Fluke
Anomaly Detection for Solar PV Inspection Using IR Thermography
Unmanned Aerial Vehicle (UAV) inspection systems are becoming an efficient method for operating and maintaining various types of infrastructure. One of the use cases for UAV systems is to detect anomalies in photovoltaic power plants. UAV systems can be equipped with infrared and visual cameras and take images from photovoltaic panels. An image processing algorithm is used to detect and classify the type of anomaly. This student team worked to create a UAV system that can detect anomalies on photovoltaic panels using infrared and visual light cameras. All the computations was to be done using the Nvidia Jetson Nano Developer Kit mounted on the UAV system.
Faculty Adviser
Payman Arabshahi,
Associate Professor, UW ECE,
Electrical & Computer Engineering
Students
Ali Issa Salman
Cheng-Ho Liao
Fumin Hsu
Ting Jones
Wesley Huang
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