제목

방사선 투과 이미지에서의 용접 결함 검출을 위한 딥러닝 알고리즘 비교 연구

저자

오상진, 윤광호, 임채옥, 신성철

초록

An automated system is needed for the effectiveness of non-destructive testing. In order to utilize the radiographic testing data accumulated in the film, the types of welding defects were classified into 9 and the shape of defects were analyzed. Data was preprocessed to use deep learning with high performance in image classification, and a combination of one-stage/two-stage method and convolutional neural networks/Transformer backbone was compared to confirm a model suitable for welding defect detection. The combination of two-stage, which can learn step-by-step, and deep-layered CNN backbone, showed the best performance with mean average precision 0.868.

한국산업융합학회 논문집. 2022. 25(4)