Deep Learning Based Detection of Missing Wind Turbine Tower Nuts

The integrity of the tower screws and nuts of wind turbines, a key component of renewable energy technologies, is critical to the stability and safe operation of the entire structure. Traditional inspection methods rely on manual visual inspection, which is not only time-consuming and labour intensive, but also susceptible to subjective factors and environmental conditions. In this study, a deep learning approach, based on a target detection algorithm model, is able to accurately locate missing nuts on wind turbine towers by training a homemade dataset training and analysing it, which improves the maintenance efficiency and safety of wind turbine equipment.