2d image analysis using wipfrag software compared with actual

Report 2009:P1 ISSN 1653-5006

Swedish Blasting Research CentreMejerivägen 1, SE-117 43 Stockholm

Luleå University of TechnologySE-971 87 Luleå www.ltu.se

2D image analysis using WipFrag software compared with actual sieving data of Kiruna magnetite loaded from a drawpoint

2D-bildanalys med WipFrag-programmet, jämförelse med siktning av Kirunamagnetit från en lastort

Matthias Wimmer, SwebrecFinn Ouchterlony, Swebrec

Universitetstryckeriet, L

uleå

Swebrec Report 2009:P1

2D image analysis using WipFrag software compared with actual sieving data of Kiruna magnetite loaded from a draw point

2D-bildanalys med WipFrag-programmet, jämförelse med siktning av Kirunamagnetit från en lastort

Matthias Wimmer, Swebrec

Finn Ouchterlony, Swebrec

Luleå October 2009, revised November 17, 2009

Swebrec - Swedish Blasting Research Centre

Luleå University of Technology

Department of Civil and Environmental Engineering • Division of Rock Engineering

i

2D image analysis (WipFrag) compared with sieving data Swebrec Report 2009:P1

SUMMARY

The objective of this study is to compare actual fragmentation data from a full-scale test sieving

campaign with images evaluated by using the granulometry analysis software WipFrag.

The input data is summarized as follows:

6 individual samples taken at an SLC draw point at 7.5 % extraction rate;

Images from buckets (underground) and piles spread and re-mixed (on the surface);

Image resolution 640 x 480 and 1600 x 1200 pixels;

Manual delineation and automatic net delineation using LKAB`s standard parameters.

To quantify the results of the WipFrag evaluation its derived percentile sizes (x25, x50, xc, x75 and x90)

were compared with the percentiles from full-scale sieving for the respective sample.

Automatic analysis based on 640 x 480 images and LKAB`s standard edge detection parameters

causes systematic errors by the fusion of small particles and disintegration of larger fragments.

Reasonable correlation curves found for bucket and pile images would allow correction of this.

Linking old recordings to true fragmentation calibration shots with the on-site WipFrag system during

actual production conditions would be required. The latest version of WipFrag incorporates re-worked

edge detection settings. Rapid first-trials using auto edge detection settings have given better results

compared with LKAB`s standard parameters to generate a fragmentation net. Indeed, a test of the

latest version of WipFrag is recommended.

Manual analysis based on 640 x 480 images still causes deviation in the fines region (0 - 0.2 m) within

or above the magnitude of the actual sizes of interest. Reliable estimates can be expected for the mid-

range 0.2 - 0.4 m, but differences occur again in the coarser fractions and might then be due to

sampling error.

Evaluating manually delineated images with 1600 x 1200 resolutions considerably improves the

estimation of sizes in the fines region. The effect measured as mean deviation from sizes determined

by sieving amounts to 59.1, 48.9 and 30.5 % in the size classes 0 - 0.05, 0.05 - 0.1 and 0.1 - 0.2 m

respectively. Almost no deviation from the actual sieved sizes is recognizable for fractions 0.2 - 0.3 m.

Again, deviations occurring at coarser fractions than that might be explained by sampling error.

Severe segregation is likely to occur during the loading process and be present in the images taken

from buckets, which causes a wider spread of the measured sizes compared with pile images. This

effect increases in the large size fractions.

The larger image section (1600 x 1200) and more particles identifiable within the pile images do not

substantially improve the problematic deviations from the actual sieve sizes within the fine fractions.

The errors related to bucket images appear to be more erratic whereas comparing piles before (mix 1)

and after re-mixing (mix 2) a tendency for smaller sizes can be recognized after materials handling.

ii


SAMMANFATTNING

Syftet med denna rapport är att jämföra det verkliga styckefallet från fullskaleförsök med värden

erhållna ur bilder med programvaran WipFrag. Indata till bildanalysen utgörs av:

Sex siktprov från en lastort vid 7,5 % utlastningsgrad;

Bilder från skopor (under jord) och berghögar, utjämnade och sedan omblandade (ovan jord);

Bildupplösning 640 × 480 och 1600 × 1200 pixlar;

Manuell kantlinjedetektering och automatisk sådan med LKAB:s standardinställning.

För att kvantifiera resultaten från uppskattning av fragmentering med WipFrag så jämfördes de

erhållna percentilerna (x25, x50, xc, x75 and x90) med motsvarande percentiler från siktning av första

delen av en fullskalig skivrassalva.

En automatiska analys av bilder med 640 × 480 pixlar och LKAB:s standardinställning ger

systematiska fel genom att små stenar klumpas ihop och stora stenar splittras upp. Om rimliga

korrelationskurvor tas fram för bilderna av skopor och berghögar så kan detta kompenseras för. Det

skulle emellertid kräva att gamla bilder korreleras med riktiga kalibreringsbilder tagna med det

platsinstallerade WipFrag-systemet under produktionsförhållanden. Det bör också noteras att den

senaste versionen av WipFrag har omarbetade kantdetekteringsinställningar som gett rimligare kantnät

än standardinställningen vid ett snabbt förstaprov.

En manuell analys av bilder med 640 × 480 pixlar orsakar fortfarande avvikelser ovanför den verkliga

kumulativa siktkurvan i finområdet (0 - 0,2 m). I mellanområdet 0,2 - 0,4 m erhålls tillförlitliga

siktvärden men för större stenar erhålls fel som kan förklaras av samplingsfelet.

En manuell analys av bilder med 1600 × 1200 pixlar minskar felen i finområdet betydligt. Avvikelsen

från siktvärdena är respektive som mest 59,1, 48,9 och 30,5 % i klasserna 0 - 0,05, 0,05 - 0,1 och 0,1 -

0,2 m. I storleksområdet 0,2 - 0,3 m är avvikelserna försumbara. Samplingsfelet bedöms åter vara

huvudorsaken till avvikelserna i grovområdet.

Allt tyder på att en avsevärd segregering av materialet sker under lastningen, vilket orsakar större

variationer i de kumulativa siktdata från skoporna än från berghögarna. Denna tendens är större för

stora stenar. Berghögarna täcker en större del av bilden och uppvisar betydligt fler identifierbara

småstenar. Ändå verkar inte det problematiska felet i finområdet påverkas särskilt mycket. Felen som

erhålls från skopbilderna verkar vara mer slumpmässiga än felen från bilderna av berghögarna. När

högarna blandas om verkar siktvärdena sjunka.

iii


Contents

1 INTRODUCTION ..................................................................................................... 1

2 WORKING PROCEDURE ....................................................................................... 2

2.1 Image acquisition .................................................................................................................... 2

2.2 2D image analysis (WipFrag) .................................................................................................. 4

3 RESULTS ............................................................................................................... 5

3.1 Manual versus automatic net delineation (640 x 480 resolution) ............................................ 5

3.2 Influence of image resolution (640 x 480 vs. 1600 x 1200 resolution) ................................... 7

3.3 Segregation effects (1600 x 1200 resolution) .......................................................................... 8

