correlation between froth properties and flotation performance
TRANSCRIPT
Process Technology
A Correlation Between Visiofroth™Measurements and the Performance of a
Flotation Cell
Kym Runge, Jaclyn McMaster Michael Wortley, David La RosaOlivier Guyot
Correlation of Visiofroth Parameters with Flotation Cell Performance2 Process Technology
Froth Vision Systems
- Operator often makes decisions based on the appearance of the froth and how it flows
- Vision systems enable us to capture this information quantitatively and use in process control strategies
Correlation of Visiofroth Parameters with Flotation Cell Performance3 Process Technology
VisioFrothTM
• Algorithms calculate froth parameters- Quantify how fast the froth is moving- Evaluate bubble size distribution and
loading- Determine image stability and froth
collapse rates- Quantify the froth colour- Indicate a froth textural change
Correlation of Visiofroth Parameters with Flotation Cell Performance4 Process Technology
VisioFrothTM : Software Display
Correlation of Visiofroth Parameters with Flotation Cell Performance5 Process Technology
VisioFroth/OCS SystemVisioFroth/OCS System
OCSOCS©©
DCSDCSPLCPLC
Correlation of Visiofroth Parameters with Flotation Cell Performance6 Process Technology
Velocity• Modified fourier transform technique calculates the displacement between
two consecutive images • Velocity measured in both the x and y directions• Ability to process 30 frames/second• Commonly measured to assess and control the mass pull rate from a
flotation cell
Parameters Measured by Visiofroth
Correlation of Visiofroth Parameters with Flotation Cell Performance7 Process Technology
Bubble Size Measurement• Watershed techniques used to delineate bubble contours and calculate
bubble surface area• Measured in real time on all frames• The segmented image and bubble size distribution are displayed pictorially
within the software• Ability to tune watershed algorithm parameters• Bubble segmentation affected by camera zoom setting
Parameters Measured by Visiofroth
Correlation of Visiofroth Parameters with Flotation Cell Performance8 Process Technology
Colour and Brightness Descriptors• Visiofroth analyses a segment of the image and calculates the parameters
associated with three different colour models:- RGB Colour Cube- HSV Colour Model- Lab Colour Model
• The average colour descriptors of the image are reported as well as the proportion of pixels within a subset of the colour descriptors.
• Lighting and reflectance off the bubbles affects value of colour descriptors
Parameters Measured by Visiofroth
Colour Model Representations (after Gonalez and Woods, 2002 and Morar et al, 2005)
Correlation of Visiofroth Parameters with Flotation Cell Performance9 Process Technology
Collapse Rate• Relative measure of the rate of bubble coalescence on the
froth surface• Measured as the percentage change in bubble surface area
per frame pair• Related to the size and presence of bubbles• Affected by froth velocity
Parameters Measured by Visiofroth
Correlation of Visiofroth Parameters with Flotation Cell Performance10 Process Technology
Experimental Testwork (AMIRA P9 Campaign)
Rougher Feed Cleaner ScavengerTailing
Rougher ScavengerScavengerTailing
RougherConcentrate
ScavengerConcentrate
CollectorCollectorNASHFrother
• 1st Rougher, 3rd Rougher, 1st Scavenger and 3rd Scavenger cells run at three different air rates and froth depths
• Feed, timed concentrate, tailing and top of froth samples collected at each cell condition
• Five to 15 minutes of froth vision recorded using a JVC hand held camera mounted above each cell
Correlation of Visiofroth Parameters with Flotation Cell Performance11 Process Technology
Metallurgical Assessment of Flotation Cell Performance
1st Rougher
0
10
20
30
40
50
60
20 30 40 50 60
Copper Recovery (%)
Copp
er G
rade
(%)
Top of Froth GradeConcentrate Grade
(a)
3rd Scavenger
05
101520253035
0 5 10 15 20
Copper Recovery (%)
Copp
er G
rade
(%) Top of Froth Grade
Concentrate Grade
(b)
Correlation of Visiofroth Parameters with Flotation Cell Performance12 Process Technology
Metallurgical Assessment of Flotation Cell Performance
0.0
10.0
20.0
30.0
40.0
50.0
0.0 10.0 20.0 30.0 40.0 50.0
Water Flow to Concentrate (%)
Conc
entra
te G
rade
(%)
Rougher 1Rougher 3Scavenger 3Scavenger 1
0.0
10.0
20.0
30.0
40.0
50.0
0.0 20.0 40.0 60.0
Top of Froth Grade (%)
Conc
entra
te G
rade
(%)
Rougher 1Rougher 3Scavenger 3Scavenger 4
Correlation of Visiofroth Parameters with Flotation Cell Performance13 Process Technology
Correlations Associated with Flow
0.05.0
10.015.020.025.030.035.040.045.0
0.0 5.0 10.0 15.0 20.0 25.0
Froth Velocity (cm/sec)
Flow
(TPH
)
SolidsWaterSolids + Water
(a)
0.0
5.0
10.0
15.0
20.0
25.0
30.0
35.0
40.0
0.0 2.0 4.0 6.0 8.0 10.0
Froth Velocity (cm/sec)
Flow
(TPH
)
SolidsWaterSolids + Water
(b)
Rougher 1 Scavenger 3
• Flow best correlated with froth velocity• Relationship not linear
Correlation of Visiofroth Parameters with Flotation Cell Performance14 Process Technology
Correlations Associated with Flow
• Flow versus velocity relationship changesfrom day to day
0.0
5.0
10.0
15.0
20.0
25.0
30.0
35.0
0.0 2.0 4.0 6.0 8.0 10.0 12.0
Froth Velocity (cm/sec)
Flow
(TPH
