Health monitoring of wind turbines is typically performed using conventional sensors (e.g. strain-gages and accelerometers) that are usually mounted to the nacelle or gearbox. Although many wind turbines stop operating due to blade failures, there are typically few to no sensor mounted on the blades. Placing sensors on the rotating parts of the structure is a challenge due to the wiring and data transmission constraints. Within the current work, an approach to monitor full-field dynamic response of rotating structures (e.g. wind turbine blades or helicopter rotors) is developed and experimentally verified. A wind turbine rotor was used as the test structure and was mounted to a block and horizontally placed on the ground. A pair of bearings connected to the rotor shaft allowed the turbine to freely spin along the shaft. Several optical targets were mounted to the blades and a pair of high-speed cameras was used to monitor the dynamics of the spinning turbine. Displacements of the targets during rotation were measured using three-dimensional point tracking. The point tracking technique measured both rigid body displacement and flexible deformation of the blades at target locations. While the structure is rotating, only flap displacements of optical targets (displacements out of the rotation plane) were used in strain prediction process. The measured displacements were expanded and applied to the finite element model of the turbine to extract full-field dynamic strain on the structure. The proposed approach enabled the prediction of dynamic response on the outer surface as well as within the inner points of the structure where no other sensor could be easily mounted. In order to validate the proposed approach, the predicted strain was compared to strain measured at four locations on the spinning blades using a wireless strain-gage system.
This paper proposes a non-contact measurement technique for health monitoring of wind turbine blades using acoustic beamforming techniques. The technique works by mounting an audio speaker inside a wind turbine blade and observing the sound radiated from the blade to identify damage within the structure. The main hypothesis for the structural damage detection is that the structural damage (cracks, edge splits, holes etc.) on the surface of a composite wind turbine blade results in changes in the sound radiation characteristics of the structure. Preliminary measurements were carried out on two separate test specimens, namely a composite box and a section of a wind turbine blade to validate the methodology. The rectangular shaped composite box and the turbine blade contained holes with different dimensions and line cracks. An acoustic microphone array with 62 microphones was used to measure the sound radiation from both structures when the speaker was located inside the box and also inside the blade segment. A phased array beamforming technique and CLEAN-based subtraction of point spread function from a reference (CLSPR) were employed to locate the different damage types on both the composite box and the wind turbine blade. The same experiment was repeated by using a commercially available 48-channel acoustic ring array to compare the test results. It was shown that both the acoustic beamforming and the CLSPR techniques can be used to identify the damage in the test structures with sufficiently high fidelity.
As part of a project to predict the full-field dynamic strain in rotating structures (e.g. wind turbines and helicopter
blades), an experimental measurement was performed on a wind turbine attached to a 500-lb steel block and excited
using a mechanical shaker. In this paper, the dynamic displacement of several optical targets mounted to a turbine placed
in a semi-built-in configuration was measured by using three-dimensional point tracking. Using an expansion algorithm
in conjunction with a finite element model of the blades, the measured displacements were expanded to all finite element
degrees of freedom. The calculated displacements were applied to the finite element model to extract dynamic strain on
the surface as well as within the interior points of the structure. To validate the technique for dynamic strain prediction,
the physical strain at eight locations on the blades was measured during excitation using strain-gages. The expansion was
performed by using both structural modes of an individual cantilevered blade and using modes of the entire structure
(three-bladed wind turbine and the fixture) and the predicted strain was compared to the physical strain-gage
measurements. The results demonstrate the ability of the technique to predict full-field dynamic strain from limited sets
of measurements and can be used as a condition based monitoring tool to help provide damage prognosis of structures
Digital image correlation (DIC) has been becoming increasingly popular as a means to perform structural health
monitoring because of its full-field, non-contacting measurement ability. In this paper, 3D DIC techniques are used to
identify the mode shapes of a wind turbine blade. The blade containing a handful of optical targets is excited at different
frequencies using a shaker as well as a pluck test. The response is recorded using two PHOTRON™ high speed cameras.
Time domain data is transferred to the frequency domain to extract mode shapes and natural frequencies using an
Operational Modal Approach. A finite element model of the blade is also used to compare the mode shapes.
Furthermore, a modal hammer impact test is performed using a more conventional approach with an accelerometer. A
comparison of mode shapes from the photogrammetric, finite element, and impact test approaches are presented to show
the accuracy of the DIC measurement approach.