ArticleSensors (Basel, Switzerland)2022
Identification of Corrosion Minerals Using Shortwave Infrared Hyperspectral Imaging.
Article in Sensors (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
4 citing papers in PubMed.
- Standardized Short-Wave Infrared Hyperspectral Imaging for Non-Destructive Spectral Comparison of Coin Denominations, Design Variants, and Surface-Use Conditions.Sensors (Basel, Switzerland) · 2026Article
- From hyperspectral to multispectral: Robust corrosion detection in iron and steel using minimal bands.PNAS nexus · 2026Article
- Spectral-Structural Collaborative Learning for Fine-Grained Hyperspectral Mineral Classification.Sensors (Basel, Switzerland) · 2026Article
- Quantitative detection of corrosion minerals in carbon steel using shortwave infrared hyperspectral imaging.RSC advances · 2022Article
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
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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Registered trials
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