EP1106713A2 - Méthode pour déterminer le temps de décapage d'une bande métallique couvert de calamine - Google Patents

Méthode pour déterminer le temps de décapage d'une bande métallique couvert de calamine Download PDF

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Publication number
EP1106713A2
EP1106713A2 EP00126992A EP00126992A EP1106713A2 EP 1106713 A2 EP1106713 A2 EP 1106713A2 EP 00126992 A EP00126992 A EP 00126992A EP 00126992 A EP00126992 A EP 00126992A EP 1106713 A2 EP1106713 A2 EP 1106713A2
Authority
EP
European Patent Office
Prior art keywords
information
scale
metal strip
bath
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.)
Granted
Application number
EP00126992A
Other languages
German (de)
English (en)
Other versions
EP1106713A3 (fr
EP1106713B1 (fr
Inventor
Otto Dr. Gramckow
Hans-Ulrich Dr. Löffler
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
Siemens Corp
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Siemens AG
Siemens Corp
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Publication date
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Publication of EP1106713A2 publication Critical patent/EP1106713A2/fr
Publication of EP1106713A3 publication Critical patent/EP1106713A3/fr
Application granted granted Critical
Publication of EP1106713B1 publication Critical patent/EP1106713B1/fr
Anticipated expiration legal-status Critical
Expired - Lifetime legal-status Critical Current

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Classifications

    • C—CHEMISTRY; METALLURGY
    • C23—COATING METALLIC MATERIAL; COATING MATERIAL WITH METALLIC MATERIAL; CHEMICAL SURFACE TREATMENT; DIFFUSION TREATMENT OF METALLIC MATERIAL; COATING BY VACUUM EVAPORATION, BY SPUTTERING, BY ION IMPLANTATION OR BY CHEMICAL VAPOUR DEPOSITION, IN GENERAL; INHIBITING CORROSION OF METALLIC MATERIAL OR INCRUSTATION IN GENERAL
    • C23G—CLEANING OR DE-GREASING OF METALLIC MATERIAL BY CHEMICAL METHODS OTHER THAN ELECTROLYSIS
    • C23G1/00—Cleaning or pickling metallic material with solutions or molten salts
    • C—CHEMISTRY; METALLURGY
    • C23—COATING METALLIC MATERIAL; COATING MATERIAL WITH METALLIC MATERIAL; CHEMICAL SURFACE TREATMENT; DIFFUSION TREATMENT OF METALLIC MATERIAL; COATING BY VACUUM EVAPORATION, BY SPUTTERING, BY ION IMPLANTATION OR BY CHEMICAL VAPOUR DEPOSITION, IN GENERAL; INHIBITING CORROSION OF METALLIC MATERIAL OR INCRUSTATION IN GENERAL
    • C23G—CLEANING OR DE-GREASING OF METALLIC MATERIAL BY CHEMICAL METHODS OTHER THAN ELECTROLYSIS
    • C23G1/00—Cleaning or pickling metallic material with solutions or molten salts
    • C23G1/02—Cleaning or pickling metallic material with solutions or molten salts with acid solutions
    • C—CHEMISTRY; METALLURGY
    • C23—COATING METALLIC MATERIAL; COATING MATERIAL WITH METALLIC MATERIAL; CHEMICAL SURFACE TREATMENT; DIFFUSION TREATMENT OF METALLIC MATERIAL; COATING BY VACUUM EVAPORATION, BY SPUTTERING, BY ION IMPLANTATION OR BY CHEMICAL VAPOUR DEPOSITION, IN GENERAL; INHIBITING CORROSION OF METALLIC MATERIAL OR INCRUSTATION IN GENERAL
    • C23G—CLEANING OR DE-GREASING OF METALLIC MATERIAL BY CHEMICAL METHODS OTHER THAN ELECTROLYSIS
    • C23G1/00—Cleaning or pickling metallic material with solutions or molten salts
    • C23G1/02—Cleaning or pickling metallic material with solutions or molten salts with acid solutions
    • C23G1/08—Iron or steel

