Automatic detection of fastener safety wire twisting direction based on machine vision

Safety wire status detection is of great significance to aircraft operation safety. To address the problems of low efficiency and leakage in the current manual-led safety wire twisting direction inspection, we propose a machine vision-based safety wire twisting direction detection method for aviation fasteners. Firstly, the Yolov4-MSC objective detection algorithm is proposed for fastener and safety wire region localization. After segmentation of the region localization, we pinpoint the precise location of the fastener by the gradient Hough transform method, the safety wire braiding is detected using the Maximally Stable Extremal Regions (MSER) with Non-Maximum Suppression (NMS), and the safety wire centerline location is fitted using the Random Sample Consensus (RANSAC) algorithm. Lastly, the safety wire twisting direction detection is obtained by the position relationship between the safety wire centerline and the fastener. The experimental results show that the proposed safety wire twisting direction method is effective, has high accuracy and robustness, and can achieve fastener and safety wire location and safety wire twisting direction detection in complex aircraft maintenance scenarios.