Application of Dempster-Shafer theory for fusion of lap joints inspection data

In this work the Dempster-Shafer (DS) theory has been used for fusing nondestructive inspection (NDI) data. The success of a DS-based method depends on how the basic probability assignment (BPA) or probability mass function is defined. In the case of nondestructive inspection of aircraft lap joints, which is of interest here, the inspection data is presented in raster-scanned images. These images are discriminated by iteratively trained classifiers. The BPA is defined based on the conditional probability of information classes and data classes, which are obtained from ground truth data and NDI measurements respectively. Then, the Dempster rule of combination is applied to fuse multiple NDI inputs. The maximum mass outputs determine the final classification results. In this work, conventional eddy current (ET) and pulsed eddy current (P-ET) techniques were employed to inspect the fuselage lap joints of a service-retired Boeing 727 aircraft in order to map corrosion sites. Estimation of the remaining thickness from the inspection data is the aim of this work. The ground truth data was obtained by teardown inspections followed by a digital X-ray thickness mapping technique, which provides accurate thickness values. The experimental results verify the efficiency of the proposed method.