期刊
SENSORS AND ACTUATORS B-CHEMICAL
卷 117, 期 1, 页码 244-252出版社
ELSEVIER SCIENCE SA
DOI: 10.1016/j.snb.2005.11.034
关键词
gas sensors; mono-class sensors; hybrid class sensors; volatile organic compounds (VOCs); principal component analysis (PCA); neural networks (NN)
Detection of volatile organic compounds (VOCs) using non-selective sensor requires an array of multiplexed sensors followed by pattern recognition approach. Based on this concept, we compare three different approaches for selective detection of ethanol, ammonia, toluene, acetone and chloroform at different concentrations using non-selective sensors which are: (a) an array of sensors operated at a fixed temperature (hybrid class sensors), (b) operating one sensor at different temperatures (mono-class sensors), and (c) operating all sensors in an array at different temperatures (hybrid and mono-class sensors). Contrary to common practice of using sensors with partially overlapping response patterns (hybrid class sensors) in an array, we demonstrate that even one type of sensors (mono-class sensors) operated at different temperatures can be used for the selective detection of VOCs. It is further shown that an array consisting of hybrid and mono-class sensors each operated at different temperatures not only results in approaching 100% classification but also the quantified samples fall within 10% of error, which is an encouraging result. (c) 2005 Elsevier B.V. All rights reserved.
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