Paper
19 January 1995 Chemical recognition software
John S. Wagner, Michael W. Trahan, Willie E. Nelson, Philip J. Hargis Jr., Gary C. Tisone
Author Affiliations +
Proceedings Volume 2367, Optical Sensors for Environmental and Chemical Process Monitoring; (1995) https://doi.org/10.1117/12.199671
Event: Optical Sensing for Environmental and Process Monitoring, 1994, McLean, VA, United States
Abstract
We have developed a capability to make real time concentration measurements of individual chemicals in a complex mixture using a multispectral laser remote sensing system. Our chemical recognition and analysis software consists of three parts: (1) a rigorous multivariate analysis package for quantitative concentration and uncertainty estimates, (2) a genetic optimizer which customizes and tailors the multivariate algorithm for a particular application, and (3) an intelligent neural net chemical filter which pre-selects from the chemical database to find the appropriate candidate chemicals for quantitative analyses by the multivariate algorithms, as well as providing a quick-look concentration estimate and consistency check. Detailed simulations using both laboratory fluorescence data and computer synthesized spectra indicate that our software can make accurate concentration estimates from complex multicomponent mixtures, even when the mixture is noisy and contaminated with unknowns.
© (1995) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
John S. Wagner, Michael W. Trahan, Willie E. Nelson, Philip J. Hargis Jr., and Gary C. Tisone "Chemical recognition software", Proc. SPIE 2367, Optical Sensors for Environmental and Chemical Process Monitoring, (19 January 1995); https://doi.org/10.1117/12.199671
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KEYWORDS
Chemical analysis

Neural networks

Genetics

Databases

Genetic algorithms

Detection and tracking algorithms

Luminescence

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