Characterization of Defects in Aluminum Plates Using GMR Probes and Neural Network Signal Processing

Abstrac t – Conductive specimens such as aluminum plates are tested in order to extract information about possible cracks, flaws and other mechanical damages. Nowadays, eddy current testing (ECT) despite its major benefits (e.g. low cost, high checking speed, robustness and high sensitivity to large classes of defects) implies the utilization of fully coil based architecture probes or hybrid coilmagnetoresistive probes. This work presents an eddy-current testing system based on a giant magnetoresistive sensing device. The application detects and estimates the size of cracks in an aluminum plate specimen. A neural network processing architecture is used to find out the correspondence between the cracks and the signal characteristics measured on the eddy current probe. The crack detection and the estimation of its size using different eddy-current frequencies are described in the paper.