased. According to the experiment of the present inventor, for example, by using a sample T of about 5 to 10 of the granular material S, it is possible to set the relational expression K having a correlation coefficient r of about 0.995.

  Note that the setting of the relational expression K in steps S101 to S104 is not necessarily performed at the construction site. For example, the relational expression K is set in advance using a plurality of samples T of the granular material S in a laboratory or the like, and the relational expression is set. It is also possible to input K to the on-site computer 10 and store it in the storage means 16. In this case, it is sufficient to provide a step of inputting the relational expression K to the computer 10 instead of steps S101 to S104, and the relational expression setting means 26 of the computer 10 for obtaining the relational expression K from the sample T of the granular material S can be omitted. It is.

  Steps S105 to S110 in FIG. 2 are based on the relational expression K stored in the storage unit 16, and calculate the particle size accumulation curve P (d) of the granular material S continuously supplied from the sampling site 1 or the crushing device 2. Indicates the process to create. First, in step S105, similarly to step S101 described above, in the case of FIG. 1, after the particulate material S is separated from the particulate material S by the separating device 6 and the particulate material having a particle diameter less than a predetermined particle size D (for example, 5 mm) is separated, the imaging device 5 A rolled-out image G of the material S is captured and input to the computer 10. In steps S106 to S107, as in steps S102 to 103 described above, the detection means 17 of the computer 10 detects the contours of the individual granular materials in the rolled-out image G, and the calculation means 18 detects a plurality of granular materials in the granular material S. The particle size index Ii of the particle size di (for example, 10 mm, 20 mm, 40 mm, etc.) is calculated.

  In step S110, the particle size index Ii of a plurality of particle sizes di in the granular material S is input to the creation unit 20, and the creation unit 20 calculates the particle size index Ii of each particle size di using the relational expression K and the cumulative passage rate P (di ) To create a particle size accumulation curve P (d). FIG. 7 shows an example of the particle size accumulation curve P (d ≧ D) of the predetermined particle diameter D or more created by the creating means 20 for the granular material S after separation of the fine granular material having a particle diameter of less than the predetermined particle diameter D by the separating device 5. Indicates. In the particle size accumulation curve P in the illustrated example, the particle size index Ii of a plurality of particle sizes di (10 mm, 20 mm, and 40 mm in the illustrated example) is calculated by the calculating unit 18, and the particle size index Ii is generated by the creating unit 20 in FIG. Is converted into a product passage rate P (di) by the relational expression K, and the converted product passage rate P (di) is plotted and connected for each particle size di.

  In steps S111 to 112, the particle diameter accumulation curve P (d) of the granular material S created in step S110 is input to the determination means 24. In the determination means 24, the particle diameter accumulation curve P (d) of the granular material S is input. Is compared with the grain size accumulation curves Pr (d) and Ps (d) of the coarsest grain sample Tr and the finest grain sample Ts, and the process of determining the particle size quality is shown. The coarsest grain sample Tr and the finest grain sample Ts are selected in advance by a number of particle size tests of the granular material S as described above, and the particle size accumulation curves Pr (d) and Ps obtained by the particle size test are selected. For example, (d) can be registered in the storage unit 16 in step S101. Alternatively, as shown in FIG. 7, when comparing with the particle size accumulation curve P (d ≧ D) of the granular material S obtained by separating the fine granular material having a particle size smaller than the predetermined particle size D, the coarsest sample Tr and the finest particle Particle size accumulation curves Pr (d ≧ D) and Ps (d ≧ D) of a predetermined particle size D or more obtained by separating the microparticulate material from the sample Ts can be created and registered in the storage means 16 (FIG. 10). For example, whether or not the particle size accumulation curve P (d ≧ D) of the granular material is within a specified range between the particle size accumulation curves Pr (d ≧ D) and Ps (d ≧ D) by the determination unit 24. The particle size quality of the granular material S is determined by checking (normal or not), which particle size accumulation curve Pr, Ps is fluctuating (trend of variation), and the like.

