Automatic Weld Bead Recognition and Defect Detection in Pipeline Radiographs

Abstract

The current work contributes to the research in the area of pipelines non-destructive testing by presenting new methodologies for the automatic analysis of welds radiographs. Object recognition techniques based on genetic algorithms were used for the automatic weld bead detection. In addiction, we developed an image digital filter for the detection of defects in the weld bead zone. These methodologies were tested for 120 digital radiographs from carbon steel pipeline welded joints. These images were acquired by a storage phosphor system using double-wall radiographic exposing technique with single-wall radiographic viewing, according to the ASME V code. As a result, even defects that are hard to be detected by human vision are automatically highlighted and extracted from the whole image to be classified in the further stages of the weld inspection process.