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A Review and Case Analysis on Biaxial Synchronous Loading Technology and Fast Moment-Matching Methods for Fatigue Tests of Wind Turbine Blades

Author

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  • Liang Lu

    (School of Mechanical Engineering, Tongji University, Shanghai 200094, China
    Frontiers Science Center for Intelligent Autonomous Systems, Shanghai 201210, China)

  • Minyan Zhu

    (School of Mechanical Engineering, Tongji University, Shanghai 200094, China)

  • Haijun Wu

    (School of Mechanical Engineering, Tongji University, Shanghai 200094, China)

  • Jianzhong Wu

    (School of Mechanical Engineering, Tongji University, Shanghai 200094, China)

Abstract

Wind power utilization is attracting worldwide attention in the renewable energy field, and as wind power develops from land to sea, the size of the blades is becoming incredibly larger. The fatigue test, especially the biaxial synchronous fatigue test for the blades, is becoming an indispensable step to ensure the blade’s quality before mass production, which means the biaxial independent test presently used may have difficulty reproducing the real damage for large-sized blades that oscillate simultaneously in flap-wise and edgewise directions in service conditions. The main point of the fatigue test is to carry out accelerated and reinforced oscillations on blades in the experimental plan. The target moments of critical blade sections are reached or not during the test are treated as one significant evaluation criterion. For independent tests, it is not hard to realize moment matching using additional masses fixed on certain critical blade sections, which may be not easy to put into effect for biaxial synchronous tests, since the mechanical properties and target moments in the flap-wise and edgewise directions are widely varied. To realize the mechanical decoupling for loading force or additional mass inertia force in two directions is becoming one of the key issues for blade biaxial synchronous fatigue testing. For this problem, the present paper proposed one mechanical decoupling design concept after a related literature review. After that, the blade moment design and target matching approach are also proposed, using the Transfer Matrix Method (TMM) for moment quick calculation and Particle Swarm Optimization (PSO) for case optimization.

Suggested Citation

  • Liang Lu & Minyan Zhu & Haijun Wu & Jianzhong Wu, 2022. "A Review and Case Analysis on Biaxial Synchronous Loading Technology and Fast Moment-Matching Methods for Fatigue Tests of Wind Turbine Blades," Energies, MDPI, vol. 15(13), pages 1-34, July.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:13:p:4881-:d:854693
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    References listed on IDEAS

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    1. Toft, Henrik Stensgaard & Svenningsen, Lasse & Sørensen, John Dalsgaard & Moser, Wolfgang & Thøgersen, Morten Lybech, 2016. "Uncertainty in wind climate parameters and their influence on wind turbine fatigue loads," Renewable Energy, Elsevier, vol. 90(C), pages 352-361.
    2. Marino, Enzo & Giusti, Alessandro & Manuel, Lance, 2017. "Offshore wind turbine fatigue loads: The influence of alternative wave modeling for different turbulent and mean winds," Renewable Energy, Elsevier, vol. 102(PA), pages 157-169.
    3. Xin Cai & Jie Zhu & Pan Pan & Rongrong Gu, 2012. "Structural Optimization Design of Horizontal-Axis Wind Turbine Blades Using a Particle Swarm Optimization Algorithm and Finite Element Method," Energies, MDPI, vol. 5(11), pages 1-14, November.
    4. Liao, C.C. & Zhao, X.L. & Xu, J.Z., 2012. "Blade layers optimization of wind turbines using FAST and improved PSO Algorithm," Renewable Energy, Elsevier, vol. 42(C), pages 227-233.
    5. Lu, Liang & Wu, Haijun & Wu, Jianzhong, 2021. "A case study for the optimization of moment-matching in wind turbine blade fatigue tests with a resonant type exciting approach," Renewable Energy, Elsevier, vol. 174(C), pages 769-785.
    6. Jang, Yun Jung & Choi, Chan Woong & Lee, Jang Ho & Kang, Ki Weon, 2015. "Development of fatigue life prediction method and effect of 10-minute mean wind speed distribution on fatigue life of small wind turbine composite blade," Renewable Energy, Elsevier, vol. 79(C), pages 187-198.
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    Cited by:

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