  Step S113 in FIG. 2 shows processing for adjusting the particle size of the granular material S as necessary when it is determined in steps S111 to 112 that the granular material quality is outside the specified range. The particle size adjustment method differs depending on, for example, whether the particle size accumulation curve P (d ≧ D) of the granular material S in FIG. 7 is out of the coarsest sample Tr or the finest sample Ts. The particle size of the granular material S can be adjusted by comprehensively considering the determination result of the particle size accumulation curve P. After adjusting the particle size, the process returns to step S105, and the above-described steps S105 to S112 are performed again. However, the particle size adjustment in step S113 is not essential to the present invention, and the unit water amount mixed into the granular material S can be adjusted in step S113 so as to be within the specified range of the rhombus in FIG. When the granular material S determined to be out of the range is not used for civil engineering work, step S113 can be omitted.

If the particle size quality of the granular material S is determined to be within the prescribed range at Step S111~112 proceeds to step S114, for example, the particle size index I _t of each particle size di of the current supplied particulate material S _t in FIG. 7 In addition, after accumulating the particle size accumulation curve P _t (d ≧ D) in the storage unit 16, it is determined whether or not to continue the particle size measurement of the granular material S in step S115. When continuing, it returns to step S105, repeats step S105-S112 mentioned above about the granular material St _{t + 1} supplied next time, calculates the particle size index I _{t + 1} of di of each particle size, and creates the particle size accumulation curve P _{t + 1} To do. In step S114, the particle size index I and / or the particle size accumulation curve P of the granular material S is accumulated and stored in the storage unit 16, so that the determination unit 24 supplies the current time in the determination processing of the next steps S111 to 112. comparing the particle size index _{I t} or grain size accumulation curve P _{(d) t} and particle size index of the previous feed _{S t-1 I t-1} or grain size accumulation curve P _{(d) t-1} of the material _{S t} Thus, it is possible to determine a change with time in the particle size of the granular material S (particle size variation) and quickly grasp the change in the particle size quality of the granular material S.

  The present invention uses a relational expression between the particle size index Ii of each particle size di that can be detected relatively easily from the rolled-out image G of the granular material S and the accumulated passage rate P (d) of the particle size di, The accumulated passage rate P (d) of a plurality of particle sizes d is estimated from the rolled-out image G of the granular material S, and the particle size accumulation curve P of the granular material S is obtained using the accumulated passage rate P (d). It can be created easily. Further, by comparing the particle size accumulation curve P with the diameter accumulation curves Pr and Ps of the coarsest grain sample Tr and the finest grain sample Ts, the continuously supplied granular material S becomes the coarsest grain sample Tr. And the granularity quality of whether or not it is within a specified range surrounded by the finest specimen Ts. Therefore, by applying the present invention to the civil engineering work that requires the granularity control of the granular material S, the frequency of the granularity management of the granular material S can be greatly increased as compared with the conventional method. Can contribute to improving the quality control of civil engineering structures.

  Thus, the provision of a “system and program capable of creating a particle size accumulation curve from an image of a granular material”, which is an object of the present invention, can be achieved.

  As described above with reference to FIG. 7, in the present invention, a particle size accumulation curve P (d ≧ D) of a predetermined particle size D (for example, 5 mm) or more from the granular material S after separation of the fine granular material according to the flowchart of FIG. 2. And the particle size accumulation curve P (d ≧ D) is equal to or larger than the predetermined particle size D of the coarsest sample Tr and the finest sample Ts, and Ps (d ≧ D). By comparing with ≧ D), it is possible to easily determine the particle size quality. However, the particle size accumulation curve P (d ≧ D) in FIG. 7 does not reflect the content of the fine granular material having a particle size less than the predetermined particle size D. When a large amount of granular material is included, the particle size accumulation curve P (d ≧ D) of the granular material S is compared with the coarsest sample Tr and the finest sample Ts in the vicinity of the predetermined particle size D. It becomes difficult to confirm to which side it is fluctuating (trend of fluctuation). In order to simplify the comparison between the coarsest grain sample Tr and the finest grain sample Ts, a particle size accumulation curve P (d ≧ D) is created in consideration of the content of the fine granular material having a particle size less than the predetermined particle size D. It is useful to do.

