[1] |
Zhang Jing,Li Ning,Li Shao-yuan,et al. Health assessment of wind turbine generator based on data[J].Information and Control,2018,47(6):694-701.(in Chinese)
|
[2] |
Cao Meng-nan, Qiu Ying-ning, Feng Yan-hui, et al. Fault diagnosis of a wind generator based on equivalent thermal network method[J].Journal of Engineering Thermophysics,2019,40(2):306-313.(in Chinese)
|
[3] |
Yang C,Liu J,Zeng Y,et al.Real-time condition monitoring and fault detection of components based on machine-learning reconstruction model[J].Renewable Energy,2019,133:433-441.
|
[4] |
Wang L,Zhang Z,Long H,et al.Wind turbine gearbox failure identification with deep neural networks[J].IEEE Transactions on Industrial Informatics,2017,
|
13 |
(3):1360-1368.
|
[5] |
Zhao H,Liu H,Hu W,et al.Anomaly detection and fault analysis of wind turbine components based on deep learning network[J].Renewable Energy,2018,127:825-834.
|
[6] |
Jiang Li.Nonlinear process monitoring based on auto-encoder model[D].Hangzhou:Zhejiang University,2018.(in Chinese)
|
[7] |
Moussavi-Khalkhali A,Jamshidi M.Constructing a deep regression model utilizing cascaded sparse autoencoders and stochastic gradient descent[C]
|
|
∥Proc of the 2016 15th IEEE International Conference on Machine Learning and Applications (ICMLA),2016:559-564.
|
[8] |
Sun Z,Sun H.Stacked denoising autoencoder with density-grid based clustering method for detecting outlier of wind turbine components[J].IEEE Access,2019,
|
7: |
13078-13091.
|
|
附中文参考文献:
|
[1] |
张静,李柠,李少远,等.基于数据的风电机组发电机健康状况评估[J].信息与控制,2018,47(6):694-701.
|
[2] |
曹梦楠,邱颖宁,冯延晖,等.基于等效热网络法的风力发电机故障诊断[J].工程热物理学报,2019,40(2):306-313.
|
[6] |
蒋立.基于自编码器模型的非线性过程监测[D].杭州:浙江大学,2018.
|