Methane detection using wavelength modulation spectroscopy and a multiline quantitation method
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Identificadores
URI: http://hdl.handle.net/10902/2360DOI: 10.1117/12.623141
ISSN: 1996-756X
ISSN: 0277-786X
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Conde Portilla, Olga María



Date
2005-09-14Derechos
© 2005 Society of Photo-Optical Instrumentation Engineers. One print or electronic copy may be made for personal use only. Systematic electronic or print reproduction and distribution, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper are prohibited.
Publicado en
Proceedings of SPIE, 2005, vol. 5948, 59482J
Photonics Applications in Industry and Research IV, Varsovia, 2005
Publisher
SPIE Society of Photo-Optical Instrumentation Engineers
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Palabras clave
Methane
Wavelength modulation spectroscopy (WMS)
Inverse least squares (ILS)
Abstract:
In this paper the application of the Inverse Least Squares algorithm (ILS) to the detection of methane using its behaviour in the near-infrared band is presented. In order to test the effectiveness of this method, different methane concentrations were measured. Wavelength Modulation Spectroscopy (WMS) was employed to obtain the first and second harmonics of the modulation signal. The use of both harmonics in spectroscopy eliminates the dependence of the measured absorbance on parameters such as: fiber misalignments, optical power fluctuations, etc. This property greatly increases the accuracy of the concentration readings. The benefits of analysing multiple lines in gas detection are discussed together with the capabilities of the ILS algorithm. The ILS algorithm is based on the Beer-Lambert law. This law is extended to include multiple wavelengths and rearranged in such a way that the concentration of the chemical species depends on the measured absorbances. In order to apply the previous algorithm, three absorption lines centered at 1665.961 nm, 1666.201 nm and 1666.483 nm were used. The obtained results are compared with the most usual single-line calibration method based on linear regression. This comparison shows that ILS gives a superior performance. Specifically, results indicate that the ILS multiline algorithm is less noise dependent and has a higher reliability than single-line calibration methods.
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