Enhancement of Electroluminescence images for fault detection in photovoltaic panels

Harsh R. Parikh; Sergiu Spataru; Dezso Sera; Claire Mantel; Søren Forchhammer; Gisele A. dos Reis Benatto; Nicholas Riedel; Peter Behrensdorff Poulsen

doi:10.1109/PVSC.2018.8547442

Enhancement of Electroluminescence images for fault detection in photovoltaic panels

Harsh R. Parikh, Sergiu Spataru, Dezso Sera, Claire Mantel, Søren Forchhammer, Gisele A. dos Reis Benatto, Nicholas Riedel, Peter Behrensdorff Poulsen

Aalborg University

Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-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 language	English
Title of host publication	Proceedings of 2018 IEEE 7th World Conference on Photovoltaic Energy Conversion
Publisher	IEEE
Publication date	2018
Pages	0447-0452
ISBN (Print)	9781538685297
DOIs	https://doi.org/10.1109/PVSC.2018.8547442
Publication status	Published - 2018
Event	7th World Conference on Photovoltaic Energy Conversion - Hilton Waikoloa Village Resort, Waikoloa, United States Duration: 10 Jun 2018 → 15 Jun 2018 Conference number: WCPEC-7

Conference

Conference	7th World Conference on Photovoltaic Energy Conversion
Number	WCPEC-7
Location	Hilton Waikoloa Village Resort
Country/Territory	United States
City	Waikoloa
Period	10/06/2018 → 15/06/2018

Keywords

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

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1109/PVSC.2018.8547442

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Full text

DronEL
Poulsen, P. B. (Project Manager), Thorsteinsson, S. (Project Participant), Forchhammer, S. (Project Participant), Benatto, G. A. D. R. (Project Participant), Riedel-Lyngskær, N. C. (Project Participant), Thorseth, A. (Project Participant), Dam-Hansen, C. (Project Participant) & Mantel, C. (Project Participant)
01/01/2017 → 31/12/2019
Project: Research

Cite this

@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",

note = "7th World Conference on Photovoltaic Energy Conversion ; Conference date: 10-06-2018 Through 15-06-2018",

}

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, Hawaii, United States, 10/06/2018. https://doi.org/10.1109/PVSC.2018.8547442

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

N1 - Conference code: WCPEC-7

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

SN - 9781538685297

SP - 447

EP - 452

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

PB - IEEE

T2 - 7th World Conference on Photovoltaic Energy Conversion

Y2 - 10 June 2018 through 15 June 2018

ER -

Enhancement of Electroluminescence images for fault detection in photovoltaic panels

Abstract

Conference

Keywords

UN SDGs

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OpenUrl availability

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Projects

DronEL

Cite this