Strain Monitoring of Wind Turbines Using a Semi-Autonomous Drone

Javad Baqersad, Ashim Khadka, Arash Afshar, Mehrdad Zadeh

Research output: Contribution to journalArticlepeer-review

Abstract

In this work, an approach is proposed that can perform a nondestructive evaluation of wind turbine structures using a non-contact, three-dimensional full-field optical digital image correlation (DIC) technique. This approach can quantify the level of strain and loading conditions that rotating structures such as wind turbines experience during operation. The optical technique does not interfere with the structural functionality of the wind turbine. Moreover, the use of Unmanned Aerial Vehicles (UAVs) for remote inspection enables robust measurements for periodic inspection. The strain obtained using the proposed approach is validated using strain gauges mounted on the blades. A control algorithm is designed for the UAV to stabilized and obtain the desired field of interest and working distance based on the turbine size. Blending the benefits of the remote accessibility of UAVs and full-field dynamic evaluation of structures using strain data obtained with DIC is a novel method of monitoring wind turbines.

Original languageAmerican English
JournalWind Engineering
DOIs
StatePublished - Jul 2 2021

Keywords

  • Wind Turbine
  • Photogrammetry
  • Vibration
  • Structural Health Monitoring
  • Digital Image Correlation
  • Drone
  • Remote Inspection

Disciplines

  • Energy Systems
  • Mechanical Engineering

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