Minimizing profile error when estimating the sieve-size distribution of iron ore pellets using ordinal logistic regression
作者: Tobias AnderssonMatthew J. Thurley
作者单位: 1Luleå University of Technology, Department of Computer Science & Electrical Engineering, Luleå SE-97187, Sweden
刊名: Powder Technology, 2010, Vol.206 (3), pp.218-226
来源数据库: Elsevier Journal
DOI: 10.1016/j.powtec.2010.09.021
关键词: Particle size and shapeClassificationImage analysis
原始语种摘要: Abstract(#br)Size measurement of pellets in industry is usually performed by manual sampling and sieving techniques. Automatic on-line analysis of pellet size based on image analysis techniques would allow non-invasive, frequent and consistent measurement. We evaluate the statistical significance of the ability of commonly used size and shape measurement methods to discriminate among different sieve-size classes using multivariate techniques. Literature review indicates that earlier works did not perform this analysis and selected a sizing method without evaluating its statistical significance. Backward elimination and forward selection of features are used to select two feature sets that are statistically significant for discriminating among different sieve-size classes of pellets. The...
全文获取路径: Elsevier  (合作)
影响因子:2.024 (2012)

  • estimating 价值估计
  • ordinal 序数
  • sieve 筛子
  • statistical 统计的
  • regression 海退
  • selection 选择
  • unexpected 突然的
  • multivariate 多元
  • feature 结构元件
  • logistic 暹辑斯谛