電弧爐煉鋼爐渣成分實時預報模型

楊凌志; 薛波濤; 宋景凌; 魏光升; 郭宇峰; 謝鑫; 劉全勝

doi:10.13374/j.issn2095-9389.2020.04.05.s12

電弧爐煉鋼爐渣成分實時預報模型

doi: 10.13374/j.issn2095-9389.2020.04.05.s12

1.
中南大學資源加工與生物工程學院，長沙 410083
2.
衡陽華菱鋼管有限公司，衡陽 421000
3.
北京科技大學冶金與生態工程學院，北京 100083

基金項目: 國家自然科學基金資助項目（51804345）；中國博士后科學基金資助項目（2020T130053，2019M660459）

詳細信息

通訊作者:
E-mail：weiguangsheng@ustb.edu.cn

中圖分類號: TG741.5
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出版歷程
- 收稿日期: 2020-04-05
- 刊出日期: 2020-12-25

Real-time prediction model of slag composition in electric arc furnace steelmaking

1.
School of Minerals Processing and Bioengineering, Central South University, Changsha 410083, China
2.
Hengyang Valin Steel Tube Co., Ltd., Hengyang 421000, China
3.
School of Metallurgical and Ecological Engineering, University of Science and Technology Beijing, Beijing 100083, China

More Information

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

摘要

摘要: 為了實現冶煉過程中對爐渣成分的實時預測，給電弧爐煉鋼過程中加料等工藝操作提供幫助，對影響爐內爐渣成分的因素（爐內反應、加料與流渣）進行了研究，構建了電弧爐煉鋼爐渣成分實時預報模型。結果顯示，該模型能夠實時預測爐內爐渣質量和成分變化，預報爐內鐵元素氧化狀況，可為冶煉過程中添加輔料與流渣等工藝操作提供指導作用。通過與現場爐渣取樣檢測結果進行對比，得到爐渣中CaO、SiO₂和FeO實測成分與模型預測成分的平均相對誤差分別為12.66%、11.17%和19.16%。
- 電弧爐煉鋼 /
- 爐渣成分 /
- 實時預測 /
- 爐內反應 /
- 加料 /
- 流渣
Abstract: To realize the real-time prediction of slag composition in the smelting process and provide the assistance to the operations in electric arc furnace (EAF) steelmaking process such as charging, the influence factors on the slag composition in the furnace (furnace reaction, charging, and slag overflowing) were studied, and the real-time prediction model of slag composition in EAF steelmaking process was established. In the results, the model could predict the slag quality, the slag composition, and the oxidation status of Fe element in the furnace in real time, providing the guidance for the auxiliary material charging and the slag flowing in the smelting process. Compared with the slag sampling results, the average relative errors of CaO, SiO₂, and FeO content in the slag between the actual measurement and the model predicted values were 12.66%, 11.17%, and 19.16%, respectively.
- electric arc furnace steelmaking /
- slag composition /
- real-time prediction /
- furnace reaction /
- charging /
- slag overflowing

HTML全文

圖 1 鋼液中元素選擇性氧化機理

Figure 1. Selective oxidation mechanism of elements in the liquid steels

下載: 全尺寸圖片幻燈片

圖 2 選擇性氧化模型計算流程

Figure 2. Calculation process of the selective oxidation model

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圖 3 爐渣溢出過程拍攝示意圖

Figure 3. Shooting schematic diagram of the slag overflowing

下載: 全尺寸圖片幻燈片

圖 4 電弧爐煉鋼過程輔料加入示意圖

Figure 4. Schematic diagram of the auxiliary material charging in EAF steelmaking process

下載: 全尺寸圖片幻燈片

圖 5 電弧爐煉鋼爐渣成分實時預報模型理論結構圖

Figure 5. Theoretical structure diagram of the real-time prediction model of slag composition in EAF steelmaking

下載: 全尺寸圖片幻燈片

圖 6 模型計算流程圖

Figure 6. Flow chart of the model calculation

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圖 7 模型計算界面

Figure 7. Calculation interface of model

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圖 8 模型預測爐渣組元質量分數

Figure 8. Prediction results of the slag mass fraction by model

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圖 9 模型預測爐渣各組元質量

Figure 9. Prediction results of the slag mass by model

下載: 全尺寸圖片幻燈片

表 1 模型預測與實驗結果相對誤差

Table 1. Relative error between the model prediction and the experimental results

Time	Type	CaO		SiO₂		FeO conversion
Time	Type	Mass fraction / %	Error, δ/ %	Mass fraction / %	Error, δ/ %	Mass fraction / %	Error, δ/ %
Early	Detection	26.16	5.96	17.19	3.40	47.53	3.50
Early	Prediction	27.72	5.96	16.61	3.40	45.83	3.50
Middle	Detection	36.78	4.00	11.15	25.50	39.28	0.50
Middle	Prediction	38.14	4.00	13.99	25.50	39.07	0.50
Later	Detection	31.66	19.00	6.85	16.10	52.12	5.20
Later	Prediction	37.69	19.00	7.95	16.10	49.36	5.20

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