Issue |
EPJ Web Conf.
Volume 132, 2017
XXV-th Congress on Spectroscopy
|
|
---|---|---|
Article Number | 03033 | |
Number of page(s) | 2 | |
Section | Poster talks | |
DOI | https://doi.org/10.1051/epjconf/201713203033 | |
Published online | 13 December 2016 |
https://doi.org/10.1051/epjconf/201713203033
Selection of the optimal combination of water vapor absorption lines for detection of temperature in combustion zones of mixing supersonic gas flows by diode laser absorption spectrometry
Institute for Spectroscopy RAS, 108840 Troitsk, Moscow, Russia
* Corresponding author: miron@isan.troitsk.ru
Published online: 13 December 2016
Determination of a gas medium temperature by diode laser absorption spectrometry (DLAS) is based on the measurement of integral intensities of the absorption lines of a test molecule (generally water vapor molecule). In case of local thermodynamic equilibrium temperature is inferred from the ratio of the integral intensities of two lines with different low energy levels. For the total gas pressure above 1 atm the absorption lines are broadened and one cannot find isolated well resolved water vapor absorption lines within relatively narrow spectral interval of fast diode laser (DL) tuning range (about 3 cm−1). For diagnostics of a gas object in the case of high temperature and pressure DLAS technique can be realized with two diode lasers working in different spectral regions with strong absorption lines. In such situation the criteria of the optimal line selection differs significantly from the case of narrow lines. These criteria are discussed in our work. The software for selection the optimal spectral regions using the HITRAN-2012 and HITEMP data bases is developed. The program selects spectral regions of DL tuning, minimizing the error of temperature determination δТ/T, basing on the attainable experimental error of line intensity measurement δS. Two combinations of optimal spectral regions were selected – (1.392 & 1.343 μm) and (1.392 & 1.339 μm). Different algorithms of experimental data processing are discussed.
© The Authors, published by EDP Sciences, 2017
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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