A new analytical technique, named fragmentary spectrum registration (FSR), with use of acousto-optical spectrometers
(AOS’s) is proposed and studied. It is based on the method of differential optical absorption spectroscopy (DOAS) and
the unique AOS feature of fast (10 μs) random spectral access (RSA). The technique is the most efficient for objects
exhibiting sparse optical spectra. The technique permits a substantial (up to 100 times) reduction of detection time in
comparison with the record time of total spectrum and provides the decrease of inaccuracy of quantitative analysis of
multicomponent mixtures containing substances with similar spectral features. The results of numerical simulation with
use of real spectra detected by the trace gas monitoring system GAOS based on AOS are presented and discussed. The
experimental results demonstrate the capabilities of the FSR-technique for the huge reduction of the measurement time
or for the decrease of measurement error (up to 2.5 times) when the total measurement time is fixed while concentrations
being varied from the environment background up to industrial emissions level.
It is discussed the reliability problem of time-optimized method for remote optical spectral analysis of gas-polluted
ambient air. The method based on differential optical absorption spectroscopy (DOAS) enables fragmentary spectrum
registration (FSR) and is suitable for random-spectral-access (RSA) optical spectrometers like acousto-optical (AO)
ones. Here, it is proposed the algorithm based on statistical method of independent component analysis (ICA) for estimation of a correctness of absorption spectral lines selection for FSR-method. Implementations of ICA method for RSA-based real-time adaptive systems are considered. Numerical simulations are presented with use of real spectra detected by the trace gas monitoring system GAOS based on AO spectrometer.
An optimized algorithm of quantitative gas analysis for spectrometers based on acousto-optical tunable filters (AOTFs)
is presented. Efficiency of the algorithm is based on unique feature of AOTFs - random spectral access. This property
makes it possible utilization of specialized procedures for on-line processing of spectral information without any
significant loss of time. The procedure of finding optimal set of spectral points has developed and presented. The
optimized algorithm has been tested with use of gas analytical system GAOS comprising movable spectrometer based on
double-stage collinear AOTF. GAOS uses differential optical absorption spectroscopy (DOAS) for measuring gases
abundance. Optimized algorithm improves the accuracy of the results and reduces measurement time compared to
spectral-scanning algorithm. It can be used for such applications as rapid analysis of emissions in emergency, the
analysis of large collection of samples in the laboratory or in the production processes, etc. An optimized calibration
procedure for gas analyzers employing AOTF-based spectrometers is presented. It takes into account the possible
interference of the calibration coefficients of different substances and is insensitive to possible ill-conditioned calibration
matrix. Using the optimized calibration procedure allows to reduce the systematic error.
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