Wind Turbine Blade Breakage Monitoring With Mogrifier LSTM Autoencoder

Wind turbines (WTs) often work in harsh environmental conditions. The risk of blade breakage by hitting the tower has increased because of the decreased bending stiffness of the WT blades with the increasing sizes of WTs. To address the system dynamics of WTs, this article proposes a Mogrifier long...

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Bibliographic Details
Published in:	IEEE transactions on instrumentation and measurement Vol. 72; pp. 1 - 10
Main Authors:	Wu, Ping, Wang, Yixuan, Zhang, Xujie, Gao, Jinfeng, Wang, Lin, Liu, Yichao
Format:	Journal Article
Language:	English
Published:	New York IEEE 2023 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:	Blade breakage monitoring Blades Correlation coefficients Data models False alarms Feature extraction long short-term memory (LSTM) mogrifier long short-term memory autoencoder (MLSTM-AE) Monitoring Sensors Supervisory control and data acquisition supervisory control and data acquisition (SCADA) data System dynamics Turbine blades Wind farms Wind power wind turbine (WT) Wind turbines
ISSN:	0018-9456, 1557-9662
Online Access:	Get full text
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