CN107794335A - A kind of method for improving automatic Steelmaking dynamic model precision - Google Patents

A kind of method for improving automatic Steelmaking dynamic model precision Download PDF

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Publication number
CN107794335A
CN107794335A CN201610802984.4A CN201610802984A CN107794335A CN 107794335 A CN107794335 A CN 107794335A CN 201610802984 A CN201610802984 A CN 201610802984A CN 107794335 A CN107794335 A CN 107794335A
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mrow
msub
model
tsc
dynamic
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Inventor
王小善
何海龙
王成青
舒耀
高洪涛
李泊
朱国强
李冰
曹琳
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Angang Steel Co Ltd
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Angang Steel Co Ltd
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    • C—CHEMISTRY; METALLURGY
    • C21—METALLURGY OF IRON
    • C21C—PROCESSING OF PIG-IRON, e.g. REFINING, MANUFACTURE OF WROUGHT-IRON OR STEEL; TREATMENT IN MOLTEN STATE OF FERROUS ALLOYS
    • C21C5/00—Manufacture of carbon-steel, e.g. plain mild steel, medium carbon steel or cast steel or stainless steel
    • C21C5/28—Manufacture of steel in the converter
    • C21C5/30—Regulating or controlling the blowing

Abstract

The present invention provides a kind of method for improving automatic Steelmaking dynamic model precision, and automatic Steelmaking dynamic model includes decarburization model and temperature rising model, and Model Self-Learning process is mainly the automatic modification to decarburization model parameter and temperature rising model parameter；The parametric classification of dynamic model is refined by molten iron silicon content and procedural test carbon content, when the dynamic model stability contorting and smelting process of one heat steel water are stable, the heat carries out manual self study, and is updated according to the parameter of the corresponding dynamic group number of molten iron silicon content and procedural test carbon content progress of reality；After procedural test terminates, dynamic model starts, and automatically selects corresponding model parameter α, β, γ, δ value of dynamic group number according to molten iron silicon content and procedural test carbon content, carries out blowing control.The present invention can improve the control accuracy of automatic Steelmaking dynamic model, reduce single decarburization programming rate and the deviation actually controlled, improve the carbon temperature hit rate of automatic Steelmaking.

