Neural network aided estimation of near-surface material properties using planar type micromagnetic sensors

The impedance of a coil in proximity of any metal surface is a complex function of many parameters including near-surface properties (such as conductivity, permeability, liftoff etc.) of the material. The transfer impedance (i.e., the ratio between the sensing voltage and the exciting current) of the planar type micromagnetic sensors consisting of exciting and sensing coil is used for the estimation of the near-surface material properties. Two methods have been discussed for the post-processing of output parameters from the measured impedance data. Based on the estimation of near-surface properties it is possible to detect the existence of defects and to predict the degradation of material, fatigue etc.