Ect-data Fusion by the Independent Component Analysis for Non-destructive Evaluation of Metallic Slabs

The aim of this paper is to present an application of ICA to non-destructive evaluation by unsupervised data-fusion, which aims at discovering the flaws affecting a metallic slab. The signals acquired through an eddy-currentprobe for nondestructive evaluation purposes are affected by strong noise and disturbances due to the mechanical system that the probe is mounted on. The availability of multiple measurements allows performing a linear data-fusion which returns independent latent signals, one of which represents the flawrelated signal recovered from the noisy mixture. A one-unit neural ICA system is employed to extract such latent signal.