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7/30/2019 AVANCE EN EL CONTROL EN CELDAS DE FLOTACION.pdf
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Advanced Process Control of aFroth Flotation Circuit
October 23, 2008
Dr. Sebastian GaulocherDr. Eduardo GallesteyABB Switzerland Ltd.
Henrik Lindvall
2008 ABB Switzerland Ltd, Corporate Research, CH-RD.C1
Boliden Mineral AB, Sweden
7/30/2019 AVANCE EN EL CONTROL EN CELDAS DE FLOTACION.pdf
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2
What material is this coin made of?
A riddle to make you awake
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copper
zinc
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3Zinc is omnipresent
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4Production and price of zinc
Zinc mines in the world Artists view of mining
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Total annual production:
10 million tons (2006)
Zinc price is skyrocketing(Annaberger Bergaltar)
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5
Flotation: unit operation at the heart of mineral processing
What is flotation?
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6Explanation of the Flotation Process
Objective:separation of valuable minerals and gangue
Ore is
extracted from the mine
ground in a mill, and
mixed with water and chemical rea ents
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(activator, collector, and depressant).
Pulp flow in which
desired mineral particles are
hydrophobic gangue particles are hydrophilic
Reagent addition
Semi-autogenous mill
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7Explanation of the Flotation Process
In a flotation cell,
a feed port provides incoming pulp,
an impeller mixes the pulp,
air is blown into the cell and dispersed,
hydrophobic particles attach to the air
air bubbles float and form froth on the
concentrate
feed
air
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surface
Separation between
hydrophobic (desired mineral) and
hydrophilic (gangue) particles
into concentrate (froth) and tailings (pulp)
airbubble
Hydrophobicparticles
buoyancy
Flotation of mine-
ral particles
Sketch of a flotation cell
tailings
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Flotation cell
Several flotation cells form a flotation bank
Several flotation banks form a flotation circuit
Explanation of the Flotation Process
conc.
tail.feed
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Several flotation circuits form a concentrator
Cu-Pbflotation
Cuflotation
Znflotation
Cu conc.
Pb conc.
Zn conc.
gangue
ore
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9Manipulated and measured variables of a circuit
FA301 FA302 FA303 FA304 FA305
tailingsfeed
FT
FT
AT
AT
AT
AT
BL031
Legend:
recirculating flow
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FA101FA104 FA103 FA102
concentrate
hydro-cyclone
regrindingmill
FTATAT
AT
AT
FT
X-ray analyzer
volume flow meter
air addition
froth level change
reagent addition
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10Where are we and where do we want to go?
State of the art Manual control, intricate due to
intricate dynamics (e.g. recirculating flows),
frequent feed variations (quantity and quality), and
operator shift changes
No circuit-wide automatic controlat present
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Objectives Maximizationof plant output
Observanceof minimum concentrate grade
Reductionof chemical reagent use Preventionof costly unplanned plant stops by respecting operating
range of plant
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11Expert Optimizer ABB Standard platform for APC
Features: General Calculations
Arithmetic, Boolean
Fuzzy Logic Human reasoning
Neural Networks
Soft sensors
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Model Predictive Control (Piecewise) Linear
Hybrid systems
Non-linear (Modelica)
Web Based HMIs Highly Configurable
Drag and Drop
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12General set-up of estimation and control
process
Sensors
Signal processing
State estimates
Estimation of process state variables
(MHE, moving horizon estimation)
Measurements
on
tro
lp
latfor
m
Parameter
Requiresolving an
rcommun
icat
ion
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Flotat
io
Actua
tors
Computation of optimal set-points
(MPC, model predictive control)
Postprocessing of set-points
Set-points
ABB800xA
c
es ma on
problem
OPC
pro
toco
lf
Done in Expert Optimizer
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The process model is:
Mechanistic (first principles)
Mass and volume balances
Pulp-to-froth transfer model
Variables: volumes and volumeflows of relevant fractions
Linearised first-principle approach
Component model
MLD Fl. cell
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near ze a out an operat ng po nt Formulated in discrete time
Generic and modular (component-wise):
flotation cell, mixing tank, analyzers, volume flow meters,
Easily understandable, maintainable,adaptable, and reusable
Component library
Circuit assembly inExpert Optimizer
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14Linearised first-principle approach
Model predictive control (MPC):
Optimization variables:
Air rates
Collector addition
Objectives:
Minimize tailings flow
Guarantee minimum concentrate grade
click on picture to enlarge
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Moving horizon estimation (MHE):
Optimization variables:
Dynamic states (cell and tank contents)
External disturbances (feed, water)
Objective:
Find a compromise between pastmeasurements and the process model inorder to obtain the optimal estimates forplant states and disturbances
click on picture to enlarge
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15Pilot Plant and Results
Development of control strategy in a cooperationbetween
ABB (Switzerland and Sweden) and
Boliden Minerals AB, Garpenberg Concentrator (Sweden) Application of control strategy to an industrial plant
(zinc flotation circuit as shown in flow sheet)
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on ro er s curren y e ng ong- erm es ewith encouraging results so far:
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Method for handling disturbances and forecast changes
Main ingredients are
Plant model
Objective functional
Model predicts system
Model Predictive Control
past future
controlled
variable
manipulatedvariable
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into the future
Requires solution of
optimization problem at
every sampling time
t t+ t+m t+p
t+1t+2
t+1+m t+1+p
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18Linearised first-principle approach
Assembly of flotation circuit for model predictive control:
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19Linearised first-principle approach
Assembly of flotation circuit for moving horizon estimation:
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20Mixed Logical Dynamical System (MLD)
Developed at Federal Institute of Technology Zrich(ETH Zrich), Switzerland
Framework for handling both real-valued and boolean-
valued variables (hybrid system) Can describes plant constraints, interconnections and
the objective function
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54132
321
321
)()()()(
)()()()()(
)()()()()1(
EtxEtuEtzEtE
tzDtDtuDtCxty
tzBtBtuBtAxtx
+++
+++=
+++=+
x ens on o c ass ca s a e-space approac re ox
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21Flotation Cell
Mechanistic model of a flotation cell
Three inputs: feed, froth level, and air
Two outputs: concentrate and tailings
Volume balance in the cell:
vol[k+1] = vol[k] + T( feed[k] tail[k] conc[k] )
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22Flow sheet of a froth flotation circuit
FA301 FA302 FA303 FA304 FA305
tailingsfeed
FT
FT
AT
AT
AT
AT
BL031
Legend:
recirculating flow
2008ABBSw
itzerland
Ltd
FA101FA104 FA103 FA102
concentrate
hydro-cyclone
regrindingmill
FTATAT
AT
AT
FT
X-ray analyzer
volume flow meter
air addition
froth level change
reagent addition
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23Feed grade variation
Zincgrade
Solidfraction
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Day time (Mar 3, 2008) Day time (Feb 27, 2008)