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Onboard assessment of XRF spectra using genetic algorithms for decision making on an autonomous underwater vehicle

Citation

Breen, J and de Souza, P and Timms, GP and Ollington, R, Onboard assessment of XRF spectra using genetic algorithms for decision making on an autonomous underwater vehicle, Nuclear Instruments and Methods in Physics Research. Section B. Beam Interactions With Materials and Atoms, 269, (12) pp. 1341-1345. ISSN 0168-583X (2011) [Refereed Article]


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DOI: doi:10.1016/j.nimb.2011.03.012

Abstract

In order to optimise use of the limited resources (time, power) of an autonomous underwater vehicle (AUV) with a miniaturised X-ray fluorescence (XRF) spectrometer on board to carry out in situ autono- mous chemical mapping of the surface of sediments with desired resolution, a genetic algorithm for rapid curve fitting is reported in this paper. This method quickly converges and provides an accurate in situ assessment of metals present, which helps the control system of the AUV to decide on future sampling locations. More thorough analysis of the available data could be performed once the AUV has returned to the base (laboratory).

Item Details

Item Type:Refereed Article
Keywords:Genetic algorithms X-ray fluorescence Autonomous underwater vehicle Environmental monitoring Marine sediments Heavy metals
Research Division:Information and Computing Sciences
Research Group:Artificial Intelligence and Image Processing
Research Field:Neural, Evolutionary and Fuzzy Computation
Objective Division:Environment
Objective Group:Physical and Chemical Conditions of Water
Objective Field:Physical and Chemical Conditions of Water for Urban and Industrial Use
Author:Breen, J (Mr Jeremy Breen)
Author:de Souza, P (Professor Paulo de Souza Junior)
Author:Ollington, R (Dr Robert Ollington)
ID Code:76308
Year Published:2011
Web of Science® Times Cited:6
Deposited By:Computing and Information Systems
Deposited On:2012-03-05
Last Modified:2017-11-18
Downloads:2 View Download Statistics

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