Selectivity Enhancement in Multisensor Systems Using Flow Modulation Techniques
Selectivity Enhancement in Multisensor Systems Using Flow Modulation Techniques
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DOI：
10.3390/s8117369
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发表时间：
2008-11-01
期刊：
影响因子：
3.9
通讯作者：
Llobet, Eduard
中科院分区：
文献类型：
--
作者：
El Barbri, Noureddine;Duran, Cristhian;Llobet, Eduard
在本文中，使用一种新的技术，以获得瞬态传感器信息的介绍和它的有用性，以提高金属氧化物气体传感器的选择性进行了讨论。该方法基于调制载气的流量，载气将待测量的物质带入传感器室。以这种方式，传感器表面处的分析物浓度被改变。因此，传感器响应中的可再现模式发展，其携带用于帮助传感器系统的重要信息，不仅用于区分所考虑的挥发物，而且用于半定量它们。这已被证明是通过使用离散小波变换（DWT）从传感器动态提取特征，并通过建立和验证支持向量机（SVM）分类模型。所获得的良好结果（5种挥发性化合物的100%正确识别和这些挥发物的近89%正确同时识别和定量）明显优于使用稳态响应时所获得的结果，证明了流量调制背后的概念。
In this paper, the use of a new technique to obtain transient sensor information is introduced and its usefulness to improve the selectivity of metal oxide gas sensors is discussed. The method is based on modulating the flow of the carrier gas that brings the species to be measured into the sensor chamber. In such a way, the analytes' concentration at the surface of the sensors is altered. As a result, reproducible patterns in the sensor response develop, which carry important information for helping the sensor system, not only to discriminate among the volatiles considered but also to semi-quantify them. This has been proved by extracting features from sensor dynamics using the discrete wavelet transform (DWT) and by building and validating support vector machine (SVM) classification models. The good results obtained (100% correct identification among 5 volatile compounds and nearly a 89% correct simultaneous identification and quantification of these volatiles), which clearly outperform those obtained when the steady-state response is used, prove the concept behind flow modulation.