Intelligent wind turbine sensor fault detection on benchmark model using support vector machine
Author:
Publisher
Springer Science and Business Media LLC
Subject
Geometry and Topology,Theoretical Computer Science,Software
Link
https://link.springer.com/content/pdf/10.1007/s00500-023-09064-1.pdf
Reference19 articles.
1. Blanke M, Kinnaert M, Lunze J, Staroswiecki M (2006) Diagnosis and fault tolerant control. Springer, Berlin
2. Ciang CC, Lee JR, Bang HJ (2008) Structural health monitoring for a wind turbine system: a review of damage detection methods. Meas Sci Technol 19(12):122001. https://doi.org/10.1088/0957-0233/19/12/122001
3. Crabtree CJ (2010a) URL http://www.supergen-wind.org.uk/docs/.SurveyofcommerciallyavailableCMSforWT
4. Crabtree CJ (2010b) Survey of commercially available condition monitoring systems for wind turbines
5. Elmaati YA, Bahir LE, Faitah K (2015) Fault detection and isolation in wind turbines three sensor faults case. In: 3rd international renewable and sustainable energy conference (IRSEC), pp 1–6
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