101 citations · 104 across the 4 of their papers we have counts for
5 papers
Georeferencing of Photovoltaic Modules from Aerial Infrared Videos using Structure-from-Motion
Lukas Bommes, Claudia Buerhop-Lutz, Tobias Pickel +3
To identify abnormal photovoltaic (PV) modules in large-scale PV plants economically, drone-mounted infrared (IR) cameras and automated video processing algorithms are frequently u…
Anomaly Detection in IR Images of PV Modules using Supervised Contrastive Learning
Lukas Bommes, Mathis Hoffmann, Claudia Buerhop-Lutz +5
Increasing deployment of photovoltaic (PV) plants requires methods for automatic detection of faulty PV modules in modalities, such as infrared (IR) images. Recently, deep learning…
Computer Vision Tool for Detection, Mapping and Fault Classification of PV Modules in Aerial IR Videos
Lukas Bommes, Tobias Pickel, Claudia Buerhop-Lutz +3
Increasing deployment of photovoltaics (PV) plants demands for cheap and fast inspection. A viable tool for this task is thermographic imaging by unmanned aerial vehicles (UAV). In…
PV Modules and Their Backsheets -- A Case Study of a Multi-MW PV Power Station
Claudia Buerhop-Lutz, Oleksandr Stoyuk, Tobias Pickel +3
Degradation of backsheets (BS) and encapsulant polymer components of silicon PV modules is recognized as one of the main reasons for losses in PV plant performance and lifetime exp…
Deep Learning-based Pipeline for Module Power Prediction from EL Measurements
Mathis Hoffmann, Claudia Buerhop-Lutz, Luca Reeb +8
Automated inspection plays an important role in monitoring large-scale photovoltaic power plants. Commonly, electroluminescense measurements are used to identify various types of d…