EP0977897A1 - Procede et dispositif pour refroidir des metaux dans une usine metallurgique - Google Patents

Procede et dispositif pour refroidir des metaux dans une usine metallurgique

Info

Publication number
EP0977897A1
EP0977897A1 EP98930646A EP98930646A EP0977897A1 EP 0977897 A1 EP0977897 A1 EP 0977897A1 EP 98930646 A EP98930646 A EP 98930646A EP 98930646 A EP98930646 A EP 98930646A EP 0977897 A1 EP0977897 A1 EP 0977897A1
Authority
EP
European Patent Office
Prior art keywords
metal
temperature
cooling
parameters
model
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Withdrawn
Application number
EP98930646A
Other languages
German (de)
English (en)
Inventor
Markus HÖHFELD
Rolf-Martin Rein
Thomas Ruge
Otto Gramckow
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Siemens AG
Original Assignee
Siemens AG
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Siemens AG filed Critical Siemens AG
Publication of EP0977897A1 publication Critical patent/EP0977897A1/fr
Withdrawn legal-status Critical Current

Links

Classifications

    • C—CHEMISTRY; METALLURGY
    • C21—METALLURGY OF IRON
    • C21D—MODIFYING THE PHYSICAL STRUCTURE OF FERROUS METALS; GENERAL DEVICES FOR HEAT TREATMENT OF FERROUS OR NON-FERROUS METALS OR ALLOYS; MAKING METAL MALLEABLE, e.g. BY DECARBURISATION OR TEMPERING
    • C21D11/00—Process control or regulation for heat treatments
    • C21D11/005—Process control or regulation for heat treatments for cooling
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B21—MECHANICAL METAL-WORKING WITHOUT ESSENTIALLY REMOVING MATERIAL; PUNCHING METAL
    • B21B—ROLLING OF METAL
    • B21B37/00—Control devices or methods specially adapted for metal-rolling mills or the work produced thereby
    • B21B37/74—Temperature control, e.g. by cooling or heating the rolls or the product
    • B21B37/76—Cooling control on the run-out table
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B22—CASTING; POWDER METALLURGY
    • B22D—CASTING OF METALS; CASTING OF OTHER SUBSTANCES BY THE SAME PROCESSES OR DEVICES
    • B22D11/00—Continuous casting of metals, i.e. casting in indefinite lengths
    • B22D11/16—Controlling or regulating processes or operations
    • B22D11/22—Controlling or regulating processes or operations for cooling cast stock or mould
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B21—MECHANICAL METAL-WORKING WITHOUT ESSENTIALLY REMOVING MATERIAL; PUNCHING METAL
    • B21B—ROLLING OF METAL
    • B21B1/00—Metal-rolling methods or mills for making semi-finished products of solid or profiled cross-section; Sequence of operations in milling trains; Layout of rolling-mill plant, e.g. grouping of stands; Succession of passes or of sectional pass alternations
    • B21B1/46—Metal-rolling methods or mills for making semi-finished products of solid or profiled cross-section; Sequence of operations in milling trains; Layout of rolling-mill plant, e.g. grouping of stands; Succession of passes or of sectional pass alternations for rolling metal immediately subsequent to continuous casting

