Internal defects inspection of arc magnets using multi-head attention-based CNN

•A novel data augmentation strategy named the overlapping sampling augmentation (OSA) technique is designed to generate large amounts of arc magnet data.•The multi-head attention strategy is introduced into the arc magnet defect detection model for the first time to highlight features that play an important role in defect detection.•A comprehensive experimental scheme including single category samples, multi categories samples, small samples, and the coexistence of noise and insufficient data is designed to verify the generalization and robustness of the proposed method from multiple perspectives. The results show that the arc magnet internal defect classification method has good industrial applications prospects.•Construct an acoustic-based detection system regarding arc magnet internal defect.