JP5658613B2 - Method and system for dividing particle size of granular material - Google Patents
Method and system for dividing particle size of granular material Download PDFInfo
- Publication number
- JP5658613B2 JP5658613B2 JP2011109125A JP2011109125A JP5658613B2 JP 5658613 B2 JP5658613 B2 JP 5658613B2 JP 2011109125 A JP2011109125 A JP 2011109125A JP 2011109125 A JP2011109125 A JP 2011109125A JP 5658613 B2 JP5658613 B2 JP 5658613B2
- Authority
- JP
- Japan
- Prior art keywords
- granular material
- particle size
- image
- passage rate
- predetermined
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- 239000008187 granular material Substances 0.000 title claims description 448
- 239000002245 particle Substances 0.000 title claims description 435
- 238000000034 method Methods 0.000 title claims description 52
- 238000009825 accumulation Methods 0.000 claims description 119
- 230000001186 cumulative effect Effects 0.000 claims description 35
- 238000000926 separation method Methods 0.000 claims description 23
- 238000004364 calculation method Methods 0.000 claims description 22
- 239000000463 material Substances 0.000 claims description 21
- 238000005259 measurement Methods 0.000 claims description 20
- 238000003384 imaging method Methods 0.000 claims description 17
- 238000003860 storage Methods 0.000 claims description 15
- 238000000691 measurement method Methods 0.000 claims description 8
- 238000005096 rolling process Methods 0.000 claims description 3
- 230000011218 segmentation Effects 0.000 claims description 3
- 238000002955 isolation Methods 0.000 claims 2
- 230000008569 process Effects 0.000 description 15
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 description 14
- 238000010276 construction Methods 0.000 description 13
- 238000001514 detection method Methods 0.000 description 12
- 239000002352 surface water Substances 0.000 description 10
- 238000010191 image analysis Methods 0.000 description 9
- 238000003908 quality control method Methods 0.000 description 9
- 238000009826 distribution Methods 0.000 description 7
- 239000011236 particulate material Substances 0.000 description 7
- 238000007873 sieving Methods 0.000 description 6
- 238000007726 management method Methods 0.000 description 5
- 238000012360 testing method Methods 0.000 description 5
- 230000008859 change Effects 0.000 description 4
- 238000010586 diagram Methods 0.000 description 4
- 238000012545 processing Methods 0.000 description 4
- 230000002194 synthesizing effect Effects 0.000 description 4
- 238000010521 absorption reaction Methods 0.000 description 3
- 238000002474 experimental method Methods 0.000 description 3
- 238000002360 preparation method Methods 0.000 description 3
- 238000006243 chemical reaction Methods 0.000 description 2
- 238000007796 conventional method Methods 0.000 description 2
- 238000011161 development Methods 0.000 description 2
- 230000018109 developmental process Effects 0.000 description 2
- 239000010432 diamond Substances 0.000 description 2
- 238000003703 image analysis method Methods 0.000 description 2
- 238000009434 installation Methods 0.000 description 2
- 239000011435 rock Substances 0.000 description 2
- 238000005070 sampling Methods 0.000 description 2
- 238000003892 spreading Methods 0.000 description 2
- 230000007480 spreading Effects 0.000 description 2
- 239000004575 stone Substances 0.000 description 2
- 230000015572 biosynthetic process Effects 0.000 description 1
- 239000004568 cement Substances 0.000 description 1
- 239000004927 clay Substances 0.000 description 1
- 239000011362 coarse particle Substances 0.000 description 1
- 230000001419 dependent effect Effects 0.000 description 1
- 238000011496 digital image analysis Methods 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 239000010419 fine particle Substances 0.000 description 1
- 230000005484 gravity Effects 0.000 description 1
- 230000006872 improvement Effects 0.000 description 1
- 238000002372 labelling Methods 0.000 description 1
- LFEUVBZXUFMACD-UHFFFAOYSA-H lead(2+);trioxido(oxo)-$l^{5}-arsane Chemical group [Pb+2].[Pb+2].[Pb+2].[O-][As]([O-])([O-])=O.[O-][As]([O-])([O-])=O LFEUVBZXUFMACD-UHFFFAOYSA-H 0.000 description 1
- 238000010298 pulverizing process Methods 0.000 description 1
- 239000004576 sand Substances 0.000 description 1
- 239000002689 soil Substances 0.000 description 1
- 239000007787 solid Substances 0.000 description 1
- 238000010415 tidying Methods 0.000 description 1
- 238000005406 washing Methods 0.000 description 1
Landscapes
- Image Processing (AREA)
- Length Measuring Devices By Optical Means (AREA)
Description
本発明は粒状材料の分割式粒度計測方法及びシステムに関し、とくに粒径の異なる粒状材が混在した粒状材料を複数に分割したうえで分割前の粒度を計測する方法及びシステムに関する。 The present invention relates to a divided particle size measurement method and system for granular materials, and more particularly to a method and system for measuring particle sizes before division after dividing a granular material in which granular materials having different particle sizes are mixed.
ダム・堤防・路体・路盤・路床・コンクリート・舗装・植栽基盤等の土木構造物を構築する場合に、粒度が調整された骨材や砕石ではなく、現場付近の地山等の採取場で調達された地盤材料、原石を破砕装置等で砕いただけの岩砕材料その他の粒状材料S(粒径の異なる粒状材が混在した土木材料)を用いる工法を採用する場合がある(例えば非特許文献1のCSG(Cemented Sand and Gravel)工法等)。このような粒状材料Sを用いる工法(CSG工法等)では、材料合理化の観点から、調達した粒状材料S(CSG材)に水及びセメントを混合してそのまま土木構造物の材料(CSG)とすることが多く、構造物の品質(特に強度)を確保するために粒状材料Sの粒度が規定範囲内にあるか否かを確認・管理することが必要となる。 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 procured on the ground, a rough material obtained by crushing raw stone with a crushing device, or other granular material S (a civil engineering material in which granular materials having different particle diameters are mixed) is employed (for example, non- CSG (Cemented Sand and Gravel) method of Patent Document 1). In such a construction method using the granular material S (CSG construction method, etc.), from the viewpoint of material rationalization, water and cement are mixed with the procured granular material S (CSG material) to obtain a civil engineering structure material (CSG) as it is. In many cases, it is necessary to confirm and manage whether or not the particle size of the granular material S is within a specified range in order to ensure the quality (particularly strength) of the structure.
図13は、CSG工法によって構築する土木構造物の強度管理方法の一例を示す(ひし形理論、非特許文献1参照)。先ず、粒状材料S(CSG材)の粒度について数多くの粒度試験を行い、粒度が最も粗い標本Tr(大径粒状材の含有率が最も多い標本。以下、最粗粒標本ということがある)と粒度が最も細かい標本Ts(小径粒状材の含有率が最も多い標本。以下、最細粒標本ということがある)とを選定する。次いで、最粗粒標本Tr及び最細粒標本Tsの範囲内の粒状材料Sを用いたCSGについて単位水量を変えながら強度試験を行い、強度不足となる下限値と施工に不向きな上限値とを検出する。そのうえでCSGの製造時ないし打設時に、CSGの粒度及び単位水量を、最粗粒標本Trの粒度−強度曲線(図中の点線)と最細粒標本Tsの粒度−強度曲線(図中の実線)と2本の許容単位水量範囲を示す縦線とで囲まれた「ひし形」(斜線部分)の規定範囲内となるように管理する。図示例のひし形の規定範囲内で最も低い強度はCSG強度と呼ばれ、このひし形の範囲内にあるCSGを用いることで構造物にCSG強度以上の強度を確保することができる。 FIG. 13 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 conducted 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, sometimes referred to as the most coarse particle sample) A sample Ts having the finest particle size (a sample having the largest content of small-diameter granular material, hereinafter may be referred to as the finest particle sample) is selected. 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.
一般に粒状材料Sの粒度は、混在している各粒状材の粒径dを横軸(対数軸)とし、その粒径d以下の粒状材の全体に対する質量百分率P(d)(粒径dの粒状材より小径の粒状材の総質量/粒状材全体の総質量×100。以下、加積通過率ということがある)を縦軸(線形軸)とした片対数グラフ、すなわち図12に示すような粒径加積曲線P(d)によって表される。従って、図12のように粒状材料Sの最粗粒標本Trの粒径加積曲線Pr(d)と最細粒標本Tsの粒径加積曲線Ps(d)とを予め求めておき、継続的に供給される粒状材料Sの粒径加積曲線P(d)が粒径加積曲線Pr(d)と粒径加積曲線Ps(d)とで囲まれた範囲(規定範囲)内にあるか否かを確認すれば、図13のひし形理論に基づく粒度の品質管理が実現できる。 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 As shown in FIG. 12, a semi-logarithmic graph with the vertical axis (linear axis) as the total mass of the granular material having a diameter smaller than that of the granular material / the total mass of the entire granular material x 100. Represented by a simple particle size accumulation curve P (d). Accordingly, as shown in FIG. 12, 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 and continued. The particle size accumulation curve P (d) of the granular material S to be supplied is within a range (specified range) surrounded by the particle size accumulation curve Pr (d) and the particle size accumulation curve Ps (d). If it is confirmed whether or not there is, quality control with granularity based on the rhombus theory of FIG. 13 can be realized.
しかし、様々な粒径dの粒状材が混在している粒状材料Sの粒径加積曲線Pを作成するためには、例えばダム等の土木工事において1回当たり数百〜数千kgにもなる大量の粒状材料Sを何度も篩い分けする作業と、篩い分け毎(篩目のサイズ毎)に通過率(通過質量)を求める作業とが必要であり、しかも現段階ではそれらを全て人力で行う必要があるため、多大な労力と時間を要する問題点がある。CSG工法の品質管理では、とくに施工開始当初において使用する粒状材料Sの粒度をできるだけ頻繁に(例えば1回/1時間で)確認することが望ましいとされているが(非特許文献1参照)、多大な労力・時間を要する篩い分け作業を繰り返すことは土木工事の進捗上の問題ともなるので、粒状材料Sの粒度を簡単に計測できる技術の開発が望まれている。 However, in order to create the particle size accumulation curve P of the granular material S in which granular materials of various particle sizes d are mixed, for example, in civil engineering work such as dams, several hundred to several thousand kg per time It is necessary to screen a large amount of granular material S many times and to obtain a passing rate (passing mass) for each screen (each screen size). Therefore, there is a problem that requires a lot of labor and time. In the quality control of the CSG method, it is desirable to check the granularity 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). Since repeating the sieving work that requires a great amount of labor and time is also a problem in the progress of civil engineering work, development of a technique that can easily measure the particle size of the granular material S is desired.
これに対し本発明者らは、コンピュータによる画像解析技術を用いて粒状材料Sの粒度を求めるシステムを開発し、特許文献1及び2に開示した。従来から、粒状材料S中の各粒状材の輪郭をコンピュータの画像解析により特定し、その輪郭から各粒状材の形状をモデル化して粒度分布曲線を作成する方法が知られている(特許文献3及び4参照)。しかし、従来の画像解析方法は粒状材料Sのうち輪郭の検出できる範囲の粒状材の粒度分布を求めるのみであり、輪郭の検出されない粒状材の材料全体に対する割合を求めることができない問題点がある。上述したCSG工法において粒状材料Sの粒度を管理するためには、粒状材料S中の粒径d毎に全体に対する割合として加積通過率P(d)を求めて粒径加積曲線P(d)を作成する必要があるが、例えばロックフィルダム等で用いる粒状材料Sは最大粒径(1m以上)が最小粒径(0.1mm以下)の1万倍以上にも達する粒径分布幅の広いものであり、そのような粒径分布幅の非常に広い粒状材料Sの粒径加積曲線P(d)を従来の画像解析方法で作成することは困難であった。 On the other hand, the present inventors developed a system for obtaining the particle size of the granular material S by using an image analysis technique by a computer and disclosed it in Patent Documents 1 and 2. Conventionally, a method is known in which the contour of each granular material in the granular material S is specified by computer image analysis, and the shape of each granular material is modeled from the contour to create a particle size distribution curve (Patent Document 3). And 4). However, the conventional image analysis method only obtains the particle size distribution of the granular material in the range where the contour can be detected in the granular material S, and there is a problem that the ratio of the granular material whose contour is not detected to the whole material cannot be obtained. . In order to manage the particle size of the granular material S in the above-described CSG method, the cumulative passage rate P (d) is obtained as a ratio with respect to the entire particle size d in the granular material S, and the particle size accumulation curve P (d However, the granular material S used in, for example, rock fill dams has a wide particle size distribution range in which the maximum particle size (1 m or more) reaches 10,000 times the minimum particle size (0.1 mm or less). Therefore, it has been difficult to create a particle size accumulation curve P (d) of such a granular material S having a very wide particle size distribution width by a conventional image analysis method.