Description

A kind of method for improving automatic Steelmaking dynamic model precision
Technical field
The invention belongs to pneumatic steelmaking automation field, more particularly to a kind of molten iron and steel scrap it is complex under the conditions of carry The method of high automatic Steelmaking dynamic model precision.
Background technology
Automation of converter steel-making based on sublance is all process carbon content and mistake after sublance process (TSC) test terminates Under the premise of journey temperature test is successful, starts dynamic model and carry out smelting control.When molten iron condition and steel scrap conditional stability, move States model heats up according to certain speed decarburization after starting and controlled.But when molten iron, steel scrap conditional fluctuation are larger, directly affect certainly Dynamicization makes steel the control accuracy of dynamic model, control accuracy is deteriorated, therefore single heating decarbonization rate can not meet reality The needs of border production.
The content of the invention
The purpose of the present invention aim to provide it is a kind of can be according to the different condition and sublance procedural test situation of molten iron to converter Dynamic model condition is classified automatically, is realized in varied situations, starts the different decarburization programming rate of dynamic model, so as to carry The control accuracy of high automatic Steelmaking dynamic model.
Therefore, the technical solution that the present invention is taken is：
It is a kind of improve automatic Steelmaking dynamic model precision method, automatic Steelmaking dynamic model include decarburization model and Temperature rising model, Model Self-Learning process are mainly the automatic modification to decarburization model parameter and temperature rising model parameter；Pass through molten iron The parametric classification of silicone content and procedural test carbon content refinement dynamic model, improves model controlling precision.(1) decarburization model Formula：
In formula：Ccal- real-time carbon content, %；C0The critical carbon content of molten steel of-carbon and oxygen balance, %；Ctsc-TSC tests carbon Content, %；Wst- total charge weight, t；V0Moment blowing oxygen quantity after-TSC tests, m3；V0tsc- TSC tests blowing oxygen quantity, m3；hi—i The unit oxygen content of type coolant；riThe coolant i, t added after-TSC tests；α, β-decarburization model return ginseng Number.
(2) temperature rising model formula：
In formula：T-real time temperature, DEG C TtscThe bath temperature of-TSC measurements, DEG C；V0Moment blowing oxygen quantity after-TSC tests, m3；V0tsc- TSC tests blowing oxygen quantity, m3；Wst- total charge weight, t；Ctsc-TSC tests carbon content, %；Ccal- in real time carbon contain Amount, %；C0The critical carbon content of molten steel of-carbon and oxygen balance, %；kiThe cooling energy coefficient of-i type coolants；ri- TSC is tested The coolant i, t added afterwards；γ, δ-temperature rising model regression parameter.
(3) dynamic model is classified：
(4) when the dynamic model stability contorting and smelting process of one heat steel water are stable, the heat carries out manual self study, And enter according to the molten iron silicon content and (what TSC represents, refers to procedural test, yes) procedural test (TSC) carbon content of reality The parameter renewal of the corresponding dynamic group number of row；
(5) after procedural test (TSC) terminates when smelting, dynamic model starts, and according to molten iron silicon content and procedural test (TSC) carbon content automatically selects corresponding model parameter α, β, γ, δ value of dynamic group number, carries out blowing control；
Decarburization model parameter alpha, β and temperature rising model parameter γ, δ correspond to respectively Alfa, Beta in dynamic parameter interface, Gamma、Delta。
Beneficial effects of the present invention are：
