Data fusion method for the optimal mixing of multi-frequency eddy current signals

Eddy current testing methods are commonly used in the inspection of aircraft fuselage splice joints for corrosion and fatigue damage. However, the inspection of these components suffers from the spurious effects introduced by liftoff, interlayer gaps, rivets, and paint. To overcome these effects, multi-frequency eddy current testing has been proposed, but has not been widely employed due to the difficulty of correctly mixing the different signals. In this study, we investigated the potential of using a data fusion technique to combine the results of different frequencies and quantify hidden corrosion in service-retired aircraft lap splice joints. An updating mechanism based on a contextual Dempster-Shafer approach was used to combine probability mass values from multiple sources. The final classification results were obtained by making decisions based on the maximum belief of the fused results.