図9は、特許文献1の開示する粒状材料Sの粒度計測システムの一例を示す。図示例のシステムは、所定の採取場(地山や地層)1又は破砕装置2で採取された粒状材料Sの体積Vを測定する測定装置9と、体積計測後の粒状材料Sを薄く撒き出した画像G(図10(A)参照)を撮像する撮像装置5と、粒状材料Sの標本Tから予め求めた所定粒径D未満の微小粒状材の粒径加積曲線P(d≦D)をその標本T中の微小粒状材の加積通過率P(D)の関数U、Rとして記憶する記憶手段16付きコンピュータ10とを有する。またコンピュータ10には、撮像装置5による粒状材料Sの撒き出し画像Gから所定粒径D以上の大径粒状材の輪郭(図10(B)及び(C)参照)を検出する画像解析手段31と、その輪郭の検出値から大径粒状材の各々の体積vを算出して粒径加積曲線P(d≧D)を作成する作成手段37と、大径粒状材の体積vの合計Σvと粒状材料Sの全体積Vの測定値とから粒状材料S中の微小粒状材の加積通過率P(D)(=V−Σv)を算出し且つそ加積通過率P(D)から関数U、Rにより微小粒状材の粒径加積曲線P(d≦D)を推定する推定手段38と、作成手段37で作成した粒径加積曲線P(d≧D)と推定手段38で推定した粒径加積曲線P(d≦D)とを合成する合成手段39(図11参照)を設けている。 FIG. 9 shows an example of a particle size measurement system for the granular material S disclosed in Patent Document 1. The system in the illustrated example includes a measuring device 9 for measuring the volume V of the granular material S collected at a predetermined sampling site (natural ground or formation) 1 or the crushing device 2, and thinly pulverizing the granular material S after volume measurement. The image pickup device 5 for picking up the image G (see FIG. 10 (A)) and 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 in advance from the sample T of the granular material S Is stored as a function U, R of the accumulation passage rate P (D) of the fine granular material in the sample T. Further, the computer 10 has an image analysis means 31 for detecting the outline (see FIGS. 10B and 10C) of a large-diameter granular material having a predetermined particle diameter D or more from the rolled-out image G of the granular material S by the imaging device 5. And a creation means 37 for calculating the volume v of each large-diameter granular material from the detected value of the contour to create a particle size accumulation curve P (d ≧ D), and the total volume Σv of the large-diameter granular material v From the measured value of the total volume V of the granular material S, the cumulative passage rate P (D) (= V−Σv) of the fine granular material in the granular material S is calculated and from the cumulative passage rate P (D). The estimation means 38 for estimating the particle size accumulation curve P (d ≦ D) of the fine granular material by the functions U and R, the particle size accumulation curve P (d ≧ D) created by the creation means 37 and the estimation means 38 A synthesizing means 39 (see FIG. 11) for synthesizing the estimated particle size accumulation curve P (d ≦ D) is provided.
図9の粒度計測システムによれば、画像解析によって輪郭が検出できる大径粒状材の粒径加積曲線P(d≧D)から輪郭が検出できない微小粒状材の粒径加積曲線P(d≦D)を推定し、両者を合成して図11のように粒状材料Sの粒径加積曲線P(d)とすることにより、上述したように粒径分布幅の非常に広い粒状材料Sの粒径加積曲線P(d)を画像解析によって迅速・簡単に作成することができる。そして、粒径加積曲線P(d)を迅速に作成できることから、例えばCSG工法において粒状材料Sの粒度管理の頻度を大幅に増やし、CSG工法により構築される土木構造物の品質管理の精度向上を図ることができる。 According to the particle size measurement system of FIG. 9, the particle size accumulation curve P (d) of the fine granular material whose contour cannot be detected from the particle size accumulation curve P (d ≧ D) of the large granular material whose contour can be detected by image analysis. ≦ D) and synthesizing both to obtain a particle size accumulation curve P (d) of the granular material S as shown in FIG. 11, so that the granular material S having a very wide particle size distribution width as described above. The particle size accumulation curve P (d) can be quickly and easily created by image analysis. And since the particle size accumulation curve P (d) can be created quickly, for example, in the CSG method, the frequency of the particle size control of the granular material S is greatly increased, and the quality control of the civil engineering structure constructed by the CSG method is improved. Can be achieved.
しかし図9の粒度計測システムは、微小粒状材を含む粒径分布幅の広い粒状材料Sの粒径加積曲線P(d)を画像解析処理により迅速・簡単に作成することができ、従来の篩い分け方法に比して粒径加積曲線P(d)の作成に要する労力・時間を大幅に削減できるものの、上述したCSG工法等の土木工事では数百〜数千kgにも及ぶ大量の粒状材料Sの粒度を計測する必要があるので、その撒き出し画像G(図10(A)参照)を撮影するための準備作業(撒き出し作業又は片付け作業)に依然として甚大な労力・時間を要する問題点がある。すなわち、図9において粒状材料Sの撒き出し画像Gを撮影するためには、所定粒径D以上の大径粒状材の輪郭が検出できるような所定厚さ(例えば、所定粒径D以下の厚さ)に粒状材料Sを撒き出す必要があるが(図5(A)参照)、粒状材料Sの量が多くなると撒き出し面積(A×B)も大きくなるのでその撒き出し作業に労力・時間がかかると共に、撒き出し面積の全体が写り込むように撮像装置5の設置高さh(粒状材料Sの撒き出し面から撮像装置5までの距離h≒(A/2)/tan(θ/2)、ただしA≒B、θは撮像装置の画角)も大きくする必要があるので撮影装置5の支持枠等も大型化・大規模化する必要が生じる。 However, the particle size measurement system of FIG. 9 can quickly and easily create a particle size accumulation curve P (d) of a granular material S containing a fine granular material and having a wide particle size distribution range by image analysis processing. Although the labor and time required to create the particle size accumulation curve P (d) can be greatly reduced compared to the sieving method, the civil engineering work such as the CSG method mentioned above has a large amount of several hundred to several thousand kg. Since it is necessary to measure the particle size of the granular material S, a great amount of labor and time are still required for the preparation work (the drawing work or the tidying work) for photographing the rolled image G (see FIG. 10A). There is a problem. That is, in order to photograph the rolled-out image G of the granular material S in FIG. 9, a predetermined thickness (for example, a thickness equal to or smaller than the predetermined particle diameter D) that can detect the outline of the large-diameter granular material having the predetermined particle diameter D or larger. The granular material S needs to be sprinkled (see FIG. 5 (A)), but as the amount of the granular material S increases, the sprinkling area (A × B) also increases, so labor and time for the sprinkling work In addition, the installation height h of the imaging device 5 (distance h from the surface of the granular material S to the imaging device 5≈ (A / 2) / tan (θ / 2) so that the entire protruding area is reflected. However, since A≈B and θ are the angles of view of the image pickup apparatus, it is necessary to increase the size and size of the support frame of the image pickup apparatus 5.
本発明者の実験によれば、例えば1m以上の大粒径の粒状材を含む数百〜数千kgの粒状材料Sを対象として図5(A)のような撒き出し画像Gを撮影する場合は、5m×5m以上の撒き出し面積が必要であり、撮像装置5の設置高さhも7m以上とする必要がある。このように撒き出し面積が大きくなると、単に撒き出し・敷き均し作業の負担が大きくなるだけでなく、撮像装置5の高さhの増大に伴って撒き出し画像Gから輪郭を検出できる粒状材の粒径にも限界が生じるので、画像Gからの粒状材の輪郭検出精度が低下し、ひいては粒状材料Sの粒度管理の精度低下を招くおそれもある。このため、大粒径の粒状材を含む大量の粒状材料Sの粒度を短時間で精度よく計測できる技術の開発が望まれている。 According to the experiment of the present inventor, for example, when a rolled-out image G as shown in FIG. 5 (A) is taken for a granular material S of several hundred to several thousand kg including a granular material having a large particle diameter of 1 m or more. Requires a protruding area of 5 m × 5 m or more, and the installation height h of the imaging device 5 needs to be 7 m or more. In this way, when the protruding area is increased, not only is the burden of spreading and leveling work increased, but also the granular material that can detect the contour from the protruding image G as the height h of the imaging device 5 increases. Therefore, the accuracy of detecting the contour of the granular material from the image G is lowered, and there is a possibility that the accuracy of the particle size management of the granular material S is lowered. For this reason, development of the technique which can measure the particle size of a large amount of granular material S containing a granular material with a large particle size in a short time is desired.
そこで本発明の目的は、大粒径の粒状材を含む粒状材料の分割式粒度を短時間で精度よく計測する方法及びシステムを提供することにある。 Accordingly, an object of the present invention is to provide a method and a system for accurately measuring a divided particle size of a granular material including a granular material having a large particle size in a short time.
図1のブロック図及び図2の流れ図を参照するに、本発明による粒状材料の分割式粒度計測方法は、粒径dの異なる粒状材sが混在した粒状材料Sを複数に分割して各分割粒状材群Sjの撒き出し画像Gj(図10(A)参照)を撮影し、その撒き出し画像Gj毎に各粒状材sの輪郭から面積e及び粒径dと粒状材全体の投影面積Ejとを検出し、前記画像Gj毎の各粒状材sの粒径dから所定粒径diの加積通過率Pj(di)を算出し、撒き出し画像Gj毎の投影面積Ejで重み付けした所定粒径diの加積通過率Pj(di)の全画像にわたる面積平均値(=(ΣPj(di)・Ej)/ΣEj)により分割前の粒状材料Sの所定粒径diの加積通過率P(di)を計測してなるものである。 Referring to the block diagram of FIG. 1 and the flow chart of FIG. 2, the granular material division type particle size measuring method according to the present invention divides a granular material S mixed with granular materials s having different particle diameters d into a plurality of divisions. A rolled-out image Gj (see FIG. 10A) of the granular material group Sj is photographed, and for each rolled-out image Gj, the area e and the particle diameter d from the outline of each granular material s, and the projected area Ej of the entire granular material , And the cumulative passage rate Pj (di) of the predetermined particle diameter di is calculated from the particle diameter d of each granular material s for each image Gj, and the predetermined particle diameter weighted by the projected area Ej for each rolled-out image Gj The accumulated passage rate P (di of a predetermined particle diameter di of the granular material S before division is calculated based on the area average value (= (ΣPj (di) · Ej) / ΣEj) of the accumulated passage rate Pj (di) of di. ) Is measured.
また、図1のブロック図を参照するに、本発明による粒状材料の分割式粒度計測システムは、粒径dの異なる粒状材sが混在した粒状材料Sを複数に分割した各分割粒状材群Sjの撒き出し画像Gj(図10(A)参照)を撮影する撮像装置5、その撒き出し画像Gj毎に各粒状材sの輪郭から面積e及び粒径dと粒状材全体の投影面積Ejとを検出する検出手段17、撒き出し画像Gj毎の各粒状材sの粒径dから所定粒径diの加積通過率Pj(di)を算出する算出手段18、並びに撒き出し画像Gj毎の投影面積Ejで重み付けした所定粒径diの加積通過率Pj(di)の全画像にわたる面積平均値(=(ΣPj(di)・Ej)/ΣEj)により分割前の粒状材料Sの所定粒径diの加積通過率P(di)を計測する計測手段19を備えてなるものである。 In addition, referring to the block diagram of FIG. 1, the divided particle size measuring system for granular materials according to the present invention is divided into a plurality of divided granular material groups Sj obtained by dividing a granular material S mixed with granular materials s having different particle diameters d. The image pickup device 5 that captures the unrolled image Gj (see FIG. 10A), and for each unrolled image Gj, the area e and the particle size d from the outline of each granular material s and the projected area Ej of the entire granular material Detection means 17 for detecting, calculation means 18 for calculating an accumulation passage rate Pj (di) of a predetermined particle diameter di from the particle diameter d of each granular material s for each rolled-out image Gj, and a projected area for each rolled-out image Gj The area average value (= (ΣPj (di) · Ej) / ΣEj) of the cumulative passage rate Pj (di) of the predetermined particle diameter di weighted by Ej over the entire image represents the predetermined particle diameter di of the granular material S before division. Measuring means 19 for measuring the cumulative passage rate P (di) Is provided.
好ましくは、図1に示すように、各分割粒状材群Sjを一定面密度又は一定厚さに撒き出す撒き出し装置4を設ける。撒き出し装置4を設ければ、撒き出し条件の一定化によって撮影条件も一定化することができ、撒き出し条件の変動に起因する計測値の変動要因を除去することができる。また、予め粒状材料S中の最大粒径を測定しておき、その最大粒径の1〜3倍長さを一辺とする矩形面積で各分割粒状材群Sjを撒き出すことが望ましい。 Preferably, as shown in FIG. 1, a rolling-out device 4 is provided for rolling out each divided granular material group Sj to a constant surface density or a constant thickness. If the whirling device 4 is provided, the photographing condition can be made constant by making the whirling condition constant, and the variation factor of the measurement value caused by the fluctuation of the whirling condition can be removed. In addition, it is desirable to measure the maximum particle size in the granular material S in advance and to squeeze each divided granular material group Sj with a rectangular area having one side that is 1 to 3 times as long as the maximum particle size.
望ましくは、図1に示すように、粒状材料Sから所定限界粒径D未満の微小粒状材を分離する分離装置6、分離前後の粒状材料Sの重量M及び含水率Zを測定する測定器7、8、並びに重量M及び含水率Zの測定値から粒状材料S中の微小粒状材の加積通過率P(D)を求める演算手段22を設け、計測手段19において、撒き出し画像Gj毎の投影面積Ejで重み付けした所定粒径diの加積通過率Pj(di)の全画像にわたる面積平均値(=(ΣPj(di)・Ej)/ΣEj)と微小粒状材の加積通過率P(D)とから分割前の粒状材料Sの所定粒径diの加積通過率P(di)を計測する。 Desirably, as shown in FIG. 1, a separation device 6 that separates a particulate material having a particle size less than a predetermined limit particle size D from the particulate material S, and a measuring device 7 that measures the weight M and moisture content Z of the particulate material S before and after separation. , 8, and the calculation means 22 for obtaining the accumulation 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 are provided. The area average value (= (ΣPj (di) · Ej) / ΣEj) over the entire image of the cumulative passage rate Pj (di) of the predetermined particle diameter di weighted by the projected area Ej and the cumulative passage rate P ( From (D), the accumulation passage rate P (di) of the predetermined particle diameter di of the granular material S before division is measured.
更に好ましくは、算出手段18により、撒き出し画像Gj毎の加積通過率Pj(di)の算出に代えて、撒き出し画像Gj毎の粒状材全体の投影面積Ejに対する所定粒径di以上の粒状材の面積割合(=Σe/Ej)を所定粒径diの粒度インデクスIj(di)として算出し、粒状材料Sの標本Tから求めた所定粒径diの粒度インデクスI(di)とその標本T中の所定粒径di以下の粒状材の加積通過率P(di)との関係式K(図6参照)を記憶する記憶手段16を設け、その関係式Kに基づき、計測手段19により画像Gj毎の投影面積Ejで重み付けした所定粒径diの粒度インデクスIj(di)の全画像にわたる面積平均値I(di)(=(ΣIj(di)・Ej)/ΣEj)を分割前の粒状材料Sの所定粒径diの加積通過率P(di)に変換する。 More preferably, instead of calculating the accumulation passage rate Pj (di) for each rolled-out image Gj by the calculation means 18, the granularity is equal to or larger than a predetermined particle diameter di with respect to the projected area Ej of the entire granular material for each rolled-out image Gj. The area ratio (= Σe / Ej) of the material is calculated as the particle size index Ij (di) of the predetermined particle size di, and the particle size index I (di) of the predetermined particle size di obtained from the sample T of the granular material S and the sample T A storage unit 16 is provided for storing a relational expression K (see FIG. 6) with an accumulation passage rate P (di) of a granular material having a predetermined particle diameter di or less, and based on the relational expression K, an image is measured by the measurement means 19. Granular material before dividing the average area value I (di) (= (ΣIj (di) · Ej) / ΣEj) over the entire image of the particle size index Ij (di) of the predetermined particle size di weighted by the projected area Ej for each Gj Addition of S with a predetermined particle diameter di To convert the rate P (di).
