Machine Learning for Optical Gas Sensing: A Leaky-Mode Humidity Sensor as Example
V.V. Kornienko
1, 2
,
I.A. Nechepurenko
1, 3
,
Peter N Tananaev
1
,
Eugeny D Chubchev
1
,
Aleksandr S Baburin
1, 4
,
V Echeistov
1, 4
,
Alexander V Zverev
1, 4
,
Ivan I Novoselov
1, 5
,
Ivan A. Kruglov
1, 5
,
I. V. Rodionov
1, 4
,
Alexander V Dorofeenko
1, 3, 6, 7
5
Moscow State Technical University, Moscow, Russia
|
Publication type: Journal Article
Publication date: 2020-07-01
scimago Q1
wos Q1
SJR: 1.039
CiteScore: 8.2
Impact factor: 4.5
ISSN: 1530437X, 15581748, 23799153
Electrical and Electronic Engineering
Instrumentation
Abstract
Optical gas sensing attracts growing attention in the recent years. This is governed by progressive availability of optical nanostructures fabrication and complex techniques of optical spectrum processing. In the present paper, a room-temperature optical humidity sensor based on a hydrophilic polymer Nafion is theoretically and experimentally investigated. Sensor geometry is optimized for maximum sensitivity of an angle-resolved ATR dip in the Kretschmann configuration. The reflectance dip is attributed to the 2nd order Nafion layer leaky waveguide mode hybridized with the surface plasmon-polariton at the silver/Nafion interface. Results of the relative humidity (RH) retrieval with the regression of the physical model parameters is compared to these obtained with different machine learning (ML) techniques. It is shown that a limited raw data set is enough for using ML algorithms. Accuracy of 0.3% has been demonstrated in RH measurements.
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32
Total citations:
32
Citations from 2024:
14
(43.75%)
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GOST
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Kornienko V. et al. Machine Learning for Optical Gas Sensing: A Leaky-Mode Humidity Sensor as Example // IEEE Sensors Journal. 2020. Vol. 20. No. 13. pp. 6954-6963.
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Kornienko V., Nechepurenko I., Tananaev P. N., Chubchev E. D., Baburin A. S., Echeistov V., Zverev A. V., Novoselov I. I., Kruglov I. A., Rodionov I. V., Baryshev A. V., Dorofeenko A. V. Machine Learning for Optical Gas Sensing: A Leaky-Mode Humidity Sensor as Example // IEEE Sensors Journal. 2020. Vol. 20. No. 13. pp. 6954-6963.
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TY - JOUR
DO - 10.1109/JSEN.2020.2978931
UR - https://doi.org/10.1109/JSEN.2020.2978931
TI - Machine Learning for Optical Gas Sensing: A Leaky-Mode Humidity Sensor as Example
T2 - IEEE Sensors Journal
AU - Kornienko, V.V.
AU - Nechepurenko, I.A.
AU - Tananaev, Peter N
AU - Chubchev, Eugeny D
AU - Baburin, Aleksandr S
AU - Echeistov, V
AU - Zverev, Alexander V
AU - Novoselov, Ivan I
AU - Kruglov, Ivan A.
AU - Rodionov, I. V.
AU - Baryshev, Alexander V
AU - Dorofeenko, Alexander V
PY - 2020
DA - 2020/07/01
PB - Institute of Electrical and Electronics Engineers (IEEE)
SP - 6954-6963
IS - 13
VL - 20
SN - 1530-437X
SN - 1558-1748
SN - 2379-9153
ER -
Cite this
BibTex (up to 50 authors)
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@article{2020_Kornienko,
author = {V.V. Kornienko and I.A. Nechepurenko and Peter N Tananaev and Eugeny D Chubchev and Aleksandr S Baburin and V Echeistov and Alexander V Zverev and Ivan I Novoselov and Ivan A. Kruglov and I. V. Rodionov and Alexander V Baryshev and Alexander V Dorofeenko},
title = {Machine Learning for Optical Gas Sensing: A Leaky-Mode Humidity Sensor as Example},
journal = {IEEE Sensors Journal},
year = {2020},
volume = {20},
publisher = {Institute of Electrical and Electronics Engineers (IEEE)},
month = {jul},
url = {https://doi.org/10.1109/JSEN.2020.2978931},
number = {13},
pages = {6954--6963},
doi = {10.1109/JSEN.2020.2978931}
}
Cite this
MLA
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Kornienko, V.V., et al. “Machine Learning for Optical Gas Sensing: A Leaky-Mode Humidity Sensor as Example.” IEEE Sensors Journal, vol. 20, no. 13, Jul. 2020, pp. 6954-6963. https://doi.org/10.1109/JSEN.2020.2978931.