4 CONCLUDING REMARKS ..................................................................................... 9

5 ACKNOWLEDGEMENTS ......................................................................................11

6 REFERENCES .......................................................................................................12

7 APPENDICES ........................................................................................................13

iv


APPENDICES

Appendix 1. Examples of bucket images taken from the WipFrag system (640x480). ........................ 13

Appendix 2. Description of edge detection parameters (WipWare 2006). ........................................... 14

Appendix 3. Bucket images, 640 x 480, manual delineation. ............................................................... 15

Appendix 4. Bucket images, 1600 x 1200, manual delineation. ........................................................... 17

Appendix 5. Bucket images, 640 x 480, automatic delineation. ........................................................... 19

Appendix 6. Pile images, mix 1, 640 x 480, manual delineation. ......................................................... 21

Appendix 7. Pile images, mix 1, 1600 x 1200, manual delineation. ..................................................... 23

Appendix 8. Pile images, mix 1, 640 x 480, automatic delineation. ..................................................... 25

Appendix 9. Pile images, mix 2, 640 x 480, manual delineation. ......................................................... 27

Appendix 10. Pile images, mix 2, 1600 x 1200, manual delineation. ................................................... 29

Appendix 11. Pile images, mix 2, 640 x 480, automatic delineation. ................................................... 31

Appendix 12. Fragmentation data, sample 1. ........................................................................................ 33






Appendix 18. Percentile sizes (m) for sieving and WipFrag evaluation, all samples. .......................... 39

Appendix 19. WipFrag statistics, all samples. ...................................................................................... 40

Appendix 20. Definition of WipFrag statistics. ..................................................................................... 41

FIGURES

Figure 1. Principles of sieving campaign. ............................................................................................... 2

Figure 2. Image acquisition underground with camera installed at the roof. .......................................... 3

Figure 3. Individual rock piles. ............................................................................................................... 3

Figure 4. Re-mixing of a rock pile. ......................................................................................................... 3

Figure 5. Deviation between percentile sizes automatically analyzed by WipFrag and sieving result vs.

pe-centile sizes from sieving, buckets and piles. Data count (24/12/18/15/12/9). .............. 5

Figure 6. Deviation between percentile sizes manually analyzed by WipFrag and sieving result vs.

percen-tile sizes from sieving, buckets and piles. Data count (24/12/18/15/12/9). ............ 5

Figure 7. Deviation between percentile sizes automatically analyzed by WipFrag and sieving result vs.

per-centile sizes from sieving, grouped into buckets and piles. .......................................... 6

Figure 8. Deviation between percentile sizes manually analyzed by WipFrag and sieving result vs.

percen-tile sizes from sieving, buckets and piles, image resolution 640 x 480 (gray) and

1600 x 1200 (green). Data count (24/12/18/15/12/9). ........................................................ 7

v


Figure 9. Deviation between percentile sizes manually analyzed by WipFrag and sieving result vs. per-

centile sizes from sieving, image resolution 1600 x 1200, buckets (gray), piles mix 1

(orange) and piles mix 2 (green). Data count (16/7/7). ....................................................... 8

TABLES

Table 1. Summary of analyzed images.................................................................................................... 4

1


1 INTRODUCTION

This report complements Swebrec Report 2008:P2 “The fragment size distribution of Kiruna

magnetite loaded from a draw point – Evaluation and analysis of a full-scale test” (Wimmer et al.,

2008). During this campaign images of all 6 samples have been taken at different stages and

resolutions, both directly from the buckets underground as well as from piles spread and re-mixed on

the surface. The fragmentation analysis program WipFrag (Maerz et al., 1996) was chosen for the

secondary image evaluation since there is an automatic imaging and analyzing system at the mine site

which is periodically in use at dedicated test sites. The aim was to calibrate the on-line fragmentation

measurement system WipFrag owned by LKAB. Technical problems (data communication) prevented

us from using the intended system camera. Instead, pictures were taken with a remote controlled

digital camera (Canon, Powershot G7, 10 MPixel). In addition, the influence of resolution (640 x 480

and 1600 x 1200) on the image algorithm could be tested. Calibration shots under actual production

conditions would be needed to directly transfer the results of this report.

Sieving constitutes the true fragment size distribution if the process itself is done without error.

Methods based on digital imaging to determine the fragment size distribution of rock are widely used.

These have the major advantage of producing fast estimates without interfering with production

(Ouchterlony, 2003). Thereby systematic errors in combination with controlled testing conditions are

generally well understood (Maerz & Zhou, 1998; anchidri n et al., 2009) whereas those caused under

severe production conditions (segregation effects, dust conditions, etc.) are relatively difficult to take

into account. This is the last link that is needed to obtain an estimation of how the old recordings relate

to the true fragmentation.

To meet the requirements the present report will investigate:

(a) differences between manual and automatic net delineation (LKAB`s standard parameters),

(b) the influence of image resolution,

(c) and segregation effects.

The latter should furthermore be used for decision-making if an upgrade to a WipFrag system with

increased resolution (1600 x 1200 pixels) gives a considerably better resolution in the fines region

without sacrifices in the coarse range.

2


2 WORKING PROCEDURE

2.1 Image acquisition

A total of 6 buckets and 96 tonnes of magnetite ore have been taken from ring no. 7, drift 377 within

block 37, level 907 of the Kiruna mine. To ensure loading of pure magnetite the 6 individual samples

have been taken in series just after an initial extraction of 20 buckets (~7.5 % extraction).

The entire test campaign is summarized by the following flow sheet, see Figure 1.

Figure 1. Principles of sieving campaign.

To begin with we intended to calibrate the on-line fragmentation measurement system WipFrag owned

by LKAB. Technical problems (data communication) prevented us from using the intended system

camera. Instead, pictures were taken with a remote controlled digital camera (Canon, Powershot G7,

10 MPixel). In addition, the influence of resolution (640 x 480 and 1600 x 1200) on the image

algorithm could be tested. The camera was mounted close to the WipFrag system under the roof (see

Figure 2). The loader (CAT 980G, 16 tonne capacity) used was much smaller than the units used in

production. By comparing the present images with those taken by the WipFrag camera in the past

(some examples within Appendix 1) large differences quality can be seen even if both were taken at

the same resolution (640 x 480 pixels). Besides advances in camera technology this is most likely due

to the fact that the images were taken in a static way this time as loader stopped shortly for the image

to be taken. Moreover, images within that campaign were made under perfect conditions (even

lighting, reduced dust, etc.). However, diagonal banding effects appearing on the pictures taken by the

3


WipFrag system require closer examination of the hardware. Later calibration shots of arbitrarily

chosen buckets, but under similar conditions to compare the two cameras are a possibility.

Figure 2. Image acquisition underground with camera installed at the roof.

The material was then transported up to the surface and spread out on a plane tarmac surface close to

the processing plants (Figure 3 - Figure 4). After flattening the piles, reference points were added and

surveyed. From the images taken from a sky-lift 3D models have been reconstructed by means of

photogrammetry. After re-mixing the piles the same procedure was repeated. The 3D data provides for

the moment only a detailed documentation of the piles.