Definitions

  • the invention relates to a method or a device for cooling metals in a steel mill, the cooling being carried out by means of a temperature model of the metal to be cooled or the cooling. To e.g. It is necessary to regulate the outlet temperature of a steel strip, the expected one
  • the task is solved according to the invention by a method according to claim 1, claim 2 or a device according to claim 18 and claim 19.
  • a method for cooling metal in a steel mill the cooling being set as a function of the temperature of the metal in such a way that the metal reaches a desired target temperature, and the temperature of the metal is determined or predicted by means of a temperature model
  • This method has proven to be particularly suitable for obtaining an optimal temperature model taking into account the large number of its parameters.
  • a temperature model usually comprises up to 100 parameters - there may be more - so that previous attempts to achieve improved cooling by means of an improved temperature model have not achieved the desired success.
  • excellent results can be achieved in terms of improving the cooling. 7 to 10 illustrate this unexpectedly great success of the method according to the invention.
  • FIGS. 7 and 8 relate to a cooling section
  • FIGS. 9 and 10 relate to a further cooling section. 7 to 10 show histograms in which the frequency of certain values for the deviation between the desired outlet temperature and the actual outlet running temperature are plotted.
  • FIG. 7 shows the results of cooling with the conventional method
  • FIG. 8 on the other hand with the inventive method.
  • the mean value of the deviation from the desired target outlet temperature is -
  • the mean value of the deviation is only 8.2 ° C.
  • the known method is therefore more than 600% worse than the method according to the invention.
  • the enormous improvement in cooling becomes even clearer when comparing FIG. 9 and FIG. 10.
  • the mean value of the deviation is -68.8 ° C.
  • the deviation with the method according to the invention is only 3.4 ° C.
  • the known method is even 2000% worse than the method according to the invention.
  • the cooling according to the invention is therefore surprisingly clearly superior to the known cooling method. Certain advantageous measures are responsible for the clarity with which the inventive method is superior to the conventional method.
  • parameters relating to one and the same physical effect are grouped together, the values of a group not being torn apart when genes are recombined, ie groups are only recombined as a whole when recombined.
  • Another particularly advantageous measure is that the optimization function has a quadratic weighting for small deviations, but large deviations are weighted linearly.
  • the method according to the invention can be further improved if the values for the parameters are scaled in such a way that they have a homogeneous sensitivity with respect to the optimization function, ie that the parameters are scaled in such a way that their sensitivity to the optimization function is the same or at least that the sensitivities are of the same order of magnitude.
  • the method according to the invention has proven to be particularly advantageous when used for the cooling of sheets which are wound onto a reel after leaving a cooling section, since it is particularly important when reeling that the coiled metal has the correct temperature. If the deviations from the desired target temperature are too large, the quality of the metal is impaired.
  • FIG. 1 shows a device for cooling a metal strip F FIIGG 2 2 the structure of the cooling method according to the invention
  • 5 shows a schematic diagram of a steel strip production plant
  • FIG. 7 shows the frequency distribution of the deviation of the outlet temperature from a desired outlet temperature in the known method
  • FIG. 8 shows the frequency distribution of the deviation of the outlet temperature from a desired outlet temperature in the method according to the invention
  • FIG. 9 shows the frequency distribution of the deviation of the outlet temperature from a desired outlet temperature in the known method
  • FIG. 10 shows the frequency distribution of the deviation of the outlet temperature from a desired outlet temperature in the method according to the invention
  • FIG. 11 shows a quadratic optimization function IG 12 an optimization function with square and linear gates IG 13 a physically implausible relationship between the heat transfer coefficient and the amount of coolant
  • FIG 14 a physically plausible relationship between the heat transfer coefficient and the amount of coolant
  • FIG 15 thermal conductivity plotted against the steel temperature
  • FIG 16 thermal conductivity plotted against the steel temperature
