Title
Inspection and maintenance optimization for OWT’s using Bayesian networks
Author
Courage, W.M.G.
Nicoreac, M.P.
Kempker, P.L.
Contributor
Walls, L. (editor)
Revie, M. (editor)
Bedford, T. (editor)
Publication year
2017
Abstract
For offshore wind turbines (OWT’s) environmental and accessibility conditions make inspection and maintenance costly. Hence the potential of cost reduction when the planning of these actions can be optimized. Taking uncertainties into account, a risk based concept is adopted in which probabilities of failure and its consequences are balanced against costs of inspections and actions, including different inspection and maintenance methods. The evolution over time of the structure’s state is represented by a state of the art crack growth model that takes retardation effects into account due to possible overloads in the fatigue load sequences. Optimizations are obtained by a Bayesian Network schematization of the problem at hand and making use of the Limited Memory Influence Diagram. The paper describes the background of the procedures and illustrates their performance by presenting an example with OWT data.
Subject
ICT
CSR - Cyber Security & Robustness
TS - Technical Sciences
Cost reduction
Inspection
Maintenance
Offshore wind turbines
Reliability
Reliability theory
Safety engineering
Wind turbines
Crack growth model
Fatigue loads
Influence diagram
Inspection and maintenance
Limited memory
Retardation effect
Risk-based
State of the art
Bayesian networks
To reference this document use:
http://resolver.tudelft.nl/uuid:3b80c201-3e8a-490f-a0e3-e8c5996f12b9
TNO identifier
753498
Publisher
CRC Press/Balkema
ISBN
9781138029972
Source
Proceedings of the 26th European Safety and Reliability Conference, ESREL 2016, Glasgow, Scotland, UK, 25-29 September 2016, 1044-1049
Document type
conference paper