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Performance of a Module and Defect Detection Algorithm for Aerial Infrared Images as a Function of the Flying Altitude
M. Dalsass, S. Deitsch, P. Luchscheider, F. Gallwitz, C.J. Brabec
Monitoring, Aerial Thermography, PV Module Defects, Automatic Detection
Operation, Performance, Reliability and Sustainability of Photovoltaics
Subtopic: Operation of PV Systems
Event: 32nd European Photovoltaic Solar Energy Conference and Exhibition
Session: 5BV.2.60
2036 - 2040
ISBN: 3-936338-41-8
Paper DOI: 10.4229/EUPVSEC20162016-5BV.2.60
0,00 EUR
Document(s): paper, poster


In recent years, remote-controlled unmanned air vehicles (UAV) have been used increasingly to attain aerial infrared (aIR) recordings of large photovoltaic (PV) power plants with which thermally suspicious PV modules can be identified and localized. But so far, aIR recordings are still analyzed mostly manually – a process which can be extremely time-consuming and error-prone. In this context, the performance of a module and defect detection algorithm for aIR images is evaluated as a function of the flying altitude. For this purpose, aIR recordings of a PV power plant are generated from six flying altitudes from 5 m to 30 m above ground level by means of a drone measurement system and used as data input for the image processing tool. The results indicate optimal flying altitudes for both module and defect detection. However, the most suitable flying altitude may be a compromise with further conditions. The findings of this work will advance future automatic monitoring and early detection systems.