Bi-axial neutral axis tracking for crack detection in wind turbine towers

This work concentrates on Structural Health Monitoring (SHM) of a wind turbine tower. The paper investigates the use of a decision level data fusion based on bi-axial tracking of change in the neutral axis (NA) position for damage detection in wind turbine towers. A discrete Kalman Filter (KF) is employed for the estimation of the NA in the presence of measurement noise from the strain sensors. The KF allows data fusion from the strain sensors and the yaw mechanism for the accurate estimation of the NA. Any change in the NA position may be used for detecting and locating the damage. The tan inverse of the ratio of the change in the NA along two perpendicular axes is taken and used for the localization. The study was carried out on a simulated finite element (FE) model of a wind turbine tower with a surface crack. The sensitivity studies carried out on the structure in terms of different crack sizes, crack locations and crack orientations indicate that the methodology is robust enough to detect the crack under different operational loading conditions.