A longwave-infrared (LWIR) passive-spectrometer performance was evaluated with a short-pathlength gas cell. This
cell was accurately positioned between the sensor and a NIST-traceable blackbody radiance source. Cell contents were
varied over the Beer's Law absorbance range from the limit of detection to saturation for the gas analytes of sulfur
hexafluoride and hexafluoroethane. The spectral impact of saturation on infrared absorbance was demonstrated for the
passive sensor configuration. The gas-cell contents for all concentration-pathlength products was monitored with an
active traditional-laboratory Fourier Transform Infrared (FTIR) spectrometer and was verified by comparison with the
established PNNL/DOE vapor-phase infrared (IR) spectral database. For the passive FTIR measurements, the blackbody
source employed a range of background temperatures from 5oC to 50oC. The passive measurements without the presence of a gas cell permitted a determination of the noise equivalent spectral noise (NESR) for each set of passive
gas-cell measurements. In addition, the no-cell condition allowed the evaluation of the effect of gas cell window
materials of low density poly(ethylene), potassium chloride, potassium bromide, and zinc selenide. The components of
gas cell, different window materials, temperature differentials, and absorbances of target-analyte gases supplied the
means of evaluating the LWIR performance of a passive FTIR spectrometer. The various LWIR-passive measurements
were found to simulate those often encountered in open-air scenarios important to both industrial and environmental
monitoring applications.
Infrared airborne spectral measurements were collected over the Gulf Coast area during the aftermath of Hurricanes Katrina and Rita. These measurements allowed surveillance for potentially hazardous chemical vapor releases from industrial facilities caused by storm damage. Data was collected with a mid-longwave infrared multispectral imager and a hyperspectral Fourier transform infrared spectrometer operating in a low altitude aircraft. Signal processing allowed detection and identification of targeted spectral signatures in the presence of interferents, atmospheric contributions, and thermal clutter. Results confirmed the presence of a number of chemical vapors. All detection results were immediately passed along to emergency first responders on the ground. The chemical identification, location, and vapor species concentration information were used by the emergency response ground teams for identification of critical plume releases and subsequent mitigation.
The purged gas containment cell is composed of readily available materials. This cell is charged with analyte samples under the conditions of ambient temperature and pressure. The analyte samples are obtained from dilution of commercially available pure material in lecture bottles. This is achieved by injecting pure analyte material into a Tedlar® bags during filling with a known amount of nitrogen diluent. This study demonstrates the utility of the approach using a series of gas samples with concentration-pathlength products spanning the Beer's law range of infrared absorbances. These absorbance values and blackbody radiance levels are within the linearity range of both the active and passive Fourier transform infrared spectrometers that are used in this study. In addition, these conditions are representative of environments that are often encountered in open-air measurements.
KEYWORDS: Absorbance, Spectroscopy, FT-IR spectroscopy, Black bodies, Infrared spectroscopy, Binary data, Temperature metrology, Signal to noise ratio, Liquids, Sensors
Gravimetrically prepared aqueous binary solutions permit the generation of target vapors of methanol and ammonia in a portable vapor cell. A passive Fourier transform infrared (FT-IR) spectrometer monitors a short pathlength optical cell using a calibrated extended-blackbody background source. The temperature of the blackbody ranges from 5°C to 50°C in five degree increments. This temperature range simulates the radiance levels most often encountered for ambient temperature backgrounds in open-air field measurements. The solute liquid mole fractions determine the resultant vapor concentrations. The water component attenuates the target vapor concentration from that of the pure solute component depending on the solute liquid mole fraction. This study demonstrates the utility of a portable vapor cell using a series of binary aqueous solutions per target compound over the Beer’s Law range of infrared absorbances. These Beer’s Law infrared absorbances and blackbody radiance levels are within the linearity range of the passive FT-IR spectrometer and are representative of open-air field conditions.
Vapor analytes of methanol and ammonia are quantitatively generated separately and as mixtures in the presence of water vapor. Generation of these analytes relies on the vapor liquid equilibria properties of associated aqueous solutions for delivering targeted vapor amounts into an equilibrium vapor cell. Gravimetric solution preparation and maintaining a constant solution temperature permits control of the analyte amount that is delivered to the optical equilibrium vapor cell. A laboratory Fourier transform infrared spectrometer examines the fixed path length optical cell contents. This examination furnishes vapor-phase infrared absorbances for analyte mixtures in the Beer's Law concentration range. Literature vapor liquid equilibrium data and infrared absorbance measurements show that the methanol/ammonia binary compontents of the ternary aqueous solutions of this study exhibit ideal solution behavior.
The use of the equilibrium vapor cell method quantitatively supplies one or more analytes in the presence of water vapor by using the vapor liquid equilibrium properties of aqueous solutions to delivery target vapors. This study demonstrates vapor generation of ammonia, ethanol, and ammonia/ethanol mixtures from aqueous solutions.
