Abstract

This study describes a portable system based on mimicking the mammalian olfactory mechanism (electronic nose), that can sense and identify chemical vapors by automated odor recognition. The electronic nose developed in this research consists of an array of tin oxide sensors, with each sensor in the array giving a different electrical response for a particular target vapor introduced into the sensing chamber. The combined output from the sensor array forms a fingerprint, or signature, that is unique for a particular odor. Pattern recognition techniques based on principal component analysis and artificial neural networks were developed for learning different chemical signatures. The electronic nose was successfully trained and tested in the laboratory to recognize various chemicals such as benzene, toluene, ethyl benzene, xylene, and gasoline. This study successfully demonstrates the feasibility of an electronic nose for detecting and identifying chemical and explosive vapors.

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