Operational damage localization of wind turbine blades

Abstract

This study tackles the challenge of operational damage identification on wind turbine blades and proposes a novel framework for damage detection and localization. A vibration-based scheme is proposed, which tracks the variability of the mode shape curvatures (MSCs) of the blade along its plane direction. The method consists of a training and a diagnostics stage. In the former, MSC information for a number of predefined modes is extracted over varying operational conditions in the healthy state of the blade and, via the implementation of the principal component analysis (PCA), a statistical characterization of each blade’s node is estimated. Then, during the diagnostics stage, the MSCs are assembled and the same PCA mapping is enforced. A corresponding damage index is established, in order to detect and localize damage, if it exists. In both stages, MSC extraction is based on the successful estimation of vector autoregressive moving average (VARX) models that rely on pressure excitation and distributed strain measurements.