Hotspots Infrared detection of photovoltaic modules based on Hough line transformation and Faster-RCNN approach

In the last two decades, the installation and production of photovoltaic (PV) plants increased widely. As the PV system operation time grew, more and more defect occurred on the PV modules. One of the most significant open issues in the PV sector is to find appropriate inspection methods to detect PV modules' failures. In this paper, two approaches are proposed to detect the hotspots in the infrared image of PV modules. The classical digital image processing technology mainly uses Hough line transformation and canny operator to detect hotspots. The deep learning model is based on Faster-RCNN and transfer learning, which perform better with more compute resources.