Condition Monitoring System for Main Shaft Bolts in Wind Turbines Based on YOLOv11 - CHEN Huai; CHEN Yanan; LI Ziyuan; ZHANG Jiayou; QIN Long; SHU Hui (Kongzhi Yu Xinxi Jishu)
Abnormal condition monitoring of main shaft bolts plays a crucial role in ensuring the stable and efficient operation of wind turbines. The traditional inspection method of manual patrols has proven inefficient and lacking in real-time performance, which hinders its ability to meet the requirements of efficient operation and maintenance for modern wind turbines. Although sensor-based monitoring methods support automated detection, they are restricted from large-scale applications due to their simple functionality and high operational and maintenance costs. This paper proposes a YOLOv11-based system to facilitate intelligent condition monitoring for main shaft bolts. First, the YOLOv11 algorithm is implemented to detect a variety of abnormal conditions of main shaft bolts, including nut detachment, bolt loosening, and bolt falling-off. Next, the information regarding the recognized abnormal conditions is integrated and displayed on the SCADA system interface of the wind turbines, which reminds operators to take corresponding maintenance measures in time, thereby ensuring safe operation. The experimental demonstrated the proposed method achieved a detection accuracy of up to 96.2% and a detection frame rate of 400 FPS, aligning with the requirements of efficient operation and maintenance for wind turbines.