Analysis of fast gas-chromatographic signals with artificial neural systems

Douglas A. Palmer; Eugene K. Achter; David Lieb

doi:10.1117/12.142889

1 April 1993 Analysis of fast gas-chromatographic signals with artificial neural systems

Douglas A. Palmer, Eugene K. Achter, David Lieb

Proceedings Volume 1824, Applications of Signal and Image Processing in Explosives Detection Systems; (1993) https://doi.org/10.1117/12.142889
Event: Applications in Optical Science and Engineering, 1992, Boston, MA, United States

Abstract

Thermedics Detection's explosive detectors use fast gas chromatograph analyzers to identify key components in explosives. The analyzer produces a time series of measurements which identify mobility through the columns. This time series of measurements appears as a spectrum of values with peaks corresponding to certain substances, explosive and otherwise. The analytical task of the system is to isolate the signal peaks from the detection noise, background, pedestals and peaks from extraneous substances. A uniquely modified back- propagation neural network (non-linear adaptive filter) was developed to perform the signal analysis. The unique feature of this signal analysis system was the analysis to train the network to provide only signal amplitudes but, additionally, a measure of confidence in the derived amplitudes with respect to the simulated interferents, random noise and peak time jitter included in the training. Alarms can then be set according to confidence of detection.

Citation Download Citation

Douglas A. Palmer, Eugene K. Achter, and David Lieb "Analysis of fast gas-chromatographic signals with artificial neural systems", Proc. SPIE 1824, Applications of Signal and Image Processing in Explosives Detection Systems, (1 April 1993); https://doi.org/10.1117/12.142889

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