本発明による粒状材料の分割式粒度計測方法及びシステムは、粒状材料Sを複数に分割したうえで各分割粒状材群Sjの撒き出し画像Gjを撮影し、その撒き出し画像Gj毎に各粒状材sの輪郭から面積e及び粒径dと粒状材全体の投影面積Ejとを検出して所定粒径diの加積通過率Pj(di)を算出し、撒き出し画像Gj毎の投影面積Ejで重み付けした所定粒径diの加積通過率Pj(di)の全画像にわたる面積平均値により分割前の粒状材料Sの所定粒径diの加積通過率P(di)を計測するので、次の有利な効果を奏する。 In the granular material division type particle size measuring method and system according to the present invention, the granular material S is divided into a plurality of parts, and then a rolled image Gj of each divided granular material group Sj is photographed, and each granular material is divided for each rolled image Gj. The area e, the particle size d, and the projected area Ej of the entire granular material are detected from the contour of s to calculate the accumulation passage rate Pj (di) of the predetermined particle size di, and the projected area Ej for each rolled-out image Gj. Since the accumulated passage rate P (di) of the predetermined particle size di of the granular material S before division is measured by the area average value over the entire image of the weighted passage size Pj (di) of the predetermined particle size di, There is an advantageous effect.
(イ)粒状材料Sを複数に分割したうえで撒き出し画像Gjを撮影するので、撒き出し面積を比較的小さく抑え、粒状材料Sの撒き出し・敷き均し作業の短時間化、簡単化を図ることができる。
(ロ)また、撒き出し面積を小さく抑えることにより、その面積全体が写り込む撮像装置5の高さhの比較的低く抑え、撮像装置5の小型化が図れると共に、撮像装置5の高さの増大(撒き出し面からの離隔)に伴う画像Gj中の粒状材の輪郭検出精度の低下、ひいては粒状材料Sの粒度計測精度の低下を抑えることができる。
(ハ)更に、粒状材料Sを分割したうえで撒き出し画像Gjを撮影するので、各分割粒状材群Sjについて撒き出し画像Gjの撮影を同時並行に進めることにより、粒状材料Sの粒度計測に要する時間を大幅に削減することも可能となる。
(ニ)撒き出し画像Gj毎に所定粒径diの加積通過率Pj(di)の算出に代えて粒度インデクスIj(di)を算出し、画像Gj毎の粒度インデクスIj(di)から分割前の粒状材料Sの所定粒径diの加積通過率P(di)に変換することにより、画像Gj毎に加積通過率Pj(di)を算出する手間を省き、粒状材料Sの粒度計測の更なる迅速化、簡単化を図ることができる。
(ヘ)とくに1m以上の大粒径の粒状材を含む大量の粒状材料Sの粒度を短時間で計測することが可能となり、例えばロックフィルダム建設工事等の粒状材料Sを用いた建設工事に適用した場合に、粒状材料Sの品質管理の容易化を図ると共に粒度管理の頻繁を増やすことで品質管理の高精度化を図ることが期待できる。
(A) Since the rolled-out image Gj is taken after the granular material S is divided into a plurality of parts, the rolled-out area is kept relatively small, and the rolling and leveling work of the granular material S is shortened and simplified. You can plan.
(B) Further, by suppressing the protruding area, the height h of the image pickup device 5 in which the entire area is reflected can be kept relatively low, the image pickup device 5 can be downsized, and the height of the image pickup device 5 can be reduced. It is possible to suppress a decrease in the accuracy of detecting the contour of the granular material in the image Gj due to an increase (separation from the protruding surface), and hence a decrease in the accuracy of measuring the particle size of the granular material S.
(C) Further, since the rolled-out image Gj is shot after dividing the granular material S, the shooting of the rolled-out image Gj for each divided granular material group Sj is advanced in parallel to measure the particle size of the granular material S. It is also possible to greatly reduce the time required.
(D) The granularity index Ij (di) is calculated instead of calculating the cumulative passage rate Pj (di) of the predetermined particle diameter di for each rolled-out image Gj, and before division from the granularity index Ij (di) for each image Gj The granular material S is converted into an accumulated passage rate P (di) of a predetermined particle diameter di, thereby eliminating the trouble of calculating the accumulated passage rate Pj (di) for each image Gj. Further speeding up and simplification can be achieved.
(F) In particular, it is possible to measure the particle size of a large amount of granular material S including granular material with a large particle size of 1 m or more in a short time, and it is applicable to construction work using granular material S such as rock fill dam construction work. In this case, it is expected that the quality control of the granular material S is facilitated and the accuracy of the quality control is increased by increasing the frequency of the particle size management.
以下、添付図面を参照して本発明を実施するための形態及び実施例を説明する。
図1は、本発明の分割式粒度計測システムのブロック図を示す。図示例のシステムは、粒状材料Sを複数の分割粒状材群Sjに小分けして撒き出す撒き出し装置4と、各分割粒状材群Sjの撒き出し画像Gj(図10(A)参照)を撮影する撮像装置5と、各分割粒状材群Sjの撒き出し画像Gjを入力して分割前の粒状材料Sの粒度を計測するコンピュータ10とを有する。例えばCSG工法で土木構造物を構築する場合に、構築現場付近の採取場(地山や地層)1で調達してダンプトラック等の運搬機械3で工事現場へ継続的に供給される地盤材料等の全体又は一部を品質管理用の粒状材料Sとし、その運搬単位毎に粒状材料Sの粒度を計測して品質を管理する。運搬機械3で搬送する材料が均質とみなせる場合は、運搬機械3上の一部を管理対象の粒状材料Sとすれば足りる。なお、本発明の適用対象は地山等から調達される地盤材料等に限らず、例えば原石を所定破砕装置2で破砕して継続的に供給される岩砕材料等の粒状材料Sにも広く適用可能である。 FIG. 1 shows a block diagram of the divided particle size measurement system of the present invention. The system of the illustrated example shoots a rolling-out device 4 that divides the granular material S into a plurality of divided granular material groups Sj, and a rolled-out image Gj (see FIG. 10A) of each divided granular material group Sj. And the computer 10 that inputs the rolled-out image Gj of each divided granular material group Sj and measures the particle size of the granular material S before division. For example, when constructing civil engineering structures using the CSG method, the ground materials, etc. that are procured at a collection site (ground or geological layer) 1 near the construction site and continuously supplied to the construction site by a transporting machine 3 such as a dump truck The whole or a part of is used as the granular material S for quality control, and the quality is controlled by measuring the particle size of the granular material S for each conveyance unit. 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. The application target of the present invention is not limited to the ground material and the like procured from the natural ground and the like, but is also widely applied to, for example, granular materials S such as a crushed material continuously crushed by a predetermined crushing device 2 by crushing raw stone. Applicable.
図示例の撒き出し装置4は、粒状材料Sを複数の分割粒状材群Sjに分割してそれぞれ所定面積に一定面密度となるように撒き出すものである。例えば最大粒径Dmaxが1m以上の大粒径の粒状材sを含む数百〜数千kgの粒状材料Sの全体を図5(A)のように撒き出し面積(A×B)で撒き出す場合、本発明者の実験によれば、撒き出し面積の一辺A(及びB)を最大粒径Dmaxの4〜10倍程度に設定する必要があり、その撒き出し作業の労力・時間が大きくなると共に、その全体が写り込む撮像装置5の高さhも大きくする必要が生じる。これに対し、例えば図5(B)のように粒状材料Sを分割して撒き出し面積の一辺aj(及びbj)を最大粒径Dmaxの1〜3倍程度に設定すれば、短時間での撒き出し作業が可能になると共に、撮像装置5の高さの増大(撒き出し面からの離隔)を防ぐことができる。 The whirling device 4 in the illustrated example divides the granular material S into a plurality of divided granular material groups Sj and rolls them out so as to have a constant surface density in a predetermined area. For example, the entire granular material S of several hundred to several thousand kg including the granular material s having a large particle diameter having a maximum particle diameter Dmax of 1 m or more is rolled out in a rolled area (A × B) as shown in FIG. In this case, according to the experiment of the present inventor, it is necessary to set the side A (and B) of the unrolling area to about 4 to 10 times the maximum particle size Dmax, and the labor and time of the unloading work increase. At the same time, it is necessary to increase the height h of the imaging device 5 in which the entire image is reflected. On the other hand, for example, as shown in FIG. 5B, if the granular material S is divided and the side aj (and bj) of the unrolled area is set to about 1 to 3 times the maximum particle size Dmax, it can be achieved in a short time. The whirling work can be performed and the height of the imaging device 5 (separation from the whirling surface) can be prevented.
例えば、分割前の粒状材料S中の最大粒径Dmaxを予め測定しておき、各分割粒状材群Sjをその最大粒径Dmaxの1〜3倍の一辺長さの矩形面積に順次撒き出して画像Gjを撮影する。こうすれば、粒状材料Sの全体を撮影する場合に比して画像枚数は増えるが、各画像の撮影準備作業(撒き出し作業及び片付け作業)の短時間化・簡単化を図ると共に、画像からの粒状材輪郭の検出精度ひいては粒状材料Sの粒度計測精度を高めることができる。最大粒径Dmaxは一般に粒状材料S中の全ての粒状材sが通過する篩の最小呼び寸法として定義されるが、例えば同じ採取場で採取された粒状材料Sからそのような最大粒径Dmaxを予め求め、本発明における各分割粒状材群Sjの撒き出しに利用することができる。 For example, the maximum particle size Dmax in the granular material S before division is measured in advance, and each divided granular material group Sj is sequentially sprinkled into a rectangular area having a side length of 1 to 3 times the maximum particle size Dmax. An image Gj is taken. In this way, the number of images increases as compared with the case where the entire granular material S is photographed. However, it is possible to shorten and simplify the photographing preparation work (breading work and clearing work) of each image and from the image. The granular material contour detection accuracy and the granular material S particle size measurement accuracy can be increased. The maximum particle size Dmax is generally defined as the minimum nominal size of the sieve through which all the granular material s in the granular material S passes. For example, such maximum particle size Dmax is obtained from the granular material S collected at the same sampling site. It can obtain | require beforehand and can use for the division | segmentation of each division | segmentation granular material group Sj in this invention.
望ましくは、分割前の粒状材料Sの全重量を測定し、その重量を均等分することで分割後の各分割粒状材群Sjの重量を揃えたうえで、それぞれ一定面積に撒き出す。各分割粒状材群Sjの重量及び撒き出し面積を揃えることで、一定面密度の撒き出し作業の効率化を図ることができる。なお、各分割粒状材群Sjの撒き出し面の形状および各辺の大きさは図示例に限定されず、例えば各辺の長さの比(aj/bj)を0.5〜1.5の範囲内で選択することができ、矩形面に代えて円形面状に撒き出すことも可能である。 Desirably, the total weight of the granular material S before division is measured, and the weight of each divided granular material group Sj after the division is equalized by dividing the weight into equal parts. By aligning the weight and the area of the divided granular material group Sj, it is possible to improve the efficiency of the constant area density. In addition, the shape of the facing surface and the size of each side of each divided granular material group Sj are not limited to the illustrated example, and for example, the ratio of lengths of each side (aj / bj) is 0.5 to 1.5. It is possible to select within a range, and it is also possible to roll out a circular surface instead of a rectangular surface.
或いは、各分割粒状材群Sjの重量を測定し、その測定重量に応じて一定面密度(例えば10〜400kg/m2程度)となるように各粒状材群Sjの撒き出し面積(aj×bj)を設定する。各粒状材群Sjが1m以上の大粒径粒状材を含有しており重量を直接測定することが難しい場合は、粒状材料Sの比重に応じて所定撒き出し面積(aj×bj)における各粒状材群Sjの撒き出し厚さを一定とすることで、面密度を一定にすることも可能である。その撒き出し厚さより大きな粒径の粒状材sはそのまま撒き出さざるを得ないが、その撒き出し厚さより小粒の粒状材sを一定厚さで撒き出すことで、各分割粒状材群Sjの撒き出し面密度の均一化を図ることができる。好ましくは、後述するように撒き出し画像Gjから所定限界粒径D(例えば5〜10mm)以上の粒状材の輪郭を全て検出可能とするため、所定限界粒径D以上の粒状材が埋もれない厚さに各分割粒状材群Sjを撒き出す。 Alternatively, the weight of each divided granular material group Sj is measured, and the protruding area (aj × bj) of each granular material group Sj so as to have a constant surface density (for example, about 10 to 400 kg / m 2 ) according to the measured weight. ) Is set. When each granular material group Sj contains a granular material having a large particle diameter of 1 m or more and it is difficult to directly measure the weight, each granular material in a predetermined protruding area (aj × bj) according to the specific gravity of the granular material S It is also possible to make the surface density constant by making the rolled thickness of the material group Sj constant. The granular material s having a particle size larger than the squeezed thickness must be squeezed out as it is, but by squeezing the granular material s having a smaller particle size than the squeezed thickness, the squeezing of each divided granular material group Sj is performed. It is possible to make the exit surface density uniform. Preferably, as described later, in order to detect all the contours of the granular material having a predetermined limit particle diameter D (for example, 5 to 10 mm) or more from the rolled-out image Gj, the thickness at which the granular material having the predetermined limit particle diameter D or more is not buried. Then, each divided granular material group Sj is rolled out.
