Graphic Augmented Defect Recognition for Phased Array Ultrasonic Testing on Tubular TKY Joints
Source abstract
Abstract
A graphic augmented defect recognition algorithm was developed for phased array ultrasonic testing (PAUT) on tubular TKY joints. Based on PAUT sector scan (S-scan), 2D maps of the scans are obtained in terms of signal intensity and locations using spatial clustering and segmentation. The transformed S-scan data was further mapped with weld geometrical model to discriminate defect indications from the signals due to weld boundaries. Geometrical features of the identified defect indications were extracted to estimate the size and depth of the defects. The algorithm was verified by experiments on a TKY artefact with purposely-made defects. It shows that our algorithm was able to identify and locate all the defects in the artefact. Compared with the results obtained manually using the standard ultrasonic testing method, the differences of our results in terms of the defect size and depth were within 2 mm. The algorithm, coded into a software tool, demonstrated that the defects in the tubular TKY welds can be detected automatically and visualized in an intuitive manner.
Source: openaire · Quality: candidate unverified · Source record ↗
Research context
OpenAlex topics: Ultrasonics and Acoustic Wave Propagation · Non-Destructive Testing Techniques · Welding Techniques and Residual Stresses
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
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