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...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2023-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10286042/ |