Fault Identification for Wind Turbine Based on Attention Mechanism and RCN-BiLSTM Fusion

To improve the identification accuracy of wind turbine faults, an RCN-BiLSTM-Attention wind turbine fault identification method based on the attention mechanism (AM) and the fusion of residual capsule network (RCN) and bidirectional long short-term memory (BiLSTM) network is proposed. First, the abn...

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Huvudupphov:	Xiaoqian CHEN, Liang YIN, Zonghui ZHAN, Fang WANG, Xutao LI
Materialtyp:	Artigo
Språk:	Chinês
Utgiven:	State Grid Energy Research Institute 2025-08-01
Serie:	Zhongguo dianli
Ämnen:	wind turbine fault identification bidirectional long short-term memory
Länkar:	https://www.electricpower.com.cn/CN/10.11930/j.issn.1004-9649.202412081
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