Diagnosis of Faults and Defects in Photovoltaic Panels: Imaging, Data Driven Methods, Intelligent Systems

This book presents a comprehensive overview of intelligent fault diagnosis for photovoltaic (PV) systems in the context of modern large-scale solar installations. It reviews common electrical, mechanical, and environmental faults and highlights the limitations of traditional inspection and monitoring methods. The book focuses on advanced sensing and imaging techniques, including RGB, infrared thermography, and electroluminescence, and explains how these data sources are combined with machine learning and deep learning methods for automated fault detection, classification, and localization. Key topics such as data preprocessing, feature extraction, model training, evaluation, and deployment are discussed, providing a solid reference for researchers and engineers working on intelligent PV monitoring and maintenance systems.