Advanced Fault Detection in PV Panels Using Deep Neural Networks: Leveraging Transfer Learning and Electroluminescence Image Processing

Key Points

• To enhance fault detection in photovoltaic systems using advanced deep learning techniques.
• Utilized deep neural networks for fault detection analysis.
• Applied transfer learning to improve model accuracy.
• Employed electroluminescence image processing for fault visualization.
• Achieved notable improvements in fault detection accuracy.
• Identified various fault types affecting power generation and reliability.
• Demonstrated effectiveness of transfer learning in reducing training time.