• DocumentCode
    702131
  • Title

    Inferential sensor for the olive oil industry

  • Author

    Bordons, Carlos ; Zafra, Manuel L.

  • Author_Institution
    Depto. de Ingeniería de Sistemas y Automática, Escuela Superior de Ingenieros, Camino de los Descubrimientos s/n, 41092-Sevilla (Spain)
  • fYear
    2003
  • fDate
    1-4 Sept. 2003
  • Firstpage
    1940
  • Lastpage
    1946
  • Abstract
    This paper shows an inferential sensor that has been developed to be used in the olive oil industry. This sensor has been designed to measure two variables that appear in the elaboration of olive oil in a mill which are very difficult to be measured on line by a physical sensor. The knowledge of these variables on line is crucial for the optimal operation of the process, since they provide the state of the plant, allowing the development of a control strategy that can improve the quality and yield of the product. This sensor measures variables that in other case should come form laboratory analysis with large processing delays or from very expensive and difficult to use on line analysers. The sensor has been devised based upon artificial Neural Networks (NN) and has been implemented as a routine running on a Programmable Logic Controller (PLC) and successfully tested on a real plant.
  • Keywords
    Artificial neural networks; Delays; Estimation; Moisture; Temperature measurement; Training; Food Industry; Inferential Sensors; Neural Networks;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    European Control Conference (ECC), 2003
  • Conference_Location
    Cambridge, UK
  • Print_ISBN
    978-3-9524173-7-9
  • Type

    conf

  • Filename
    7085250