Optimization of SWIR Image Capture and Processing for Defect Detection in Photovoltaic Panels

This work introduces a methodology for capturing and processing Short-Wave Infrared (SWIR) images focused on detecting structural defects in photovoltaic panels. Indium Gallium Arsenide (InGaAs) sensors were used in combination with perspective correction, background subtraction, and contrast enhancement through the CLAHE algorithm. Experimental testing showed that adjusting capture parameters appropriately, along with efficient preprocessing, allows precise identification of defects such as cracks, inactive zones, and discontinuities in collector bars. This approach supports preventive maintenance strategies and helps extend the operational lifespan of photovoltaic installations.