Friedmann, H.H.FriedmannGrießmann, T.T.GrießmannKremling, S.S.KremlingNuber, A.A.NuberSayer, F.F.Sayer2022-03-142022-03-142018https://publica.fraunhofer.de/handle/publica/407727Rotor Blades (RB) are key components wind turbines. They convert the kinetic energy of wind into a usable torque at the turbine. The RB design decides on the performance of a wind turbine and no manufacturer discloses all design data being necessary for a FEM model. This is the reason why the complete construction documents of RB are not available for research purposes. However, within the research project MultiMonitor RB all design date will be available for modelling purposes. During the entire life cycle of a wind turbine, RB are exposed to a large number of cyclic dynamic loads which can lead to material fatigue until failure. Structural Health Monitoring (SHM) systems can ensure the functionality and safety as they continuously measure stress and strain. Unfortunately, for damage monitoring there are currently no clear limit values. The damage event has to be recorded based on the reduction of the RB stiffness. However, without knowledge of loads and design data there is no information about the ultimate limit state or the remaining lifetime. Within the research project MultiMonitor RB we fundamentally investigate the failure mechanism of a full scale, 40 m long RB. First, in a FEM simulation the RB will be modeled in all details, starting from the precise laminate structure to the exact knowledge of all geometric dimensions up to the specific material characteristics. Furthermore, inevitable fabrication defects and flaws will be considered within the simulation. Therefore, the RB will be inspected by an authorized expert to assess the positions and characteristics of imperfections. Second, the RB will be probed on a test stand with a defined procedure until failure and break. During the tests, the RB is equipped with the monitoring system SHM.Blade and additional strain sensors, accelerometers and others. The signal analysis relies on methods of statistics, pattern recognition, self-organizing maps, neural networks and machine learning. This leads to the development of damage indicators based on modal parameters. By comparing measurements and simulation, the FEM model can be verified. Numerically established fatigue and failure models for laminates are also included in the calculations. Finally, general criteria for the evaluation of the load bearing capacity of RB are derived. The combination of simulation and measurement to breakage promises groundbreaking insights, especially with regard to the transferability to other RB types.enconference paper