Wind Turbine Condition Monitoring Using SCADA Data and Data Mining Method

被引:0
|
作者
Pei, Yan [1 ]
Qian, Zheng [2 ]
Tao, Siyu [1 ]
Yu, Hao [3 ]
机构
[1] Beihang Univ, Beijing, Peoples R China
[2] Beihang Univ, Instrument Sci & Technol, Beijing, Peoples R China
[3] China Elect Power Res Inst Beijing, High Voltage Dept, Beijing 100192, Peoples R China
基金
中国国家自然科学基金;
关键词
Wind turbine condition monitoring; data mining; feature vector; outlier detection;
D O I
暂无
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
WTCM (Wind Turbine Condition Monitoring) system is important for wind farm operators to realize condition-based O&M (operation & maintenance), in the purpose of reducing O&M cost and improving wind turbine reliability. A WTCM method using only SCADA data based on data mining algorithm is proposed in this paper. Firstly, ARD (Automatic Relevance Determination) algorithm is adopted to determine the effective variables that are relevant to wind turbine condition. Feature vector is then extracted using the effective variables to represent the operation condition of wind turbine. Finally, the condition of a wind turbine is determined using outlier detection algorithm based on the extracted feature vector. Real-world dataset is used to validate the efficiency of the proposed method. Experiment results show that the proposed method can provide advanced failure alarm for wind turbines many days before failure happens. O&M cost can be reduced by condition-based O&M strategy using the result of our proposed WTCM method.
引用
收藏
页码:3760 / 3764
页数:5
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