Please use this identifier to cite or link to this item:
https://doi.org/10.21256/zhaw-3501
Publication type: | Article in scientific journal |
Type of review: | Peer review (publication) |
Title: | Novel semi-parametric algorithm for interference-immune tunable absorption spectroscopy gas sensing |
Authors: | Michelucci, Umberto Venturini, Francesca |
DOI: | 10.3390/s17102281 10.21256/zhaw-3501 |
Published in: | Sensors |
Volume(Issue): | 17 |
Issue: | 10 |
Page(s): | 2281 |
Issue Date: | 2017 |
Publisher / Ed. Institution: | MDPI |
ISSN: | 1424-8220 1424-8239 |
Language: | English |
Subjects: | Spectroscopy sensor; Interference; Digital filtering |
Subject (DDC): | 530: Physics |
Abstract: | One of the most common limits to gas sensor performance is the presence of unwanted interference fringes arising, for example, from multiple reflections between surfaces in the optical path. Additionally, since the amplitude and the frequency of these interferences depend on the distance and alignment of the optical elements, they are affected by temperature changes and mechanical disturbances, giving rise to a drift of the signal. In this work, we present a novel semi-parametric algorithm that allows the extraction of a signal, like the spectroscopic absorption line of a gas molecule, from a background containing arbitrary disturbances, without having to make any assumption on the functional form of these disturbances. The algorithm is applied first to simulated data and then to oxygen absorption measurements in the presence of strong fringes. To the best of the authors’ knowledge, the algorithm enables an unprecedented accuracy particularly if the fringes have a free spectral range and amplitude comparable to those of the signal to be detected. The described method presents the advantage of being based purely on post processing, and to be of extremely straightforward implementation if the functional form of the Fourier transform of the signal is known. Therefore, it has the potential to enable interference-immune absorption spectroscopy. Finally, its relevance goes beyond absorption spectroscopy for gas sensing, since it can be applied to any kind of spectroscopic data. |
URI: | https://digitalcollection.zhaw.ch/handle/11475/2384 |
Fulltext version: | Published version |
License (according to publishing contract): | CC BY 4.0: Attribution 4.0 International |
Departement: | School of Engineering |
Organisational Unit: | Institute of Applied Mathematics and Physics (IAMP) |
Appears in collections: | Publikationen School of Engineering |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
sensors-17-02281-v2.pdf | 642.5 kB | Adobe PDF | View/Open |
Show full item record
Michelucci, U., & Venturini, F. (2017). Novel semi-parametric algorithm for interference-immune tunable absorption spectroscopy gas sensing. Sensors, 17(10), 2281. https://doi.org/10.3390/s17102281
Michelucci, U. and Venturini, F. (2017) ‘Novel semi-parametric algorithm for interference-immune tunable absorption spectroscopy gas sensing’, Sensors, 17(10), p. 2281. Available at: https://doi.org/10.3390/s17102281.
U. Michelucci and F. Venturini, “Novel semi-parametric algorithm for interference-immune tunable absorption spectroscopy gas sensing,” Sensors, vol. 17, no. 10, p. 2281, 2017, doi: 10.3390/s17102281.
MICHELUCCI, Umberto und Francesca VENTURINI, 2017. Novel semi-parametric algorithm for interference-immune tunable absorption spectroscopy gas sensing. Sensors. 2017. Bd. 17, Nr. 10, S. 2281. DOI 10.3390/s17102281
Michelucci, Umberto, and Francesca Venturini. 2017. “Novel Semi-Parametric Algorithm for Interference-Immune Tunable Absorption Spectroscopy Gas Sensing.” Sensors 17 (10): 2281. https://doi.org/10.3390/s17102281.
Michelucci, Umberto, and Francesca Venturini. “Novel Semi-Parametric Algorithm for Interference-Immune Tunable Absorption Spectroscopy Gas Sensing.” Sensors, vol. 17, no. 10, 2017, p. 2281, https://doi.org/10.3390/s17102281.
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.