Abstract
One of the critical challenges to the scalability, cost-effectiveness, and sustainability of floating offshore wind systems is the fatigue life of mooring lines, which are subjected to loads covering a wide range of amplitudes and frequencies.
Structural health monitoring of mooring lines requires an accurate tension load history, which is obtained from strain gauges mounted at the fairlead level. However these measurements drift significantly over time and are affected by noise.
The present study aims at adressing this issue and performing real-time tension estimation of the mooring lines on a large 22MW floating wind turbine, subjected to wave and wind loads. It is a purely numerical exercise: reference data are obtained from SIMA, a nonlinear dynamic fluid-structure coupled solver. The resulting tension signals are artificially polluted with noise and bias, and are used as a starting point for the estimation problem.
The reconstruction of the tension is based on an inverse Finite Element method (iFEM). This method formulates an optimization problem with quadratic costs on the deviation from measurements and on the estimated unknown parameters, while equality constraints enforce the dynamic equilibrium.
Results show fairly good tension estimation and good reconstruction of the model parameters with scarce measurements.