Title
Autonomous Offshore Wind Farm Inspection

CoPED ID
d33c1cdb-c937-45dc-a48e-593485cb3d3f

Status
Closed


Value
£1,978,958

Start Date
March 31, 2018

End Date
Sept. 29, 2020

Description

More Like This


"Offshore wind is a key energy source for the UK. It will play an increasingly significant role in future years, as part of an energy mix that is moving towards cleaner and more renewable sources. Offshore Wind Turbines (OWTs) have significant environmental challenges in terms of both the marine environment and the weather. This project, led by Perceptual Robotics and in partnership with ASV, the University of Bristol and VulcanUAV - will be developing and testing key technologies to address the autonomous inspection of offshore turbines.

Building on an existing capability for the inspection of onshore wind turbines, the team will be working on integrating this with an autonomous surface boat provided by ASV, creating a system which will automatically deploy and recover the inspection drone without the need for human interaction. The long term vision of this project is to enable fully autonomous inspection for OWT - working from an autonomous boat whilst being monitored remotely from land. Key challenges associated with this project include mechanical deployment, robust operations, multi vehicle cooperation, communications and the handling and processing of large datasets.

The team consists of specialists in drone design, construction and operation with Perceptual Robotics and VulcanUAV; specialists in autonomous marine vehicles through ASV; experts in computer vision with Bristol University and the ideal facilities in which to develop and test the system at the ORE Catapult facilities. Working together to solve the problems associated with operating an autonomous system in the extreme environment found offshore, the team will need to use modern control theory, sensors, materials, computer technology and AI algorithms to create a platform which can carry out rapid, robust inspections in the marine environment.

A fully autonomous system for offshore turbine inspection will not only significantly reduce the costs associated with ongoing inspection, but will also improve the quality and quantity of the inspection data. Modern sensing, including the vision processing offered by the University of Bristol will allow Perceptual Robotics to fly closer and more accurately with respect to the blades, thereby improving the images and maximising the flight envelope. This in turn will offer the potential for accurate condition monitoring and possible lifetime extensions. The UK is currently a world leader in offshore wind energy and this project will provide a further step change in the efficiency and quality of inspections."

Subjects by relevance
  1. Wind energy
  2. Renewable energy sources
  3. Robots
  4. Robotics
  5. Inspection and revision
  6. Autonomous systems
  7. Automation
  8. Turbines
  9. Autonomous robots
  10. Wind power stations
  11. Energy efficiency

Extracted key phrases
  1. Autonomous Offshore Wind Farm Inspection
  2. Offshore Wind Turbines
  3. Offshore wind energy
  4. Key energy source
  5. Quot;offshore wind
  6. Offshore turbine inspection
  7. Autonomous inspection
  8. Autonomous marine vehicle
  9. Autonomous system
  10. Autonomous surface boat
  11. Key challenge
  12. Significant environmental challenge
  13. Inspection drone
  14. Robust inspection
  15. Renewable source

Related Pages

UKRI project entry

UK Project Locations