Key points are not available for this paper at this time.
An application of machine vision applied to the analysis of radioscopic images of incomplete weld geometries is described. The rationale of the work is to identify weld defects as soon as they are produced, thereby reducing the costs of any subsequent repairs. Existing methods of weld and defect identification are compared, leading to the development of filtering and 'window' based variance operator for segmentation of suspect defect areas inside the weld region is described. The software and radioscopic imaging system have been benchmarked through a series of demonstration trials on both 80 mm thick carbon steel submerged arc welded testpieces, and 25mm thick carbon steel tungsten inert gas welded testpieces. The range of intentionally implanted defects, from root cracks to lack of side wall fusion, were detected with an overall accuracy of 87 percent, and classified in terms of defect size, shape, and position within the weld region.
Bonser et al. (Sun,) studied this question.