风力发电
振动
涡轮机
涡轮叶片
可靠性(半导体)
断层(地质)
状态监测
海洋工程
计算机科学
汽车工程
环境科学
可靠性工程
结构工程
工程类
机械工程
地质学
功率(物理)
地震学
声学
物理
量子力学
电气工程
作者
Ahmed Ali Farhan Ogaili,Alaa Abdulhady Jaber,Mohsin Noori Hamzah
出处
期刊:Data in Brief
[Elsevier BV]
日期:2023-07-16
卷期号:49: 109414-109414
被引量:45
标识
DOI:10.1016/j.dib.2023.109414
摘要
Globally, wind turbines play a significant role in generating sustainable and clean energy. Ensuring optimal performance and reliability is crucial to minimize failures and reduce operating and maintenance costs. However, due to their conventional design, identifying faults in wind turbines is challenging. This dataset provides vibration data for faulty wind turbine blades, which covers common vibration excitation mechanisms associated with various faults and operating conditions, including wind speed. The introduced faults in the wind turbine blades include surface erosion, cracked blade, mass imbalance, and twist blade fault. This data article serves as a valuable resource for validating condition monitoring methods in industrial wind turbine applications and facilitates a better understanding of vibration signal characteristics associated with different faults.
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