Abstract

The Type 4 hydrogen storage tank has an internal liner made of polymer material. Instead of the joining of two cylinder-shaped liners through butt-joint thermal fusion bonding, a faster joining can be achieved through lap-joint laser welding. Non-destructive testing is required to inspect the quality of laser-welded areas and to detect pore defects. In this study, the interface of a laser-welded region is investigated using optical coherence tomography to detect internal pore defects, where the maximum thickness of the liner is found to be approximately 3 mm. Optical coherence tomography images with defects are then used for supervised YOLOv2 deep learning. Real-time detection of internal defects is successfully performed on laser-welded liner samples.

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