An SVM approach with electromagnetic methods to assess metal plate thickness

• We use transient eddy currents (TEC) to assess metallic plate thickness.
• Giant Magneto Resistors (GMR) are used as magnetic sensors.
• Metal plate thickness is determined from measurements.
• Support vector machines (SVM) are used to multi-class classification of plate thickness.
• Support vector machines for regression (SVR) are developed to a reliable estimation of plate thickness.

Eddy current testing (ECT) is a non-destructive technique that can be used in the measurement of conductive material thickness. In this work ECT and a machine learning algorithm (support vector machine – SVM) are used to determine accurately the thickness of metallic plates. The study has been made with ECT measurements on real specimens. At a first stage, a few number of plates is considered and SVM is used for a multi-class classification of the conductive plate thicknesses within a finite number of categories. Several figures of merit were tested to investigate the features that lead to “good” separating hyperplanes. Then, based on a SVM regressor, a reliable estimation of the thickness of a large quantity of plates is tested.Eddy currents are induced by imposing a voltage step in an excitation coil (transient eddy currents – TEC), while a giant magnetoresistance (GMR) is the magnetic sensor that measures the transient magnetic field intensity in the sample vicinity. An experimental validation procedure, including machine training with linear and exponential kernels and classification errors, is presented with sets of samples with thicknesses up to 7.5 mm.