电子鼻
甲醇
化学
调制(音乐)
人工神经网络
材料科学
计算机科学
纳米技术
人工智能
声学
有机化学
物理
作者
Liu Hua-Bin,Ruijie Wu,Qianyu Guo,Zhongqiu Hua,Yi Wu
出处
期刊:ACS omega
[American Chemical Society]
日期:2021-11-05
卷期号:6 (45): 30598-30606
被引量:23
标识
DOI:10.1021/acsomega.1c04350
摘要
An electronic nose based on metal oxide semiconductor (MOS) sensors has been used to identify liquors with excessive methanol. The technique for a square wave temperature modulated MOS sensor was applied to generate the response patterns and a back-propagation neural network was used for pattern recognition. The parameters of temperature modulation were optimized according to the difference in response features of target gases (methanol and ethanol). Liquors with excessive methanol were qualitatively and quantitatively identified by the neural network. The results showed that our electronic nose system could well identify the liquors with excessive methanol with more than 92% accuracy. This electronic nose based on temperature modulation is a promising portable adjunct to other available techniques for quality assurance of liquors and other alcoholic beverages.
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