Wind Turbine Fault Detection and Estimation Based On Nonlinear Observer
Ichrak Eben Zaid, Moez Boussada, Ahmed Saïd Nouri
Abstract
This article deals with the fault detection strategy used to ensure wind turbine reliability. The proposed approach is based on an Unknown Input High Gain Observer (UIHGO) for a class of nonlinear systems subject to actuator and sensor faults. Compared to some usually used algorithms, this method presents the benefits of reduced calculation time as well as development effort and accuracy, which makes it useful for online implementation even for fast processes. Used for linear systems, such approaches demonstrated interesting performances and results. The problem becomes harder for nonlinear systems, where models are characterized by complex and coupled behaviors. Moreover, faults have to be detected as early as possible to avoid catastrophic and irreversible damage. Applied to a simulated wind turbine plant to reconstruct not only the full system state but also the faults altering the electromechanical torque subpart and the generator speed signal, the results confirmed the accuracy and time convergence performances of the proposed observer, which make it an interesting candidate to overcome fault detection for nonlinear systems.