Fuzzy finite element model updating of a laboratory wind turbine blade for structural modification detection

Heather Turnbull, Piotr Omenzetter

Research output: Contribution to journalArticlepeer-review

4 Citations (Scopus)
10 Downloads (Pure)

Abstract

Wind turbine blades are a key structural component of the wind turbine and are crucial to efficient energy generation. The consequences of blade failure can be very expensive or even catastrophic and therefore a means of continuously monitoring the blades to determine their condition will provide substantial benefits. In this research, a novel application of Fuzzy Finite Element Model Updating (FFEMU) to wind turbine blades for their structural health assessment is demonstrated. Experimental frequencies obtained from modal analysis on a small-scale wind turbine blade were described by fuzzy numbers to model measurement uncertainty. Structural modification, intended to be in lieu of damage, was simulated experimentally in a non-destructive way through addition of a small mass to the blade trailing edge, inducing a structural change. A numerical model was constructed with the added mass parameters in several locations considered as updating parameters. Analyses were run with varying extents of the modification to obtain objective function values and fuzzy updated parameters were constructed that minimized the objective function. This methodology was able to successfully identify the location and extent of modification.

Original languageEnglish
Pages (from-to)2274-2281
Number of pages8
JournalProcedia Engineering
Volume199
DOIs
Publication statusPublished - 12 Sept 2017
EventX International Conference on Structural Dynamics, EURODYN 2017 - Faculty of Civil and Industrial Engineering of Sapienza University of Rome Italy, Rome, Italy
Duration: 10 Sept 201713 Sept 2017
http://Faculty of Civil and Industrial Engineering of Sapienza University of Rome Italy

Keywords

  • Fuzzy finite element model updating
  • uncertinaty quantification
  • structural health monitoring
  • damage severity assesment

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