• DocumentCode
    1536969
  • Title

    Application of an Optical Fiber Sensor on the Determination of Sucrose and Ethanol Concentrations in Process Streams and Effluents of Sugarcane Bioethanol Industry

  • Author

    Fujiwara, Eric ; Ono, Eduardo ; Suzuki, Carlos Kenichi

  • Author_Institution
    Lab. of Photonic Mater. & Devices, State Univ. of Campinas, Campinas, Brazil
  • Volume
    12
  • Issue
    9
  • fYear
    2012
  • Firstpage
    2839
  • Lastpage
    2843
  • Abstract
    In this paper, the measurement of process streams and effluents from the sugar-ethanol industry using an optical fiber sensor based on the Fresnel reflection principle is reported. Firstly, binary sucrose-water and ethanol-water solutions with predetermined concentrations were measured for calibration purposes. Secondly, the coproducts from various processing stages were analyzed in order to identify the sucrose or ethanol content. The measured data were processed by an artificial neural network model, which correlated the reflected intensity values to the sample concentration. The absolute error was calculated by a comparison between the nominal concentration values obtained by the plant laboratory analysis and the sensor response, yielding errors ≤ 3& wt% and ≤ 5.1 vol% for the sucrose and ethanol contents, respectively. The fiber sensor has the potential to provide reliable results even for samples with more complex compositions than pure sucrose or ethanol solutions, with perspectives of application on the several stages of the plant facility.
  • Keywords
    biofuel; biotechnology; calibration; chemical sensors; chemical variables measurement; computerised instrumentation; fibre optic sensors; light reflection; neural nets; production engineering computing; sugar industry; Fresnel reflection principle; absolute error calculation; artificial neural network model; binary sucrose-water solution; calibration; ethanol concentration; ethanol-water solution; optical fiber sensor; plant laboratory analysis; process stream measurement; sucrose determination; sugarcane bioethanol industry; Artificial neural networks; Ethanol; Optical fiber networks; Optical fiber sensors; Optical fibers; Refractive index; Sugar; Bioethanol; chemical industry; optical fiber sensors; reflectometry; sugar industry;
  • fLanguage
    English
  • Journal_Title
    Sensors Journal, IEEE
  • Publisher
    ieee
  • ISSN
    1530-437X
  • Type

    jour

  • DOI
    10.1109/JSEN.2012.2204246
  • Filename
    6215009