Skip to main content

Wind turbine blade surface damage detection by sound signal

Buy Article:

$15.00 + tax (Refund Policy)

The purpose of this study is to propose a method to detect the surface damage on wind turbine blades by using the sound signals. The noise of the blades is generated when the wind turbines are operated. In this work the sound signal of a normal wind turbine is measured first and the time-frequency spectrum is obtained by the short-time Fourier transform method. Then apply the time integration to obtain the marginal frequency spectrum and use the curve-fitting to obtain the noise referenced curve of normal condition. The summations of square error of normal and testing wind turbines are calculated and also the index is calculated. A threshold of the index value is determined based upon the comparisons of normal and damaged wind blades operating noise. This threshold is used to judge whether the wind blades are damaged. The results are verified by the photos of the wind turbine obtained during the repaired process.

The requested document is freely available to subscribers. Users without a subscription can purchase this article.

Sign in

Document Type: Research Article

Affiliations: National Taiwan University, Taiwan, Republic of China

Publication date: 07 December 2017

More about this publication?
  • The Noise-Con conference proceedings are sponsored by INCE/USA and the Inter-Noise proceedings by I-INCE. NOVEM (Noise and Vibration Emerging Methods) conference proceedings are included. All NoiseCon Proceedings one year or older are free to download. InterNoise proceedings from outside the USA older than 10 years are free to download. Others are free to INCE/USA members and member societies of I-INCE.

  • Membership Information
  • INCE Subject Classification
  • Ingenta Connect is not responsible for the content or availability of external websites
  • Access Key
  • Free content
  • Partial Free content
  • New content
  • Open access content
  • Partial Open access content
  • Subscribed content
  • Partial Subscribed content
  • Free trial content