Hyperspectral Imaging of a Turbine Engine Exhaust Plume to Determine Radiance, Temperature, and Concentration Spatial Distributions

摘要

The usefulness of imaging Fourier transform spectroscopy (IFTS) when looking at a rapidly varying turbine engine exhaust scene was explored by characterizing the scene change artifacts (SCAs) present in the plume and the effect they have on the calibrated spectra using the Telops, Inc.-manufactured Field-portable Imaging Radiometric Spectrometer Technology, Midwave Extended (FIRST-MWE). It was determined that IFTS technology can be applied to the problem of a rapidly varying turbine engine exhaust plume due to the zero mean, stochastic nature of the SCAs, through the use of temporal averaging. The FIRST- MWE produced radiometrically calibrated hyperspectral datacubes, with calibration uncertainty of 35% in the 1800 - 2500 cm(-1) (4 - 5.5 micrometer) spectral region for pixels with signal-to-noise ratio (SNR) greater than 1.5; the large uncertainty was due to the presence of SCAs. Spatial distributions of temperature and chemical species concentration pathlengths for CO2, CO, and H2O were extracted from the radiometrically calibrated hyperspectral datacubes using a simple radiative transfer model for diesel and kerosene fuels, each with fuel flow rates of 300 cm3/min and 225 cm3/min. The temperatures were found to be, on average, within 212 K of in situ measurements, the difference attributed to the simplicity of the model. Although no in situ concentration measurements were made, the concentrations of CO2 and CO were found to be within expected limits set by the ambient atmospheric parameters and the calculated products of the turbine engine, on the order of 10 to the 15th power and 10 to the 17th power molecules/cm3, respectively.