A real-time inspection and opportunistic maintenance strategies for floating offshore wind turbines.

This paper proposes an FMEA-BN model to determine the inspection and opportunistic maintenance strategies of floating offshore wind turbines. A mapping algorithm is proposed to establish a mirrored Bayesian Network (BN) model from a given failure mode and effect analysis (FMEA) structure to realize the FMEA-BN modelling, which is efficient to consider common cause failures. The failure probabilities of items of floating offshore wind turbines are first updated by the BN sub-model, in which, various operation scenarios are considered. The updated failure probabilities are then imported to the FMEA sub-model to determine the items of the floating offshore wind turbines that are to be inspected and to which the opportunistic maintenance action would be applied. With the FMEA-BN model, inspection and opportunistic maintenance strategies for a floating offshore wind turbine are suggested under several commonly occurring operation scenarios. The validation of the results is illustrated by the failure rate of the floating offshore wind turbine predicted by the BN sub-model, the uncertainty of which is lower than 3%. Overall, the presented FMEA-BN model supports real-time inspection and opportunistic maintenance strategies determination of complicated systems like floating offshore wind turbines. • FMEA-BN is proposed to determine the inspection and opportunistic maintenance strategies of floating offshore wind turbines. • A mapping algorithm is proposed to establish a Bayesian Network model from a given failure mode and effect analysis (FMEA). • The failure probabilities of items of floating offshore wind turbines are first updated by the BN sub-model. • The updated failure probabilities are then imported to the FMEA sub-model to determine the items that are to be inspected. • The presented FMEA-BN model supports real-time inspection and opportunistic maintenance strategies. [ABSTRACT FROM AUTHOR]