A Wireless Electronic Nose System Using a Fe₂O₃ Gas Sensing Array and Least Squares Support Vector Regression

Author： Song Kai Wang Qi Liu Qi Zhang Hongquan Cheng Yingguo

Publisher： MDPI

E-ISSN： 1424-8220|11|1|485-505

ISSN： 1424-8220

Source： Sensors, Vol.11, Iss.1, 2011-01, pp. : 485-505

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Abstract

This paper describes the design and implementation of a wireless electronic nose (WEN) system which can online detect the combustible gases methane and hydrogen (CH₄/H₂) and estimate their concentrations, either singly or in mixtures. The system is composed of two wireless sensor nodes—a slave node and a master node. The former comprises a Fe₂O₃ gas sensing array for the combustible gas detection, a digital signal processor (DSP) system for real-time sampling and processing the sensor array data and a wireless transceiver unit (WTU) by which the detection results can be transmitted to the master node connected with a computer. A type of Fe₂O₃ gas sensor insensitive to humidity is developed for resistance to environmental influences. A threshold-based least square support vector regression (LS-SVR)estimator is implemented on a DSP for classification and concentration measurements. Experimental results confirm that LS-SVR produces higher accuracy compared with artificial neural networks (ANNs) and a faster convergence rate than the standard support vector regression (SVR). The designed WEN system effectively achieves gas mixture analysis in a real-time process.