Analysis and pattern recognition of blast furnace burden surface based on multi-radar data

Author

Zhou, Xiang ; Li, Xiaoli ; Liu, Dexin ; Yin, Yixin ; Chen, Xianzhong ; Hou, Qingwen

Author_Institution

Dept. of Autom., Univ. of Sci. & Technol. Beijing, Beijing, China

fYear

2010

fDate

13-15 Aug. 2010

Firstpage

286

Lastpage

291

Abstract

Iron making is the first stage and also an important part in steel making process, which will bring the problem of energy efficiency and economic benefits. In this process, the distribution of the blast burden impacts greatly on the production of BF (blast furnace). Therefore, the prediction of furnace burden distribution in furnace throat will play an important role in the control strategy of furnace burden. Based on the data from the multi-radar, the blast burden curve can be formed. Feature extraction and classification based on different curves (i.e. different pattern) can be made by using BP neural networks. The work proposed in this paper will be a guidance for the future research of burden surface based on the data of phased-array radar.

Keywords

backpropagation; blast furnaces; feature extraction; neural nets; phased array radar; production engineering computing; steel manufacture; BP neural networks; blast furnace burden surface; feature extraction; furnace burden distribution prediction; furnace throat; iron making; multiradar data; pattern recognition; phased-array radar data; steel making process; Blast furnaces; Feature extraction; Radar imaging; Surface treatment; Turning;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Control and Information Processing (ICICIP), 2010 International Conference on

Conference_Location

Dalian

Print_ISBN

978-1-4244-7047-1

Type

conf

DOI

10.1109/ICICIP.2010.5564323

Filename

5564323