Modelling the impact of UAV navigation errors on infrared PV inspection data quality and efficiency
| Autor: | Anders Rodningsby, Tor Atle Solend, Hans Jonas Fossum Moen |
|---|---|
| Rok vydání: | 2021 |
| Předmět: |
Data acquisition
GNSS applications Computer science Real Time Kinematic Data quality Photovoltaic system Real-time computing ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Navigation system ComputerSystemsOrganization_SPECIAL-PURPOSEANDAPPLICATION-BASEDSYSTEMS ComputerApplications_COMPUTERSINOTHERSYSTEMS Satellite Inertial navigation system |
| Zdroj: | 2021 IEEE 48th Photovoltaic Specialists Conference (PVSC). |
| DOI: | 10.1109/pvsc43889.2021.9518810 |
| Popis: | Unmanned aerial vehicles (UAVs) are well suited for infrared (IR) thermography of solar photovoltaics (PV). For an autonomous UAV system, precise and accurate navigation is vital for data quality and acquisition efficiency. The navigation system of a UAV is typically based on a flight controller (FC) using global navigation satellite systems (GNSS), barometric altimeter and inertial navigation. In this paper, position estimates from an integrated FC are compared with a standalone high-performance real time kinematic (RTK) navigation system and modelled for IR fault classification scenarios. The results show that position estimation errors have a strong impact on IR image resolution and data acquisition efficiency. These results are important to consider when assessing cost effective autonomous IR inspection of large PV plants. |
| Databáze: | OpenAIRE |
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