Detection of Fault in Solar Panel Using Thermal Image Processing

This paper explores the practical application of thermal cameras mounted on drones for thermal image processing in solar panel maintenance, with an emphasis on hotspot fault detection. Traditional manual inspection methods for solar panels are often time-consuming and labour-intensive, prompting the exploration of more efficient alternatives. By leveraging the capabilities of drones equipped with thermal cameras, high-resolution images and videos of solar panels can be captured swiftly and effectively. Advanced thermal image processing techniques are then employed to analyse these visuals, with a particular focus on identifying hotspot faults. The study introduces novel methodologies aimed at enhancing the accuracy and speed of anomaly detection in thermal imagery, thereby enabling proactive maintenance interventions. Real-time inspection capabilities integrated into the drone-based system provide immediate feedback to maintenance personnel, facilitating prompt decision-making and action. Through the adoption of this approach, solar panel maintenance operations are streamlined, leading to improved efficiency and cost-effectiveness. Ultimately, the implementation of drone-based thermal imaging solutions contributes to the sustainability and longevity of solar energy systems.