Details concerning the subsequent sieving campaign are given by Wimmer et al. (2008).

Figure 3. Individual rock piles. Figure 4. Re-mixing of a rock pile.

4


2.2 2D image analysis (WipFrag)

For the generation of fragment nets WipFrag (version 2.6) has been in use. To measure fragment size

distribution the later version (WipFrag, version 2010, build 6) has been used since problems were

encountered with the earlier one in particular when analyzing larger images.

Images have been scaled using the bucket dimensions or from calculated distances of surveyed points

(at about same altitude) sprayed on the piles. A total of 48 images were processed whereas 30 were

carefully manually delineated. Fragments that were impossible to recognize were marked as areas to

be ignored by the sizing algorithm. The automatic image evaluation based on images with 640 x 480

resolution was done by using LKAB`s standard edge detection settings (Lith, 2003 & 2004), see

Appendix 2. Exclusion zones have been drawn before the automatic net generation took place. Any

further processing of the automatically generated nets was intentionally omitted to compare the

outcome of an independently working automatic system with pre-selected parameters with actual

sieving data.

To quantify the results of the WipFrag evaluation its derived percentile sizes (x25, x50, xc, x75 and x90)

were compared with the percentiles from full-scale sieving for the respective sample.

Table 1 provides a summary of the analyzed images. Appendix 3 - Appendix 11 contains all images

analyzed and its manually or automatically generated delineation of fragments.

All fragmentation data both from the sieving and the image analysis is contained in Appendix 12 -

Appendix 17; percentile sizes in Appendix 18; granulometry statistics for the WipFrag evaluation in

Appendix 19 and its definitions summarized in Appendix 20.

Table 1. Summary of analyzed images.

Type of sample Mix Resolution Mode Images

Buckets 0 640 x 480 M / A 6 / 6

Piles

1

640 x 480 M / A 6 / 6

1600 x 1200 M 6

2

640 x 480 M / A 6 / 6

1600 x 1200 M 6

M…manual delineation, A…automatic delineation

5


3 RESULTS

3.1 Manual versus automatic net delineation (640 x 480 resolution)

Figure 5 and Figure 6 plot the deviation of percentile sizes (x25, x50, xc, x75 and x90) derived by

automatic and manual WipFrag analysis of images with resolution 640 x 480 from the sieving data

versus the actual percentile sizes based on sieving in box-and-whisker charts1.

Figure 5. Deviation between percentile sizes automatically analyzed by WipFrag and sieving result vs. pe-centile sizes from sieving, buckets and piles. Data count (24/12/18/15/12/9).

Figure 6. Deviation between percentile sizes manually analyzed by WipFrag and sieving result vs. percen-tile sizes from sieving, buckets and piles. Data count (24/12/18/15/12/9).

1 Explanations regarding Box and Whisker charts: The inner quartiles of each sample are represented by light gray boxes,

separated at the median by a thin line. The height of the gray boxes together makes up the interquartile (IQ) range. The range

of data falling within 1.5 interquartile ranges of the median is represented by whiskers. Any outliers that fall between 1.5 and

3 IQ ranges from the mean are represented by asterisk markers, while any outliers falling beyond 3 IQ ranges from the

median are represented by circular markers. The average of each sample is represented by a diamond marker overlying the

box and whisker for that sample.separated at the median by a thin line. The height of the gray boxes together makes up the

interquartile (IQ) range. The range of data falling within 1.5 interquartile ranges of the median is represented by whiskers.

Any outliers that fall between 1.5 and 3 IQ ranges from the mean are represented by asterisk markers, while any outliers

falling beyond 3 IQ ranges from the median are represented by circular markers. The average of each sample is represented

by a diamond marker overlying the box and whisker for that sample.

-0.4

-0.3

-0.2

-0.1

0

0.1

0.2

0.3

0 - 0.05 0.05 - 0.1 0.1 - 0.2 0.2 - 0.3 0.3 - 0.4 > 0.4

Percentile sizes (sieving), m

Dev

iati

on

(W

ipF

rag

au

tom

ati

c - s

iev

ing

), m

-0.3

-0.2

-0.1

0

0.1

0.2

0.3

0.4

0.5

0 - 0.05 0.05 - 0.1 0.1 - 0.2 0.2 - 0.3 0.3 - 0.4 > 0.4


Dev

iati

on

(W

ipF

rag

ma

nu

al -

sie

vin

g),

m

6


The automatic analysis displays fines that are systematically estimated to be larger, and coarse

material to be finer than is the actual sieved material. Referring to the images in Appendix 5,

Appendix 8 and Appendix 11 this means that small particles are not resolved as individual grains

(fusion) and large fragments are shown as being segmented by the automatic analysis (disintegration).

Deviations in the fines region (0 - 0.1 m) are within the magnitude or even exceed the value of the

actual percentile size of interest. Considering possible segregation effects, Figure 7 depicts the

correlation for analyzed bucket and pile images separately and allows for correction for automatically

analyzed images.

With regard to the manual evaluation shown in Figure 6 the deviations with a maximum of 0.1 m have

a more erratic nature, but generally show a coarser result for the image analysis compared with sieving

data. Deviations from the actual sieved sizes in the fines region arise from the low image resolution

which makes identification of small particles difficult. This result is unsatisfactory if, for instance, one

wishes to measure the percentile x50 reliably from samples which have turned out to be quite fine

grained (actual sieved x50 varies between 14 and 278 mm with a mean value of 87 mm).

Any percentile size with a characteristic fragment size of 0.2 - 0.4 m therefore gives a reliable

estimate. Differences again occurring within the coarse domain might be explained by there being

fewer particles within these size classes. This results in, firstly, an image section which might not be

representative for the entire sample (segregation effects), and, secondly, in the exposure of particles

which might not be representative when compared with a quadratic sieve opening. This is called the

flakiness effect.

Figure 7. Deviation between percentile sizes automatically analyzed by WipFrag and sieving result vs. per-centile sizes from sieving, grouped into buckets and piles.

y = -0.80x + 0.05

R2 = 0.98

y = -0.62x + 0.13

R2 = 0.80

-0.5

-0.4

-0.3

-0.2

-0.1

0

0.1

0.2

0.3

0 0.1 0.2 0.3 0.4 0.5 0.6


Devia

tion

(W

ipF

rag a

uto

mati

c -

sie

vin

g),

m

buckets piles, mix 1+2

7


3.2 Influence of image resolution (640 x 480 vs. 1600 x 1200 resolution)

Increasing the image resolution from 640 x 480 to 1600 x 1200 allows a considerably larger amount of

fragments to be identified in the image, i.e. 2.8 and 3.7 times more identified particles for bucket and

pile images respectively. Processing time – if images are manually delineated as for this comparison –

increases considerably as well. The influence of image resolution on the WipFrag result compared

with the actual sieving data for specific percentile sizes (x25, x50, xc, x75 and x90) is highlighted in

Figure 8. It is apparent that results based on images with higher resolution (1600 x 1200) lead to an

improved result within the fine fractions. The effect measured by the mean deviation from the value

determined by sieving gradually decreases within the individual fractions, i.e.:

0 - 0.05 m: 59.1 %

0.05 - 0.1 m: 48.9 %

0.1 - 0.2 m: 30.5 %

Almost no deviation from the actual sizes is recognizable for fractions 0.2 - 0.3 m if the WipFrag

analysis has been manually carried out on images with high resolution. Deviations occurring at coarser

fractions might be explained by sampling effects (see chapter 3.1).

