Multi-Branch Deep Fusion Network-Based Automatic Detection of Weld Defects Using Non-Destructive Ultrasonic Test
This study introduces a deep learning engine designed for the non-destructive automatic detection of defects within weld beads.A 1D waveform ultrasound signal was collected using an A-scan pulser receiver to gather defect signals from inside the weld bead.We established 5,108 training datasets and 500 test datasets for five pass/fail labels in this