The keywords used for the search were: Solar panel defect detection; PV module degradation; PV module fault detection, PV module degradation measurement methods, and techniques; Solar cell degradation detection technique; PV module, Solar panel performance measurement, PV module wastage, and its environmental effect, and PV module fault diagnosis.
However, this method is based on expanding a UV beam to illuminate an extensive area of the PV sample, making it troublesome as fluorescence signal (typically small) tends to fade quickly. The least used solar panel defect detection method is the scanning electron microscopy (SEM) imaging technique.
Visualizing feature map (The figure illustrates the change in the feature map after the SRE module.) We propose a photovoltaic cell defect detection model capable of extracting topological knowledge, aggregating local multi-order dynamic contexts, and effectively capturing diverse defect features, particularly for small flaws.
However, traditional object detection models prove inadequate for handling photovoltaic cell electroluminescence (EL) images, which are characterized by high levels of noise. To address this challenge, we developed an advanced defect detection model specifically designed for photovoltaic cells, which integrates topological knowledge extraction.
6. Discussion and comparative analysis The solar panel defects can be classified as optical and electrical-mismatch-related degradation, such as discoloration of the encapsulant, front cover glass breakage, delamination, shading, cell fracture snail trails, poor soldering, broken interconnection ribbons, and short-circuited cells [ 80 ].
Moreover, to generalize the PV cell defect detection methods, this paper divide them into (i) imaging-based techniques, (ii) rapid visual inspection methods, and (iii) I–V curve measurements, which are the most powerful diagnostic tools for field-level testing.