It should also be noted that considering the statistical value sphericity (Appendix 18) larger image

resolution has a systematic effect of reducing this parameter by 4.7 ± 1.4 %.

Figure 8. Deviation between percentile sizes manually analyzed by WipFrag and sieving result vs. percen-tile sizes from sieving, buckets and piles, image resolution 640 x 480 (gray) and 1600 x 1200 (green). Data

count (24/12/18/15/12/9).

-0.3

-0.2

-0.1

0

0.1

0.2

0.3

0.4

0 - 0.05 0.05 - 0.1 0.1 - 0.2 0.2 - 0.3 0.3 - 0.4 > 0.4

percentile sizes (sieving) [m]

dev

iati

on

(W

ipF

rag

ma

nu

al -

sie

vin

g)

[m]

640 x 480

1600 x 1200

8


3.3 Segregation effects (1600 x 1200 resolution)

Segregation effects are likely to occur during material handling involving images taken from buckets

(after the loading cycle) and piles spread on the surface which have been re-mixed. Other factors may

be: (a) different lighting conditions (underground with artificial light vs. surface with daylight), (b)

approx 4 times larger image sections (buckets 2.7 x 1.7 m and piles Ø 5 m) with more particles being

apparent (2.5 times at 1600 x 1200 and 1.9 times at 640 x 480), (c) autogeneous grinding effects (self-

breakage of large fragments and abrasion between particles).

Figure 9 compares WipFrag results (image resolution 1600 x 1200) with actual sieving data based on

specific percentile sizes (x25, x50, xc, x75 and x90) and categorizes into images based on buckets and

piles (mix 1 and 2). The analysis based on buckets does for a total of 6 samples not necessarily give a

worse result with respect to the average value compared with piles. The data has a wider spread with

increasing sizes, but also compared to the analysis of pile images. Sample 5 constitutes an apparent

example of the problem of hidden coarse particles (cf. Appendix 4 with Appendix 7/Appendix 10).

Larger image section and more particles that are identifiable within the pile images do not

substantially improve the deviation from the actual sizes within the fine fractions. Furthermore, the

errors relating to bucket images appear to be more erratic. If the piles before (mix 1) and after re-

mixing (mix 2) are compared there is a tendency for smaller sizes to be recognized after material

handling.

Figure 9. Deviation between percentile sizes manually analyzed by WipFrag and sieving result vs. per-centile sizes from sieving, image resolution 1600 x 1200, buckets (gray), piles mix 1 (orange) and piles

mix 2 (green). Data count (16/7/7).

-0.3

-0.2

-0.1

0

0.1

0.2

0.3

0.4

0 - 0.15 0.15 - 0.3 > 0.3

percentile sizes (sieving) [m]

dev

iati

on

(W

ipF

rag

man

ual -

sie

vin

g)

[m]

buckets

piles mix 1

piles mix 2

9


4 CONCLUDING REMARKS

These conclusions are based on a comparison of actual fragmentation data with images evaluated

using the granulometry analysis software WipFrag. The input data is summarized as follows:

6 individual samples taken from an SLC draw point at ~7.5 % extraction rate;

Images from buckets (underground) and piles spread and re-mixed (on the surface);

Image resolution 640 x 480 and 1600 x 1200 pixels;

Manual delineation and automatic net delineation using LKAB`s standard parameters.

The automatic analysis based on 640 x 480 resolution and LKAB`s standard edge detection parameters

systematically displays an error which involves the fusion of small grains and the disintegration of

larger fragments. Reasonable correlation curves could have been established for bucket and pile

images which allow correction of automatically analyzed images. However, to link old recordings to

true fragmentation calibration shots using the actual WipFrag camera on-site under real production

conditions would be required to do this.

The edge detection parameters of the new version of WipFrag (Version 2010 Build 6) have been

improved and simplified. In addition, the ability to control the Gaussian blur level which could help

for larger images (depending on the material) has been created. Rapid first-trials using auto edge

detection setting have given better results than if LKAB`s standard parameters had been used to

generate a fragmentation net. Indeed, a test of the latest version of WipFrag is recommended.

The manual evaluation of images with resolution 640 x 480 still shows that calculated deviations for

fines (0 - 0.2 m) could exceed or just be within the same order of the sizes of interest. This is

unsatisfactory if, for instance, one is interested in measuring the percentile x50 reliably from samples

which have turned out to be quite fine grained (actual sieved x50 varies between 14 and 278 mm with a

mean value of 87 mm). The mid-range (0.2 – 0.4 m) gives a reliable estimate though. Differences

within the coarse region might be explained by sampling errors.

The evaluation based on resolution 1600 x 1200 images considerably improved the results within the

fine fractions. Around 2.8 and 3.7 times more particles for bucket and pile images respectively are

identifiable, but the processing time also increases – if images are manually delineated – by some

multiple. The effect measured by the mean deviation from the sizes determined by sieving is gradually

reduced within the individual fractions, i.e.:

0 - 0.05 m: 59.1 %

0.05 - 0.1 m: 48.9 %

0.1 - 0.2 m: 30.5 %

10


Almost no deviation from the actual sieved sizes is recognizable for fractions 0.2 - 0.3 m. Again,

deviations occurring at coarser fractions than that might be explained by sampling errors.

With respect to segregation effects a clear tendency is evident that severe segregation as likely to

occur during the loading process and to be present for the images taken of buckets causes a wider

spread of the measured sizes compared with pile images. This effect increases for large size fractions.

It is also noticeable that the larger image section and more particles identifiable within the pile images

do not substantially improve the problematic deviations from the actual sieved sizes within the fine

fractions. Furthermore, the errors relating to bucket images appear to be more erratic whereas

comparing the piles before (mix 1) and after re-mixing (mix 2) a tendency for these to be smaller sizes

can be recognized after material handling.

11


5 ACKNOWLEDGEMENTS

Hjalmar Lundbohm Research Centre (HLRC) of Luleå University of Technology and endowed by

LKAB is thanked for continuing support within the PhD project “Improved breakage and flow in

sublevel caving”. LKAB is thanked for their support of this project and their practical support on-site.

12


6 REFERENCES

Lith, A. (2003). Study on the usage of WipFrag to describe blasted ore fragmentation in sublevel

caving operations at the Kiruna mine (Unpublished internal report). Kiruna, Sweden: LKAB.

Lith, A. (2004). Prediction of fragmentation for ring blasting in large-scale sublevel caving (Master

thesis). Delft University of Technology, Delft, Netherlands.

Maerz, N.H., Palangio, T.C. & Franklin, J.A. (1996). WipFrag image based granulomatry system. In

B. Mohanty (Ed.), 5th International Symposium on Rock Fragmentation by Blasting, Workshop on

measurement of blast fragmentation (pp. 91-99). Montreal, Canada: Balkema.

