Ball Mill Control [Compatibility Mode]

Slegten grinding course 1

Grinding Circuit Control Systems

“In the name of Allah, the Beneficent, the Merciful”


1. Why a control / What to control

2. Available Tools

3. Control Strategies

Summary


• Optimum Production Rate• Consistent Quality• Smooth Operation• Quick Mill Stabilization (disturbance)

(quality change)• Operator relief

1. Why a Control Systems


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 ?


• Functional layout• Controller objective• Controller ON-OFF• Controller P.I.D. • Expert system

2. Available Tools


Setpoints

ControlledQuantities

ManipulatedQuantities

Disturbances

PROCESS


PROCESS

Manual Control

ControlledQuantities

ManipulatedQuantities

Disturbances

PROCESS

Feedback Control

Hardware

Actions Needed

MeasuredValues

Setpoints


finalcontrolelement

transmissionsystem

transmissionsystem

feedbackcontroller

ControlledMan

ipul

ated

Disturbances

sensor

errorsignal

inputelements -

+SetpointsPROCESS

Controllerbox On site

Functional Layout of a Feedback Loop


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


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


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


Equilibrium

Steam

Undercharge

1

2

3

4

Steam

Integral action

Setpoint

Time

OffsetChargeapplication

Rotationalspeed

Offset


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


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


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


• 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


• 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


• SIGNAL USED FOR CONTROL

Strategies

- MILL MOTOR POWER- MILL SOUND (1st OR / AND 2nd COMPARTMENT)- ELEVATOR POWER- REJECT FLOW- SEPARATOR SPEED- (FINISH PRODUCT FINENESS)


Finish product

Separator speed

Reject

Fresh feedP.I.

Fresh Feed Control by Elevator

Elevator

Set Point+ -

- High Lag time

- Poor Signal from Elevator


Finish product

Separator speed

Reject

Fresh feedP.I.

Fresh Feed Control by Ear Signal

Sound

Set Point+ -

- Uneven Mill Flow

EAR


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


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


Finish product

Separator speed

Reject

Fresh feed

P.I.Reject

setpoint -+

Reject Control by Separator Speed

- Not suitable with uneven clinker


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


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


HOLDERBANK (MISSISAUGA)Mill Load Control Strategy


Mill Load Control Strategy


K-TRON / HASLER Control Strategy


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


Slegten Multivariable and Fineness Control

Fineness SP

Prediction

LaboratorySampling

Separator

Speed

Finish product

Mill

Reject

Feed rate

Finish product

Reject


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

Ball Mill Control [Compatibility Mode]

Documents

Transcript of Ball Mill Control [Compatibility Mode]