Comparative Evaluation for Tracking the Capability of Solar Cell Malfunction Caused by Soil Debris between UAV Video versus Photo-Mosaic

Abstract

Monitoring the malfunction of the solar cells (for instance, 156 mm by 156 mm) caused by the soil debris requires a very low flight altitude when taking aerial photos, utilizing the autopilot function of unmanned aerial vehicle (UAV). The autopilot flight can only operate at a certain level of altitude that can guarantee collision avoidance for flight obstacles (for instance, power lines, trees, buildings) adjacent to the place where the solar panel is installed. For this reason, aerial photos taken by autopilot flight capture unnecessary objects (surrounding buildings and roads) around the solar panel at a tremendous level. Therefore, the autopilot-based thermal imaging causes severe data redundancy with very few matched key-points around the malfunctioned solar cells. This study aims to explore the tracking capability on soil debris defects in solar cell scale between UAV video versus photo-mosaic. This study experimentally validated that the video-based thermal imaging can track the thermal deficiency caused by the malfunction of the solar cell at the level of the photo-mosaic in terms of correlation of thermal signatures (0.98–0.99), detection on spatial patterns (81–100%), and distributional property (90–95%) with 2.5–3.4 times more matched key-points on solar cells. The results of this study could serve as a valuable reference for employing video stream in the process of investigating soil debris defects in solar cell scale.