WO3 sensors array coupled with pattern recognition method for gases identification

Abstract

This paper presents the performance of gas sensors as electronic nose coupled with pattern recognition method for gases identification. In fact, the implementation of the electronic nose in a characterization process is based on two fundamental phases: a learning phase and a phase of identification. That is why we need an accurate extraction method in order to obtain performant classification. In this study, we propose to extract transient parameters in a dynamic mode: derivate and integral. The performance of these features is validated by the analysis method: principal component analysis (PCA) and K nearest neighbors (KNN), which present 98, 74% rate classification.