Detecting faults in wind turbines
Abstract
A wind turbine generator fault detection method is described. The method includes obtaining a first signal from a generator of a wind turbine and a second signal from a vibration sensor coupled to the wind turbine, the first signal representing an output current of the generator, and the second signal being a time-sampled signal representing vibrations of a bearing in the wind turbine. Determining a shaft rotation frequency signal from the first signal, the shaft rotation frequency signal representing a time-varying rotational speed of a shaft of the wind turbine. Resampling an envelope of the second signal based on the shaft rotation frequency signal to provide a third signal, the third signal being an angular sampled signal. Detecting, by the at least one processor, a fault in the bearing of the wind turbine by identifying a characteristic signature of a bearing fault in the third signal.
- Inventors:
- Issue Date:
- Research Org.:
- NUtech Ventures, Lincoln, NE (United States)
- Sponsoring Org.:
- USDOE
- OSTI Identifier:
- 1771687
- Patent Number(s):
- 10852214
- Application Number:
- 15/985,226
- Assignee:
- NUtech Ventures (Lincoln, NE)
- Patent Classifications (CPCs):
-
F - MECHANICAL ENGINEERING F03 - MACHINES OR ENGINES FOR LIQUIDS F03D - WIND MOTORS
F - MECHANICAL ENGINEERING F05 - INDEXING SCHEMES RELATING TO ENGINES OR PUMPS IN VARIOUS SUBCLASSES OF CLASSES F01-F04 F05B - INDEXING SCHEME RELATING TO MACHINES OR ENGINES OTHER THAN NON-POSITIVE-DISPLACEMENT MACHINES OR ENGINES, TO WIND MOTORS, TO NON-POSITIVE DISPLACEMENT PUMPS, AND TO GENERATING COMBUSTION PRODUCTS OF HIGH PRESSURE OR HIGH VELOCITY
- DOE Contract Number:
- EE0006802
- Resource Type:
- Patent
- Resource Relation:
- Patent File Date: 05/21/2018
- Country of Publication:
- United States
- Language:
- English
Citation Formats
Qiao, Wei, Wang, Jun, and Qu, Liyan. Detecting faults in wind turbines. United States: N. p., 2020.
Web.
Qiao, Wei, Wang, Jun, & Qu, Liyan. Detecting faults in wind turbines. United States.
Qiao, Wei, Wang, Jun, and Qu, Liyan. Tue .
"Detecting faults in wind turbines". United States. https://www.osti.gov/servlets/purl/1771687.
@article{osti_1771687,
title = {Detecting faults in wind turbines},
author = {Qiao, Wei and Wang, Jun and Qu, Liyan},
abstractNote = {A wind turbine generator fault detection method is described. The method includes obtaining a first signal from a generator of a wind turbine and a second signal from a vibration sensor coupled to the wind turbine, the first signal representing an output current of the generator, and the second signal being a time-sampled signal representing vibrations of a bearing in the wind turbine. Determining a shaft rotation frequency signal from the first signal, the shaft rotation frequency signal representing a time-varying rotational speed of a shaft of the wind turbine. Resampling an envelope of the second signal based on the shaft rotation frequency signal to provide a third signal, the third signal being an angular sampled signal. Detecting, by the at least one processor, a fault in the bearing of the wind turbine by identifying a characteristic signature of a bearing fault in the third signal.},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = {2020},
month = {12}
}
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