IDEAS home Printed from https://ideas.repec.org/a/eee/renene/v78y2015icp60-67.html
   My bibliography  Save this article

Dynamic response analysis on torsional vibrations of wind turbine geared transmission system with uncertainty

Author

Listed:
  • Wei, Sha
  • Zhao, Jingshan
  • Han, Qinkai
  • Chu, Fulei

Abstract

Gearbox transmission system is the major part of the wind turbine drive train. Due to the manufacturing and assembling errors, lubrication condition, wear and uncertainties in material and geometric properties, the system parameters, including mesh stiffness, transmission error and damping of the meshing gears are always uncertain. For a more reasonable evaluation of dynamic characteristics of the gearbox transmission system, the influence of the uncertain parameters should be taken into consideration. Based on the Chebyshev interval method (CIM), the dynamic responses of a geared transmission system with uncertain parameters are thus investigated in this paper. A torsional vibration model is derived for a geared system, in which some parameters including the mesh stiffness, the transmission error, the mesh damping, the shaft damping, the moment of inertia of the input blades and the torsional stiffness of the driving coupling shaft are considered as uncertain but bounded parameters. Interval dynamic equations of the geared system are solved by use of the CIM in combination with the variable-step Runge-Kutta numerical integration method. The accuracy of the CIM is demonstrated in comparison with the Monte Carlo (MC) simulation. Variations of the upper and lower bounds of the dynamic mesh force with input speed are obtained. The effects of those uncertain parameters on the frequency response of the dynamic mesh force are discussed in detail. It is shown that small parameter uncertainties might be propagated in the vibration system and lead to relatively large uncertainties of the dynamic response of system. The result is of significance for the design and condition monitoring of wind turbine drive trains.

