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International Journal of Applied Mathematics and Computer Science
Volume 28 (2018): Issue 2 (June 2018)
Open Access
Data–Driven Techniques for the Fault Diagnosis of a Wind Turbine Benchmark
Silvio Simani
Silvio Simani
,
Saverio Farsoni
Saverio Farsoni
and
Paolo Castaldi
Paolo Castaldi
| Jun 29, 2018
International Journal of Applied Mathematics and Computer Science
Volume 28 (2018): Issue 2 (June 2018)
Advanced Diagnosis and Fault-Tolerant Control Methods (special section, pp. 233-333), Vicenç Puig, Dominique Sauter, Christophe Aubrun, Horst Schulte (Eds.)
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Published Online:
Jun 29, 2018
Page range:
247 - 268
Received:
Mar 15, 2017
Accepted:
Jan 29, 2018
DOI:
https://doi.org/10.2478/amcs-2018-0018
Keywords
fault diagnosis
,
analytical redundancy
,
fuzzy systems
,
neural networks
,
residual generators
,
fault estimation
,
wind turbine benchmark.
© 2018 Silvio Simani, published by Sciendo
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.
Silvio Simani
Department of Engineering University of Ferrara, Via Saragat 1/E, 44124
Ferrara, Italy
Saverio Farsoni
Department of Engineering University of Ferrara, Via Saragat 1/E, 44124
Ferrara, Italy
Paolo Castaldi
Department of Electronics, Computer Science and Systems University of Bologna, Via Fontanelle 40, 47100
Forlì, Italy