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Classification of complex gas mixtures from automotive leather using an electronic nose

机译:使用电子鼻对汽车皮革中的复杂气体混合物进行分类

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A semiconductor gas sensor array combined with a routine for pattern recognition - a so-called electronic nose - for the detection of gas emissions from the leather used in car compartments is described. The gas sensors are 10 metal oxide semiconductor field effect transistors (MOSFETs) with gates of thin, catalytic metals, and five semiconducting metal oxide sensors. The sensor array data are processed by multivariate means using principal component analysis (PCA) and are shown to give similar and add additional information compared to gas chromatography-mass spectrometry (GC-MS) and a human sensory panel. The total volatile organic compound concentration as measured by GC did not differ between good and bad samples and could therefore not be used as a quality control tool, whilst the electronic nose together with pattern recognition could readily discover the deviating samples with unusual emitting gases. This set-up could be useful in on-line quality monitoring systems to detect anomalies in incoming car interior trim materials. (C) 2000 Elsevier Science B.V. All rights reserved. [References: 14]
机译:描述了一种半导体气体传感器阵列,其与用于图案识别的例程(所谓的电子鼻)相结合,用于检测来自车厢中皮革的气体排放。气体传感器是10个带有薄催化金属栅极的金属氧化物半导体场效应晶体管(MOSFET)和5个半导体金属氧化物传感器。传感器阵列数据通过使用主成分分析(PCA)的多元方法进行处理,与气相色谱-质谱(GC-MS)和人体感应面板相比,显示出的数据相似且添加了更多信息。通过GC测量的总挥发性有机化合物浓度在好样品和坏样品之间没有差异,因此不能用作质量控制工具,而电子鼻和模式识别可以轻松发现异常排放的样品。此设置可能在在线质量监控系统中有用,以检测传入的汽车内部装饰材料中的异常。 (C)2000 Elsevier Science B.V.保留所有权利。 [参考:14]

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