  In the embodiment of FIG. 1, the particle size measuring system includes a separation device 6 that separates the fine granular material, and a measuring device 7 that measures the weight M and moisture content Z of the granular material S before and after separating the fine granular material, 8, the computer 10 is provided with computing means 25 for obtaining the accumulated passage rate P (D) of the fine granular material in the granular material S from the measured values of the weight M and the moisture content Z. In step S108 of FIG. 2, the calculation means 25 of the computer 10 determines the content of the fine granular material in the granular material S, that is, the addition from the measured values of the weight M and the moisture content Z of the granular material S before and after separating the fine granular material. The process which calculates | requires the product passage rate P (D) is shown. In step S110, the accumulated passage rate P (D) of the fine granular material obtained by the computing means 25 is input to the creating means 20 (see also FIG. 1), and the creating means 20 performs the particle size accumulation of the granular material S in FIG. By adjusting the curve P (d ≧ D) according to the accumulation passage rate P (D) of the fine granular material, for example, the particle size of the granular material S in consideration of the content of the fine granular material as shown in FIG. An accumulation curve P (d ≧ D) is created.

  FIG. 3 shows a detailed flowchart of the processing by the computing means 25 in step S108 of FIG. First, in steps S201 to S202, the weight Mb and the moisture content measuring instrument 8b are used to determine the weight Mb and moisture content Zb of the granular material S before separating the fine particulate material having a particle diameter of less than a predetermined particle size D (for example, 5 mm) by the separation device 6. In step S203, the dry weight Mdb of the granular material S before separation of the fine granular material is calculated. Next, the weight Ma and moisture content Za of the granular material S after separation of the fine granular material by the separation device 6 in steps S204 to S205 are measured by the weight measuring device 7a and the moisture content measuring device 8a, and in step S206, the fine granular material is measured. The dry weight Mda of the granular material S after separation is calculated. An example of the weight measuring devices 7b and 7a is a device conventionally used for measuring the mass of the granular material S such as a balance or a load cell. An example of the moisture content measuring devices 8b and 8a irradiates the granular material S with near infrared rays. Thus, a near-infrared moisture meter (see Patent Document 3) or an RI moisture meter that measures the moisture content of the granular material S in a non-contact manner from the attenuation amount of transmitted light or reflected light. In step S207, from the dry weights Mdb and Mda of the granular material S before and after the separation of the fine granular material, the mass percentage of the fine granular material having a particle diameter less than D in the granular material S, that is, the cumulative passage rate P (D) is calculated. .

  In step S110 of FIG. 2, the creation means 20 inputs the accumulated passage rate P (D) of the fine granular material having a particle diameter less than the predetermined particle diameter D in the granular material S input from the calculating means 25 and the particle size calculated by the calculating means 18. The particle size accumulation considering the accumulation passage rate P (D) of the fine granular material as shown in FIG. 8 from the accumulation passage rate P (di) of each particle size di obtained by converting the index Ii by the relational expression K. A curve P (d ≧ D) is created. Specifically, a mass ratio of a predetermined particle diameter D or more is obtained from the accumulation passage ratio P (D) of the fine granular material (100-P (D)), and the accumulation passage converted from the mass ratio and relational expression K is obtained. Multiplying by the rate P (di) (mass ratio of the granular material having the particle size di or more in the entire granular material having the predetermined particle size D or more), the accumulated passage rate P ′ (di) (= P (D) + (100−P (D)) × P (di)) is recalculated. By plotting and connecting the accumulation passage rate P ′ (di) of each particle size di after recalculation and the accumulation passage rate P (D) of the fine granular material for each particle size di, as shown in FIG. A particle size accumulation curve P (d ≧ D) can be created.

