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Found 8 papers, 5 papers with code
Computer Vision Tool for Detection, Mapping and Fault Classification of PV Modules in Aerial IR Videos
In this work, we develop a computer vision tool for the semi-automatic extraction of PV modules from thermographic UAV videos.
Anomaly Detection in IR Images of PV Modules using Supervised Contrastive Learning
Instead, we frame fault detection as more realistic unsupervised domain adaptation problem where we train on labelled data of one source PV plant and make predictions on another target plant.
Georeferencing of Photovoltaic Modules from Aerial Infrared Videos using Structure-from-Motion
Comparison with an accurate orthophoto of one of the large-scale plants yields a root mean square error of the estimated module geocoordinates of 5. 87 m and a relative error within each plant row of 0. 22 m to 0. 82 m. Finally, we use the module geocoordinates and extracted IR images to visualize distributions of module temperatures and anomaly predictions of a deep learning classifier on a map.
Bridging the gap between photovoltaics R&D and manufacturing with data-driven optimization
Novel photovoltaics, such as perovskites and perovskite-inspired materials, have shown great promise due to high efficiency and potentially low manufacturing cost.
Applied Physics
Deep Learning-based Pipeline for Module Power Prediction from EL Measurements
However, knowledge of the power at maximum power point is important as well, since drops in the power of a single module can affect the performance of an entire string.
Joint Super-Resolution and Rectification for Solar Cell Inspection
Visual inspection of solar modules is an important monitoring facility in photovoltaic power plants.
Module-Power Prediction from PL Measurements using Deep Learning
While these areas can be easily identified from electroluminescense (EL) images, this is much harder for photoluminescence (PL) images.
Introducing flexible perovskites to the IoT world using photovoltaic-powered wireless tags
Our evaluation of the prototypes suggests that: i) flexible PV cells are durable up to a bending radius of 5 mm with only a 20 % drop in relative efficiency; ii) RFID communication range increased by 5x, and meets the energy needs (10-350 microwatt) to enable self-powered wireless sensors; iii) perovskite powered wireless sensors enable many battery-less sensing applications (e. g., perishable good monitoring, warehouse automation)
