A review of artificial intelligence applications in wind turbine health monitoring
Abirami Sasinthiran, Sakthivel Gnanasekaran, Ramesh Ragala
Abstract
Wind energy is a promising renewable source, necessitating effective monitoring of wind turbine (WT) conditions for reliable and costeffective energy production, amidst environmental challenges.Condition monitoring of WTs employs traditional methods, signal processing, and emerging artificial intelligence (AI) approaches.AIdriven 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.