Maerz, N.H. & Zhou, W. (1998). Optical digital fragmentation measuring systems – inherent sources

of error. Fragblast - International Journal for Blasting and Fragmentation, 2(4), 415-431.

Ouchterlony, F. (2003). Influence of blasting on the size distribution and properties of muckpile

fragments, a state-of-the-art review. (Report MinFo project P2000-10: Energy optimization during

comminution. Stockholm, Sweden: Swebrec, Swedish Blasting Research Centre at Luleå University of

Technology.

anchidri n, .A., egarra, P., uchterlon , . L pez, L.M. (2 . On the accuracy of fragment

size measurement by image analysis in combination with some distribution functions. Rock Mechanics

and Rock Engineering, 42(1), 95-116.

Wimmer, M., Kangas, J. & Ouchterlony, F. (2008). The fragment size distribution of Kiruna magnetite

loaded from a draw point – Evaluation and analysis of a full-scale test (Swebrec Report 2008:P2).

Luleå, Sweden: Luleå University of Technology.

WipFrag (version 2.6) [Computer software]. North Bay, Canada: WipWare Inc.

WipFrag (version 2010, build 6) [Computer software]. North Bay, Canada: WipWare Inc.

13


7 APPENDICES

Appendix 1. Examples of bucket images taken from the WipFrag system (640x480).

Extraction rate of 3000 tonnes

Extraction rate of 8000 tonnes

14


Appendix 2. Description of edge detection parameters (WipWare 2006).

Edge detection parameters are numerical values used by WipFrag during various stages of fragment

edge detection. The following is a description of the parameters used.

Window size is the length in pixels of the side of a square window used for thresholding. The

image size is 640 x 480 pixels (768 x 574 for PAL versions) and the largest fragment should

measure about 100 - 130 pixels across, about 15 % to 20 % of the image width). Decreasing

the Window size will tend to cause fusion of finer particles, whereas increasing it leads to

breakdown of larger particles and loss of information in shadows.

o LKAB`s standard parameter: 80

Threshold is the difference in intensity (gray tone level, range between a pixel and its window

average). Increasing the threshold results in fewer blocks (some blocks falsely eliminated)

and decreasing the threshold results in more blocks (some falsely identified).

o LKAB`s standard parameter: 2

Valley threshold specifies a minimum level of gray tone slope to trigger. Increasing the

Valley threshold gives fewer blocks (some falsely joined together) and decreasing it produces

more blocks (some of the larger ones disintegrate).

o LKAB`s standard parameter: -0.2

Search length 1, 2 and 3 are the radial search lengths in pixels measured from a given vertex

that the segment operator searches and joins. “ earch length 1” should be greater than

“ earch length 2”, which should be greater than “ earch length 3”. Increasing these

parameters results in more blocks (some falsely identified), whereas decreasing them results

in fewer blocks (some blocks falsely eliminated).

o LKAB`s standard parameters: 28/20/16

15


Appendix 3. Bucket images, 640 x 480, manual delineation.

Sample no 1

Sample no 2

Sample no 3

16


Sample no 4

Sample no 5

Sample no 6

17


Appendix 4. Bucket images, 1600 x 1200, manual delineation.

Sample no 1

Sample no 2

Sample no 3

18


Sample no 4

Sample no 5

Sample no 6

19


Appendix 5. Bucket images, 640 x 480, automatic delineation.

Sample no 1

Sample no 2

Sample no 3

20


Sample no 4

Sample no 5

Sample no 6

21


Appendix 6. Pile images, mix 1, 640 x 480, manual delineation.

Sample no 1

Sample no 2

Sample no 3

22


Sample no 4

Sample no 5

Sample no 6

23



Sample no 1

Sample no 2

Sample no 3

24


Sample no 4

Sample no 5

Sample no 6

25


Appendix 8. Pile images, mix 1, 640 x 480, automatic delineation.

Sample no 1

Sample no 2

Sample no 3

26


Sample no 4

Sample no 5

Sample no 6

27



Sample no 1

Sample no 2

Sample no 3

28


Sample no 4

Sample no 5

Sample no 6

29



Sample no 1

Sample no 2

Sample no 3

30


Sample no 4

Sample no 5

Sample no 6

31


Appendix 11. Pile images, mix 2, 640 x 480, automatic delineation.

Sample no 1

Sample no 2

Sample no 3

32


Sample no 4

Sample no 5

Sample no 6

33


Appendix 12. Fragmentation data, sample 1.

