By analyzing temperature differences across PV modules during various operating states, IR thermography identifies issues such as hot spots, bypass diode failures, and internal shorts, supporting proactive and non-destructive quality assurance. . This position paper examines several computer vision algorithms that automate thermal anomaly detection in infrared imagery. We demonstrate our infrared thermography data collection approach, the PV thermal imagery benchmark dataset, and the measured performance of image processing transformations. . Thermography is a non-invasive inspection technique that can be performed remotely over large areas and provides immediate feedback; because of these characteristics, it has long been used to detect anomalies in photovoltaic panels. Thermal camera inspections can be conducted under normal plant. . Inspection of the photovoltaic modules with a thermal imager is critical to identify any problems. Optimizing the efficiency of solar energy farms necessitates comprehensive. .
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