Multiscale dynamic analysis of blast furnace system based on intensive signal processing

被引:7
|
作者
Chu, Yanxu [1 ]
Gao, Chuanhou [1 ]
Liu, Xiangguan [1 ]
机构
[1] Zhejiang Univ, Dept Math, Hangzhou 310027, Peoples R China
基金
高等学校博士学科点专项科研基金; 中国国家自然科学基金;
关键词
blast furnaces; entropy; fractals; Hilbert transforms; Lyapunov methods; signal processing; EMPIRICAL MODE DECOMPOSITION; FLUIDIZED-BED HYDRODYNAMICS; PHASE-SPACE STRUCTURE; CHAOTIC TIME-SERIES; SILICON CONTENT; COMPUTATIONAL ALGORITHMS; MULTIRESOLUTION ANALYSIS; HAMMERSTEIN SYSTEMS; PREDICTION; DIMENSION;
D O I
10.1063/1.3458899
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
In this paper, the Hilbert-Huang transform method and time delay embedding method are applied to multiscale dynamic analysis on the time series of silicon content in hot metal collected from a medium-sized blast furnace with the inner volume of 2500 m(3). The results provide clear evidence of multiscale features in blast furnace ironmaking process. Ten intrinsic mode functions (IMFs) are decomposed from the silicon content time series; the presence of noninteger fractal dimension, positive finite Kolmogorov entropy, and positive finite maximum Lyapunov exponent are found in some IMF components. In addition, the coupling of subscale structures of blast furnace system is studied using the dimension of interaction dynamics and a robust algorithm for detecting interdependence. It is found that IMF(3) is the main driver in the coupling system IMF(2) and IMF(3) while for the coupling system IMF(3) and IMF(4) neither subsystem can act as the driver. All these provide a guideline for studying blast furnace ironmaking process with multiscale theory and methods, and may open way for more candidate tools to model and control blast furnace system in the future. (c) 2010 American Institute of Physics. [doi: 10.1063/1.3458899]
引用
收藏
页数:14
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