scispace - formally typeset
F

Farid Khazaeli Moghadam

Researcher at Norwegian University of Science and Technology

Publications -  11
Citations -  186

Farid Khazaeli Moghadam is an academic researcher from Norwegian University of Science and Technology. The author has contributed to research in topics: Drivetrain & Turbine. The author has an hindex of 5, co-authored 9 publications receiving 51 citations. Previous affiliations of Farid Khazaeli Moghadam include University of Georgia.

Papers
More filters
Journal ArticleDOI

Online condition monitoring of floating wind turbines drivetrain by means of digital twin

TL;DR: The stochastic degradation model proposed for estimation of real-time fatigue damage in the components is based on a proven model-based approach which is tested under different drivetrain operations, namely normal, faulty and overload conditions.
Journal ArticleDOI

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

TL;DR: A torsional model of drivetrain system as the digital twin model for monitoring the remaining useful lifetime of the drivetrain components, which can be implemented by integrating with the current turbine control and monitoring system without a need for a new system and sensors installation.
Journal ArticleDOI

Evaluation of PMSG-based drivetrain technologies for 10-MW floating offshore wind turbines: Pros and cons in a life cycle perspective

TL;DR: MoMoghadam et al. as mentioned in this paper presented an in depth evaluation and comparison of three different drivetrain choices based on permanent-magnet synchronous generator (PMSG) technology for 10MW offshore wind turbines.
Journal ArticleDOI

Theoretical and experimental study of wind turbine drivetrain fault diagnosis by using torsional vibrations and modal estimation

TL;DR: Local sensitive analysis shows that abnormal deviations in stiffness and moment of inertia due to the presence of faults result in considerable changes in natural frequencies and modal responses which can be measured and used as fault detecting features by using the proposed analytical approach.