Journal of Northeastern University Natural Science ›› 2015, Vol. 36 ›› Issue (7): 952-956.DOI: 10.12068/j.issn.1005-3026.2015.07.009

• Materials & Metallurgy • Previous Articles     Next Articles

Evaluation of Blast Furnace Operation Profile Based on Principal Component Analysis (PCA)

YAN Bing-ji, ZHANG Jian-liang, GUO Hong-wei, CAO Ying-jie   

  1. School of Metallurgical and Ecological Engineering, University of Science and Technology Beijing, Beijing 100083, China.
  • Received:2014-07-21 Revised:2014-07-21 Online:2015-07-15 Published:2015-07-15
  • Contact: GUO Hong-wei
  • About author:-
  • Supported by:
    -

Abstract: Aiming at solving the existing problems that there are many indexes used in operation profile evaluation and there are many overlaps among them, an improved method based on principal component analysis (PCA) was proposed. The method can generate three new core indicators from traditional indexes in operation profile evaluation (coke ratio, coal ratio, comprehensive coke ratio, utilization coefficient and the silicon content in hot metal). The new core indicators are independent of each other in space, and can represent the original ones. The above problems are thus solved. The improved model of operation profile evaluation was developed and applied to No.1 1780m3 blast furnace in Guofeng Steel, and the main categories of operation profile of the blast furnace were determined and evaluated.

Key words: operation profile, clustering, production indexes, principal component analysis, comprehensive evaluation

CLC Number: