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Sensors 2018, 18(5), 1562; https://doi.org/10.3390/s18051562

Multivariate Analysis as a Tool to Identify Concentrations from Strongly Overlapping Gas Spectra

1
Heinrich Blasius Institute of Physical Technologies, Hamburg University of Applied Sciences, Berliner Tor 21, 20099 Hamburg, Germany
2
School of Engineering and Computing, University of the West of Scotland, High Street, Paisley PA1 2BE, UK
*
Author to whom correspondence should be addressed.
Received: 20 February 2018 / Revised: 7 May 2018 / Accepted: 14 May 2018 / Published: 15 May 2018
(This article belongs to the Special Issue I3S 2017 Selected Papers)
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Abstract

We applied a multivariate analysis (MVA) to spectroscopic data of gas mixtures in the mid-IR in order to calculate the concentrations of the single components which exhibit strongly overlapping absorption spectra. This is a common challenge in broadband spectroscopy. Photoacoustic (PA) measurements of different volatile organic compounds (VOCs) in the wavelength region of 3250 nm to 3550 nm served as the exemplary detection technique. Partial least squares regression (PLS) was used to calculate concentrations from the PA spectra. After calibration, the PLS model was able to determine concentrations of single VOCs with a relative accuracy of 2.60%. View Full-Text
Keywords: multivariate analysis; partial least squares regression; PLS; photoacoustic spectroscopy; PAS; OPO; overlapping spectra; concentration determination; VOC multivariate analysis; partial least squares regression; PLS; photoacoustic spectroscopy; PAS; OPO; overlapping spectra; concentration determination; VOC
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
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Saalberg, Y.; Wolff, M. Multivariate Analysis as a Tool to Identify Concentrations from Strongly Overlapping Gas Spectra. Sensors 2018, 18, 1562.

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