Line Insulator

Line insulator inspection is crucial for maintaining reliable power grids, and recent research focuses on automating this process using computer vision and machine learning. Current methods leverage deep learning, particularly object detection models, often incorporating techniques like transfer learning and anomaly detection to improve accuracy, especially when dealing with limited data or imbalanced datasets. These advancements aim to enhance the efficiency and accuracy of powerline inspections, enabling predictive maintenance and reducing the risk of power outages. Explainable AI methods are also being integrated to increase transparency and trust in automated inspection systems.