Digital twin modeling for predictive maintenance of gearboxes in floating offshore wind turbine drivetrains; [Modellierung eines digitalen Zwillings zur vorausschauenden Wartung von Getrieben in Antriebssträngen schwimmender Offshore-Windkraftanlagen]

被引:0
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作者
Moghadam F.K. [1 ]
Rebouças G.F.S. [1 ]
Nejad A.R. [1 ]
机构
[1] Norwegian University of Science and Technology, Trondheim
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D O I
10.1007/s10010-021-00468-9
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摘要
This paper presents a multi-degree of freedom torsional model of drivetrain system as the digital twin model for monitoring the remaining useful lifetime of the drivetrain components. An algorithm is proposed for the model identification, which receives the torsional response and estimated values of rotor and generator torques, and calculates the drivetrain dynamic properties, e.g. eigenvalues, and torsional model parameters. The applications of this model in prediction of gearbox remaining useful lifetime is discussed. The proposed method is computationally fast, and can be implemented by integrating with the current turbine control and monitoring system without a need for a new system and sensors installation. A test case, using 5 MW reference drivetrain, has been demonstrated. © 2021, The Author(s).
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页码:273 / 286
页数:13
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  • [1] Digital twin modeling for predictive maintenance of gearboxes in floating offshore wind turbine drivetrains
    Moghadam, Farid K.
    Reboucas, Geraldo F. de S.
    Nejad, Amir R.
    FORSCHUNG IM INGENIEURWESEN-ENGINEERING RESEARCH, 2021, 85 (02): : 273 - 286