Use of Multivariate Analysis to Determine Temperature from Low-Resolution Infrared Spectra of Carbon Dioxide

Szczepanski, Michael P.; Fountain, Augustus W.

doi:10.1366/0003702001949393

Cited by 3 publications

(2 citation statements)

References 7 publications

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“…Previous work by Gary Small et al 4 and Szczepanski et al 5 has shown that the determination of plume concentration by passive-remote IR sensing is highly dependent on temperature. Even though the filament reached temperatures at or above 500 8C, the pressures and temperatures of the generated gases were small.…”

Section: Resultsmentioning

confidence: 99%

Development of a Thermal Evaporation Cell for Gas-Phase Infrared Absorption Spectroscopy of Compounds with Low Volatility

Ingram

Fountain

2007

Appl Spectrosc

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To facilitate in-depth hazard prediction models, we must understand the spectral properties of expulsion plumes from conventional weapon attacks. Precise data on the spectral absorption of three chemical weapon agent simulants, in the infrared regime, are required to properly determine the mass of simulant in expulsion plumes from field demonstrations and small scale tests. Data for triethyl phosphate (a Soman simulant), triethyl phosphite (a Sarin simulant), and tributyl phosphate (a VX simulant) are presented. A thermal evaporation cell was designed and built that incorporated features that are not commercially available.

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Section: Resultsmentioning

confidence: 99%

Development of a Thermal Evaporation Cell for Gas-Phase Infrared Absorption Spectroscopy of Compounds with Low Volatility

Ingram

Fountain

2007

Appl Spectrosc

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“…After the calibration measurements a calibration model is constructed, which is then used for determining the content of the tested substances. This method can also be used to determine temperature, but only to a very limited extent [13]. Conditions applicable to the empirical calibration measurements in emission spectroscopy are achieved only for very short measurement paths [14].…”

Section: Introductionmentioning

confidence: 99%

Inversion of Remote Sensing Data Using Multiple Ratios of Spectral Radiation Intensities and Neural Networks

Cięszczyk

2017

Acta Phys. Pol. A

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The article presents a method for determining the content and temperature on the basis of spectra from remote measurements. The technique uses measurements of a high resolution radiation spectrum that allows the visibility of the individual rotational lines of gases such as CO2, used here in the range of 2470-2495 cm −1 . At the same time a new algorithm is applied of pre-processing the spectrum, involving the use of multiple ratios of intensity at several wavenumbers as input to an inverse model based on neural networks. Due to it, the dimensionality of the input can significantly be reduced. Additionally, the data interpreted do not have to be measured in units of spectral radiance. Thus only the calibration of the sensitivity of the spectrometer at various wavelengths is required. The neural models were constructed on the basis of data from the simulation. The proposed method works with a uniform layer of radiating gas for determining the temperature and CO2 content. For a non-uniform layer it is possible to determine the line-of-sight temperature profile and average gas content. The method can be extended to different spectral ranges and to other gases present in substantial quantities in the exhaust gases of various processes.

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Comparison of Spectral and Interferogram Processing Methods Using Simulated Passive Fourier Transform Infrared Remote Sensing Data

Shaffer¹,

Combs²

2001

Appl Spectrosc

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Computer-generated synthetic single-beam spectra and interferograms provide a means of comparing signal processing strategies that are employed with passive Fourier transform infrared (FT-IR) sensors. With the use of appropriate radiance models and spectrometer characteristics, synthetic data are generated for one-, two-, and four-component mixtures of organic vapors (ethanol, methanol, acetone, and methyl ethyl ketone) in two passive FT-IR remote sensing scenarios. The single-beam spectra are processed by using Savitsky–Golay smoothing and first-derivative and second-derivative filters. Interferogram data are processed by Fourier filtering using Gaussian-shaped bandpass digital filters. Pattern recognition is performed with soft independent modeling of class analogy (SIMCA). Quantitative models for the target gas integrated concentration-path-length product are built by using either partial least-squares (PLS) regression or locally weighted regression (LWR). Pattern recognition and calibration models of the filtered spectra or interferograms produced comparable results. Discrimination of target analytes in complex mixtures requires a sufficiently large temperature differential between the infrared background source and analyte cloud. Quantitative analysis is found to be possible only when the temperature of the analyte cloud is stable or known and differs significantly from the background temperature. Net analyte signal (NAS) methods demonstrate that interferogram and spectral processing methods supply identical information for multivariate pattern recognition and calibration.

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Use of Multivariate Analysis to Determine Temperature from Low-Resolution Infrared Spectra of Carbon Dioxide

Cited by 3 publications

References 7 publications

Development of a Thermal Evaporation Cell for Gas-Phase Infrared Absorption Spectroscopy of Compounds with Low Volatility

Development of a Thermal Evaporation Cell for Gas-Phase Infrared Absorption Spectroscopy of Compounds with Low Volatility

Inversion of Remote Sensing Data Using Multiple Ratios of Spectral Radiation Intensities and Neural Networks

Comparison of Spectral and Interferogram Processing Methods Using Simulated Passive Fourier Transform Infrared Remote Sensing Data

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