Fault detection and isolation for a wind turbine benchmark using a mixed Bayesian/Set-membership approach-Reference-Cited by-同舟云学术

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Fault detection and isolation for a wind turbine benchmark using a mixed Bayesian/Set-membership approach

Published:2015 Issue: Volume:40 Page:59-69
ISSN:1367-5788
Container-title:Annual Reviews in Control
language:en
Short-container-title:Annual Reviews in Control

Author:

Fernandez-Canti Rosa M.,Blesa Joaquim,Tornil-Sin Sebastian,Puig Vicenç

Publisher

Elsevier BV

Subject

Control and Systems Engineering,Software

Reference38 articles.

1. Detection of abrupt changes: Theory and applications;Basseville,1993

2. Diagnosis and fault-tolerant control;Blanke,2006

3. Satool: a software tool for structural analysis of complex automation systems;Blanke,2006

4. Fault diagnosis of wind turbines using a set-membership approach.;Blesa,2011

5. FDI and FTC of wind turbines using the interval observer approach and virtual actuators/sensors;Blesa;Control Engineering Practice,2014

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1. Condition Monitoring Using Digital Fault-Detection Approach for Pitch System in Wind Turbines;Energies;2024-08-13

2. Fault Diagnosis using Interval Data-driven LPV Observers and Structural Analysis;IFAC-PapersOnLine;2024

3. A Multi-Adversarial Joint Distribution Adaptation Method for Bearing Fault Diagnosis under Variable Working Conditions;Applied Sciences;2023-09-23

4. Robust intelligent fault diagnosis strategy using Kalman observers and neuro-fuzzy systems for a wind turbine benchmark;Renewable Energy;2023-03

5. A Survey of Machine Learning Applications in Renewable Energy Sources;IETE Journal of Research;2022-11-15

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