Journal of Northeastern University ›› 2010, Vol. 31 ›› Issue (12): 1737-1740.DOI: -

• OriginalPaper • Previous Articles     Next Articles

Supply-demand forecasting model of blast furnace gas in iron & steel works and its application

Zhang, Qi (1); Gu, Yan-Liang (2); Ti, Wei (1); Cai, Jiu-Ju (1)   

  1. (1) School of Materials and Metallurgy, Northeastern University, Shenyang 110004, China; (2) Shouqin Metal Materials Co. Ltd., Qinhuangdao 066326, China
  • Received:2013-06-20 Revised:2013-06-20 Online:2010-12-15 Published:2013-06-20
  • Contact: Zhang, Q.
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Abstract: With the blast furnace gas (BFG) system of an iron and steel works taken as an object, the relationship between the gas throughput and influencing factors on BFG generation/consumption was analyzed by grey correlation. A prediction model of BFG was developed on the basis of BP neural network for forecasting the supply and demand of BFG in the whole iron/steel-making process. The reasonability of the forecasting of BFG generation and consumption was discussed on various working conditions including normal operation and troubleshooting. The results showed that the forecasting model developed is of high precision with small errors and available to predict actually the BFG supply and demand so as to decrease the unnecessary BFG emission. The model is therefore able to lay a theoretical foundation to schedule the BFG utilization reasonably.

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