ball mill control [compatibility mode]
TRANSCRIPT
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Slegten grinding course 1
Grinding Circuit Control Systems
“In the name of Allah, the Beneficent, the Merciful”
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Slegten grinding course 2
1. Why a control / What to control
2. Available Tools
3. Control Strategies
Summary
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Slegten grinding course 3
• Optimum Production Rate• Consistent Quality• Smooth Operation• Quick Mill Stabilization (disturbance)
(quality change)• Operator relief
1. Why a Control Systems
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Slegten grinding course 4
FOR THE OPTIMUM EQUIPMENT EFFICIENCY
Reject FlowFinish product
Feed rate
Ratio material/airsteady
Material flowsteady
Material levelsteady
Total mill flowsteady
Ratio fines/rejectssteady
Reject flowsteady
What to control ?
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Slegten grinding course 5
• Functional layout• Controller objective• Controller ON-OFF• Controller P.I.D. • Expert system
2. Available Tools
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Slegten grinding course 6
Setpoints
ControlledQuantities
ManipulatedQuantities
Disturbances
PROCESS
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Slegten grinding course 7
PROCESS
Manual Control
ControlledQuantities
ManipulatedQuantities
Disturbances
PROCESS
Feedback Control
Hardware
Actions Needed
MeasuredValues
Setpoints
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Slegten grinding course 8
finalcontrolelement
transmissionsystem
transmissionsystem
feedbackcontroller
ControlledMan
ipul
ated
Disturbances
sensor
errorsignal
inputelements -
+SetpointsPROCESS
Controllerbox On site
Functional Layout of a Feedback Loop
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Slegten grinding course 9
Setpoint
Setpoint
Setpoint
Time
Time
Time
Controlled variable:reject flow rate , p.e.
Manipulated variable:feed rate , p.e.
Ideal
Reality
1. stay on the setpoint2. track a setpoint change
Controllers Objectives
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Slegten grinding course 10
Dead Zone
Setpoint
On
Off
Fuel valve
Time
Controlled variable:room temperature
Manipulated variable:
quickly changes to either a maximum ora minimum value (minimum = 0 or off).
Mechanism = usually a simple relay
Discontinuous control
Controllers : On - Off
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Slegten grinding course 11
K EE c
K ce m
Control algorithm: m = K ec
K = proportional sensitivity or gain
C 1/K X100 = proportional band (PB)
+
-
Rapid responseDynamicaly relatively stable
Offset
E = errorm= Manipulated variable
C
Controllers : Proportional
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Slegten grinding course 12
Equilibrium
Steam
Undercharge
1
2
3
4
Steam
Integral action
Setpoint
Time
OffsetChargeapplication
Rotationalspeed
Offset
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Slegten grinding course 13
E1
T pi
ET
t
i
e m
Control algorithm: m = 1/T e dti
Ti = integral timep = action of integration with respect to time (dt)
+
-
Combines advantages of proportionaland the reset of the offset
Tuning difficulty increasedLess stable
m= Manipulated variable
P+I:e=error
Controllers : Integral
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Slegten grinding course 14
E T pd
E Td d
e m
Control algorithm: m = T d/dt (e)d
Td = derivative timep = action of derivation with respect to time (dt)
+
-
If extensive lagMore stable if well tuned
Tuning difficulty increasedReduced but not eliminated offset,
m= Manipulated variable
P+D:
e=error
D: Not alone in practice, because huge errorIf unchanging error rate
Adds lead to the controller for lag around the loopIt's based on the rate of change of e
Controllers : Derivative
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Slegten grinding course 15
On -Off:InexpensiveExtremely simple
P:SimpleInherently stable when properly tunedEasy to tuneExperiences offset at steady state
P + D:Stable Less offset than proportional alone
(use of higher Kc possible)Reduces lags, i.e. more rapid response
P + I + D:Most complexMost expensiveRapid responseNo offsetDifficult to tuneBest control if properly tuned
P+ I:No offsetBetter dynamic response than reset alonePossibilities exist for instability due to lag
introduced
P+I+D: the most sophisticated
Characteristics of controller algorithms
Controllers : P I D
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Slegten grinding course 16
• Rule-based• Combines several methods, and tries to emulate human
responses to given conditions• Based on a decision table, which gives each possible
combination of conditions which could occur for x number of measured parameters
• Although these systems are becoming more and more common, it must be remembered that a considerable amount of study and tuning is required to get the program right.The programmer must, in essence, teach the computerto operate the mill
• The current restriction on these systems is that they act only on one parameter at a time.
