Lift-off nulling and internal state inspection of multi-layer conductive structures by combined signal features in pulsed eddy current testing

Pulsed eddy current (PEC) testing, as an emerging technique of eddy current testing, has been used for detection and analysis of internal states of multi-layer conductive structures. However, the lift-off noise, caused by irregular sample surface, varying coating thicknesses or movement of probes, may seriously influence the accuracy. Therefore, in order to improve the detection accuracy under lift-off noise, an algorithm is proposed. Firstly, the response signals with lift-off noise are analysed theoretically and experimentally; secondly, according to analysis of the multi-collinearity between the lift-off and the response signal, a model to predict the lift-off is constructed by Partial Least Square (PLS); then, based on the prediction value of the lift-off by the PLS model, an approach to detect the internal states of multi-layer conductive structures is proposed. In this approach, the internal states are determined by the classification model, which is constructed by Support Vector Machine (SVM) based on combined features. The combined signal features are composed of the lift-off feature and principal component features. Finally, a bimetallic thermostat is taken as our experimental subject to validate the proposed method. The experimental results indicate that the proposed method can reduce the effect of lift-off fluctuations and improve detection accuracy.