Sieving result

WipFrag evaluation

mesh mm

Buckets Piles

Mix 1 Mix 2

640x480 1600x1200 640x480 640x480 1600x1200 640x480 640x480 1600x1200 640x480

manual automatic manual automatic manual automatic

mesh mm passing % passing %

572 100.0 1000 100.0 100.0 100.0 100.0 100.0

129.9 51.2 500 100.0 100.0 94.2 95.5 95.2 93.0 94.4 100.0

63 34.7 300 93.4 95.0 100.0 75.8 82.0 84.0 81.2 86.0 92.2

40 31.1 150 68.0 77.6 96.0 32.2 50.3 38.5 39.4 53.3 53.7

35 30.3 125 55.8 67.6 93.5 22.2 41.0 25.0 30.6 46.3 38.8

30 28.5 100 40.8 56.3 86.5 12.7 30.7 13.4 17.7 34.7 20.5

25 26.8 75 22.6 41 68.4 5.8 18.8 5.1 7.2 21.7 9.1

20 25.1 50 8.6 22.5 32.5 1.9 6.1 1.8 2.2 9.4 3.1

16 23.7 40 3.5 13.7 18.2 1.2 3.0 0.9 1.4 4.8 1.8

13.2 22.3 37.5 2.3 11.5 14.7 1.0 2.4 0.7 1.2 3.8 1.5

12.5 21.6 35.5 1.5 9.7 12.3 0.9 1.9 0.6 1.0 3.0 1.3

10 19.2 31.5 1.1 6.9 9.3 0.7 1.4 0.5 0.7 2.0 0.9

8 15.7 25 0.5 2.9 5.3 0.4 0.7 0.2 0.3 0.9 0.4

6.3 12.4 16 0.1 0.4 1.7 0.2 0.3 0.3

5 10.7 12.5 0.3 0.8 0.2 0.1 0.2

4 9.2 10 0.2 0.3 0.1 0.1

2 6.3 8 0.1 0.1

1 4.6 6.7 0.1

0.5 3.7 5.6

0.25 2.9 4.75

0.13 2.2 4

0.06 1.4 3.35

2

1.4

1

0.85

0.6

34



Sieving result

WipFrag evaluation

mesh mm

Buckets Piles

Mix 1 Mix 2

640x480 1600x1200 640x480 640x480 1600x1200 640x480 640x480 1600x1200 640x480



660 100.0 1000 100.0 100.0 100.0 100.0 100.0 100.0 100.0

129.9 30.7 500 67.6 69.6 100.0 80.4 84.7 93.9 78.6 80.8 100.0

63 18.1 300 47.5 47.9 96.7 61.9 66.0 76.7 59.3 61.1 82.7

40 16.0 150 26.3 27.9 76.5 24.6 35.6 34.3 27.9 34.7 40.9

35 15.5 125 21.9 23.9 71.7 17.4 29.6 21.0 20.1 27.8 26.8

30 14.5 100 16.4 19.1 62.7 10.1 22.3 12.0 12.0 21.2 13.6

25 13.4 75 10.8 14.0 41.3 4.3 14.4 4.5 4.5 13.6 5.7

20 12.4 50 3.6 7.5 18.7 1.5 5.2 1.7 1.2 5.1 2.3

16 11.5 40 1.8 4.7 11.9 0.9 2.7 1.1 0.7 2.7 1.2

13.2 10.7 37.5 1.6 4.0 10.3 0.8 2.2 0.9 0.6 2.1 1.0

12.5 10.3 35.5 1.3 3.6 9.1 0.7 1.8 0.8 0.5 1.7 0.8

10 9.5 31.5 1.1 2.9 6.9 0.5 1.3 0.6 0.4 1.2 0.6

8 8.4 25 0.8 1.7 4.0 0.2 0.7 0.2 0.2 0.6 0.3

6.3 7.3 16 0.3 0.4 1.5 0.3 0.2

5 6.5 12.5 0.1 0.2 0.8 0.1 0.1

4 6.0 10 0.2 0.3

2 4.1 8 0.1

1 2.8 6.7

0.5 2.1 5.6

0.25 1.6 4.75

0.13 1.2 4

0.06 0.7 3.35

2

1.4

1

0.85

0.6

35



Sieving result

WipFrag evaluation

mesh mm

Buckets Piles

Mix 1 Mix 2

640x480 1600x1200 640x480 640x480 1600x1200 640x480 640x480 1600x1200 640x480



429 100.0 1000 100.0 100.0 100.0

129.9 67.0 500 100.0 100.0 96.4 97.7 97.3 100.0 100.0 100.0

63 48.7 300 70.9 76.5 100.0 74.2 80.7 81.1 80.1 92.4 96.9

40 44.9 150 50.0 60.6 98.0 36.4 53.2 28.1 43.9 68.2 63.3

35 44.1 125 43.5 56.5 95.9 26.1 45.5 17.2 34.5 60.5 45.8

30 41.6 100 39.5 53.3 88.5 13.5 34.5 10.9 24.4 49.8 25.2

25 39.2 75 26.8 43.7 65.0 5.5 20.7 5.2 10.3 38.4 11.9

20 36.7 50 13.4 28.7 30.3 1.7 6.9 1.8 2.9 21.1 4.0

16 34.8 40 7.3 21.0 17.3 0.9 3.2 1.0 1.7 12.4 2.3

13.2 32.8 37.5 5.5 19.0 14.3 0.7 2.4 0.7 1.4 10.1 1.9

12.5 32.3 35.5 4.2 17.3 12.1 0.6 1.9 0.6 1.2 8.4 1.6

10 30.7 31.5 2.5 13.3 9.2 0.5 1.4 0.4 0.9 5.6 1.1

8 28.0 25 0.8 7.4 5.2 0.3 0.8 0.1 0.4 2.2 0.5

6.3 25.2 16 0.4 1.5 1.9 0.1 0.3 0.6

5 23.4 12.5 0.2 0.5 0.9 0.1 0.4

4 21.4 10 0.1 0.4 0.3 0.2

2 15.4 8 0.3 0.1

1 11.0 6.7 0.2

0.5 8.3 5.6 0.1

0.25 6.6 4.75

0.13 5.0 4

0.06 3.0 3.35

2

1.4

1

0.85

0.6

36



Sieving result

WipFrag evaluation