The present invention is carried out automatically according to the different condition and sublance procedural test (TSC) result of molten iron to converter dynamic model Classification, is realized under different situations, model selection Different Dynamic group number parameter, starts different decarburization programming rates, so as to improve The control accuracy of automatic Steelmaking dynamic model, reduces single decarburization programming rate and the deviation actually controlled, improves The carbon temperature hit rate of automatic Steelmaking.
Embodiment
Automatic Steelmaking dynamic model of the present invention includes decarburization model and temperature rising model, and the model includes self study process, Model Self-Learning process is mainly the automatic modification to decarburization model parameter and temperature rising model parameter；Pass through molten iron silicon content and mistake The parametric classification of journey test carbon content refinement dynamic model, improves model controlling precision.
(1) decarburization model formula：
In formula：Ccal- real-time carbon content, %；C0The critical carbon content of molten steel of-carbon and oxygen balance, %；Ctsc-TSC tests carbon Content, %；Wst- total charge weight, t；V0Moment blowing oxygen quantity after-TSC tests, m3；V0tsc- TSC tests blowing oxygen quantity, m3；hi—i The unit oxygen content of type coolant；riThe coolant i, t added after-TSC tests；α, β-decarburization model return ginseng Number.
(2) temperature rising model formula：
In formula：T-real time temperature, DEG C；TtscThe bath temperature of-TSC measurements, DEG C；V0Moment oxygen blast after-TSC tests Amount, m3；V0tsc- TSC tests blowing oxygen quantity, m3；Wst- total charge weight, t；Ctsc-TSC tests carbon content, %；Ccal- real-time carbon Content, %；C0The critical carbon content of molten steel of-carbon and oxygen balance, %；kiThe cooling energy coefficient of-i type coolants；ri- TSC is surveyed The coolant i, t added after examination；γ, δ-temperature rising model regression parameter.
(3) dynamic model is classified：
(4) when the dynamic model stability contorting and smelting process of one heat steel water are stable, the heat carries out manual self study, And updated according to the parameter of the corresponding dynamic group number of molten iron silicon content and procedural test TSC carbon contents progress of reality.
(5) after procedural test TSC terminates when smelting, dynamic model starts, and according to molten iron silicon content and procedural test TSC Carbon content automatically selects corresponding model parameter α, β, γ, δ value of dynamic group number, carries out blowing control.
Decarburization model parameter alpha, β and temperature rising model parameter γ, δ correspond to respectively Alfa, Beta in dynamic parameter interface, Gamma、Delta。
Embodiment 1：
Produce Smelting number 16DD4897, steel code ABHN31, molten iron Si：0.403%, TSC test carbon content 0.41%, 1626 DEG C of TSC test temperatures.Dynamic group number selects 5, therefore α, β, γ, δ value choose 9.593,9.136,13.392, -11.7 respectively. This heat charge weight Wst：208.6 tons, moment blowing oxygen quantity V after TSC tests0：Blowing oxygen quantity V when 9068m3, TSC are tested0tsc： 7788m3.The critical carbon content of molten steel C of carbon and oxygen balance0Take 0.01%.Because this heat does not add cold burden after TSC tests, therefore Material riIt is not involved in calculating.Known numeric value is substituted into formula：
Ccal=0.057%
T=1708 DEG C
Steel grade process control needs are met according to result of calculation.
Embodiment 2：
Produce Smelting number 16ED5007, steel code AB782A, molten iron Si：0.52%, TSC test carbon content 0.48%, 1611 DEG C of TSC test temperatures.Dynamic group number selects 6, thus α, β, γ, δ value choose 9.315 respectively, 10.752,12.194 ,- 15.17.This heat charge weight Wst：205.9 tons, moment blowing oxygen quantity V after TSC tests0：Blowing oxygen quantity when 8973m3, TSC are tested V0tsc：7661m3.The critical carbon content of molten steel C of carbon and oxygen balance0Take 0.01%.Because this heat does not add cold burden after TSC tests, Therefore material riIt is not involved in calculating.Known numeric value is substituted into formula：
Ccal=0.066%
T=1688 DEG C
Steel grade process control needs are met according to result of calculation.