Definitions

  • the invention relates to a method for determining a Pickling time of a scale layer for removal the scale layer to be treated in a pickling bath.
  • iron oxides are produced in the production of hot strip, i.e. hot-rolled metal strip.
  • the composition of this scale is dependent, among other things, on the specific cooling process, since different iron oxides form or different phases are formed depending on the cooling of the hot metal strip. Primarily these are wustite formation (FeO), magnetite (Fe 3 O 4 ) and hematite (Fe 2 O 3 ), and various Fe (II) and Fe (III) hydroxides also occur.
  • the scale must be removed in a subsequent descaling process. As part of this, mechanical descaling is first carried out and then the scale is removed in a pickling bath.
  • Hot hydrochloric acid (HCl) with a temperature between 80 - 90 ° C is mainly used as the pickling liquid, whereby the bath is usually divided into several zones in which the hydrochloric acid concentration is different. In the beginning there is usually a low concentration (e.g. 4%), in the last bath section the highest concentration (e.g. 15-17 ° C) to carry out the final cleaning there.
  • a stretch straightener is primarily used for mechanical descaling. In this stretcher, the metal strip is guided under tensile stress around several deflection rollers and bent so that the scale layer cracks and in some cases already peels off. The acid penetrates these cracks and comes into contact with the metal, where hydrogen is formed. The hydrogen bubbles then blow off the scale. Due to the direct contact between the acid bath and the metal, descaling is much faster than if there was a closed scale layer and the acid would first have to diffuse through the scale layer to the metal.
  • the time required for complete descaling depends on various factors such as acid temperature, acid concentration, Degree of mechanical descaling and especially from the Amount and type of scale.
  • As a measure of the amount of scale only the reel temperature, i.e. the temperature, with which the hot band e.g. after hot rolling before Descaling is wound on a reel, and experience about the scaling of different types of steel used.
  • the required pickling time is based on some of the roughly estimated values above. The quality control the stained tapes only find visually through one Controller instead.
  • control has a number of disadvantages.
  • the pickling time required is only rough estimated. This can lead to unsatisfactory pickling results lead to a short pickling time.
  • the pickling time is as short as to keep possible in order to achieve the highest possible throughput.
  • Another disadvantage is that it is only visual control. It does not give an objective measure of the degree of scaling the result depends heavily on the respective controller and can vary greatly from layer to layer. On useful assessment criterion for determining a more precise This does not result in pickling time.
  • the invention is therefore based on the problem, one possibility specify how the pickling time is determined more precisely can.
  • one method is the beginning mentioned type provided according to the invention that the Pickling time using a calculation model based on at least one band specific information of the scaled metal band and at least one piece of information that is specific to the bzbad is modeled becomes.
  • the pickling time is used of a calculation model is calculated and modeled and no longer roughly estimated based on the given parameters.
  • the calculation model which is, for example a neural network or a fuzzy controller can act, but any other model can be used, processed at least one band-specific information of the scaled Metal bands, so information that the tinder describes itself or the scale formation and for the to be treated Band is specific. Furthermore, at least one processed information specific to bebebad, as for determination the pickling time, of course, also the specific descaling properties of the pickling bath are relevant.
  • At least one can be formed as band-specific information Scale layer self-descriptive information and / or one for the formation of the scale layer during the Production of the metal strip relevant information and / or one for mechanical treatment of the metal strip Information relevant to mechanical scale removal be used.
  • Each of these individual pieces of information contains a considerable amount of information, which Is evaluated and processed by the calculation model. Although only one of these pieces of information is processed , it has proven to be advantageous if several or all are taken into account because the pickling time is all the more can be modeled more precisely, the more information regarding the scale layer and its pretreatment are available stand.
  • the surface-specific information which is a description of the scaled band surface supplies.
  • this information can be obtained by an optical surface scan by means of an image of the Belt surface supplying camera, the image of which is automatically Determination of a surface describing the surface covered with scale Information value is analyzed, obtained.
  • the information value allows a classification of the different Tinder types and / or the amount of tinder. Any type of scale appears somewhat different in color in an image or structure.
  • the picture taken with the camera can be analyzed in this regard, so that on the basis of this Surface scanning a classification can be made can. Additionally or alternatively, it can be based on the image acquisition the amount of scale per unit area is also determined in this case gives the analytically obtained information value a quantitative measure of the actual Amount of scale.
  • Scale layer Another in the context of modeling the optimized pickling time important information is regarding the formation of the Scale layer itself.
  • one for the manufacturing process of the metal strip specific information can be used, in particular for this the temperature of the metal strip during winding a reel, one related to the cooling process of the metal strip Information relating to the degree of deformation of the metal strip Information, the chemical reaction behavior information relating to scale formation is used.
  • Relevant are also information regarding the steel grade itself, regarding the oxygen partial pressure of the surrounding atmosphere etc. All of this information can be found in the model be taken into account. This is information for indirect information, i.e. information, that do not describe the tinder itself, but indirectly reflect its educational conditions.
  • mechanical pre-descaling is usually carried out carried out. This is usually the closed one Scale layer broken, which facilitates the acid attack. Obviously, descaling can be easier and the faster the mechanical pre-descaling is. Consequently, the related information also provides an important model parameter.
