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Progress and trends in nondestructive testing and evaluation for wind turbine composite blade

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  • Yang, Ruizhen
  • He, Yunze
  • Zhang, Hong

Abstract

Wind energy is one of the fastest growing renewable energy resources. It is distinctly important to increase reliability and availability of wind turbines and further to reduce the wind energy cost. Blades are considered to be one of the most critical components in wind turbine system because they convert Kinetic energy of wind into useable power. Blades are fabricated by carbon fiber reinforced polymer (CFRP) or glass fiber reinforced polymer (GFRP). Flaws and damages are inevitable during either fabrication or lifetime of a composite blade. Thus, non-destructive testing (NDT) and structural health monitoring (SHM) for wind turbine blade (WTB) are required to prevent failures and increase reliability in both manufacturing quality control and in-service inspection. In this work, a fully, in-depth and comprehensive review of NDT techniques for WTB inspection was reported based on an orderly and concise literature survey. Firstly, typical flaw and damage occurring in manufacturing progress and in service of WTB were introduced. Next, the developments of visual, sonic and ultrasonic, optical, electromagnetic, thermal and radiographic NDT for composite WTB inspection were reviewed. Thereafter, strengths and limitations of NDT techniques were concluded through comparison studies. In the end, some research trends in WTB NDT have been predicted, for example in combination with SHM. This work will provide a guide for NDT and SHM of WTB, which plays an important role in wind turbine safety control and wind energy cost savings. In addition, this work can benefit the NDT development in the field of renewable energy, such as solar energy, and energy conservation field, such as building diagnosis.

Suggested Citation

  • Yang, Ruizhen & He, Yunze & Zhang, Hong, 2016. "Progress and trends in nondestructive testing and evaluation for wind turbine composite blade," Renewable and Sustainable Energy Reviews, Elsevier, vol. 60(C), pages 1225-1250.
    • Handle: RePEc:eee:rensus:v:60:y:2016:i:c:p:1225-1250
    DOI: 10.1016/j.rser.2016.02.026
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    References listed on IDEAS

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    1. Yang, Xiyun & Zhang, Yanfeng & Lv, Wei & Wang, Dong, 2021. "Image recognition of wind turbine blade damage based on a deep learning model with transfer learning and an ensemble learning classifier," Renewable Energy, Elsevier, vol. 163(C), pages 386-397.
    2. Sun, Shilin & Wang, Tianyang & Yang, Hongxing & Chu, Fulei, 2022. "Damage identification of wind turbine blades using an adaptive method for compressive beamforming based on the generalized minimax-concave penalty function," Renewable Energy, Elsevier, vol. 181(C), pages 59-70.
    3. Murray, Robynne E. & Roadman, Jason & Beach, Ryan, 2019. "Fusion joining of thermoplastic composite wind turbine blades: Lap-shear bond characterization," Renewable Energy, Elsevier, vol. 140(C), pages 501-512.
    4. García Márquez, Fausto Pedro & Peco Chacón, Ana María, 2020. "A review of non-destructive testing on wind turbines blades," Renewable Energy, Elsevier, vol. 161(C), pages 998-1010.
    5. Wei Li & Shinai Xu & Baiyun Qian & Xiaoxia Gao & Xiaoxun Zhu & Zeqi Shi & Wei Liu & Qiaoliang Hu, 2022. "Large-Scale Wind Turbine’s Load Characteristics Excited by the Wind and Grid in Complex Terrain: A Review," Sustainability, MDPI, vol. 14(24), pages 1-29, December.
    6. Abdul Ghani Olabi & Tabbi Wilberforce & Khaled Elsaid & Enas Taha Sayed & Tareq Salameh & Mohammad Ali Abdelkareem & Ahmad Baroutaji, 2021. "A Review on Failure Modes of Wind Turbine Components," Energies, MDPI, vol. 14(17), pages 1-44, August.
    7. Andrius Kulsinskas & Petar Durdevic & Daniel Ortiz-Arroyo, 2021. "Internal Wind Turbine Blade Inspections Using UAVs: Analysis and Design Issues," Energies, MDPI, vol. 14(2), pages 1-19, January.
    8. Sun, Shilin & Wang, Tianyang & Chu, Fulei, 2022. "In-situ condition monitoring of wind turbine blades: A critical and systematic review of techniques, challenges, and futures," Renewable and Sustainable Energy Reviews, Elsevier, vol. 160(C).
    9. Liu, Y. & Hajj, M. & Bao, Y., 2022. "Review of robot-based damage assessment for offshore wind turbines," Renewable and Sustainable Energy Reviews, Elsevier, vol. 158(C).
    10. 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).
    11. Xiaowen Song & Zhitai Xing & Yan Jia & Xiaojuan Song & Chang Cai & Yinan Zhang & Zekun Wang & Jicai Guo & Qingan Li, 2022. "Review on the Damage and Fault Diagnosis of Wind Turbine Blades in the Germination Stage," Energies, MDPI, vol. 15(20), pages 1-17, October.

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