Journal of Electrical Engineering and Technology

The Korean Institute of Electrical Engineers (대한전기학회)
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ANN Modeling of a Gas Sensor

  • Baha, H. (Advance Electronics Laboratory, University of Batna Algeria) ;
  • Dibi, Z. (Advance Electronics Laboratory, University of Batna Algeria)
  • Received : 2010.08.06
  • Accepted : 2010.04.05
  • Published : 2010.09.01
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Abstract

At present, Metal Oxide gas Sensors (MOXs) are widely used in gas detection because of its advantages, including high sensitivity and low cost. However, MOX presents well-known problems, including lack of selectivity and environment effect, which has motivated studies on different measurement strategies and signal-processing algorithms. In this paper, we present an artificial neural network (ANN) that models an MOX sensor (TGS822) used in a dynamic environment. This model takes into account dependence in relative humidity and in gas nature. Using MATLAB interface in the design phase and optimization, the proposed model is implemented as a component in an electronic simulator library and accurately expressed the nonlinear character of the response and that its dependence on temperature and relative humidity were higher than gas nature.

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References

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