DocumentCode :
2652487
Title :
Application of Clustering Algorithm to Blast Furnace Expert System
Author :
Hongwei, Guo ; Jianliang, Zhang ; Haibin, Zuo ; Xu, Zhang
Author_Institution :
Univ. of Sci. & Technol. Beijing, Beijing
fYear :
2009
fDate :
22-24 Jan. 2009
Firstpage :
171
Lastpage :
175
Abstract :
Focusing on the complex, nonlinear and great hysteresis characteristics in the iron making process of blast furnace, the mathematical model of metallurgical can not satisfy the requirement of guiding operation, so the expert system based on the blast furnace expertspsila knowledge and experience developed rapidly. However, because of the limitation of the expertspsila knowledge and experience, this paper applied clustering algorithm to the development of blast furnace expert system. Based on the clustering algorithm, this system developed not only operational furnace profile management model, but also two methods of gas flow distribution pattern recognition to cross thermometric and top infrared imaging. This new system had achieved satisfying results when applied in blast furnaces of WISGCO, Jinan steel and Ansteel.
Keywords :
blast furnaces; expert systems; hysteresis; image recognition; infrared imaging; pattern clustering; production engineering computing; steel industry; Ansteel; Jinan steel; WISGCO; blast furnace expert system; clustering algorithm; gas flow distribution pattern recognition; hysteresis characteristics; iron making process; operational furnace profile management model; thermometric imaging; top infrared imaging; Blast furnaces; Clustering algorithms; Expert systems; Fluid flow; Hysteresis; Infrared imaging; Iron; Mathematical model; Pattern recognition; Thermal management; blast furnace; data mining; expert system;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Advanced Computer Control, 2009. ICACC '09. International Conference on
Conference_Location :
Singapore
Print_ISBN :
978-1-4244-3330-8
Type :
conf
DOI :
10.1109/ICACC.2009.80
Filename :
4777330
Link To Document :
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