Infrared Thermography Based Hotspot Detection Of Photovoltaic Module using YOLO

Regarding clean energy production high curiosity is gained by Solar Photovoltaic (PV) worldwide. Faults in the PV modules cause significant issues for the PV systems. Detecting faults of PV modules could help to take the necessary measures. This study uses Infrared thermography (IRT) to detect the hotspot of PV modules. The objective is to develop a hotspot detection tool using ‘YOLO: You Only Look once.’ The images are converted into a data set for a classifier to detect the hotspot of PV modules. Then the learner is trained and tested with the dataset. After that, the output validates with the IRT images of PV modules. The outcome of this study is to apply a real-time object detection tool identifying the defect of the PV module. The result shows that with a more diversified data set, the confidence of detecting the hotspot increases.