図示例の撮像装置5は、図5(A)に示すように、撒き出し装置4で撒き出された分割粒状材群Sjの全体が写り込む高さhに下向きに設置されており、各分割粒状材群Sjの全体が写り込む撒き出し画像Gjを撮像する。上述したように本発明では、粒状材料Sを複数に分割して撒き出し面積を小さく抑えることで撮像装置5の大型化(撒き出し面からの離隔)を防ぐことができるので、例えば小型デジタルカメラ等の撮像装置5を用いて比較的高精細な撒き出し画像Gjを撮影することができる。 As shown in FIG. 5A, the imaging device 5 in the illustrated example is installed downward at a height h at which the entire divided granular material group Sj rolled out by the rolling-out device 4 is reflected. A rolled-out image Gj in which the entire granular material group Sj is reflected is captured. As described above, in the present invention, the granular material S is divided into a plurality of parts to keep the surface area small, so that the imaging device 5 can be prevented from being enlarged (separated from the surface), for example, a small digital camera. A relatively high-definition start-up image Gj can be taken using the imaging device 5 such as the above.
図示例のコンピュータ10は、キーボード等の入力装置11と、ディスプレイ等の出力装置12と、一次又は二次記憶装置等の記憶手段16とを有する。またコンピュータ10は内蔵プログラムとして、撮像装置5から各分割粒状材群Sjの撒き出し画像Gjを入力する入力手段14と、その撒き出し画像Gj毎に分割粒状材群Sj中の各粒状材sの輪郭から面積e及び粒径dと粒状材全体の投影面積Ejとを検出する検出手段17と、その各粒状材sの粒径dから画像Gj毎に所定粒径diの加積通過率Pj(di)を算出する算出手段18と、その画像Gj毎の所定粒径diの加積通過率Pj(di)から分割前の粒状材料Sの所定粒径diの加積通過率P(di)を計測する計測手段19と、計測した加積通過率P(di)等を出力装置12に出力する出力手段15とを有する。図示例のコンピュータ10の内蔵プログラムには、分割前の粒状材料Sの所定粒径diの加積通過率P(di)から粒径加積曲線P(d)を作成する作成手段20、及びその粒状材料Sの粒径加積曲線P(d)と最粗粒標本Tr及び最細粒標本Tsの粒径加積曲線Pr(d)、Ps(d)とを比較して粒度品質を判定する判定手段21も含まれる。 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. Further, the computer 10 has, as an internal program, an input means 14 for inputting a rolled-out image Gj of each divided granular material group Sj from the imaging device 5, and each granular material s in the divided granular material group Sj for each rolled-out image Gj. The detecting means 17 for detecting the area e and the particle diameter d from the contour and the projected area Ej of the whole granular material, and the accumulated passage rate Pj (with a predetermined particle diameter di for each image Gj from the particle diameter d of the granular material s. The calculation means 18 for calculating (di) and the accumulated passage rate P (di) of the predetermined particle size di of the granular material S before division from the accumulated passage rate Pj (di) of the predetermined particle size di for each image Gj. It has a measuring means 19 for measuring, and an output means 15 for outputting the measured product passage rate P (di) and the like to the output device 12. The built-in program of the computer 10 in the illustrated example includes a creation means 20 for creating a particle size accumulation curve P (d) from an accumulation passage rate P (di) of a predetermined particle size di of the granular material S before division, and its The particle size quality is determined by comparing the particle size accumulation curve P (d) of the granular material S with the particle size accumulation curves Pr (d) and Ps (d) of the coarsest sample Tr and the finest sample Ts. A determination means 21 is also included.
好ましくは、図示例のように、分割前の粒状材料Sから所定限界粒径D(例えば5〜10mm)未満の微小粒状材(シルト・粘土等)を分離する分離装置6を設け、分離装置6により粒状材料Sから微小粒状材を分離したうえで撒き出し装置4により複数に分割し、微小粒状材を分離した各分割粒状材群Sjの撒き出し画像Gjをコンピュータ10に入力する。例えば、画像Gjから輪郭を検出することが困難な限界粒径D未満の微小粒状材が分割粒状材群Sj中に多量に含まれていると、限界粒径D以上の粒状材が微小粒状材に埋もれてしまい、検出手段17において画像Gjから必要な粒状材の輪郭を検出することが難しくなる。また、微小粒状材が団子状に固まり又は大径の粒子にこびり付くことによって、検出手段17が各粒状材の粒径を誤認識し、検出した面積e及び粒径dに誤差を生じるおそれがある。予め分離装置6によって粒状材料Sから微小粒状材を分離しておくことにより、検出手段17における各粒状材の輪郭検出精度を高めることができる。使用する分離装置6は粒状材料S中の微小粒状材の状態に応じて異なりうるが、例えば微小粒状材が乾燥している場合は篩い分け装置とし、微小粒状材が湿潤して他の粒状材にこびり付いている場合は水洗い装置等とすることができる。ただし、分離装置6は本発明のシステムに必須のものではなく、例えば粒状材料S中に含まれる微小粒状材が少なく、検出手段17において粒状材の粒径を誤認識するおそれが小さいときは、分離装置6は省略可能である。 Preferably, as shown in the figure, a separation device 6 is provided for separating a fine granular material (silt, clay, etc.) having a particle size less than a predetermined limit particle size D (for example, 5 to 10 mm) from the granular material S before division. Then, after separating the fine granular material from the granular material S, the fine particle material is divided into a plurality by the separation device 4 and the divided image group Gj of the divided granular material group Sj separated from the fine granular material is input to the computer 10. For example, if a minute granular material having a particle size less than the limit particle size D, for which it is difficult to detect the contour from the image Gj, is contained in a large amount in the divided granular material group Sj, a granular material having a particle size larger than the limit particle size D is a minute particle material. It becomes difficult for the detection means 17 to detect the necessary contour of the granular material from the image Gj. Further, when the fine granular material is agglomerated or stuck to a large diameter particle, the detection means 17 may misrecognize the particle size of each granular material and may cause an error in the detected area e and particle size d. There is. By separating the fine granular material from the granular material S by the separating device 6 in advance, the contour detecting accuracy of each granular material in the detecting means 17 can be increased. 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.
図2は、図1のシステムを用いた本発明による粒状材料Sの分割式粒度計測方法の流れ図を示す。以下、図2の流れ図を参照して図1のシステムを説明する。先ず図2のステップS101は、上述した撒き出し装置4により粒状材料Sを複数に分割して撒き出し、撮像装置5により各分割粒状材群Sjの撒き出し画像Gj(図10(A)参照)を撮像してコンピュータ10に入力する処理を示す。次いでステップS102〜S104において、入力した撒き出し画像Gj毎に、そこに写り込んだ分割粒状材群Sjについて所定粒径diの加積通過率Pj(di)を算出する。 FIG. 2 shows a flow chart of a divided particle size measuring method for granular material S according to the present invention using the system of FIG. The system of FIG. 1 will be described below with reference to the flowchart of FIG. First, in step S101 in FIG. 2, the granular material S is divided into a plurality of parts by the above-described extruding device 4, and the extruding image Gj of each divided granular material group Sj by the imaging device 5 (see FIG. 10A). The process which image | photographs and inputs into the computer 10 is shown. Next, in steps S102 to S104, for each input rolled-out image Gj, the cumulative passage rate Pj (di) of the predetermined particle diameter di is calculated for the divided granular material group Sj reflected therein.
ステップS102では、入力した撒き出し画像Gjをコンピュータ10の検出手段17に入力し、先ず図10(C)に示すように画像G中の個々の粒状材の輪郭を検出する。例えば画像Gを画素の明暗に基づいて二値化処理し、その二値化画像からラベリングやパターンマッチング等の手法を用いて各粒子の輪郭を抽出する(図10(B)参照)。望ましくは、上述したように画像Gjから所定限界粒径D(例えば5〜10mm)以上の粒状材の輪郭を全て検出する。 In step S102, the input rolled-out image Gj is input to the detecting means 17 of the computer 10, and first, the contour of each granular material in the image G is 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. 10B). Desirably, as described above, all the outlines of granular materials having a predetermined limit particle diameter D (for example, 5 to 10 mm) or more are detected from the image Gj.
またステップS102において、検出した各粒状材の輪郭から各粒状材の面積e及び粒径dを求め、面積情報(二次元情報)を体積情報(三次元情報)へ変換すると共に、粒状材全体の投影面積Ej(=Σe)を求める。例えば図5(C)のように粒状材が球体とみなせる場合は、その粒状材の面積等価径を粒径dとし、その球体の断面積を面積eとする。或いは図5(D)に示すように、各粒状材の輪郭に楕円形を(例えば最小二乗近似により)フィッティングさせて長径b・短径aを求め、その短径aを粒状材の粒径d(篩い径)とし、近似した楕円形の面積を粒状材の面積eとする。楕円近似に代えて各粒状材の輪郭に外接する最小矩形を求め、その最小矩形の短径aを粒径dとし、その最小矩形の面積を粒状材の面積eとしてもよい。或いは各粒状材の輪郭内部の画素数を面積に換算して各粒状材の面積eを算出することも可能である。 In step S102, the area e and the particle diameter d of each granular material are obtained from the detected outline of each granular material, and the area information (two-dimensional information) is converted into volume information (three-dimensional information). The projected area Ej (= Σe) is obtained. For example, when the granular material can be regarded as a sphere as shown in FIG. 5C, the area equivalent diameter of the granular material is the particle diameter d, and the cross-sectional area of the sphere is the area e. Alternatively, as shown in FIG. 5D, 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 particle size d of the granular material. (Sieving diameter), and the approximate elliptical area is defined as the area e of the granular material. Instead of ellipse approximation, a minimum rectangle circumscribing the contour of each granular material may be obtained, the short axis a of the minimum rectangle may be set as the particle size d, and the area of the minimum rectangle may be set 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.
次いでステップS103において、検出手段17で検出された各粒状材sの粒径dをコンピュータ10の算出手段18に入力し、撒き出し画像Gj毎の所定粒径diの加積通過率Pj(di)を算出する。例えば、算出手段18により各粒状材sの粒径dから各粒状材を等価径の単純立体(球又は立方体)にモデル化して体積vを算出し、各粒状材の体積vを粒径dの降順に並べると共に全体積Vj(=Σv)を算出し、その全体積Vjに対する所定粒径diより小径の粒状材の割合として所定粒径diの加積通過率Pj(di)を算出する。各粒状材sの体積vから加積通過率Pj(di)を算出する方法に代えて、粒状材料Sの各粒状材sの土粒子密度又は単位体積重量を予め求めておき、それらを用いて所定粒径diの加積通過率Pj(di)を算出することも可能である。好ましくは、複数の所定粒径di(例えば10mm、20mm、30mm、40mm等)について、それぞれ全体積Vjに対する所定粒径diより小径の粒状材の割合pを求めることにより、撒き出し画像G毎に複数の所定粒径diの加積通過率Pj(di)を算出する。ステップS104は、全ての撒き出し画像GjについてステップS102〜S103を繰り返すことを示す。 Next, in step S103, the particle diameter d of each granular material s detected by the detection means 17 is input to the calculation means 18 of the computer 10, and the cumulative passage rate Pj (di) of the predetermined particle diameter di for each rolled-out image Gj. Is calculated. For example, the volume v is calculated by modeling each granular material into a simple solid (sphere or cube) having an equivalent diameter from the particle size d of each granular material s by the calculation means 18, and the volume v of each granular material is calculated as the particle size d. They are arranged in descending order and the total volume Vj (= Σv) is calculated, and the cumulative passage rate Pj (di) of the predetermined particle diameter di is calculated as the ratio of the granular material having a smaller diameter than the predetermined particle diameter di with respect to the total volume Vj. Instead of the method of calculating the cumulative passage rate Pj (di) from the volume v of each granular material s, the soil particle density or unit volume weight of each granular material s of the granular material S is obtained in advance, and they are used. It is also possible to calculate the accumulation passage rate Pj (di) of the predetermined particle diameter di. Preferably, for a plurality of predetermined particle diameters di (for example, 10 mm, 20 mm, 30 mm, 40 mm, etc.), the ratio p of granular materials having a diameter smaller than the predetermined particle diameter di with respect to the total volume Vj is obtained for each rolled image G. A cumulative passage rate Pj (di) of a plurality of predetermined particle diameters di is calculated. Step S104 indicates that steps S102 to S103 are repeated for all the extracted images Gj.
ステップS102〜S104において全ての撒き出し画像Gjについて所定粒径diの加積通過率Pj(di)を算出したのち、その算出結果をステップS107においてコンピュータ10の計測手段19に入力し、分割前の粒状材料Sの所定粒径diの加積通過率P(di)を計測する。図5(B)に示すように、粒状材料Sを分割した各分割粒状材群Sjの所定粒径diの加積通過率Pj(di)を、各分割粒状材群Sjの撒き出し面積(aj×bj)で重み付けしたうえで総計し、その総計を撒き出し面積の総計(=Σaj×Σbj=A×B)で除して平均値を求めることにより、分割前の粒状材料Sの所定粒径diの加積通過率P(di)が得られる。具体的には、各画像Gjの投影面積Ejで重み付けされた所定粒径diの加積通過率Pj(di)の総計(=(ΣPj(di)・Ej)を求め、その加積通過率Pj(di)の総計を全画像Gjの投影面積Ejの総計(=ΣEj)によって除して面積平均値(=(ΣPj(di)・Ej)/ΣEj)を算出することにより分割前の粒状材料Sの所定粒径diの加積通過率P(di)を求める。或いは、各画像Gjの投影面積Ejで重み付けするのではなく、上述した各画像Gjに写り込んだ粒状材の全体積Vj(=Σv)で所定粒径diの加積通過率Pj(di)を重み付けし、それを全画面Gjの総計全体積V(=ΣVj)により除して体積平均値を算出することにより、分割前の粒状材料Sの所定粒径diの加積通過率P(di)を求めることも可能である。 In steps S102 to S104, the cumulative passage rate Pj (di) of the predetermined particle diameter di is calculated for all the unrolled images Gj, and the calculation result is input to the measuring means 19 of the computer 10 in step S107. The accumulated passage rate P (di) of the granular material S with a predetermined particle diameter di is measured. As shown in FIG. 5 (B), the cumulative passage rate Pj (di) of the predetermined particle diameter di of each divided granular material group Sj obtained by dividing the granular material S is expressed as the unrolling area (aj) of each divided granular material group Sj. Xbj) is weighted and summed, and the sum is divided by the sum of the unrolled areas (= Σaj × Σbj = A × B) to obtain an average value, thereby obtaining a predetermined particle size of the granular material S before division A product passage rate P (di) of di is obtained. Specifically, the sum (= (ΣPj (di) · Ej)) of the accumulated passage rate Pj (di) of the predetermined particle diameter di weighted by the projected area Ej of each image Gj is obtained, and the accumulated passage rate Pj. By dividing the sum of (di) by the sum of the projected areas Ej of all the images Gj (= ΣEj) and calculating an area average value (= (ΣPj (di) · Ej) / ΣEj), the granular material S before division The cumulative passage rate P (di) of the predetermined particle diameter di is calculated, or the total volume Vj (= of the granular material reflected in each image Gj described above is not weighted by the projected area Ej of each image Gj. Σv) weights the product passage rate Pj (di) of the predetermined particle diameter di, and divides it by the total total volume V (= ΣVj) of the entire screen Gj to calculate the volume average value. The accumulation pass rate P (di) of the granular material S with a predetermined particle diameter di is obtained. It is also possible.
