Acousto-Ultrasonic Damage Monitoring in a Thick Composite Beam for Wind Turbine Applications

Monitoring of wind turbine components is more and more important to guarantee a safe and efficient operation of these systems, in particular when off-shore wind turbines are considered. Fatigue is a dominant failure mechanism and therefore a critical design parameter. Earlier research of the authors revealed that one of the critical components in a wind turbine blade is the spar cap. Failure of it is detrimental for the functioning of the wind turbine and can lead to an accumulation of failures and to an increase in the wind turbine operation and maintenance cost. Fatigue is often detected based on a stiffness reduction of the component. A common problem observed in monitoring systems based on stiffness reduction is that the damage accumulates without causing an observable change of stiffness. As a result, the response time between stiffness drop and component failure is relatively short. An alternative monitoring method, based on acousto-ultrasonics (AU) is proposed, allowing for damage accumulation monitoring. The method is based on the Reconstruction Algorithm for Probabilistic Inspection of Damage (RAPID) as applied to thin-walled (composite) structures to identify damages such as cracks and delaminations. The suitability of this damage identification method for a thick-walled glass fibre beam, representing a spar cap, was tested by the authors. Based on the positive outcome, a similar beam was equipped with eight piezo-electric transducers and subjected to a three-point bending fatigue test. The bending stiffness is measured using the force and displacement of the test bank and at regular intervals, an AU measurement is executed. In a mutual comparison of the measurements, it is shown that the AU measurements are sensitive to damage accumulation, whereas the stiffness measurement is not. The newly proposed method thus allows for a much earlier warning of imminent failure and can be used for prognostics and improved maintenance planning.