IDEAS home Printed from https://ideas.repec.org/a/eee/renene/v99y2016icp1299-1305.html
   My bibliography  Save this article

A light lithium niobate transducer for the ultrasonic de-icing of wind turbine blades

Author

Listed:
  • Wang, Zhenjun
  • Xu, Yuanming
  • Su, Fei
  • Wang, Yibing

Abstract

This paper proposes a non-thermal method for wind turbine blade de-icing. A lead-free lithium niobate compound is based to fabricate a light ultrasonic transducer as such material has a high Curie temperature of 1210 °C, compared with the commonly used piezoelectric ceramics (PZT). The detail of fabricating the transducer is provided, which includes an examination of the critical properties of the material, construction of the transducer and harmonic analysis of the plate-ice layered model. Test results showed that the lithium niobate transducer can remove effectively the ice layer created in a freezer at −15 °C on the outer surface of wind turbine blade sample. In addition, the optimal frequency of ultrasonic de-icing for wind turbine blade is found to be at 442 kHz driven under 50 V, which is agreeable with theoretical analysis.

Suggested Citation

  • Wang, Zhenjun & Xu, Yuanming & Su, Fei & Wang, Yibing, 2016. "A light lithium niobate transducer for the ultrasonic de-icing of wind turbine blades," Renewable Energy, Elsevier, vol. 99(C), pages 1299-1305.
  • Handle: RePEc:eee:renene:v:99:y:2016:i:c:p:1299-1305
    DOI: 10.1016/j.renene.2016.05.020
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0960148116304311
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.renene.2016.05.020?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Jiménez, Alfredo Arcos & García Márquez, Fausto Pedro & Moraleda, Victoria Borja & Gómez Muñoz, Carlos Quiterio, 2019. "Linear and nonlinear features and machine learning for wind turbine blade ice detection and diagnosis," Renewable Energy, Elsevier, vol. 132(C), pages 1034-1048.
    2. Zeng, Jing & Song, Bingliang, 2017. "Research on experiment and numerical simulation of ultrasonic de-icing for wind turbine blades," Renewable Energy, Elsevier, vol. 113(C), pages 706-712.
    3. Wang, Yibing & Xu, Yuanming & Su, Fei, 2020. "Damage accumulation model of ice detach behavior in ultrasonic de-icing technology," Renewable Energy, Elsevier, vol. 153(C), pages 1396-1405.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:renene:v:99:y:2016:i:c:p:1299-1305. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/renewable-energy .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.