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Condition Maintenance Decision of Wind Turbine Gearbox Based on Stochastic Differential Equation

Author

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  • Hongsheng Su

    (School of Automation and Electrical Engineering, Lanzhou Jiaotong University, Lanzhou 730070, China
    Rail Transit Electrical Automation Engineering Laboratory of Gansu Province, Lanzhou Jiaotong University, Lanzhou 730070, China)

  • Dantong Wang

    (School of Automation and Electrical Engineering, Lanzhou Jiaotong University, Lanzhou 730070, China
    Rail Transit Electrical Automation Engineering Laboratory of Gansu Province, Lanzhou Jiaotong University, Lanzhou 730070, China)

  • Xuping Duan

    (School of Automation and Electrical Engineering, Lanzhou Jiaotong University, Lanzhou 730070, China)

Abstract

Maintenance decision analysis is necessary to ensure the safe and stable operation of wind turbine equipment. To address gearboxes with a high failure rate in wind turbines, this paper establishes a new stochastic differential equation model of gearbox state transition to maximize the utilization of gearboxes. This model divides the state of the gearbox into two parts: internal degradation and external random interference. Weibull distribution and polynomial approximation were used to construct the internal degradation model of the gearbox. The external random interference is simulated by Brownian motion. On the basis of the analysis of monitoring data, the parameters of the gearbox state model were solved using the Newton–Raphson iterative method and entropy method. The state change of the gearbox was simulated in MATLAB, and the residual value between the predicted state and the real state was calculated. Compared with the state transformation model constructed by the traditional ordinary differential equation and the gamma distribution, the Weibull polynomial approximation stochastic model can better reflect the state of the device. With reliability set as the decision goal, the maintenance time of the gearbox is predicted, and the validity of the model is verified through case analysis.

Suggested Citation

  • Hongsheng Su & Dantong Wang & Xuping Duan, 2020. "Condition Maintenance Decision of Wind Turbine Gearbox Based on Stochastic Differential Equation," Energies, MDPI, vol. 13(17), pages 1-13, August.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:17:p:4480-:d:406545
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    References listed on IDEAS

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    1. 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.
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    Cited by:

    1. Sabarathinam Srinivasan & Suresh Kumarasamy & Zacharias E. Andreadakis & Pedro G. Lind, 2023. "Artificial Intelligence and Mathematical Models of Power Grids Driven by Renewable Energy Sources: A Survey," Energies, MDPI, vol. 16(14), pages 1-56, July.
    2. Sunoh Kim & Jin Hur, 2020. "A Probabilistic Modeling Based on Monte Carlo Simulation of Wind Powered EV Charging Stations for Steady-States Security Analysis," Energies, MDPI, vol. 13(20), pages 1-13, October.
    3. Hongsheng Su & Yifan Zhao & Xueqian Wang, 2023. "Analysis of a State Degradation Model and Preventive Maintenance Strategies for Wind Turbine Generators Based on Stochastic Differential Equations," Mathematics, MDPI, vol. 11(12), pages 1-20, June.

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