金属学报  2004, Vol. 40 Issue (4): 347-350

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高炉冶炼过程的混沌性辨识

郜传厚 刘祥官

浙江大学数学系; 杭州 310027

CHAOTIC IDENTIFICATION OF BF IRONMAKING PROCESS I. The Calculation of Saturated Correlative Dimension

GAO Chuanhou; LIU Xiangguan

Department of Mathematics; Zhejiang University; Hangzhou 310027

郜传厚; 刘祥官 . 高炉冶炼过程的混沌性辨识[J]. 金属学报, 2004, 40(4): 347-350 .
, . CHAOTIC IDENTIFICATION OF BF IRONMAKING PROCESS I. The Calculation of Saturated Correlative Dimension[J]. Acta Metall Sin, 2004, 40(4): 347-350 .

摘要 参考文献 相关文章 Metrics 全文: PDF(177 KB)   摘要: 以山东莱钢1号高炉和山西临钢6号高炉在线采集的[Si]时间序列为样本空间, 容量为1000炉数据, 利用相空间重构技术和G--P算法, 得出莱钢1号高炉和临 钢6号高炉冶炼过程的混沌吸引子的饱和关联维数分别约为3.36和3.12. 由高炉冶炼过程混沌吸引子的饱和关联维数存在且为分数, 可证明两座高炉冶 炼过程存在混沌特性. 关键词 ： 高炉冶炼,  时间序列,  相空间重构     Abstract：As [Si] time series of No.1 BF at Laiwu Iron and Steel Group Co. and No.6 BF at Linfen Iron and Steel Group Co. to be sample space, based on phase space reconstruction technology and G--P algorithm, the saturated correlative dimensions of chaotic attractor of Laiwu Blast Furnace Ironmaking Process and Linfen Blast Furnace Ironmaking Process are about 3.36 and 3.12, respectively. The existence of saturated correlative dimension with fraction value means there is chaos in both blast furnace ironmaking process. Key words： BF ironmaking    time series    phase space reconstruction 收稿日期: 2003-04-02      ZTFLH:  TF53   服务 把本文推荐给朋友 加入引用管理器 E-mail Alert RSS 作者相关文章 郜传厚 刘祥官 44.8K 链接本文: https://www.ams.org.cn/CN/      或      https://www.ams.org.cn/CN/Y2004/V40/I4/347 [1] Lorenz E N. J Atmospheric Sci, 1963; 20: 130 [2] Huang R S. Chaos and its Application. Hubei: Wuhan University Press, 2001: 112(黄润生.混沌及其应用.湖北:武汉大学出版社,2001:112) [3] Packard N H, Grutchfield J P, Farmer J D, Shaw R. S.Phys Rev Lett, 1980; 45(9) : 712 [4] Takens F. Lecture Notes in Mathematics, 1981; 898: 366 [5] Committee of National Natural Science Foundation of China. Automatic Science and Technology-The Research Report on Development Stratagem of Natural Science Subject. Beijing: Science Press, 1995: 132(国家自然科学基金委员会.自动化科学与技术-自然科学学科发展战略调研报告.北京:科学出版社, 1995:132) [6] Rosenstein M T, Collins J J, De Luca C J. Physica D,1994; 73(1) : 82 [7] Jang Y D, Wu Z Q, Chen Y Q, Jiang Y. J University ofScience and Technology Beijing, 2002; 24(3) : 295(江亚东,吴竹清,陈因颀,江月.北京科技大学学报,2002;24(3) :295) [8] Zhong K D, Hu G S. Digital Signal Disposal, Beijing: Ts-inghua University Press, 1988: 117(宗孔德,胡广书.数字信号处理,北京:清华大学出版社,1988:117) [9] Grassberger P, Procaccia I. Physica D, 1983; 9(3) : 189 [10] Liu X G, Liu X Z, Jiang M H, Wu X F, Chen Y M, Zhang X J, Chen T J. Metallurgical Industry Automation, 2002; 26(6) : 15(刘祥官,刘显著,蒋美华,吴晓峰,陈玉明,张晓军,陈铁军.冶金自动化,2002;26(6) :15) [11] Liu X G, Liu F. Optimization and Intelligent Control System of BF Ironmaking Process, Beijing: Metallurgy Industry Press, 2003: 51(刘祥官,刘 芳.高炉炼铁过程优化与智能控制系统,北京:冶金工业出版社,2003:51) [1] 侯自兵, 徐瑞, 常毅, 曹江海, 文光华, 唐萍. 高碳钢连铸方坯拉坯方向偏析C元素分布的时间序列波动特征[J]. 金属学报, 2018, 54(6): 851-858. [2] 杜鹤桂;邹安华. 高炉型含钛炉渣中MnO对TiO_2还原的影响[J]. 金属学报, 1991, 27(4): 73-79. Viewed Full text Abstract Cited   Shared      Discussed