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An integrated modeling method for prediction of sulfur content in agglomerate

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Abstract

Based on the idea of fusing modeling, an integrated prediction model for sintering process was proposed. A framework for sulfur content prediction was established, which integrated multi modeling ways together, including mathematical model combined with neural network(NN), rule model based on empirical knowledge and modelchoosing coordinator. Via metallurgic mechanism analysis and material balance computation, a mathematical model calculated the sulfur content in agglomerate by the material balance equation with some parameters predicted by NN method. In the other model, the relationship between sulfur content and key factors was described in the form of expert rules. The model-choosing coordinator based on fuzzy logic was introduced to decide the weight of result of each model according to process conditions. The model was tested by industrial application data and produced a relatively satisfactory prediction error. The model also preferably reflected the varying tendency of sulfur content in agglomerate as the evidence of its prediction performance.

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Authors and Affiliations

  1. College of Information Science & Engineering, Central South University, 410083, Changsha, China

    Chen Xiao-fang, Gui Wei-hua, Wang Ya-lin & Wu Min

Authors
  1. Chen Xiao-fang
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  2. Gui Wei-hua
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  3. Wang Ya-lin
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  4. Wu Min
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Additional information

Foundation item: The National 863 High Technology Program of China (No. 2001AA411040 & 2001AA414240)

Biography of the first author: CHEN Xiao-fang, doctoral candidate, born in 1975, majoring in process optimal control and modeling and genetic algorithm.

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Chen, Xf., Gui, Wh., Wang, Yl. et al. An integrated modeling method for prediction of sulfur content in agglomerate. J Cent. South Univ. Technol. 10, 145–150 (2003). https://doi.org/10.1007/s11771-003-0057-z

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  • DOI: https://doi.org/10.1007/s11771-003-0057-z

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