NDLI: Multispectral Mid-Infrared Camera System for Accurate Stand-Off Temperature and Column Density Measurements on Flames

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Multispectral Mid-Infrared Camera System for Accurate Stand-Off Temperature and Column Density Measurements on Flames

Content Provider	MDPI
Author	Juan, Meléndez Guarnizo, Guillermo
Copyright Year	2021
Abstract	Accurate measurement of temperature in flames is a challenging problem that has been successfully addressed by hyperspectral imaging. This technique is able to provide maps of not only temperature T (K) but also of column density Q (ppm $\cdot$ m) of the main chemical species. Industrial applications, however, require cheaper instrumentation and faster and simpler data analysis. In this work, the feasibility and performance of multispectral imaging for the retrieval of T and Q $_{{C O}_{2}}$ in flames are studied. Both the hyperspectral and multispectral measurement methods are described and applied to a standard flame, with known T and Q $_{{C O}_{2}}$ , and to an ordinary Bunsen flame. Hyperspectral results, based on emission spectra with $0.5$ cm $^{- 1}$ resolution, were found in previous works to be highly accurate, and are thus considered as the ground truth to compare with multispectral measurements of a mid-IR camera (3 to 5 $μ$ m) with a six interference filter wheel. Maps of T and Q obtained by both methods show that, for regions with T $≳ 1300$ K, the average of relative errors in multispectral measurements is ∼5% for T (and can be reduced to ∼2.5% with a correction based on a linear regression) and ∼20% for Q. Results obtained with four filters are very similar; results with two filters are also similar for T but worse for Q.
Starting Page	8395
e-ISSN	14248220
DOI	10.3390/s21248395
Journal	Sensors
Issue Number	24
Volume Number	21
Language	English
Publisher	MDPI
Publisher Date	2021-12-16
Access Restriction	Open
Subject Keyword	Sensors Spectroscopy Infrared Imaging Multispectral Imaging Hyperspectral Imaging Combustion Monitoring Remote Sensing and Sensors Fourier Transform Image Processing
Content Type	Text
Resource Type	Article

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