Using 2D Phase-Based Motion Estimation and Video Magnification for Binary Damage Identification on a Wind Turbine Blade

Abstract

Videos (sequence of images) as three-dimensional signals may be considered as a very rich source of information for several applications in structural dynamics identification and structural health monitoring (SHM) systems. Within this paper high-speed cameras are used to record the sequence of images (video) of a baseline and damaged wind turbine blade (WTB) while vibrating due to the external loadings. Among several computer vision algorithms for motion extraction from the videos, phase-based motion estimation technique is used to extract the response of both the baseline and damaged wind turbine blade. Modal parameters (natural frequencies and operating deflection shapes) were used as damage sensitive features in order to detect the occurrence of damage in the wind turbine blade. The first four natural frequencies of the both baseline and damaged wind turbine blade are extracted by analyzing the estimated motion provided by the phase based motion estimation in the frequency domain. The motion magnification algorithm is also utilized to visualize and extract the operating deflection shapes of the wind turbine blade which may be used later as an indicator of the presence of damage. It has been shown that changes in the dynamic behavior of the wind turbine blade will result to deviations in the nominal natural frequencies and operating deflection shapes, and the damaged wind turbine blade can be differentiated from the baseline WTB using this non-contact measurement approach.