A Survey of Wind Turbine Control Monitoring and Fault Detection on Wind Energy

被引：0
|
作者：
Kokila, M. [1 ]
Devi, P. Isakki [2 ]
机构：
[1] Ayya Nadar Janaki Ammal Coll, Dept Comp Sci, Sivakasi, India
[2] Ayya Nadar Janaki Ammal Coll, Dept Comp Applicat, Sivakasi, India
来源：
2016 INTERNATIONAL CONFERENCE ON COMPUTING TECHNOLOGIES AND INTELLIGENT DATA ENGINEERING (ICCTIDE'16) | 2016年
关键词：
Wind energy; clustering; power curve; the condition monitoring and the fault detection;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Most applications of data mining had been overwhelming in a wind turbine energy system reviewed. Wind power prediction is the biggest challenges in the world. Wind energy research, involving wind turbine control, Turbine monitoring and to detection of fault are surveyed. To monitor the wind farm performance, three types of curve include the power curve, blade curve, rotor curve are presented. Particular faulty components are identified. Wind turbine conditions are monitored and fault defects are analyzed. This paper's aim is to predict wind turbine fault and replaced the faulty components. Data mining techniques used for wind turbine energy is focused.
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页数：4
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