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Long-term prediction of dynamic responses on an offshore wind turbine using a virtual sensor approach
Iliopoulos, A.; Weijtjens, W.; Van Hemelrijck, D.; Devriendt, C. (2015). Long-term prediction of dynamic responses on an offshore wind turbine using a virtual sensor approach, in: Chang, F.-K. et al. (Ed.) 10th International Workshop on Structural Health Monitoring 2015: System Reliability for Verification and Implementation. pp. 2793-2800
In: Chang, F.-K.; Kopsaftopoulos, F. (Ed.) (2015). 10th International Workshop on Structural Health Monitoring 2015: System Reliability for Verification and Implementation. DEStech Publications: Lancaster. ISBN 978-1-60595-275-8. 3220 pp., more

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Keyword
    Marine/Coastal

Authors  Top 
  • Iliopoulos, A., more
  • Weijtjens, W., more
  • Van Hemelrijck, D., more
  • Devriendt, C., more

Abstract
    Since fatigue life is a design driver for the foundations, the continuous monitoring for life-time assessment of an offshore wind turbine during its wide range of operational states can serve as a valuable tool for maintenance, end-of-life decisions and feedback into design for optimization of future substructures. For the offshore wind turbine, though, practical limitations prohibit to mount sensors at stress (and fatigue) hotspots. E.g. for a monopile foundation, the most popular design, the stress hot spot is at the mudline below the water level. Installing a measurement system at the mudline is unfavourable in terms of cost and maintenance. This limitation is overcome by reconstructing the full-field response of the structure based on the limited number of accelerometers and a calibrated Finite Element Model of the system. A reduced-order model that exploits the limited information obtained by the acceleration sensor data and adaptively incorporates them to permit adaptation to system changes is utilised for optimal generation of virtual dynamic strains. The model uses a multi band modal decomposition and expansion approach for reconstructing the responses at all degrees of freedom of the finite element model. The paper will demonstrate the possibility to estimate dynamic strains from acceleration measurements based on the aforementioned methodology. These virtual dynamic strains will then be evaluated and validated based on long term actual strain measurements obtained from a monitoring campaign on an offshore wind turbine on a monopile foundation. This new structural health monitoring approach has the ability to interrogate an entire structure and accurately assess fatigue life consumption and remaining useful life at the true fatigue hot spots.

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