Using Order Tracking Analysis Method to Detect the Angle Faults of Blades on Wind Turbine

Pengfei Li, Weihao Hu, Juncheng Liu, Zhe Chen

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1 Citationer (Scopus)

Abstrakt

The angle faults of blades on wind turbines are usually included in the set angle fault and the pitch angle fault. They are occupied with a high proportion in all wind turbine faults. Compare with the traditional fault detection methods, using order tracking analysis method to detect angle faults has many advantages, such as easy implementation and high system reliability. Because of using Power Spectral Density method (PSD) or Fast Fourier Transform (FFT) method cannot get clear fault characteristic frequencies, this kind of faults should be detected by an effective method. This paper proposes a novel method of using order tracking analysis to analyze the signal of input aerodynamic torque which is received by hub. After the analyzed process, the fault characteristic frequency could be extracted by the analyzed signals and compared with the signals from normal operating conditions. By analyzing and reconstructing the fault signals, it is easy to detect the fault characteristic frequency and see the characteristic frequencies of angle faults depend on the shaft rotating frequency, which is known as the 1P frequency and 3P frequency distinctly.
OriginalsprogEngelsk
TitelProceedings of 35th Chinese Control Conference (CCC), 2016
Antal sider6
ForlagIEEE Press
Publikationsdatojul. 2016
Sider6801-6806
ISBN (Elektronisk)978-9-8815-6391-0
DOI
StatusUdgivet - jul. 2016
BegivenhedThe 35th Chinese Control Conference - New International Convention and Exhibition Center, Chengdu, Kina
Varighed: 27 jul. 201629 jul. 2016
Konferencens nummer: 35
http://ccc2016.swjtu.edu.cn/

Konference

KonferenceThe 35th Chinese Control Conference
Nummer35
LokationNew International Convention and Exhibition Center
LandKina
ByChengdu
Periode27/07/201629/07/2016
Internetadresse

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Citationsformater

Li, P., Hu, W., Liu, J., & Chen, Z. (2016). Using Order Tracking Analysis Method to Detect the Angle Faults of Blades on Wind Turbine. I Proceedings of 35th Chinese Control Conference (CCC), 2016 (s. 6801-6806). IEEE Press. https://doi.org/10.1109/ChiCC.2016.7554428