19 April 2017 Scheduling structural health monitoring activities for optimizing life-cycle costs and reliability of wind turbines
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Abstract
Optimization of the life-cycle costs and reliability of offshore wind turbines (OWTs) is an area of immense interest due to the widespread increase in wind power generation across the world. Most of the existing studies have used structural reliability and the Bayesian pre-posterior analysis for optimization. This paper proposes an extension to the previous approaches in a framework for probabilistic optimization of the total life-cycle costs and reliability of OWTs by combining the elements of structural reliability/risk analysis (SRA), the Bayesian pre-posterior analysis with optimization through a genetic algorithm (GA). The SRA techniques are adopted to compute the probabilities of damage occurrence and failure associated with the deterioration model. The probabilities are used in the decision tree and are updated using the Bayesian analysis. The output of this framework would determine the optimal structural health monitoring and maintenance schedules to be implemented during the life span of OWTs while maintaining a trade-off between the life-cycle costs and risk of the structural failure. Numerical illustrations with a generic deterioration model for one monitoring exercise in the life cycle of a system are demonstrated. Two case scenarios, namely to build initially an expensive and robust or a cheaper but more quickly deteriorating structures and to adopt expensive monitoring system, are presented to aid in the decision-making process.
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Anu Hanish Nithin, Anu Hanish Nithin, Piotr Omenzetter, Piotr Omenzetter, } "Scheduling structural health monitoring activities for optimizing life-cycle costs and reliability of wind turbines", Proc. SPIE 10171, Smart Materials and Nondestructive Evaluation for Energy Systems 2017, 101710F (19 April 2017); doi: 10.1117/12.2257935; https://doi.org/10.1117/12.2257935
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