  The particle diameter accumulation curve P (d ≧ D) of the granular material S prepared in consideration of the accumulation passage rate P (D) of the fine granular material is the coarsest particle as shown in FIG. The particle size quality can be determined by directly comparing with the particle size accumulation curves Pr (d) and Ps (d) of the sample Tr and the finest sample Ts. For example, in FIG. 8, the particle size accumulation curve P (d ≧ D) of the granular material S is within the specified range of the particle size accumulation curves Pr and Ps, but in the vicinity of the predetermined particle size D, the coarsest sample Tr It can be determined that the particle size distribution is closer to the finest sample Ts side than the side and slightly finer than the average particle size. In addition, if the particle size accumulation curve P (d ≧ D) as shown in FIG. 8 is accumulated and stored, by comparing the current particle size accumulation curve P with the previous one in steps S111 to S112, the granular material is obtained. It is possible to quickly grasp an accurate change with time in the particle size of S (particle size variation).

  Steps S208 to S211 in FIG. 3 include a measuring instrument (not shown) for measuring the water absorption q and the surface dry density ρ for each particle diameter di of the granular material S in the particle diameter measuring system of the present invention. 10 shows a process of calculating the surface water amount W of the granular material S from the measured values of the water absorption rate q and the surface dry density ρ by 10 arithmetic means 25. As described above with reference to FIG. 11, in the CSG method, it is necessary to manage the unit water amount together with the particle size of the granular material S (see the prescribed range of the rhombus (hatched portion) in FIG. 11), and the surface water amount of the granular material S If W is obtained, it can be used to manage the unit water volume. In the flowchart of FIG. 3, the water absorption rate q of the granular material S is input from the measuring instrument in steps S208 to S209, and the surface water content ω of the granular material S is calculated based on the moisture content Zb measured in step S202. In step S210, the surface dry density ρ of the granular material S is input from the measuring instrument, and in step S211, the surface water amount W is calculated from the surface water ratio ω and the surface dry density ρ of the granular material S. For example, in step S113 in FIG. 3, based on the surface water amount W obtained in step S211, the amount of water mixed in the granular material S is adjusted and managed so as to be within the prescribed range of “diamonds” in FIG.

Further, in step S114 of FIG. 2, the current feed _S particle size of each particle size di of _t index _{I t} and particle size accumulation curve _P t (d) together with the surface water _{W t} obtained in step S211 in the storage unit 16 Once you have accumulatively stored, compared in the determination process of the next subsequent step S111～112, the determination means 24 of the current and the previous and granularity index _{I t} and grain size accumulation curve P _{(d) t} and surface water _{W t} Thus, fluctuations in particle size and surface water amount can be quickly determined. By quickly grasping the change in the particle size and surface water amount of the granular material S, detailed quality control in construction work using the granular material S such as the CSG method can be performed, and further improvement in management accuracy can be expected.

  Further, in the embodiment of FIG. 1, the storage means 16 of the computer 10 stores the particle size accumulation curve P (d ≦ D) of the fine granular material having a particle size less than the predetermined particle size D obtained from the sample T of the granular material S. If stored as functions U and R of the cumulative passage rate P (D) of the fine granular material in T, the fine granularity in the granular material S obtained by the calculating means 25 described above in the estimating means 27 of the computer 10 is stored. The particle size accumulation curve P (d ≦ D) of the fine granular material can be estimated from the material passing rate P (D) by the functions U and R. Further, in the creating means 20, for example, as shown in FIG. 8, the particle size accumulation curve P (d ≧ D) of the granular material S after separation of the fine granular material, and the fine granular material of the granular material S estimated by the estimating means 27 The particle size accumulation curve P (d) over the entire particle size range as shown in FIG. 9, for example, can be created by synthesizing the particle size accumulation curve P (d ≦ D).

