Abstract: The accurate detection and classification of invisible weld defects is very important to ensure the quality of welding products. A magneto-optical (MO) imaging detection system excited by a ...

The goal of this project is to classify weld defects using a deep learning model. We use the DenseNet121 architecture, which is a convolutional neural network known for its efficiency and accuracy in ...

Improved product quality and production methods, and decreased production costs are important objectives of industries. Welding processes are part of this goal. There are many studies about monitoring ...

Abstract: Developing an online pipeline magnetic flux leakage (MFL) weld defect detection method deployed in industrial sites is essential to expedite the localization and repair of defects. However, ...