Detecting and Identifying Industrial Gases by a Method Based on Olfactory Machine at Different Concentrations
Joint Authors
Sun, Yunlong
Li, Hui
Zhu, Chuchu
Xu, Ou
Gholam Hosseini, Hamid
Luo, Dehan
Source
Journal of Electrical and Computer Engineering
Issue
Vol. 2018, Issue 2018 (31 Dec. 2018), pp.1-9, 9 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2018-03-01
Country of Publication
Egypt
No. of Pages
9
Main Subjects
Information Technology and Computer Science
Abstract EN
Gas sensors have been widely reported for industrial gas detection and monitoring.
However, the rapid detection and identification of industrial gases are still a challenge.
In this work, we measure four typical industrial gases including CO2, CH4, NH3, and volatile organic compounds (VOCs) based on electronic nose (EN) at different concentrations.
To solve the problem of effective classification and identification of different industrial gases, we propose an algorithm based on the selective local linear embedding (SLLE) to reduce the dimensionality and extract the features of high-dimensional data.
Combining the Euclidean distance (ED) formula with the proposed algorithm, we can achieve better classification and identification of four kinds of gases.
We compared the classification and recognition results of classical principal component analysis (PCA), linear discriminate analysis (LDA), and PCA + LDA algorithms with the proposed SLLE algorithm after selecting the original data and performing feature extraction.
The experimental results show that the recognition accuracy rate of the SLLE reaches 91.36%, which is better than the other three algorithms.
In addition, the SLLE algorithm provides more efficient and accurate responses to high-dimensional industrial gas data.
It can be used in real-time industrial gas detection and monitoring combined with gas sensor networks.
American Psychological Association (APA)
Sun, Yunlong& Luo, Dehan& Li, Hui& Zhu, Chuchu& Xu, Ou& Gholam Hosseini, Hamid. 2018. Detecting and Identifying Industrial Gases by a Method Based on Olfactory Machine at Different Concentrations. Journal of Electrical and Computer Engineering،Vol. 2018, no. 2018, pp.1-9.
https://search.emarefa.net/detail/BIM-1184349
Modern Language Association (MLA)
Sun, Yunlong…[et al.]. Detecting and Identifying Industrial Gases by a Method Based on Olfactory Machine at Different Concentrations. Journal of Electrical and Computer Engineering No. 2018 (2018), pp.1-9.
https://search.emarefa.net/detail/BIM-1184349
American Medical Association (AMA)
Sun, Yunlong& Luo, Dehan& Li, Hui& Zhu, Chuchu& Xu, Ou& Gholam Hosseini, Hamid. Detecting and Identifying Industrial Gases by a Method Based on Olfactory Machine at Different Concentrations. Journal of Electrical and Computer Engineering. 2018. Vol. 2018, no. 2018, pp.1-9.
https://search.emarefa.net/detail/BIM-1184349
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1184349