Abstract
The detection of defect in additive manufactured (AM) metal materials is of great importance for industrial applications, and remains a challenge due to the heterogeneity and anisotropic of AM materials. This study presents an internal defects detection method for WAAM aluminum alloy using phased-array ultrasound. The detailed ultrasonic testing guidance considering the properties of WAAM metal material for inspecting and locating the internal defects is provided. Phased array ultrasound multi-angle-scanning pattern is applied for detecting the AM parts more reliably. The multi-angle data fusion algorithm is applied to manage the raw data obtained by different angle beams for generating ultrasound data sets encoded with physical information. The velocity of ultrasound beams with different angles propagated in the WAAM material is investigated and the relationship between the velocity and the angle of incidence can be established using the quadratic regression analysis. A modified data fusion algorithm considering the actual velocity variations is proposed. Comparisons are made between the actual depth of the artificial defect in WAAM deposited 2319 aluminum alloy block and depth measured by data fusion algorithm without/with velocity anisotropy correction. Results show the modified algorithm improves the accuracy of defect localization.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
