Electronic Nose System and Principal Component Analysis Technique for Gases Identification

Abstract

An electronic nose is an intelligent system which consists of a sensor network and a pattern recognition system able to know simple and complex odors. As the human nose, the artificial nose must learn to recognize different odors: the learning phase. There are several types of sensors such as fiber optic sensors, piezoelectric sensors, and sensor type MOSFET. The performance of the sensor network is discussed by using pattern recognition methods. In this paper, we tested Principal Component Analysis (PCA) to evaluate the ability of our sensor array to distinguish between different groups of target gases according to their nature: only in binary mixture and ternary mixture.

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