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

Farid K. Moghadam, Geraldo F. de S. Rebouças, Amir R. Nejad

2021Forschung im Ingenieurwesen82 citationsDOIOpen Access PDF

Abstract

Abstract 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.

Topics & Concepts

DrivetrainTurbineRotor (electric)EngineeringAutomotive engineeringTorqueControl theory (sociology)Modular designStatorControl engineeringComputer scienceControl (management)Mechanical engineeringThermodynamicsPhysicsOperating systemArtificial intelligenceGear and Bearing Dynamics AnalysisMachine Fault Diagnosis TechniquesHydraulic and Pneumatic Systems
Digital twin modeling for predictive maintenance of gearboxes in floating offshore wind turbine drivetrains | Litcius