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http://dx.doi.org/10.5370/JEET.2010.5.3.493

ANN Modeling of a Gas Sensor  

Baha, H. (Advance Electronics Laboratory, University of Batna Algeria)
Dibi, Z. (Advance Electronics Laboratory, University of Batna Algeria)
Publication Information
Journal of Electrical Engineering and Technology / v.5, no.3, 2010 , pp. 493-496 More about this Journal
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.
Keywords
ABM; ANN; Gas sensor; Implementation; Modeling;
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