Photovoltaic thermal images Dataset

For its collection, a thermographic inspection of a ground-based PV system was carried out on a PV plant with a power of approximately 66 MW in Tombourke, South Africa. The thermographic acquisitions were made in 7 working days, from 21 to 27 January 2019 with sky predominantly clear and with maximum irradiation. This situation is optimal to enhance any abnormal behaviour of the entire panels or portion of them. The images are captured during the inspection of the PV plants. The operator has selected the images with the presence of one or more anomaly cells. Then, the associated binary mask is generated. This mask contains white pixels indicated the anomaly cell. The detection of the anomalous cell is made only through the use of thermal data: the operator immediately identifies where the anomaly is placed because the cell has a temperature value totally different from all the surrounding cells. This difference has been evaluated by a software called ThermoViewer

To obtain this dataset, as well as the implementation code, we ask you to complete, sign and return the form below. After that, I will send you the credentials to download it. Note that the dataset is available only for research purposes.

  • Fill out this form: request form
  • Send it to: (Note: you should send the email from an email address that is linked to your research institution/university)
  • Wait for the credentials
  • You will be sent a link for the download.

Please cite our works using the following bib:

title={Automatic Faults Detection of Photovoltaic Farms: solAIr, a Deep Learning-Based System for Thermal Images},
author={Pierdicca, Roberto and Paolanti, Marina and Felicetti, Andrea and Piccinini, Fabio and Zingaretti, Primo},
publisher={Multidisciplinary Digital Publishing Institute}

author={Pierdicca, R. and Malinverni, E.S. and Piccinini, F. and Paolanti, M. and Felicetti, A. and Zingaretti, P.},
title={Deep convolutional neural network for automatic detection of damaged photovoltaic cells},
journal={International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives},