Quantitative monitoring of localized pitting corrosion in steel bars through a combined use of distributed optical fiber sensors and finite element analyses

Abstract

Pitting corrosion of steel bars can greatly impair mechanical properties of steel bars, so detecting pitting corrosion timely and accurately is crucial for assessing the health of structures. However, most current corrosion detection methods have some difficulties measuring pitting corrosion level of steel bars effectively. Considering that corrosion pits can cause strain redistribution of steel bar in the tensile state, this study proposes a method to quantitatively determine the pitting corrosion level through monitoring the steel strain distribution. Distributed optical fiber sensors (DOFS) based on Rayleigh scattering and capable of achieving the spatial resolution in millimeter scale were adopted to monitor the strain distributions of notched HRB400E steel bars subjected to tensile stress, and finite element (FE) method was employed to analyze the strain distributions of steel bars with different pit geometries. Experimental results showed that the bare fiber sensors (PI-FS) measured steel strain more accurately than jacketed fiber sensors. From strain distributions monitored by PI-FS, the pit location and pit length can be directly determined. Further, FE results revealed that the strain distribution along the fiber sensor position was significantly affected by the fiber sensor position relative to the pit mouth. Finally, the procedures to determine the pitting corrosion level from DOFS data and FE results were presented by mathematically comparing the similarity of strain curves given by the fiber sensor on a pitting-corroded bar and FE analyses of steel bars with different corrosion levels. In the end, the issues related to the practical applicability of the proposed method were discussed and limitations of this study were addressed. Although with limitations, this study provided a novel and promising way to quantitatively monitor the pitting corrosion level based on the strain distribution of steel bars.