Damage detection techniques for wind turbine blades: A review

Ying Du, Shengxi Zhou, Xingjian Jing, Yeping Peng, Hongkun Wu, Ngaiming Kwok

Research output: Journal article publicationReview articleAcademic researchpeer-review

41 Citations (Scopus)

Abstract

Blades play a vital role in wind turbine system performances. However, they are susceptible to damage arising from complex and irregular loading or even cause catastrophic collapse, and they are expensive to maintain. Defects or damages on wind turbine blades (WTBs) not only reduce the lifespan and power generation efficiency of the wind turbine, but also increase monitoring errors, safety risks and maintenance costs. Therefore, damage detection for WTBs is of great importance for failure avoidance, maintenance planning, and operation sustainability of wind turbines. This paper provides a comprehensive review of state-of-the-art damage detection techniques for WTBs, including most of those updated methods based on strain measurement, acoustic emission, ultrasound, vibration, thermography and machine vision. Firstly, typical damages of WTBs are comprehensively introduced. Secondly, detection principles, development methods, pros and cons of the aforementioned techniques for blade inspection, and their fault indicators are reviewed. Finally, potential research directions of WTB damage detection techniques are addressed via a comparative analysis, and conclusions are drawn. It is expected that this review will provide guidelines for practical WTB inspections, as well as research prospects for damage detection techniques.

Original languageEnglish
Article number106445
JournalMechanical Systems and Signal Processing
Volume141
Early online date31 Oct 2019
DOIs
Publication statusPublished - Jul 2020

Keywords

  • Damage detection techniques
  • Nonlinearity
  • Structural health monitoring
  • Wind turbine blades

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Signal Processing
  • Civil and Structural Engineering
  • Aerospace Engineering
  • Mechanical Engineering
  • Computer Science Applications

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