Resumé

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.
OriginalsprogEngelsk
Artikelnummer998
TidsskriftEnergies
Vol/bind12
Udgave nummer6, Special Issue
ISSN1996-1073
DOI
StatusE-pub ahead of print - 2019

Fingerprint

Turbine Blade
Wind Turbine
Wind turbines
Turbomachine blades
Maintenance
Defects
Planning
Inspection
Markov Chain Model
Damage
Costs
Blade
Transition Probability
Markov processes
Condition-based Maintenance
Decision Theory
Decision theory
Categorization
Chord or secant line
Probabilistic Model

Bibliografisk 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 Turbines.

Emneord

  • Discrete Markov Chain Model
  • Transverse cracks
  • Condition-based maintenance
  • Maintenance strategy

Citer dette

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title = "Cost-optimal Maintenance Planning for Defects on Wind Turbine Blades",
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.",
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Cost-optimal Maintenance Planning for Defects on Wind Turbine Blades. / Yang, Yi; Sørensen, John Dalsgaard.

I: Energies, Bind 12, Nr. 6, Special Issue, 998, 2019.

Publikation: Bidrag til tidsskriftTidsskriftartikelForskningpeer review

TY - JOUR

T1 - Cost-optimal Maintenance Planning for Defects on Wind Turbine Blades

AU - Yang, Yi

AU - Sørensen, John Dalsgaard

N1 - 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 Turbines

PY - 2019

Y1 - 2019

N2 - 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.

AB - 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.

KW - Discrete Markov Chain Model

KW - Transverse cracks

KW - Condition-based maintenance

KW - Maintenance strategy

KW - Discrete Markov Chain Model

KW - Transverse cracks

KW - Condition-based maintenance

KW - Maintenance strategy

U2 - 10.3390/en12060998

DO - 10.3390/en12060998

M3 - Journal article

VL - 12

JO - Energies

JF - Energies

SN - 1996-1073

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ER -