Retrieving dimensions of surface features on conductors covered by insulation using the maximum Variation Ratio (MVR) in capacitive imaging

Abstract

In recent years, Capacitive Imaging (CI) technique has been identified as a promising technique to detect Corrosion under insulation (CUI). Previous work focused on the detection of CUI, and this work aims to find a potential way for CUI characterisation by proposing a method to retrieve dimensions of surface features on conductors covered by insulation using the Maximum Variation Ratio (MVR) obtained in CI scans at different lift-offs. Surface features on aluminium specimens covered by 2 mm plastic panels were used to simulate CUIs. In this method, the target metal surface features are divided into juxtaposed thin cuboids defined by CI line scans. Maximum Variation Ratio (MVR), which is related to both depth and width of the cross-section of the surface feature along the line scan path, can be obtained and used for retrieving the dimensions of each thin cuboids. This method relies on both Finite Element (FE) simulations and experiments. The steps of the proposed method, including establish MVR data grids in FE models, find the relation between simulated MVR and experimental MVR, obtain the calibrated MVR data grids, and retrieve the width and depth of the slot, are descried in detail. The method was validated by line scans over a circular flat-bottomed hole and surface scans over two less regular features on aluminium specimens covered by 2 mm plastic panel. The result demonstrated reasonable accuracy (error smaller than 10.00%) in retrieving the dimensions of the target surface features, indicating this proposed method is promising for CUI characterisation.