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Identification of ice mass accumulated on wind turbine blades using its natural frequencies
Luleå University of Technology, Department of Engineering Sciences and Mathematics, Product and Production Development.ORCID iD: 0000-0001-8216-9464
Luleå University of Technology, Department of Engineering Sciences and Mathematics, Product and Production Development.
Luleå University of Technology, Department of Engineering Sciences and Mathematics, Product and Production Development.
2017 (English)In: Wind Engineering: The International Journal of Wind Power, ISSN 0309-524X, E-ISSN 2048-402XArticle in journal (Refereed) Epub ahead of print
Abstract [en]

This work demonstrates a technique to identify information about the ice mass accumulation on wind turbine blades using its natural frequencies, and these frequencies reduce differently depending on the spatial distribution of ice mass along the blade length. An explicit relation to the natural frequencies of a 1-kW wind turbine blade is defined in terms of the location and quantity of ice mass using experimental modal analyses. An artificial neural network model is trained with a data set (natural frequencies and ice masses) generated using that explicit relation. After training, this artificial neural network model is given an input of natural frequencies of the iced blade (identified from experimental modal analysis) corresponding to 18 test cases, and it identified ice masses’ location and quantity with a weighted average percentage error value of 17.53%. The proposed technique is also demonstrated on the NREL 5-MW wind turbine blade data.

Place, publisher, year, edition, pages
Sage Publications, 2017.
Keyword [en]
Wind turbine blade, ice detection, natural frequency, experimental modal analysis, artificial neural network
National Category
Applied Mechanics
Research subject
Computer Aided Design
Identifiers
URN: urn:nbn:se:ltu:diva-65213DOI: 10.1177/0309524X17723207OAI: oai:DiVA.org:ltu-65213DiVA: diva2:1134549
Projects
Wind power in cold climates
Funder
Swedish Energy Agency
Available from: 2017-08-21 Created: 2017-08-21 Last updated: 2017-11-24

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Gantasala, SudhakarLuneno, Jean-ClaudeAidanpää, Jan-Olov
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Product and Production Development
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Wind Engineering: The International Journal of Wind Power
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CiteExportLink to record
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Citation style
  • apa
  • harvard1
  • ieee
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  • vancouver
  • Other style
More styles
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  • de-DE
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  • nn-NB
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  • Other locale
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Output format
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