A Prognostic Method for Fault Detection in Wind Turbine Drivetrains

Amir R. Nejada, Peter Fogh Odgaard, Zhen Gao, Torgeir Moan

Publikation: Bidrag til tidsskriftTidsskriftartikelForskningpeer review

38 Citationer (Scopus)

Resumé

In this paper, a prognostic method is presented for fault detection in gears and bearings in wind turbine drivetrains. This method is based on angular velocity measurements from the gearbox input shaft and the output to the generator, using two additional angular velocity sensors on the intermediate shafts inside the gearbox. An angular velocity error function is defined and compared in the faulty and fault-free conditions in frequency domain. Faults can be detected from the change in the energy level of the frequency spectrum of an error function. The method is demonstrated by detecting bearing faults in three locations: the high-speed shaft stage, the planetary stage and the intermediate-speed shaft stage. Simulations of the faulty and fault-free cases are performed on a gearbox model implemented in multibody dynamic simulation software. The global loads on the gearbox are obtained from a dynamometer test bench and applied to the numerical gearbox model. The method is exemplified using a 750 kW wind turbine gearbox. The case study results show that defects in the high- and intermediate-speed bearings can be detected using this method. It is shown that this procedure is relatively simple, yet accurate enough for early fault detection in wind turbine gearboxes.
OriginalsprogEngelsk
TidsskriftEngineering Failure Analysis
Vol/bind42
Sider (fra-til)324-336
ISSN1350-6307
DOI
StatusUdgivet - jul. 2014

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Bearings (structural)
Angular velocity
Fault detection
Wind turbines
Dynamometers
Angle measurement
Velocity measurement
Electron energy levels
Gears
Numerical models
Defects
Sensors
Computer simulation

Citer dette

Nejada, Amir R. ; Odgaard, Peter Fogh ; Gao, Zhen ; Moan, Torgeir. / A Prognostic Method for Fault Detection in Wind Turbine Drivetrains. I: Engineering Failure Analysis. 2014 ; Bind 42. s. 324-336.
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title = "A Prognostic Method for Fault Detection in Wind Turbine Drivetrains",
abstract = "In this paper, a prognostic method is presented for fault detection in gears and bearings in wind turbine drivetrains. This method is based on angular velocity measurements from the gearbox input shaft and the output to the generator, using two additional angular velocity sensors on the intermediate shafts inside the gearbox. An angular velocity error function is defined and compared in the faulty and fault-free conditions in frequency domain. Faults can be detected from the change in the energy level of the frequency spectrum of an error function. The method is demonstrated by detecting bearing faults in three locations: the high-speed shaft stage, the planetary stage and the intermediate-speed shaft stage. Simulations of the faulty and fault-free cases are performed on a gearbox model implemented in multibody dynamic simulation software. The global loads on the gearbox are obtained from a dynamometer test bench and applied to the numerical gearbox model. The method is exemplified using a 750 kW wind turbine gearbox. The case study results show that defects in the high- and intermediate-speed bearings can be detected using this method. It is shown that this procedure is relatively simple, yet accurate enough for early fault detection in wind turbine gearboxes.",
keywords = "Wind turbine gearbox; Condition monitoring; Fault detection; Drivetrain",
author = "Nejada, {Amir R.} and Odgaard, {Peter Fogh} and Zhen Gao and Torgeir Moan",
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A Prognostic Method for Fault Detection in Wind Turbine Drivetrains. / Nejada, Amir R.; Odgaard, Peter Fogh; Gao, Zhen; Moan, Torgeir.

I: Engineering Failure Analysis, Bind 42, 07.2014, s. 324-336.

Publikation: Bidrag til tidsskriftTidsskriftartikelForskningpeer review

TY - JOUR

T1 - A Prognostic Method for Fault Detection in Wind Turbine Drivetrains

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AU - Odgaard, Peter Fogh

AU - Gao, Zhen

AU - Moan, Torgeir

PY - 2014/7

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N2 - In this paper, a prognostic method is presented for fault detection in gears and bearings in wind turbine drivetrains. This method is based on angular velocity measurements from the gearbox input shaft and the output to the generator, using two additional angular velocity sensors on the intermediate shafts inside the gearbox. An angular velocity error function is defined and compared in the faulty and fault-free conditions in frequency domain. Faults can be detected from the change in the energy level of the frequency spectrum of an error function. The method is demonstrated by detecting bearing faults in three locations: the high-speed shaft stage, the planetary stage and the intermediate-speed shaft stage. Simulations of the faulty and fault-free cases are performed on a gearbox model implemented in multibody dynamic simulation software. The global loads on the gearbox are obtained from a dynamometer test bench and applied to the numerical gearbox model. The method is exemplified using a 750 kW wind turbine gearbox. The case study results show that defects in the high- and intermediate-speed bearings can be detected using this method. It is shown that this procedure is relatively simple, yet accurate enough for early fault detection in wind turbine gearboxes.

AB - In this paper, a prognostic method is presented for fault detection in gears and bearings in wind turbine drivetrains. This method is based on angular velocity measurements from the gearbox input shaft and the output to the generator, using two additional angular velocity sensors on the intermediate shafts inside the gearbox. An angular velocity error function is defined and compared in the faulty and fault-free conditions in frequency domain. Faults can be detected from the change in the energy level of the frequency spectrum of an error function. The method is demonstrated by detecting bearing faults in three locations: the high-speed shaft stage, the planetary stage and the intermediate-speed shaft stage. Simulations of the faulty and fault-free cases are performed on a gearbox model implemented in multibody dynamic simulation software. The global loads on the gearbox are obtained from a dynamometer test bench and applied to the numerical gearbox model. The method is exemplified using a 750 kW wind turbine gearbox. The case study results show that defects in the high- and intermediate-speed bearings can be detected using this method. It is shown that this procedure is relatively simple, yet accurate enough for early fault detection in wind turbine gearboxes.

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