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Structural Health Monitoring of Wind Turbines Using a Digital Image Correlation System on a UAV

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Rotating Machinery, Optical Methods & Scanning LDV Methods, Volume 6

Abstract

Unmanned aerial vehicles (UAVs) have recently emerged as a robust tool for remote inspection and data acquisition at places that are either inaccessible or riskier to perform measurements. To quantify the level of strain/stress and loading conditions that the rotating structures such as wind turbine experience during operation, an approach is proposed that can perform a nondestructive evaluation of these rotating structures using non-contact, three-dimensional (3D) digital image correlation (DIC). This technique addresses the benefit of non-interference with structure functionality and can be used for rotating or non-rotating structures. In this project, a synchronized set of a stereo camera system is used to acquire the images of a rotating turbine. These images are processed to obtain displacement, geometry, and strain over the wind turbine blades during deformation.

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Authors and Affiliations

  1. NVH & Experimental Mechanics Laboratory (NVHEM Lab), Kettering University, Flint, MI, USA

    Ashim Khadka, Yaomin Dong & Javad Baqersad

Authors
  1. Ashim Khadka
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  2. Yaomin Dong
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  3. Javad Baqersad
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Corresponding author

Correspondence to Javad Baqersad .

Editor information

Editors and Affiliations

  1. Department Mechanical Engineering, University of Massachusetts Lowell, Lowell, MA, USA

    Christopher Niezrecki

  2. Kettering University, Flint, MI, USA

    Javad Baqersad

  3. Department of Mechanical Engineering, University of Bristol, Bristol, UK

    Dario Di Maio

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© 2019 Society for Experimental Mechanics, Inc.

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Khadka, A., Dong, Y., Baqersad, J. (2019). Structural Health Monitoring of Wind Turbines Using a Digital Image Correlation System on a UAV. In: Niezrecki, C., Baqersad, J., Di Maio, D. (eds) Rotating Machinery, Optical Methods & Scanning LDV Methods, Volume 6. Conference Proceedings of the Society for Experimental Mechanics Series. Springer, Cham. https://doi.org/10.1007/978-3-030-12935-4_9

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  • DOI: https://doi.org/10.1007/978-3-030-12935-4_9

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-12934-7

  • Online ISBN: 978-3-030-12935-4

  • eBook Packages: EngineeringEngineering (R0)

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