Rail corrosion forensics using 3D imaging and finite element analysis

Rail infrastructure renewal maintenance is capital intensive. As a contributor to rail deterioration, corrosion damage needs to be accurately analysed for renewal maintenance planning. The main contribution of this study is to introduce an information-dense forensic analysis method for characterizing rail corrosion damage in situ based on 3D imaging. Two state-of-the-art technologies, an arm laser scanner and handheld laser scanner, are employed for onsite digitization of the rail surface. Acquired 3D image data is analysed to characterize pitting corrosion in terms of volume, surface area coverage and average pit depth. Cyclic loading of the sampled rail is simulated using finite element analysis of the 3D image to establish risk potential for crack initiation. A case project was used to validate the feasibility of the developed approach. The results of this study demonstrate the usefulness of applying forensic methodology to renewal maintenance planning.