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Sampling, Sieving, Imaging, &
Correlating the Data Between the Two
Presenters:Kyle James – Verder Scientific Inc.
Gert Beckmann – Retsch Technology
Areas of DiscussionTOPICS
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1.) Sample Acquisition: Sampling Methodology & Techniques
2.) Sieve Analysis: Principles / Techniques / Concerns
3.) Dynamic Image Analysis: Methodology / Technique / Correlation
Quality Control / R&DApplications
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Defined product properties
Detected product properties
Agreement
Certain properties are to be achieved when products are manufactured.These depend on the particle size and the particle distribution.
Particle size/distribution = product property
Particle Sizing ExampleWhy it Matters
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Example: CoffeeThe particle size determines important taste properties
Too coarsely ground coffee: the brewing process is accelerated and gives a watery cup of coffee
Too finely ground coffee: too many aromatics, acids and bittering agents are dissolved, the filter could be blocked
Sample Acquistion
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The bigger the particle size, the more difficult it is to attain the representative part sample
Sampling Process
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Transports(belt,container, train and truck)
Accumulation(filling, feeding)
Sample Amount
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Qmin = 0.07 * dmax / ρ
Qmin = mass of a single sample [dm3]
dmax = maximum particle size [mm]
0.07 = factor [kg/mm]
ρ = bulk density [kg/dm3]
Minimum volume (Qmin) of a single samplewith grain sizes (dmax) < 120 mm
DIN 51701 part 2 - Sampling of solid fuels -
Standard Deviations of Various Sample Divisions Methods
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qualitative variation
Sample divider PT 100
Random sampling
Sample splitter
Cone and quartering
qualitative variation0 1 2 3 4 5 6 7 8 9 10 %
Coning and Quartering
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Stream of material
Single sample
Sample Extractor Chute
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Sample Extractor Bucket
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Stream of material
Single sample
Sample Extractor
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Stream of material
Single sample
Sample Dividers from Retsch
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Sample Splitters
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Rotary Tube Divider PT 200
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Laboratory Sample Divider PT 100
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4 accurate particle size analyses= 4 different results!
Importance of sample divisionSample division
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xc_min [mm]0.5 1.0 1.5 2.0 2.5 3.00
10
20
30
40
50
60
70
80
90
Q3 [%]
randomsampling
sample material: standard sand
*,* = nominal values of standard sand
xc_min [mm]0.5 1.0 1.5 2.0 2.5 3.0 3.50
10
20
30
40
50
60
70
80
90
Q3 [%]
Importance of sample divisionSample division
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sample splitter
sample material: standard sand
*,* = nominal values of standard sand
Importance of sample divisionSample division
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xc_min [mm]0.5 1.0 1.5 2.0 2.5 3.00
10
20
30
40
50
60
70
80
90
Q3 [%]
rotating sample divider
PT 100
4 accurate particle size analyses= 4 similar results!
sample material: standard sand
*,* = nominal values of standard sand
Sieveability of particlesSieving
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Free flowing particles
Van-der-Waals forces
Fluid bridges
Electrostatic Forces
Agglomerated particles
+ -
Sieving aidsSieving
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• Aerosil
• talcum powder
• aluminum oxide
solid
• wet sieving
• degreasing:
benzinealcohols
liquid
• chain rings
• brushes
• cubes
• rubber balls
• agate balls
• steatite balls
mechanical
Test sievesthat comply with standards Test sieves
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If sieve analysis is used for quality controlwithin the context of DIN EN ISO 9000:2000
then both the sieve shaker and thetest sieves must be subjected to
test agent monitoring.
w = mesh widthd = wire diameter
w
w
Ø d
Ø d
Tolerance for mean value (Y):The mean value of the mesh widthmust not differ from thenominal value w by more than thetolerance ± Y.
