LIBS controls characterization of predictor corrector-based LIBS data collection

Alex Sanders; Steven T. Griffin

doi:10.1117/12.2016193

29 May 2013 LIBS controls characterization of predictor corrector-based LIBS data collection

Alex Sanders, Steven T. Griffin

Proceedings Volume 8710, Chemical, Biological, Radiological, Nuclear, and Explosives (CBRNE) Sensing XIV; 87101P (2013) https://doi.org/10.1117/12.2016193
Event: SPIE Defense, Security, and Sensing, 2013, Baltimore, Maryland, United States

Abstract

Portable LIBS sensor communication bandwidth limitations favor local material classification for low power consumption. Partial Least Squares - Discriminant Analysis (PLS-DA) and Principle Component Analysis (PCA) have been implementation via general purpose computers and are accepted for some Department of Defense applications. Prior publications address the creation of a low mass, low power, robust hardware spectra classifier for a limited set of predetermined materials in an atmospheric matrix. The incorporation of a PCA or a PLS-DA classifier into a predictorcorrector implementation on a TI6701 has been developed. The performance modeling of the control system with an emphasis on further optimization needs addressing. This paper characterizes, from a control system standpoint, the predictor-corrector architecture applied to LIBS data collection. In addition, the application of this as a material classifier is presented. Updates in the model implemented on a low power multi-core DSP will be presented as well. Performance comparisons to alternative control system structures will be considered.

Citation Download Citation

Alex Sanders and Steven T. Griffin "LIBS controls characterization of predictor corrector-based LIBS data collection", Proc. SPIE 8710, Chemical, Biological, Radiological, Nuclear, and Explosives (CBRNE) Sensing XIV, 87101P (29 May 2013); https://doi.org/10.1117/12.2016193

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