Claims (1)

  1. A kind of 1. method for improving automatic Steelmaking dynamic model precision, it is characterised in that automatic Steelmaking dynamic model includes Decarburization model and temperature rising model, Model Self-Learning process are mainly that decarburization model parameter and the automatic of temperature rising model parameter are repaiied Change；The parametric classification of dynamic model is refined by molten iron silicon content and procedural test carbon content, improves model controlling precision； Specific method is：
    (1) decarburization model formula：
    <mrow> <msub> <mi>C</mi> <mrow> <mi>c</mi> <mi>a</mi> <mi>l</mi> </mrow> </msub> <mo>=</mo> <msub> <mi>C</mi> <mn>0</mn> </msub> <mo>+</mo> <mi>&amp;beta;</mi> <mo>&amp;times;</mo> <mi>ln</mi> <mo>{</mo> <mn>1</mn> <mo>+</mo> <mo>&amp;lsqb;</mo> <mi>exp</mi> <mrow> <mo>(</mo> <mfrac> <mrow> <msub> <mi>C</mi> <mrow> <mi>t</mi> <mi>s</mi> <mi>c</mi> </mrow> </msub> <mo>-</mo> <msub> <mi>C</mi> <mn>0</mn> </msub> </mrow> <mi>&amp;beta;</mi> </mfrac> <mo>)</mo> </mrow> <mo>-</mo> <mn>1</mn> <mo>&amp;rsqb;</mo> <mo>&amp;times;</mo> <mo>&amp;lsqb;</mo> <mi>&amp;alpha;</mi> <mo>&amp;times;</mo> <mfrac> <mrow> <msub> <mi>V</mi> <mn>0</mn> </msub> <mo>-</mo> <msub> <mi>V</mi> <mrow> <mn>0</mn> <mi>t</mi> <mi>s</mi> <mi>c</mi> </mrow> </msub> <mo>+</mo> <munder> <mi>&amp;Sigma;</mi> <mi>i</mi> </munder> <mrow> <mo>(</mo> <msub> <mi>h</mi> <mi>i</mi> </msub> <mo>&amp;times;</mo> <msub> <mi>r</mi> <mi>i</mi> </msub> <mo>)</mo> </mrow> </mrow> <msub> <mi>W</mi> <mrow> <mi>s</mi> <mi>t</mi> </mrow> </msub> </mfrac> <mo>&amp;rsqb;</mo> <mo>}</mo> </mrow>
    In formula：CcaL-real-time carbon content, %；C0The critical carbon content of molten steel of-carbon and oxygen balance, %；Ctsc-TSC test carbon contains Amount, %；Wst- total charge weight, t；V0Moment blowing oxygen quantity after-TSC tests, m3；V0tsc- TSC tests blowing oxygen quantity, m3；hi- i classes The unit oxygen content of type coolant, riThe coolant i, t added after-TSC tests；α, β-decarburization model regression parameter；
    (2) temperature rising model formula：
    <mrow> <mi>T</mi> <mo>=</mo> <msub> <mi>T</mi> <mrow> <mi>t</mi> <mi>s</mi> <mi>c</mi> </mrow> </msub> <mo>+</mo> <mi>&amp;gamma;</mi> <mo>&amp;times;</mo> <mrow> <mo>(</mo> <mfrac> <mrow> <msub> <mi>V</mi> <mn>0</mn> </msub> <mo>-</mo> <msub> <mi>V</mi> <mrow> <mn>0</mn> <mi>t</mi> <mi>s</mi> <mi>c</mi> </mrow> </msub> </mrow> <msub> <mi>W</mi> <mrow> <mi>s</mi> <mi>t</mi> </mrow> </msub> </mfrac> <mo>)</mo> </mrow> <mo>+</mo> <mi>&amp;delta;</mi> <mo>&amp;times;</mo> <mi>ln</mi> <mo>{</mo> <mfrac> <mrow> <mi>exp</mi> <mo>&amp;lsqb;</mo> <mrow> <mo>(</mo> <msub> <mi>C</mi> <mrow> <mi>t</mi> <mi>s</mi> <mi>c</mi> </mrow> </msub> <mo>-</mo> <msub> <mi>C</mi> <mn>0</mn> </msub> <mo>)</mo> </mrow> <mo>/</mo> <mi>&amp;beta;</mi> <mo>&amp;rsqb;</mo> <mo>-</mo> <mn>1</mn> </mrow> <mrow> <mi>exp</mi> <mo>&amp;lsqb;</mo> <mrow> <mo>(</mo> <msub> <mi>C</mi> <mrow> <mi>c</mi> <mi>a</mi> <mi>l</mi> </mrow> </msub> <mo>-</mo> <msub> <mi>C</mi> <mn>0</mn> </msub> <mo>)</mo> </mrow> <mo>/</mo> <mi>&amp;beta;</mi> <mo>&amp;rsqb;</mo> <mo>-</mo> <mn>1</mn> </mrow> </mfrac> <mo>}</mo> <mo>-</mo> <munder> <mi>&amp;Sigma;</mi> <mi>i</mi> </munder> <msub> <mi>k</mi> <mi>i</mi> </msub> <mo>&amp;times;</mo> <msub> <mi>r</mi> <mi>i</mi> </msub> </mrow>
    In formula：T-real time temperature, DEG C；
    TtscThe bath temperature of-TSC measurements, DEG C；
    V0Moment blowing oxygen quantity after-TSC tests, m33；
    V0tsc- TSC tests blowing oxygen quantity, m33；
    Wst- total charge weight, t；
    Ctsc-TSC tests carbon content, %；
    CcaL-real-time carbon content, %；
    C0The critical carbon content of molten steel of-carbon and oxygen balance, %；
    kiThe cooling energy coefficient of-i type coolants；
    riThe coolant i, t added after-TSC tests；
    γ, δ-temperature rising model regression parameter；
    (3) dynamic model is classified：
    (4) when the dynamic model stability contorting and smelting process of one heat steel water are stable, the heat carries out manual self study, and presses According to the facts the molten iron silicon content on border and procedural test TSC carbon contents carry out the parameter renewal of corresponding dynamic group number；
    (5) after procedural test TSC terminates when smelting, dynamic model starts, and contains according to molten iron silicon content and procedural test TSC carbon Amount automatically selects corresponding model parameter α, β, γ, δ value of dynamic group number, carries out blowing control；
    Decarburization model parameter alpha, β and temperature rising model parameter γ, δ correspond to respectively Alfa, Beta in dynamic parameter interface, Gamma, Delta。
CN201610802984.4A 2016-09-06 2016-09-06 A kind of method for improving automatic Steelmaking dynamic model precision Pending CN107794335A (en)

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CN111266405A (en) * 2020-02-27 2020-06-12 北京首钢股份有限公司 Plate and strip hot rolling process control method and control device

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CN1603424A (en) * 2003-09-29 2005-04-06 宝山钢铁股份有限公司 Bessemerizing control method based on intelligent compound dynamic model with sublance converter
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CN105200180A (en) * 2014-06-26 2015-12-30 南京梅山冶金发展有限公司 Automatic control method for converter oxygen lance

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Publication number Priority date Publication date Assignee Title
CN111266405A (en) * 2020-02-27 2020-06-12 北京首钢股份有限公司 Plate and strip hot rolling process control method and control device
CN111266405B (en) * 2020-02-27 2021-11-02 北京首钢股份有限公司 Plate and strip hot rolling process control method and control device

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