Corrosion Risk Prediction of Carbon Steels by Hyperspectral Analysis

Abstract

The utility of hyperspectral measurement was assessed as a means of predicting the corrosion risk of steel materials based on surface information. Carbon steels exposed to outdoor conditions in Choshi and Miyakojima were used as the test specimens. Exposure tests were conducted every six months for a duration of two and a half years. Corrosion loss was calculated by comparing the weight of specimens before exposure test and after removing corrosion products from the surface. Hyperspectral measurements were conducted on these specimens, with corrosion products identified through SAM (Spectral Angle Mapper) analysis. α-FeOOH, β-FeOOH, γ-FeOOH, and Fe₃O₄ were employed as reference data for SAM analysis. In both Choshi and Miyakojima test sites, γ-FeOOH was predominantly detected on the specimens after ordinary exposure tests, whereas Fe₃O₄ was prevalent on the specimens exposed to sheltered environments. The correlation between the proportion of each corrosion product identified through SAM analysis and the amount of corrosion change for one year was explored. α-FeOOH exhibited a positive correlation with the amount of corrosion change, whereas the amount of corrosion change tended to decrease with an increase in β-FeOOH fraction.s