  • the invention can be at least one mechanical as related information Stretcher treatment parameters in which the Metal strip for mechanical pre-descaling machined will be used. The metal strip is in the stretching judge led under tension around several pulleys.
  • Mechanical parameters can be, for example, the applied parameters Tensile stress or the degree of deflection and thus the bend of the metal band can be used.
  • the bath temperature, the Bath composition, the bath concentration, existing in the bath Turbulence or the iron concentration in the bathroom is taken into account become.
  • a first invention can be used for education the scale layer relevant during the manufacturing process Information processed in a scale formation model and a modeled information value describing the tinder can be determined with that in the context of the analysis of the surface scan image determined information value compared and a value describing the degree of scaling is determined the calculation model for modeling the pickling time is given.
  • a scale formation model which also for example a neural network can be a tinder Descriptive modeled information value determines which specifies a measure of the degree of scaling.
  • This Degree of scaling is determined with the information value from the surface scan, which is also a measure of the scale type represents the amount of scale, compared and from it a value describing the actual degree of scaling determined.
  • This value represents a measure of the degree of scaling which, based on the described information parameters was determined. In the event of major deviations between the two The more plausible value can be used when measuring smaller deviations is an, if necessary weighted, Average value makes sense. This value is then the Calculation model for modeling the pickling time given.
  • all information can be the computing model can also be given directly for processing, i.e. a previous determination of the descaling degree The measure is not given here, rather all go Sizes directly into the calculation model.
  • the quality of the pickling process can only checked using the pickled metal strip.
  • the information about the appearance of the stained surface and thus about the presence of any residual scale or the like is also for the optimization of the pickling time modeling relevant.
  • the pickling time modeling relevant As described in the prior art only a visual inspection of the surface of the stained Metal bands, but the information obtained from them remains largely ignored when determining the pickling time.
  • an adaptation of the or used Models based on an automatic surface scan of the pickled metal strip resulting information he follows.
  • Step 1 shows a diagram to illustrate the modeling method according to a first embodiment of the invention.
  • Step 1 is using an optical surface scan a camera that delivers an image which in an analysis model 2, which is a neural Network can act, is prepared.
  • the continuously from the continuously conveyed metal strip will be a first informational value determined in the form of a measure, which is a measure of Art and amount of scale. It is based on the analysis model a classification of the different types of scale as well as a quantitative determination of the amount of scale.
  • step 3 information about the manufacturing process of the metal strip in a scale formation model 4 for Determination of a second information value in the form of a measure processed, this measure also the degree of scaling describes.
  • Indirect information can be used here Measured variables such as the reel temperature, the degree of deformation, the cooling process of the metal strip, for example the cooling steps, the cooling time, etc. or else the storage of the metal strip during cooling and the chemical reaction behavior of the metal itself within the Scale formation are taken into account.
  • step 5 there is a Comparison of the two with the analysis model and the scale formation model determined measures to a measure 6 (it can several measures are also determined) for the degree of scaling to investigate. As shown in Fig.
  • the measure for the degree of scaling determined in step 6 is given a calculation model 7 for determining the pickling time.
  • This calculation model is also, see step 8, information given mechanical pre-descaling, for example in the form of a measure or a parameter regarding the given tensile stress during a stretch judge treatment of the metal band to break the closed Scale layer.
  • All of the information, ie the part of the computational model, which also preferably is formed as a neural network in the steps 6, 8, 9 information contained are processed to determine an optimal pickling time T pickling.
  • the pickling time can be modeled very precisely on the basis of the large amount of processed information recorded in the model.
  • the pickling time is given, for example, to an automatic control system which controls the entire pickling treatment. On the control side, depending on the optimized pickling time, there is an increase or decrease in the conveying speed of the metal strip and thus a change in the residence time of the strip in the pickling bath.
  • step 10 is a Surface scanning of the pickled metal strip for testing of the pickling result.
  • a Be used to continuously take pictures of the camera Surface supplies that are evaluated with an analysis model become.
  • a determination is based on this surface scan of the remaining scale on the pickled belt possible, whereby here too, both the type and the quantity can be determined can.
  • the result can be used to adapt the Models 2, 4, 7 can be used. For example can, if the scaling in exceptional cases the quality specifications should exceed the corrected model become.
  • this can be done Result also used directly to regulate the pickling treatment and are given to the control device
  • Result also used directly to regulate the pickling treatment and are given to the control device
  • Result also used directly to regulate the pickling treatment and are given to the control device
  • a non-negligible arises when scanning Remaining scale quantity can be on the control side the pickling time can be adjusted and extended accordingly.
  • models are also fuzzy Controller can be used.
  • FIG. 2 shows a second embodiment of the invention in the form of a diagram.
  • the same data as described with reference to FIG. 1 are recorded in steps 1, 3, 8 and 9 provided with the same reference symbols.
  • the data of the optical surface scanning are also processed here in the analysis model 2.
  • all the information required directly to the calculation model for modeling the optimal pickling time 7 T pickling It is therefore not, as with respect to FIG. 1, that a measure of the degree of scaling is determined on the basis of the information from the optical surface scanning and the information about the manufacturing process, which is in turn processed in the computing model. Rather, the "raw data" are given directly to the computing model 7 here.
  • This can also be a neural network which, as is preferred but not necessarily all the other models described, is capable of learning.

