文献类型：期刊文献

英文题名：Quality-grade evaluation of petroleum waxes using an electronic nose with a TGS gas sensor array

作者：Wang, Ji[1];Gao, Daqi[1];Wang, Zejian[2,3,4]

机构：[1]E China Univ Sci & Technol, Dept Comp Sci & Engn, Shanghai 200237, Peoples R China;[2]E China Univ Sci & Technol, State Key Lab Bioreactor Engn, Shanghai 200237, Peoples R China;[3]Shanghai Inst Biomfg Technol, Shanghai 200237, Peoples R China;[4]Collaborat Innovat Ctr, Shanghai 200237, Peoples R China

年份：2015

卷号：26

期号：8

外文期刊名：MEASUREMENT SCIENCE AND TECHNOLOGY

收录：;EI(收录号：20153501218450);WOS:【SCI-EXPANDED(收录号:WOS:000362220900016)】；

基金：This work is funded by the National Science Foundation of China (NSFC) under Grant Nos. 21176077 and 60675027, the High-Tech Development Program of China (863) under Grant No. 2006AA10Z315, and the Open Funding Project of the State Key Laboratory of Bioreactor Engineering.

语种：英文

外文关键词：electronic nose; petroleum wax; quality discrimination; principal component analysis (PCA); k-nearest neighbors (KNN); support vector machine (SVM); multilayer perceptron (MLP)

摘要：In this paper, the potential of an improved electronic nose to discriminate the quality of petroleum waxes based on their volatile profile was analyzed. Two datasets at 25 and 50 degrees C were collected from an experiment in order to compare influence by temperature. More fine-grained levels were further labeled for classification to meet various purposes. As petroleum waxes with lower odor levels are more difficult and important to identify than those with higher odor levels, we focus on the discrimination task for low-level ones. Principal component analysis was used for dimensionality reduction and data visualization. k-nearest neighbors, support vector machine, and multilayer perceptron were employed to classify among different qualities of petroleum waxes. The leave-one-out cross-validation method was employed due to the small sample sizes. Results showed good performance on both datasets, and at a temperature of 50 degrees C all pattern recognition methods showed improved classification rates. The improved electronic nose can potentially be applied to discriminate the quality of petroleum wax.