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基于纳米ZnO气体传感器阵列的乙醇、丙酮、苯、甲苯、二甲苯的识别研究
引用本文:张覃轶,b 谢长生a 李登峰a 张顺平a 柏自奎a.基于纳米ZnO气体传感器阵列的乙醇、丙酮、苯、甲苯、二甲苯的识别研究[J].传感技术学报,2006,19(3):552-554,558.
作者姓名:张覃轶  b 谢长生a 李登峰a 张顺平a 柏自奎a
作者单位:1. 华中科技大学材料科学与工程学院,武汉,430074;武汉理工大学材料科学与工程学院,武汉,430070
2. 华中科技大学材料科学与工程学院,武汉,430074
摘    要:采用6个不同掺杂的纳米ZnO气体传感器组成的阵列实现了乙醇、丙酮、苯、甲苯、二甲苯的识别。研究表明,掺杂可大幅度提高传感器的敏感度和对可挥发有机物(Vocs)的选择性。对比了k近邻法、线性判别法、反传人工神经网络、概率神经网络、学习向量量化等在本实验中的应用。反传人工神经网络具有最高识别率,可达100%。本研究表明电子鼻在空气质量监测中具有广阔的应用前景。

关 键 词:气体传感器阵列  可挥发有机物(VOCs)  模式识别
文章编号:1004-1699(2006)03-0552-03
收稿时间:2005-09-01
修稿时间:2005-09-01

Recognition of ethanol, acetone, benzene, toluene and xylene using nano ZnO gas sensor array
Zhang Qin-yi,Xie Chang-sheng,Li Deng-feng,Zhang Shunping,Bai Zi-kuia.Recognition of ethanol, acetone, benzene, toluene and xylene using nano ZnO gas sensor array[J].Journal of Transduction Technology,2006,19(3):552-554,558.
Authors:Zhang Qin-yi  Xie Chang-sheng  Li Deng-feng  Zhang Shunping  Bai Zi-kuia
Affiliation:1.Dept. of Material Sci. and Eng. , Huazhong University of Science and Technology , Wuhan 430074, China; 2. Dept of Material Sci. and Eng. , Wuhan University of Technology ,Wuhan 430070, China
Abstract:Recognition of ethanol, acetone, benzene, toluene and xylene was performed by using 6 doped nano ZnO gas sensors. It was proved that sensitivities and selectivity of gas sensors could be reasonably improved by dopants. K-nearest neighbour (k-NN), linear discriminant analysis (LDA), back-propagation artificial neural network (BP-ANN), probabilistic neural network (PNN) and learning vector quantization (LVQ) were compared for their suitability on classifying volatile organic compounds (VOCs). The accuracy of BP-ANN in terms of predicting tested samples was 100% and the highest among the pattern recognition algorithms. This work shows the potential application of the gas sensor arrays for monitoring the air quality.
Keywords:gas sensor array  volatile organic compounds (VOCs)  pattern recognition
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