Gravimetrically prepared aqueous solutions of ethanol and/or ammonia along with vapor liquid equilibrium data permits assessment of the mixed vapor target amounts delivered into an optical cell. Acquisition of the infrared vapor phase spectra is completed with a laboratory spectrometer for the target vapors in the Beer's law concentration region using a fixed pathlength optical cell. Even though ideal solution behavior is assumed for the ethanol/ammonia interactions in the ternary solutions, the infrared spectral results between the binary and ternary solutions are shown to compare favorably.
An airborne infrared (IR) line-scanner and a Fourier transform infrared (FT-IR) spectrometer operating in the 3- 5micrometers and 8-12micrometers spectral regions provide a rapid wide- area surveillance capability. The IR scene containing target vapors is mapped remotely with the wide fields of view (FOV) multi-spectral IR line-scanner using 14 bands. The narrow FOV FT-IR spectrometer permits remote verification of target vapor plume contents within the IR scene. The IR image and FT-IR interferogram analysis supply a near real-time detection that provides visual monitoring of potential downwind vapor hazards. This capability is demonstrated using the target vapor methanol. An active mono-static FT-IR configuration furnishes ground-truth monitoring for methanol released from an industrial stack and a nearby ground-level area. The airborne and ground-truth results demonstrate the usefulness of this approach in alerting first responders to potential downwind vapor hazards from an accidental release.
Rapid airborne identification and quantification of vapor hazards is an environmentally important capability for a variety of open-air scenarios. This study demonstrates the use of a commercially available passive Fourier transform IR (FT-IR) spectrometer to detect, identify, and quantify ammonia and ethanol vapor signatures depending on the appropriate signal processing strategy. The signal- processing strategy removes the need for a representative background spectrum and it consists of three steps to extract the spectral information associated with the target vapor. The first step is optimal interferogram segment selection which depends on the bandwidth of the target spectral feature. The second step applies the statistically signicant finite impulse responses matrix filter to the optimal interferogram segment to attenuate spectral interferences. The third step quantifies the FIRM filter results with a discriminant analysis. The signal processing results prove that low-altitude airborne passive FT-IR spectrometry allows rapid quantitative detection of ammonia and ethanol vapor generated plumes. This effort also documents the direct interferogram analysis of data from the fast scanning airborne passive FT-IR spectrometer.
KEYWORDS: Sensors, Light emitting diodes, Spectroscopy, Digital signal processing, FT-IR spectroscopy, Signal detection, Modulation, Calibration, Digital filtering, Temperature metrology
Calibration of Fourier transform infrared (FT-IR) spectrometer response is crucial to quantitative spectroradiometric measurements. The use of light emitting diodes (LEDs) as probes of detector channel response is further demonstrated. Detector channel response functions significantly impact spectrometer performance. LED modulation bandwidths, some extending well into the megaHertz (MHz) range, are more than fast enough for characterization of FT-IR detector channel responses. A variety of optical probe signals can be generated using LEDs driven by waveform generators, lock-in amplifiers or digital signal processors. Accurate determination of the phase and gain responses of both the IR signal and laser reference channels is straightforward. With appropriate modulation of the IR LEDs, channel response is measurable on a scan-by-scan basis, perhaps even to the point of accurately determining detector saturation in real time.
Absorbance and transmittance spectra were acquired with ground-based passive FT-IR spectrometry for industrial stack evaluations and open-air controlled vapor generation experiments. The industrial stack effluents of sulfur dioxide and nitrous oxide were detected from a coal-burning power plant and an acid plant, respectively, with both MWIR and LWIR passive sensors. The controlled open-air experiments relied on only a LWIR sensor. These experiments produced plumes of methanol and ethanol at three and four elevated plume temperatures, respectively. Various vapor concentration pathlength produces of both ethanol and methanol were generated and gravimetrically monitored in the range from 0 to 300 ppm-m. The associated absorbance values for these concentration pathlength products were found to obey Beer's Law for each elevate stack temperature of 125, 150, 175, and 200 degrees C.
KEYWORDS: Signal processing, Digital signal processing, FT-IR spectroscopy, Mirrors, Interferometers, Spectroscopy, Sensors, Data processing, Laser processing, Infrared spectroscopy
A new approach to Fourier transform-infrared (FT-IR) signal acquisition and processing has been developed recently. This approach relies on digital signal processing (DSP) and enables the use of sigma-delta analog-to-digital converters (ADCs). Data are simultaneously oversampled from both the infrared (IR) and reference laser channels at uniform time intervals. This approach contrasts sharply with the traditional method, in which reference channel zero-crossings are used to trigger ADC sampling of the IR channel at equal increments of optical path difference (OPD). In one embodiment of the new approach, data from the laser channel are processed to values of mirror position. These data can be used to interpolate the IR signal. The uniform time sampling method shifts instrument complexity from hardware to software, while improving the spectral accuracy by fully correcting the effects of optical velocity variation. The correction is sufficient even with a sinusoidal variation in the optical retardation rate. This study demonstrates the approach using the Lomb-Scargle periodogram.
Passive standoff FTIR spectrometry relies on the radiance differential between a background scene and a target vapor analyte. Unlike traditional FTIR approaches controlling radiance levels within a narrow range, the passive configuration often encounters a large variance in radiance levels. This places higher demands on the passive FTIR configuration for maintaining linearity. The present study assesses the radiometric linearity of a passive FTIR configuration using controlled blackbody radiance in conjunction with target samples such as a polystyrene film and ethanol vapors.
