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Abstract
We propose a corrosion pit modelling approach of high-strength steel wires considering orientation features using surface point cloud data, collected by three-dimensional laser scanning. Corrosion pits were identified through density-based spatial clustering of applications with noise (DBSCAN). The identified corrosion pits could be modelled as a semiellipsoid considering orientation features. The Gaussian copula model was utilised to describe the joint distribution of the geometric parameters of the corrosion pits. This approach will be valuable for simulation of the surface morphology of corroded high-strength steel wires.
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