Abstract
Due to the considerable increase in clean energy demand, there is a significant trend of increased wind turbine sizes, resulting in much higher loads on the blades. The high loads can cause significant out-of-plane deformations of the blades, especially in the area nearby the maximum chord. This paper briefly presents a discrete Markov chain model as a simplified probabilistic model for damages in wind turbine blades, based on a six-level damage categorization scheme applied by the wind industry, with the aim of providing decision makers with cost-optimal inspection intervals and maintenance strategies for the aforementioned challenges facing wind turbine blades. The in-history inspection information extracted from a database with inspection information was used to calibrate transition probabilities in the discrete Markov chain model. With the calibrated transition probabilities, the damage evolution can be statistically simulated. The classical Bayesian pre-posterior decision theory, as well as condition-based maintenance strategy, was used as a basis for the decision-making. An illustrative example with transverse cracks is presented using a reference wind turbine.
Original language | English |
---|---|
Article number | 998 |
Journal | Energies |
Volume | 12 |
Issue number | 6, Special Issue |
ISSN | 1996-1073 |
DOIs | |
Publication status | Published - 2019 |
Bibliographical note
Prof. Dr. John Dalsgaard Sørensen is Guest Editor. This article belongs to the Special Issue Probabilistic Methods for Design and Planning of Operation and Maintenance of Wind TurbinesKeywords
- Condition-based maintenance
- Discrete Markov chain model
- Maintenance strategy
- Transverse cracks