A case study on risk-based maintenance of wind turbine blades with structural health monitoring

This paper presents a case study demonstrating how to quantify the
value of structural health monitoring (SHM), when used optimally in
maintenance planning for wind turbine blades. Maintenance cost
optimization is performed using a risk-based approach based on
Bayesian decision analysis, in which probabilistic models are developed
for blade deterioration processes, blade inspections and SHM systems.
The probabilistic SHM system model is based on data from an SHM
campaign with a 225 kW Vestas V27 wind turbine, where an artificial
trailing edge crack of increasing size was introduced. The statistics
derived from this model are applied to the case study concerning
maintenance of an 8 MW offshore wind turbine. It is found that the
benefit of the SHM highly depends on the reliability of the SHM system
and on how SHM observations are used when making decisions on
inspections and maintenance. A sensitivity study confirms the generality
of the findings.