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Wind turbine generator early fault diagnosis using LSTM-based stacked denoising autoencoder network and stacking algorithm
International Journal of Green Energy ( IF 3.3 ) Pub Date : 2024-02-15 , DOI: 10.1080/15435075.2024.2315445
Junshuai Yan 1 , Yongqian Liu , Hang Meng , Li Li , Xiaoying Ren
Affiliation  

To reduce the significant economic losses caused by the fault deterioration of wind turbine generators, it is urgent to detect and diagnose the early faults of generators. The existing condition mo...

中文翻译:

基于LSTM的堆叠式去噪自编码网络和堆叠算法的风力发电机早期故障诊断

为了减少风电机组故障恶化造成的重大经济损失,迫切需要对发电机的早期故障进行检测和诊断。现有条件最...
更新日期:2024-02-16
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