Comparison of two optimization algorithms for fuzzy finite element model updating for damage detection in a wind turbine blade

Heather Turnbull, Piotr Omenzetter

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

vDifficulties associated with current health monitoring and inspection practices combined with harsh, often remote, operational environments of wind turbines highlight the requirement for a non-destructive evaluation system capable of remotely monitoring the current structural state of turbine blades. This research adopted a physics based structural health monitoring methodology through calibration of a finite element model using inverse techniques. A 2.36m blade from a 5kW turbine was used as an experimental specimen, with operational modal analysis techniques utilised to realize the modal properties of the system. Modelling the experimental responses as fuzzy numbers using the sub-level technique, uncertainty in the response parameters was propagated back through the model and into the updating parameters. Initially, experimental responses of the blade were obtained, with a numerical model of the blade created and updated. Deterministic updating was carried out through formulation and minimisation of a deterministic objective function using both firefly algorithm and virus optimisation algorithm. Uncertainty in experimental responses were modelled using triangular membership functions, allowing membership functions of updating parameters (Young's modulus and shear modulus) to be obtained. Firefly algorithm and virus optimisation algorithm were again utilised, however, this time in the solution of fuzzy objective functions. This enabled uncertainty associated with updating parameters to be quantified. Varying damage location and severity was simulated experimentally through addition of small masses to the structure intended to cause a structural alteration. A damaged model was created, modelling four variable magnitude nonstructural masses at predefined points and updated to provide a deterministic damage prediction and information in relation to the parameters uncertainty via fuzzy updating.

Original languageEnglish
Title of host publicationNondestructive Characterization and Monitoring of Advanced Materials, Aerospace, Civil Infrastructure, and Transportation XII
PublisherSPIE
Volume10599
ISBN (Electronic)9781510616943
DOIs
Publication statusPublished - 2018
EventNondestructive Characterization and Monitoring of Advanced Materials, Aerospace, Civil Infrastructure, and Transportation XII 2018 - Denver, United States
Duration: 5 Mar 20188 Mar 2018

Publication series

NameProceedings of SPIE
PublisherSPIE
ISSN (Print)0277-786X
ISSN (Electronic)1996-756X

Conference

ConferenceNondestructive Characterization and Monitoring of Advanced Materials, Aerospace, Civil Infrastructure, and Transportation XII 2018
CountryUnited States
CityDenver
Period5/03/188/03/18

Fingerprint

Model Updating
Damage Detection
Turbine Blade
turbine blades
wind turbines
Damage detection
Wind Turbine
Wind turbines
Finite Element Model
Turbomachine blades
Updating
Optimization Algorithm
damage
blades
optimization
Blade
fireflies
membership functions
Membership functions
Viruses

Keywords

  • damage detection
  • firefly algorithm
  • fuzzy finite element model updating
  • structural health monitoring
  • uncertainty quantification
  • virus optimisation algorithm
  • wind turbine blade

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering

Cite this

Turnbull, H., & Omenzetter, P. (2018). Comparison of two optimization algorithms for fuzzy finite element model updating for damage detection in a wind turbine blade. In Nondestructive Characterization and Monitoring of Advanced Materials, Aerospace, Civil Infrastructure, and Transportation XII (Vol. 10599). [105991Q] (Proceedings of SPIE). SPIE. https://doi.org/10.1117/12.2295314

Comparison of two optimization algorithms for fuzzy finite element model updating for damage detection in a wind turbine blade. / Turnbull, Heather; Omenzetter, Piotr.

Nondestructive Characterization and Monitoring of Advanced Materials, Aerospace, Civil Infrastructure, and Transportation XII. Vol. 10599 SPIE, 2018. 105991Q (Proceedings of SPIE).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Turnbull, H & Omenzetter, P 2018, Comparison of two optimization algorithms for fuzzy finite element model updating for damage detection in a wind turbine blade. in Nondestructive Characterization and Monitoring of Advanced Materials, Aerospace, Civil Infrastructure, and Transportation XII. vol. 10599, 105991Q, Proceedings of SPIE, SPIE, Nondestructive Characterization and Monitoring of Advanced Materials, Aerospace, Civil Infrastructure, and Transportation XII 2018, Denver, United States, 5/03/18. https://doi.org/10.1117/12.2295314
Turnbull H, Omenzetter P. Comparison of two optimization algorithms for fuzzy finite element model updating for damage detection in a wind turbine blade. In Nondestructive Characterization and Monitoring of Advanced Materials, Aerospace, Civil Infrastructure, and Transportation XII. Vol. 10599. SPIE. 2018. 105991Q. (Proceedings of SPIE). https://doi.org/10.1117/12.2295314
Turnbull, Heather ; Omenzetter, Piotr. / Comparison of two optimization algorithms for fuzzy finite element model updating for damage detection in a wind turbine blade. Nondestructive Characterization and Monitoring of Advanced Materials, Aerospace, Civil Infrastructure, and Transportation XII. Vol. 10599 SPIE, 2018. (Proceedings of SPIE).
@inproceedings{ceeaac389fa746659c208e1f7561d33a,
title = "Comparison of two optimization algorithms for fuzzy finite element model updating for damage detection in a wind turbine blade",
abstract = "vDifficulties associated with current health monitoring and inspection practices combined with harsh, often remote, operational environments of wind turbines highlight the requirement for a non-destructive evaluation system capable of remotely monitoring the current structural state of turbine blades. This research adopted a physics based structural health monitoring methodology through calibration of a finite element model using inverse techniques. A 2.36m blade from a 5kW turbine was used as an experimental specimen, with operational modal analysis techniques utilised to realize the modal properties of the system. Modelling the experimental responses as fuzzy numbers using the sub-level technique, uncertainty in the response parameters was propagated back through the model and into the updating parameters. Initially, experimental responses of the blade were obtained, with a numerical model of the blade created and updated. Deterministic updating was carried out through formulation and minimisation of a deterministic objective function using both firefly algorithm and virus optimisation algorithm. Uncertainty in experimental responses were modelled using triangular membership functions, allowing membership functions of updating parameters (Young's modulus and shear modulus) to be obtained. Firefly algorithm and virus optimisation algorithm were again utilised, however, this time in the solution of fuzzy objective functions. This enabled uncertainty associated with updating parameters to be quantified. Varying damage location and severity was simulated experimentally through addition of small masses to the structure intended to cause a structural alteration. A damaged model was created, modelling four variable magnitude nonstructural masses at predefined points and updated to provide a deterministic damage prediction and information in relation to the parameters uncertainty via fuzzy updating.",
keywords = "damage detection, firefly algorithm, fuzzy finite element model updating, structural health monitoring, uncertainty quantification, virus optimisation algorithm, wind turbine blade",
author = "Heather Turnbull and Piotr Omenzetter",
note = "Self archiving info: http://www.spie.org/conferences-and-exhibitions/authors-and-presenters/copyright-form-required-for-publication?webSyncID=705c4436-5263-3025-37a2-6b4a88864d38&sessionGUID=c125ea36-07dc-a460-4817-2b9918ee299b&_ga=2.10652147.654972756.1528375310-1842538005.1528375310&SSO=1",
year = "2018",
doi = "10.1117/12.2295314",
language = "English",
volume = "10599",
series = "Proceedings of SPIE",
publisher = "SPIE",
booktitle = "Nondestructive Characterization and Monitoring of Advanced Materials, Aerospace, Civil Infrastructure, and Transportation XII",
address = "United States",

