Autonomous Wind-turbine Infrastructure Inspection

Lead Participant: Perceptual Robotics Limited

Abstract

Perceptual Robotics is working with the University of Bristol and industry partners to provide fully automated visual inspection of wind turbines using smart autonomous drone technology. One of the major concerns in investing in wind farm projects relates to maintaining turbine availability, which represents the risk of lower energy yields and lost production due to periods of turbine standstill and repair. Maintaining wind turbine reliability is essential for a wind farm to perform effectively and profitably. As a consequence with huge numbers of wind turbines worldwide (315,000+), frequent visual inspection is becoming ever more important. Current techniques using industrial rope access or piloted drones are costly, time-consuming and unable to deliver repeatable and consistent inspection. The aim of this project is to address these weaknesses by developing drone technology which is able to autonomously fulfil the entire inspection to reporting requirement, providing safe, robust, repeatable inspection, reducing costs and increasing trust and quality. Such an approach to inspections will contribute to reducing wind turbine down-time, deliver more affordable operational costs and improve the return on wind farm investment. The technology will include innovative algorithms in flight control and vision based defect detection, and will be developed within a platform independent architecture. It will yield a unique product with significant technology advantage over competitor systems and open up markets in the UK and overseas, further increasing UK expertise in renewable technology.

Lead Participant

Project Cost

Grant Offer

 

Participant

Perceptual Robotics Limited
University of Bristol, United Kingdom £91,894 £ 91,894

People

ORCID iD

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