在雷击期间监测风力轮机叶片的多式数据集
Tao Li1, Chenxi Li1, Yuxin Qin2
1School of Transportation and Electrical Engineering, Hunan University of Technology, Zhuzhou, China.
Scientific data
|August 31, 2025
概括
这项研究引入了一种罕见的多式数据集,用于在闪电时监测风力轮机叶片. 这些数据有助于开发用于雷电检测和叶片损害评估的预测模型,提高风能可靠性.
科学领域:
- 工程
- 材料科学
- 可再生能源
背景情况:
- 风力轮机叶片容易受到闪电袭击, 损害结构完整性和性能.
- 在闪电事件中获取全面的动态数据很困难,这阻碍了有效的监测和损害评估.
研究的目的:
- 引入一个新的多式数据集 (MDWTBM-LS) 用于在闪电中监控风力轮机叶片.
- 促进用于雷击检测和伤害评估的先进预测模型的开发.
- 支持机器学习,状态监测和风能系统故障预测方面的研究.
主要方法:
- 收集多模式数据,包括振动,负载和应变测量.
- 使用光纤负载传感器和光纤加速度计传感器进行实时数据采集.
- 记录了刀片的运行状态,并进行了打击后损坏评估.
主要成果:
- 创建了一个罕见的多式数据集 (MDWTBM-LS),记录了风力轮机叶片对闪电的反应.
- 该数据集提供实时操作状态和损坏信息.
- 该数据集可供公众使用,以促进研究和开发.
结论:
- MDWTBM-LS数据集对于推进风力轮机防雷预测建模至关重要.
- 使用这些数据可以制定更好的监测和维护策略.
- 这种资源将有助于提高风能设施的可靠性和运行优化.
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