Data fusion of multi-view ultrasonic imaging for characterisation of large defects

The multi-view total focusing method (TFM) enables a region of interest within a specimen to be imaged using different ray paths and wave mode combinations. For defects larger than the ultrasonic wavelength, different portions of the same defect may manifest in a number of views. For a crack, the tip diffraction response may be evident in certain views and the specular reflection in others. Accurate characterisation of large defects requires the information in multiple views to be combined. In this work, three data fusion methodologies are presented: a simple sum over all views, a sum weighted according to the inverse of the noise in each view and a matched filter approach. Four large defects are examined, one stress corrosion crack (SCC), two weld cracks and a pair of slagline defects in a weld. The matched filter (matched to a small circular void) provided significant improvement over the best individual view. The data fusion process incorporates artefact removal, where non-defect artefact signals within each image view are identified and masked, using a single defect-free dataset for training. The matched filter was able to accurately visualise the full 3D extent of the four defects, allowing characterisation via the decibel drop method. When compared to x-ray CT and micrograph data in the case of the SCC, the matched filter fusion provided excellent agreement. Its performance was also superior to any individual view while providing a single fused image that is easier for an operator to interpret than a set of multi-view images.