Image Processing for daylight Electroluminescence PV Imaging acquired in movement

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Abstract

Regular photovoltaic (PV) system inspections have become a challenge with the significant growth in the number of modules and peak power capacity of PV installations. Image acquisition using drones, based on visual, thermographic, and more recently luminescence, can be a viable solution for large-scale PV inspections. As luminescence can provide a highly detailed and accurate PV module failure diagnosis, the development of a daylight electroluminescence (EL) imaging capability is of high importance. EL imaging performed in the field during the day requires the enhancement of the relatively weak luminescence signal over the noise from the sun. This is accomplished by image averaging and background subtraction, which requires the highly accurate registering of the of individual module images. A sequential EL image acquisition at high frame rates in continuous motion at different angles will be the realworld situation for a drone-based PV inspection in daylight, and to account for this movement while maintaining high quality images, several image processing steps must be developed. With this motivation, here we describe and perform EL image processing on a module with different faults to assure quality of the EL images in different motion speeds.
Original languageEnglish
Title of host publicationProceedings of the 35th European Photovoltaic Solar Energy Conference and Exhibition
Publication date2018
Pages2005 - 2009
Article number6DV.1.19
ISBN (Print)3-936338-50-7
DOIs
Publication statusPublished - 2018
Event35th European Photovoltaic Solar Energy Conference and Exhibition - Brussels, Belgium
Duration: 24 Sep 201828 Sep 2018

Conference

Conference35th European Photovoltaic Solar Energy Conference and Exhibition
CountryBelgium
CityBrussels
Period24/09/201828/09/2018

Keywords

  • Daylight electroluminescence
  • Field inspections
  • Image processing

Cite this

Benatto, G. A. D. R., Mantel, C., Santamaria Lancia, A. A., Graversen, M., Riedel, N., Thorsteinsson, S., ... Sera, D. (2018). Image Processing for daylight Electroluminescence PV Imaging acquired in movement. In Proceedings of the 35th European Photovoltaic Solar Energy Conference and Exhibition (pp. 2005 - 2009). [6DV.1.19] https://doi.org/10.4229/35thEUPVSEC20182018-6DV.1.19
Benatto, Gisele Alves dos Reis ; Mantel, Claire ; Santamaria Lancia, Adrian Alejo ; Graversen, Michael ; Riedel, Nicholas ; Thorsteinsson, Sune ; Poulsen, Peter Behrensdorff ; Forchhammer, Søren ; Parikh, Harsh ; Spataru, Sergiu ; Sera, Dezso. / Image Processing for daylight Electroluminescence PV Imaging acquired in movement. Proceedings of the 35th European Photovoltaic Solar Energy Conference and Exhibition. 2018. pp. 2005 - 2009
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title = "Image Processing for daylight Electroluminescence PV Imaging acquired in movement",
abstract = "Regular photovoltaic (PV) system inspections have become a challenge with the significant growth in the number of modules and peak power capacity of PV installations. Image acquisition using drones, based on visual, thermographic, and more recently luminescence, can be a viable solution for large-scale PV inspections. As luminescence can provide a highly detailed and accurate PV module failure diagnosis, the development of a daylight electroluminescence (EL) imaging capability is of high importance. EL imaging performed in the field during the day requires the enhancement of the relatively weak luminescence signal over the noise from the sun. This is accomplished by image averaging and background subtraction, which requires the highly accurate registering of the of individual module images. A sequential EL image acquisition at high frame rates in continuous motion at different angles will be the realworld situation for a drone-based PV inspection in daylight, and to account for this movement while maintaining high quality images, several image processing steps must be developed. With this motivation, here we describe and perform EL image processing on a module with different faults to assure quality of the EL images in different motion speeds.",
keywords = "Daylight electroluminescence, Field inspections, Image processing",
author = "Benatto, {Gisele Alves dos Reis} and Claire Mantel and {Santamaria Lancia}, {Adrian Alejo} and Michael Graversen and Nicholas Riedel and Sune Thorsteinsson and Poulsen, {Peter Behrensdorff} and S{\o}ren Forchhammer and Harsh Parikh and Sergiu Spataru and Dezso Sera",
year = "2018",
doi = "10.4229/35thEUPVSEC20182018-6DV.1.19",
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Benatto, GADR, Mantel, C, Santamaria Lancia, AA, Graversen, M, Riedel, N, Thorsteinsson, S, Poulsen, PB, Forchhammer, S, Parikh, H, Spataru, S & Sera, D 2018, Image Processing for daylight Electroluminescence PV Imaging acquired in movement. in Proceedings of the 35th European Photovoltaic Solar Energy Conference and Exhibition., 6DV.1.19, pp. 2005 - 2009, 35th European Photovoltaic Solar Energy Conference and Exhibition, Brussels, Belgium, 24/09/2018. https://doi.org/10.4229/35thEUPVSEC20182018-6DV.1.19