)
Solids 8/8/2001Solids 9/8/2001Water 8/8/2001Water 9/9/2001
Correlation of Visiofroth Parameters with Flotation Cell Performance15 Process Technology
Process Control Implications
• Appropriate to use froth velocity to control mass pull rate• Froth velocity cannot be used as a measure of mass pull rate
Correlation of Visiofroth Parameters with Flotation Cell Performance16 Process Technology
Correlations Associated with Grade
Rougher 1 – 40.9% Rougher 3 – 25.5%
Scavenger 1 – 13.3% Scavenger 3 – 2.7%
Correlation of Visiofroth Parameters with Flotation Cell Performance17 Process Technology
Correlation Between Grade and Colour Parameters
0.560.6325Lab b
0.420.4725Lab a
0.0680.05825LuminanceLab
0.130.1025Value/Intensity
0.190.3425Saturation
0.640.6325HueHSV
0.380.3925Blue
0.0980.08025Red
0.0240.01725GreenRGB Colour Cube
Top of Froth AssayConcentrate Copper Assay
Correlation Co-efficient (R2)Number ofObservations
ParameterColour Model
Correlation of Visiofroth Parameters with Flotation Cell Performance18 Process Technology
Correlation Between Grade and Colour Parameters
0.020.040.060.080.0
100.0120.0140.0160.0
0.0 10.0 20.0 30.0 40.0 50.0 60.0
Top of Froth Grade (%)
Hue
(deg
rees
)
Rougher 1 Rougher 3 Scavenger 1 Scavenger 3
Correlation of Visiofroth Parameters with Flotation Cell Performance19 Process Technology
Correlations Between Grade and Bubble Size
R2 = 0.7162
R2 = 0.7951
R2 = 0.4779
0.0
5.0
10.0
15.0
20.0
0.0 10.0 20.0 30.0 40.0 50.0 60.0
Copper Grade (%)
Aver
age
Bubb
le S
ize
(cm
)
Con Grade (Zoom 1) (24 observations)Con Grade (Zoom 2) (30 observations)Top of Froth Grade (Zoom 2) (25 observations)
• Grade related to bubble size measured on surface• Relationship better correlated with top of froth grade• Zoom setting affected bubble sizing measurement
Correlation of Visiofroth Parameters with Flotation Cell Performance20 Process Technology
Correlations Between Grade and Collapse Rate
• Grade best correlated with the collapse rate parameter• Relationship better correlated with top of froth grade• Zoom setting didn’t affected collapse rate measurement
R2 = 0.7931
R2 = 0.9088
0.0
2.0
4.0
6.0
8.0
10.0
12.0
14.0
16.0
0.0 10.0 20.0 30.0 40.0 50.0 60.0
Copper Grade (%)
Colla
pse
Rate
(% p
er fr
ame
pair)
Con Grade (Zoom 1 & 2) (58 observations)Top of Froth Grade (Zoom 2) (25 observations)
Correlation of Visiofroth Parameters with Flotation Cell Performance21 Process Technology
Concentrate Grade Prediction
0.0
10.0
20.0
30.0
40.0
50.0
0.0 10.0 20.0 30.0 40.0 50.0
Actual Concentrate Grade (%)
Pred
icte
d Co
ncen
trate
G
rade
(%) Rougher 1
Rougher 3Scavenger 1Scavenger 3
c Velocity b Rate Collapse a
1 a econcentrat ++=
Correlation of Visiofroth Parameters with Flotation Cell Performance22 Process Technology
Process Control Implications
• Concentrate grade and top of froth grade were well correlated with parameters measurable by the Visiofrothsystem
• Potential to use these correlations within a model to optimise bank performance
Correlation of Visiofroth Parameters with Flotation Cell Performance23 Process Technology
Conclusions
• Visiofroth is a system which measures parameters that are correlated to flotation cell performance
• Solids and water flow from a flotation cell are correlated with froth velocity and thus can be used to increase or decrease mass pull rates within a process control strategy
• Top of froth grade was correlated with bubble collapse rate• Concentrate grade was best predicted using both bubble
collapse rate and a velocity term• Potential to use Visiofroth to estimate concentrate purity for
use in a process control strategy • Bubble collapse rate seems to be dependent solely on the
grade of attached particles and not mass loading
Correlation of Visiofroth Parameters with Flotation Cell Performance24 Process Technology
Flotation Process Control in the Future
• Prediction of concentrate grade using froth properties
• Optimise the grade versus recovery relationship in a bank through control of froth velocity and stability
• Model based control - Model developed utilising process
instrumentation- Concentrate grade and recovery
targets established for each bank by a model
- Froth vision systems maintain operation at targeted conditions
Correlation of Visiofroth Parameters with Flotation Cell Performance25 Process Technology
Correlation Between Collapse Rate and Bubble size
• Inverse relationship between bubble size and collapse rate parameter
• Consequence of rapid surface disintegration (Hatfield, 2007)
R2 = 0.8331
R2 = 0.7209
0.02.04.06.08.0
10.012.014.016.0
0.0 5.0 10.0 15.0 20.0 25.0 30.0
Average Bubble Size (cm)
Colla
pse
Rate
(% p
er
fram
e pa
ir)
Zoom 1 (30 observations) Zoom 2 (28 observations)
Correlation of Visiofroth Parameters with Flotation Cell Performance26 Process Technology
Acknowledgements
• Northparkes Metallurgical and technicians who assisted with the test program and reviewed the testwork results (Rick Dunn, Adam Clark, Heather Gaut, Tom Rivet)
• JKMRC and McGill researchers who assisted with the testwork (David Seaman, Eddy Sanwani, Cesar Gomez, Jorge Torrealba, Brigitte Seaman, Marco Vera, Ester Sodenand Michael Rosenfield)
• AMIRA P9 Sponsors for funding the testwork campaign