Remote inspection of wind turbine blades using UAV with photogrammetry payload

Zhang, D. and Burnham, K. and Mcdonald, L. and Macleod, C. and Dobie, G. and Summan, R. and Pierce, G. (2017) Remote inspection of wind turbine blades using UAV with photogrammetry payload. In: 56th Annual British Conference of Non-Destructive Testing - NDT 2017, 2017-09-04 - 2017-09-07.

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Abstract

Visual Inspection is regularly used as a method of non-destructive testing (NDT) to find defects in large component structures. Wind turbine blades, regularly located in isolated environments, are typically difficult to access. In order to reduce operational and maintenance costs and extend asset lifetime, a project for the remote inspection of blades to accurately assess surface integrity is being undertaken. The remote inspection solution combines an unmanned aerial vehicle (UAV) with a photogrammetry payload to provide visual reconstruction of a blade for a holistic condition overview. Photogrammetric software is used to process the captured images to generate a 3D blade profile. A waypoint guidance algorithm controls the UAV to complete a full blade surface capture at constant distance, minimising motion blur. The results provide an accurate 3D reconstruction of the used blade complete with defects, discontinuities and markings and hence visual inspection using UAV combined with photogrammetry has been successfully implemented.

ORCID iDs

Zhang, D. ORCID: https://orcid.org/0000-0003-4611-4161

Macleod, C. ORCID: https://orcid.org/0000-0003-4364-9769

Dobie, G. ORCID: https://orcid.org/0000-0003-3972-5917

Summan, R. ORCID: https://orcid.org/0000-0002-4090-4528

Pierce, G. ORCID: https://orcid.org/0000-0003-0312-8766

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• Item metadata

  Item type:	Conference or Workshop Item(Paper)
  ID code:	63321
  Dates:	Date Event 4 September 2017 Published 21 April 2017 Accepted
  Subjects:	Technology > Electrical engineering. Electronics Nuclear engineering
  Department:	Faculty of Engineering > Electronic and Electrical Engineering Faculty of Engineering > Design, Manufacture and Engineering Management Technology and Innovation Centre > Sensors and Asset Management
  Depositing user:	Pure Administrator
  Date deposited:	16 Feb 2018 10:05
  Last modified:	11 Nov 2024 16:52
  URI:	https://strathprints.strath.ac.uk/id/eprint/63321