This study presents a novel and cost-effective technique for detecting degradation in photovoltaic (PV) modules using ultraviolet (UV) light-emitting diodes (LEDs). PV modules are widely used for sustainable energy generation; however, environmental factors such as ultraviolet radiation, temperature fluctuations, humidity, and water penetration significantly reduce their efficiency and operational lifetime. In this research, a custom-designed fault detection system was developed, consisting of UV LEDs (390–410 nm), an OPT101 photodiode sensor, an Arduino-based control unit, and a MATLAB-based user interface. The system was experimentally tested under Standard Test Conditions (STC: 1000 W m-², 25 °C) on 40 W polycrystalline silicon modules. The proposed method focuses on detecting surface color changes, microcracks, and snail trail formations, which are common indicators of PV module deterioration. Experimental results demonstrate that the UV-based detection approach is more effective, lightweight, and economical compared to traditional fault detection techniques such as infrared thermography and electroluminescence imaging. The system successfully identifies degradation by measuring reflected light intensity and visually mapping affected areas. This approach enables efficient maintenance strategies for PV systems, improving energy yield and reducing long-term operational costs. As future work, the developed detection system can be integrated with autonomous robots for large-scale PV plant monitoring, enabling continuous and non-invasive performance diagnostics.