For offshore wind turbines costs to operation and maintenance are substantial. This paper describes a risk-based life-cycle approach for optimal planning of operation and maintenance. The approach is based on pre-posterior Bayesian decision theory. Deterioration mechanisms such as fatigue, corrosion, wear and erosion are associated with significant uncertainty. Observations of the degree of damage can increase the reliability of predictions, especially in connection with condition-based maintenance. The approach can be used for gearboxes, generators, cracks, corrosion, etc. The paper also describes how probabilistic indicators can be used to quantify indirect information about the damage state for critical components, e.g. gearboxes.
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