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A survey of health monitoring systems for wind turbines

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  1. Yang, Zhimin & Chai, Yi, 2016. "A survey of fault diagnosis for onshore grid-connected converter in wind energy conversion systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 66(C), pages 345-359.
  2. Wei-Hua Hu & De-Hui Tang & Ming Wang & Jun-Le Liu & Zuo-Hua Li & Wei Lu & Jun Teng & Samir Said & Rolf. G. Rohrmann, 2020. "Resonance Monitoring of a Horizontal Wind Turbine by Strain-Based Automated Operational Modal Analysis," Energies, MDPI, vol. 13(3), pages 1-21, January.
  3. Giovanni Rinaldi & Philipp R. Thies & Lars Johanning, 2021. "Current Status and Future Trends in the Operation and Maintenance of Offshore Wind Turbines: A Review," Energies, MDPI, vol. 14(9), pages 1-28, April.
  4. Rubert, T. & Zorzi, G. & Fusiek, G. & Niewczas, P. & McMillan, D. & McAlorum, J. & Perry, M., 2019. "Wind turbine lifetime extension decision-making based on structural health monitoring," Renewable Energy, Elsevier, vol. 143(C), pages 611-621.
  5. Stetco, Adrian & Dinmohammadi, Fateme & Zhao, Xingyu & Robu, Valentin & Flynn, David & Barnes, Mike & Keane, John & Nenadic, Goran, 2019. "Machine learning methods for wind turbine condition monitoring: A review," Renewable Energy, Elsevier, vol. 133(C), pages 620-635.
  6. Ruiz de la Hermosa González-Carrato, Raúl, 2018. "Wind farm monitoring using Mahalanobis distance and fuzzy clustering," Renewable Energy, Elsevier, vol. 123(C), pages 526-540.
  7. Andreas Baumann-Ouyang & Jemil Avers Butt & Matej Varga & Andreas Wieser, 2023. "MIMO-SAR Interferometric Measurements for Wind Turbine Tower Deformation Monitoring," Energies, MDPI, vol. 16(3), pages 1-20, February.
  8. Artigao, Estefania & Martín-Martínez, Sergio & Honrubia-Escribano, Andrés & Gómez-Lázaro, Emilio, 2018. "Wind turbine reliability: A comprehensive review towards effective condition monitoring development," Applied Energy, Elsevier, vol. 228(C), pages 1569-1583.
  9. Jijian Lian & Ou Cai & Xiaofeng Dong & Qi Jiang & Yue Zhao, 2019. "Health Monitoring and Safety Evaluation of the Offshore Wind Turbine Structure: A Review and Discussion of Future Development," Sustainability, MDPI, vol. 11(2), pages 1-29, January.
  10. Wang, Bingkai & Sun, Wenlei & Wang, Hongwei & Xu, Tiantian & Zou, Yi, 2024. "Research on rapid calculation method of wind turbine blade strain for digital twin," Renewable Energy, Elsevier, vol. 221(C).
  11. Mario Vieira & Brian Snyder & Elsa Henriques & Craig White & Luis Reis, 2023. "Economic Viability of Implementing Structural Health Monitoring Systems on the Support Structures of Bottom-Fixed Offshore Wind," Energies, MDPI, vol. 16(13), pages 1-20, June.
  12. Igliński, Bartłomiej & Iglińska, Anna & Koziński, Grzegorz & Skrzatek, Mateusz & Buczkowski, Roman, 2016. "Wind energy in Poland – History, current state, surveys, Renewable Energy Sources Act, SWOT analysis," Renewable and Sustainable Energy Reviews, Elsevier, vol. 64(C), pages 19-33.
  13. Paula Helming & Axel von Freyberg & Michael Sorg & Andreas Fischer, 2021. "Wind Turbine Tower Deformation Measurement Using Terrestrial Laser Scanning on a 3.4 MW Wind Turbine," Energies, MDPI, vol. 14(11), pages 1-14, June.
  14. Fallahi, F. & Bakir, I. & Yildirim, M. & Ye, Z., 2022. "A chance-constrained optimization framework for wind farms to manage fleet-level availability in condition based maintenance and operations," Renewable and Sustainable Energy Reviews, Elsevier, vol. 168(C).
  15. Sakaris, Christos S. & Yang, Yang & Bashir, Musa & Michailides, Constantine & Wang, Jin & Sakellariou, John S. & Li, Chun, 2021. "Structural health monitoring of tendons in a multibody floating offshore wind turbine under varying environmental and operating conditions," Renewable Energy, Elsevier, vol. 179(C), pages 1897-1914.
  16. Tadeusz Głowacki, 2022. "Monitoring the Geometry of Tall Objects in Energy Industry," Energies, MDPI, vol. 15(7), pages 1-15, March.
  17. Bakir, I. & Yildirim, M. & Ursavas, E., 2021. "An integrated optimization framework for multi-component predictive analytics in wind farm operations & maintenance," Renewable and Sustainable Energy Reviews, Elsevier, vol. 138(C).
  18. Sungmok Hwang & Cheol Yoo, 2021. "Health Monitoring and Diagnosis System for a Small H-Type Darrieus Vertical-Axis Wind Turbine," Energies, MDPI, vol. 14(21), pages 1-18, November.
  19. Urmeneta, Jon & Izquierdo, Juan & Leturiondo, Urko, 2023. "A methodology for performance assessment at system level—Identification of operating regimes and anomaly detection in wind turbines," Renewable Energy, Elsevier, vol. 205(C), pages 281-292.
  20. ASM Shihavuddin & Xiao Chen & Vladimir Fedorov & Anders Nymark Christensen & Nicolai Andre Brogaard Riis & Kim Branner & Anders Bjorholm Dahl & Rasmus Reinhold Paulsen, 2019. "Wind Turbine Surface Damage Detection by Deep Learning Aided Drone Inspection Analysis," Energies, MDPI, vol. 12(4), pages 1-15, February.
  21. Castellano-Aldave, Carlos & Carlosena, Alfonso & Iriarte, Xabier & Plaza, Aitor, 2023. "Ultra-low frequency multidirectional harvester for wind turbines," Applied Energy, Elsevier, vol. 334(C).
  22. Lorin Jenkel & Stefan Jonas & Angela Meyer, 2023. "Privacy-Preserving Fleet-Wide Learning of Wind Turbine Conditions with Federated Learning," Energies, MDPI, vol. 16(17), pages 1-29, September.
  23. Pliego Marugán, Alberto & Peco Chacón, Ana María & García Márquez, Fausto Pedro, 2019. "Reliability analysis of detecting false alarms that employ neural networks: A real case study on wind turbines," Reliability Engineering and System Safety, Elsevier, vol. 191(C).
  24. Burgaç, Alper & Yavuz, Hakan, 2019. "Fuzzy Logic based hybrid type control implementation of a heaving wave energy converter," Energy, Elsevier, vol. 170(C), pages 1202-1214.
  25. Kaewniam, Panida & Cao, Maosen & Alkayem, Nizar Faisal & Li, Dayang & Manoach, Emil, 2022. "Recent advances in damage detection of wind turbine blades: A state-of-the-art review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 167(C).
  26. Bakdi, Azzeddine & Kouadri, Abdelmalek & Mekhilef, Saad, 2019. "A data-driven algorithm for online detection of component and system faults in modern wind turbines at different operating zones," Renewable and Sustainable Energy Reviews, Elsevier, vol. 103(C), pages 546-555.
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