図2のステップS108は、分割前の粒状材料Sについて算出した所定粒径diの加積通過率P(di)をコンピュータ10の作成手段20に入力し、粒状材料Sの粒径加積曲線P(d)を作成する処理を示す。図7は、上述した分離装置6により所定限界粒径D未満の微小粒状材を分離した後の粒状材料Sについて、作成手段20で作成した所定限界粒径D以上の粒径加積曲線P(d≧D)の一例を示す。図示例の粒径加積曲線Pは、算出手段18において各撒き出し画像Gjの複数の所定粒径di(図示例では10mm、20mm、40mm)についてそれぞれ加積通過率Pj(di)を算出し、計測手段19において分割前の粒状材料Sの複数の所定粒径diにおける各加積通過率P(di)に変換したものである。 Step S108 in FIG. 2 inputs the accumulation passage rate P (di) of the predetermined particle diameter di calculated for the granular material S before division into the creating means 20 of the computer 10, and the particle diameter accumulation curve P of the granular material S is input. The process of creating (d) is shown. FIG. 7 shows a particle size accumulation curve P (not less than the predetermined limit particle diameter D created by the creating means 20 for the granular material S after the fine granular material having a particle diameter less than the predetermined limit particle diameter D is separated by the separating device 6 described above. An example of d ≧ D) is shown. In the particle diameter accumulation curve P in the illustrated example, the calculation means 18 calculates the accumulated passage rate Pj (di) for each of a plurality of predetermined particle diameters di (10 mm, 20 mm, and 40 mm in the illustrated example) of each rolled-out image Gj. The measuring means 19 converts the accumulated material passage rate P (di) into a plurality of predetermined particle diameters di of the granular material S before division.
ステップS109〜S110は、ステップS108で作成した粒状材料Sの粒径加積曲線P(d)をコンピュータ10の判定手段21に入力し、判定手段21において、粒状材料Sの粒径加積曲線P(d)を最粗粒標本Tr及び最細粒標本Tsの粒径加積曲線Pr(d)、Ps(d)と比較して粒度品質を判定する処理を示す。このような最粗粒標本Tr及び最細粒標本Tsは、上述したように粒状材料Sの数多くの粒度試験によって予め選定し、その粒度試験で求めた粒径加積曲線Pr(d)、Ps(d)を例えばステップS101において記憶手段16に登録しておくことができる。或いは、図7に示すように所定限界粒径D未満の微小粒状材を分離した粒状材料Sの粒径加積曲線P(d≧D)と対比する場合は、最粗粒標本Tr及び最細粒標本Tsから微小粒状材を分離した所定限界粒径D以上の粒径加積曲線Pr(d≧D)、Ps(d≧D)を作成して記憶手段16に登録しておくことができる(図12も参照)。例えば、判定手段21により粒状材料の粒径加積曲線P(d≧D)が粒径加積曲線Pr(d≧D)、Ps(d≧D)の間の規定範囲内にあるか否か(正常か否か)、何れの粒径加積曲線Pr、Psの側に変動しているか(変動の傾向)等を確認することにより、粒状材料Sの粒度品質を判定する。 In steps S109 to S110, the particle diameter accumulation curve P (d) of the granular material S created in step S108 is input to the determination means 21 of the computer 10, and in the determination means 21, the particle diameter accumulation curve P of the granular material S is input. The process of determining the particle size quality is shown by comparing (d) with the particle size accumulation curves Pr (d) and Ps (d) of the coarsest sample Tr and the finest sample Ts. 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 from which the fine granular material having a particle diameter less than the predetermined limit particle size D is separated, the coarsest sample Tr and the finest particle Particle size accumulation curves Pr (d ≧ D) and Ps (d ≧ D) of a predetermined limit particle size D or more obtained by separating the fine granular material from the grain sample Ts can be created and registered in the storage means 16. (See also FIG. 12). 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 means 21. 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.
図2のステップS111は、ステップS109〜S110において粒状材料Sの粒度品質が規定範囲外であると判定された場合に、必要に応じて粒状材料Sの粒度を調整する処理を示す。粒度の調整方法は、例えば図7において粒状材料Sの粒径加積曲線P(d≧D)が最粗粒標本Tr及び最細粒標本Tsの何れの側に外れているかによって相違するが、粒径加積曲線Pの判定結果を総合的に考慮して粒状材料Sの粒度を調整することができる。粒度調整後にステップS101へ戻り、上述したステップS101〜S110の処理をやり直す。ただし、ステップS111の粒度調整は本発明に必須の処理ではなく、ステップS111において図13のひし形の規定範囲内となるように粒状材料Sに混合する単位水量を調整することも可能であり、規定範囲外であると判定された粒状材料Sを土木工事に使用しない場合はステップS111を省略できる。 Step S111 in FIG. 2 shows processing for adjusting the particle size of the granular material S as necessary when it is determined in steps S109 to S110 that the particle size quality of the granular material S 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 S101, and the above-described processes of steps S101 to S110 are performed again. However, the particle size adjustment in step S111 is not an essential process for the present invention. In step S111, the unit water amount mixed into the granular material S can be adjusted 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 S111 can be omitted.
ステップS109〜S110で粒状材料Sの粒度品質が規定範囲内であると判定された場合はステップS112へ進み、例えば図7の今回供給された粒状材料Stの所定粒径diの加積通過率Pt(di)及び粒径加積曲線Pt(d≧D)を記憶手段16に累積記憶したのち、ステップS113において粒状材料Sの粒度計測を継続するか否かを判断する。継続する場合はステップS101へ戻り、次回供給される粒状材料St+1について上述したステップS101〜S118を繰り返し、所定粒径diの加積通過率Pt+1(di)を計測して粒径加積曲線Pt+1を作成する。ステップS112において粒状材料Sの加積通過率P(di)及び粒径加積曲線Pを記憶手段16に累積記憶しておくことにより、次回以降のステップS109〜S110の判定処理において、判定手段21により今回供給材料Stの加積通過率Pt(di)又は粒径加積曲線Pt(d)と前回供給材料St−1の加積通過率Pt−1(di)又は粒径加積曲線P(d)t−1とを比較して粒状材料Sの粒度の経時的変化(粒度変動)を判定し、粒状材料Sの粒度品質の変化を迅速に把握することが可能となる。 If the particle size quality of the granular material S is determined to be within the prescribed range in step S109~S110 proceeds to step S112, for example, pressurized product passing rate of a given particle size di of the current supplied particulate material S t in FIG. 7 After accumulating and storing P t (di) and the particle size accumulation curve P t (d ≧ D) in the storage means 16, it is determined whether or not to continue measuring the particle size of the granular material S in step S113. When continuing, it returns to step S101, repeats step S101-S118 mentioned above about granular material St t + 1 supplied next time, measures the accumulation passage rate Pt + 1 (di) of predetermined particle size di, and is a particle size accumulation curve. Create Pt + 1 . In step S112, the accumulation passage rate P (di) and the particle size accumulation curve P of the granular material S are accumulated and stored in the storage unit 16, so that the determination unit 21 in the determination process of the next steps S109 to S110. this feed S t of the pressurized product passage rates P t (di) or particle size accumulation curve P t (d) as the previous feed S t-1 of the pressurized product passage rates P t-1 (di) or particle size by Comparison with the accumulation curve P (d) t-1 makes it possible to determine the change in the particle size of the granular material S over time (particle size variation) and to quickly grasp the change in the particle size quality of the granular material S. .
本発明は、粒状材料Sを複数に分割したうえで撒き出し画像Gjを撮影し、複数の撒き出し画像Gjから分割前の加積通過率P(di)を計測し、さらに粒径加積曲線P(d)を作成するので、撒き出し面積を比較的小さく抑え、粒状材料Sの撒き出し・敷き均し作業の短時間化、簡単化を図ることができる。また、撒き出し面積全体が写り込む撮像装置5の高さhの比較的低く抑え、撮像装置5の高さの増大に伴う計測精度の低下、ひいては粒状材料Sの粒度計測精度の低下を抑えることができる。更に、各分割粒状材群Sjの撒き出し画像Gjの撮影を同時並行に進めることにより、粒状材料Sの粒度計測に要する時間を大幅に削減することも期待できる。 In the present invention, the granular material S is divided into a plurality of images, and then a rolled-out image Gj is photographed, the accumulated passing rate P (di) before the division is measured from the plurality of rolled-out images Gj, and the particle size accumulation curve is further measured. Since P (d) is created, the spread area can be kept relatively small, and the work for spreading and leveling the granular material S can be shortened and simplified. In addition, the height h of the imaging device 5 in which the entire exposed area is reflected is suppressed to be relatively low, and a decrease in measurement accuracy due to an increase in the height of the imaging device 5 and a decrease in the particle size measurement accuracy of the granular material S are suppressed. Can do. Furthermore, it can be expected that the time required for measuring the particle size of the granular material S will be significantly reduced by proceeding with the shooting of the rolled-out image Gj of each divided granular material group Sj in parallel.
こうして本発明の目的である「大粒径の粒状材を含む粒状材料の分割式粒度を短時間で精度よく計測する方法及びシステム」の提供を達成できる。 Thus, it is possible to achieve the object of the present invention, “a method and system for accurately measuring a divided particle size of a granular material including a granular material having a large particle size in a short time”.
図4は、本発明による粒状材料Sの分割式粒度計測方法の他の流れ図を示す。上述した図2の流れ図のステップS102〜103では、撒き出し画像Gj毎に各粒状材sの輪郭及び粒径dから体積vを算出すると共に全粒状材sの体積Vj(=Σv)を算出し、その全体積Vjに対する所定粒径diより小径の粒状材の割合として所定粒径diの加積通過率Pj(di)を算出している。ただし、例えば図10(A)に示すような撒き出し画像Gから所定粒径di(例えば10mm)以下の全ての粒状材sの輪郭及び粒径dを検出することが画像解析上困難であることも多い。このような所定粒径di以下の粒状材sの検出に比して、その所定粒径di(例えば10mm)以上の粒状材の検出は画像解析上比較的容易であり、例えば撒き出し画像G中の粒状材全体の投影面積Ejに対する所定粒径di以上の粒状材sの面積eの総和(Σe)の面積割合Σe/E(以下、所定粒径diの粒度インデクスI(di)という)は比較的容易に精度よく求めることができる。 FIG. 4 shows another flow chart of the divided particle size measuring method for the granular material S according to the present invention. In steps S102 to S103 in the flowchart of FIG. 2 described above, the volume v is calculated from the contour and the particle diameter d of each granular material s for each rolled-out image Gj, and the volume Vj (= Σv) of all the granular materials s is calculated. The cumulative passage rate Pj (di) of the predetermined particle diameter di is calculated as the ratio of the granular material having a smaller diameter than the predetermined particle diameter di with respect to the total volume Vj. However, for example, it is difficult in image analysis to detect the contours and particle diameters d of all the granular materials s having a predetermined particle diameter di (for example, 10 mm) or less from the spread image G as shown in FIG. There are many. Compared to the detection of the granular material s having a predetermined particle size di or less, detection of the granular material having the predetermined particle size di (for example, 10 mm) or more is relatively easy in image analysis. The area ratio Σe / E (hereinafter referred to as the particle size index I (di) of the predetermined particle size di) of the total sum (Σe) of the area e of the granular material s having the predetermined particle size di or more with respect to the projected area Ej of the entire granular material of Can be obtained easily and accurately.
図6は、同じ地山から採取された複数の粒状材料Sについて、それぞれ篩分け作業等の従来方法により粒径di=10mm、20mm、30mm、40mm以下の粒状材の加積通過率P(di)を求めると共に、その撒き出し画像Gから各粒径di=10mm、20mm、30mm、40mm以上の粒状材の粒度インデクスI(di)を算出し、それらの結果を二次平面(加積通過率P(d)を縦軸とし面積割合(Σe/E)を横軸とした平面)上にプロットしたものである。図6のグラフは、粒状材料Sの異なる粒径diにおける加積通過率P(di)がそれぞれ、粒度インデクスI(di)の多次元回帰モデル(y=Σan・xn)で表わせることを示している。図6のような関係式(例えば多次元回帰モデル)を利用すれば、撒き出し画像Gから検出した所定粒径diの粒度インデクスI(di)に基づき、その所定粒径diの加積通過率P(d)を推定することができる。図4の流れ図は、図2(ステップS103)のように撒き出し画像Gj毎に加積通過率Pj(di)を算出することに代えて、撒き出し画像Gj毎の粒度インデクスI(di)を用いて粒状材料Sの粒度を計測する方法である。 FIG. 6 shows the accumulated passage rate P (di) of a granular material having a particle size of di = 10 mm, 20 mm, 30 mm, 40 mm or less by a conventional method such as sieving for a plurality of granular materials S collected from the same ground. ) And the particle size index I (di) of each granular material having a particle size 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 (cumulative passage rate). P (d) is plotted on the vertical axis and the area ratio (Σe / E) is plotted on the horizontal axis). The graph of FIG. 6, the pressurized product passing rate in different particle sizes di granular material S P (di), respectively, expressed it in a multidimensional regression model granularity index I (di) (y = Σa n · x n) Is shown. If a relational expression as shown in FIG. 6 (for example, a multidimensional regression model) is used, based on the particle size index I (di) of the predetermined particle size di detected from the rolled-out image G, the accumulated passage rate of the predetermined particle size di P (d) can be estimated. The flowchart of FIG. 4 shows the granularity index I (di) for each starting image Gj, instead of calculating the product passage rate Pj (di) for each starting image Gj as shown in FIG. 2 (step S103). This is a method of measuring the particle size of the granular material S by using it.