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  • Chemical & Material Sciences (AREA)
  • Chemical Kinetics & Catalysis (AREA)
  • General Chemical & Material Sciences (AREA)
  • Engineering & Computer Science (AREA)
  • Materials Engineering (AREA)
  • Mechanical Engineering (AREA)
  • Metallurgy (AREA)
  • Organic Chemistry (AREA)
  • Cleaning And De-Greasing Of Metallic Materials By Chemical Methods (AREA)
EP00126992A 1999-12-08 2000-12-08 Méthode pour déterminer le temps de décapage d'une bande métallique couvert de calamine Expired - Lifetime EP1106713B1 (fr)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
DE19959204A DE19959204A1 (de) 1999-12-08 1999-12-08 Verfahren zur Ermittlung einer Beizzeit eines eine Zunderschicht aufweisenden Metallbandes
DE19959204 1999-12-08

Publications (3)

Publication Number Publication Date
EP1106713A2 true EP1106713A2 (fr) 2001-06-13
EP1106713A3 EP1106713A3 (fr) 2002-07-31
EP1106713B1 EP1106713B1 (fr) 2005-06-22

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EP00126992A Expired - Lifetime EP1106713B1 (fr) 1999-12-08 2000-12-08 Méthode pour déterminer le temps de décapage d'une bande métallique couvert de calamine

