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Mass and Aerodynamic Imbalance Estimates of Wind Turbines

Author

Listed:
  • Jenny Niebsch

    (Johann Radon Institute, Austrian Academy of Science, Altenbergerstr. 69, 4040 Linz, Austria)

  • Ronny Ramlau

    (Institute for Industrial Mathematics, Johannes Kepler University, Altenbergerstr. 69, 4040 Linz, Austria)

  • Thien T. Nguyen

    (Institute for Applied Geometry, Johannes Kepler University, Altenbergerstr. 69, 4040 Linz, Austria)

Abstract

Due to its effect on the operation time of wind turbines, rotor imbalances of a wind turbine have to be detected early enough. We present a method that determines inhomogeneous mass distributions of the rotor as well as deviations in the pitch angles of the rotor blades from vibrational data only. To this end, a mathematical model connecting the load caused by the imbalances to the resulting vibrations was developed. After discretization, the resulting vibration equation was solved analytically. The inverse problem, i.e. , the calculation of the mass and aerodynamic imbalance from vibrational data, was solved by using nonlinear regularization theory. Numerical simulations were performed using artificial vibration data.

Suggested Citation

  • Jenny Niebsch & Ronny Ramlau & Thien T. Nguyen, 2010. "Mass and Aerodynamic Imbalance Estimates of Wind Turbines," Energies, MDPI, vol. 3(4), pages 1-15, April.
    • Handle: RePEc:gam:jeners:v:3:y:2010:i:4:p:696-710:d:7834
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    Citations

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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. Francesco Mazzeo & Derek Micheletto & Alessandro Talamelli & Antonio Segalini, 2022. "An Experimental Study on a Wind Turbine Rotor Affected by Pitch Imbalance," Energies, MDPI, vol. 15(22), pages 1-16, November.
    3. Ren, Zhengru & Verma, Amrit Shankar & Li, Ye & Teuwen, Julie J.E. & Jiang, Zhiyu, 2021. "Offshore wind turbine operations and maintenance: A state-of-the-art review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 144(C).
    4. Davide Astolfi & Ravi Pandit & Linyue Gao & Jiarong Hong, 2022. "Individuation of Wind Turbine Systematic Yaw Error through SCADA Data," Energies, MDPI, vol. 15(21), pages 1-5, November.
    5. Xing, Zuoxia & Chen, Mingyang & Cui, Jia & Chen, Zhe & Xu, Jian, 2022. "Detection of magnitude and position of rotor aerodynamic imbalance of wind turbines using Convolutional Neural Network," Renewable Energy, Elsevier, vol. 197(C), pages 1020-1033.
    6. Bon-Yong Koo & Dae-Yi Jung, 2019. "A Comparative Study on Primary Bearing Rating Life of a 5-MW Two-Blade Wind Turbine System Based on Two Different Control Domains," Energies, MDPI, vol. 12(13), pages 1-16, July.
    7. Pinjia Zhang & Delong Lu, 2019. "A Survey of Condition Monitoring and Fault Diagnosis toward Integrated O&M for Wind Turbines," Energies, MDPI, vol. 12(14), pages 1-22, July.
    8. Lin, Kun & Xiao, Shaohui & Zhou, Annan & Liu, Hongjun, 2020. "Experimental study on long-term performance of monopile-supported wind turbines (MWTs) in sand by using wind tunnel," Renewable Energy, Elsevier, vol. 159(C), pages 1199-1214.
    9. Xiaoling Sheng & Shuting Wan & Kanru Cheng & Xuan Wang, 2020. "Research on the Fault Characteristic of Wind Turbine Generator System Considering the Spatiotemporal Distribution of the Actual Wind Speed," Energies, MDPI, vol. 13(2), pages 1-16, January.
    10. Maria Martinez Luengo & Athanasios Kolios, 2015. "Failure Mode Identification and End of Life Scenarios of Offshore Wind Turbines: A Review," Energies, MDPI, vol. 8(8), pages 1-16, August.

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