Wind turbine frequent principal fault detection based on a self-attentive LSTM encoder-decoder model

With the development of intelligent monitoring technology, internet information technology, and data storage technology, data-driven fault detection and diagnosis method in the wind turbine system has become a focus of research in recent years. In this paper, we design a data-driven architecture for...

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Bibliographic Details

Published in:	Chinese Control Conference pp. 4171 - 4176
Main Authors:	JIANG, Na, LI, Ning
Format:	Conference Proceeding
Language:	English
Published:	Technical Committee on Control Theory, Chinese Association of Automation 01.07.2020
Subjects:	Data models Fault detection Feature extraction Feature sequence extraction Frequent principal fault detection Logic gates SALSTMED Time series Time series analysis Wind power generation Wind turbine system Wind turbines
ISSN:	1934-1768
Online Access:	Get full text
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