Fault detection of a benchmark wind turbine using interval analysis

Seyed Mojtaba Tabatabaeipour, Peter Fogh Odgaard, Thomas Bak

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11 Citationer (Scopus)
866 Downloads (Pure)

Abstrakt

This paper investigates a state estimation set- membership approach for fault detection of a benchmark wind turbine. The main challenges in the benchmark are high noise on the wind speed measurement and the nonlinearities in the aerodynamic torque such that the overall model of the turbine is nonlinear. We use an effective wind speed estimator to estimate the effective wind speed and then using interval analysis and monotonicity of the aerodynamic torque with respect to the effective wind speed, we can apply the method to the nonlinear system. The fault detection algorithm checks the consistency of the measurement with a closed set that is computed based on the past measurements and a model of the system. If the measurement is not consistent with this set, a fault is detected. The result demonstrates effectiveness of the method for fault detection of the benchmark wind turbine.
OriginalsprogEngelsk
Titel2012 American Control Conference (ACC)
Antal sider6
Publikationsdato27 jun. 2012
Sider4387-4392
ISBN (Trykt)978-1-4577-1095-7
ISBN (Elektronisk)978-1-4673-2102-0
StatusUdgivet - 27 jun. 2012
Begivenhed2012 American Control Conference - Montreal, Canada
Varighed: 27 jun. 201229 jun. 2012

Konference

Konference2012 American Control Conference
LandCanada
ByMontreal
Periode27/06/201229/06/2012
NavnAmerican Control Conference
ISSN0743-1619

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  • Citationsformater

    Tabatabaeipour, S. M., Odgaard, P. F., & Bak, T. (2012). Fault detection of a benchmark wind turbine using interval analysis. I 2012 American Control Conference (ACC) (s. 4387-4392). American Control Conference http://ieeexplore.ieee.org/xpl/articleDetails.jsp?reload=true&arnumber=6315162