- Volume 5 Issue 3
DOI QR Code
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
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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