Artificial Neural Network Approach for Evaluation of Gas Sensor Array Responses

  • Iwona Rutkowska
  • Barbara Flisowska-Wiercik
  • Przemysław M. Szecówka
  • Andrzej Szczurek
Conference paper
Part of the Advances in Intelligent and Soft Computing book series (AINSC, volume 95)


Neural processing was applied for evaluation of gas sensors responses. Thin layer type gas sensors based on TiO2 sensing film were fabricated using sol-gel technology. Several variants of these devices were obtained by different technology parameters. They were characterized by exposition to air containing various volatile organic compounds. Neural processing was applied for classification of compounds according to the chemical function group and number of carbon atoms in molecules. Different statistics of correct classification obtained for the two variants deliver significant knowledge about sensing mechanisms and quality of information that may be extracted from sensor responses.


Sensor Array Neural Processing Neural Network Approach Diaphragm Pump Sensor Reaction 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Kozłowska, K., Łukowiak, A., Szczurek, A., Dudek, K., Maruszewski, K.: Sol gel coatings for electrical gas sensors. Optica Applicata 35, 783–790 (2005)Google Scholar
  2. 2.
    Łukowiak, A., Kozłowska, K., Urbański, K., Szczurek, A., Dudek, K., Maruszewski, K.: The application of an artificial neural network in the processing of output signals from a gas sensor with sol-gel-derived TiO2 film. Materials Science - Poland 25, 861–868 (2007)Google Scholar
  3. 3.
    Łukowiak, A., Maciejewska, M., Szczurek, A., Maruszewski, K.: Application of titania thin film for the discrimination between diesel fuel and heating oil. Thin Solid Films 515, 7005–7010 (2007)CrossRefGoogle Scholar
  4. 4.
    Moseley, P.T., Norris, J., Williams, D.: Techniques and mechanisms of gas sensing. IOP Publishing Ltd., New York (1991)Google Scholar
  5. 5.
    Pardo, M., Kwong, L.G., Sberveglieri, G., Brubaker, K., Schneider, J.F., Penrose, W.R., Stetter, J.R.: Data analysis for a hybrid sensor array. Sensors and Actuators B 106, 136–143 (2005)CrossRefGoogle Scholar
  6. 6.
    Sberveglieri, G.: Gas sensors. Kluwer Academic Publishers, Dordrecht (1992)Google Scholar
  7. 7.
    Shi, X., Wang, L., Kariuki, N., Luob, J., Zhongb, C.-J., Lua, S.: A multi-module artificial neural network approach to pattern recognition with optimized nanostructured sensor array. Sensors and Actuators B 117, 65–73 (2006)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Iwona Rutkowska
    • 1
  • Barbara Flisowska-Wiercik
    • 2
  • Przemysław M. Szecówka
    • 3
  • Andrzej Szczurek
    • 2
  1. 1.Faculty of ChemistryWrocław University of TechnologyWrocławPoland
  2. 2.Faculty of Environmental EngineeringWrocław University of TechnologyWrocławPoland
  3. 3.Faculty of Microsystem Electronics and PhotonicsWrocław University of TechnologyWrocławPoland

Personalised recommendations