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Resonance Monitoring of a Horizontal Wind Turbine by Strain-Based Automated Operational Modal Analysis

Author

Listed:
  • Wei-Hua Hu

    (School of Civil and Environmental Engineering, Harbin Institute of Technology (Shenzhen), Shenzhen 518055, China)

  • De-Hui Tang

    (School of Civil and Environmental Engineering, Harbin Institute of Technology (Shenzhen), Shenzhen 518055, China)

  • Ming Wang

    (School of Civil and Environmental Engineering, Harbin Institute of Technology (Shenzhen), Shenzhen 518055, China)

  • Jun-Le Liu

    (School of Civil and Environmental Engineering, Harbin Institute of Technology (Shenzhen), Shenzhen 518055, China)

  • Zuo-Hua Li

    (School of Civil and Environmental Engineering, Harbin Institute of Technology (Shenzhen), Shenzhen 518055, China)

  • Wei Lu

    (School of Civil and Environmental Engineering, Harbin Institute of Technology (Shenzhen), Shenzhen 518055, China)

  • Jun Teng

    (School of Civil and Environmental Engineering, Harbin Institute of Technology (Shenzhen), Shenzhen 518055, China)

  • Samir Said

    (Federal Institute for Materials Research and Testing (BAM), 12205 Berlin, Germany)

  • Rolf. G. Rohrmann

    (Struktur Analyse & Bauwerks Monitoring (SABM) GbR, 10965 Berlin, Germany)

Abstract

A strain-based automated operational modal analysis algorithm is proposed to track the long-term dynamic behavior of a horizontal wind turbine under operational conditions. This algorithm is firstly validated by a scaled wind turbine model, and then it is applied to the dynamic strain responses recorded from a 5 MW wind turbine system. We observed variations in the fundamental frequency and 1f, 3f excitation frequencies due to the mass imbalance of the blades and aerodynamic excitation by the tower dam or tower wake. Inspection of the Campbell diagram revealed that the adverse resonance phenomenon and Sommerfeld effect causing excessive vibrations of the wind tower.

Suggested Citation

  • 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.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:3:p:579-:d:313280
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    References listed on IDEAS

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    1. Wymore, Mathew L. & Van Dam, Jeremy E. & Ceylan, Halil & Qiao, Daji, 2015. "A survey of health monitoring systems for wind turbines," Renewable and Sustainable Energy Reviews, Elsevier, vol. 52(C), pages 976-990.
    2. Liu, Xiong & Lu, Cheng & Liang, Shi & Godbole, Ajit & Chen, Yan, 2017. "Vibration-induced aerodynamic loads on large horizontal axis wind turbine blades," Applied Energy, Elsevier, vol. 185(P2), pages 1109-1119.
    3. Presas, Alexandre & Luo, Yongyao & Wang, Zhengwei & Guo, Bao, 2019. "Fatigue life estimation of Francis turbines based on experimental strain measurements: Review of the actual data and future trends," Renewable and Sustainable Energy Reviews, Elsevier, vol. 102(C), pages 96-110.
    4. García Márquez, Fausto Pedro & Tobias, Andrew Mark & Pinar Pérez, Jesús María & Papaelias, Mayorkinos, 2012. "Condition monitoring of wind turbines: Techniques and methods," Renewable Energy, Elsevier, vol. 46(C), pages 169-178.
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    Cited by:

    1. Jijian Lian & Huan Zhou & Xiaofeng Dong, 2022. "A Theoretical Approach for Resonance Analysis of Wind Turbines under 1P/3P Loads," Energies, MDPI, vol. 15(16), pages 1-15, August.
    2. 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).

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