To ensure that laser chips meet stringent reliability standards in practical applications, comprehensive limit testing and reliability verification must be performed before deployment. This paper proposes an electroluminescence (EL) imaging-based detection method for Catastrophic Optical Mirror Damage (COMD) and Catastrophic Optical Bulk Damage (COBD). A novel model, PCMBA-YOLO, is developed on the YOLOv12 framework, integrating a Multi-Branch Aided Feature Pyramid Network (MBAFPN) and a Pinwheel Convolution (PConv) structure to enhance weak-signal feature extraction and expand the receptive field with minimal parameters. Furthermore, a Shape-IoU-based regression loss is introduced to model bounding-box shape and scale, improving localization precision and convergence. Experimental results show that PCMBA-YOLO achieves 99.4% mAP@0.5, 97.6% Precision, and 98.7% Recall, with a 14% reduction in parameters compared to the baseline. The proposed method demonstrates superior accuracy, efficiency, and robust generalization, providing a high-performance solution for automated visual inspection in semiconductor manufacturing.
Wáng et al. (Wed,) studied this question.