Quantitative analysis of gas mixtures using a tin oxide gas sensor and fast pattern recognition methods

반도체식 가스센서와 패턴인식방법을 이용한 혼합가스의 정량적 분석

A fuzzy ARTMAP neural network and a fuzzy ART neural network are proposed to identify $H_2S$, $NH_3$ and their mixtures and to estimate their concentrations, respectively. Features are extracted from a micro gas sensor array operated in a thermal modulation plan. After dimensions of the features are reduced by a preprocessing scheme, the features are fed into the proposed fuzzy neural networks. By computer simulations, the proposed methods are shown to be fast in learning and accurate in concentration estimating. The results are compared with other methods and discussed.