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Content Provider | IET Digital Library |
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Author | Ferguson, David Donald, Alasdair Mc Carroll, James Lee, Hyunjoo |
Abstract | This study presents a method of anomaly detection within a gearbox by way of standardising temperature data. Assessing measured parameters in isolation is not sufficient to detect faults within a wind turbine. This technique uses temperature, rotational speed, and generator torque to detect a bearing fault within the gearbox. Standardising data allows a parameter to be analysed which also takes into consideration the operating state of the wind turbine, therefore providing a more holistic view of the health of the wind turbine and component being monitored. |
Starting Page | 5147 |
Ending Page | 5151 |
Page Count | 5 |
Volume Number | 2019 |
e-ISSN | 20513305 |
Issue Number | Issue 18, Jul (2019) |
Alternate Webpage(s) | https://digital-library.theiet.org/content/journals/joe/2019/18 |
Alternate Webpage(s) | https://digital-library.theiet.org/content/journals/10.1049/joe.2018.9319 |
Journal | The Journal of Engineering |
Publisher | The Institution of Engineering and Technology |
Publisher Date | 2019-03-15 |
Access Restriction | Open |
Rights License | Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0/) |
Subject Keyword | Anomaly Detection Bearing Fault Condition Monitoring Data Acquisition System Data Analysis Data Handling Technique Digital Signal Processing Fault Diagnosis Fuzzy Reasoning Gearbox Fault Detection Gears Power Engineering Computing Power System Reliability Reliability SCADA System Signal Processing And Detection Signal Reconstruction Standardisation Standardising Data Temperature Data Wind Power Plant Wind Turbine Wind Turbine SCADA Data |
Content Type | Text |
Resource Type | Article |
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