Data analysis for chemical sensor arrays

被引:0
|
作者
Di Natale, C [1 ]
Martinelli, E [1 ]
Pennazza, G [1 ]
Orsini, A [1 ]
Santonico, M [1 ]
机构
[1] Univ Roma Tor Vergata, Dept Elect Engn, Via Politecn 1, I-00133 Rome, Italy
关键词
electronic nose; principal component analysis; pattern recognition; chemical sensors; sensor arrays; olfaction system; multivariate data analysis;
D O I
暂无
中图分类号
O65 [分析化学];
学科分类号
070302 ; 081704 ;
摘要
Arrays were introduced in the mid-eighties as a method to counteract the cross-selectivity of gas sensors. Their use has since become a common practice in sensor applications [1]. The great advantage of this technique is that once arrays are matched with proper multivariate data analysis, the use of non-selective sensors for practical applications becomes possible. Again in the eighties, Persaud and Dodds argued that such arrays has a very close connection with mammalian olfaction systems. This conjecture opened the way to the advent of electronic noses [2], a popular name for chemical sensor arrays used for qualitative analysis of complex samples. It is worth remarking that a gas sensor array is a mere mathematical construction where the sensor outputs are arranged as components of a vector. Arrays can also be utilized to investigate the properties of chemical sensors, or even better, the peculiar behaviour of a sensor as a component of an array. In this chapter, the more common sensor array methodologies are critically reviewed, including the most general steps of a multivariate data analysis. The application of such methods to the study of sensor properties is also illustrated through a practical example.
引用
收藏
页码:147 / +
页数:4
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