Expert Systems
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Slegten grinding course 17
• HOME MADE SOLUTIONS
• COMMERCIALIZED SOLUTIONS :
3. Control Strategies
- HOLDERBANK (Canada)- SCAP- MILLTRONICS- K-TRON/HASLER- GO CONTROL
• Elevator Control• Ear Control• Reject Flow Control by Fresh Feed• Total Feed Control• Reject Flow Control by Separator Speed
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Slegten grinding course 18
• SIGNAL USED FOR CONTROL
Strategies
- MILL MOTOR POWER- MILL SOUND (1st OR / AND 2nd COMPARTMENT)- ELEVATOR POWER- REJECT FLOW- SEPARATOR SPEED- (FINISH PRODUCT FINENESS)
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Slegten grinding course 19
Finish product
Separator speed
Reject
Fresh feedP.I.
Fresh Feed Control by Elevator
Elevator
Set Point+ -
- High Lag time
- Poor Signal from Elevator
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Slegten grinding course 20
Finish product
Separator speed
Reject
Fresh feedP.I.
Fresh Feed Control by Ear Signal
Sound
Set Point+ -
- Uneven Mill Flow
EAR
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Slegten grinding course 21
Finish product
Separator speed
Reject
Fresh feedP.I.
Reject Flow Control by Fresh Feed
- Long lag time
- No detection of build up in mill
-+
Total feed
Set Point
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Slegten grinding course 22
Finish product
Separator Speed
Reject
Fresh feed
P.I.Reject setpoint
-+
++
Total Flow Control by Fresh Feed
- Long lag time
- Material build up not detected
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Slegten grinding course 23
Finish product
Separator speed
Reject
Fresh feed
P.I.Reject
setpoint -+
Reject Control by Separator Speed
- Not suitable with uneven clinker
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Slegten grinding course 24
SCAP Strategy
DependentLoop
DependentLoop
MasterLoop
Process
Filling Degree
Elevator Power
Mill Power
Feed
FillingDegreeSet Point
FeedElevatorPowerSet Point
STRATEGY : Maximize Feed Rate and Mill Power
Commercialized solutions
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Slegten grinding course 25
Milltronics Strategy
k + k + k = 100 %
k %
k %
k %
P I D
1
2
3
ear
reject
elevator
power
Set Point
Feed+
+ +
1 2 3
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Slegten grinding course 26
HOLDERBANK (MISSISAUGA)Mill Load Control Strategy
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Slegten grinding course 27
Mill Load Control Strategy
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Slegten grinding course 28
K-TRON / HASLER Control Strategy
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Slegten grinding course 29
100(elev)PB
2(ear)Full(ear)Empty
(ear)level_Full Ear
*+
Pid-1 :Fresh regulation set point = Fresh set point + F (pid) (Mill set point Mill flow)
« Grits/fresh » Fresh SetpointMill set point = Fresh set point (1 + Grits/fresh)Mill flow = SFresh + Grits
If full mill : Ear < Full level (ear)Ear P 3
Elevator Then :Mill Setpoint
Mill set-point =
Mill Flow =GritsFreshΣ+ PID 1 Fresh regulation set point
Mill set-point (1 +
% WF 1 % WF2If full mill : elev > full level (elev)
Then :
WF 1 WF 2 Mill set point =
Mill regulation Mill set point (1 +
100PB(elev)
2(elev)Full(elev)Empty
Elev(elev)levelEmpty_
*+
-
K-TRON / HASLER Control Strategy
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Slegten grinding course 30
Slegten Multivariable and Fineness Control
Fineness SP
Prediction
LaboratorySampling
Separator
Speed
Finish product
Mill
Reject
Feed rate
Finish product
Reject
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Slegten grinding course 31
Regardless of the control system, the grinding will still be done in the mill, andthe mill should be optimized to be both
effective and efficient
Conclusions