図4のステップS301〜S303は、コンピュータ10の関係式設定手段23(図1参照)により、粒状材料Sの所定粒径diの粒度インデクスI(di)とその粒径di以下の粒状材の加積通過率P(di)との関係式Kを設定する初期処理を示す。先ずステップS301において、粒状材料Sの標本Tを用い、例えば図1の分離装置6によって標本Tから所定限界粒径D(例えば5〜10mm)未満の微小粒状材を分離したうえで、撮像装置5により標本Tの撒き出し画像Gを撮像してコンピュータ10に入力する。また、その微小粒状材分離後の標本Tについて、標本T中の所定粒径di(例えば図6に示す10mm、20mm、30mm、40mm等)以下の粒状材の加積通過率P(di)を篩い分けその他の従来方法により求め、求めた各粒径diの加積通過率P(di)を入力装置11からコンピュータ10に入力する。 Steps S301 to S303 in FIG. 4 are performed by the relational expression setting means 23 (see FIG. 1) of the computer 10 to add the particle size index I (di) of the granular material S having a predetermined particle size di and the granular material having the particle size di or less. An initial process for setting a relational expression K with the product passage rate P (di) is shown. First, in step S301, the sample T of the granular material S is used, for example, a fine granular material having a particle diameter less than a predetermined limit particle diameter D (for example, 5 to 10 mm) is separated from the sample T by the separation device 6 in FIG. The picked-up image G of the sample T is picked up and input to the computer 10. Further, with respect to the sample T after the separation of the fine granular material, the cumulative passage rate P (di) of the granular material having a predetermined particle diameter di (for example, 10 mm, 20 mm, 30 mm, 40 mm, etc. shown in FIG. It is obtained by sieving or other conventional methods, and the accumulated passing rate P (di) of each obtained particle diameter di is input to the computer 10 from the input device 11.
ステップS302において、撒き出し画像Gをコンピュータ10の検出手段17に入力し、図10(C)に示すように画像G中の各粒状材の輪郭を検出し、更にその輪郭から各粒状材の面積e及び粒径dを求めると共に、粒状材全体の投影面積E(=Σe)を求める。画像G中の全ての粒状材の輪郭及び粒径dを検出することが難しい場合でも、輪郭が検出できる限界粒径D(例えば5〜10mm)以上の粒状材の輪郭を全て検出することが望ましく、少なくともステップS301において加積通過率P(di)を求めた最小の粒径di(例えば10mm)以上の粒状材の輪郭及び粒径dを全て検出する。 In step S302, the rolled-out image G is input to the detection means 17 of the computer 10, and the contour of each granular material in the image G is detected as shown in FIG. e and the particle diameter d are obtained, and the projected area E (= Σe) of the whole granular material is obtained. Even when it is difficult to detect the contours and particle diameters d of all the granular materials in the image G, it is desirable to detect all the contours of the granular materials that are larger than the limit particle diameter D (for example, 5 to 10 mm) that can be detected. At least in step S301, the contours and particle diameters d of the granular material having the minimum particle diameter di (for example, 10 mm) for which the cumulative passage rate P (di) is obtained are detected.
またステップS302において、検出手段17で検出した撒き出し画像G中の各粒状材の粒径dをコンピュータ10の粒度インデクス算出手段18aに入力し、例えば撒き出し画像G中の複数の所定粒径di(例えば10mm、20mm、30mm、40mm等)について、それぞれ各粒径di以上の粒状材の面積の総和Σeを求め、撒き出し画像G中の粒状材全体の投影面積Eに対する粒径di以上の粒状材の面積割合(=Σe/E)を各粒径diの粒度インデクスI(di)として算出する。 In step S302, the particle diameter d of each granular material in the rolled-out image G detected by the detecting means 17 is input to the particle size index calculating means 18a of the computer 10, for example, a plurality of predetermined particle diameters di in the rolled-out image G. For each (for example, 10 mm, 20 mm, 30 mm, 40 mm, etc.), the sum Σe of the areas of the granular materials each having a particle diameter di or larger is obtained, and the particles having a particle diameter di or larger with respect to the projected area E of the whole granular material in the rolled-out image G The area ratio (= Σe / E) of the material is calculated as the particle size index I (di) of each particle size di.
次いで、ステップS303において、算出手段18aで求めた複数の所定粒径diの粒度インデクスI(di)を関係式設定手段23に入力し、関係式設定手段23においてステップS301で入力した各所定粒径diの加積通過率P(di)と算出手段18aで求めた粒度インデクスI(di)との関係式Kを設定する。例えば図6に示すように、複数の所定粒径diの加積通過率P(di)及び粒度インデクスI(di)をそれぞれ二次平面上にプロットし、加積通過率P(di)を目的変数(従属変数)とし粒度インデクスI(di)を説明変数(独立変数)とする適切な回帰モデル(例えば粒度インデックスの多項式(多次元回帰モデル)、対数関数、べき関数、指数関数等)を設定して関係式Kとし、設定した関係式Kを記憶手段16に記憶する。 Next, in step S303, the particle size index I (di) of a plurality of predetermined particle diameters di obtained by the calculation means 18a is input to the relational expression setting means 23, and each predetermined particle diameter input in step S301 in the relational expression setting means 23. A relational expression K between the cumulative passing rate P (di) of di and the granularity index I (di) obtained by the calculation means 18a is set. For example, as shown in FIG. 6, the product passage rate P (di) and the particle size index I (di) of a plurality of predetermined particle sizes di are plotted on the secondary plane, and the product pass rate P (di) is obtained. Set an appropriate regression model (eg, a granularity index polynomial (multidimensional regression model), logarithmic function, power function, exponential function, etc.) with the variable (dependent variable) as the granularity index I (di) and the explanatory variable (independent variable) Then, the relational expression K is set, and the set relational expression K is stored in the storage unit 16.
好ましくは、ステップS301において複数の標本Tの撒き出し画像Gを撮像すると共にその複数の標本Tからそれぞれ加積通過率P(di)を求め、ステップS303において複数の標本Tから求めた加積通過率P(di)及び粒度インデクスI(di)に基づき関係式Kを設定する。図6から分かるように、同じ採取場で採取した粒状材料Sの標本Tから求めた各粒径diの加積通過率P(di)及び粒度インデクスI(di)は概ね近似しているが、標本T毎に多少の変動がみられるので、複数の標本Tに基づき相関係数rのできるだけ大きい関係式Kを設定することにより、後述する粒度インデクスI(di)から加積通過率P(di)を推定する精度を高めることができる。本発明者の実験によれば、例えば粒状材料Sの5〜10程度の標本Tを用いることにより、例えば相関係数rが0.995程度の関係式Kを設定することが可能である。 Preferably, in step S301, picked-up images G of a plurality of specimens T are imaged, and the product passage rate P (di) is obtained from each of the plurality of specimens T, and the product passage obtained from the plurality of specimens T in step S303. A relational expression K is set based on the rate P (di) and the granularity index I (di). As can be seen from FIG. 6, the accumulation passage rate P (di) and the particle size index I (di) of each particle size di obtained from the sample T of the granular material S collected at the same collection site are approximately approximate. Since some variation is observed for each sample T, by setting a relational expression K having a correlation coefficient r as large as possible based on a plurality of samples T, a product passage rate P (di ) Can be improved. 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, for example.
なお、ステップS301〜S303の関係式Kの設定は、必ずしも工事現場で行う必要はなく、例えば実験室等において粒状材料Sの複数の標本Tを用いて予め関係式Kを設定し、その関係式Kを現場のコンピュータ10に入力して記憶手段16に記憶することも可能である。この場合は、ステップS301〜S303に代えて関係式Kをコンピュータ10に入力するステップを設ければ足り、粒状材料Sの標本Tから関係式Kを求めるコンピュータ10の関係式設定手段23(図1参照)は省略可能である。 Note that the setting of the relational expression K in steps S301 to S303 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 S301 to S303, and the relational expression setting means 23 of the computer 10 for obtaining the relational expression K from the sample T of the granular material S (FIG. 1). Can be omitted.
図4のステップS304〜S309は、記憶手段16に記憶された関係式Kに基づき、採取場1又は破砕装置2から継続的に供給される粒状材料Sの分割式粒度計測方法の流れを示す。先ずステップS304において、上述した図2のステップS101と同様に、撒き出し装置4により粒状材料Sを複数に分割して撒き出し、撮像装置5により各分割粒状材群Sjの撒き出し画像Gj(図10(A)参照)を撮像してコンピュータ10に入力する。次いでステップS305〜S306において、コンピュータ10の検出手段17において撒き出し画像Gj毎に各粒状材の輪郭から面積e及び粒径dを求めると共に粒状材全体の投影面積Ej(=Σe)を求め、更に上述したステップS302と同様に、粒度インデクス算出手段18aにおいて撒き出し画像G毎に所定粒径diの粒度インデクスIj(di)を算出する。 Steps S304 to S309 in FIG. 4 show the flow of the divided particle size measurement method for the granular material S continuously supplied from the collection site 1 or the crushing device 2 based on the relational expression K stored in the storage unit 16. First, in step S304, similarly to step S101 of FIG. 2 described above, the granular material S is divided into a plurality of parts by the separating device 4, and the rolled-out images Gj (see FIG. 10 (A)) is captured and input to the computer 10. Next, in steps S305 to S306, the detection means 17 of the computer 10 obtains the area e and the particle diameter d from the outline of each granular material for each rolled-out image Gj, and obtains the projected area Ej (= Σe) of the entire granular material. Similar to step S302 described above, the granularity index calculating unit 18a calculates the granularity index Ij (di) of the predetermined particle diameter di for each rolled-out image G.
ステップS309において、撒き出し画像G毎の所定粒径diの粒度インデクスIj(di)をコンピュータ10の計測手段19の粒度インデクス変換手段19aに入力し、分割前の粒状材料Sの所定粒径diの加積通過率P(di)を計測する。粒度インデクス変換手段19aは、先ず上述した図2のステップS107と同様に、各画像Gjの投影面積Ejで重み付けした所定粒径diの粒度インデクスIj(di)の総計(=(ΣIj(di)・Ej)を求め、その粒度インデクスIj(di)の総計を全画像Gjの投影面積Ejの総計(=ΣEj)によって除して面積平均値(=(ΣIj(di)・Ej)/ΣEj)を算出することにより分割前の粒状材料Sの所定粒径diの粒度インデクスI(di)を求める。次いで、関係式Kにより、算出した粒状材料Sの所定粒径diの粒度インデクスI(di)を加積通過率P(di)に変換する。或いは、各画像Gjの投影面積Ejによる重み付けに代えて、上述したステップS108の場合と同様に、各画像Gjの全体積Vj(=Σv)で重み付けを行うことも可能である。 In step S309, the particle size index Ij (di) of the predetermined particle size di for each rolled-out image G is input to the particle size index converting unit 19a of the measuring unit 19 of the computer 10, and the predetermined particle size di of the granular material S before division is input. The accumulated passage rate P (di) is measured. The granularity index conversion means 19a first calculates the sum of the granularity indexes Ij (di) of a predetermined particle diameter di weighted by the projection area Ej of each image Gj (= (ΣIj (di) · Ej) is calculated, and the total of the granularity index Ij (di) is divided by the total of the projected areas Ej of all the images Gj (= ΣEj) to calculate the area average value (= (ΣIj (di) · Ej) / ΣEj) Thus, the particle size index I (di) of the predetermined particle size di of the granular material S before division is obtained, and then the calculated particle size index I (di) of the predetermined particle size di of the granular material S is added by the relational expression K. In other words, instead of weighting by the projected area Ej of each image Gj, the total product Vj (= Σv) of each image Gj is used in the same manner as in step S108 described above. It is also possible to perform weighting with.
図4のステップS310は、図2のステップS108と同様に、コンピュータ10の作成手段20により、粒状材料Sの加積通過率P(di)から粒径加積曲線P(d)を作成する処理を示す(図7参照)。またステップS311は、図2のステップS109と同様に、コンピュータ10の判定手段21により、粒状材料Sの粒径加積曲線P(d)を最粗粒標本Tr及び最細粒標本Tsの粒径加積曲線Pr(d)、Ps(d)と比較して粒度品質を判定する処理を示す。図3の流れ図のように、粒状材料Sの撒き出し画像Gから比較的容易に検出できる所定粒径diの粒度インデクスI(di)とその粒径diの加積通過率P(d)との関係式Kを用いることにより、撒き出し画像Gj毎に加積通過率Pj(di)を算出する手間を省き、粒状材料Sの粒度計測の更なる迅速化、簡単化を図ることができる。 Step S310 in FIG. 4 is a process of creating a particle size accumulation curve P (d) from the accumulation passage rate P (di) of the granular material S by the creation means 20 of the computer 10 in the same manner as step S108 in FIG. (See FIG. 7). Further, in step S311, as in step S109 of FIG. 2, the particle size accumulation curve P (d) of the granular material S is converted into the particle diameters of the coarsest sample Tr and the finest sample Ts by the determination means 21 of the computer 10. A process for determining the granularity quality in comparison with the accumulation curves Pr (d) and Ps (d) is shown. As shown in the flowchart of FIG. 3, the particle size index I (di) of a predetermined 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 By using the relational expression K, it is possible to save time and effort for calculating the accumulated passage rate Pj (di) for each rolled-out image Gj, and to further speed up and simplify the particle size measurement of the granular material S.
