Wind Turbine Fault Detection Using a Denoising Autoencoder With Temporal Information

Data-driven approaches have gained increasing interests in the fault detection of wind turbines (WTs) due to the difficulty in system modeling and the availability of sensor data. However, the nonlinearity of WTs, uncertainty of disturbances and measurement noise, and temporal dependence in time-ser...

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Veröffentlicht in:	IEEE/ASME transactions on mechatronics Jg. 23; H. 1; S. 89 - 100
Hauptverfasser:	Jiang, Guoqian, Xie, Ping, He, Haibo, Yan, Jun
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	IEEE 01.02.2018
Schlagworte:	Complex mechatronics Correlation denoising autoencoder (DAE) Fault detection Mechatronics Monitoring multivariate data driven Noise reduction Robustness Temperature measurement temporal information wind turbines (WTs)
ISSN:	1083-4435, 1941-014X
Online-Zugang:	Volltext
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