Technical requirements & testingaccording to ISO 3310
100 200 300 40040 50 60 70 80 90particle size x[µm]
10
20
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50
60
70
80
90
Q3 [%]
10
20
30
40
50
60
70
80
90
Q3 [%]
44%
+Y 66,4
36%
-Y 59,6
Importance of mesh widthConsequences of tolerances Test sieves
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63 µmtolerance ± Y = 3,4 µm
40%
Real Mesh WidthReal Mesh
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x [µm] 200 400 600 800 1000 1200 0
10
20
30
40
50
60
70
80
90 Passing [%]
Sample-1__xc_min_002.rdf Sieving-upper-range-S1.ref
Excellent correlation
when using the real mesh opening sizes
Influence of Mesh WidthMesh measurements
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1400µm 1400µm 1429.5µm
Nominal Sieve Mesh = 1400µm Real Sieve Mesh >1400=1455
only beads < 1400µm
will pass the sieve mesh
beads > 1400µm will not pass the sieve mesh
Upper mesh size range ~1455µmsieve No. 03033531 (nominal 1400µm)
Theory: Reality:
Mesh sizes warp Mesh sizes weft
Calibrationcertificate
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Nomial mesh width
Tolerances
Number ofmeasured apertures
Mean mesh width
Standard deviation σ
Wire diameter
Sample AmountSieve Analysis
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4 mm2 mm1 mm
500 µm250 µm125 µm
63 µm45 µm
collecting pan
Sieving Methods forparticle size determination Basics
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Horizontal sievingVibratory sieving Air jet sievingTap sieving
dry wet
vibratory
horizontal
tap
air jet
AS 200 jet AS 200 tap AS 200 AS 300 AS 400 AS 450 control
Selection of amplitudeVibratory sieve shakers
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0
10
20
30
40
50
60
70
80
90
100
Q3(
x) /
%
10 50 100 500 1000 5000Particle size / µm
Quartz,sieving time: 5 min.
AMP- 2 mmAMP- 0.5 mmAMP- 1.2 mm
Statistical resonanceVibratory sieve shakers
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T = periodic time of sieve bottom vibration
particle
sieve bottom
t
A
T T
Sieve analysis procedureProcess
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Potential Concerns & IssuesSampling & Sieving
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1.) Sampling problems:Sampling Technique (pouring and “spooning“)Material Behavior & Composition
2.) Sieving problems: Sieve OverloadSieving Technique / Technology UsedNominal Size Real Mesh SizeMaterial Behavior & Composition
3.) Scale Problems:Low Resolution (0.1g of sample)Not Sensitive Enough (sieves vs actual)
Digital Imaging SievingImage Analysis
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x [µm]200 400 600 8000
10
20
30
40
50
60
70
80
90
Q3 [%]
RT669_3993_Z_LB_05%_xc_min_001.rdfRT669_RT_3993.ref
Particle SizeMorphology
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xcmin
xc min
“width”
A
A‘ = Ax a
rea
“diameter overprojection surface”
xarea“length”
xFe max
xFemax
CAMSIZER results are
compatible with
sieve analysis
Digital Image ProcessingComparison
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x [mm]0.1 10
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
Q3
Tinovetin-B-CA584A_BZ_xc_min_002.rdfSyngenta-1mm-2min-Sieb.ref
--- width measurement
-*- Sieving
comparisonCAMSIZER-measurement xc min (red)and sieving * (black)
xc min
Ellipsoid ParticlesComparison
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x [mm]1.0 1.25 1.5 1.75 2.00
10
20
30
40
50
60
70
80
Q3 [%]
rice
xcmin
A‘ = A
x are
a
A
Red CAMSIZER curve of particle width gives excellent correlation
at the black sieve points
Lenticular ParticlesComparison
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x [mm]0.2 0.4 0.6 10
10
20
30
40
50
60
70
80
Q3 [%]
Sample A_BZ_0.2%_xc_min_001.rdfSample A_.ref
Digital Imaging SievingLenticular Particles
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x [mm]0.2 0.4 0.6 10
10
20
30
40
50
60
70
80
Q3 [%]
Sample A_BZ_0.2%_xc_min_001.rdfSample A_.ref
Digital Imaging SievingCubes / Angular
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x [µm]200 400 600 8000
10
20
30
40
50
60
70
80
90
Q3 [%]
RT669_3993_Z_LB_05%_xc_min_001.rdfRT669_RT_3993.ref
Angular ParticlesCoal, Sand, Sugar
