• DocumentCode
    2773602
  • Title

    Odor recognition systems for natural gas odorization monitoring

  • Author

    Zanchettin, Cleber ; Almeida, Leandro M. ; Menezes, Frederico D. ; Ludermir, Teresa B. ; Azevedo, Walter M.

  • Author_Institution
    Centre of Inf., Fed. Univ. of Pernambuco, Recife, Brazil
  • fYear
    2012
  • fDate
    10-15 June 2012
  • Firstpage
    1
  • Lastpage
    8
  • Abstract
    This paper presents a system consisting of physical sensors and intelligent software for the automatic identification of the concentration of natural gas odorants and details the development of the sensor and pattern recognition systems. The sensor system uses spectroscopic technology and the pattern recognition system uses wavelet and artificial neural network technology. The aim is to determine the concentration of a natural gas odorant in the environment and associate this concentration with the benchmark index, which measures the degree of human perception to the presence of gas in the environment. Experiments were conducted comparing the performance of the system with human performance, which is normally used to deal with this problem. The proposed system demonstrated promising results.
  • Keywords
    chemical engineering computing; chemical variables measurement; computerised monitoring; electronic noses; natural gas technology; neural nets; spectroscopy computing; wavelet transforms; artificial neural network technology; automatic natural gas odorant concentration identification; intelligent software; natural gas odorization monitoring; odor recognition systems; pattern recognition systems; physical sensors; spectroscopic technology; wavelet technology; Chemical sensors; Compounds; Natural gas; Optical sensors; Pattern recognition; Sensor systems;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks (IJCNN), The 2012 International Joint Conference on
  • Conference_Location
    Brisbane, QLD
  • ISSN
    2161-4393
  • Print_ISBN
    978-1-4673-1488-6
  • Electronic_ISBN
    2161-4393
  • Type

    conf

  • DOI
    10.1109/IJCNN.2012.6252601
  • Filename
    6252601