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Identification of Corrosion Minerals Using Shortwave Infrared Hyperspectral Imaging

In this study, we propose a new method to identify corrosion minerals in carbon steel using hyperspectral imaging (HSI) in the shortwave infrared range (900–1700 nm). Seven samples were artificially corroded using a neutral salt spray test and examined using a hyperspectral camera. A normalized cros...

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Autores principales: De Kerf, Thomas, Pipintakos, Georgios, Zahiri, Zohreh, Vanlanduit, Steve, Scheunders, Paul
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8749733/
https://www.ncbi.nlm.nih.gov/pubmed/35009949
http://dx.doi.org/10.3390/s22010407
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author De Kerf, Thomas
Pipintakos, Georgios
Zahiri, Zohreh
Vanlanduit, Steve
Scheunders, Paul
author_facet De Kerf, Thomas
Pipintakos, Georgios
Zahiri, Zohreh
Vanlanduit, Steve
Scheunders, Paul
author_sort De Kerf, Thomas
collection PubMed
description In this study, we propose a new method to identify corrosion minerals in carbon steel using hyperspectral imaging (HSI) in the shortwave infrared range (900–1700 nm). Seven samples were artificially corroded using a neutral salt spray test and examined using a hyperspectral camera. A normalized cross-correlation algorithm is used to identify four different corrosion minerals (goethite, magnetite, lepidocrocite and hematite), using reference spectra. A Fourier Transform Infrared spectrometer (FTIR) analysis of the scraped corrosion powders was used as a ground truth to validate the results obtained by the hyperspectral camera. This comparison shows that the HSI technique effectively detects the dominant mineral present in the samples. In addition, HSI can also accurately predict the changes in mineral composition that occur over time.
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spelling pubmed-87497332022-01-12 Identification of Corrosion Minerals Using Shortwave Infrared Hyperspectral Imaging De Kerf, Thomas Pipintakos, Georgios Zahiri, Zohreh Vanlanduit, Steve Scheunders, Paul Sensors (Basel) Article In this study, we propose a new method to identify corrosion minerals in carbon steel using hyperspectral imaging (HSI) in the shortwave infrared range (900–1700 nm). Seven samples were artificially corroded using a neutral salt spray test and examined using a hyperspectral camera. A normalized cross-correlation algorithm is used to identify four different corrosion minerals (goethite, magnetite, lepidocrocite and hematite), using reference spectra. A Fourier Transform Infrared spectrometer (FTIR) analysis of the scraped corrosion powders was used as a ground truth to validate the results obtained by the hyperspectral camera. This comparison shows that the HSI technique effectively detects the dominant mineral present in the samples. In addition, HSI can also accurately predict the changes in mineral composition that occur over time. MDPI 2022-01-05 /pmc/articles/PMC8749733/ /pubmed/35009949 http://dx.doi.org/10.3390/s22010407 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
De Kerf, Thomas
Pipintakos, Georgios
Zahiri, Zohreh
Vanlanduit, Steve
Scheunders, Paul
Identification of Corrosion Minerals Using Shortwave Infrared Hyperspectral Imaging
title Identification of Corrosion Minerals Using Shortwave Infrared Hyperspectral Imaging
title_full Identification of Corrosion Minerals Using Shortwave Infrared Hyperspectral Imaging
title_fullStr Identification of Corrosion Minerals Using Shortwave Infrared Hyperspectral Imaging
title_full_unstemmed Identification of Corrosion Minerals Using Shortwave Infrared Hyperspectral Imaging
title_short Identification of Corrosion Minerals Using Shortwave Infrared Hyperspectral Imaging
title_sort identification of corrosion minerals using shortwave infrared hyperspectral imaging
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8749733/
https://www.ncbi.nlm.nih.gov/pubmed/35009949
http://dx.doi.org/10.3390/s22010407
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