<?xml version="1.0" encoding="UTF-8"?><ns2:project xmlns:ns1="http://gtr.rcuk.ac.uk/gtr/api" xmlns:ns2="http://gtr.rcuk.ac.uk/gtr/api/project" xmlns:ns3="http://gtr.rcuk.ac.uk/gtr/api/fund" xmlns:ns4="http://gtr.rcuk.ac.uk/gtr/api/person" xmlns:ns5="http://gtr.rcuk.ac.uk/gtr/api/project/outcome" xmlns:ns6="http://gtr.rcuk.ac.uk/gtr/api/organisation" ns1:created="2026-06-03T15:52:43Z" ns1:href="http://gtr.ukri.org/gtr/api/projects/65D66481-2311-42CC-9E3B-DB90A38DC07B" ns1:id="65D66481-2311-42CC-9E3B-DB90A38DC07B"><ns1:links><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/persons/AC200532-CA1A-4C45-973F-E6E373B4FEDC" ns1:rel="PM_PER"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/99FF2333-555A-4103-9D40-D12F195084FF" ns1:rel="LEAD_ORG"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/99FF2333-555A-4103-9D40-D12F195084FF" ns1:rel="PARTICIPANT_ORG"/><ns1:link ns1:end="2014-02-28T00:00:00Z" ns1:href="http://gtr.ukri.org/gtr/api/funds/4C902A67-433C-4FDA-8F63-61AD8D4BF0E2" ns1:rel="FUND" ns1:start="2013-04-30T23:00:00Z"/></ns1:links><ns2:identifiers><ns2:identifier ns2:type="RCUK">131202</ns2:identifier></ns2:identifiers><ns2:title>Feasibility Assessment of ReliaWind Condition Monitoring Technology for Offshore Wind Turbine Drivetrains</ns2:title><ns2:status>Closed</ns2:status><ns2:grantCategory>Feasibility Studies</ns2:grantCategory><ns2:leadFunder>Innovate UK</ns2:leadFunder><ns2:abstractText>Reliability is vital in the growth of the wind industry, especially offshore, and to realise the UK's targets for 2020. Wind Technologies has developed a novel and patent-pending condition monitoring technology, ReliaWind, with highly enhanced precision and wider range of fault prediction for wind turbine drivetrains, enabling more than 30% reduction in maintenance cost of offshore wind farms.
 The unique feature of ReliaWind is utilising both mechanical and electrical measurements, fed into an advanced self-learning algorithm, which enables accurate prediction of various faults in the gearbox, generator and bearings.
 The project aims to assess the feasibility of ReliaWind technology, proven on a small-scale laboratory test rig, for large offshore wind turbines by assessing its performance in a real 20 kW wind turbine and studying its fault prediction capability for commonly used drivetrain architectures in offshore turbines.</ns2:abstractText></ns2:project>