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Using UAV Imagery and Deep Learning for Wind Turbine Inspection

Abby Lehman

When it comes to using a UAV to collect imagery for wind turbine inspections, maneuvering a drone around a huge turbine isn’t the only challenge involved. There’s also the issue of capturing extra positional information so images can be projected onto a plane, which is necessary since the camera is not positioned to look directly down as in most UAV imagery applications. Then there’s ensuring the quality of the capture while in the field to avoid the costs associated with having to re-fly a job. Finally, there is the time and rigor required to analyze all that data to identify and locate damage and other abnormalities on turbine blades.

In this recorded webinar, we discuss: how to account for camera projection when shooting straight ahead rather than straight down; how deep learning technology can be applied to UAV imagery to automatically identify and locate abnormalities on wind turbine blades; and, how cutting-edge software tools can help define and document the right flight procedure to ensure the quality of a capture before leaving a site. This webinar also provides insight and advice about training drone pilots to fly consistent, high-quality captures.

This recorded webinar is great for:

  • Anyone interested in the role of UAVs in utility operations
  • UAV/drone service providers interested in ensuring in the field if the data collected meets required mission criteria
  • Wind farm operators and managers who want to save time and money by performing proactive maintenance using imagery and deep learning

To download the presentation slide deck click here.