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Journal articles
SAW sensor’s frequency shift characterization for odor recognition and concentration estimation
Abstract : In this paper, we propose an approach to determine the time constants and the amplitudes of the mass loading effect and of the viscoelastic contribution of SAW sensor's frequency shift. This approach consists in optimizing a function of these parameters, which is independent of the concentration profile. We experimentally establish in laboratory conditions (T = 22 °C), on a data set composed of seven different gases, that these features are suitable for chemical compounds identification. In particular, we obtain a higher classification rate than the traditional amplitudes of the signals during the steady state, and we show that the classification success rate can be increased by using both of them in conjunction with a feature subset selection heuristic. We also propose a method based on deconvolution and kernel regression to estimate the temporal concentration profile.
Keywords :
odor concentration estimation
odor recognition
SAW sensor frequency shift characterization
viscoelasticity
surface acoustic wave sensors
feature extraction
electronic nose
deconvolution
chemical variables measurement
Frequency estimation
Convergence
Chemical compounds
Loading
Surface acoustic waves
Frequency modulation
concentration evaluation
odour recognition
SAW sensors
time constants
mass loading effect amplitudes
frequency shift viscoelastic effect
parameter optimization
chemical compounds identification
feature subset selection heuristic
deconvolution method
kernel regression method
temporal concentration profile estimation
detector
sensor
instrumentation
diamond
signal processing
https://hal-cea.archives-ouvertes.fr/cea-01847213
Contributor : Léna Le Roy Connect in order to contact the contributor
Submitted on : Tuesday, April 5, 2022 - 5:34:30 PM
Last modification on : Wednesday, April 6, 2022 - 9:36:28 AM
Long-term archiving on: : Wednesday, July 6, 2022 - 7:21:02 PM
Contributor : Léna Le Roy Connect in order to contact the contributor
Submitted on : Tuesday, April 5, 2022 - 5:34:30 PM
Last modification on : Wednesday, April 6, 2022 - 9:36:28 AM
Long-term archiving on: : Wednesday, July 6, 2022 - 7:21:02 PM
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