Inductive Thermography and Data Fusion for Enhanced Detection of Tunneling Defects in Friction Stir Welding

Inductive thermography is a non-destructive testing (NDT) method used for checking friction stir welding (FSW) joints, which can have defects like tunneling. In this research, inductive thermography was used to find tunneling defects in three FSW samples that had already been looked at with radiography and ultrasonic testing. Using thermal signal reconstruction (TSR) techniques in MATLAB made the thermography images clearer, helping to identify defects that were hard to see otherwise. To make defect detection more accurate, an image fusion method was used. This combined thermography and radiographic images and then checked them against ultrasonic images to confirm the findings. The fusion process in MATLAB helped combine different types of data to give a fuller view of the defects, thus improving the identification of defects like tunneling in FSW joints. The study shows that inductive thermography when paired with image fusion, provides quicker, safer, and cheaper defect detection compared to classical methods like radiography. Merging multiple NDT methods through data fusion improves accuracy in finding defects, leading to better reliability and safety in welded structures.