In this research, drones were used to capture thermal images and detect different types of failure of solar modules, and MATLAB® image analysis was also conducted to evaluate the health of the solar modules. The
1A snail trail is a discoloration of the panel. Fig. 1. System at work in a PV plant. The DJI Matrice 300 drone was equipped with a hybrid RGB and a thermal camera, the DJI Zenmuse XT2. if
solar panel defects and various forms of inspection. Drones were also flown to Drone flights were taken in November of 2018. Photos included are gathered from the articles read or were
Abstract. Due to weathering and external forces, solar panels are subject to fouling and defects after a certain amount of time in service. These fouling and defects have
Inspection drones offer a wide range of advantages to the stakeholders in the construction industry, this is why they are preferred by roofing companies and most building owners, whether they want to detect storm damage, inspect
Fig. 2 shows a fault detected in a solar panel by a thermogram taken with a drone. The correct application of IT can be complex, especially in the large areas of solar farms with thousands of
Utilize a thermal imaging camera and a drone to inspect the defective solar panel in a solar farm. A traditional way of finding defects is to walk on foot and inspect each panel one by one. This project can help reduce time and increase the
Defects in photovoltaic panels are generally detected by analyzing infrared images taken by drones. However, the photovoltaic panel defects to be detected in infrared images are small,
The method is based on the following three steps, whose output is shown in Fig. 1: (i) during the Preprocessing step, the lines in the images (white lines in Fig. 1b) are
Liao and Lu employed an unmanned aerial vehicle (UAV) to conduct the detection of solar panel faults by inspecting solar panel infrared (IR) images. These infrared image displays could be divided into three health
The objective of this research is to compare the fault detection analyses performed, for two different solar PV plants, using alternatively an unmanned drone and a manned aircraft as aerial platforms, equipped with different IR cameras to provide reliable and comparable thermal images over the same inspected sites.
In this research, drones were used to capture thermal images and detect different types of failure of solar modules, and MATLAB ® image analysis was also conducted to evaluate the health of the solar modules. The processes included image acquisition and transmission by drone, grayscale conversion, filtering, 3D image construction, and analysis.
Alsafasfeh et al. proposed a safer and low-cost real-time model combining two cameras, a thermal imager, and a charge-coupled device (CCD) mounted on a drone, to indicate and detect the faults in a PV system [ 4 ]. According to the experiment, it could detect internal and external faults.
Airplane-based inspections are more convenient than UAV surveys for PV plants > 40 MW. The continuous increase in the number and scale of solar photovoltaic power plants requires the implementation of reliable diagnostic tools for fault detection.
The autonomous inspection of PV plants through UAV photogrammetry has been explored in the literature , , , . The UAV is given a set of waypoints, usually arranged in such a way to cover a delimited area to ensure the required horizontal and vertical overlapping of images.
Generally, UAVs used for PV inspection are equipped with a thermal camera (which may or may not complement a standard RGB camera or other sensors) to identify defects that can produce heat anomalies on the solar panels.
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