  • FIG. 1 shows a device for cooling a metal strip 1, 2, 3, which runs out of a finishing train 8 in the direction of the arrow identified by reference number 4 and which is wound onto a reel 5.
  • a cooling section which has cooling nozzle arrangements 6 and 7. Coolant, in particular water, emerges from the cooling nozzles, by means of which the steel strip 1, 2, 3 is cooled.
  • the cooling nozzle blocks 6 and 7 are controlled or regulated by means of a control device 90, via which they are connected by means of a data line 92.
  • the control device 90 also receives measured values via the outlet temperature of the metal strips 3, which is measured by means of a measuring device 91.
  • a cooling section 16, into which metal 17 runs and cooled metal 18 runs out, is regulated by means of a controller 9, which specifies setpoints 13 for cooling. These setpoints 13 for cooling are regulated by the control system 9 as a function of the desired setpoint outlet temperature 8 of the cooled metal 18 and an estimated outlet temperature 10 of the metal 18.
  • the estimated outlet temperature 10 is determined using a temperature model 11 as a function of the setpoints 13 for cooling.
  • the parameters 14 of the temperature model 11 are optimized depending on the current parameters 14 of the estimated outlet temperature 10 and the actual outlet temperature 15 by means of genetic algorithms 12.
  • a cooling section 21, into which metal 25 runs and cooled metal 27 runs out, is regulated by means of a model-controlled control system 19, which specifies setpoints 24 for cooling.
  • the model-based control 19 determines the setpoints 24 for the cooling as a function of the desired outlet temperature 22.
  • the parameters 23 of the model-based control 19 are optimized as a function of the current parameters 23 of the desired setpoint temperature 22 of the outlet temperature 26 by means of genetic algorithms 20.
  • FIG. 4 shows in simplified form the procedure for optimization using genetic algorithms.
  • the optimization is carried out in such a way that values for the parameters are arranged in so-called genes 40, which in turn are assigned to individuals 41 of a so-called population, so that an individual 41 values for the parameters to be optimized, i.e. Genes, and that the optimization takes place in such a way
  • FIG. 5 shows a schematic diagram of a steel strip production plant.
  • This has a mold 42 and a strand cooling 43, 44 for cooling the cast strand 45.
  • This runs in the direction of arrow 46 into a finishing train 47, in which it is processed into a steel strip 49.
  • the steel strip 49 is cut at certain intervals by means of a scissors 48. It then runs through a cooling section 51, 52 and is wound onto a reel 53.
  • the cooling method according to the invention is used particularly advantageously to control or regulate the cooling of the cooling section 51, 52. It can also advantageously be used for regulating or controlling the cooling of the strand cooling 43, 44.
  • Reference numeral 61 designates the cast strand which has a solidified part 63 and a liquid sump part 62.
  • the strand is moved with drive or guide rollers 64 and cooled on its way through cooling devices 65. These are advantageously designed as water spray devices. For reasons of clarity, not all drive or guide rollers 64 and cooling devices 65 are provided with reference symbols.
  • the cooling devices 65 are divided into cooling segments 66. This division is not necessary in the new and inventive method, but can be taken into account.
  • Both the drive rollers 64 and the cooling devices are data-technically with a computing facility connected. In the present exemplary embodiment, both are connected in terms of data technology to one and the same programmable logic controller 67.
  • the programmable logic controller 67 optionally also has a terminal 69 and a keyboard 68.
  • the programmable logic controller 67 has a higher-level computing system
  • the material required for continuous casting in this case liquid steel, is fed through a feed device
  • the manipulated variables for the cooling devices 65 are determined using a temperature model, i.e. a thermal model of the strand, which is implemented on the programmable logic controller 67 in the exemplary embodiment.
  • the optimization of the parameters of the temperature model according to the invention by means of genetic algorithms advantageously takes place on the superordinate computer system 70.
  • FIG. 7 to 10 show histograms in which the frequency of certain values for the deviation between the desired outlet temperature and the actual outlet temperature are plotted.
  • FIG. 7 shows the results of cooling with the conventional method
  • FIG. 8 on the other hand with the inventive method.
  • the mean value of the deviation from the desired target outlet temperature is -50.6 ° C. in the conventional method.
