轉爐吹煉后期碳含量預報的改進指數模型

林文輝; 焦樹強; 孫建坤; 周凱嘯; 劉敏; 蘇醒; 劉青

doi:10.13374/j.issn2095-9389.2019.11.23.001

轉爐吹煉后期碳含量預報的改進指數模型

doi: 10.13374/j.issn2095-9389.2019.11.23.001

1.
北京科技大學鋼鐵冶金新技術國家重點實驗室，北京 100083
2.
江西新余鋼鐵集團有限公司技術中心，新余 338001
3.
江西新余鋼鐵集團有限公司第一煉鋼廠，新余 338001

基金項目: 國家自然科學基金資助項目(51974023)；江西省重點研發計劃資助項目(20171ACE50020)

詳細信息

通訊作者:
E-mail: qliu@ustb.edu.cn

中圖分類號: TF711
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出版歷程
- 收稿日期: 2019-11-23
- 刊出日期: 2020-07-01

Modified exponential model for carbon prediction in the end blowing stage of basic oxygen furnace converter

1.
State Key Laboratory of Advanced Metallurgy, University of Science and Technology Beijing, Beijing 100083, China
2.
Technology and Research Center, Xinyu Iron and Steel Group Co. Ltd., Xinyu 338001, China
3.
No.1 Steelmaking Plant, Xinyu Iron and Steel Group Co. Ltd., Xinyu 338001, China

More Information

Corresponding author: E-mail: qliu@ustb.edu.cn

摘要

摘要: 介紹了幾種主要的轉爐煙氣分析碳含量預報模型，并分析了其中的指數衰減模型及其三種改進算法的基本原理和優缺點。在綜合三種模型優點的基礎上，提出了基于“極限碳含量擬合+曲線同步更新”算法的改進指數模型。首先，利用歷史爐次吹煉后期的脫碳氧效率和碳含量數據，通過指數擬合得到“歷史脫碳曲線”和極限碳含量參數；其次，使用當前爐次吹煉中期的最大脫碳氧效率值對“歷史脫碳曲線”的特征參數進行替換，得到當前爐次吹煉后期的“參考脫碳曲線”，再對其進行歸一化處理，得到歸一化的“參考脫碳曲線”；然后，采用多點校正的方法，計算當前爐次吹煉至各等距離校正點時“參考脫碳曲線”的脫碳量，并根據計算脫碳量與轉爐實際脫碳量的偏差，對熔池碳含量及脫碳曲線參數進行計算與校正，得到“計算脫碳曲線”；最后，通過逐次迭代計算對“參考脫碳曲線”和“計算脫碳曲線”進行同步更新，進而實現對轉爐吹煉后期熔池碳含量的精準預報。研究表明，改進的指數模型具有較高的準確率，終點碳含量預報誤差在±0.02%范圍內的命中率達到90%。
- 煙氣分析 /
- 碳含量預報 /
- 指數衰減模型 /
- 脫碳氧效率 /
- 極限碳含量 /
- 曲線同步更新
Abstract: Several common models for carbon prediction were discussed based on an off-gas analysis of the basic oxygen furnace (BOF) process, and the basic principles, advantages and disadvantages of three exponential decay models with different correction algorithm were analyzed respectively. An improved exponential model of “critical carbon content fitting + update curves simultaneously” algorithm was established by combining the advantages of previous algorithms. Firstly, the historical decarburization curve in the end blowing stage and the critical carbon content in the bath were obtained by exponentially fitting the decarburization data of historical heats. Secondly, the reference decarburization curve was obtained by replacing the corresponding parameter of the historical decarburization curve with the maximum specific decarburization rate in the middle blowing stage of the real-time heat. Subsequently, the specific decarburization rates of the historical decarburization curve and the reference decarburization curve were converted to dimensionless values within the range of 0 to 1 by normalizing. Then, a multi-point correction method was used to correct the calculation results of the carbon content in the bath and repeatedly modify the key parameters of the calculated decarburization curve, according to the deviation of the removed carbon amount between the normalized reference curve and the actual process. The key parameters of the calculated and the reference decarburization curves were updated simultaneously after each calculation step, and the calculation error of the carbon content prediction decreased gradually through iterative calculation. Finally, the carbon content in the bath were precisely predicted in the end blowing stage of the BOF process. Plant trials were carried out in a BOF converter to demonstrate the performance of the proposed models. The results show that the new model exhibits better adaptability and higher accuracy than the other ones. The hit ratio of the new model to predict the end-point carbon content reaches 90% within a tolerance of ±0.02%.
- off-gas analysis /
- carbon prediction /
- exponential decay model /
- specific decarburization rate /
- critical carbon content /
- update curves simultaneously

