Marcelo Gontijo
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Transcript of Marcelo Gontijo
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Advanced control of crushing and
autogenous grinding circuits using
image analysis
CEMI Process Technology and Engineering
Minas Gerais, Brazil
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Objectives
Demonstrate tools applicability for advanced
process control and online particle size image
analysis in crushing and autogenous grinding
c rcu ts
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Advanced Process Control (APC)
PLC/DCS
APC
Control Room
OperatorProcess
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Differentiation
Manual Control Regulatory Control Advanced Control
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Manual Control
High variability;
Process operated far from ideal economic point.
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Regulatory Control
Low variability
Process operated far from ideal economic point.
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Advanced Control
Low variability
Process operated close to ideal economic point.
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Advanced Control Techniques
Expert System/Fuzzy Logic;
MPC (Model Predictive Control);
eura etwor .
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Advantages: Expert System/Fuzzy Logic
Avoid difficulties obtaining a trustable model
(MPC) or trustable data (Neural Network);
Easy to deal with data from online sampling
analysers and laboratory analysis;
Easy to track/debug system actions.
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Vision Systems
There are systems that use image analysis to infer
ore size distribution curve, an important
measurement for crushing and autogenous
grinding process.
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Up To Date Vision Systems Features
OPC communication, allowing easy interface with
PLC, DCS, PIMS and APC systems;
IP Network Cameras;
Multiple cameras processing simultaneously;
Led Lighting.
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Hardware
Network HD Camera
with remote zoom
and focus and IP 66protection
Led lighting has a
lifetime of more than
50000 hours and lowenergy consumption
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Hardware
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Architeture
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Vale Mutuca Flowsheet
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Crushing Controlled Variables
BR-02/BR-03 Chamber level;
BR-02/BR-03 Power;
BR-02/BR-03 Vibration;
BR-02/BR-03 Product Size Distribution (available
from Vision System);
TC-04 (Circulation Load) Mass flow rate.
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Crushing Manipulated Variables
TC-03 (Fresh Feed) Mass Flow Rate;
BR-02/BR-03 Opening/Closing teeth.
Variables to define how and when to act in each
Manipulated Variable.
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Crushing Results
Project at Vale Mutuca is still in progress, a similar
application was performed in 2008 at RPM/Kinross
Gold Corporation in Paracatu, Minas Gerais, Brazil.
Feed particle size (F80) reduced from 13mm to
11.2mm, representing an increase of 100.000
tons/year, payback in 6 months.
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SAG/AG Grinding Flowsheet
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SAG/AG Grinding Controlled Variables
TC-01 Product Size Distribution (available from
Vision System);
AL-01/AL-02/AL-03 Product Size Distribution
(available from Vision System).
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SAG/AG Grinding Manipulated Variables
AL-01/AL-02/AL-03 Feeders speed
Due to the effect of particle segregation, feeders
under the extremes of stock pile are supposed to
operate with coarser material compared to central
feeder.
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SAG/AG Grinding
AL-02 (Feeder under pile center) has
speed increased and AL-03 (Feeder
under pile extreme) is stopped.
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SAG/AG Grinding
TC-01 Vision System detects increase in fines
amount and reduction in coarse fraction.
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SAG/AG Grinding
SAG noise increased, confirming
that material became finer.
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Conclusion
The use of image analysis tool combined with
expert fuzzy logic system are suitable to crushingand autogenous grinding circuits.
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Conclusion
The expected improvements are:
Capacity optimization of ore processing;
Process stability;
Increase average production;
Increase efficiency of the circuit.