Matti Aula

Matti Aula, Mikko Jokinen, Luxmet Oy, Finland Paavo Hooli, Sapotech Oy, Finland Timo Fabritius, Juha Roininen, University of Oulu, Finland Kimmo Vallo, Outokumpu Stainless Oy, Finland

Why OES measurements beats conventional methods in control of EAF

11th European Steelmaking Conference & Expo, Venice

Matti Aula

Control of EAF

• The main source of performance fluctuations in EAF process is the scrap used as a raw material

• Composition and size of the scrap varies significantly heat by heat

• Despite fluctuations caused by scrap, many EAFs are still operated with static control

• If changes are made to the process practice, those mainly rely on the expertise of the furnace operator

Matti Aula

Conventional measurement methods Conventional measurements used to analyze process:

− temperature behavior of the cooling water of the side panels

− electrode positions − off-gas temperature

Phenomenon Controlled variables

Control signals

Slag foaming Carbon and oxygen injection

Off-gas CO/CO2 ratio

Electrode regulation

Electrode position Electrical parameters

EAF voltage flicker

Electrical parameters

Electrical parameters

Scrap melting Arc length/ carbon injection

Electrode position, Optical emission spectrum, Cooling water temperature gradient

Burners Burner power Electrode THD

Examples of dynamic EAF control applications.

Schematic picture of positioning of conventional measurements and on-line OES

Matti Aula

Side panel cooling water heat loss

• Increasing loss of energy to the cooling water indicates higher energy transfer from arc or atmosphere to the side panels

• Slag accumulating on the side panels causes delay between the scrap melting and the increase of the cooling water temperature

• The slag accumulating on the side panels is advantageous to EAF process since it decreases the heat loss and the wear of the side panels

Examples of slag accumulation on the side panels: high slag accumulation (upper), low

slag accumulation (lower)

Slag amount on the side panes varies Æ complicates reading

Matti Aula

Electrode position

• Another measurement describing melting of scrap in an electric arc furnace is the behaviour of the electrode positions

• The positions of the electrodes can be used to define the length of the bore-down period and analyse scrap melting to some extent

00.20.40.60.8

1

6:30 6:35 6:40 6:45 6:50Elec

trod

e po

sitio

n an

d po

wer

inpu

t (re

lativ

e)

Time

Power input Electrode 2 position

Matti Aula

Optical emission spectrometry • Optical emission spectrometry (OES) relies on

measurement of electromagnetic radiation in wavelengths visible to human eye.

• The light emitted from the EAF can be measured by placing an optical gathering systems looking through the furnace side walls or roof.

• Optical emissions vary significantly during the EAF process: in early melting periods the intensity of the emitted light is small, but it increases when scrap melts in the furnace

Examples of pictures taken with CCD camera during different process periods: melting

period (upper) heating period (lower).

Example of optical emission spectrum

0.0E+001.0E+062.0E+063.0E+064.0E+065.0E+066.0E+06

450 550 650 750 850 950

Inte

nsity

(arb

. uni

ts)

Wavelength (nm)

Matti Aula

OES measurement system

• The optical emissions from the furnace can be gathered with an optical fiber, multiple measurement heads can be used to gain information about local conditions of the EAF

• The presented examples are obtained by simultaneous measurement of three hot spot regions of Outokumpu Stainless, Tornio Works, EAF 2

• The measurements were conducted through holes made in the water-cooled panels on the EAF roof

Cabinet

User interface

Measurement heads

Fiber bundle

Ethernet

Matti Aula

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0

0.2

0.4

0.6

0.8

1

1.2

15:00 15:05 15:10 15:15 15:20 15:25 15:30 15:35 15:40 15:45

Side

pan

el te

mpe

ratu

re g

radi

ent

(rel

ativ

e)

Arc

pow

er a

nd s

pect

rum

inte

nsity

(r

elat

ive)