  Conventionally, a particle size accumulation curve (particle size distribution) of a granular material S such as a ground material is represented by a normal distribution function, a log normal distribution function, a Talbot (Gates-Gaudin-Schuhmann) function, a Gaudin-Meloy function, a Rosin-Rammeler function, and the like. It is known that can be approximated by (see Non-Patent Document 2). In addition, the present inventors estimate an approximate function of a particle size accumulation curve P (d <D) of a fine granular material having a predetermined particle size D (for example, 50 mm) from a plurality of specimens T of the granular material S, and the granular material A particle size accumulation curve P (d ≧ D) having a predetermined particle size D or more is created from the rolled-out image G of S using an image analysis technique, and the particle size accumulation curve P (d ≧ D) and the particle size accumulation are created. The approximate function of the curve P (d <D) is synthesized so as to coincide with the accumulation passage rate P (D) of the predetermined particle size D, and the particle size accumulation curve P (d over the entire particle size range of the granular material S is obtained. ) Was developed and disclosed in Patent Document 4.

Also in the present invention, if an approximate function U of a particle size accumulation curve P (d ≦ D) of a fine granular material having a particle size less than a predetermined particle size D is obtained in advance from the sample T of the granular material S, Similarly, an approximate function U of a particle size accumulation curve P (d ≧ D) of a predetermined particle size D or more obtained from the particle size index Ii in the creating means 20 and a particle size accumulation curve P (d ≦ D) of a fine granular material. And a particle size accumulation curve P (d) over the entire particle size range of the granular material S can be created. The particle size accumulation curve P (d ≦ D) of the granular material S less than the predetermined particle size D is, for example, a predetermined exponential function U {(d / D) ⁿ }. Examples of such an exponential function P are Talbot function (P / P (D) = (d / D) ⁿ ), Gaudin-Meloy function (P / P (D) = 1− (1-d / D) ⁿ ) Or Rosin-Rammler function (P / P (D) = 1−exp (−d / D) ⁿ )).

In step S109 of FIG. 2, the particle size accumulation curve P (d ≦ D) of the fine granular material is calculated by the function U from the cumulative passage rate P (D) of the fine granular material in the granular material S by the estimating means 27 of the computer 10. ) Is shown. For example, if the index ^{n of} the above-mentioned predetermined exponential function U {(d / D) ⁿ } is constant regardless of the cumulative passage rate P (D) of the fine granular material, the fine granular material obtained by the calculating means 25 By substituting the accumulation passage rate P (D) into the designated function U {(d / D) ⁿ }, the particle size accumulation curve P (d ≦ D) of the fine granular material can be estimated. In step S110 of FIG. 2, the particle diameter accumulation curve P (d ≦ D) of the fine granular material estimated by the estimating means 27 is input to the creating means 20, and the particle diameter accumulation curve P (d ≦ D) and a predetermined value are inputted. By connecting the particle size accumulation curve P (d ≧ D) of the particle size D or more, the particle size accumulation curve P (d) over the entire particle size range as shown in FIG. 9 can be created.

Further, as disclosed in Patent Document 4, when the particle size accumulation curve P (d ≦ D) of a fine granular material is approximated by a predetermined exponential function U {(d / D) ⁿ }, the exponential function U { The index n of (d / D) ⁿ } may vary depending on the cumulative passage rate P (D) of the fine granular material in the granular material S. In this case, an exponential function U {(d / D) ⁿ } is obtained from a plurality of samples T of the granular material S, and the exponent n and the cumulative passage rate P (D) of the fine granular material in the granular material S are obtained. The relational expression R is detected, and the relational expression R is stored in the storage unit 16 of the computer 10. In step S109 of FIG. 2, first, an exponent n is obtained from the accumulated passage rate P (D) of the fine granular material obtained by the computing means 25, and an exponential function U {(d / D) ⁿ } is determined. By substituting the cumulative passage rate P (D) of the fine granular material into the exponential function U {(d / D) ⁿ }, the particle size accumulation curve P (d ≦ D) of the fine granular material is estimated. If the particle size accumulation curve P (d) over the entire particle size range as shown in FIG. 9 is created in step S110, the particle size addition of the coarsest sample Tr and the finest sample Ts is performed in steps S111 to 112. The product curves Pr (d) and Ps (d) can be compared over the entire particle size range, and the particle size quality of the granular material S can be determined with high accuracy.

