Research on State Prediction of Wind Turbine Gearbox Based on Monitoring Data Distribution Similarity and Feature-Based Transfer Learning

Author:

Zhu Yongchao,Zhu Caichao,Tan Yong,Tan Jianjun,Zhou Ye

Publisher

Springer Nature Singapore

Reference17 articles.

1. Zhu, Y., Zhu, C., Tan, J., Song, C., Chen, D., Zheng, J.: Fault detection of offshore wind turbine gearboxes based on deep adaptive networks via considering Spatio-temporal fusion. Renew. Energy 200, 1023–1036 (2022)

2. Rinaldi, G., Garcia-Teruel, A., Jeffrey, H., Thies, P., Johanning, L.: Incorporating stochastic operation and maintenance models into the techno-economic analysis of floating offshore wind farms. Appl. Energy 301, 1–18 (2021)

3. Wang, Y., Zhu, C., Li, Y., Tan, J.: The effect of reduced power operation of faulty wind turbines on the total power generation for different wind speeds. Sustainable Energy Technol. Assess. 45, 1–13 (2021)

4. Crabtree C., Tavner P.: Detecting incipient wind turbine gearbox failure: a signal analysis method for on-line condition monitoring. In: Proceedings of the Scientific Track of the European Wind Energy Conference.154–156. Warsaw, Poland (2010)

5. Zhu, Y., Zhu, C., Tan, J., Tan, Y., Rao, L.: Anomaly detection and condition monitoring of wind turbine gearbox based on LSTM-FS and transfer learning. Renew. Energy 189, 90–103 (2022)

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