Active Fault Diagnosis on a Hydraulic Pitch System Based on Frequency-Domain Identification

The blade pitch system is a critical subsystem of variable-speed variable-pitch wind turbines that is characterized by a high failure rate. This paper addresses the fault detection and isolation (FDI) of a blade pitch system with hydraulic actuators. Focus is placed on incipient multiplicative faults, namely hydraulic oil contamination with water and air, bearing damage resulting in increased friction, and drop of the supply pressure of the hydraulic pump. An active model-based FDI approach is considered, where changes in the operating conditions (i.e., mean wind speed and turbulence intensity) are accounted through the identification of a linear parameter-varying model for the pitch actuators. Frequency-domain estimators are used to identify continuous-time models in a user-defined frequency band, which facilitates the design of the FDI algorithm. Besides, robustness with respect to noise in measurements and stochastic nonlinear distortions is ensured by estimating confidence bounds on the parameters used for FDI. The approach is thoroughly validated on a wind turbine simulator based on the FAST software that includes a detailed physical model of the hydraulic pitch system. This paper presents the design methodology and validation results for the proposed FDI approach. We show that an appropriate design of the excitation signal used for active fault detection allows an early fault diagnosis (except for oil contamination with water) while ensuring a short experiment duration and an acceptable impact on the wind turbine operation.