Automated Detection of Trichloroethylene by Fourier Transform Infrared Remote Sensing Measurements

Abstract

Passive Fourier transform infrared (FT-IR) remote sensing measurements are used to implement the automated detection of trichloroethylene (TCE) vapor in the presence of a variety of infrared background signatures. Through the use of a combination of bandpass digital filtering and piecewise linear discriminant analysis, this detection procedure is applied directly to short segments of the interferogram data collected by the FT-IR spectrometer. Data employed in this work were collected during openair/passive cell terrestrial and passive cell laboratory measurements. Infrared backgrounds employed included terrain, low-angle sky, and water backgrounds, in addition to laboratory blackbody measurements. Other potentially interfering chemical species present were carbon tetrachloride, acetone, methyl ethyl ketone, and sulfur hexafluoride (SF 6 ). These data are used to assemble two data sets of differing complexity. Optimization studies are performed separately with each data set to study the influence of filter bandpass position, bandpass width, interferogram segment location, and segment size on the ability to detect TCE.The optimal parameters found consist of a Gaussian-shaped filter positioned at 939.5 cm -1 , with a width at half-height of 123.4 cm -1 . This filter is applied to interferogram points 111-220 (relative to the centerburst). When applied to a prediction set of 60 000 interferograms, the piecewise linear discriminant developed on the basis of these optimal parameters is found to detect TCE successfully in 96.2% of the cases in which it is present. The overall rate of false detections is 0.5%. The limit of detection of TCE is found to be 102 ppm-m at a temperature difference of 10.5 °C between the infrared background and the analyte. SF 6 is observed to provide the greatest spectral interference among the compounds tested, producing a false detection rate of 8.6%. It is found that this false detection rate can be reduced to 1.5% through the development of a probabilitybased interpretation of the piecewise linear discriminant results. These results are observed to compare favorably with those obtained in a separate analysis of filtered singlebeam spectra.

Software for Generating Synthetic Passive Fourier Transform Infrared Interferograms and Single-beam Spectra.

“…Groups of 50 consecutive interferograms were acquired and subsequently averaged for each specific blackbody radiance temperature. This or similar laboratory experimental configurations have been employed in several other studies [9,10,19,20].…”

“…The traditional limitations to the passive measurement have been the lack of a stable infrared background and the occurrence of weak spectral signatures for the analytes of interest. Recently, workers have demonstrated great promise in overcoming these limitations through the application of advanced signal processing and pattern recognition algorithms to raw FT-IR interferograms [8][9][10][11]. While powerful, these methods require specific information about the analytes of interest and robust signal processing schemes since each interferogram point contain components of all spectral frequencies.…”

Advances in optical methods for trace gas analysis

“…For these sensors, the rapidly changing field of view places particularly high demands on the data acquisition/processing rates. Continued research and development of ultrahigh-speed interferometers [10], focal plane array spectrometers [11], and direct interferogram analysis methods [12] will further improve the spectral and spatial imaging capabilities of passive airborne sensors as well as improve infrared spectrometer performance in general.…”

Vibrational Detection of Hazardous Materials Based on Multivariate Sensors

“…IR vibrational spectra can to be used for identify and quantify samples in complex matrices because each substance has its own fingerprint spectrum in the mid IR (MIR). This means that IR spectroscopy can be used for discriminant analysis even when the target analyte is in very small quantities [10][11][12].…”