Search

Wind energy is a promising renewable source, necessitating effective monitoring of wind turbine (WT) conditions for reliable and cost-effective energy production, amidst environmental challenges. Condition monitoring of WTs employs traditional methods, signal processing, and emerging artificial intelligence (AI) approaches. AI-driven techniques excel in data-driven decision-making, addressing big data challenges in condition monitoring. This review paper presents a comprehensive overview of all streams of condition monitoring associated with WT, offering detailed insights into the related tasks. It also provides details on AI-based approaches and their application in executing various tasks within condition monitoring for WT. Finally, the study summarises the current trends, advantages, and disadvantages of AI-based techniques for real-world decision making in condition monitoring. This systematic review covers fundamentals to future developments in AI-driven approaches in condition monitoring for WT, serving as a valuable resource for readers and novice researchers in this field. [ABSTRACT FROM AUTHOR]