Diffusive Representation: A Powerful Method to Analyze Temporal Signals from Metal-Oxide Gas Sensors Used in Pulsed Mode
The main objective of this work was to find the most efficient method to interpolate metal oxide gas sensor used in a pulsed-temperature operating mode. This pulsed thermal profile is obtained by applying 6 power steps of 2 s each on the heater resistor. The experimental values of the sensing layer...
Guardado en:
Autores principales: | , , , , , , , |
---|---|
Formato: | article |
Lenguaje: | EN |
Publicado: |
MDPI AG
2021
|
Materias: | |
Acceso en línea: | https://doaj.org/article/4f40b9c846ee488f96c4b13f140f38b0 |
Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
id |
oai:doaj.org-article:4f40b9c846ee488f96c4b13f140f38b0 |
---|---|
record_format |
dspace |
spelling |
oai:doaj.org-article:4f40b9c846ee488f96c4b13f140f38b02021-11-11T15:36:53ZDiffusive Representation: A Powerful Method to Analyze Temporal Signals from Metal-Oxide Gas Sensors Used in Pulsed Mode10.3390/electronics102125782079-9292https://doaj.org/article/4f40b9c846ee488f96c4b13f140f38b02021-10-01T00:00:00Zhttps://www.mdpi.com/2079-9292/10/21/2578https://doaj.org/toc/2079-9292The main objective of this work was to find the most efficient method to interpolate metal oxide gas sensor used in a pulsed-temperature operating mode. This pulsed thermal profile is obtained by applying 6 power steps of 2 s each on the heater resistor. The experimental values of the sensing layer resistance, with a sampling time of 4ms, were interpolated by using two different static methods: a polynomial modelling and a neural network modelling, and one dynamic method: the diffusive representation. Then, the results have been compared in terms of precision and number of useful output data, as minimum as possible for high performance and rapid data treatment which is great of interest in embedded systems. The best results are obtained with the diffusive representation; it allows converting 500 measurements into 11 output coefficients.Cyril TropisNicolas DufourGermain GarciaGerard MontsenyChaabane TalhiFrédéric BlancBernard FrancPhilippe MeniniMDPI AGarticlemetal-oxide gas sensorspulsed-temperature operating modediffusive representationinterpolationElectronicsTK7800-8360ENElectronics, Vol 10, Iss 2578, p 2578 (2021) |
institution |
DOAJ |
collection |
DOAJ |
language |
EN |
topic |
metal-oxide gas sensors pulsed-temperature operating mode diffusive representation interpolation Electronics TK7800-8360 |
spellingShingle |
metal-oxide gas sensors pulsed-temperature operating mode diffusive representation interpolation Electronics TK7800-8360 Cyril Tropis Nicolas Dufour Germain Garcia Gerard Montseny Chaabane Talhi Frédéric Blanc Bernard Franc Philippe Menini Diffusive Representation: A Powerful Method to Analyze Temporal Signals from Metal-Oxide Gas Sensors Used in Pulsed Mode |
description |
The main objective of this work was to find the most efficient method to interpolate metal oxide gas sensor used in a pulsed-temperature operating mode. This pulsed thermal profile is obtained by applying 6 power steps of 2 s each on the heater resistor. The experimental values of the sensing layer resistance, with a sampling time of 4ms, were interpolated by using two different static methods: a polynomial modelling and a neural network modelling, and one dynamic method: the diffusive representation. Then, the results have been compared in terms of precision and number of useful output data, as minimum as possible for high performance and rapid data treatment which is great of interest in embedded systems. The best results are obtained with the diffusive representation; it allows converting 500 measurements into 11 output coefficients. |
format |
article |
author |
Cyril Tropis Nicolas Dufour Germain Garcia Gerard Montseny Chaabane Talhi Frédéric Blanc Bernard Franc Philippe Menini |
author_facet |
Cyril Tropis Nicolas Dufour Germain Garcia Gerard Montseny Chaabane Talhi Frédéric Blanc Bernard Franc Philippe Menini |
author_sort |
Cyril Tropis |
title |
Diffusive Representation: A Powerful Method to Analyze Temporal Signals from Metal-Oxide Gas Sensors Used in Pulsed Mode |
title_short |
Diffusive Representation: A Powerful Method to Analyze Temporal Signals from Metal-Oxide Gas Sensors Used in Pulsed Mode |
title_full |
Diffusive Representation: A Powerful Method to Analyze Temporal Signals from Metal-Oxide Gas Sensors Used in Pulsed Mode |
title_fullStr |
Diffusive Representation: A Powerful Method to Analyze Temporal Signals from Metal-Oxide Gas Sensors Used in Pulsed Mode |
title_full_unstemmed |
Diffusive Representation: A Powerful Method to Analyze Temporal Signals from Metal-Oxide Gas Sensors Used in Pulsed Mode |
title_sort |
diffusive representation: a powerful method to analyze temporal signals from metal-oxide gas sensors used in pulsed mode |
publisher |
MDPI AG |
publishDate |
2021 |
url |
https://doaj.org/article/4f40b9c846ee488f96c4b13f140f38b0 |
work_keys_str_mv |
AT cyriltropis diffusiverepresentationapowerfulmethodtoanalyzetemporalsignalsfrommetaloxidegassensorsusedinpulsedmode AT nicolasdufour diffusiverepresentationapowerfulmethodtoanalyzetemporalsignalsfrommetaloxidegassensorsusedinpulsedmode AT germaingarcia diffusiverepresentationapowerfulmethodtoanalyzetemporalsignalsfrommetaloxidegassensorsusedinpulsedmode AT gerardmontseny diffusiverepresentationapowerfulmethodtoanalyzetemporalsignalsfrommetaloxidegassensorsusedinpulsedmode AT chaabanetalhi diffusiverepresentationapowerfulmethodtoanalyzetemporalsignalsfrommetaloxidegassensorsusedinpulsedmode AT fredericblanc diffusiverepresentationapowerfulmethodtoanalyzetemporalsignalsfrommetaloxidegassensorsusedinpulsedmode AT bernardfranc diffusiverepresentationapowerfulmethodtoanalyzetemporalsignalsfrommetaloxidegassensorsusedinpulsedmode AT philippemenini diffusiverepresentationapowerfulmethodtoanalyzetemporalsignalsfrommetaloxidegassensorsusedinpulsedmode |
_version_ |
1718434982711525376 |