An engineering condition indicator for condition monitoring of wind turbine bearings
Abstract Condition monitoring (CM) of wind turbine becomes significantly important part of wind farms in order to cut down operation and maintenance costs. The large amount of CM system vibration data collected from wind turbines are posing challenges to operators in signal processing. It is crucial...
| Main Authors: | , , |
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| 格式: | Article |
| 語言: | English |
| 出版: |
Wiley
2020-02-01
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| 叢編: | Wind Energy |
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| 在線閱讀: | https://doi.org/10.1002/we.2423 |
| 總結: | Abstract Condition monitoring (CM) of wind turbine becomes significantly important part of wind farms in order to cut down operation and maintenance costs. The large amount of CM system vibration data collected from wind turbines are posing challenges to operators in signal processing. It is crucial to design sensitive and reliable condition indicator (CI) in wind turbine CM system. Bearing plays an important role in wind turbine because of its high impact on downtime and component replacement. CIs for wind turbine bearing monitoring are reviewed in the paper, and the advantages and disadvantages of these indicators are discussed in detail. A new engineering CI (ECI), which combined the energy and kurtosis representation of the vibration signal, is proposed to meet the requirement of easy applicability and early detection in wind turbine bearing monitoring. The quantitative threshold setting method of the ECI is provided for wind turbine CM practice. The bearing run‐to‐failure experiment data analysis demonstrates that ECI can evaluate the overall condition and is sensitive to incipient fault of bearing. The effectiveness in engineering of ECI is validated though a certain amount of real‐world wind turbine generator and gearbox bearing vibration data. |
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| ISSN: | 1095-4244 1099-1824 |