* Required fields
Autonomous robotics specialist BeeX, offshore survey and inspection specialist Sulmara, and structural integrity specialists at the University of Strathclyde share a vision to deliver an autonomous low carbon solution for windfarm integrity monitoring. Ultimately the end goal is a Robotics-as-a-Service (RaaS) solution drastically reducing the resources required to conduct essential underwater inspections and asset integrity assessment of offshore wind turbines.
This solution would contribute to meeting Europe’s net-zero commitments by slashing energy requirements and emissions related to inspection activities in the wind sector. Large diesel fuelled and carbon intensive vessels are currently required to inspect energy assets, making the introduction of optimised, automated, lower carbon solutions a crucial part of any net-zero future.
Assisted by the grant funding, BeeX will be delivering their next-generation Hovering Autonomous Underwater Vehicle (HAUV) specifically for Offshore Wind; carrying specific survey & inspection payloads suitable for monopile and jacket inspections, piloted by artificial intelligence to automate inspection tasks & deliver repeatable efficient inspection of windfarm monopiles from seabed to the air water interface.
This HAUV platform will be enhanced with new features including enhanced endurance and improved sensor payload from critical learnings discovered from BeeX experience with their flagship HAUV, A.IKANBILIS on the Nordsee One windfarm, offshore Germany last year.
Sulmara’s scope will define the vertical asset inspection capabilities and sensor payloads needed for this next generation HAUV to meet the demands of the offshore wind sector as well as managing field trials and demonstration of the system alongside BeeX in 2024, with the ultimate aim to integrate the HAUV into a bespoke Unmanned Surface Vessel. The inspection missions will be optimised based on research by the University of Strathclyde, in developing a Structural Integrity framework to generate risk-based, fit-for-purpose, inspection missions that will feed into the HAUV automated mission control software.