• Title of article

    Grindability soft-sensors based on lithological composition and on-line measurements

  • Author/Authors

    Casali، نويسنده , , A. and Gonzalez، نويسنده , , G. and Vallebuona، نويسنده , , G. and Perez، نويسنده , , C. and Vargas، نويسنده , , R.، نويسنده ,

  • Issue Information
    روزنامه با شماره پیاپی سال 2001
  • Pages
    12
  • From page
    689
  • To page
    700
  • Abstract
    The grinding efficiency evaluation can be performed through the comparison of the operational work index with the ore work index Wi. In this work, the development of an ore grindability soft-sensor (ESTMOL) is presented. The ore work index is estimated on the basis of its lithological composition. Also addressed is the experimental development of a lithological composition sensor (ACOLITO) for ores on a conveyor belt. The lithological composition is determined from image analysis on samples obtained by a color video camera. Finally, a global operational work index for a complete grinding section is defined here, and its on-line estimation (PREDIMOL) is addressed, including the required soft-sensors to overcome the measurement problems. The experimental work is done with samples obtained from the CODELCO - Andina grinding plant. All the sensors have given up to now good results.
  • Keywords
    NEURAL NETWORKS , Modelling , Grinding , Artificial Intelligence , on—line analysis
  • Journal title
    Minerals Engineering
  • Serial Year
    2001
  • Journal title
    Minerals Engineering
  • Record number

    2273685