上述した図2及び図4の流れ図では、図7に示すように微小粒状材分離後の粒状材料Sから所定限界粒径D(例えば5〜10mm)以上の粒径加積曲線P(d≧D)を作成し、その粒径加積曲線P(d≧D)を最粗粒標本Tr及び最細粒標本Tsの所定限界粒径D以上の粒径加積曲線Pr(d≧D)、Ps(d≧D)と対比して粒度品質を判定している。しかし、図7の粒径加積曲線P(d≧D)には所定限界粒径D未満の微小粒状材の含有率が反映されておらず、とくに粒状材料S中に所定限界粒径D未満の微小粒状材が多量に含まれている場合は、所定限界粒径Dの近傍において粒状材料Sの粒径加積曲線P(d≧D)と最粗粒標本Tr及び最細粒標本Tsとを対比し、その何れの側に変動しているか(変動の傾向)等を確認することが難しくなる。最粗粒標本Tr及び最細粒標本Tsとの対比を簡単化するためには、所定限界粒径D未満の微小粒状材の含有率を考慮した粒径加積曲線P(d≧D)を作成することが有用である。 In the flowcharts of FIG. 2 and FIG. 4 described above, as shown in FIG. 7, a particle size accumulation curve P (d ≧ D) of a predetermined limit particle size D (for example, 5 to 10 mm) or more from the granular material S after separation of the fine granular material. ) And the particle size accumulation curve P (d ≧ D) is equal to or larger than the predetermined limit particle size D of the coarsest sample Tr and the finest sample Ts, and Ps (d ≧ D), Ps The particle size quality is determined in comparison with (d ≧ D). 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 limit particle size D, and is less than the predetermined limit particle size D in the granular material S. In the case where a large amount of the fine granular material is contained, in the vicinity of the predetermined limit particle size D, the particle size accumulation curve P (d ≧ D) of the granular material S, the coarsest particle sample Tr, and the finest particle sample Ts It is difficult to confirm which side is fluctuating (trend of fluctuation) or the like. 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) in consideration of the content of a fine granular material having a particle size less than a predetermined limit particle size D is used. It is useful to create.
図1の実施例では、粒径計測システムに微小粒状材を分離する分離装置6を含めると共に、微小粒状材を分離する前後の粒状材料Sの重量M及び含水率Zを計測する測定器7、8を含め、その重量M及び含水率Zの計測値から粒状材料S中の微小粒状材の加積通過率P(D)を求める演算手段22をコンピュータ10に設けている。図2のステップS105及び図4のステップS307は、コンピュータ10の演算手段22において、微小粒状材を分離する前後の粒状材料Sの重量M及び含水率Zの計測値から粒状材料S中の微小粒状材の含有率すなわち加積通過率P(D)を求める処理を示す。図2のステップS107及び図4のステップ309において演算手段22で求めた微小粒状材の加積通過率P(D)を算出手段19へ入力し(図1も参照)、算出手段19で算出した粒状材料Sの所定粒径diの加積通過率P(di)を微小粒状材の加積通過率P(D)に基づき調整している。 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 22 for obtaining the cumulative 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. Step S105 in FIG. 2 and step S307 in FIG. 4 are performed by the calculation means 22 of the computer 10 based on the measured values of the weight M and moisture content Z of the granular material S before and after separating the fine granular material. The process which calculates | requires the content rate of a material, ie, the accumulation passage rate P (D), is shown. 2 is input to the calculation means 19 (see also FIG. 1), and the calculation means 19 calculates the accumulated passage rate P (D) of the fine granular material obtained by the calculation means 22 in step S107 of FIG. 2 and step 309 of FIG. The accumulated passage rate P (di) of the granular material S with a predetermined particle diameter di is adjusted based on the accumulated passage rate P (D) of the minute granular material.
図3は、演算手段22による処理(図2のステップS105及び図4のステップS307)の詳細な流れ図を示す。先ず、ステップS201〜S202において分離装置6で所定限界粒径D(例えば5〜10mm)未満の微小粒状材を分離する前の粒状材料Sの重量Mb及び含水率Zbを重量測定器7b及び含水率測定器8bにより計測し、ステップS203において微小粒状材分離前の粒状材料Sの乾燥重量Mdbを算出する。次いで、ステップS204〜S205において分離装置6で微小粒状材を分離した後の粒状材料Sの重量Ma及び含水率Zaを重量測定器7a及び含水率測定器8aにより計測し、ステップS206において微小粒状材分離後の粒状材料Sの乾燥重量Mdaを算出する。重量測定器7b、7aの一例は、天秤、ロードセル等の粒状材料Sの質量測定で従来使用される装置であり、含水率測定器8b、8aの一例は近赤外線水分計やRI水分計である。ステップS207において、微小粒状材分離前後の粒状材料Sの乾燥重量Mdb、Mdaから、粒状材料S中の所定限界粒径D未満の微小粒状材の質量百分率すなわち加積通過率P(D)を算出する。 FIG. 3 shows a detailed flowchart of the processing (step S105 in FIG. 2 and step S307 in FIG. 4) by the computing means 22. First, in steps S201 to S202, the weight Mb and moisture content Zb of the granular material S before separating the fine granular material having a particle size less than the predetermined limit particle diameter D (for example, 5 to 10 mm) by the separation device 6 are determined. Measurement is performed by the measuring device 8b, and the dry weight Mdb of the granular material S before separation of the fine granular material is calculated in step S203. Next, the weight Ma and the water content Za of the granular material S after the fine granular material is separated by the separation device 6 in steps S204 to S205 are measured by the weight measuring device 7a and the water content measuring device 8a. 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 and a load cell, and examples of the moisture content measuring devices 8b and 8a are a near infrared moisture meter and an RI moisture meter. . 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 S less than the predetermined limit particle diameter D, that is, the cumulative passage rate P (D) is calculated. To do.
図2のステップS107及び図4のステップS309において、微小粒状材の加積通過率P(D)に基づき加積通過率P(di)を用いることにより、コンピュータ10の作成手段20において、ステップS108及びステップS310において、図8に示すような微小粒状材の加積通過率P(D)を考慮した粒径加積曲線P(d≧D)を作成することができる。具体的には、ステップS107及びステップS309において、演算手段22で求めた微小粒状材の加積通過率P(D)から所定限界粒径D以上の質量割合を求め(100−P(D))、その質量割合と計測手段19で計測した所定粒径diの加積通過率P(di)とを乗算することで所定粒径diの加積通過率P´(di)(=P(D)+(100−P(D))×P(di))を再計算する。再計算後の所定粒径diの加積通過率P´(di)と微小粒状材の加積通過率P(D)とを粒径di別にプロットして連結することにより、図8のような粒径加積曲線P(d≧D)を作成する。 In step S107 of FIG. 2 and step S309 of FIG. 4, the creation means 20 of the computer 10 uses step S108 by using the accumulation passage rate P (di) based on the accumulation passage rate P (D) of the fine granular material. In step S310, a particle diameter accumulation curve P (d ≧ D) can be created in consideration of the accumulation passage rate P (D) of the fine granular material as shown in FIG. Specifically, in step S107 and step S309, a mass ratio equal to or larger than a predetermined limit particle diameter D is obtained from the accumulated passage rate P (D) of the fine granular material obtained by the calculation means 22 (100-P (D)). By multiplying the mass ratio by the accumulated passage rate P (di) of the predetermined particle size di measured by the measuring means 19, the accumulated passage rate P '(di) (= P (D) of the predetermined particle size di. + (100−P (D)) × P (di)) is recalculated. By plotting and connecting the accumulation passage rate P ′ (di) of the predetermined particle diameter di after recalculation and the accumulation passage ratio P (D) of the fine granular material for each particle diameter di, as shown in FIG. A particle size accumulation curve P (d ≧ D) is created.
微小粒状材の加積通過率P(D)を考慮して作成した粒状材料Sの粒径加積曲線P(d≧D)は、図2のステップS109〜S110及び図4のステップS311において、図8に示すように最粗粒標本Tr及び最細粒標本Tsの粒径加積曲線Pr(d)、Ps(d)と直接比較して粒度品質を判定することができる。例えば、図8において粒状材料Sの粒径加積曲線P(d≧D)は、粒径加積曲線Pr、Psの規定範囲内にあるが、所定限界粒径Dの近傍において最粗粒標本Tr側よりも最細粒標本Ts側に近接しており、平均粒径よりも若干細かい粒径分布であると判定できる。また、図8のような粒径加積曲線P(d≧D)を累積記憶しておけば、今回と前回の粒径加積曲線Pとを比較することにより、粒状材料Sの粒度の正確な経時的変化(粒度変動)を迅速に把握することができる。 The particle size accumulation curve P (d ≧ D) of the granular material S created in consideration of the accumulation passage rate P (D) of the fine granular material is obtained in steps S109 to S110 in FIG. 2 and step S311 in FIG. As shown in FIG. 8, the particle size quality can be determined by directly comparing the particle size accumulation curves Pr (d) and Ps (d) of the coarsest 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 prescribed range of the particle size accumulation curves Pr and Ps, but in the vicinity of the predetermined limit particle size D, the coarsest grain sample It can be determined that the particle size distribution is closer to the finest grain sample Ts side than the Tr side and is slightly finer than the average particle size. Further, 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, the accuracy of the particle size of the granular material S can be compared. Change over time (granularity fluctuation) can be quickly grasped.
なお、図3のステップS208〜S211は、本発明の粒径計測システムに粒状材料Sの粒径di毎の吸水率q及び表乾密度ρを計測する測定器(図示せず)を含め、コンピュータ10の演算手段22により、その吸水率q及び表乾密度ρの計測値から粒状材料Sの表面水量Wを算出する処理を示す。図13を参照して上述したように、CSG工法では粒状材料Sの粒度と共にCSGの単位水量を管理する必要があり(図13のひし形(斜線部分)の規定範囲を参照)、粒状材料Sの表面水量Wが求まればCSGの単位水量の管理に利用できる。図3の流れ図ではステップS208〜209において粒状材料Sの吸水率qを測定器から入力し、ステップS202で計測した含水率Zbに基づき粒状材料Sの表面水率ωを算出する。そして、ステップS210において粒状材料Sの表乾密度ρを測定器から入力し、ステップS211において粒状材料Sの表面水率ωと表乾密度ρとから表面水量Wを算出する。例えば図2のステップS111において、図3のステップS211で求めた表面水量Wに基づき、粒状材料Sに混合する水量を図13の「ひし形」の規定範囲内となるように調整・管理する。 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 the 10 calculating means 22. As described above with reference to FIG. 13, in the CSG method, it is necessary to control the unit water amount of the CSG together with the particle size of the granular material S (see the prescribed range of the rhombus (hatched portion) in FIG. 13). If the surface water amount W is obtained, it can be used to manage the unit water amount of the CSG. In the flowchart of FIG. 3, the water absorption rate q of the granular material S is input from the measuring device in steps S208 to 209, 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 device, 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 S111 in FIG. 2, based on the surface water amount W obtained in step S211 in FIG. 3, the amount of water mixed into the granular material S is adjusted and managed so as to be within the specified range of “diamonds” in FIG.
また、図2のステップS112において、今回供給材料Stの各粒径diの粒度インデクスIt及び粒径加積曲線Pt(d)と共に図3のステップS211で求めた表面水量Wtを記憶手段16に累積記憶しておけば、次回以降のステップS109〜110の判定処理において、判定手段21により今回及び前回の粒度インデクスItと粒径加積曲線P(d)tと表面水量Wtとを比較して粒度及び表面水量の変動を迅速に判定することができる。粒状材料Sの粒度及び表面水量の変動を迅速に把握することにより、CSG工法等の粒状材料Sを用いた建設工事における詳細な品質管理が可能となり、管理精度の更なる向上が期待できる。 Further, in step S112 of FIG. 2, the storage surface water W t obtained at step S211 in FIG. 3 with a particle size index I t and particle size accumulation curve P t (d) of the particle size di of the current feed S t if cumulatively stored in unit 16, in the determination process of the next subsequent step S109~110, particle size of the current and the previous index by determining means 21 I t and grain size accumulation curve P (d) t and surface water W t Can be quickly determined for particle size and surface water fluctuation. 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.
図1の実施例においても、上述した特許文献1と同様に、コンピュータ10の記憶手段16に、粒状材料Sの標本Tから求めた所定限界粒径D未満の微小粒状材の粒径加積曲線P(d≦D)をその標本T中の微小粒状材の加積通過率P(D)の関数U、Rとして記憶しておけば、上述した演算手段22で求めた粒状材料S中の微小粒状材の加積通過率P(D)から関数U、Rにより微小粒状材の粒径加積曲線P(d≦D)を推定することができる(図1の推定手段24参照)。更に、コンピュータ10の作成手段20(図2のステップS108及び図4のステップS310)において、例えば図8に示すような微小粒状材分離後の粒状材料Sの粒径加積曲線P(d≧D)と、推定手段24で推定した粒状材料Sの微小粒状材の粒径加積曲線P(d≦D)とを合成することにより、例えば図11に示すように全粒径範囲にわたる粒径加積曲線P(d)を作成することができる。 In the embodiment of FIG. 1 as well, as in the above-described Patent Document 1, the particle size accumulation curve of a fine granular material having a particle size less than a predetermined limit particle size D obtained from the sample T of the granular material S is stored in the storage means 16 of the computer 10. If P (d ≦ D) is stored as the functions U and R of the accumulation passage rate P (D) of the fine granular material in the sample T, the minute amount in the granular material S obtained by the calculation means 22 described above is stored. The particle size accumulation curve P (d ≦ D) of the fine granular material can be estimated from the accumulated passage rate P (D) of the granular material by the functions U and R (see the estimation means 24 in FIG. 1). Further, in the creation means 20 (step S108 in FIG. 2 and step S310 in FIG. 4) of the computer 10, for example, the particle size accumulation curve P (d ≧ D) of the granular material S after separation of the fine granular material as shown in FIG. ) And the particle size accumulation curve P (d ≦ D) of the fine granular material S of the granular material S estimated by the estimating means 24, for example, as shown in FIG. A product curve P (d) can be created.
