Full-field dynamic strain prediction on a wind turbine using displacements of optical targets measured by stereophotogrammetry. (October 2015)

• Record Type: Journal Article
• Authors: Baqersad, Javad; Niezrecki, Christopher; Avitabile, Peter
• Is Part Of: Mechanical systems and signal processing. Volume 62/63(2015)
• Page Start: 284
• Page End: 295
• Publication Date: 2015-10
• Subjects: Point tracking -- Full-field strain -- Wind turbine -- Health monitoring -- Blade; Structural dynamics -- Periodicals; Vibration -- Periodicals; Constructions -- Dynamique -- Périodiques; Vibration -- Périodiques; Structural dynamics; Vibration; Periodicals; 621
• DOI: 10.1016/j.ymssp.2015.03.021
• Languages: English
• ISSNs: 0888-3270

Abstract

Abstract: Health monitoring of rotating structures (e.g. wind turbines and helicopter blades) has historically been a challenge due to sensing and data transmission problems. Unfortunately mechanical failure in many structures initiates at components on or inside the structure where there is no sensor located to predict the failure. In this paper, a wind turbine was mounted with a semi-built-in configuration and was excited using a mechanical shaker. A series of optical targets was distributed along the blades and the fixture and the displacement of those targets during excitation was measured using a pair of high speed cameras. Measured displacements with three dimensional point tracking were transformed to all finite element degrees of freedom using a modal expansion algorithm. The expanded displacements were applied to the finite element model to predict the full-field dynamic strain on the surface of the structure as well as within the interior points. To validate the methodology of dynamic strain prediction, the predicted strain was compared to measured strain by using six mounted strain-gages. To verify if a simpler model of the turbine can be used for the expansion, the expansion process was performed both by using the modes of the entire turbine and modes of a single cantilever blade. The results indicate that the expansion approach can accurately predict the strain throughout the turbine blades from displacements measured by using stereophotogrammetry. Highlights: Strain of a turbine was predicted by using a limited set of measured displacements. The approach can be used to identify strain at locations where no sensors exist. The strain could be predicted on the surface and at interior points. The application of the approach enables a new type of structural health monitoring. The technique requires few optical targets that can be removed after the test.