Jannie Sønderkær Nielsen

On risk-based operation and maintenance of offshore wind turbine components

Operation and maintenance are significant contributors to the cost of energy for offshore wind turbines. Optimal planning could rationally be based on Bayesian pre-posterior decision theory, and all costs through the lifetime of the structures should be included. This paper contains a study of a generic case where the costs are evaluated for a single wind turbine with a single component. Costs due to inspections, repairs, and lost production are included in the model. The costs are compared for two distinct maintenance strategies, namely with and without inclusion of periodic imperfect inspections. Finally the influence of different important parameters, e.g. failure rate, reliability of inspections, inspection interval, and decision rule for repairs, is evaluated.

Computational framework for risk-based planning of inspections, maintenance, and condition monitoring using discrete Bayesian networks

Abstract This paper presents a computational framework for risk-based planning of inspections and repairs for deteriorating components. Two distinct types of decision rules are used to model decisions: simple decision rules that depend on constants or observed variables (e.g. inspection outcome), and advanced decision rules that depend on variables found using Bayesian updating (e.g. probability of failure). Two decision models are developed, both relying on dynamic Bayesian networks (dBNs) for deterioration modelling. For simple decision rules, dBNs are used directly for exact assessment of total expected life-cycle costs. For advanced decision rules, simulations are performed to estimate the expected costs, and dBNs are used within the simulations for decision-making. Information from inspections and condition monitoring are included if available. An example in the paper demonstrates the framework and the implemented strategies and decision rules, including various types of condition-based maintenance. The strategies using advanced decision rules lead to reduced costs compared to the simple decision rules when condition monitoring is applied, and the value of condition monitoring is estimated by comparing the lowest costs obtained with and without condition monitoring.

Risk-based decision making for deterioration processes using POMDP

This paper proposes a method for risk-based decis ion making for maintenance of deteriorating components, based on the partially observable Marko v decision process (POMDP). Unlike most methods, the decision polices do not need to be stationary an d can vary according to seasons and near the end of the lifetime. The approach is demonstrated through tw o examples, and the total expected costs are similar to those of another efficient method.