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Proceedings Paper

Radiation acquisition and RBF neural network analysis on BOF end-point control
Author(s): Qi Zhao; Hong-yuan Wen; Mu-chun Zhou; Yan-ru Chen
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Paper Abstract

There are some problems in Basic Oxygen Furnace (BOF) steelmaking end-point control technology at present. A new BOF end-point control model was designed, which was based on the character of carbon oxygen reaction in Basic Oxygen Furnace steelmaking process. The image capture and transformation system was established by Video for Windows (VFW) library function, which is a video software development package promoted by Microsoft Corporation. In this paper, the Radial Basic Function (RBF) neural network model was established by using the real-time acquisition information. The input parameters can acquire easily online and the output parameter is the end-point time, which can compare with the actual value conveniently. The experience results show that the predication result is ideal and the experiment results show the model can work well in the steelmaking adverse environment.

Paper Details

Date Published: 3 February 2009
PDF: 4 pages
Proc. SPIE 7160, 2008 International Conference on Optical Instruments and Technology: Optoelectronic Measurement Technology and Applications, 71602M (3 February 2009); doi: 10.1117/12.807041
Show Author Affiliations
Qi Zhao, Nanjing Univ. of Science & Technology (China)
Hong-yuan Wen, Nanjing Univ. of Science & Technology (China)
Mu-chun Zhou, Nanjing Univ. of Science & Technology (China)
Yan-ru Chen, Nanjing Univ. of Science & Technology (China)


Published in SPIE Proceedings Vol. 7160:
2008 International Conference on Optical Instruments and Technology: Optoelectronic Measurement Technology and Applications

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