DESCRIPTION OF SYMBOLS 1 ... Collection place (natural ground) 2 ... Crushing device 3 ... Conveying device 5 ... Imaging device 6 ... Separation device 6, 8 ... Measuring instrument 7a, 8a ... Weight measuring instrument 7b, 8b ... Water content measuring instrument 10 ... Computer 11 ... Input device 12 ... Output device 14 ... Input means 15 ... Output means 16 ... Storage means 17 ... Detection means 18 ... Calculation means 20 ... Create means 21 ... Adjustment means 22 ... Synthesis means 24 ... Determining means 25 ... Calculation means 26 ... Relational expression Setting means 27 ... Estimating means S ... Granular material T ... Granular material specimen P ... Accumulation passage rate, particle size accumulation curve I ... Particle size index Di ... Particle size Ei ... Area G ... Extruded image M ... Weight Z ... Water content

Claims (12)

An imaging device that captures a sputtered image of granular material supplied from a predetermined collection site or crushing device, detection means for detecting the contour of each granular material in the image, and obtaining the particle size and area from the contour of each granular material In addition, for a plurality of particle diameters di, calculation means for calculating, as a particle size index Ii, an area ratio of the granular material having the particle diameter di or larger with respect to the entire area of the granular material in the image, each particle diameter di obtained from the sample of the granular material Storage means for storing a relational expression between the particle size index Ii and the cumulative passage rate P (di) which is the mass ratio of the granular material having a particle size di or less in the sample to the total mass of the sample, and each calculated particle A creation means for creating a particle size accumulation curve P (d) by converting the particle size index Ii of the diameter di into a product passage rate P (di) which is a mass ratio with respect to the total mass of the granular material by the relational expression is provided. Particle size measurement system comprising particulate material. 2. The system according to claim 1, wherein a separation device for separating a fine granular material having a particle size less than a predetermined particle size D from the granular material is provided, and a particle size index Ii obtained from the granular material sample after separation of the fine granular material is added to the storage means. A granular material particle size measurement system that stores a relational expression with a passing rate P (di) and creates a particle size accumulation curve P (d ≧ D) of a predetermined particle size D or more by the creation means. 3. The system according to claim 2, wherein the measuring device measures the weight and moisture content of the granular material before and after separating the fine granular material, and the accumulated passage of the fine granular material in the granular material from the measured value of the weight and moisture content. An arithmetic means for obtaining a rate P (D) is provided, and by the creation means, the cumulative passage rate P (di) of each particle diameter di of the granular material after separation of the fine granular material and the fine granular material in the granular material are determined. A particle size measurement system for a granular material obtained by creating a particle size accumulation curve P (d ≧ D) from the accumulation passage rate P (D). 4. The system according to claim 3, wherein a particle size accumulation curve P (d ≦ D) of a fine granular material having a particle diameter less than a predetermined particle size D obtained from a granular material sample is stored in the storage means. This is stored as a function of the passage rate P (D), and the particle size accumulation curve P (d ≦ D) of the fine granular material is estimated by the above function from the cumulative passage rate P (D) of the fine granular material in the granular material. The estimation means is provided, and by the creation means, the particle size accumulation curve P (d ≧ D) of the granular material after separation of the fine granular material and the particle size accumulation curve P (d ≦ D) of the fine granular material of the granular material are determined. D) and a particle size measurement system for a granular material obtained by creating a particle size accumulation curve P (d). The system according to any one of claims 1 to 4 , wherein the storage means stores particle size accumulation curves Pr, Ps of the coarsest sample and the finest sample of granular material, and the particle size accumulation curve of the granular material. A granular material particle size measurement system provided with a determining means for comparing P with the particle size accumulation curves Pr and Ps of the coarsest sample and the finest sample to determine the particle quality. 