A commercial digital signal processor (DSP) board with custom software monitors the operation of an FTIR spectrometer. The DSP board acquires interferogram data simultaneously from both the infrared and reference laser channels of the FTIR spectrometer. This approach permits post-processing of the signals to obtain conventional spectra, as well as a variety of diagnostics. Such diagnostics include extraction of interferometer mirror velocity and the combined transfer functions of the detectors, amplifiers and filters. The DSP board resides in the accessory bus of a personal computer (PC), allowing use of the PC and its peripherals for data display, storage and post-processing. A method for extracting the transfer functions of the laser and infrared channels by the use of solid state emitters is presented. These are the key elements required to monitor and correct the effects of velocity error. The simultaneous digitization of both interferometer channels may be a trend in FTIR spectrometer design, which shifts signal processing further towards soft implementations.
Diagnostic computer programs permit the evaluation of FTIR spectrometer thermal, spectral, and interferogram stability. Raw interferogram data is required under four conditions: (1) equal time increments, (2) error code detection, (3) interferogram center burst threshold change, and (4) user request. Collection of raw interferogram data furnishes a robust means of detection and identification of various instabilities, which occur in passive FTIR spectrometers.
Computer-generated synthetic single-beam spectra and interferograms are used to study signal processing strategies for passive Fourier transform IR (FTIR) sensor. Synthetic data are generated for one-, two-, and four- component mixtures of organic vapors in two passive FTIR remote sensing scenarios. The single-beam spectra are processed using Savitsky-Golay smoothing, first derivative, and second derivative filters of various orders and widths. Interferogram data are processed by Fourier filtering using Gaussian-shaped bandpass digital filters. Pattern recognition of the target analyte spectral signature is performed using soft independent modeling of class analogy. Quantitative models for the target gas integrated concentration-path length product are built using partial least-squares regression and locally weighted regression. Pattern recognition and calibration models of the filtered spectra and interferograms produced similar results. Chemical detection is possible for complex mixtures if the temperature difference between the source and analyte cloud is sufficiently large. Quantitative analysis is possible if the temperature of the analyte cloud is stable or known and is sufficiently different from the background temperature.
The spectroradiometric performance characteristics of a FT- IR spectrometer are evaluated as a function of temperature, optical mirror velocity, and spectral resolution. The noise equivalent radiance per root Hertz is used in these noise evaluations and is shown to be an important Michelson interferometer figure of merit.
A FT-IR spectrometer thermal stability, responsivity and self emission was evaluated under controlled laboratory conditions. Internal diagnostics provided by the FT-IR spectrometer design insured the acquisition of accurate and precise spectral data. Absorbance measurements performed using the spectrometer agreed to within 3% of the literature values. The internal polystyrene film permitted a reliable assessment of the wavenumber axis registration which is critical in the identification of target analyte spectral features.
KEYWORDS: Digital filtering, Spectroscopy, Optical filters, Pattern recognition, Signal to noise ratio, FT-IR spectroscopy, Black bodies, Infrared radiation, Infrared spectroscopy, Signal attenuation
The detection of gaseous ammonia with open-path Fourier transform spectrometry furnishes a means of accessing fugitive emissions from various industrial production processes by stack and site monitoring. This study relies on direct interferogram analysis of passive infrared data from open-air industrial and controlled laboratory environments. Direct interferogram analysis permits the identification of ammonia emissions by detection of the (nu) 2 spectral bands in the interferogram time domain.
In the interest of developing practical methodologies for remote passive FT-IR analysis of sulfur dioxide in heated smoke stack plumes, IR spectra have been collected in a number of relevant experiments. Field data includes passive remote FT-IR spectra collected at a coal-burning power plant for which plume conditions were characterized by in-stack continuous emission monitors (CEMs), spectra collected of a controlled plume from a model spectrometer, into which controlled levels of sulfur dioxide could be introduced while the spectrometer viewed sky backgrounds similar to those behind the actual power plant plume. An extensive spectral data set has also been collected in the laboratory under controlled target and background conditions using a heated cell. Typical spectra are presented and the potential for characterizing many of the important factors involved in remote passive FT-IR analyses through controlled- condition experiments such as these is discussed.
In many open-air monitoring applications of Fourier transform spectrometry (FTS), the lack of a valid background reference spectrum limits the ability to perform quantitative measurements. Suppression of the broad band detector envelope overcomes this limitation. Interferogram processing provides a means of suppressing the broad band background, while maintaining the target spectral signatures of interest. A combination of interferogram segment selection, digital filtering, and pattern discrimination techniques achieve the background suppression of the variable broad band detector envelope. The spectral band position, width, and strength of the target vapor determine the parameters that are used for background suppression. Interferogram segment selection depends primarily on spectral band width. Digital filter design requires inputs of both spectral band position and width. The pattern discrimination techniques compensate for variation in the spectral shape with band strength.
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