Abstract
Layered structures of nonmagnetic materials such as the aluminium alloy are broadly used in the engineering field such as aerospace, energy, etc. Whereas, the corrosive environment leaves in-service layered structures inevitably prone to the subsurface corrosion which poses a severe threat to the structural integrity. Therefore, it is indispensable to quantitatively evaluate corrosion via non-destructive evaluation techniques. Gradient-field Pulsed Eddy Current technique (GPEC) has been found to be advantageous for high-sensitivity inspection of hidden corrosion. In this paper a Planar Current Sheet (PCS) probe of GPEC is proposed with the optimised trace layout for implementation of high degree of field uniformity. Following the acquisition of the raw corrosion image with the optimised GPEC probe, an image processing algorithm integrating the Sparse Bayesian Learning (SBL) with Baseline Estimation and Denoising with Sparsity (BEADS) has been proposed for reproduction of corrosion images conceiving the information regarding the corrosion-depth profile. The investigation via simulations and experiments reveals that through the 2D scanning of the proposed PCS probe of GPEC, the raw corrosion images and reproduced images derived by using the proposed SBL-BEADS algorithm simultaneously gives the comprehensive evaluation of the subsurface corrosion hidden within the layered structures in terms of the corrosion-opening and corrosion-depth profiles, respectively.
Published Version
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