5. The system according to claim 1, wherein the particle size index I or the particle size accumulation curve P created from the granular material continuously supplied to the storage means is accumulated and stored, and the particle size index I _{t of the} current supply material is stored. or grain size accumulation curve P _t and particulate material formed by providing a determining means for determining a particle size variation of particulate material by comparing the particle size index I _t-1 or grain size accumulation curve P _t-1 of the previous feed Particle size measurement system. A computer for measuring the particle size of the granular material supplied from a predetermined sampling site or a crushing device; input means for inputting a spear image of the granular material; detection means for detecting the contour of each granular material in the image; Calculating means for calculating a particle size and an area from an outline of each granular material and calculating an area ratio of the granular material equal to or larger than the particle size di with respect to the total area of the granular material in the image for a plurality of particle sizes di as the particle size index Ii; Relational expression between the particle size index Ii of each particle size di obtained from the sample of the granular material and the cumulative passage rate P (di) which is the mass ratio of the granular material having the particle size di or less in the sample to the total mass of the sample And a particle size index Ii of each calculated particle size di is converted into a product passage rate P (di) which is a mass ratio with respect to the total mass of the granular material by the relational expression. Grain 径加 granularity measurement program of the particulate material to function as a creating means for creating a product curve P (d) Te. 8. The program according to claim 7, wherein the squeezed image is a squeezed image of a granular material from which a fine granular material having a particle diameter less than a predetermined particle size D is separated, and the particle size obtained from the granular material sample after separation of the fine granular material in the storage means. The relational expression between the index Ii and the cumulative passage rate P (di) is stored, and the particle size measurement of the granular material formed by creating the particle diameter accumulation curve P (d ≧ D) of the predetermined particle diameter D or more by the creating means. program. 9. The program according to claim 8, wherein the weight and moisture content of the granular material before and after separating the fine granular material are input to the input means, and the computer detects the fine granular material in the granular material from the input values of the weight and moisture content. The cumulative passage rate P (di) of each particle size di of the granular material after separation of the fine granular material is determined by the creation means so as to calculate the cumulative passage rate P (D) of the granular material. Is a particle size measurement program for a granular material obtained by creating a particle size accumulation curve P (d ≧ D) from the accumulated passage rate P (D) of the fine granular material. 10. The program according to claim 9, wherein a particle size accumulation curve P (d ≦ D) of a fine granular material having a particle size less than a predetermined particle size D obtained from a granular material sample is stored in the storage means. It is stored as a function of the passage rate P (D), and the computer calculates the particle size accumulation curve P (d ≦ d) of the fine granular material according to the function from the accumulated passage rate P (D) of the fine granular material in the granular material. D) functions as an estimation means for estimating the particle diameter accumulation curve P (d ≧ D) of the granular material after separation of the fine granular material and the particle diameter accumulation of the fine granular material of the granular material. A particle size measurement program for a granular material obtained by synthesizing a curve P (d ≦ D) to create a particle size accumulation curve P (d). 11. The program according to claim 7 , wherein the storage means stores the coarsest grain sample of the granular material and the particle size accumulation curves Pr and Ps of the finest grain sample, and the computer stores the grain of the granular material. A particle size measurement program for a granular material that functions as a determination means for determining the particle size quality by comparing the diameter accumulation curve P with the particle size accumulation curves Pr and Ps of the coarsest sample and the finest sample. 11. The program according to claim 7 , wherein the particle size index I or the particle size accumulation curve P of the granular material continuously supplied to the storage means is accumulated and stored, and the computer stores the particle size index of the current supply material. to function as a judging means for judging particle size variation of I _t or grain size accumulation curve P _t and particle size index I _t-1 or grain size accumulation curve P _t-1 and the particulate material by comparing the previous feed Particle size measurement program for granular materials.