Open AccessSensor and actuator fault diagnosis for wind turbine systems by using robust observer and filter
Author(s) -
Wei X.,
Verhaegen M.
Publication year - 2011
Publication title -
wind energy
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.743
H-Index - 92
eISSN - 1099-1824
pISSN - 1095-4244
DOI - 10.1002/we.438
Subject(s) - control theory (sociology) , observer (physics) , residual , turbine , fault detection and isolation , actuator , fault (geology) , engineering , filter (signal processing) , wind power , blade pitch , computer science , control (management) , algorithm , artificial intelligence , physics , quantum mechanics , seismology , geology , mechanical engineering , electrical engineering
In this paper, we consider sensor and actuator fault detection and estimation issues for large scale wind turbine systems where individual pitch control (IPC) is used for load reduction. The faults considered are the blade root bending moment sensor faults and blade pitch actuator faults. In the first part, with the aid of a dynamical model of the wind turbine system, a so‐called H ∞ / H − observer in the finite frequency range, is applied to generate the residual for fault detection. The observer is designed to be sensitive to faults but insensitive to disturbances, such as wind turbulence. When there is a detectable fault, the observer sends an alarm signal if the residual evaluation is larger than a predefined threshold. In addition to the fault detection, we also consider the fault estimation problem, where a dynamic filter is used to estimate the fault magnitude. The effectiveness of the proposed approach is demonstrated by simulation results for several fault scenarios. Copyright © 2010 John Wiley & Sons, Ltd.