AUTOMATED DETECTION OF METHANOL VAPOR BY OPEN-PATH FOURIER-TRANSFORM INFRARED SPECTROMETRY

Signal processing techniques are developed to detect the presence of methanol vapour in an open path Fourier transform infrared (FTIR) measurement. An automated detection algorithm is implemented through the direct application of digital filtering and pattern recognition methods to short segments of FTIR interferograms. To test the data analysis methodology, a pollutant source of methanol vapour is simulated by the use of open air active bistatic, passive terrestrial, and passive laboratory spectrometer configurations. Approximately 30,000 interferograms collected from these experiments are used in optimizing and testing the digital filtering and pattern recognition techniques. Interferogram segment lengths ranging from 40 to 150 points are evaluated, along with different segment starting positions and filter bandpass widths. Interferogram segments as short as 40 points (0.01 cm optical retardation) are found to yield detection percentages approaching 100%. These results are achieved while maintaining an extremely low rate of false detections (0.5%).