Proceedings of the 2018 2nd International Conference on Electrical Engineering and Automation (ICEEA 2018)

Gas Composition Recognition Based on Analyzing Acoustic Relaxation Absorption Spectra: Wavelet Decomposition and Support Vector Machine Classifier

Authors
Yaqiong Jia, Bin Yu, Mingdi Du, Xiaoli Wang
Corresponding Author
Yaqiong Jia
Available Online March 2018.
DOI
10.2991/iceea-18.2018.28How to use a DOI?
Keywords
gas compositions recognition; gas acoustic relaxation absorption spectrum; wavelet multi-resolution analysis; multi-class support vector machine
Abstract

Gas acoustic spectrum represents properties of acoustic propagation, which can distinguish gas compositions. However in few existing methods of gas-composition-unknown recognition, the approaches of programmatically processing the acoustic spectrum curves have not yet been presented. We propose a method for gas-composition-unknown recognition by analyzing gas acoustic relaxation absorption spectrum (GARAS) based on wavelet multi-resolution analysis (MRA) and multi-class support vector machine (SVM). Features of GARAS are extracted by wavelet MRA, and then selected to obtain a few feature coefficients which are utilized to train and test multi-class SVM. Simulation results show that the proposed method completely classifies four examples of gas mixtures, and that it recognizes the mixtures with the same and similar concentration or temperature. This method realizes the numerically extracting and programmatically processing the information of GARAS, and implements gas-composition-unknown sensing based on acoustic spectrums.

Copyright
© 2018, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2018 2nd International Conference on Electrical Engineering and Automation (ICEEA 2018)
Series
Advances in Engineering Research
Publication Date
March 2018
ISBN
978-94-6252-497-2
ISSN
2352-5401
DOI
10.2991/iceea-18.2018.28How to use a DOI?
Copyright
© 2018, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Yaqiong Jia
AU  - Bin Yu
AU  - Mingdi Du
AU  - Xiaoli Wang
PY  - 2018/03
DA  - 2018/03
TI  - Gas Composition Recognition Based on Analyzing Acoustic Relaxation Absorption Spectra: Wavelet Decomposition and Support Vector Machine Classifier
BT  - Proceedings of the 2018 2nd International Conference on Electrical Engineering and Automation (ICEEA 2018)
PB  - Atlantis Press
SP  - 126
EP  - 130
SN  - 2352-5401
UR  - https://doi.org/10.2991/iceea-18.2018.28
DO  - 10.2991/iceea-18.2018.28
ID  - Jia2018/03
ER  -