Aspects of structural health and condition monitoring of offshore wind turbines.
Aspects of structural health and condition monitoring of offshore wind turbines.
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DOI：
10.1098/rsta.2014.0075
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发表时间：
2015-02-28
期刊：
影响因子：
--
通讯作者：
Worden K
中科院分区：
文献类型：
--
作者：
Antoniadou I;Dervilis N;Papatheou E;Maguire AE;Worden K
在过去几年中，风力发电已经显著扩展，尽管风力涡轮机系统的可靠性，特别是海上风力涡轮机的可靠性，在过去多次不令人满意。风力涡轮机故障相当于重大的经济损失。因此，创建和应用策略，提高其组件的可靠性是很重要的成功实施这样的系统。结构健康监测（SHM）通过监测指示所检查结构状态的参数来解决这些问题。另一方面，状态监测（CM）可以被看作是SHM社区的一个专门领域，其目的是对旋转机械进行损伤检测。论文分为两个部分：第一部分，以风力涡轮机齿轮箱和叶片损伤检测为例，讨论了先进的信号处理和机器学习方法用于SHM和CM。在第二部分中，提出了海上风电场的监控和数据采集系统数据的初步探索，并提出了数据驱动的方法来检测风力涡轮机的异常行为。结果表明，先进的信号处理方法是有效的，它是重要的，在风能部门采用这些SHM策略。
Wind power has expanded significantly over the past years, although reliability of wind turbine systems, especially of offshore wind turbines, has been many times unsatisfactory in the past. Wind turbine failures are equivalent to crucial financial losses. Therefore, creating and applying strategies that improve the reliability of their components is important for a successful implementation of such systems. Structural health monitoring (SHM) addresses these problems through the monitoring of parameters indicative of the state of the structure examined. Condition monitoring (CM), on the other hand, can be seen as a specialized area of the SHM community that aims at damage detection of, particularly, rotating machinery. The paper is divided into two parts: in the first part, advanced signal processing and machine learning methods are discussed for SHM and CM on wind turbine gearbox and blade damage detection examples. In the second part, an initial exploration of supervisor control and data acquisition systems data of an offshore wind farm is presented, and data-driven approaches are proposed for detecting abnormal behaviour of wind turbines. It is shown that the advanced signal processing methods discussed are effective and that it is important to adopt these SHM strategies in the wind energy sector.
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发表时间：
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影响因子：
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作者：
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发表时间：
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