Wind turbine planetary gearbox feature extraction and fault diagnosis using a deep-learning-based approach
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DOI: 10.1177/1748006X18768701
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References listed on IDEAS
- Chen, Jinglong & Pan, Jun & Li, Zipeng & Zi, Yanyang & Chen, Xuefeng, 2016. "Generator bearing fault diagnosis for wind turbine via empirical wavelet transform using measured vibration signals," Renewable Energy, Elsevier, vol. 89(C), pages 80-92.
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Cited by:
- K. N. Ravikumar & Suhas S. Aralikatti & Hemantha Kumar & G. N. Kumar & K. V. Gangadharan, 2022. "Fault diagnosis of antifriction bearing in internal combustion engine gearbox using data mining techniques," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 13(3), pages 1121-1134, June.
- Sridharan Naveen Venkatesh & Vaithiyanathan Sugumaran, 2022. "A combined approach of convolutional neural networks and machine learning for visual fault classification in photovoltaic modules," Journal of Risk and Reliability, , vol. 236(1), pages 148-159, February.
- Pan, Yubin & Hong, Rongjing & Chen, Jie & Wu, Weiwei, 2020. "A hybrid DBN-SOM-PF-based prognostic approach of remaining useful life for wind turbine gearbox," Renewable Energy, Elsevier, vol. 152(C), pages 138-154.
- Jorge Maldonado-Correa & Sergio Martín-Martínez & Estefanía Artigao & Emilio Gómez-Lázaro, 2020. "Using SCADA Data for Wind Turbine Condition Monitoring: A Systematic Literature Review," Energies, MDPI, vol. 13(12), pages 1-21, June.
- Lei Fu & Tiantian Zhu & Kai Zhu & Yiling Yang, 2019. "Condition Monitoring for the Roller Bearings of Wind Turbines under Variable Working Conditions Based on the Fisher Score and Permutation Entropy," Energies, MDPI, vol. 12(16), pages 1-20, August.
- Li, Yanting & Jiang, Wenbo & Zhang, Guangyao & Shu, Lianjie, 2021. "Wind turbine fault diagnosis based on transfer learning and convolutional autoencoder with small-scale data," Renewable Energy, Elsevier, vol. 171(C), pages 103-115.
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Keywords
Fault diagnostics; planetary gearbox; feature extraction; large memory storage and retrieval networks; deep learning; wind turbine;All these keywords.
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