• DocumentCode
    830266
  • Title

    Artificial Neural Network Analysis of Microwave Spectrometry on Pulp Stock: Determination of Consistency and Conductivity

  • Author

    Green, Eric C. ; Jean, Buford Randall ; Marks, R.J., II

  • Author_Institution
    Sch. of Law, Texas Univ., Austin, TX
  • Volume
    55
  • Issue
    6
  • fYear
    2006
  • Firstpage
    2132
  • Lastpage
    2135
  • Abstract
    A method for calibrating a microwave sensor is described. The method utilizes an artificial neural network trained to infer the consistency and conductivity of pulp stock slurry from the measured output spectrum of a microwave instrument. The method is both efficient and robust for extracting the multiple parameter information from the microwave signal output
  • Keywords
    microwave detectors; microwave spectrometers; neural nets; paper pulp; slurries; artificial neural network analysis; microwave instrument; microwave sensor; microwave signal output; microwave spectrometry; pulp stock slurry; Artificial neural networks; Conductivity measurement; Data mining; Instruments; Microwave measurements; Microwave sensors; Microwave theory and techniques; Robustness; Slurries; Spectroscopy; Microwave sensor; microwave spectrometry; neural network; pulp stock;
  • fLanguage
    English
  • Journal_Title
    Instrumentation and Measurement, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0018-9456
  • Type

    jour

  • DOI
    10.1109/TIM.2006.884284
  • Filename
    4014709