Ma, P.; Li, J.; Zhuo, Y.; Jiao, P.; Chen, G. Coating Condition Detection and Assessment on the Steel Girder of a Bridge through Hyperspectral Imaging. Coatings2023, 13, 1008.
Ma, P.; Li, J.; Zhuo, Y.; Jiao, P.; Chen, G. Coating Condition Detection and Assessment on the Steel Girder of a Bridge through Hyperspectral Imaging. Coatings 2023, 13, 1008.
Ma, P.; Li, J.; Zhuo, Y.; Jiao, P.; Chen, G. Coating Condition Detection and Assessment on the Steel Girder of a Bridge through Hyperspectral Imaging. Coatings2023, 13, 1008.
Ma, P.; Li, J.; Zhuo, Y.; Jiao, P.; Chen, G. Coating Condition Detection and Assessment on the Steel Girder of a Bridge through Hyperspectral Imaging. Coatings 2023, 13, 1008.
Abstract
The organic coating of bridge steel girders is subjected to physical scratches, corrosion, and aging in natural weathering. The breakdown of the coating may cause serviceability and safety problems if left unnoticed. A hyperspectral imaging method is proposed to detect the condition of steel coatings based on coating-responsive features in reflectance spectra. A field test was conducted on the real-world bridge which shows obvious signs of degradation. The hyperspectral signature enables an assessment of the coating health and defect severity. The results indicated that the coating scratch can be effectively located in the domain of a hyperspectral image and the scratch depth can be determined by mapping a scratch depth indicator (SDI=R532nm / R641nm). Rust sources and products in steel girders can be identified by the unique spectral signatures and the rust stains (and thus stain areas) scattered on the coating can be pinpointed at pixel level by the corrosion rust indicators. The chemical integrity of a topcoat is demonstrated by the short-wave infrared spectroscopy and the topcoat degradation can be evaluated by the absorption at 8000 cm-1 and 5850 cm-1.
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