Time

Arc power Spectrum intensity Side panel temperature gradient

2 min

2 min

Side panel cooling water temperature gradient

Matti Aula

0

1

2

3

4

5

6

7

8

9

10

-0.5

-0.3

-0.1

0.1

0.3

0.5

0.7

0.9

6:30 6:35 6:40 6:45 6:50

Spec

trum

inte

nsity

(rel

ativ

e)

Elec

trod

e po

sitio

n an

d po

wer

inpu

t (re

lativ

e)

Time

Power input Electrode 1 positionElectrode 2 position Electrode 3 positionHot spot 1 spectrum intensity Hot spot 2 spectrum intensityHot spot 3 spectrum intensity

Matti Aula

3

4

5

6

7

8

9

10

11

12

13

0

1

2

3

4

5

6

7

21:10 21:15 21:20 21:25

Coo

ling

wat

er te

mpe

ratu

re g

radi

ent

Spec

trum

inte

nsity

, ele

ctro

de p

ositi

on,

pow

er in

put (

rela

tive)

Time

Power input Electrode 1 positionHot spot 1 spectrum intensity Panel 1 temperature gradient

Matti Aula

Combining different methods

• Every EAF is different Æ on-line OES has to be tailored to the process practice of an individual EAF

• The optimal use of on-line OES requires good understanding of different process phenomena, e. g. slag accumulation and combustion reactions

• This understanding can only be acquired by combining spectrum data and the conventional sensor data

Matti Aula

An example of using on-line OES in process control

• ArcSpec system installed in February 2016 to Outokumpu Stainless Oy, Tornio Works, EAF 1

• Minimal maintenance required • Tested in on-line process control • Refractory wear constantly monitored • Dynamic control of arc voltage with on-line OES

allowed the use of the highest arc voltages, which previously caused water panel problems and increased furnace wear excessively

• High power melting period reduced by 200 s, which was 7 % of the total power-on-time

Matti Aula

Other applications

• Timing of second basket charging • Dynamic control of arc balance • Timing of carbon injection • Slag surface temperature • Monitoring of slag foaming • Slag composition (in development)

Matti Aula

Conclusions

• Advantages of on-line OES over conventional measurements: − Sensor measures EAF process directly − No delay or sensor dead time − Contains additional information about

process phenomenon Æ phenomenon can be differentiated

• On-line OES is a novel and reliable way to measure and control EAFs

Matti Aula

References

[1] M. IACUZZI, Proc. 10th European Electric Arc Furnace Conference (2012), Graz, Aimet.

[2] H.D. GOODFELLOW, L. FERRO and P. GALBIATI. Ironmak. Steelmak. 32, (2005) p. 216.

[3] T. MATSCHULLAT, D. RIEGER, B. DITTMER, K. KRÜGER, A. DÖBBELER and H. MEES, Proc. AISTech - Iron and Steel Technology Conference, Atlanta, (2012), p. 2577.

[4] L. LEI and M. ZHIZHONG Neurocomputing, 82, (2015) p. 91.

[5] A. YAZDANI. M.L CROW, J. and GUO. IEEE Trans. Power Del., 24, (2009), p. 2284.

[6] M. AULA, A. LEPPÄNEN, J. ROININEN, E.-P. HEIKKINEN, K. VALLO, T. FABRITIUS and M. HUTTULA. Metall. Mater. Trans. B, 45B, (2014) p. 839.

[7] M. AULA, A. MÄKINEN, A. LEPPÄNEN, M. HUTTULA and T. FABRITIUS 2015. ISIJ International, 55, (2015), p. 1702..

[8] ANON, Teräskirja (2009), 8 edition. Tampere, Metallinjalostajat ry.

[9] B. KLEMT, P. NYSSEN, C. MATHY, M. WEBER, J. BORLÉE, P. SIMON, J.C. BAUMERT, S. LANDA, R. KÜHN and J. DENG. Dynamic control of EAF burners and injectors for carbon and oxygen for improved and reproducible furnace operation and slag foaming, EUR 23920. Brussels, (2007), European commission.