Design of Lock Defect Detection System Based on Intelligent Algorithm AI Technology

Lock buckle is an important limiting device in aviation cargo holds, used to restrict the movement of container units during air transportation. Whether the lock buckle is working properly is an important part of ensuring the safe operation of the flight. At present, it is mainly based on manual inspection, which not only has low efficiency but is also susceptible to subjective factors, resulting in delayed identification of lock deformation, hidden cracks, and other situations, which can easily cause safety hazards. An aviation lock detection system based on artificial intelligence technology is proposed to address the above situation. Firstly, a comprehensive inspection vehicle was used to collect the lock images, and then the classic YOLOv5-M model was used to capture the lock images. Defect detection was performed through feature extraction and machine learning algorithms, achieving good detection results.