Papers by Keyword: Blast Furnace Raceway

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Authors: Bo Yang, Ning Li, Liang Lei, Xue Wang
Abstract: Three-layer BP neural network, particularly using Levenberg-Marquardt back-propagation with early stopping algorithm, is widely used in curve fitting, attributing to its fast speed and free from over-fitting. Hence, the trained network by Levenberg-Marquardt back-propagation was used for curve fitting of the radiation spectrum of blast furnace raceway. The results showed that Levenberg-Marquardt back-propagation with early stopping algorithm presented a better fitting ability. Additionally, the results of spectral fitting model showed that the blast furnace raceway had an effective radiation spectrum in the wavelength range from 420nm to 880nm, where the raceway could be considered as the gray body radiation.
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Authors: Xiao Qin Liu, Sheng Li Wu, Cheng Song Liu, Jian Xu, Chang Liang Fu, Ming Yin Kou
Abstract: The shape feature of tuyere raceway possesses an important effect on hearth state and BF operation. With analyzing channel for permeating gas and liquid in the hearth section in the position of tuyere raceway, it can be seen that the channel amount is mainly determined by section of raceway and section between the raceways. On the basic of theoretical and statistical analysis on practical production data, the new evaluation index of indicating tuyere raceway shape feature was proposed. In the condition of high blast volume, the new index AITR tended to increase and BF production was improved gradually as blast volume increases. The good evaluation character of this new index AITR has been validated with practical production data in this work.
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