Wind turbine Bearing Condition Monitoring Based on High Frequency Resonance method

被引:0
作者
Zhang, Xueyan [1 ]
Yang, Shenggang [2 ]
Li, Xiaoli [2 ]
机构
[1] Ningbo TV & Radio Univ, Dept Informat Technol, Ningbo 315020, Zhejiang, Peoples R China
[2] Yanshan Univ, Inst Elect Engn, Key Lab Ind Comp Control Engn, Qingdao 066004, Peoples R China
来源
2011 INTERNATIONAL CONFERENCE ON ELECTRONICS, COMMUNICATIONS AND CONTROL (ICECC) | 2011年
基金
中国国家自然科学基金;
关键词
Bearing; Condition Monitoring; Fault Diagnosis; Wind Turbine; High Frequency Resonance; WAVELET FILTER;
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Bearing is the most frequently used component in a wind turbine, and its' faults would lead to completely stall of a machine. Therefore, bearing Fault Diagnosis is an important part of condition monitoring in a wind turbine. This paper presented a High Frequency Resonance (HFR) method to implement bearing fault detection and fault diagnosis. This technique extracted the amplitude and frequency modulations of the vibration signals which measured from a wind turbine system. For the amplitude demodulation is inherent in the vibration signals, the fault frequency will be detected from the spectrum of the transformed original signals. And the effectiveness of this approach has been validated by simulated signal and experimental data.
引用
收藏
页码:1792 / 1795
页数:4
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