  • the mean value of the deviation is only 8.2 ° C.
  • the known method is therefore more than 600% worse than the method according to the invention.
  • the enormous improvement in cooling becomes even clearer when comparing FIG. 9 and FIG. 10.
  • the mean value of the deviation is -68.8 ° C.
  • the deviation with the method according to the invention is only 3.4 ° C.
  • the known method is even 2000% worse than the method according to the invention.
  • the scatter in the method according to the invention is also reduced by the mean value of the deviation.
  • the standard deviation in the histogram is 68.6 ° C in FIG. 7, 32.9 ° C in FIG. 8, 57.0 ° C in FIG. 9 and 25.1 ° C in FIG. Due to the reduced mean deviation of the desired outlet temperature and the lower. If the spread is around this value, the proportion of tapes with an impermissibly high deviation from the desired outlet temperature can be significantly reduced.
  • the optimization method with which the results according to FIG. 8 and FIG. 10 were achieved is based on a cooling model with 92 parameters which were optimized according to the invention using genetic algorithms.
  • the 92 parameters consist of: 5 parameters or support points for the thermal conductivity of the steel strip, 11 parameters or support points for the temperature conductivity of the steel strip, one parameter for the constant portion for convection in air, one parameter for the linear portion for the Convection at
  • Air a parameter for the belt speed-dependent portion of the convection, a parameter for the heat radiation, a factor for weighting the cooling of the belt top and belt underside, a parameter for the cooling in the roller table, a parameter for the pressure-dependent and the speed-dependent adaptation the heat transfer coefficient, a lower and an upper limit for the speed in relation to the speed-dependent adaptation of the heat transfer coefficient, a parameter for the influence of the water temperature, 4 parameters for describing the temperature dependency of the heat transfer coefficient, 40 parameters for the water quantity dependence of the heat transfer coefficient on the top of the belt ( 10 water levels for 4 cooling areas), 8 parameters for the spray pattern dependence of the heat transfer coefficient (4 spray patterns for 2 cooling areas) on the top of the belt, 3 additional parameters for the heat transfer coefficient on the top of the belt (for 3 cooling areas), 4 parameters for the water quantity dependency of the heat transfer coefficient on the underside of the belt (one water level for 4 cooling areas), 4 parameters for the spray pattern dependency of the heat transfer coefficient (4 spray patterns for one cooling area) on the underside of the belt and 2 additional parameters
  • FIG. 11 shows a quadratic optimization function 80, as is usually used for optimization problems.
  • an optimization function 81 according to FIG. 12 which has small deviations from the desired target temperature, in the present exemplary embodiment deviations up to 15 ° C, square and large deviations, i.e. In the present embodiment, deviations> 15 ° C, weighted linearly.
  • parameters relating to one and the same physical effect are combined in groups, the values of a group not being torn apart when genes are recombined, i.e. that groups are only recombined as a whole when recombined. It has been shown that it is possible in this way to exclude physically contradicting solutions. In this way, the result of the
  • FIG. 13 shows an example of a physically inconclusive solution.
  • the necessary coolant quantity of a nozzle is plotted for the heat transfer coefficient ⁇ , the coolant quantity L being plotted in% of the maximum output of the corresponding cooling nozzle.
  • the necessary amount of coolant would have to be physically correct
  • the heat transfer coefficient ⁇ increases, as is shown, for example, by curve 83 in FIG. 14.
  • curve 82 has areas in FIG. 13 in which the necessary amount of coolant L increases as the heat transfer coefficient ⁇ decreases. This is not physically correct.
  • Such physically inconsistent solutions can be prevented by the grouping of parameters mentioned above.
  • 15 and 16 illustrate the advantage of the use of genetic algorithms according to the invention.
  • 15 shows a simplified relationship between the thermal conductivity ⁇ and the steel temperature T scee ⁇ .
  • Three parameters ⁇ 0 , ⁇ i, ⁇ 2 are necessary to describe this relationship. Since genetic algorithms make it possible to solve optimization problems with many parameters, the method according to the invention also allows a more precise modeling in relation to the model structure. By using more parameters, the physical relationship between
  • FIG. 16 shows the relationship between thermal conductivity ⁇ and

