Teng Wei, Ding Xian, Tang Shiyao, Xu Jin, Shi Bingshuai, Liu Yibing
Key Laboratory of Power Station Energy Transfer Conversion and System, North China Electric Power University, Ministry of Education, Beijing 102206, China.
China Green Development Investment Group Co. Ltd., Beijing 100020, China.
Sensors (Basel). 2021 Mar 1;21(5):1686. doi: 10.3390/s21051686.
Vibration analysis is an effective tool for the condition monitoring and fault diagnosis of wind turbine drivetrains. It enables the defect location of mechanical subassemblies and health indicator construction for remaining useful life prediction, which is beneficial to reducing the operation and maintenance costs of wind farms. This paper analyzes the structure features of different drivetrains of mainstream wind turbines and introduces a vibration data acquisition system. Almost all the research on the vibration-based diagnosis algorithm for wind turbines in the past decade is reviewed, with its effects being discussed. Several challenging tasks and their solutions in the vibration-based fault detection of wind turbine drivetrains are proposed from the perspective of practicality for wind turbines, including the fault detection of planetary subassemblies in multistage wind turbine gearboxes, fault feature extraction under nonstationary conditions, fault information enhancement techniques and health indicator construction. Numerous naturally damaged cases representing the real operational features of industrial wind turbines are given, with a discussion of the failure mechanism of defective parts in wind turbine drivetrains as well.
振动分析是风力发电机组传动系统状态监测与故障诊断的有效工具。它能够实现机械子组件的缺陷定位以及用于剩余使用寿命预测的健康指标构建，这有利于降低风电场的运维成本。本文分析了主流风力发电机组不同传动系统的结构特点，并介绍了一种振动数据采集系统。回顾了过去十年中几乎所有关于风力发电机组基于振动的诊断算法的研究，并讨论了其效果。从风力发电机组的实用性角度出发，提出了风力发电机组传动系统基于振动的故障检测中的几个具有挑战性的任务及其解决方案，包括多级风力发电机组齿轮箱中行星子组件的故障检测、非平稳条件下的故障特征提取、故障信息增强技术以及健康指标构建。给出了大量代表工业风力发电机组实际运行特征的自然损坏案例，并讨论了风力发电机组传动系统中缺陷部件的失效机制。
