Further development of artificial neural networks for spectral interference correction in optical emission spectrometry

Z. Li; S. Huang; V. Karanassios

doi:10.1117/12.919570

10 May 2012 Further development of artificial neural networks for spectral interference correction in optical emission spectrometry

Z. Li, S. Huang, V. Karanassios

Author Affiliations +

Proceedings Volume 8401, Independent Component Analyses, Compressive Sampling, Wavelets, Neural Net, Biosystems, and Nanoengineering X; 84010Y (2012) https://doi.org/10.1117/12.919570
Event: SPIE Defense, Security, and Sensing, 2012, Baltimore, Maryland, United States

Abstract

Spectral overlaps causing spectral interference are a key concern in elemental analysis by optical emission spectrometry. Spectral interferences are addressed using a variety of methods, including artificial neural networks (ANNs). In my lab, these methods are being developed using both experimentally-obtained results and spectral simulations. ANNs are being developed for inductively coupled plasma-atomic emission spectrometry (ICP-AES) and for optical emission measurements using microplasmas and portable emission spectrometers. In this paper, the application of ANNS for spectral interference correction is described in some detail.

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Z. Li, S. Huang, and V. Karanassios "Further development of artificial neural networks for spectral interference correction in optical emission spectrometry", Proc. SPIE 8401, Independent Component Analyses, Compressive Sampling, Wavelets, Neural Net, Biosystems, and Nanoengineering X, 84010Y (10 May 2012); https://doi.org/10.1117/12.919570

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