mesh mm

Buckets Piles

Mix 1 Mix 2

640x480 1600x1200 640x480 640x480 1600x1200 640x480 640x480 1600x1200 640x480



330 100.0 1000

129.9 56.9 500 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0

63 35.1 300 89.0 93.7 100.0 81.7 86.2 88.4 89.7 91.1 97.0

40 31.3 150 55.7 65.6 97.4 41.5 59.1 48.8 52.0 63.8 56.1

35 30.5 125 46.6 58.1 92.6 29.5 50.9 32.3 38.1 54.1 39.5

30 28.4 100 35.5 47.6 83.6 16.8 40.2 17.3 25.6 43.3 23.5

25 26.3 75 21.5 30.9 58.5 5.3 27.3 7.2 12.1 31.5 9.6

20 24.2 50 7.6 17.2 26.1 1.9 12.4 2.5 3.4 15.8 3.3

16 22.5 40 3.8 11.4 14.4 1.2 6.9 1.4 1.8 9.5 2.0

13.2 20.9 37.5 3.0 9.9 12.0 1.0 5.6 1.1 1.5 7.9 1.8

12.5 20.3 35.5 2.4 8.7 10.2 0.9 4.6 0.9 1.2 6.7 1.6

10 19.0 31.5 1.7 6.3 7.6 0.6 3.2 0.6 0.9 4.5 1.1

8 16.9 25 0.9 2.8 4.1 0.3 1.5 0.2 0.5 1.8 0.4

6.3 14.6 16 0.4 0.6 1.5 0.5 0.5

5 13.3 12.5 0.2 0.3 0.6 0.2 0.3

4 12.1 10 0.1 0.2 0.2 0.1 0.2

2 8.5 8 0.2

1 5.9 6.7 0.1

0.5 4.6 5.6

0.25 3.7 4.75

0.13 2.9 4

0.06 1.8 3.35

2

1.4

1

0.85

0.6

37



Sieving result

WipFrag evaluation

mesh mm

Buckets Piles

Mix 1 Mix 2

640x480 1600x1200 640x480 640x480 1600x1200 640x480 640x480 1600x1200 640x480



286 100.0 1000 100.0

129.9 85.6 500 100.0 100.0 96.7 100.0

63 67.3 300 100.0 100.0 100.0 90.2 93.7 92.9 100.0 100.0 96.0

40 63.6 150 93.2 98.1 99.2 52.9 70.7 37.6 62.6 79.1 56.5

35 62.8 125 83.3 94.7 96.8 42.0 63.9 25.2 52.1 73.3 40.3

30 59.9 100 75.5 88.2 87.9 24.5 53.2 12.5 40.1 64.7 23.0

25 56.9 75 54.1 73.4 65.4 11.4 35.8 5.6 18.5 51.7 11.1

20 54.0 50 31.8 54.3 32.9 3.1 16.2 2.1 4.2 31.7 4.1

16 51.7 40 19.0 41.4 19.3 1.4 8.4 1.2 2.1 20.1 2.4

13.2 49.3 37.5 15.3 38.0 16.3 1.1 6.6 0.9 1.8 16.9 2.0

12.5 48.7 35.5 12.4 34.9 14.0 0.9 5.3 0.8 1.5 14.4 1.7

10 46.8 31.5 7.7 25.8 10.5 0.6 3.6 0.5 1.1 9.6 1.2

8 43.7 25 2.7 12.9 5.9 0.3 1.6 0.2 0.6 3.6 0.5

6.3 39.9 16 1.0 2.2 2.2 0.1 0.6 0.2 0.8

5 37.2 12.5 0.6 1.0 1.0 0.3 0.1 0.5

4 34.3 10 0.2 0.6 0.3 0.2 0.3

2 25.8 8 0.4 0.1 0.1

1 18.4 6.7 0.3

0.5 14.1 5.6 0.2

0.25 11.2 4.75 0.1

0.13 8.5 4

0.06 5.2 3.35

2

1.4

1

0.85

0.6

38



Sieving result

WipFrag evaluation

mesh mm

Buckets Piles

Mix 1 Mix 2

640x480 1600x1200 640x480 640x480 1600x1200 640x480 640x480 1600x1200 640x480



550 100.0 1000 100.0 100.0 100.0 100.0 100.0

129.9 74.0 500 82.0 88.0 95.7 85.8 90.9 100.0

63 60.4 300 100.0 100.0 100.0 68.1 77.9 78.2 78.4 86.1 94.1

40 56.5 150 64.7 68.9 96.9 36.9 57.0 29.0 50.5 70.1 53.4

35 55.6 125 50.7 58.4 94.3 28.3 50.8 17.7 41.4 62.5 38.4

30 53.0 100 47.3 54.7 90.1 16.1 40.7 9.5 30.5 54.9 21.6

25 50.5 75 33.4 42.0 69.1 6.0 27.7 4.1 15.0 40.9 10.2

20 47.9 50 12.4 23.8 32.9 2.2 11.0 1.5 3.3 21.1 3.7

16 45.9 40 5.5 16.2 18.8 1.2 5.6 0.7 2.0 11.8 2.1

13.2 43.9 37.5 4.0 14.3 15.4 1.0 4.4 0.6 1.9 9.4 1.8

12.5 43.0 35.5 3.0 12.8 12.9 0.8 3.5 0.5 1.7 7.6 1.6

10 40.2 31.5 2.1 10.3 9.9 0.7 2.6 0.3 1.4 4.9 1.1

8 36.9 25 1.0 5.9 5.7 0.4 1.4 0.1 1.0 1.8 0.5

6.3 33.6 16 0.3 1.0 2.0 0.2 0.5 0.6 0.6

5 31.5 12.5 0.3 0.3 0.9 0.3 0.6 0.3

4 29.6 10 0.2 0.2 0.4 0.1 0.5 0.2

2 22.0 8 0.1 0.1 0.1

1 15.6 6.7 0.1 0.1

0.5 11.9 5.6 0.1

0.25 9.5 4.75

0.13 7.2 4

0.06 4.5 3.35

2

1.4

1

0.85

0.6

39


Appendix 18. Percentile sizes (m) for sieving and WipFrag evaluation, all samples.

No

Per-

centile

sizes

(m)