Suggested Citation

  • Wei, Sha & Zhao, Jingshan & Han, Qinkai & Chu, Fulei, 2015. "Dynamic response analysis on torsional vibrations of wind turbine geared transmission system with uncertainty," Renewable Energy, Elsevier, vol. 78(C), pages 60-67.
    • Handle: RePEc:eee:renene:v:78:y:2015:i:c:p:60-67
    DOI: 10.1016/j.renene.2014.12.062
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0960148114009008
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.renene.2014.12.062?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Zhu, Caichao & Xu, Xiangyang & Liu, Huaiju & Luo, Tianhong & Zhai, Hongfei, 2014. "Research on dynamical characteristics of wind turbine gearboxes with flexible pins," Renewable Energy, Elsevier, vol. 68(C), pages 724-732.
    2. Rahimi, Mohsen & Parniani, Mostafa, 2009. "Dynamic behavior and transient stability analysis of fixed speed wind turbines," Renewable Energy, Elsevier, vol. 34(12), pages 2613-2624.
    3. Helsen, Jan & Vanhollebeke, Frederik & Marrant, Ben & Vandepitte, Dirk & Desmet, Wim, 2011. "Multibody modelling of varying complexity for modal behaviour analysis of wind turbine gearboxes," Renewable Energy, Elsevier, vol. 36(11), pages 3098-3113.
    4. Hameed, Z. & Hong, Y.S. & Cho, Y.M. & Ahn, S.H. & Song, C.K., 2009. "Condition monitoring and fault detection of wind turbines and related algorithms: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 13(1), pages 1-39, January.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Liu, Hongwei & Zhang, Pengpeng & Gu, Yajing & Shu, Yongdong & Song, Jiajun & Lin, Yonggang & Li, Wei, 2022. "Dynamics analysis of the power train of 650 kW horizontal-axis tidal current turbine," Renewable Energy, Elsevier, vol. 194(C), pages 51-67.
    2. de Bessa, Iury Valente & Palhares, Reinaldo Martinez & D'Angelo, Marcos Flávio Silveira Vasconcelos & Chaves Filho, João Edgar, 2016. "Data-driven fault detection and isolation scheme for a wind turbine benchmark," Renewable Energy, Elsevier, vol. 87(P1), pages 634-645.
    3. Liu, Wenyi, 2016. "Design and kinetic analysis of wind turbine blade-hub-tower coupled system," Renewable Energy, Elsevier, vol. 94(C), pages 547-557.
    4. Liu, Xianzeng & Yang, Yuhu & Zhang, Jun, 2018. "Resultant vibration signal model based fault diagnosis of a single stage planetary gear train with an incipient tooth crack on the sun gear," Renewable Energy, Elsevier, vol. 122(C), pages 65-79.
    5. W. Dheelibun Remigius & Anand Natarajan, 2022. "A review of wind turbine drivetrain loads and load effects for fixed and floating wind turbines," Wiley Interdisciplinary Reviews: Energy and Environment, Wiley Blackwell, vol. 11(1), January.
    6. Zhiyu Jiang & Weifei Hu & Wenbin Dong & Zhen Gao & Zhengru Ren, 2017. "Structural Reliability Analysis of Wind Turbines: A Review," Energies, MDPI, vol. 10(12), pages 1-25, December.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Guerine, A. & El Hami, A. & Walha, L. & Fakhfakh, T. & Haddar, M., 2017. "Dynamic response of wind turbine gear system with uncertain-but-bounded parameters using interval analysis method," Renewable Energy, Elsevier, vol. 113(C), pages 679-687.
    2. Liu, Hongwei & Zhang, Pengpeng & Gu, Yajing & Shu, Yongdong & Song, Jiajun & Lin, Yonggang & Li, Wei, 2022. "Dynamics analysis of the power train of 650 kW horizontal-axis tidal current turbine," Renewable Energy, Elsevier, vol. 194(C), pages 51-67.
    3. W. Dheelibun Remigius & Anand Natarajan, 2022. "A review of wind turbine drivetrain loads and load effects for fixed and floating wind turbines," Wiley Interdisciplinary Reviews: Energy and Environment, Wiley Blackwell, vol. 11(1), January.
    4. He, Guolin & Ding, Kang & Wu, Xiaomeng & Yang, Xiaoqing, 2019. "Dynamics modeling and vibration modulation signal analysis of wind turbine planetary gearbox with a floating sun gear," Renewable Energy, Elsevier, vol. 139(C), pages 718-729.
    5. Liu, Xianzeng & Yang, Yuhu & Zhang, Jun, 2018. "Resultant vibration signal model based fault diagnosis of a single stage planetary gear train with an incipient tooth crack on the sun gear," Renewable Energy, Elsevier, vol. 122(C), pages 65-79.
    6. Fan, Zhixin & Zhu, Caichao, 2019. "The optimization and the application for the wind turbine power-wind speed curve," Renewable Energy, Elsevier, vol. 140(C), pages 52-61.
    7. Beganovic, Nejra & Söffker, Dirk, 2016. "Structural health management utilization for lifetime prognosis and advanced control strategy deployment of wind turbines: An overview and outlook concerning actual methods, tools, and obtained result," Renewable and Sustainable Energy Reviews, Elsevier, vol. 64(C), pages 68-83.
    8. Habibi, Hamed & Howard, Ian & Simani, Silvio, 2019. "Reliability improvement of wind turbine power generation using model-based fault detection and fault tolerant control: A review," Renewable Energy, Elsevier, vol. 135(C), pages 877-896.
    9. Wang, Shuaishuai & Nejad, Amir R. & Bachynski, Erin E. & Moan, Torgeir, 2020. "Effects of bedplate flexibility on drivetrain dynamics: Case study of a 10 MW spar type floating wind turbine," Renewable Energy, Elsevier, vol. 161(C), pages 808-824.
    10. Xueli An & Dongxiang Jiang, 2014. "Bearing fault diagnosis of wind turbine based on intrinsic time-scale decomposition frequency spectrum," Journal of Risk and Reliability, , vol. 228(6), pages 558-566, December.
    11. Le Zhang & Qiang Yang, 2020. "Investigation of the Design and Fault Prediction Method for an Abrasive Particle Sensor Used in Wind Turbine Gearbox," Energies, MDPI, vol. 13(2), pages 1-13, January.
    12. Ding Zhai & Anyang Lu & Jinghao Li & Qingling Zhang, 2016. "Fault detection for singular switched linear systems with multiple time-varying delay in finite frequency domain," International Journal of Systems Science, Taylor & Francis Journals, vol. 47(13), pages 3232-3257, October.
    13. Jin, Xin & Ju, Wenbin & Zhang, Zhaolong & Guo, Lianxin & Yang, Xiangang, 2016. "System safety analysis of large wind turbines," Renewable and Sustainable Energy Reviews, Elsevier, vol. 56(C), pages 1293-1307.
    14. Ruiz de la Hermosa González-Carrato, Raúl & García Márquez, Fausto Pedro & Dimlaye, Vichaar, 2015. "Maintenance management of wind turbines structures via MFCs and wavelet transforms," Renewable and Sustainable Energy Reviews, Elsevier, vol. 48(C), pages 472-482.
    15. Sellak, Hamza & Ouhbi, Brahim & Frikh, Bouchra & Palomares, Iván, 2017. "Towards next-generation energy planning decision-making: An expert-based framework for intelligent decision support," Renewable and Sustainable Energy Reviews, Elsevier, vol. 80(C), pages 1544-1577.
    16. Quan Zhou & Taotao Xiong & Mubin Wang & Chenmeng Xiang & Qingpeng Xu, 2017. "Diagnosis and Early Warning of Wind Turbine Faults Based on Cluster Analysis Theory and Modified ANFIS," Energies, MDPI, vol. 10(7), pages 1-15, July.
    17. Moynihan, Bridget & Moaveni, Babak & Liberatore, Sauro & Hines, Eric, 2022. "Estimation of blade forces in wind turbines using blade root strain measurements with OpenFAST verification," Renewable Energy, Elsevier, vol. 184(C), pages 662-676.
    18. Yang, Wenxian & Court, Richard & Jiang, Jiesheng, 2013. "Wind turbine condition monitoring by the approach of SCADA data analysis," Renewable Energy, Elsevier, vol. 53(C), pages 365-376.
    19. Taylor, Josh A. & Dhople, Sairaj V. & Callaway, Duncan S., 2016. "Power systems without fuel," Renewable and Sustainable Energy Reviews, Elsevier, vol. 57(C), pages 1322-1336.
    20. Peng Guo & Nan Bai, 2011. "Wind Turbine Gearbox Condition Monitoring with AAKR and Moving Window Statistic Methods," Energies, MDPI, vol. 4(11), pages 1-17, November.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:renene:v:78:y:2015:i:c:p:60-67. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/renewable-energy .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.