Computer vision tool for detection, mapping, and fault classification of photovoltaics modules in aerial IR videos

Author:

Bommes Lukas1ORCID,Pickel Tobias1,Buerhop‐Lutz Claudia1ORCID,Hauch Jens1,Brabec Christoph12,Peters Ian Marius1ORCID

Affiliation:

1. Forschungszentrum Jülich GmbH Helmholtz‐Institute Erlangen‐Nuremberg for Renewable Energies (HI ERN) Erlangen Germany

2. Institute Materials for Electronics and Energy Technology Universität Erlangen‐Nürnberg (FAU) Erlangen Germany

Publisher

Wiley

Subject

Electrical and Electronic Engineering,Condensed Matter Physics,Renewable Energy, Sustainability and the Environment,Electronic, Optical and Magnetic Materials

Reference44 articles.

1. Renewable energy—BP statistical review of world energy 2020;2020.

2. Reliability of IR-imaging of PV-plants under operating conditions

3. BuerhopC WeißmannR ScheuerpflugH AuerR BrabecC.Quality control of PV‐modules in the field using a remote‐controlled drone with an infrared camera. In: European Photovoltaic Solar Energy Conference and Exhibition (EUPVSEC). Frankfurt Germany;2012.

4. ScheuerpflugH Buerhop‐LutzC.Field inspection of PV‐modules using aerial drone‐mounted thermography. In: European Photovoltaic Solar Energy Conference and Exhibition (EUPVSEC). Amsterdam Netherlands;2014.

5. Light Unmanned Aerial Vehicles (UAVs) for Cooperative Inspection of PV Plants

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