An Electronic Nose System Based on an Array of Carbon Nanotubes Gas Sensors with Pattern Recognition Techniques

Abstract-This paper presents design of an electronic nose based on an array of aligned multi-walled carbon nanotubes (MWNT) ionization gas sensors and pattern recognition techniques for gas detection. The raw data, including discharge voltages and currents, is acquired by measurement of sensor array response and transformed to the computer by peripheral circuit, and processed by Principal Components Analysis (PCA). Back-propagation neural networks (BPNN) are applied to determine gas varieties. Results demonstrate the developed electronic nose system is capable to identify target gases successfully and is promising for field applications.