Author:
Abouhnik A.,Ibrahim G.,Deng Rongfeng,Brethee K.,Badawood A.,Abushanab W.,Zhang X.,Batunlu C.,Albarbar A.
Publisher
Springer Nature Switzerland
Reference14 articles.
1. Xu, Z., et al.: A state-of-the-art review of the vibration and noise of wind turbine drivetrains. Sustainable Energy Technol. Assess. 48, 101629 (2021)
2. Liu, Z., Yang, B., Wang, X., Zhang, L.: Acoustic emission analysis for wind turbine blade bearing fault detection under time-varying low-speed and heavy blade load conditions. IEEE Trans. Ind. Appl. 57(3), 2791–2800 (2021)
3. An, X., Jiang, D., Li, S.: Application of back propagation neural network to fault diagnosis of direct-drive wind turbine. In: World Non-Grid-Connected Wind Power and Energy Conference (WNWEC), pp. 1–5 (2010)
4. Park, J.-H., Park, H.-Y., Jeong, S.-Y., Lee, S.I., Shin, Y.-H., Park, J.P.: Linear vibration analysis of rotating wind-turbine blade. Curr. Appl. Phys. 3 (2009)
5. Abouhnik, A., Ibrahim, Ghalib R., Shnibha, R., Albarbar, A.: Novel approach to rotating machinery diagnostics based on principal component and residual matrix analysis. ISRN Mech. Eng. 2012, 1–7 (2012). https://doi.org/10.5402/2012/715893