Image Processing for daylight Electroluminescence PV Imaging acquired in movement. / Benatto, Gisele Alves dos Reis; Mantel, Claire; Santamaria Lancia, Adrian Alejo; Graversen, Michael; Riedel, Nicholas; Thorsteinsson, Sune; Poulsen, Peter Behrensdorff; Forchhammer, Søren; Parikh, Harsh; Spataru, Sergiu; Sera, Dezso.

Proceedings of the 35th European Photovoltaic Solar Energy Conference and Exhibition. 2018. p. 2005 - 2009 6DV.1.19.

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

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T1 - Image Processing for daylight Electroluminescence PV Imaging acquired in movement

AU - Benatto, Gisele Alves dos Reis

AU - Mantel, Claire

AU - Santamaria Lancia, Adrian Alejo

AU - Graversen, Michael

AU - Riedel, Nicholas

AU - Thorsteinsson, Sune

AU - Poulsen, Peter Behrensdorff

AU - Forchhammer, Søren

AU - Parikh, Harsh

AU - Spataru, Sergiu

AU - Sera, Dezso

PY - 2018

Y1 - 2018

N2 - Regular photovoltaic (PV) system inspections have become a challenge with the significant growth in the number of modules and peak power capacity of PV installations. Image acquisition using drones, based on visual, thermographic, and more recently luminescence, can be a viable solution for large-scale PV inspections. As luminescence can provide a highly detailed and accurate PV module failure diagnosis, the development of a daylight electroluminescence (EL) imaging capability is of high importance. EL imaging performed in the field during the day requires the enhancement of the relatively weak luminescence signal over the noise from the sun. This is accomplished by image averaging and background subtraction, which requires the highly accurate registering of the of individual module images. A sequential EL image acquisition at high frame rates in continuous motion at different angles will be the realworld situation for a drone-based PV inspection in daylight, and to account for this movement while maintaining high quality images, several image processing steps must be developed. With this motivation, here we describe and perform EL image processing on a module with different faults to assure quality of the EL images in different motion speeds.

AB - Regular photovoltaic (PV) system inspections have become a challenge with the significant growth in the number of modules and peak power capacity of PV installations. Image acquisition using drones, based on visual, thermographic, and more recently luminescence, can be a viable solution for large-scale PV inspections. As luminescence can provide a highly detailed and accurate PV module failure diagnosis, the development of a daylight electroluminescence (EL) imaging capability is of high importance. EL imaging performed in the field during the day requires the enhancement of the relatively weak luminescence signal over the noise from the sun. This is accomplished by image averaging and background subtraction, which requires the highly accurate registering of the of individual module images. A sequential EL image acquisition at high frame rates in continuous motion at different angles will be the realworld situation for a drone-based PV inspection in daylight, and to account for this movement while maintaining high quality images, several image processing steps must be developed. With this motivation, here we describe and perform EL image processing on a module with different faults to assure quality of the EL images in different motion speeds.

KW - Daylight electroluminescence

KW - Field inspections

KW - Image processing

U2 - 10.4229/35thEUPVSEC20182018-6DV.1.19

DO - 10.4229/35thEUPVSEC20182018-6DV.1.19

M3 - Article in proceedings

SN - 3-936338-50-7

SP - 2005

EP - 2009

BT - Proceedings of the 35th European Photovoltaic Solar Energy Conference and Exhibition

ER -

Benatto GADR, Mantel C, Santamaria Lancia AA, Graversen M, Riedel N, Thorsteinsson S et al. Image Processing for daylight Electroluminescence PV Imaging acquired in movement. In Proceedings of the 35th European Photovoltaic Solar Energy Conference and Exhibition. 2018. p. 2005 - 2009. 6DV.1.19 https://doi.org/10.4229/35thEUPVSEC20182018-6DV.1.19