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  • Engineering & Computer Science (AREA)
  • Chemical & Material Sciences (AREA)
  • Mechanical Engineering (AREA)
  • Physics & Mathematics (AREA)
  • Thermal Sciences (AREA)
  • Crystallography & Structural Chemistry (AREA)
  • Materials Engineering (AREA)
  • Metallurgy (AREA)
  • Organic Chemistry (AREA)
  • Control Of Heat Treatment Processes (AREA)

Abstract

L'invention concerne un procédé pour refroidir du métal dans une usine métallurgique, le refroidissement étant ajusté en fonction de la température du métal, de sorte que le métal atteigne une température de consigne souhaitée. La température du métal est déterminée ou estimée au préalable, au moyen d'un modèle de température. Les paramètres du modèle de température, notamment le coefficient de transmission thermique et la conductivité thermique du métal, sont adaptés aux propriétés du métal et au refroidissement, à l'aide d'algorithmes génétiques, dans le but d'optimiser ledit modèle.
EP98930646A 1997-04-25 1998-04-09 Procede et dispositif pour refroidir des metaux dans une usine metallurgique Withdrawn EP0977897A1 (fr)

Applications Claiming Priority (3)

Application Number Priority Date Filing Date Title
DE1997117615 DE19717615A1 (de) 1997-04-25 1997-04-25 Verfahren und Einrichtung zur Kühlung von Metallen in einem Hüttenwerk
DE19717615 1997-04-25
PCT/DE1998/001026 WO1998049354A1 (fr) 1997-04-25 1998-04-09 Procede et dispositif pour refroidir des metaux dans une usine metallurgique

Publications (1)

Publication Number Publication Date
EP0977897A1 true EP0977897A1 (fr) 2000-02-09

Family

ID=7827797

Family Applications (1)

Application Number Title Priority Date Filing Date
EP98930646A Withdrawn EP0977897A1 (fr) 1997-04-25 1998-04-09 Procede et dispositif pour refroidir des metaux dans une usine metallurgique

Country Status (3)

Country Link
EP (1) EP0977897A1 (fr)
DE (1) DE19717615A1 (fr)
WO (1) WO1998049354A1 (fr)

Families Citing this family (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
DE19740691A1 (de) * 1997-09-16 1999-03-18 Siemens Ag Verfahren und Einrichtung zur Kühlung von Metallen in einem Hüttenwerk
DE10042386A1 (de) * 2000-08-29 2002-03-28 Siemens Ag Verfahren zur Bestimmung der thermischen Materialeigenschaften von Metall-Formteilen
ATE348671T1 (de) * 2003-02-25 2007-01-15 Siemens Ag Verfahren zur regelung der temperatur eines metallbandes, insbesondere in einer kühlstrecke
ATE360483T1 (de) * 2003-02-25 2007-05-15 Siemens Ag Verfahren zur regelung der temperatur eines metallbandes, insbesondere in einer fertigstrasse zum walzen von metallwarmband
CN1329133C (zh) * 2003-02-25 2007-08-01 西门子公司 尤其在轧制金属热轧带材的精轧机列中调节金属带温度的方法
PL3645182T3 (pl) * 2017-06-26 2022-01-03 Arcelormittal Sposób i elektroniczne urządzenie do określania temperatury taśmy metalowej, powiązany sposób sterowania, program komputerowy, aparat sterujący oraz instalacja do walcowania na gorąco

Family Cites Families (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JPS58120742A (ja) * 1982-01-11 1983-07-18 Nippon Steel Corp 鋼帯の冷却制御方法
JPH04237552A (ja) * 1991-01-18 1992-08-26 Hitachi Zosen Corp 連続鋳造設備の二次冷却制御方法
AT408197B (de) * 1993-05-24 2001-09-25 Voest Alpine Ind Anlagen Verfahren zum stranggiessen eines metallstranges
JP2954485B2 (ja) * 1994-02-07 1999-09-27 新日本製鐵株式会社 熱延鋼帯の捲取温度制御方法

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
See references of WO9849354A1 *

Also Published As

Publication number Publication date
WO1998049354A1 (fr) 1998-11-05
DE19717615A1 (de) 1998-10-29

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