基于特征比值法的电子鼻农药识别系统

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英文篇名：Electronic Nose System for the Recognition of Pesticides Based on the Characteristic Ratios Method 中文刊名：传感技术学报 英文刊名：Chinese Journal of Sensors and Actuators 作者：王昌龙 ; 黄惟一 英文作者：WANG Chang-long1 ; HUANG Wei-yi2 1.Mechanical Institute ; Yangzhou University ; Yangzhou Jiangsu 225009 ; China ; 2.Dept. of Instrument ; Southeast University ; Nanjing 210018 ; China 中文关键词：特征比值法 ; 小波降噪 ; 电子鼻 ; 残留农药 英文关键词：characteristic ratio ; wavelet de-noise ; electronic nose ; remaining pesticides 出版日期：2006-03-30 机构：扬州大学机械学院,东南大学仪器系 江苏扬州225009,南京210018 年：2006 期：03 出版单位：传感技术学报

摘要

采用二氧化锡半导体气敏传感器、热线型和催化型气敏传感器构成气体传感器阵列,用小波降噪和数据压缩对传感器响应信号进行预处理,采用特征比值法对响应曲线进行特征提取。选取不同浓度的常用农药等10种气体用径向基神经网络进行训练和识别试验,气味识别正确率达到83.3%。
The SnO_2, hotwire and catalytic gas sensors were employed to build the sensors array. The experiment data were de-noised and compressed with wavelet transformation. The characteristic ratios were used to the feature extraction of the responding curves. The RBF neural networks were trained with the data of 10 kinds of pesticides and other gases. The correct recognition rate reaches 83.3%.

引文

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