模糊C均值聚類算法在高爐料面分類中的應用

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模糊C均值聚類算法在高爐料面分類中的應用

劉德馨, 李曉理, 周翔, 陳先中, 尹怡欣, 侯慶文

文章導航 > 工程科學學報 > 2012 > 34(6): 683-690

劉德馨, 李曉理, 周翔, 陳先中, 尹怡欣, 侯慶文. 模糊C均值聚類算法在高爐料面分類中的應用[J]. 工程科學學報, 2012, 34(6): 683-690. doi: 10.13374/j.issn1001-053x.2012.06.015

引用本文:

劉德馨, 李曉理, 周翔, 陳先中, 尹怡欣, 侯慶文. 模糊C均值聚類算法在高爐料面分類中的應用[J]. 工程科學學報, 2012, 34(6): 683-690. doi: 10.13374/j.issn1001-053x.2012.06.015

LIU De-xin, LI Xiao-li, ZHOU Xiang, CHEN Xian-zhong, YIN Yi-xin, HOU Qing-wen. Application of the fuzzy C-means clustering algorithm in blast furnace burden surface identification[J]. Chinese Journal of Engineering, 2012, 34(6): 683-690. doi: 10.13374/j.issn1001-053x.2012.06.015

Citation:

LIU De-xin, LI Xiao-li, ZHOU Xiang, CHEN Xian-zhong, YIN Yi-xin, HOU Qing-wen. Application of the fuzzy C-means clustering algorithm in blast furnace burden surface identification[J]. Chinese Journal of Engineering, 2012, 34(6): 683-690. doi: 10.13374/j.issn1001-053x.2012.06.015

劉德馨, 李曉理, 周翔, 陳先中, 尹怡欣, 侯慶文. 模糊C均值聚類算法在高爐料面分類中的應用[J]. 工程科學學報, 2012, 34(6): 683-690. doi: 10.13374/j.issn1001-053x.2012.06.015

引用本文:

劉德馨, 李曉理, 周翔, 陳先中, 尹怡欣, 侯慶文. 模糊C均值聚類算法在高爐料面分類中的應用[J]. 工程科學學報, 2012, 34(6): 683-690. doi: 10.13374/j.issn1001-053x.2012.06.015

LIU De-xin, LI Xiao-li, ZHOU Xiang, CHEN Xian-zhong, YIN Yi-xin, HOU Qing-wen. Application of the fuzzy C-means clustering algorithm in blast furnace burden surface identification[J]. Chinese Journal of Engineering, 2012, 34(6): 683-690. doi: 10.13374/j.issn1001-053x.2012.06.015

Citation:

LIU De-xin, LI Xiao-li, ZHOU Xiang, CHEN Xian-zhong, YIN Yi-xin, HOU Qing-wen. Application of the fuzzy C-means clustering algorithm in blast furnace burden surface identification[J]. Chinese Journal of Engineering, 2012, 34(6): 683-690. doi: 10.13374/j.issn1001-053x.2012.06.015

模糊C均值聚類算法在高爐料面分類中的應用

doi: 10.13374/j.issn1001-053x.2012.06.015

劉德馨^1,2,
李曉理^1,2, ,,
周翔^1,2,
陳先中^1,2,
尹怡欣^1,2,
侯慶文^1,2

1. 北京科技大學自動化學院, 北京 100083;
2. 北京科技大學鋼鐵流程先進控制教育部重點實驗室, 北京 100083

基金項目:

北京市優秀人才培養資助項目(2009D013001000016)

國家自然科學基金資助項目(61074055)

國家高技術研究發展計劃資助項目(2009AA04Z156)

北京市教委共建重點學科資助項目(xk100080537)

通訊作者:
李曉理,E-mail:lixiaoli@hotmail.com

中圖分類號: TF325.3;TP273⁺.4
計量
- 文章訪問數: 143
- HTML全文瀏覽量: 20
- PDF下載量: 5
- 被引次數: 0
出版歷程
- 收稿日期: 2011-04-06
- 網絡出版日期: 2021-07-30

Application of the fuzzy C-means clustering algorithm in blast furnace burden surface identification

LIU De-xin^1,2,
LI Xiao-li^{1,2
, ,},
ZHOU Xiang^1,2,
CHEN Xian-zhong^1,2,
YIN Yi-xin^1,2,
HOU Qing-wen^1,2

1. School of Automation, University of Science and Technology Beijing, Beijing 100083, China;
2. Key Laboratory of Advanced Control of Iron and Steel Process (Ministry of Education), University of Science and Technology Beijing, Beijing 100083, China

摘要: 通過對多雷達掃描得到的高爐料面進行數據處理,根據數據的特征,分別采用模糊C均值聚類和特征加權模糊C均值聚類算法對料面數據進行分類,建立標準料面模型庫.再通過模糊模式識別中貼近度的方法把待分類的目標料面與模型庫相匹配,為后續的布料控制提供依據.該算法在某2500 m³高爐上進行了實驗,取得良好的效果.仿真結果表明了其有效性.
- 高爐 /
- 布料 /
- 模糊聚類 /
- 聚類算法 /
- 模式識別
Abstract: Blast furnace burden surface data derived from multi radars were processed. Fuzzy C-means and feature weighted fuzzy C-means clustering were applied to identify the burden surface data according to the data information, and a standard burden surface model database was set up. Each target burden surface was matched with the model database by using the method of nearness in fuzzy pattern recognition, and this provides a basis for the next burden surface control. The algorithm was carried out into a 2 500 m³ blast furnace, and the control effect has been improved. The simulation results show the effectiveness of the proposed method.
- blast furnaces /
- burden /
- fuzzy clustering /
- clustering algorithms /
- pattern recognition

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