中国计量大学学报2017，Vol.28Issue(3)：388-393,6.DOI:10.3969/j.issn.2096-2835.2017.03.019
电子鼻的混合气体分类研究
Study on mixed gas detection based on electronic noses
摘要
Abstract
Targeting air pollutants of ammonia ,ethanol and the ammonia ethanol mixed gas ,an online electronic nose system was established .Different feature extraction methods were used to obtain their features .Principal component analysis (PCA) and linear discriminant analysis (LDA) were used to classify them .The results showed that the three kinds of gases could be distinguished by using the maximum response characteristics of the sensor and LDA .Based on the maximum response value ,a multilayer perceptron (MLP) neural network and an SVM optimized by particle swarm optimization (POS) were used to test 110 samples classification .The results showed that the correct rate of the MLP neural network was 70% and the SVM optimized by POS was 96 .3640% .Finally ,according to the loadings analysis ,the TGS2602 ,MQ138 and MQ3 sensors were removed and the sensor array was optimized .The online electronic nose system can be applied to the classification of these three types of air pollutants .关键词
电子鼻/特征提取/模式识别/传感器阵列优化/大气污染物Key words
electronic nose/feature extraction/pattern recognition/sensor array optimization/air pollutant分类
资源环境引用本文复制引用
梁子跃,杨昊,黄灿灿,周建,江正伟,方志明..电子鼻的混合气体分类研究[J].中国计量大学学报,2017,28(3):388-393,6.基金项目
国家重大科学仪器设备开发专项(No.2012YQ15008705),浙江省科技计划项目(No.2015C33009). （No.2012YQ15008705）
