Automated detection-classification of defects on photo-voltaic modules assisted by thermal drone inspection

A new computational procedure is proposed for the automated detection-classification of defects on photovoltaic (PV) modules-panels. Thermal imaging or IR thermography is an important and powerful non-destructive technique for the investigation of structural or operational defects on PV modules and...

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Autores principales:	Gurras Arsenios, Gergidis Leonidas, Mytafides Christos, Tzounis Lazaros, Paipetis Alkiviadis S.
Formato:	article
Lenguaje:	EN FR
Publicado:	EDP Sciences 2021
Materias:	Engineering (General). Civil engineering (General) TA1-2040
Acceso en línea:	https://doaj.org/article/67514d1741914628af0e639eb9700876
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spelling	oai:doaj.org-article:67514d1741914628af0e639eb97008762021-12-02T17:13:46ZAutomated detection-classification of defects on photo-voltaic modules assisted by thermal drone inspection2261-236X10.1051/matecconf/202134903015https://doaj.org/article/67514d1741914628af0e639eb97008762021-01-01T00:00:00Zhttps://www.matec-conferences.org/articles/matecconf/pdf/2021/18/matecconf_iceaf2021_03015.pdfhttps://doaj.org/toc/2261-236XA new computational procedure is proposed for the automated detection-classification of defects on photovoltaic (PV) modules-panels. Thermal imaging or IR thermography is an important and powerful non-destructive technique for the investigation of structural or operational defects on PV modules and when it is combined with drones can provide a fully automated inspection, detection and defect classification procedure. The aforementioned image processing approach adopts pre- and post-processing tools and methodologies assisting the infrared (IR) thermography for the evaluation of a photovoltaic (PV) module performance. In particular, the passive approach of IR thermography was adopted, a portable thermal imager was used for the in-situ acquisition of images that show the distribution of infrared luminance of the PV panel surface. The acquired images are processed and analyzed for the detection and classification of defects and hot spots on the module’s surface that are potential candidates for faulty operation. The proposed computational methodology adopts gaussian filters for the IR images, thresholding operations, morphological transformations and Artificial Neural Networks. The use of IR thermography assisted by Unmanned Aerial Vehicles (UAVs) for the inspection of PV modules-panels proved to be a very reliable and efficient tool towards the automated detection-classification of defects.Gurras ArseniosGergidis LeonidasMytafides ChristosTzounis LazarosPaipetis Alkiviadis S.EDP SciencesarticleEngineering (General). Civil engineering (General)TA1-2040ENFRMATEC Web of Conferences, Vol 349, p 03015 (2021)
institution	DOAJ
collection	DOAJ
language	EN FR
topic	Engineering (General). Civil engineering (General) TA1-2040
spellingShingle	Engineering (General). Civil engineering (General) TA1-2040 Gurras Arsenios Gergidis Leonidas Mytafides Christos Tzounis Lazaros Paipetis Alkiviadis S. Automated detection-classification of defects on photo-voltaic modules assisted by thermal drone inspection
description	A new computational procedure is proposed for the automated detection-classification of defects on photovoltaic (PV) modules-panels. Thermal imaging or IR thermography is an important and powerful non-destructive technique for the investigation of structural or operational defects on PV modules and when it is combined with drones can provide a fully automated inspection, detection and defect classification procedure. The aforementioned image processing approach adopts pre- and post-processing tools and methodologies assisting the infrared (IR) thermography for the evaluation of a photovoltaic (PV) module performance. In particular, the passive approach of IR thermography was adopted, a portable thermal imager was used for the in-situ acquisition of images that show the distribution of infrared luminance of the PV panel surface. The acquired images are processed and analyzed for the detection and classification of defects and hot spots on the module’s surface that are potential candidates for faulty operation. The proposed computational methodology adopts gaussian filters for the IR images, thresholding operations, morphological transformations and Artificial Neural Networks. The use of IR thermography assisted by Unmanned Aerial Vehicles (UAVs) for the inspection of PV modules-panels proved to be a very reliable and efficient tool towards the automated detection-classification of defects.
format	article
author	Gurras Arsenios Gergidis Leonidas Mytafides Christos Tzounis Lazaros Paipetis Alkiviadis S.
author_facet	Gurras Arsenios Gergidis Leonidas Mytafides Christos Tzounis Lazaros Paipetis Alkiviadis S.
author_sort	Gurras Arsenios
title	Automated detection-classification of defects on photo-voltaic modules assisted by thermal drone inspection
title_short	Automated detection-classification of defects on photo-voltaic modules assisted by thermal drone inspection
title_full	Automated detection-classification of defects on photo-voltaic modules assisted by thermal drone inspection
title_fullStr	Automated detection-classification of defects on photo-voltaic modules assisted by thermal drone inspection
title_full_unstemmed	Automated detection-classification of defects on photo-voltaic modules assisted by thermal drone inspection
title_sort	automated detection-classification of defects on photo-voltaic modules assisted by thermal drone inspection
publisher	EDP Sciences
publishDate	2021
url	https://doaj.org/article/67514d1741914628af0e639eb9700876
work_keys_str_mv	AT gurrasarsenios automateddetectionclassificationofdefectsonphotovoltaicmodulesassistedbythermaldroneinspection AT gergidisleonidas automateddetectionclassificationofdefectsonphotovoltaicmodulesassistedbythermaldroneinspection AT mytafideschristos automateddetectionclassificationofdefectsonphotovoltaicmodulesassistedbythermaldroneinspection AT tzounislazaros automateddetectionclassificationofdefectsonphotovoltaicmodulesassistedbythermaldroneinspection AT paipetisalkiviadiss automateddetectionclassificationofdefectsonphotovoltaicmodulesassistedbythermaldroneinspection
_version_	1718381322313924608

Automated detection-classification of defects on photo-voltaic modules assisted by thermal drone inspection

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