Monitoring system for corrosion in metal structures using a probe based hyperspectral imager

Antony, Maria Merin; Sandeep, C. S. Suchand; Matham, Murukeshan Vadakke

doi:10.1117/12.2542907

Cited by 5 publications

(4 citation statements)

References 16 publications

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“…For instance, Halford et al [ 27 ] used a HSI to inspect corrosion on bronze sculptures. As for steel samples, Antony et al [ 28 ] used an HSI with a fiber bundle probe attached to classify corrosion on steel samples. Thanks to the fiber bundle, the device can be efficiently used in difficult to access spaces.…”

Section: Introductionmentioning

confidence: 99%

Identification of Corrosion Minerals Using Shortwave Infrared Hyperspectral Imaging

Kerf

Pipintakos

Zahiri

et al. 2022

Sensors

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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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Section: Introductionmentioning

confidence: 99%

Identification of Corrosion Minerals Using Shortwave Infrared Hyperspectral Imaging

Kerf

Pipintakos

Zahiri

et al. 2022

Sensors

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“…De Kerf et al could determine areas with the corrosion minerals goethite, magnetite, lepidocrocite and hematite via spectral correlation in the wavelength range from 900 to 1700 nm and could further detect changes in mineral composition over time in the laboratory and compared it with fourier-transform infrared spectroscopy [2]. Antony et al applied a fiber bundle probe attached to a hyperspectral camera to classify corrosion areas on steel [3,4]. Aljah et al worked on hyperspectral classification models to predict and evaluate conditions of steel bridges, however only preliminary results are reported [5].…”

Section: State Of the Art Of Hyperspectral Corrosion Detectionmentioning

confidence: 99%

Hyperspectral imaging systems for corrosion detection from remotely operated vehicles

Thomas,

Gündel

2023

ce papers

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The detection of corrosion, especially in early stages, is a key factor for cost reduction in the maintenance of steel infrastructure. However, manual inspection is time consuming and takes considerable effort of people and equipment. Remotely operated vehicles with application‐specific sensors may overcome this problem. Novel sensing approaches like hyperspectral imaging (HSI) systems in combination with machine learning algorithms open new pathways for the rapid inspection of large surface areas in complex environments. In contrast to conventional RGB imaging, HSI contains both spatial and spectral reflectivity information over the complete visual spectral range and near infrared. This offers improved material characterization and classification possibilities using the chemical properties contained in the local reflection spectrum.This paper presents advantages and disadvantages of hyperspectral imaging systems for the detection of corrosion of steel infrastructure as well as suitable wavelength ranges for use with remotely operated vehicles. Furthermore, in‐field measurements with HSI for the inspection of corrosion on steel structures are shown.

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“…Most of the vertical farms rely on manual visual inspection for crop monitoring, which can be quite subjective, timeconsuming, and tedious, especially in the case of large farms [2]. Hyperspectral imaging (HSI) is a promising nondestructive technique for automated sensing and monitoring in biomedical [3][4][5], agriculture [6][7][8][9], marine [10][11][12], pharmaceutical [13] and remote sensing applications [14,15]. There are methods that offer automated systems based on HSI for crop monitoring using advanced digital image processing and artificial intelligence (AI) [16].…”

Section: Introductionmentioning

confidence: 99%

A fast analysis approach for crop health monitoring in hydroponic farms using hyperspectral imaging

Merin Antony,

Suchand Sandeep,

M.M.

et al. 2024

Photonic Technologies in Plant and Agricultural Science

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Hydroponic farming is considered as a more sustainable solution in comparison to conventional farming. Most of the hydroponic farms rely on manual visual inspection for crop monitoring, which can be subjective, time-consuming, and tedious, especially in the case of large area farms. Hyperspectral imaging (HSI) is a promising technique for automated sensing and monitoring. Though several automated systems based on HSI have been developed recently for crop monitoring, these tend to be computationally complex and demand significant processing power and time, especially when handling extensive data from large farms. In this context, we explore an approach using spectral ratios for crop growth monitoring and the detection of early-stage nutrient stress. The early detection of the nutrient stress can enable effective crop, resource, and time management in large hydroponic farms. A sensitive nutrient deficiency index, named normalized nutrient deficiency index (NNDI), has been formulated for the early-stage detection of nutrient deficiencies. Evaluating these indices is computationally simple and quick. A methodology for crop growth monitoring and nutrient deficiency stress using these indices is demonstrated on Lactuca sativa L. crops. It is envisaged that the proposed quick, nondestructive imaging technique can enable future automation possibilities and serve as an invaluable tool in indoor hydroponic farms.

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Monitoring system for corrosion in metal structures using a probe based hyperspectral imager

Cited by 5 publications

References 16 publications

Identification of Corrosion Minerals Using Shortwave Infrared Hyperspectral Imaging

Identification of Corrosion Minerals Using Shortwave Infrared Hyperspectral Imaging

Hyperspectral imaging systems for corrosion detection from remotely operated vehicles

A fast analysis approach for crop health monitoring in hydroponic farms using hyperspectral imaging

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