An electronic nose for the discrimination of forane 134a and carbon dioxide in a humidity controlled atmosphere

The great interest for the development of performed gas sensors has now an increasing application field - the electronic nose. We propose here to deve lop such a system for an environmental application in the field of the air quality control. Our application is based on the study of the learning proc ess of our sensor system for a performed discrimination of a refrigerant ga s forane 134a and carbon dioxide in a humidity and temperature controlled a tmosphere. In this paper, we present first the characterisation results obt ained for the metal oxide sensors used in this application. Afterwards, we propose to compare the discrimination results of the gases with several rep resentative variables by using two pattern recognition methods: principal c omponent analysis (PCA) and discriminant factorial analysis (DFA). We show the importance to use two types of complementary variables: the steady-stat e conductance and the conductance dynamic slope. We also propose a new meth od to reduce the drift effect and then we show the discrimination of the ga ses and also the identification of unknown cases by the way of the created decisive law. (C) 2001 Elsevier Science B.V. All rights reserved.