粒状材料Sの所定限界粒径D未満の粒径加積曲線P(d≦D)は、例えば微小粒状材の所定限界粒径Dに対する粒径比(=d/D)の所定指数関数U{(d/D)n}として近似することができる。そのような指数関数Pの一例は、Talbot関数(P/P(D)=(d/D)n)、Gaudin−Meloy関数(P/P(D)=1−(1−d/D)n)、又はRosin−Rammler関数(P/P(D)=1−exp(−d/D)n))である。図2及び図4の流れ図においても、予め粒状材料Sの標本Tから所定限界粒径D未満の微小粒状材の粒径加積曲線P(d≦D)の近似関数Uを求めておけば、ステップS108又はステップS310において、作成手段20によって所定限界粒径D以上の粒径加積曲線P(d≧D)と微小粒状材の粒径加積曲線P(d≦D)の近似関数Uとを合成することにより、粒状材料Sの全粒径範囲にわたる粒径加積曲線P(d)を作成することができる。 The particle size accumulation curve P (d ≦ D) less than the predetermined limit particle size D of the granular material S is, for example, a predetermined exponential function U {of the particle size ratio (= d / D) to the predetermined limit particle size D of the fine granular material. (D / D) n } can be approximated. 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 )). Also in the flowcharts of FIGS. 2 and 4, if an approximate function U of a particle size accumulation curve P (d ≦ D) of a fine granular material less than a predetermined limit particle size D is obtained in advance from the sample T of the granular material S, In step S108 or step S310, the creation means 20 approximates a particle size accumulation curve P (d ≧ D) greater than or equal to the predetermined limit particle size D and a particle size accumulation curve P (d ≦ D) of the fine granular material, , The particle size accumulation curve P (d) over the entire particle size range of the granular material S can be created.
図2のステップS106及び図4のステップS308は、コンピュータ10の推定手段24により、粒状材料S中の微小粒状材の加積通過率P(D)から関数Uにより微小粒状材の粒径加積曲線P(d≦D)を推定する処理を示す。例えば、上述した所定指数関数U{(d/D)n}の指数nが微小粒状材の加積通過率P(D)に拘わらず一定であれば、演算手段22で求めた微小粒状材の加積通過率P(D)を指定関数U{(d/D)n}へ代入することにより、微小粒状材の粒径加積曲線P(d≦D)を推定することができる。図2のステップS108又は図4のステップS310において、推定手段24で推定した微小粒状材の粒径加積曲線P(d≦D)を作成手段20に入力し、その粒径加積曲線P(d≦D)と所定限界粒径D以上の粒径加積曲線P(d≧D)とを連結することにより、図11に示すような全粒径範囲にわたる粒径加積曲線P(d)を作成することができる。 Step S106 in FIG. 2 and step S308 in FIG. 4 are performed by the estimation means 24 of the computer 10 and the particle size accumulation of the fine granular material by the function U from the accumulation passage rate P (D) of the fine granular material in the granular material S. The process which estimates the curve P (d <= D) is shown. For example, if the index n of the above-mentioned predetermined exponential function U {(d / D) n } is constant irrespective of the accumulation passage rate P (D) of the fine granular material, the fine granular material obtained by the calculating means 22 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 S108 of FIG. 2 or step S310 of FIG. 4, the particle size accumulation curve P (d ≦ D) of the fine granular material estimated by the estimation unit 24 is input to the creation unit 20, and the particle size accumulation curve P ( d ≦ D) and a particle size accumulation curve P (d) over the entire particle size range as shown in FIG. Can be created.
また、特許文献1が開示するように、微小粒状材の粒径加積曲線P(d≦D)を所定指数関数U{(d/D)n}で近似した場合に、その指数関数U{(d/D)n}の指数nが粒状材料S中の微小粒状材の加積通過率P(D)に依存して変化する場合がある。その場合は、粒状材料Sの複数の標本Tから指数関数U{(d/D)n}を求めると共に、その指数nと粒状材料S中の微小粒状材の加積通過率P(D)との関係式Rを検出し、その関係式Rをコンピュータ10の記憶手段16に記憶しておく。図2のステップS106又は図4のステップS308において、先ず演算手段22で求めた微小粒状材の加積通過率P(D)から指数nを求めて指数関数U{(d/D)n}を定めたうえで、その指数関数U{(d/D)n}に微小粒状材の加積通過率P(D)を代入することにより、微小粒状材の粒径加積曲線P(d≦D)を推定する。例えば図2のステップS108において、図11のような全粒径範囲にわたる粒径加積曲線P(d)を作成しておけば、ステップS109〜110の判定処理において最粗粒標本Tr及び最細粒標本Tsの粒径加積曲線Pr(d)、Ps(d)と全粒径範囲にわたり比較することができ、粒状材料Sの粒度品質を高精度で判定することが可能となる。 Further, as disclosed in Patent Document 1, 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 S106 of FIG. 2 or step S308 of FIG. 4, first, an exponent n is obtained from the accumulated passage rate P (D) of the fine granular material obtained by the computing means 22, and an exponential function U {(d / D) n } is obtained. Then, 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 ). For example, in step S108 of FIG. 2, if the particle size accumulation curve P (d) over the entire particle size range as shown in FIG. 11 is created, the coarsest sample Tr and the finest sample are determined in the determination processing of steps S109 to 110. The particle size accumulation curves Pr (d) and Ps (d) of the particle sample Ts 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.
1…採取場(地山) 2…破砕装置
3…運搬装置 4…撒き出し装置
5…撮像装置 6…分離装置
7a、8a…重量測定器 7b、8b…含水率測定器
9…体積測定装置
10…コンピュータ 11…入力装置
12…出力装置 14…入力手段
15…出力手段 16…記憶手段
17…検出手段
18…算出手段 18a…粒度インデクス算出手段
19…計測手段 19a…粒度インデクス変換手段
20…作成手段 21…判定手段
22…演算手段 23…関係式設定手段
24…推定手段
30…粒度試験装置 31…画像解析手段
32…(粒径加積曲線)作図手段 33…関係式検知手段
34…体積測定手段 37…(粒径加積曲線)作成手段
38…推定手段 39…合成手段
S…粒状材料 T…粒状材料標本
Sj…分割粒状材群 s…粒状材
Gj…撒き出し画像 Ej…(画像毎の)粒状材全体の投影面積
P…加積通過率、粒径加積曲線 I…粒度インデクス
Pj…(画像毎の)加積通過率 Ij…(画像毎の)粒度インデクス
d…(粒状材の)粒径
M…重量 Z…含水率
DESCRIPTION OF SYMBOLS 1 ... Collection place (natural ground) 2 ... Crushing device 3 ... Conveying device 4 ... Unloading device 5 ... Imaging device 6 ... Separation device 7a, 8a ... Weight measuring device 7b, 8b ... Water content measuring device 9 ... Volume measuring device 10 ... Computer 11 ... Input device 12 ... Output device 14 ... Input means 15 ... Output means 16 ... Storage means 17 ... Detection means 18 ... Calculation means 18a ... Granularity index calculation means 19 ... Measurement means 19a ... Granularity index conversion means 20 ... Create means DESCRIPTION OF SYMBOLS 21 ... Judgment means 22 ... Calculation means 23 ... Relational expression setting means 24 ... Estimation means 30 ... Particle size test apparatus 31 ... Image analysis means 32 ... (Particle size accumulation curve) drawing means 33 ... Relational expression detection means 34 ... Volume measurement means 37 ... (particle diameter accumulation curve) creating means 38 ... estimating means 39 ... synthesizing means S ... granular material T ... granular material specimen Sj ... divided granular material group s ... granular material Gj ... unrolled image Ej ... ( Projected area P of the whole granular material (for each image) ... Accumulated passage rate, particle size accumulation curve I ... Granularity index Pj ... (per image) Accumulated passage rate Ij ... (per image) Particle size index d ... (granular) Particle size M ... weight Z ... moisture content
Claims (8)
Priority Applications (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
JP2011109125A JP5658613B2 (en) | 2011-05-16 | 2011-05-16 | Method and system for dividing particle size of granular material |
Applications Claiming Priority (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
JP2011109125A JP5658613B2 (en) | 2011-05-16 | 2011-05-16 | Method and system for dividing particle size of granular material |
Publications (2)
Publication Number | Publication Date |
---|---|
JP2012242099A JP2012242099A (en) | 2012-12-10 |
JP5658613B2 true JP5658613B2 (en) | 2015-01-28 |
Family
ID=47463989
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
JP2011109125A Active JP5658613B2 (en) | 2011-05-16 | 2011-05-16 | Method and system for dividing particle size of granular material |
Country Status (1)
Country | Link |
---|---|
JP (1) | JP5658613B2 (en) |
Families Citing this family (7)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
JP6189059B2 (en) * | 2013-03-15 | 2017-08-30 | 五洋建設株式会社 | Soil size analysis method |
JP6243640B2 (en) * | 2013-06-28 | 2017-12-06 | 大成建設株式会社 | Particle size distribution measurement system and weight conversion coefficient calculation system |
JP6173894B2 (en) * | 2013-11-30 | 2017-08-02 | 鹿島建設株式会社 | Surface water volume management method and system for ground material |
JP6319791B2 (en) * | 2014-03-19 | 2018-05-09 | 鹿島建設株式会社 | Method and system for measuring particle size of ground material |
JP6489912B2 (en) * | 2015-04-14 | 2019-03-27 | 前田建設工業株式会社 | Particle size distribution analysis method and quality control method for construction materials |
CN105043947A (en) * | 2015-08-07 | 2015-11-11 | 中国水利水电科学研究院 | Grain gradation detection system and detection method of earth-stone work material |
CN111898083B (en) * | 2020-08-07 | 2024-03-22 | 河北师范大学 | Model for describing particle size distribution of dry agglomerates |
Family Cites Families (7)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
JPS63208740A (en) * | 1987-02-25 | 1988-08-30 | Osaka Gas Co Ltd | Measuring instrument for particle size distribution for lump body |
JPH0216432A (en) * | 1988-07-05 | 1990-01-19 | Seiki Tokyu Kogyo Kk | Aggregate grading analyzing method and broken stone grading control method for asphalt plant using image processing |
JP2006078234A (en) * | 2004-09-07 | 2006-03-23 | Kyoto Univ | Gravel measuring instrument and method |
JP4883799B2 (en) * | 2007-07-31 | 2012-02-22 | 鹿島建設株式会社 | Ground material particle size measurement system and program |
JP5253059B2 (en) * | 2008-09-10 | 2013-07-31 | 太平洋セメント株式会社 | Measuring system and measuring method of particle size distribution of granular material |
JP5234649B2 (en) * | 2009-04-13 | 2013-07-10 | 鹿島建設株式会社 | Granular quality control system and program for granular materials |
JP5582806B2 (en) * | 2010-02-06 | 2014-09-03 | 鹿島建設株式会社 | Granule size measurement system and program |
-
2011
- 2011-05-16 JP JP2011109125A patent/JP5658613B2/en active Active
Also Published As
Publication number | Publication date |
---|---|
JP2012242099A (en) | 2012-12-10 |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
JP5658613B2 (en) | Method and system for dividing particle size of granular material | |
JP5582806B2 (en) | Granule size measurement system and program | |
JP4883799B2 (en) | Ground material particle size measurement system and program | |
JP5896465B2 (en) | Method and system for measuring particle size distribution of granular material | |
Slominski et al. | Application of particle image velocimetry (PIV) for deformation measurement during granular silo flow | |
Bertin et al. | Effect of surface texture and structure on the development of stable fluvial armors | |
Kuhnle et al. | Sand transport over an immobile gravel substrate | |
Ren et al. | The grain size distribution and composition of the Touzhai rock avalanche deposit in Yunnan, China | |
JP5234649B2 (en) | Granular quality control system and program for granular materials | |
Gili et al. | Rockfalls: Analysis of the block fragmentation through field experiments | |
Seitz et al. | From picture to porosity of river bed material using Structure-from-Motion with Multi-View-Stereo | |
Spreitzer et al. | Porosity and volume assessments of large wood (LW) accumulations | |
Wei et al. | Automated bughole detection and quality performance assessment of concrete using image processing and deep convolutional neural networks | |
An et al. | A fast and practical method for determining particle size and shape by using smartphone photogrammetry | |
CN118096865A (en) | Rock-fill material grading detection method and device based on pre-screening and video image optimization | |
JP6672823B2 (en) | Ground material particle size monitoring method and three-dimensional image processing equipment | |
Sajeevan et al. | Investigation of boundary layer impact on pervious concrete | |
JP2017198017A (en) | Quality management method for rock zone in rock fill dam | |
Zapico et al. | Morpho-textural implications to bedload flux and texture in the sand-gravel ephemeral Poveda Gully | |
JP6319791B2 (en) | Method and system for measuring particle size of ground material | |
Arrieta | Novel Approach for Particle Size Distribution Analysis. Applied Case to Rockfills and Waste Dumps Using Unmanned Aerial Vehicle (UAV) | |
Santamarina et al. | Development and testing of a zooming technique for fragmentation measurement | |
JP6156852B2 (en) | Method and system for measuring particle size distribution of granular material | |
JP7207842B2 (en) | Grain size determination method and system for ground material | |
Guo et al. | Research on the intelligent detection technology of multi-objective coarse aggregates |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
A621 | Written request for application examination |
Free format text: JAPANESE INTERMEDIATE CODE: A621 Effective date: 20131102 |
|
A977 | Report on retrieval |
Free format text: JAPANESE INTERMEDIATE CODE: A971007 Effective date: 20140304 |
|
TRDD | Decision of grant or rejection written | ||
A01 | Written decision to grant a patent or to grant a registration (utility model) |
Free format text: JAPANESE INTERMEDIATE CODE: A01 Effective date: 20141110 |
|
A61 | First payment of annual fees (during grant procedure) |
Free format text: JAPANESE INTERMEDIATE CODE: A61 Effective date: 20141128 |
|
R150 | Certificate of patent or registration of utility model |
Ref document number: 5658613 Country of ref document: JP Free format text: JAPANESE INTERMEDIATE CODE: R150 |
|
R250 | Receipt of annual fees |
Free format text: JAPANESE INTERMEDIATE CODE: R250 |
|
R250 | Receipt of annual fees |
Free format text: JAPANESE INTERMEDIATE CODE: R250 |
|
R250 | Receipt of annual fees |
Free format text: JAPANESE INTERMEDIATE CODE: R250 |