Eddy current testing (ECT) is a non destructive technique that can be used in the measurement of
conductive material thickness. In this work a machine learning algorithm (support vector machine - SVM) is
applied to ECT data, obtained for three different types of conductive plates, and classifies their thicknesses.
Eddy currents are induced by imposing a voltage step in an excitation coil, while a giant magnetoresistor (GMR)
magnetic sensor measures the transitory magnetic field intensity in the sample vicinity. An experimental
validation procedure, including machine training with linear and exponential kernels and classification errors,
was made for each metal type with sets of sample thicknesses up to 7.5 mm.