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圖 1 轉爐吹煉過程典型的煙氣成分變化曲線

Figure 1. Typical variation curve of BOF off-gas composition

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圖 2 轉爐吹煉后期典型脫碳曲線

Figure 2. Typical decarburization curve in the end-blowing stage of BOF

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圖 3 三種指數衰減模型校正算法示意圖

Figure 3. Correction algorithm schematic of three exponential decay models

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圖 4 等距離多點連續校正算法

Figure 4. Algorithm of isometric multi-point correction

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圖 5 采用不同C₀設定方法得到的歷史脫碳曲線

Figure 5. Historical decarburization curves with different C₀ values

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圖 6 改進算法的計算脫碳曲線

Figure 6. Calculated decarburization curves using the improved algorithm

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圖 7 不同模型預測誤差分布。（a）積分模型；（b）三次方模型；（c）固定C₀且曲線不更新的指數模型；（d）固定C₀且曲線更新的指數模型；（e）擬合C₀且曲線不更新的指數模型；（f）擬合C₀且曲線更新的指數模型

Figure 7. Prediction error distribution of the different models: (a) integral model; (b) cubic model; (c) exponential model with fixed C₀ but without updated curve; (d) exponential model with fixed C₀ and updated curve; (e) exponential model with fitted C₀ but without updated curve; (f) exponential model with fitted C₀ and updated curve

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表 1 “極限碳含量擬合+曲線同步更新”算法改進模型驗證數據

Table 1. Validation of proposed model based on improved algorithm %

Heat No.	Predicted end-point carbon content					Actual end-point carbon content
Heat No.	Curve updated for 1 time	Curve updated for 2 times	Curve updated for 3 times	…	Curve updated for n times	Actual end-point carbon content
H-1	0.0463	0.0519	0.0538	…	0.0558	0.0609
H-2	0.0412	0.0424	0.0462	…	0.0550	0.0501
H-3	0.0491	0.0529	0.0536	…	0.0559	0.0530
H-4	0.0450	0.0487	0.0510	…	0.0556	0.0591
H-5	0.0543	0.0619	0.0553	…	0.0567	0.0615
H-6	0.0502	0.0470	0.0614	…	0.0554	0.0625
H-7	0.0589	0.0571	0.0540	…	0.0563	0.0612
H-8	0.0686	0.0568	0.0565	…	0.0563	0.0485
H-9	0.0414	0.0452	0.0520	…	0.0582	0.0865
H-10	0.0434	0.0447	0.0505	…	0.0552	0.0673

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表 2 幾種模型終點碳含量預測命中率

Table 2. Hit ratios of the different models

Model	Hit ratio of end-point carbon prediction/%(ΔC≤±0.02%)	Notes
Integral model	72.50	Fig.7（a）
Cubic model	85.00	Fig.7（b）
Exponential model	85.00	Fig.7（c）, fixed ${C_0}$, without updated curve
Exponential model	87.50	Fig.7（d）, fitted ${C_0}$, without updated curve
Modified exponential model proposed in current study	88.75	Fig.7（e）, fixed ${C_0}$, with updated curve
Modified exponential model proposed in current study	90.00	Fig.7（f）, fitted ${C_0}$, with updated curve

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