Paper
2 February 2009 Radiation acquisition and RBF neural network analysis on BOF end-point control
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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.
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Qi Zhao, Hong-yuan Wen, Mu-chun Zhou, and Yan-ru Chen "Radiation acquisition and RBF neural network analysis on BOF end-point control", Proc. SPIE 7160, 2008 International Conference on Optical Instruments and Technology: Optoelectronic Measurement Technology and Applications, 71602M (2 February 2009); https://doi.org/10.1117/12.807041
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KEYWORDS
Neural networks

Oxygen

Video

Control systems

Carbon

Evolutionary algorithms

Standards development

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