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Automated Wind Turbine Blade Damage Identification with Drone

Company Name: SkySpecs
Program Office: Wind
Location: Ann Arbor, Michigan
Award Amount: $254,000
Project Term: 12 months
Project Status: Active
Participating Lab(s): Sandia National Laboratories


SkySpecs develops self-sufficient drones to inspect wind turbine blades. A deployed drone can be faster, less costly, and more accurate than alternative inspection methods, and can provide actionable insights. Throughout the industry there is a widespread need for reducing the number of personnel in the field, reducing risks in conducting inspections, and increasing the frequency of those inspections.  

The greatest barrier may be the lack of public knowledge of drone use. Drone technology is still new, lacking a history validating its use as a primary inspection tool. Lacking technical knowledge, the public is hesitant to replace human inspectors with flying robots, especially in the monitoring of equipment and review of data collected.

The biggest challenge SkySpecs is facing is the adoption and validation of its technology as a primary tool and resource for wind turbine blade inspection. SkySpecs' goal is to demonstrate that autonomous data collection, damage identification, and analytics are benefits of drone use over current manual inspection methods.

Obtaining the DOE Small Business Voucher would help SkySpecs overcome such challenges. As a successful project, the SkySpecs drone will immediately benefit the wind energy mission area and set a precedent for the eventual use of autonomous drones with automatic damage analytics, not only for wind turbines, but also for building and solar energy inspections.


Originally working on research at the University of Michigan, the SkySpecs team has been working in autonomous drone technology for the last 7 years. Launched in 2012, SkySpec has focused on its goal of commercializing this research in wind turbine inspection with significant interest in applying the technology to other infrastructure inspection activities.

SkySpecs differentiates itself with the single button-push, self-ruling operation of inspection drones. Most companies currently operating in the drone space purchase hobby-grade drones and hire pilots to travel to the field and manually fly. SkySpecs develops algorithms to handle the end-to-end inspection process from the flight operations to the data classification and report generation. 


The results of this project will allow SkySpecs to complete the development of the autonomous damage identification and classification engine. A large data set of wind turbine damage and defects are crucial for the system to learn highly categorized algorithms in a shorter amount of time. Sandia National Laboratories experts will validate the accuracy of these results compared to existing inspection methods. This validation would allow SkySpecs to produce a reputable tool for all wind turbine visual inspections, ultimately developing systems that could autonomously identify and navigate unknown buildings with no human input.

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