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Novel early warning fault detection for wind-turbine-based DG systems

机译:基于风轮机的DG系统的新型预警故障检测

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This paper will study condition monitoring signals of a distributed generation (DG) system not only due to the mechanical and electrical faults inside the wind turbines but also due to the grid system fluctuations. A novel feature extraction and characterisation method based on singularity detection of the monitoring data will be presented, aiming to identify the abnormal events and fault conditions as early as possible. The algorithm used to calculate Lipschitz values is given in the paper and efficient processing and storage of monitoring data is also discussed. The preliminary research has produced promising results.
机译:本文将研究分布式发电(DG)系统的状态监测信号,这不仅是由于风力涡轮机内部的机械和电气故障,还由于电网系统的波动。提出了一种基于奇异性检测数据的特征提取与表征的新方法,旨在尽早识别异常事件和故障情况。文中给出了用于计算Lipschitz值的算法,并讨论了监控数据的有效处理和存储。初步研究产生了可喜的结果。

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