Abstract

Numerous damage detection methods have been discovered to provide an early warning at the earliest possible stage against structural damage or any type of abnormality in the wind turbine system. In this paper, a comprehensive literature review is carried out in the field of damage detection for wind turbine systems. Several modern signal processing techniques including time-domain and frequency-domain analysis, joint time–frequency methods, entropy-based damage detection, supervisory control and data acquisition (SCADA), and machine learning approaches are all emphasized, and how to estimate the damage in wind turbine system by utilizing these various approaches is discussed. It is concluded that each of these methods offers its own unique merits and shortcomings in detecting certain types of damage with various levels of complexity. This research paper is aimed to inform the readers and experts about the damage detection techniques of the wind turbine system and fault diagnosis with various advanced signal processing methods.

Graphical abstract

中文翻译：

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基于信号处理方法的风轮机系统损伤检测：关键评论

摘要

已经发现了许多损坏检测方法，以在早期阶段就结构损坏或风力涡轮机系统中的任何类型的异常提供预警。本文在风力涡轮机系统的损伤检测领域进行了全面的文献综述。强调了几种现代信号处理技术，包括时域和频域分析，联合时频方法，基于熵的损伤检测，监督控制和数据采集（SCADA）以及机器学习方法，以及如何估计损伤讨论了利用这些各种方法在风力涡轮机系统中的应用。结论是，这些方法在检测具有不同复杂程度的某些类型的损害时，都有其独特的优缺点。

图形概要