This paper presents a novel framework for collaborative inspection of solar panel farms that use the complementary capabilities of Unmanned Ground Vehicles (UGVs) and Unmanned
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This article proposes a method for detecting solar cell faults with unmanned aerial vehicle (UAV) equipped with a thermal imager and a visible light camera, and providing a fast and reliable
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The existing hot-spot fault detection methods of photovoltaic panels cannot adequately complete the real-time detection task; hence, a detection model considering both detection accuracy and speed is
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The use of thermal imagery and UAVs has become increasingly common for detecting faults in solar panel systems, particularly in large-scale arrays where traditional electrical methods are difficult to
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This paper presents a novel localization pipeline that directly integrates PV module detection with UAV navigation, allowing precise positioning during inspection. The detections are
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Timely and accurate detection of defects and contaminants in solar panels is critical for maintaining the efficiency and reliability of photovoltaic (PV) systems.
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In this article, a hot spot defect detection algorithm according to infrared images of aerial PV is proposed for practical engineering problems such as defects with different morphology, unclear
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In this study, a lightweight real-time detection model, TA-YOLOv11, is proposed for UAV-based IR PV panel defect identification.
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The growing reliance on photovoltaic (PV) systems as a sustainable energy source is challenged by performance degradation due to faults, necessitating efficient fault detection methods.
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It examines key components of UAV-based PV inspection, including data acquisition protocols, panel segmentation and geolocation, anomaly classification, and optimizations for model
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