A novel information geometry method for estimating parameters of the Weibull wind speed distribution

Kurban, Mehmet; Dokur, Emrah; Ceyhan, Salim

doi:10.3176/proc.2018.1.01

Cited by 3 publications

(1 citation statement)

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“…A large number of studies have shown that the wind energy curve fitted by the two-parameter Weibull density function is closer to the actual wind speed distribution. 23,24 Therefore, this article uses two-parameter Weibull distribution to simulate the change of local wind speed. The input torque of the wind turbine gearbox is calculated according to the rated parameters of the wind turbine and the external wind speed, and the time-varying wear depth of the gear is studied in combination with the Archard wear model.…”

Section: Wind Turbine Gearbox Wear Modelingmentioning

confidence: 99%

Research on time-varying meshing stiffness of wind turbine gearbox considering tooth surface wear

Mo,

Hu,

Liu

et al. 2023

Proceedings of the Institution of Mechanical Engineers, Part J:

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The time-varying meshing stiffness (TVMS) is an important element of the gear system. In this paper, the TVMS of each gear set of a wind turbine gearbox is calculated based on the principle of potential energy method, where wear is the most likely failure in the operation of a wind turbine gearbox. Therefore, the Archard wear model is brought into it, and theoretically the analytical formula of stiffness considering tooth wear is derived, and the time-varying wear depth is deduced as the natural wind speed keeps changing and the input torque of the wind turbine gearbox keeps changing. The interrelationship between gear tooth wear and meshing pressure angle and number of meshes is studied in depth, and the TVMS of each gear set under wear is calculated using the modified tooth profile model. The results show that the tooth profile wear depth is related to the gear meshing angle, and the tooth profile wear depth becomes larger as the number of meshes increases, thus reducing the TVMS of the wind turbine, and the TVMS shows irregular fluctuations under time-varying wear.

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Section: Wind Turbine Gearbox Wear Modelingmentioning

confidence: 99%