Journal of Sensors
Volume 2008 (2008), Article ID 465209, 6 pages
doi:10.1155/2008/465209
Abstract
Gas recognition is a new emerging research area with many civil, military, and industrial applications. The success
of any gas recognition system depends on its computational
complexity and its robustness. In this work, we propose a
new low-complexity recognition method which is tested and
successfully validated for tin-oxide gas sensor array chip. The
recognition system is based on a vector angle similarity measure
between the query gas and the representatives of the different gas
classes. The latter are obtained using a clustering algorithm based
on the same measure within the training data set. Experimented results on our in-house gas sensors array show more than 98%
of correct recognition. The robustness of the proposed method
is tested by recognizing gas measurements with simulated drift.
Less than 1% of performance degradation is noted at the worst case
scenario which represents a significant improvement when
compared to the current state-of-the-art.