A CBA-KELM-Based Recognition Method for Fault Diagnosis of Wind Turbines with Time-Domain Analysis and Multisensor Data Fusion
Fault diagnosis technology (FDT) is an effective tool to ensure stability and reliable operation in wind turbines. In this paper, a novel fault diagnosis methodology based on a cloud bat algorithm (CBA)-kernel extreme learning machines (KELM) approach for wind turbines is proposed via combination of...
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Main Authors: | Xiafei Long, Ping Yang, Hongxia Guo, Zhuoli Zhao, Xiwen Wu |
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Format: | Article |
Language: | English |
Published: |
Wiley
2019-01-01
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Series: | Shock and Vibration |
Online Access: | http://dx.doi.org/10.1155/2019/7490750 |
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