Early fault detection in the main bearing of wind turbines based on Gated Recurrent Unit (GRU) neural networks and SCADA data
© 2022 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting /republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to...
| Authors: | , , , , |
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| Format: | article |
| Publication Date: | 2022 |
| Country: | España |
| Institution: | Universitat Politècnica de Catalunya (UPC) |
| Repository: | UPCommons. Portal del coneixement obert de la UPC |
| Language: | English |
| OAI Identifier: | oai:upcommons.upc.edu:2117/371579 |
| Online Access: | https://hdl.handle.net/2117/371579 https://dx.doi.org/10.1109/TMECH.2022.3185675 |
| Access Level: | Open access |
| Keyword: | Wind turbines Anomaly detection Early fault detection Gated recurrent unit (GRU) neural network (NN) Main bear- ing Supervisory control and data acquisition (SCADA) data Wind turbine (WT). Aerogeneradors Àrees temàtiques de la UPC::Informàtica::Automàtica i control |
| Summary: | © 2022 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting /republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works |
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