Enhancement of Electroluminescence images for fault detection in photovoltaic panels

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

Abstract

Good quality images are necessary for electroluminescence (EL) image analysis and failure quantification in solar panels. In this work, a method for determining image quality in terms of more accurate failure detection in PV panels through EL imaging is proposed. The goal of the paper is to highlight the different methods for image quality improvement and to determine if the enhanced image provides more useful diagnostic information for accurate micro cracks and fracture detection. From the work carried out in this paper, it is to be noted that averaging technique helps in improving the SNR value. Additionally, subtracting the background from the obtained averaged EL image proves to be an enhancing method for cell fracture identification and more number of edges are also detected which can be useful for micro crack quantification.
Original languageEnglish
Title of host publicationProceedings of 2018 IEEE 7th World Conference on Photovoltaic Energy Conversion
PublisherIEEE
Publication date2018
Pages0447-0452
ISBN (Print)9781538685297
DOIs
Publication statusPublished - 2018
Event7th World Conference on Photovoltaic Energy Conversion - Hilton Waikoloa Village Resort, Waikoloa, United States
Duration: 10 Jun 201815 Jun 2018
Conference number: WCPEC-7

Conference

Conference7th World Conference on Photovoltaic Energy Conversion
NumberWCPEC-7
LocationHilton Waikoloa Village Resort
CountryUnited States
CityWaikoloa
Period10/06/201815/06/2018

Keywords

  • Signal to noise ratio
  • Image quality
  • Image enhancement
  • Benchmark testing
  • Image edge detection
  • Cameras
  • Sensitivity

Cite this

Parikh, H. R., Spataru, S., Sera, D., Mantel, C., Forchhammer, S., dos Reis Benatto, G. A., ... Poulsen, P. B. (2018). Enhancement of Electroluminescence images for fault detection in photovoltaic panels. In Proceedings of 2018 IEEE 7th World Conference on Photovoltaic Energy Conversion (pp. 0447-0452). IEEE. https://doi.org/10.1109/PVSC.2018.8547442
Parikh, Harsh R. ; Spataru, Sergiu ; Sera, Dezso ; Mantel, Claire ; Forchhammer, Søren ; dos Reis Benatto, Gisele A. ; Riedel, Nicholas ; Poulsen, Peter Behrensdorff. / Enhancement of Electroluminescence images for fault detection in photovoltaic panels. Proceedings of 2018 IEEE 7th World Conference on Photovoltaic Energy Conversion. IEEE, 2018. pp. 0447-0452
@inproceedings{648283147067418dbc5f3a6ab339b29b,
title = "Enhancement of Electroluminescence images for fault detection in photovoltaic panels",
abstract = "Good quality images are necessary for electroluminescence (EL) image analysis and failure quantification in solar panels. In this work, a method for determining image quality in terms of more accurate failure detection in PV panels through EL imaging is proposed. The goal of the paper is to highlight the different methods for image quality improvement and to determine if the enhanced image provides more useful diagnostic information for accurate micro cracks and fracture detection. From the work carried out in this paper, it is to be noted that averaging technique helps in improving the SNR value. Additionally, subtracting the background from the obtained averaged EL image proves to be an enhancing method for cell fracture identification and more number of edges are also detected which can be useful for micro crack quantification.",
keywords = "Signal to noise ratio, Image quality, Image enhancement, Benchmark testing, Image edge detection, Cameras, Sensitivity",
author = "Parikh, {Harsh R.} and Sergiu Spataru and Dezso Sera and Claire Mantel and S{\o}ren Forchhammer and {dos Reis Benatto}, {Gisele A.} and Nicholas Riedel and Poulsen, {Peter Behrensdorff}",
year = "2018",
doi = "10.1109/PVSC.2018.8547442",
language = "English",
isbn = "9781538685297",
pages = "0447--0452",
booktitle = "Proceedings of 2018 IEEE 7th World Conference on Photovoltaic Energy Conversion",
publisher = "IEEE",
address = "United States",

}

Parikh, HR, Spataru, S, Sera, D, Mantel, C, Forchhammer, S, dos Reis Benatto, GA, Riedel, N & Poulsen, PB 2018, Enhancement of Electroluminescence images for fault detection in photovoltaic panels. in Proceedings of 2018 IEEE 7th World Conference on Photovoltaic Energy Conversion. IEEE, pp. 0447-0452, 7th World Conference on Photovoltaic Energy Conversion , Waikoloa, United States, 10/06/2018. https://doi.org/10.1109/PVSC.2018.8547442

Enhancement of Electroluminescence images for fault detection in photovoltaic panels. / Parikh, Harsh R.; Spataru, Sergiu; Sera, Dezso; Mantel, Claire; Forchhammer, Søren; dos Reis Benatto, Gisele A.; Riedel, Nicholas; Poulsen, Peter Behrensdorff.

Proceedings of 2018 IEEE 7th World Conference on Photovoltaic Energy Conversion. IEEE, 2018. p. 0447-0452.

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

TY - GEN

T1 - Enhancement of Electroluminescence images for fault detection in photovoltaic panels

AU - Parikh, Harsh R.

AU - Spataru, Sergiu

AU - Sera, Dezso

AU - Mantel, Claire

AU - Forchhammer, Søren

AU - dos Reis Benatto, Gisele A.

AU - Riedel, Nicholas

AU - Poulsen, Peter Behrensdorff

PY - 2018

Y1 - 2018

N2 - Good quality images are necessary for electroluminescence (EL) image analysis and failure quantification in solar panels. In this work, a method for determining image quality in terms of more accurate failure detection in PV panels through EL imaging is proposed. The goal of the paper is to highlight the different methods for image quality improvement and to determine if the enhanced image provides more useful diagnostic information for accurate micro cracks and fracture detection. From the work carried out in this paper, it is to be noted that averaging technique helps in improving the SNR value. Additionally, subtracting the background from the obtained averaged EL image proves to be an enhancing method for cell fracture identification and more number of edges are also detected which can be useful for micro crack quantification.

AB - Good quality images are necessary for electroluminescence (EL) image analysis and failure quantification in solar panels. In this work, a method for determining image quality in terms of more accurate failure detection in PV panels through EL imaging is proposed. The goal of the paper is to highlight the different methods for image quality improvement and to determine if the enhanced image provides more useful diagnostic information for accurate micro cracks and fracture detection. From the work carried out in this paper, it is to be noted that averaging technique helps in improving the SNR value. Additionally, subtracting the background from the obtained averaged EL image proves to be an enhancing method for cell fracture identification and more number of edges are also detected which can be useful for micro crack quantification.

KW - Signal to noise ratio

KW - Image quality

KW - Image enhancement

KW - Benchmark testing

KW - Image edge detection

KW - Cameras

KW - Sensitivity

U2 - 10.1109/PVSC.2018.8547442

DO - 10.1109/PVSC.2018.8547442

M3 - Article in proceedings

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BT - Proceedings of 2018 IEEE 7th World Conference on Photovoltaic Energy Conversion

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Parikh HR, Spataru S, Sera D, Mantel C, Forchhammer S, dos Reis Benatto GA et al. Enhancement of Electroluminescence images for fault detection in photovoltaic panels. In Proceedings of 2018 IEEE 7th World Conference on Photovoltaic Energy Conversion. IEEE. 2018. p. 0447-0452 https://doi.org/10.1109/PVSC.2018.8547442