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 SnO2, 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%.
出处
《传感技术学报》
EI
CAS
CSCD
北大核心
2006年第3期573-576,580,共5页
Chinese Journal of Sensors and Actuators
基金
扬州大学科研基金资助(JK0313089)
机械基金资助(YJXK0408)
关键词
特征比值法
小波降噪
电子鼻
残留农药
characteristic ratio
wavelet de-noise
electronic nose
remaining pesticides