A novel sensor selection using pattern recognition in electronic nose

A novel sensor selection using pattern recognition technique in electronic nose (E-Nose) is proposed in this paper. This paper studies the portable E-Nose based on metal oxide semiconductor (MOS) gas sensors for detection of multiple kinds of indoor air contaminants. The characteristics of portability, low cost, multiple targets detection and high performance of E-Nose monitor are the main pursuit for home use. Formaldehyde, benzene, toluene, carbon monoxide, and ammonia are the primary targets of the proposed E-Nose which benefits from the characteristics of the broad spectrum, reproducibility, sensitivity and low-cost of MOS gas sensors. Therefore, a potential and full contribution analysis of the small sized sensor array, in detection of indoor air contaminants coupled with a kernel principal component analysis (KPCA) based linear discriminant analysis (LDA) pattern recognition technique, is presented in this paper. Some experimental findings on the roles of sensors in an E-Nose have also been concluded. The recognition results clearly demonstrate the contribution of each sensor to gas detection which helps the sensor selection in E-Nose design. (C) 2014 Elsevier Ltd. All rights reserved.