Automatic detection and analysis of photovoltaic modules in aerial infrared imagery

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(Konferenzbeitrag)


Details zur Publikation

Autorinnen und Autoren: Dotenco S, Dalsaß M, Winkler L, Wurzner T, Brabec C, Maier A, Gallwitz F
Verlag: Institute of Electrical and Electronics Engineers Inc.
Jahr der Veröffentlichung: 2016
ISBN: 9781509006410
Sprache: Englisch


Abstract


Drone-based aerial thermography has become a convenient quality assessment tool for the precise localization of defective modules and cells in large photovoltaic-power plants. However, manual evaluation of aerial infrared recordings can be extremely time-consuming. Therefore, we propose an approach for automatic detection and analysis of photovoltaic modules in aerial infrared images. Significant temperature abnormalities such as hot spots and hot areas can be identified using our processing pipeline. To identify such defects, we first detect the individual modules in infrared images, and then use statistical tests to detect the defective modules. A quantitative evaluation of the detection and analysis pipeline on real-world, infrared recordings shows the applicability of our approach.



FAU-Autorinnen und Autoren / FAU-Herausgeberinnen und Herausgeber

Brabec, Christoph Prof. Dr.
Lehrstuhl für Werkstoffwissenschaften (Materialien der Elektronik und der Energietechnologie)
Dalsaß, Manuel
Lehrstuhl für Werkstoffwissenschaften (Materialien der Elektronik und der Energietechnologie)
Maier, Andreas Prof. Dr.-Ing.
Lehrstuhl für Informatik 5 (Mustererkennung)


Einrichtungen weiterer Autorinnen und Autoren

Technische Hochschule Nürnberg "Georg Simon Ohm"


Zitierweisen

APA:
Dotenco, S., Dalsaß, M., Winkler, L., Wurzner, T., Brabec, C., Maier, A., & Gallwitz, F. (2016). Automatic detection and analysis of photovoltaic modules in aerial infrared imagery. In Proceedings of the IEEE Winter Conference on Applications of Computer Vision, WACV 2016. Institute of Electrical and Electronics Engineers Inc..

MLA:
Dotenco, Sergiu, et al. "Automatic detection and analysis of photovoltaic modules in aerial infrared imagery." Proceedings of the IEEE Winter Conference on Applications of Computer Vision, WACV 2016 Institute of Electrical and Electronics Engineers Inc., 2016.

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Zuletzt aktualisiert 2019-23-06 um 07:12