AUTOMATED DETECTION OF TRICHLOROETHYLENE BY FOURIER-TRANSFORM INFRARED REWROTE SENSING MEASUREMENTS

Passive Fourier transform infrared (FT-IR) remote sensing measurements are used to implement the automated detection of trichloroethylene (T CE) vapor in the presence of a variety of infrared background signatur es, Through the use of a combination of bandpass digital filtering and piecewise linear discriminant analysis, this detection procedure is a pplied directly to short segments of the interferogram data collected by the FT-LR spectrometer, Data employed id this work were collected d uring open-air/passive cell terrestrial and passive cell laboratory me asurements, infrared backgrounds employed included terrain, low-angle sky, and water backgrounds, in addition to laboratory blackbody measur ements, Other potentially interfering chemical species present were ca rbon tetrachloride, acetone, methyl ethyl ketone, and sulfur hexafluor ide (SF6). These data are used to assemble two data sets of differing complexity, Optimization studies are performed separately with each. d ata set to study the influence of filter bandpass position, bandpass w idth, interferogram segment location, and segment size on the ability to detect TCE, The optimal parameters found consist of a Gaussian-shap ed filter positioned at 939.5 cm(-1), with a width at half-height of 1 23.4 cm(-1). This filter is applied to interferogram points 111-220 (r elative to the center-burst), When applied to a prediction set of 60 0 00 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 fals e detections is 0.5%, The limit of detection of TCE is found to be 102 ppm-m at a temperature difference of 10.5 degrees C between the infra red background and the analyte, SF6 is observed to provide the greates t 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 tile development of a probability-based in terpretation of the piecewise Linear discriminant results, These resul ts are observed to compare favorably with those obtained in a separate analysis of filtered single-beam spectra.