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Country Link
EP (1) EP1106713B1 (fr)
AT (1) ATE298375T1 (fr)
DE (2) DE19959204A1 (fr)
ES (1) ES2244389T3 (fr)

Cited By (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP1167577B1 (fr) * 2000-06-30 2008-04-16 SMS Demag AG Procédé et appareil pour détecter automatiquement la calamine sur des surfaces de bandes métalliques, en particulier des bandes laminées à chaud en acier ou en acier inoxydable
FR2925530A1 (fr) * 2007-12-21 2009-06-26 Siemens Vai Metals Tech Sas Installation et procede pour le decapage en continu de bandes d'acier
WO2010006895A1 (fr) * 2008-07-16 2010-01-21 Siemens Aktiengesellschaft Procédé de conduite d'un dispositif de traitement d'un feuillard métallique et installation de traitement d'un feuillard métallique
WO2021058044A1 (fr) * 2019-09-26 2021-04-01 Siedentop Gmbh Sélection automatique de durée de décapage

Families Citing this family (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
DE102011017371B3 (de) * 2011-04-16 2012-07-19 Technische Universität Bergakademie Freiberg Verfahren zur Verbesserung der Oberflächenqualität von Halbzeugen aus Stahl bei der Warmumformung

Family Cites Families (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
NL6401445A (fr) * 1964-02-18 1965-08-19
DE19508476A1 (de) * 1995-03-09 1996-09-12 Siemens Ag Leitsystem für eine Anlage der Grundstoff- oder der verarbeitenden Industrie o. ä.
DE19508474A1 (de) * 1995-03-09 1996-09-19 Siemens Ag Intelligentes Rechner-Leitsystem
JP3518316B2 (ja) * 1997-03-03 2004-04-12 株式会社日立製作所 酸洗プラントの制御方法とその酸洗プラント
KR100464580B1 (ko) * 1997-03-03 2005-02-28 가부시끼가이샤 히다치 세이사꾸쇼 산세정플랜트의제어방법과그산세정플랜트
DE19743022A1 (de) * 1997-09-29 1999-04-01 Siemens Ag Verfahren und Einrichtung zum Beizen eines Metallbandes

Cited By (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP1167577B1 (fr) * 2000-06-30 2008-04-16 SMS Demag AG Procédé et appareil pour détecter automatiquement la calamine sur des surfaces de bandes métalliques, en particulier des bandes laminées à chaud en acier ou en acier inoxydable
FR2925530A1 (fr) * 2007-12-21 2009-06-26 Siemens Vai Metals Tech Sas Installation et procede pour le decapage en continu de bandes d'acier
US20100269854A1 (en) * 2007-12-21 2010-10-28 Siemens Vai Metals Technologies Sas Apparatus and Method for the Continuous Pickling of Steel Strip
RU2451772C2 (ru) * 2007-12-21 2012-05-27 Сименс Фаи Металз Текнолоджиз Сас Установка и способ непрерывного травления стальных полос
KR101227282B1 (ko) * 2007-12-21 2013-01-28 지멘스 바이 메탈스 테크놀로지 에스에이에스 스틸 스트립의 연속 산세척 장치 및 방법
US8834636B2 (en) * 2007-12-21 2014-09-16 Siemens Vai Metals Technologies Sas Apparatus and method for the continuous pickling of steel strip
WO2010006895A1 (fr) * 2008-07-16 2010-01-21 Siemens Aktiengesellschaft Procédé de conduite d'un dispositif de traitement d'un feuillard métallique et installation de traitement d'un feuillard métallique
WO2021058044A1 (fr) * 2019-09-26 2021-04-01 Siedentop Gmbh Sélection automatique de durée de décapage

Also Published As

Publication number Publication date
EP1106713A3 (fr) 2002-07-31
ES2244389T3 (es) 2005-12-16
EP1106713B1 (fr) 2005-06-22
DE19959204A1 (de) 2001-07-12
ATE298375T1 (de) 2005-07-15
DE50010598D1 (de) 2005-07-28

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