Sieving

Buckets Piles

Mix 1 Mix 2

640x480 1600x1200 640x480 640x480 1600x1200 640x480 640x480 1600x1200 640x480


s 1

x10 0.0045 0.0524 0.0359 0.0324 0.0906 0.0594 0.0904 0.0824 0.0512 0.0778

x25 0.0198 0.0788 0.0530 0.0450 0.1321 0.0877 0.1251 0.1141 0.0816 0.1061

x50 0.1252 0.1154 0.0896 0.0614 0.1938 0.1493 0.1715 0.1799 0.1365 0.1435

xc 0.2388 0.1397 0.1152 0.0712 0.2358 0.1895 0.2015 0.2123 0.1859 0.1666

x75 0.3457 0.1651 0.1432 0.0825 0.2951 0.2464 0.2437 0.2612 0.2297 0.2016

x90 0.4815 0.2671 0.2293 0.1125 0.4324 0.3584 0.3687 0.4490 0.3585 0.2794

s 2

x10 0.0115 0.0720 0.0578 0.0370 0.0998 0.0641 0.0938 0.0937 0.0659 0.0892

x25 0.0996 0.1420 0.1313 0.0579 0.1515 0.1093 0.1336 0.1407 0.1144 0.1216

x50 0.2776 0.3245 0.3147 0.0849 0.2397 0.2190 0.1841 0.2497 0.2345 0.1658

xc 0.3786 0.4313 0.4130 0.1014 0.3200 0.2721 0.2245 0.3209 0.3114 0.1966

x75 0.4688 0.8259 0.8144 0.1403 0.4378 0.4017 0.2796 0.4308 0.4033 0.2417

x90 0.5835 0.9304 0.9258 0.2363 0.7093 0.6607 0.4458 0.7339 0.7134 0.3669

s 3

x10 0.0008 0.0438 0.0282 0.0326 0.0896 0.0571 0.0963 0.0742 0.0374 0.0700

x25 0.0061 0.0721 0.0450 0.0464 0.1228 0.0825 0.1435 0.1014 0.0548 0.0996

x50 0.0679 0.1501 0.0911 0.0638 0.1864 0.1387 0.2001 0.1661 0.1005 0.1303

xc 0.1160 0.1987 0.1657 0.0737 0.2329 0.1838 0.2349 0.2101 0.1325 0.1499

x75 0.2022 0.3272 0.2872 0.0850 0.3053 0.2409 0.2687 0.2659 0.1800 0.1682

x90 0.3383 0.4123 0.3999 0.1051 0.4192 0.3887 0.3765 0.3827 0.2808 0.2266

s 4

x10 0.0028 0.0553 0.0377 0.0353 0.0862 0.0460 0.0827 0.0700 0.0408 0.0763

x25 0.0219 0.0809 0.0638 0.0492 0.1161 0.0710 0.1128 0.0989 0.0647 0.1024

x50 0.1087 0.1336 0.1057 0.0677 0.1687 0.1228 0.1517 0.1466 0.1155 0.1408

xc 0.1591 0.1727 0.1414 0.0793 0.2169 0.1631 0.1768 0.1728 0.1484 0.1605

x75 0.2139 0.2124 0.1886 0.0913 0.2657 0.2287 0.2150 0.2140 0.1931 0.1860

x90 0.2836 0.3055 0.2700 0.1177 0.3501 0.3349 0.3133 0.3028 0.2896 0.2366

s 5

x10 0.0002 0.0334 0.0232 0.0309 0.0711 0.0423 0.0912 0.0632 0.0318 0.0717

x25 0.0019 0.0441 0.0311 0.0447 0.1007 0.0597 0.1247 0.0828 0.0439 0.1029

x50 0.0140 0.0702 0.0464 0.0607 0.1425 0.0954 0.1743 0.1206 0.0725 0.1399

xc 0.0375 0.0857 0.0574 0.0729 0.1766 0.1235 0.1985 0.1516 0.0970 0.1605

x75 0.0911 0.0995 0.0782 0.0853 0.2064 0.1675 0.2237 0.1824 0.1306 0.1886

x90 0.1778 0.1423 0.1070 0.1059 0.2988 0.2604 0.2719 0.2301 0.2027 0.2481

s 6

x10 0.0003 0.0472 0.0311 0.0317 0.0857 0.0485 0.1016 0.0671 0.0381 0.0743

x25 0.0028 0.0650 0.0517 0.0446 0.1183 0.0710 0.1416 0.0911 0.0546 0.1051

x50 0.0240 0.1197 0.0904 0.0613 0.1970 0.1230 0.1972 0.1487 0.0909 0.1442

xc 0.0767 0.1477 0.1380 0.0708 0.2688 0.1823 0.2340 0.1943 0.1272 0.1669

x75 0.1462 0.1660 0.1627 0.0806 0.3432 0.2761 0.2744 0.2603 0.1660 0.1955

x90 0.3885 0.2052 0.2020 0.0998 0.8415 0.5796 0.4220 0.6512 0.4364 0.2596

40


Appendix 19. WipFrag statistics, all samples.2

No Statistics

Buckets Piles

Mix 1 Mix 2

640x480 1600x1200 640x480 640x480 1600x1200 640x480 640x480 1600x1200 640x480


s 1

blocks (-) 176 578 1399 449 1345 852 458 1327 1022

min (m) 0.006 0.003 0.006 0.017 0.007 0.017 0.014 0.006 0.014

max (m) 0.393 0.401 0.264 0.669 0.664 0.700 0.744 0.741 0.595

mean (m) 0.152 0.125 0.077 0.256 0.210 0.230 0.239 0.201 0.182

stdev (m) 0.088 0.088 0.039 0.145 0.146 0.133 0.149 0.150 0.089

mode (m) 0.148 0.148 0.069 0.191 0.191 0.191 0.191 0.191 0.148

sph (-) 0.615 0.578 0.597 0.621 0.583 0.597 0.626 0.598 0.604

s 2

blocks (-) 237 445 888 505 1280 624 523 1205 915

min (m) 0.006 0.003 0.006 0.015 0.006 0.015 0.015 0.006 0.015

max (m) 1.091 1.086 0.450 1.046 1.046 0.739 1.023 1.034 0.553

mean (m) 0.491 0.472 0.124 0.364 0.324 0.255 0.367 0.342 0.219

stdev (m) 0.372 0.371 0.086 0.262 0.263 0.149 0.271 0.273 0.114

mode (m) 0.887 0.887 0.089 0.247 0.247 0.148 0.319 0.319 0.148

sph (-) 0.586 0.573 0.605 0.601 0.576 0.600 0.634 0.596 0.599

s 3

blocks (-) 166 593 1466 369 1340 876 477 1930 1411

min (m) 0.006 0.003 0.006 0.019 0.008 0.019 0.014 0.005 0.014

max (m) 0.476 0.468 0.246 0.606 0.614 0.680 0.496 0.462 0.477

mean (m) 0.217 0.179 0.076 0.251 0.204 0.248 0.220 0.145 0.160

stdev (m) 0.155 0.158 0.035 0.142 0.143 0.123 0.126 0.102 0.075

mode (m) 0.412 0.412 0.069 0.191 0.191 0.247 0.191 0.115 0.148

sph (-) 0.627 0.599 0.595 0.638 0.616 0.604 0.629 0.605 0.613

s 4

blocks (-) 347 829 1200 433 2055 911 533 1847 1067

min (m) 0.006 0.003 0.006 0.016 0.006 0.016 0.014 0.006 0.014

max (m) 0.412 0.422 0.204 0.515 0.505 0.582 0.561 0.547 0.546

mean (m) 0.176 0.149 0.081 0.222 0.179 0.197 0.188 0.158 0.169

stdev (m) 0.101 0.097 0.035 0.114 0.124 0.099 0.100 0.107 0.076

mode (m) 0.319 0.089 0.089 0.148 0.115 0.148 0.148 0.148 0.148

sph (-) 0.598 0.558 0.604 0.626 0.604 0.595 0.650 0.607 0.603

s 5

blocks (-) 127 522 1467 291 1290 968 250 1496 1242

min (m) 0.006 0.003 0.006 0.017 0.007 0.017 0.015 0.006 0.015

max (m) 0.184 0.185 0.175 0.418 0.431 0.787 0.351 0.357 0.542

mean (m) 0.087 0.064 0.074 0.183 0.139 0.216 0.151 0.108 0.171

stdev (m) 0.044 0.038 0.032 0.091 0.093 0.128 0.070 0.074 0.080

mode (m) 0.089 0.032 0.053 0.115 0.089 0.191 0.089 0.053 0.148

sph (-) 0.632 0.592 0.588 0.641 0.628 0.581 0.637 0.609 0.607

s 6

blocks (-) 224 567 1393 371 1680 775 343 1616 1347

min (m) 0.006 0.003 0.006 0.019 0.008 0.019 0.015 0.006 0.015

max (m) 0.336 0.282 0.234 1.095 1.067 0.759 0.859 0.856 0.477

mean (m) 0.136 0.123 0.075 0.340 0.254 0.257 0.260 0.185 0.178

stdev (m) 0.069 0.074 0.036 0.298 0.274 0.136 0.231 0.209 0.086

mode (m) 0.148 0.191 0.069 0.115 0.069 0.191 0.687 0.069 0.148

sph (-) 0.591 0.563 0.600 0.652 0.623 0.596 0.635 0.601 0.594

2 Definition of WipFrag statistics in Appendix 20

41


Appendix 20. Definition of WipFrag statistics.

The following is a definition of some granulometry statistics selected and employed in WipFrag.

xn Nominal diameter, or equivalent diameter, i.e. the diameter of a sphere with the same

volume as that computed for the fragment

x10,x25,… Percentile sizes. x10 is the ten-percentile, for which 10 % by weight of the sample is

finer and 90 % coarser. In terms of sieving, x10 is the size of sieve opening through

which 10 % by weight of the sample would pass.

x50 The median or 50-percentile, the value of xn for which half the sample weight is finer

and half coarser

Blocks Number of net elements detected

Max Maximum size of fragment in the image [xn (m)]

Mean Arithmetic mean (average) fragment size, equal to the sum of all equivalent spherical

diameters divided by the total number of particles [xav (m)]

Min Minimum size of fragment in the image [xn (m)]

Mode Most common sized particle, the geometric mean xn size class interval for the class

containing the greatest number of net elements (fragments) [xn (m)].

Sphericity xn/xs, the ratio of equivalent spherical diameter to the diameter of a circumscribing

sphere (long axis of the fragment)

Stdev Standard deviation of fragment size xav

xc Characteristic size, the intercept of the Rosin-Rammler straight line fitted to the

WipFrag xn data in log-log coordinates. This is equivalent to the x63.2.

xmax GGS characteristic size, the intercept of the 100 % passing and the slope of the GGS

straight line

Report 2007:1 ISSN 1653-5006

Swedish Blasting Research CentreMejerivägen 1, SE-117 43 Stockholm

Luleå University of TechnologySE-971 87 Luleå www.ltu.se

An experimental investigation of blastability

Experimentell bestämning av sprängbarhet

Matthias Wimmer, Swebrec

Universitetstryckeriet, L

uleå

2d image analysis using wipfrag software compared with actual

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