}

TY - GEN

T1 - Comparison of two optimization algorithms for fuzzy finite element model updating for damage detection in a wind turbine blade

AU - Turnbull, Heather

AU - Omenzetter, Piotr

N1 - Self archiving info: http://www.spie.org/conferences-and-exhibitions/authors-and-presenters/copyright-form-required-for-publication?webSyncID=705c4436-5263-3025-37a2-6b4a88864d38&sessionGUID=c125ea36-07dc-a460-4817-2b9918ee299b&_ga=2.10652147.654972756.1528375310-1842538005.1528375310&SSO=1

PY - 2018

Y1 - 2018

N2 - vDifficulties associated with current health monitoring and inspection practices combined with harsh, often remote, operational environments of wind turbines highlight the requirement for a non-destructive evaluation system capable of remotely monitoring the current structural state of turbine blades. This research adopted a physics based structural health monitoring methodology through calibration of a finite element model using inverse techniques. A 2.36m blade from a 5kW turbine was used as an experimental specimen, with operational modal analysis techniques utilised to realize the modal properties of the system. Modelling the experimental responses as fuzzy numbers using the sub-level technique, uncertainty in the response parameters was propagated back through the model and into the updating parameters. Initially, experimental responses of the blade were obtained, with a numerical model of the blade created and updated. Deterministic updating was carried out through formulation and minimisation of a deterministic objective function using both firefly algorithm and virus optimisation algorithm. Uncertainty in experimental responses were modelled using triangular membership functions, allowing membership functions of updating parameters (Young's modulus and shear modulus) to be obtained. Firefly algorithm and virus optimisation algorithm were again utilised, however, this time in the solution of fuzzy objective functions. This enabled uncertainty associated with updating parameters to be quantified. Varying damage location and severity was simulated experimentally through addition of small masses to the structure intended to cause a structural alteration. A damaged model was created, modelling four variable magnitude nonstructural masses at predefined points and updated to provide a deterministic damage prediction and information in relation to the parameters uncertainty via fuzzy updating.

AB - vDifficulties associated with current health monitoring and inspection practices combined with harsh, often remote, operational environments of wind turbines highlight the requirement for a non-destructive evaluation system capable of remotely monitoring the current structural state of turbine blades. This research adopted a physics based structural health monitoring methodology through calibration of a finite element model using inverse techniques. A 2.36m blade from a 5kW turbine was used as an experimental specimen, with operational modal analysis techniques utilised to realize the modal properties of the system. Modelling the experimental responses as fuzzy numbers using the sub-level technique, uncertainty in the response parameters was propagated back through the model and into the updating parameters. Initially, experimental responses of the blade were obtained, with a numerical model of the blade created and updated. Deterministic updating was carried out through formulation and minimisation of a deterministic objective function using both firefly algorithm and virus optimisation algorithm. Uncertainty in experimental responses were modelled using triangular membership functions, allowing membership functions of updating parameters (Young's modulus and shear modulus) to be obtained. Firefly algorithm and virus optimisation algorithm were again utilised, however, this time in the solution of fuzzy objective functions. This enabled uncertainty associated with updating parameters to be quantified. Varying damage location and severity was simulated experimentally through addition of small masses to the structure intended to cause a structural alteration. A damaged model was created, modelling four variable magnitude nonstructural masses at predefined points and updated to provide a deterministic damage prediction and information in relation to the parameters uncertainty via fuzzy updating.

KW - damage detection

KW - firefly algorithm

KW - fuzzy finite element model updating

KW - structural health monitoring

KW - uncertainty quantification

KW - virus optimisation algorithm

KW - wind turbine blade

UR - http://www.scopus.com/inward/record.url?scp=85047448595&partnerID=8YFLogxK

U2 - 10.1117/12.2295314

DO - 10.1117/12.2295314

M3 - Conference contribution

VL - 10599

T3 - Proceedings of SPIE

BT - Nondestructive Characterization and Monitoring of Advanced Materials, Aerospace, Civil Infrastructure, and Transportation XII

PB - SPIE

ER -