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x [µm]200 400 600 8000
10
20
30
40
50
60
70
80
90
Q3 [%]
RT669_3993_Z_LB_05%_xc_min_001.rdfRT669_RT_3993.ref
Angular ParticlesShell Limestone
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xc_min [mm]0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 1.80
10
20
30
40
50
60
70
80
90
Q3 [%]
Muschelkalk_xc_min_001.rdfRT3204_Muschelkalk_Sieb.ref
*Sieve Analysis -CAMSIZER
Digital Imaging SievingAngular
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x [µm]200 400 600 8000
10
20
30
40
50
60
70
80
90
Q3 [%]
RT669_3993_Z_LB_05%_xc_min_001.rdfRT669_RT_3993.ref
x [µm]200 400 600 8000
10
20
30
40
50
60
70
80
90
Q3 [%]
RT669_3993_Z_LB_05%_xc_min_001.rdfRT669_RT_3993.ref
angular particles without fitting
CAMSIZER-measurement xc min (red)sieve analysis * (black)
angular particles with Q3-fitting
Digital Imaging SievingDistribution
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Two samples with different width of distributionbut …
… with similar shape
(= same product type)
Limitations of Old ProceduresOld vs New
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xc_min [mm]1.0 1.5 2.0 2.5 3.00
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
Q3
CAMSIZER Elementary – Fittingxc_min [mm]1.0 1.5 2.0 2.5 3.0
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
Q3
xc_min [mm]1.0 1.5 2.0 2.5 3.00
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
Q3
Old fittingmethods
Digital Imaging SievingElementary Fitting
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Single class:Taken from the sieve stackand measured in CAMSIZER
For creating a CAMSIZER Elementary
fitting file use the more narrow sample
(green)
Elementary fitting with single (narrow) sieve class.It can be the sieve with the highest amount, one above or one below
Digital Imaging SievingElementary Fitting
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xc_min [mm]1.0 1.5 2.0 2.5 3.00
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
Q3
Elementary - Fitting
New elementary fitting with single (narrow) sieve class and entire distribution
{
Measurement of Single ClassSingle Size
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xc_min [mm]1.0 1.5 2.0 2.5 3.0 3.50
10
20
30
40
50
60
70
80
Q3 [%]
Try to geta single sieve class
as narrow as possiblein the middle
of the distributionof the sample
Elementary Fitting in PracticeSet-up
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Elementary Fitting in PracticeSet-up
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Try to get a singlesieve class as narrowas possible ~ in the
middle of thedistribution of the
sample
Try to get a sample ofyour product as
narrow as possible
Try to get a sample ofyour product as
narrow as possible
Try to get a single sieve classas narrow as possible
in the middle of the distributionof the sample
Elementary Fitting in PracticeSet-up
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Shell LimestoneExample
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xc_min [mm]0.4 0.6 0.8 1.0 1.2 1.40
10
20
30
40
50
60
70
80
90
Q3 [%]
Muschelkalk_xc_min_001.rdfRT3204_Muschelkalk_Sieb.ref
Multimodal DistributionExample
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x [mm]0.2 0.4 0.6 0.8 1.0 1.2 1.40
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40
50
60
70
80
90
Q3 [%]
SU_Demo02-05_Standaard_BZ_LB_Gl15_03%_xc_min_001.rdfStandaard.ref
x [mm]0.2 0.4 0.6 0.8 1.0 1.20
10
20
30
40
50
60
70
80
90
Q3 [%]
SU_Demo02-05_Mix_BZ_LB_Gl15_03%_xc_min_001.rdfMix-Opzak-and-stMG4502.ref
Excellent sievecorrelation evenwith bimodal or
multimodal distributions
SummaryCorrelation Wrap-Up
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CAMSIZER® Elementary Fitting:• For samples with similar shape• Fitting of different width of distribution possible
(even multimodal distributions)• Applications: Sand, Sugar, Fertilizer, Minerals, Plastics,
Foodstuffs ... and many more• Creating a CAMSIZER® correlation method
only takes 20 minutescompared to 3 hours with competitive instruments
Samples with varying particle shape, e.g. abrasiveswill need different fitting files or CAMSIZER Meta-Fitting®
Thank you for yourattention !
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