Digital twin modeling for predictive maintenance of gearboxes in floating offshore wind turbine drivetrains

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.

Automated summary

This paper introduces a multi-degree of freedom torsional model for monitoring the remaining useful lifetime of drivetrain components, particularly in predicting gearbox lifetime. The proposed method is computationally efficient and can be easily integrated with existing turbine control and monitoring systems without the need for additional installation of new systems and sensors.